(PDF) Controlled and automatic human information processing: II. Perceptual learning, automatic attending and a general theory

Psychological

Review

J

Copyright

©

1977

\^J

by the

American

Psychological Association,

Inc.

VOLUME

84

NUMBER

2

MARCH

1977

Controlled

and

Automatic Human Information Processing:

II.

Perceptual Learning, Automatic Attending,

and

a

General Theory

Richard

M.

Shiffrin

Indiana University

Walter

Schneider

University

of

California, Berkeley

The

two-process theory

of

detection, search,

and

attention presented

by

Schneider

and

Shiffrin

is

tested

and

extended

in a

series

of

experiments.

The

studies demonstrate

the

qualitative

difference

between

two

modes

of

informa-

tion

processing:

automatic detection

and

controlled search. They trace

the

course

of the

learning

of

automatic detection,

of

categories,

and of

automatic-

attention responses.

They

show

the

dependence

of

automatic detection

on at-

tending responses

and

demonstrate

how

such responses interrupt controlled

processing

and

interfere with

the

focusing

of

attention.

The

learning

of

cat-

egories

is

shown

to

improve controlled search performance.

A

general frame-

work

for

human information processing

is

proposed;

the

framework

emphasizes

the

roles

of

automatic

and

controlled processing.

The

theory

is

compared

to and

contrasted with extant models

of

search

and

attention.

I.

Introduction

In

Part

I of

this

paper (Schneider

&

Shiffrin,

1977)

we

reported

the

results

of

several

experiments

on

search

and

attention

that

led us to

formulate

a

theory

of

informa-

tion processing based

on two

fundamental

processing modes: controlled

and

automatic.

In the

context

of

search

studies,

these

modes

took

the

form

of

controlled search

and

auto-

matic detection. Controlled search

is

highly

demanding

of

attentional

capacity,

is

usually

The

research

and

theory reported here were

sup-

ported

by PHS

Grant

12717

and a

Guggenheim

Fellowship

to the first

author,

Grant

MH23878

to

the

Rockefeller

University,

and a

Miller Fellowship

at

University

of

California

at

Berkeley

to the

second

author.

This

report represents equal

and

shared

con-

tributions

of

both

authors.

Requests

for

reprints

should

be

sent

to

Richard

M.

Shiffrin,

Department

of

Psychology, Indiana

University,

Bloomington, Indiana 47401.

'

serial

in

nature with

a

limited comparison

rate,

is

easily established, altered,

and

even

reversed

by the

subject,

and is

strongly

de-

pendent

on

load. Automatic detection

is

rela-

tively well learned

in

long-term memory,

is

demanding

of

attention only when

a

target

is

presented,

is

parallel

in

nature,

is

difficult

to

alter,

to

ignore,

or to

suppress

once learned,

and is

virtually

unaffected

by

load.

In the

present article

we

shall

report

several studies

to

elucidate

further

the

proper-

ties

of

automatic

and

controlled processing

and

their interrelations,

to

demonstrate

the

qualitative

difference

between these processing

modes,

to

study

the

development

of

automatic

detection

and the

role

of the

type

and

nature

of

practice

in

such development,

to

study

the

effects

of

categorization,

and to

examine

the

development

of

automatic attending

and

its

effects. After

the

presentation

of the

studies

we

shall present

a

general theory

of

information

processing,

with

emphasis

on the

127

128

RICHARD

M.

SHIFFRIN

AND

WALTER

SCHNEIDER

CM

-

TRIAL

I

TRIAL

2

rs63

TRIAL

3

TRIAL

4

VM

-

TRIAL

I

TRIAL

2

CJK

TRIAL

3

TRIAL

4

Figure

1.

Examples

of

trials

in the

multiple-frame search paradigm

of

Experiment

1,

Part

I. In all

cases, memory-set

size

=

4 and

frame

size

= 2.

Four varied-mapping (VM) trials

and

four

con-

sistent-mapping (CM)

trials

are

depicted.

The

memory

set is

presented

in

advance

of

each trial,

then

the fixation dot

goes

on for

.5

sec

when

the

subject

starts

the

trial,

and

then

20

frames

are

presented

at a fixed

time

per

frame.

Either

0 or 1

member

of

the

memory

set is

presented during

each

trial.

Frame

time,

memory-set

size,

and

frame

size

are

varied

across

conditions.

roles

of

automatic

and

controlled processing.

Our

theory will then

be

compared

and

con-

trasted with extant theories

of

search

and

attention.

A.

Review

of

Paradigms

and

Results

From

Part

I

The

paradigm

for

most

of the

studies

of

Part

I

(and Part

II

also)

is

depicted

in

Figure

1.

Four elements

are

presented simul-

taneously

in a

square;

and

their joint presen-

tation

for a

brief

period

of

time

is

termed

a

frame.

Each trial consists

of the

presentation

of

20

frames

in

immediate succession.

The

elements

presented

are

characters (i.e., digits

or

consonants)

or

random

dot

masks.

In ad-

vance

of

each trial

the

subject

is

presented

with several items,

called

the

memory set,

and

is

then required

to

detect

any

memory-set

items that appear

in the

subsequent

frames.

The

frame

time

is

kept constant across

the

20

frames

of

each trial,

and the

basic depen-

dent

variable

is the

psychometric

function

relating

accuracy

to

frame

time

for

each

condition.

PERCEPTUAL LEARNING

AND

AUTOMATIC ATTENDING

129

Three basic independent variables were

manipulated

in

Part

I/Experiment

1.

The

number

of

characters

in

each

frame

(the

frame

size,

F) was

varied

from

1 to 4

(but

was

constant

for all

frames

of a

given

trial).

The

number

of

characters

presented

in ad-

vance

of a

trial (the memory-set size,

M)

varied

from

1 to 4. The

product

of M and F

is

termed

the

load.

A

memory-set item

that

appears

in a

frame

is

called

a

target;

an

item

in a

frame

that

is not in the

memory

set is

called

a

distractor.

One

half

of the

trials

contained

one

target,

and one

half

contained

no

target. Finally,

and

most important,

the

nature

of the

training procedure across

trials

and the

relation

of the

memory-set items

to

the

distractors were varied.

In the

consistent

mapping

(CM) procedure,

across

all

trials,

memory-set items were never distractors (and

vice

versa).

In

addition, memory-set items

were

from

one

category (e.g., digits)

and

distractors

from

another category (e.g., con-

sonants).

In the

varied

mapping

(VM)

procedure,

memory-set items

and

distractors

were

randomly

intermixed over

trials

and

were

all

from

one

category (e.g.,

consonants).

Figure

1

gives examples

of

trials

in

both

the VM and CM

conditions. Depicted

are

four

consecutive trials

from

a CM

block

and

four

from

a VM

block

in

each

of

which

M

= 4 and F

=

2.

Table

1

gives

the

memory

set,

distractor,

and

target

(if

present)

for

each trial

in

Figure

1.

Note

that

memory-set

items

and

distractors intermix across trials

in

the VM

condition

but do not

intermix over

trials

in the CM

condition.

The

most

important

results

are

shown

in

Figure

2.

These results showed

that

the VM

conditions

were strongly

affected

by

load

and

were

quite

difficult;

the CM

conditions were

virtually

unaffected

by

load

and

were

all

easier than even

the

easiest

VM

condition.

It was

suggested

that

a

controlled, serial

search

was

operating

in the VM

conditions

and

that

a

qualitatively

different

process,

automatic detection,

was

operating

in the

CM

conditions.

The

results

of

Part

I/Experiment

1

were

analyzed

on the

basis

of the

accuracy

of the

detection responses.

Part

I/Experiment

2

utilized comparable conditions

but

presented

Table

1

Examples

of CM and VM

Trials

for

Four

Successive

Trials

Trial

Memory

set

Distractor

set

Target

Consistent

mapping

(CM)

1

2

3

4

1

2

3

4

7481

2583

1739

6S82

Varied

MJDG

CJKH

GMCH

JLKF

KGJCM

CHFLD

KGFDM

CMJKD

mapping

(VM)

CFHKL

LGDFM

DLFKJ

CDGHM

4

none

7

8

D

none

L

only

a

single

frame

on

each

trial;

accuracy

was

high

and the

results

were

analyzed

on

the

basis

of the

reaction time

of the

responses.

The

results

confirmed

those

of

Part

I/Experi-

ment

1, and a

quantitative model

was fit to

the VM

results

of

both experiments.

This

model

assumed

that

controlled

search

was

a

serial,

terminating comparison process

in

which

one first

compared

all

frame

items

against

one

memory-set item

before

switching

to

the

next memory-set

item.

Each compari-

son

and

each switch

was

assumed

to

require

some time

to be

executed.

The

success

of the

model

in fitting the

results

of

both

experi-

ments suggests

that

the

same search mech-

anisms underlie search experiments

that

uti-

lize

both accuracy

and

reaction time mea-

sures,

and

suggests

that

the

same search

mechanisms underlie performance

in

both

divided-attention

and

search paradigms.

The

vast

differences

between

results

of the

CM

and VM

conditions provided

a

basis

for

reorganizing

and

classifying

the

results

of

previous search

and

detection studies.

These

studies

fell

into

a

relatively simple organiza-

tion,

and

many perplexing

and

seemingly

contradictory results became explicable.

Part

I/Experiment

3

utilized

a

multiple-

target, multiple-frame procedure.

The

study

was

similar

to

Part

I/Experiment

1,

but the

subject

was

presented either zero, one,

or two

targets

per

trial

and was

required

to

report

the

number

of

detected

targets.

The

condi-

130

RICHARD

M.

SHIFFRIN

AND

WALTER SCHNEIDER

c/)

H

I

r-

LU

100

80

60

CONSISTENT

MAPPINGS

40

4,2)

.(4,1)

(4,4)

A"

(1,4)

O)

LU

O

LJ

100

80

60

VARIED

MAPPINGS

40 80

120

FRAME

TIME (msec)

120

200

400 600 800

FRAME

TIME (msec)

Figure

2.

Data

from

Experiment

1,

Part

I.

Hits

as a

function

of

frame

time

for

each

of the 12

conditions.

Three

frame

times were

utilized

for

each

condition.

The first

number

in

parentheses

indicates

the

memory-set size

and the

second number

in

parenthesis indicates

the

frame

size.

dons

of

greatest interest were those

in

which

two

targets

per

trial

were presented.

In

these

cases

the

spacing between

the two

targets

varied

from

0 to 4 (0

spacing indicates simul-

taneous

presentation;

spacings

of

1,

2, and 4

indicate

the

number

of

intervening

frame

plus

1).

Target

similarity

also

varied,

the

two

targets

being either physically identical

(II)

or

different

(NI).

The

results

for

Part

I/Experiment

3

showed markedly

different

patterns

for the

VM

and CM

conditions. Consider target

similarity

first. In the VM

conditions

de-

tection

of

identical targets

(II)

was

superior

to

detection

of

different

targets

(NI).

How-

ever,

in the CM

conditions,

the

reverse

was

true:

NI

detection

was

superior

to II

detection. Consider

target

spacing next.

In

the VM

conditions performance

was

lowest

when

the

targets occurred

in

successive

frames

(spacing

1).

However,

in the CM

conditions

performance

was

lowest when

the

targets

were

simultaneous

(spacing

0).

These

results

helped

emphasize

the

qualitative

difference

between

the

automatic detection processing

mode

presumed

to be

utilized

in the CM

conditions,

and the

controlled search mode

presumed

to be

utilized

in the VM

conditions.

In

certain

of the

studies

in

this paper,

we

shall utilize this multiple-target, multiple-

frame

procedure

and

will

infer

the

presence

of

automatic detection

or

controlled search

from

the

nature

of the

spacing

effect

and the

target-similarity

effect.

B.

Rationale

for the

Experiments

We

argued

in

Part

I

that

the

cause

of the

difference

between

the CM and VM

results

was the

consistency

of the

mapping (over

trials)

of the

memory-set items

and

dis-

tractors

to

responses.

We

argued

that

con-

sistent mapping leads

to the

development

of

automatic

detection, which enables auto-

matic-attention responses

to

become attached

to

the

memory-set

items.

The

automatic-at-

tention responses enable

the

serial, controlled

search

to be

bypassed

by a

parallel detection

process

unaffected

by

load. However, these

hypotheses must

be

further

tested

for the

following

reasons.

First,

the

fact

that

mem-

ory-set items were categorically distinct

from

the

distractors

was

confounded

with

the

consistency

of the

mapping. These factors

will

be

separated

in

Part

II/Experiments

1,

2,

and 3.

Second,

the

course

of

development

of

the

hypothesized automatic detection

process

was not

studied

in

Part

I. The

course

of

learning

will

be

traced

in

Part

II/Experi-

ments

1 and 3.

Third, there

was no

demon-

PERCEPTUAL LEARNING

AND

AUTOMATIC ATTENDING

131

stration

in

Part

I

that

an

automatic-atten-

tion response

is

learned

in CM

paradigms.

Such

a

fact will

be

suggested

by

Part

II

/

Experiments

1 to 3 and

demonstrated

in

Part

II/Experiment

4.

Finally, although these

goals provide

an

initial justification

for the

present experiments, these studies

will

serve

an

even more important purpose

in

elu-

cidating

the

characteristics

and

development

of

automatic processing

and in

differentiating

automatic

from

controlled processing.

II. The

Development

of

Automatic Processing:

Perceptual Learning

A.

Perceptual Learning

and

Unlearning

in a

CM

Task

Using

Letters

Only

Experiment

1 of the

present series

is

simple

in

conception. With

the use of the

same basic

multiple-frame

paradigm used

in

Part

I/

Experiment

1

(see

Figure

1),

performance

is

examined

as a

function

of the

amount

of

training

under consistent-mapping conditions.

One

change

is

made, however: Both

the

dis-

tractor

set and the

memory ensemble consist

of

consonants.

This

procedure enables

us to

study

the

acquisition

of

automaticity when

the two

sets

are not

already-learned cate-

gories. Furthermore,

it had

been observed

informally

that

the use of

digits

and

con-

sonants

(in the CM

conditions

of

Part

I/

Experiment

1) led to a

relatively rapid

acquisition

of

automatic detection.

It was

felt

that

the use of

letters only

to

make

up

the two

sets

would slow down acquisition.

Values

of M and F

were chosen

so as to

make controlled processing

difficult

(M = 4,

F—2),

and a

frame

time

(/) of 200

msec

was

chosen

so as to

make performance

low

when

controlled processing

was

being utilized.

(These choices

are

justified

by the

data

in

Figure

2.)

Thus

it was

expected

that

per-

formance

would

be

quite poor

at the

start

of

training, when automatic detection

had not

been

learned

and

controlled search

had to be

used,

but

would improve markedly

as

auto-

matic detection developed.

I.

Method

The CM

presentation procedure

of

Part

I/Experi-

ment

1 was

utilized

(see

Figure

1). The

frame

size

was

always equal

to 2 and the

memory-set size

was

always equal

to 4. Two

disjoint

character

sets

were

used

for the

memory ensemble

and the

distractor

set.

One

consisted

of the

following

nine consonants:

B,

C, D, F, G, H, J, K, and L; the

other

con-

sisted

of the

following

nine consonants:

Q, R, S,

T,

V, W, X, Y, and Z.

There

were

four

new

subjects,

two of

each

sex,

all

naive

to our

tasks.1

Two

subjects

began training

with

the

consonants

from

the

second

half

of the

alphabet

'as

the

memory

ensemble,

and two

subjects

began

with

the

consonants

from

the first

half

of

the

alphabet

as the

memory ensemble. There were

five

blocks

of

trials

per

session, each containing

60

test trials. There were

no

practice

trials. Subjects

were

informed

at the

start

of the

experiment

con-

cerning

the

nature

of the

study

and the

composi-

tion

of the

memory ensemble

and the

distractor

set.

Each

trial

began

with

the

presentation

of a

memory

set (M = 4)

selected randomly

from

the

memory

ensemble.

During

the first

1,500

trials

of the

experiment

for

each

subject,

the

frame

time

was 200

msec;

during

the

following

600

trials,

120

msec.

After

these

2,100

trials

the

memory ensemble

and the

distractor

set

were switched

for

each subject

and

the

frame

time

was set

back

to 200

msec.

This

reversal

'Condition

was

then

run at the

frame

time

of

200

msec

for a

total

of

2,400

additional trials.

The

subjects

were

informed

of the

reversal

at the

time

of

the

switch.

The

subjects responded whenever

a

target

was

detected,

or

gave

a

negative response

at the end of

the

trial.

The

accuracy

of the

response

and the

reaction

time

for

hits were both recorded.

Sub-

jects heard

a

tone

signifying

an

error after

each

incorrect

response.

2.

Results

and

Discussion

The

results

are

presented

in

Figure

3. Re-

sults

for

each block, averaged across

sub-

jects,

are

graphed consecutively.

Thus,

the

graphed points

in

each interval

are

based

on

120

observations.

In the

initial group

of

1,500

trials,

the hit

rate

rose

from

just over

50%

to

about

90%,

while

the

false alarm rate dropped

from

about

12% to

about

3%

(and

the

reaction

1

Since

the

experiments

are not

reported

in

their

chronological

order,

we

list here

the

experiments

in

their

original

order

and

indicate

the

subjects

that

were

used

in

each. Experiment

1 was run

with

new

subjects.

Experiment

4 was run

next)

using

the

subjects

who

took

part

in

Experiment

3 of

Part

I.

Experiment

2 was

then

run on

three

of the

four

subjects

in

Experiment

4.

Experiment

3 was run

last,

on new

subjects.

132

RICHARD

M.

SHIFFRIN

AND

WALTER

SCHNEIDER

100

EC/)

ot

80

0:=

60

HO:

2<

LU-J

40

20

2 o

X

850

o:

£

INITIAL LEARNING

•

REVERSED

LEARNING-

200

MSEC

FRAME

TIME

120

MSEC

FRAME

TIME

_

*tt*^*fi*.

600

1200

1800

2400

I-

2

650

g

550

UJ

CC

600

1200

1800

TRIAL NUMBER

2400

Figure

3.

Data

from

Experiment

1.

Initial

consistent-mapping learning

and

reversed

consistent-

mapping

learning

for

target

and

distractor

sets

taken

from

the first and

second halves

of the

alphabet.

Memory-set

size

=

4J

frame

size

=

2,

frame

times

are

shown. Percentage

of

hits, percentage

of

false

alarms,

and

mean reaction time

for

hits

are

graphed

as a

function

of

trial

number.

After

2,100

trials

the

target

and

distractor

sets

were

switched

with each

other.

time

for

hits

dropped

from

about

770

msec

to

about

670

msec).

It

seems plausible that

the

subjects adopted

a

controlled search strategy

at the

start

of

training. Some support

for

this hypothesis

is

found

in a

comparison

of the

data

from

this

study with

the

data

from

Experiment

3 of

Part

I

(though

different

subjects were

in-

volved

in the two

studies).

The hit and

false

alarm

probabilities

in the first 60

trials

of

the

present study were

.56

and

.13,

respec-

tively.

The

estimated probability

of

detecting

a

single target

and the

observed probability

of

giving

a

false

alarm when

no

target

was

present

were

.60 and

.18, respectively,

in the

VM

condition

of

Experiment

3b of

Part

I in

which

M was

equal

to 4 and F was

equal

to 2

(this condition

and the first 60

trials

of the

PERCEPTUAL LEARNING

AND

AUTOMATIC ATTENDING

133

present

study were both

run at a

frame

time

of

200

msec).

These

two

conditions should

give similar results

if

controlled search

is

being

utilized

in

both studies;

in

fact,

the

probabilities

are

quite similar.

It

should

be

noted

that

the

subjects

all re-

ported extensive, attention-demanding

re-

hearsal

of the

memory

set

during about

the

first

600

trials

of

Experiment

1, but

they

gradually became unaware

of

rehearsal

or

other attention-demanding controlled pro-

cessing

after

this point. Both

the

objective

evidence

and

subjective reports, then, sug-

gest

that

the

subjects used controlled search

at the

start

of

Experiment

1 but

gradually

shifted

to

automatic detection.

The hit

rate

and

false

alarm

rate

after

1,500

trials appeared

to be

changing only

slowly,

but

this could have resulted

from

a

ceiling

effect.

The

frame

time

was

therefore

reduced

to 120

msec

for the

trials.

At

the

conclusion

of

this additional training,

the hit

rate

appears

to

have reached about

82%, while

the

false

alarm

rate

dropped

to

about

5%.

These results

may be

compared

with

the CM

results

from

Experiment

1 of

Part

I

(see Figure

2).

In

that

study, with

/ = 120

msec,

M

- 4, and F = 2, the CM hit

rate

was

about

92% and the

false

alarm rate

(not

shown)

was

about

5%.

Thus,

the

present results indicate

that

subjects

were utilizing

automatic

detection

by the end of the

initial 2,100 trials

of CM

training.

First,

they

performed

at a

level

not

far

from

that

of the

Part

I/Experiment

1

subjects

in the

comparable

CM

condition

with

the

same

frame

time. Furthermore,

the

present study utilized

a

larger memory

en-

semble

and

distractor

set

than

the VM

con-

ditions

of

Part

I/Experiment

1, a

fact

that

could

only have increased

the

task

difficulty.

Second,

from

the

Part

I/Experiment

1 VM

data

we can

estimate

that

a

frame

time

of

600-800

msec would have been required

to

achieve

a

similar level

of

performance

had

controlled search been used.

At

this stage

of the

experiment,

after

2,100

trials

of CM

training,

the

subjects could

be

expected

to

have

developed

a

well-learned

attention response

to the

members

of the

memory

ensemble.

If

such learning

is firmly

planted

in

long-term memory

and if the at-

tention response occurs automatically,

then

it

should prove very

difficult

for the

subject

to

alter

or

unlearn

his

automatic response

in

any

short period

of

time.

To

test

this

hy-

pothesis

we

reversed

the

memory ensemble

and

the

distractor

set for

each subject (and

set the

frame

time back

to 200

msec).

We

hypothesized

that

automatic detection would

prove impossible

and

that

the

subject would

be

forced

to

revert

to

controlled search.

The

results

of the

reversal were quite

dramatic.

The hit

rate just

after

reversal

fell

to a

level well below

that

seen

at the

start

of

training when

the

subjects were com-

pletely unpracticed. Very gradually there-

after

the hit

rate recovered,

so

that

after

2,400

trials

of

reversal training, performance

reached

a

level about equal

to

that

seen

after

1,500

trials

of

original training.

In

summary,

the

original training resulted

in

quite strong

negative

transfer, rather than positive

transfer.

Subject's verbal reports indicated

that

a

shift

back

to

controlled search occurred after

reversal. Initially,

before

reversal,

all

sub-

jects reported rehearsing

the

memory

set

during

each

trial.

After

the 2nd day

(600

trials) subjects reported

that

they were

no

longer

rehearsing

and

only glanced

at the

memory

set. However, subjects reported

that

after

reversal

they

tried

various

methods

to

perform

the

task

and

eventually ended

up

rehearsing

the

memory-set items again, though

this rehearsal also decreased

after

a

week

of

postreversal practice.

This

pattern

of re-

ports could indicate

a

shift

from

controlled

search

to

automatic detection during original

learning,

then

a

shift

after

reversal

to

con-

trolled

search,

and

then

finally a

return

to

automatic detection.

What might

be the

cause

of the

negative

transfer

after

reversal?

If the

reversal caused

subjects

to

revert

to

controlled search, then

it

might have been expected

that

perform-

ance would

fall

to the

level seen

at the

start

of

original learning (when controlled search

was

presumably

utilized).

The

actual results

suggest

that

controlled search

is

hindered

when

the

distractors

are

items

that

subjects

have been previously trained

to

respond

to as

134

RICHARD

M.

SHIFFRIN

AND

WALTER SCHNEIDER

CM

targets

(i.e., items

that,

due to

to

automatic-attention

responses).

This

hypothesis

is

verified

in

Experiment

4, to be

reported

later.2

Beyond

the

poor performance

at the

start

of

reversal learning, negative transfer

is

also

evidenced

by the

extremely large amount

of

training needed

to

overcome

the

effects

of

orig-

inal learning.

After

about

900

trials

of

original

practice

the hit

rate

reached about 90%.

However,

it

took

about

2,100 trials

to

return

to

this performance level

after

reversal.

Ap-

parently

the

necessity

to

unlearn

the at-

tention responses

to the

previous memory-set

items,

or the

necessity

to

overcome some

learned

inhibition

to the

or

both, causes

a

reduction

in the

rate

of

acquisition

of

automatic processing

after

reversal.

It

would

be

interesting

to

know whether

negative

transfer

would obtain

in

several

variations

of our

paradigm.

For

example,

in

the

present study,

the

initial training might

have caused

the

memory

set to

become

a

learned

category,

but

probably

did not

cause

categorization

of the

distractor set.

If the

distractor

set was a

well-known category,

would

reversal

still

cause

a

severe

perform-

ance drop? Furthermore,

it

could

be

argued

that

the

initial training

did not

continue long

enough

for the

negative transfer

to

reach

full

strength.

The

amount

of

negative transfer

might

depend

on the

amount

of

overtraining

during

initial learning. Such

a

view

has

been

put

forth

for

certain verbal

and

animal learn-

ing

situations (see

Handler,

1962, 196S;

Jung, 1965

for two

views

on the

subject).

Thus

it

might

be

asked whether

performance

drops would

be

caused

by

reversal

if the

original

automatic detection responses were

greatly overlearned.

These

two

questions

are

answered

by

Experiment

3.

B. The

Reversal

of

Consonants

and

Digits

for

Well-Practiced

Subjects

Throughout

the

series

of

experiments

in

Part

I, the

memory ensemble

in the CM

condition

was

always

the

same, either digits

or

consonants,

and no

member

of the CM

memory

ensemble

was

ever

a

distractor, even

in

the VM

conditions.

The VM

conditions

always consisted solely

of

items

from

the

distractor

set in the CM

conditions.

Thus

a

subject

at the

conclusion

of the

series

of

Part

I

studies

who had

been searching, say,

for

consonants

in

digit

distractors,

had

never

been given

a

consonant

as a

distractor:

Whenever

a

consonant

had

appeared,

it was

a

target.

These

facts naturally suggested

a

study

in

which

the

roles

of

consonants

and

digits were reversed

for

these subjects.

1.

Method

The

procedure

was

identical

to the

multiple-

frame,

multiple-target paradigm

of

Experiment

3a

of

Part

I

(whose results were described

in the

Introduction)

in

most

respects,

except

that

the

memory

ensemble

and the

distractor

set

were

switched

in

both

the CM and VM

conditions. Thus

in

the CM

condition

the two

subjects

who had

been

searching

for

consonants

in

digit distractors

now

searched

for

digits

in

consonant distractors;

in

the VM

condition these

two

subjects

had

been

searching

for

digits

in

digits

and now

searched

for

consonants

in

consonants.

These

contingencies were

reversed

for the

remaining

two

subjects

who had

previously been searching

for

digits

in

consonant

distractors

in

their

CM

conditions.

The

frame

time

(/) was 60

msec

for the CM

conditions

and 200

msec

for the VM

conditions.

Just

as in

Experiment

3

a of

Part

I, M was

equal

to 2, and F was

equal

to

2;

zero

targets

were pre-

sented

on one

fourth

of the

trials,

one

target

was

presented

on one

fourth

of the

trials

and two

targets were presented

on one

half

of the

trials.

When

two

targets were presented, they were

either

identical (II)

or

nonidentical

(NI),

and the

spac-

ing

between them

was

either

0, 1, 2, or 4.

Each

subject

was

given

12

blocks

of 132

trials

in

each

of

the VM and CM

conditions.

The VM and CM

blocks alternated.

Upon

'Completion

of the

initial

set of 24

blocks,

the

frame

time

was

increased

to 120

msec

and an

additional

18

blocks

of CM

trials were

run

for

each

subject.

2

One

might hypothesize

that

the

basic compari-

son

rate

of

controlled

search

is

altered

and

slowed

after

reversal,

thereby accounting

for the

negative

transfer.

Two

facts argue against this hypothesis.

Experiment

2

shows

that

controlled search proceeds

at an

unchanged

rate

even when

all

items consist

of

targets

from

conditions. Experiment

4

shows

that

even

one CM

target presented

in a

to-be-ignored spatial location greatly reduces detec-

tion

of a

simultaneously presented

target

in a

to-be-

attended location.

This

result suggests that reversal

performance

is

harmed because attention

tends

to

be

drawn

to the

distractors.

PERCEPTUAL

LEARNING

AND

AUTOMATIC

ATTENDING

135

It

should

be

noted

that

the

subjects

for

this

ex-

periment

had had roughly

20,000

trials

of

practice

in

the

various

CM and VM

conditions

in

earlier

studies

(see

Footnote

1).

2.

Results

and

Discussion

The

results

are

depicted

in

Figure

4. A

simple

correction

for

guesses

and

false

alarms

has

been carried

out on the raw

data,

as

described

in

Part

I, but

this

correction

did

not

affect

the

qualitative features

of the re-

sults.

The

circles

in the

left-hand

panel give

the

comparable

VM

prereversal

data

from

Experiment

3a of

Part

I

(/=

200

msec),

while

the

circles

in the

center panel give

the

comparable

CM

prereversal data

from

Ex-

periment

3c of

Part

I (/ = ,60

msec);

the

triangles

in the two

left-most

panels give

the

data

from

the

present experiment (see

Foot-

note

1).

The

most dramatic

findings of

Experiment

2

are

shown

in the

middle panel

of

Figure

4,

which gives

the CM

reversal

results.

It is

evident

that performance drops

off

markedly

after

reversal. Estimated percentage

of

detec-

tion

of two

targets

is

about

80%

prior

to

reversal

and

about

20%

after

reversal. Fur-

thermore,

these data represent

12

blocks

of

training

over which very little,

if

any,

re-

covery

was

taking place.

It is

interesting

to

note

that

all of the

subjects predicted

that

no

change

in

their performance would occur

after

the

consonants

and

digits were reversed,

and the

subjects were

uniformly

startled

and

even dismayed

by the

extreme

difficulty

of

the

reversed

task.

These results resolve

the

confounding

be-

tween

categorization

and the

mapping condi-

tions. Even when there

is a

well-learned

and

well-practiced categorical

difference

between

memory

ensemble

and

distractor set, reversal

in

the CM

paradigm gives rise

to

marked

impairment

of

performance. Thus, categorical

differences

between memory ensemble

and

distractor

set

cannot

be the key

factor under-

lying

the

utilization

of

automatic detection.

Rather

it is the

consistency

of

mapping

that

underlies

the

acquisition

of

automatic detec-

tion.

Consider

data given

in the

REVERSAL CONDITIONS

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Figure

4.

Data

from Experiment

2.

Probabilities

of

correctly

detecting

one

target

when

one was

presented,

or two

targets

when

two

were presented,

as a

function

of

spacing,

for

each

condition.

The

data

shown

have

been

adjusted

to

remove

effects

of

guessing

and

false

alarms.

The

observed

percentage

of

"none"

responses

to

no-target

trials

is

also

shown.

Circles show

the

estimated

percentage

of

detection

prior

to

reversal

(data

from

Experiment

3,

Part

I),

while

triangles

indicate

performance

after

reversal

in

Experiment

2. The

squares

in the

right-hand

panel

show

post-

reversal

detection

from

Experiment

2

after frame

time

was

increased

to 120

msec.

The

open

symbols

and

dashed lines indicate

the II

conditions

(identical

targets);

the

closed

circles

and

solid

lines indicate

the

NI

conditions

(different

targets).

(VM =

varied

mapping;

CM =

consistent

mapping;

f =

frame time,

in

msec.)

136

RICHARD

M.

SHIFFRIN

AND

WALTER SCHNEIDER

left-hand

panel

of

Figure

4. It is

evident

that

the

switch

from

consonants

to

digits

(or

vice versa

for

other subjects)

had

almost

no

effect.

The

levels

of

performance remain

the

same

as in

Experiment

3a of

Part

I, and

the

qualitative pattern

of

results

is

still about

the

same, showing

the

pattern indicative

of

controlled search.

That

is,

worst

perform-

ance occurred

at

spacing

1, and

performance

was

worst when

the

targets were

different

(NI).

These

effects

indicate

the

presence

of

controlled search.

In

summary,

a

change

of

the

character

set

used

in the VM

conditions

had no

appreciable

effect

under

the

present

conditions.

These

results

are

most

interesting,

be-

cause

after

reversal

the

memory ensemble

and the

distractor

set

both consisted

of

items that

had

come

to

elicit automatic-

attention responses

in

previous training.

In

the

reversal conditions

of

Experiment

1 we

saw

that

making

the

distractor

set but not the

memory ensemble consist

of

such

"automatic"

items resulted

in

considerable negative trans-

fer.

In the

present

experiment

it is

evident

that

performance

is not

worse

after

reversal

when

subjects have been trained

to re-

spond

to

both

the

targets

and

distractors

in

previously

CM

training.

These results might

be

expected

on the

basis

of the

following

reasoning.

Just

after

reversal

in

both Experiment

1 and in the CM

conditions

of

Experiment

2 the

subjects were

using

controlled search.

In

Experiment

1,

after

reversal,

the

automatic-attention responses

to the

distractor items tended

to

draw

at-

tention away

from

target items

to

which sub-

jects

had not

previously been trained

to re-

spond

and

hence

to

order

the

controlled search

in

such

a way

that

the

distractor items were

compared earlier

in the

search. Thus per-

formance

was

impaired. (This hypothesis

is

confirmed

in

Experiment

4.)

However,

in the

present experiment, after reversal,

all

items,

distractors

and

targets alike, gave rise

to

attention responses, which could

be

expected

to

cancel each other

out on the

average.

That

is,

there should

be no

selective bias

to

compare

distractors

prior

to

targets since

both

types

of

items give rise

to

equivalent

attention responses.

Thus,

the

controlled

search operates normally, with targets com-

pared

in a

random order

of

search,

and

per-

formance

is

equivalent

to

that

seen prior

to

the

switch

of

character sets.

In

short,

the use in a

search task

of

stimuli

that

elicit automatic-attention responses (de-

veloped through previous

CM

training)

can

(a)

improve performance over

that

seen

in

the

usual

VM

conditions

if

these stimuli

are

memory-set

items

but not

distractors,

in

which

case automatic detection will

be

uti-

lized;

(b)

leave performance unchanged

from

that seen

in the

usual

VM

conditions

if

these stimuli

are

both memory-set items

and

distractor items,

in

which case normal con-

trolled search will

be

utilized;

and (c) im-

pair

performance

from

that

seen

in the

usual

VM

conditions

if

these stimuli

are

distractors

but

not

memory-set items,

in

which case

subjects

will

utilize controlled search

that

will

be

reduced

in

effectiveness

by

automatic

attending

to

distractors.

Let us now

turn

to the

results

of the final

reversed

CM

training blocks.

We

suspected

that

the

subjects

in the

reversed

CM

condi-

tion

(the

middle panel) were reverting back

to the use of

controlled search,

but

perform-

ance levels were

so low

that

it was

difficult

to

interpret

the

pattern

of

results. Thus

frame

time

in the CM

reversal condition

was

increased

to 120

msec,

and 18

blocks

of

addi-

tional

CM

training were run.

The

results

of the

trials with

/ = 120

msec

are

represented

by the

squares

in the

right-

hand panel

of

Figure

4. It

should

be

noted

first

that

the

pattern

of the

results

is in-

dicative

of

controlled search

in

that

the

worst

performance

occurs

at

spacing

1.

However,

the

results

do not

show

the

target-similarity

effect

that

we

have been

led to

expect

(in

Experiment

3 of

Part

I) for

controlled search:

Results

for

conditions using

II

target pairs

are

not

superior

to

those using

NI

target

pairs. Furthermore,

the

overall level

of

per-

formance

is

higher than

one

would expect

for

the VM

conditions.

At a

frame

time

of

120

msec performance

is

higher than

that

seen

for the VM

conditions

at a

frame

time

of

200

msec

(in the

left-hand panel

of

Fig-

ure

4).

The

results

can be

explained simply

and

PERCEPTUAL

LEARNING

AND

AUTOMATIC

ATTENDING

137

elegantly

by the

hypothesis

that

the

sub-

jects were carrying

out a

controlled search

for

the

category

as a

whole.

The

Experi-

ment

2

reversal condition

differed

from

the

Part

I/Experiment

3 VM

conditions

in

that

the

memory-set items

and the

distractor

items

in the

present instance were cate-

gorically

different

(numbers

and

letters).

This

categorical

difference

obviously

did not

allow

the

subjects

to

utilize automatic detec-

tion

after

reversal. However,

the

categorical

difference

could very well have helped

the

subjects

to

adopt

a

more

efficient

controlled

search. Suppose

the

subject ignored

the

specific

members

of the

memory

set and

searched instead

for any

instance

of the

cate-

gory

"numbers"

(or

"letters"

as the

case

may

be).

Then only

one

comparison would

be

needed

for

each display item

in

each

frame,

regardless

of

memory-set

size.

Compared with

the

case when

a

categoriza-

tion

is

unavailable,

a

controlled search

for

the

category

of

each input saves search time

in

two

ways.

First,

there

is no

need

for

mul-

tiple memory-set comparisons

for

each

frame

item. Second, there

is no

need

for

time-

consuming switches between memory-set

items.

Thus

performance improves consider-

ably.

Furthermore,

the

distinction between

identical

and

nonidentical multiple targets

is

no

longer

meaningful—both

targets

are

sim-

ply

category members, regardless

of

their

physical similarity. Thus

no

difference

be-

tween

the II and

NI

conditions would

be

predicted.

The

results

in

Figure

4

support

these contentions.

As

far as we can

tell, through

a

block-by-

block

analysis

of the

reversal results,

the

sub-

jects

did not

begin

to

recover

any

appreciable

degree

of

automatic detection even

after

30

blocks

of CM

reversal training. Undoubtedly,

the

difficulty

in

relearning

(or

unlearning)

is

great

amount

of

overtrain-

ing

with

the

original mapping

of

stimuli

to

responses. Eventually, however, were

the

reversal experiment continued,

we

would

ex-

pect

automatic detection

to

develop once

again.

In

summary, then,

the

results

of

Experi-

ment

2

show

that

a

switch

of

character sets

does

not

affect

VM

performance,

but a

switch

of

memory ensemble

and

distractor

set

causes

a

great decrement

in

performance

in the CM

conditions.

The CM

decrement occurs despite

the

categorical

difference

between

the

mem-

ory-set items

and

distractor items (letters

vs.

numbers).

It is

argued

that

the

subjects,

after

reversal, adopt

a

controlled search

strategy

in

which they search

for the

category

as a

whole

rather than search

for the in-

dividual members

of the

category.

The

results

of

Experiments

1 and 2

could

hardly have provided

a

more dramatic demon-

stration

of the

qualitative

difference

between

automatic detection

and

controlled search,

and of the

dependence

of the

search mecha-

nism

on the

nature

of the

training procedures

(i.e.,

the

consistency

of the

stimulus-response

mapping).

The

results

of

Experiments

1 and 2

also

demonstrate

the

long-term nature

of the

learning underlying

the

automatic process.

Experiment

1

showed

that

even original

learning

of an

automatic response could

take

thousands

of

trials

of

practice

to

develop

if

a

previously known categorization

did not

distinguish

the

memory ensemble

and the

dis-

tractor set. Relearning

after

reversal

was

even

slower

to

develop. Experiment

2

showed

that

relearning

after

reversal could

be

very

retarded even when

the

sets were categorized,

as

long

as the

original automatic detection

process

was

well overlearned.

C. The

Role

of

Categorization

in

Controlled

Search

and in the

Development

oj

Automaticity

The

role played

by

categorization

in

con-

trolled search

and in the

development

of

automatic detection

is

suggested

by

results

of

the

preceding experiments,

but it is an

important

enough

concept

to be

examined

in

a

separate experiment. Furthermore,

the

nature

of the

process

by

which categories

are

learned

is

also worth studying.

These

considerations underlay

the

design

of

Experi-

ment

3. We

decided

to use new

subjects

and

to

train them

in two

conditions,

in

neither

of

which were

the

memory

and

distractor

sets preexperimentally categorized.

The first

condition

was

designed

to

induce controlled

138

RICHARD

M.

SHIFFRIN

AND

WALTER

SCHNEIDER

100

S

80

60

40

20

M=2

M=4

o

•

Categorical

a

•

Mixed

f =

350

0-4

5-9

10-14

15-19

20-24

^25

28

30-32

33-35

f

VM

Training

CM

Training

SESSIONS

Figure

S.

Data

from

Experiment

3.

Estimated percentage

of

detection

of

both targets,

as a

func-

tion

of

session number, averaged over spacing

and

target-similarity conditions,

for

each

of the

four

main conditions.

At

Session

25

training

was

switched

to a CM

procedure.

At

Session

30, the

frame

time

was

reduced

to 160

msec.

(VM =

varied

mapping;

CM =

consistent

mapping;

M =

memory-set

size;

f =

frame

time,

in

msec).

search

in

circumstances

such

that

a

cate-

gorization

could

not

develop.

The

second

con-

dition

was

also

designed

to

induce

controlled

search,

but in

circumstances

such

that

a

categorization

of the

memory

sets

could

be

learned.

Both

of

these

conditions

utilized

a

varied-mapping

procedure

to

prevent

auto-

matic

detection,

and

both

were

followed

by

a

series

of CM

trials,

during

which

trials

automatic

detection

developed.

Thus,

the

CM

trials

traced

the

course

of

development

of

automatic

detection

when

a

categoriza-

tion

was,

or was

not,

present

at the

start

of

CM

training.

1.

Method

The

subjects each took

part

in two

conditions

called

mixed

and

categorical,

run in

different

blocks.

In

each condition

the

memory

ensemble

and

dis-

tractor

set

were

drawn

from

a

total

of

eight con-

sonants.

The two

eight-consonant

sets

did not

over-

lap.

The

sets were

{GMFP,

CNHD}

and

{RVJZ,

BWTX}.

The

assignment

of

these

two

sets

to the

two

conditions

was

permuted across subjects.

Both conditions used

a VM

procedure

similar

in

certain respects

to

that

of

Experiment

2 of

this

report

and

Experiment

3 of

Part

I. The

multiple-

target, multiple-frame paradigm

was

used with

/ — 250

msec

per

frame.

Only

12

frames were used

on

each

trial,

with

all

targets

appearing

on

frames

3

through

10.

Frame

size

was

equal

to 2 in all

con-

ditions,

and two

memory-set sizes

were

used

in

different

blocks:

M = 2 and

Af

=

4.

In the

mixed condition,

the

members

of the

memory

set

were chosen randomly

on

each trial

from

the

ensemble

of

eight consonants;

the

distractor

set

consisted

of

four

items

randomly

chosen

from

those consonants

not

used

in the

memory set.

These

four

.distractors

were chosen randomly

to fill the

nontarget, nonmask, positions

in the

various frames

of

the

trial.

The key

feature

of the

mixed

condition

was

the

fact

that

memory-set items

and

distractors

were

randomly intermixed

from

trial

to

trial.

In the

categorical

.condition,

the

eight ensemble

items were divided

into

two

sets

of

four

that

re-

mained disjoint throughout

the

experiment

for

each

subject.

The

sets

of

four

are

indicated

by the

posi-

tion

of the

comma

in the

above

listing

of the

con-

sonants making

up

each set. Note

that

the two

sets

of

four

were chosen

to be

highly confusable

with

each other

in the

sense

that

pairs

of

visually con-

fusable

letters were

separated

into

the two

sets.

On

a

given

trial

one of

these sets

of

four

was

chosen

randomly

to be the

distractor set,

and the

memory-

set

items were then chosen randomly

from

the

remaining set. Thus,

in the

categorical condition

there

were just

two

disjoint categories

of

items,

one

from

which

the

memory

set was

drawn,

and

one

that

served

as the

distractor

set. However,

the

category

that

served

as the

distractor

set

varied

randomly

from

trial

to

trial.

Thus,

'the

procedure

still

involved

a

varied mapping,

but the

categories

were never intermixed

and

could eventually become

well learned.

To

make

it

easier

for the

subjects

to

learn

the

categories,

the

members

of the

memory

set

pre-

PERCEPTUAL LEARNING

AND

AUTOMATIC ATTENDING

139

sented

at the

start

of

each

trial

were always pre-

sented

in

alphabetical order (this

was

also done

in

the

mixed

'condition).

In

each session there were

four

blocks, always

run in the

following

order:

(a)

categorical

condition,

M

=

2;

(b)

categorical

condition,

M =

4;

(c)

mixed condition,

M =

2;

(d)

mixed

condition,

M = 4.

There were

96

trials

in

each

block,

24

with

no

target,

24

with

one

target,

and 6 for

each

of the

eight combinations

of

spacing

and

target

similarity

when

two

targets were

presented.

Four

new

subjects,

one

male

and

three

females,

took

part.

Each

ran in 24

sessions

of

about

1

hour

each.

This

finished

the first,

varied mapping, phase

of

the

study.

After

these

24

sessions

the

subjects

should have been using controlled search

in

both

conditions,

but

should have learned

the

categories

in

the

categorical condition.

Before

turning

to the

CM

procedure used

in

subsequent sessions,

we

shall

discuss

the VM

results.

2.

Results

and

Discussion

of

the

VM

Conditions

The

results

are

summarized

in

Figures

5

and 6.

Figure

5

gives

the

estimated prob-

ability

of

detecting both targets

when

two

are

present, averaged across target similarity,

spacing,

subjects

and

certain combinations

of

sessions.

Performance

in all

four

main con-

ditions tended

to

improve during

VM

train-

ing,

but is

clearly stable over

the

last

10

sessions (15-24). Initially

the M = 2

con-

dition

is

superior

to the M — 4

condition

in

both

the

categorical

and

mixed

cases.

After

training, however,

the

pattern

changes

considerably.

In the

categorical conditions

100

80

o>

2 60

c

o

*-

u

0>

lu

•a

c

<u

o

w

a>

a.

73

a>

o

E

II NI

o

—

&

M

= 2

Categorical,

VM

i

100

oo

O

a>

O

-t>

O

ro

O

Mixed,

VM

01012

4

i

Spacing

of two

targets

|

Number

of

targets

Figure

6.

Data

from

Experiment

3.

Estimated percentage

of

detection

as a

function

of

number,

spacing,

and

similarity

of

targets

for VM

Sessions 19-23

for

all

conditions.

(VM =

varied

mapping;

M

=

memory-set

size;

II

=

identical

targets;

NI =

nonidentical targets.)

140

RICHARD

M.

SHIFFRIN

AND

WALTER

SCHNEIDER

the

results

of the M — 2 and M

=

4

condi-

tions

converge (indicating category learning

and

the use of a

categorical search

strategy).

In the

mixed condition performance

in the

M

= 4

condition remains much lower than

in

the M = 2

condition,

but

performance

in

both

of

these

is

worse than

in

either

cate-

gorical condition (suggesting

that

the

pres-

ence

of

well-known

categories

reduces

the

effective

memory-set size

to 1).

To

ascertain whether controlled search

was

being

utilized

in

these various

VM

conditions

and to

determine

the

nature

of

that

search,

it

is

necessary

to

consider

the

spacing functions

shown

in

Figure

6.

This

figure

gives

the

spacing

functions

for

Sessions

19-23,

when

performance

had

stabilized, averaged across

subjects.

For

both

M = 2 and M

=

4

con-

ditions,

the

mixed condition shows

the

pat-

tern

we

have come

to

expect

for

controlled

search, with performance worse

at

spacing

1

and

worse

for

different

targets

(NI).

Performance

in the

categorical condition

was

equivalent when

M = 2 and M — 4.

The

usual performance impairment

at

spacing

1

occurs

for

identical targets (II),

but

when

the two

targets

differ

(NI),

performance

in

the

spacing

0

condition

is

greatly impaired,

a

result

not

seen

in

conditions.

Furthermore,

the II and NI

conditions show

only

a

small

difference

except

at

spacing

0.

The

results

from

the

mixed condition con-

form

to the

pattern expected

for

controlled

search

in

three respects; When

M

=

4

per-

formance

is

worse than when

M —

2;

there

is

a

performance

reduction

at

spacing

1;

and

performance

is

worse

for NI

than

II

con-

ditions.

The

results

from

the

categorical condition

were

unexpected

in

some respects

but are

explicable

in

terms

of an

hypothesis that

categories were learned

and

utilized

in

con-

trolled

search.

Let us

assume that

the

pres-

ence

of a

known category allows

one to

com-

pare

the

category

of the

memory

set to the

category

of any

given

display

item

in a

single

operation. Then

the M = 2

conditions should

not

differ

from

the M — 4

conditions,

and in

fact

both conditions should show performance

levels equivalent

to

those expected

for a

memory-set

size

of 1 in a

normal mixed con-

dition.

This

reasoning explains

why the

cate-

gorical conditions

are

both superior

to the

best mixed condition, which uses

a

memory-

set

size

of

2.

The

category hypothesis, however, sug-

gests

that

target similarity should

not

matter,

so

that

the II and NI

functions should

be

identical.

To

explain

the

spacing

0

results

without abandoning

the

category

model,

we

suggest

the

following

hypothesis. Suppose

that when

a

subject locates

a

target category,

he

or she

briefly

switches

to an

item mode,

perhaps

to

check

that

the

input

is

truly

a

category

member.

If the

second item

in the

frame

is

identical, then

it

will

be

found

in an

item-comparison

mode,

but if

nonidentical,

it

will

be

located only

if the

subject reverts

quickly

enough

to a

categorical-comparison

mode.

By the

the

reversion

to a

categorical mode

is

complete,

so the

various

functions

tend

to

converge.

Why

would sub-

jects tend

to

switch

to an

item mode?

The

categories

were constructed

so as to be ex-

tremely

confusable with each other. Perhaps

category

encoding

is

learned

under

these

cir-

cumstances

but

remains somewhat error

prone. Then

it

would

be

logical

to

check

any

target category

by

using

an

item mode.

Whatever

the

explanation

for the

details

of

the

spacing

function,

the

data

as a

whole

make

a

strong case

that

categories have been

learned

in the

categorical condition during

VM

training,

and

that

the

presence

of

cate-

gories

in a VM

situation allows

the

subject

to

adopt

a

simpler

and

more

efficient

form

of

controlled search.

The

argument

that

controlled search

is

operating

in

these conditions would

be

sub-

stantiated

if it

could

be

demonstrated

that

performance

improves when

the

subjects

switched

to CM

training.

We

turn next

to

the CM

procedure.

3.

Method

Following

the

24th session

of VM

training,

a CM

procedure

was

initiated.

In the

categorical condi-

tion,

one of the

categories

was fixed

thenceforth

as the

memory ensemble,

and the

other category

was fixed

thereafter

as the

distractor set.

In the

mixed

condition,

a set of 4 was

chosen

and was

fixed

thereafter

as the

memory

ensemble—the

re-

maining

4

items

were

fixed

thereafter

as the

dis-

PERCEPTUAL

LEARNING

AND

AUTOMATIC

ATTENDING

141

tractor set.

The two

sets

of 4

used

in the

mixed

condition

were

those indicated

by the

position

of

the

comma

in the

listing

of the two

sets

of

eight

consonants:

{GMFP,

CNHD}

and

(RVJZ,

BWTX}.

In

other

words,

these were

the

same

sets that

had

been

used

as

categories

in the

categorical

conditions

for

other

subjects. This

CM

training

procedure

was

identical

for

both

conditions

and

followed

in

other

respects

the

procedures

used

in the

preceding

VM

conditions.

Each

subject

was

given

at

least

10

sessions

of VM

training.

The

frame

time

after

CM

Session

4

(Session

24

overall)

was

reduced

to 160

msec

and

after

CM

Session

11

(Session

35

overall)

was

.reduced

again

to 120

msec

(at the

time

of

this

writing

this study

had not

been

completed).

4.

Results

and

Discussion

of

the CM

Conditions

The

changes over sessions following

the

switch

to CM

training

are

depicted

in

Figure

5.

Consider

first the

results

of

Sessions

25

through

28,

which immediately

followed

the

switch

to CM

training. Quite clearly,

a

very

rapid

and

dramatic rise

in

performance took

place,

and

furthermore,

the

results

of the

mixed

and

categorical

conditions tend

to

converge.

By

Session

28 the

performance

level

in the

mixed condition

had

risen

to

over

90%

and in the

categorical condition

had

risen

to

over 95%. Since

the

subjects were

clearly

approaching

ceiling,

the

frame time

was

then reduced

to 160

msec

and CM

train-

ing

continued

for six

additional

sessions.

Note

that

performance

was

still improving

and

that

the

mixed

and

categorical,

and M

= 2 and M

=

4,

conditions

effectively

con-

verged.

It is

interesting

to

note

that

during

VM

training,

20-25

sessions were necessary

before

the M = 2 and M = 4

performance levels

be-

came

equal

in the

categorical condition. Thus

one

might tentatively conclude

that

category

encoding

in the

present experimental context

required

20-25 sessions

to

develop.

Thus

category

encoding would

be

unlikely

to de-

velop

for the

mixed

condition

in

just

four

CM

sessions.

Yet

after

only

four

sessions

of

CM

training,

the

performance level

in the

mixed

condition rose dramatically

and ap-

proached

that

of the

categorical

condition.

This

result suggests that automatic detection

de-

veloped

in the

mixed condition

in the

absence

of

a

well-learned category

(at

least

during

the first

four

sessions

of CM

training).

In

other

words,

the

learning

of a

category

is

apparently

not a

necessary

prerequisite

for

the

development

of

automatic detection.

Figure

7

shows

the

spacing

functions

for

the six

sessions

(30-35)

of CM

training

run

at a

160-msec

frame

time.

The

results

are

averaged over subjects

and

sessions.

In ad-

dition

the M — 2 and M

=

4

conditions

are

lumped together

since

they

did not

differ.

Somewhat

to our

surprise

the

pattern

is al-

most identical

to

that

seen

for the

categorical

condition

during

the

latter

stages

of VM

training,

except

that

the

performance level

is

much higher.

The

comparable

pattern

from

the CM

conditions

of

Part

I/Experiment

3

was

quite

different:

Detection

was

about

equal

in all

conditions except

for a

depressed

detection

rate

when spacing

was 0 and

when

the

targets were identical.

At

spacing

0 the

present data clearly show performance

to be

higher when

the

targets

were

identical.

Disregarding

the

shape

of the

spacing

functions,

the

large improvement

in

perform-

ance when

CM

training commenced does sug-

gest

that

the

subjects were learning auto-

matic detection.

An

hypothesis

that

reconciles

these facts suggests

that

the

subjects were

using

automatic

detection

to

locate

the first

target,

and

were then reverting

to

controlled

search

to

check

the

accuracy

of the

target

detection.

Some time

may be

lost

before

the

subjects

revert

to

automatic detection.

Thus

the

advantage

of II at

spacing

0

would

be

due

to the

temporary

use of a

controlled

search.

This

hypothesis

is

similar

to

that

used

to

explain

the

categorical results

in the

VM

conditions (Figure

6). In

both

cases,

a

tendency

to

recheck

the first

detected item

may

have

led to an

alteration

in

search

strategy.

The

reason

may be the

same

in

both

cases: Rechecking

of

located targets

may

have been induced

by the

stimulus

sets,

which

were chosen

so

that

the

memory

set

and

distractor

set

were maximally visually

confusable.

Thus,

both

automatic

detection

and

category encoding

may

have been some-

what

error

prone,

thereby

requiring

recheck-

ing

in an

item mode.

We are

currently

ex-

ploring this hypothesis.

In

summary,

a

number

of

conclusions

can

142

RICHARD

M.

SHIFFRIN

AND

WALTER

SCHNEIDER

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Spacing

of two

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t

N

umber

of

targets

Figure

7.

Data

from

Experiment

3.

Estimated

percentage

of

detection

as a

function

of

number,

spacing,

and

similarity

of

targets

for CM

Sessions

30-35,

averaged over

memory-set

size

(which

had

no

effect)

for

all

conditions.

(CM —

consistent

mapping;

f =

frame

time;

II =

identical

targets;

NI

=

nonidentical

targets.)

be

drawn

from

the

results

of

Experiment

3.

First,

arbitrary collections

of

characters

can

be

learned

as

categories.

For

this learning

to

occur,

it is

necessary

that

the

categories

re-

main consistently

denned

across trials,

but

not

necessary

that

the

same category

re-

main

the

target

set

across trials. Second,

the

learning

of a

category

in a VM

search para-

digm

enables

the

subject

to

adopt

a

more

efficient

controlled search,

one in

which

the

category

of the

memory

set may be

com-

pared

in a

single

operation

to the

category

of

a

display item, thus eliminating

the

effects

of

variations

in

memory-set size. Third,

a

switch

to a CM

training procedure results

in

fairly rapid acquisition

of

automatic

de-

tection, with

a

concomitant improvement

in

performance

for

both

the

categorical

and

non-

categorical stimuli. These conclusions sup-

port

those

suggested

by the

results

of Ex-

periment

2 in all

important respects.

D.

What

is a

Category?

A

Discussion

and

Selective

Review

1.

Some Hypotheses Concerning Categories

Experiments

2 and 3

showed

how

search

benefits

from

the

learning

of a

categorical

distinction

between memory ensemble

and

distractor set.

But

what

is a

category? Most

generally,

we may

define

any

object

in

mem-

ory

that

refers

to

(stands for, consists

of)

any two or

more objects

in

memory

as a

category. Verbal labels

are one

common

class

of

categories,

but

other types

of

categories

might

also exist.

For

example,

a

visual symbol

might represent several objects.

Of

course,

a

category

in

general need

not

exist

in a

form

similar

to any of the

sensory modalities.

A

completely abstract node could represent

two

or

more objects

in

memory.

With

respect

to

search tasks,

the

import-

ance

of

categories

is

clear. When

all of the

members

of a

memory

set are

members

of

the

same

category

and no

distractors

are in

that

category, then

a

controlled search

can

bypass

the

individual memory-set items

and

utilize

comparisons

that

involve matching

the

single category against

the

category

of

each

display item.

For

category search

to be

uti-

lized

effectively,

however,

the

category must

be

learned well enough

that

each displayed

element will

be

encoded

automatically

and

consistently according

to its

category.

Of

course

other features, such

as the

element's

name

and

shape, will also

be

encoded,

but

only

the

category

feature

is

necessary

for a

category search.

We

suggest

that

the

category

coding

must

be

automatic, because

if it

were

not,

a

search

of

long-term memory would

have

to be

carried

out to

identify

the

cate-

gory;

the

time taken

for

such

a

long-term

search would almost certainly wipe

out any

gains

that

are due to the

reduction

in

num-

ber of

comparisons allowed

by the

category

search

(at

least

for

small memory-set

sizes).

PERCEPTUAL LEARNING

AND

AUTOMATIC ATTENDING

143

Note

that

automatic category encoding

is

not

the

same

as

automatic detection. Auto-

matic

detection

refers

to the

case

when

a

stimulus

gives rise

to an

automatic-attention

response that bypasses

the

need

for a

serial

search through either memory

or the

display.

Automatic

category encoding

refers

to the

case when

the

stimulus gives rise auto-

matically

to a

node representing

the

category

of

the

stimulus. However, without

an at-

tention

response attached

to the

stimulus

node

or the

category node,

the

presence

of

the

category would have

to be

deduced

through

a

serial search

of the

displayed

elements.

Our

studies have shown

that

an

automatic

category

encoding

of

arbitrary

collections

of

characters (consonants,

in the

case

of

Experi-

ment

3)

can

develop.

The

cause

of the

learn-

ing

is not yet

clear. Some subjects

in

early

versions

of

Experiment

3

never showed

any

evidence

of

categorical

search

(usually

sub-

jects with

low

levels

of

performance).

It may

be

that

these subjects

did not

notice

the

categorical nature

of the

memory ensemble

and

hence could

not

develop

a

well-learned

category node

in

memory. Alternatively,

these subjects could have developed

an ap-

propriate

category node

but

have failed

to

use

this node

to

facilitate their search.

There

are

several lines

of

evidence

sug-

gesting

that

automatic detection

may

develop

faster

if a

categorization

is

available

at the

start

of

consistent training.

For

example,

it

is

easy

to

learn

to

search

for a set of

stimuli

defined

by a

simple

physical

feature (see

Neisser,

1963, 1967,

and

studies

in the

The CM

results

in

Figure

5

show

that

the

categorical condition retains some superi-

ority over

the

mixed condition

for

about eight

sessions

(25-32)

but the

magnitude

of the

difference

is

surprisingly

small.

It is

possible

that

the

high confusability between

the two

categories

of

Experiment

3

makes

the

cate-

gories

and the

automatic response

difficult

to

learn.

If so,

more training prior

to the CM

phase could possibly have

led to a

larger dif-

ference

in the

rate

of

development

for the

two

groups. Alternatively

(or

additionally)

the

small size

of

these

categories

may

have

allowed

automatic responses

to the

individual

members

to

develop

so

quickly

that

advan-

tages

due to a

category response were mini-

mized.

It is

conceptually important

to

keep

in

mind

the

possibility

that

automatic responses

might

be

attached

to

different

stages

of en-

coding

of a

single stimulus.

In

particular,

when

an

automatic-attention response

de-

velops

for a

category, other attention

re-

sponses

may

develop

at a

different

rate

for

the

stimuli making

up

that

category.

Thus,

if

a

categorization

is

available

at the

start

of

CM

training,

the

attention responses

to the

category might develop sooner than

atten-

tion responses

to

some

or all of the

individual

stimuli

in the

category.

This

effect

would

be

expected since

any one

stimulus would

appear

only

occasionally

as a

target, whereas every

target

would

be an

instance

of the

category.

On

the

other hand,

in the

cases

in

which

the

memory

ensemble does

not

form

a

category

at the

start

of CM

training,

there

might

be

at

least some individual stimuli

that

come

to

elicit automatic-attention responses while

the

category

is

still being learned.

Once

an

automatic-attention

or

encoding

response

develops,

we

assume

that

it is no

longer

under control

of the

subject

and

will

occur whenever

its

corresponding stimulus

is

presented.

This assumption will

be

supported

by

Experiment

4.

However, when

a

cate-

gorial

encoding (but

not an

attention

re-

sponse)

is

learned,

it

will

not

necessarily

be

utilized

by the

subject during

a

controlled

search.

We

suppose

a

category response

will

facilitate controlled

search

only

if the

subject

both notices

the

category

and

also decides

to

alter

his

search

to

compare

the

category

rather than

the

individual stimuli. These

considerations

would

no

longer apply

if an

automatic-attention

response were learned

in

response

to the

category;

in

such

a

case sub-

ject

strategy

would

not

matter

since

attention

would

be

directed

to the

category

in any

event.

2.

Search Studies

Using

category

of

the

displayed

item

was

reached.

When

the

search

of

this category

was

completed,

a

response

was

initiated.

Homa

(1973) pre-

sented

a

his

results

sug-

gested

that

a

serial, exhaustive search

of

categories

was

followed

by a

serial, exhaustive

search within

the

category

of the

displayed

item. Williams

(1971),

who

presented

an-

other

also

argued

that

a

serial, exhaustive search

of

categories

was

followed

by a

serial search within

the

cate-

gory.

Okada

and

Burrows (1973) used mul-

tiple categories

in the

memory

set and

some-

times cued

the

subject

as to the

category

of

the

displayed item

in

advance

of the

trial.

Their

results showed

that

the

search could

be

restricted

to the

cued

category.

Clifton

and

Gutschera

(1971)

used memory

sets

con-

sisting

of

two-digit numbers

and

showed

that

on

some

trials

the

subjects would

first

com-

pare

the 10s

digits

and

then would compare

the

Is

digit only

if a 10s

digit match

was

found.

Lively

and

Sanford

(1972)

used

a

memory

set

from

one

category

and a

dis-

tractor

set

consisting

of

some members

of

that category

and

other members outside

that

category. Negative items outside

the

category

of the

memory

set

showed

a

set-size

function

with reduced slope.

The

various findings

in

these memory-

search studies

differ

in

many details

that

will

not

be

discussed here.

They

all

tend

to

show

the use of

some sort

of

controlled search

that

is

facilitated

by the

presence

of

categories

in

the

memory

set.3

The final

studies

to be

considered

are

those

visual search studies

in

which

M = 1 and F

varies,

but in

which

the

visually presented

items

fall

in two or

more

categories,

one of

which

matches

the

category

of the

memory-

3

We

shall

not

attempt

at

this

time

to

explain

why

a

particular controlled search strategy

is

adopted

in

a

particular

paradigm.

Procedural

differences

among

the

studies would make such explanations

pure guesswork. Another class

of

studies using

categories

also deserves mention

for

completeness,

but is not

discussed

in the

main text because

of a

difficulty

in

ascertaining whether

the

effects

found

in

these studies

were

due to

automatic

or

controlled

processing.

These

are

visual search studies

(M = 1,

F

varied)

that have used memory ensembles

and

distractor

sets

from

different

categories. They have

shown

either

flat

set-size

functions

or

curvilinear set-

size

functions

with reduced slopes (e.g., Brand,

1971;

Ingling, 1972; Jonides

&

Gleitman,

1972,

1976).

These studies have utilized

CM

designs

with

low

practice

levels;

this

makes

it

difficult

to

ascertain

whether

the

slope reductions

are due to the

presence

of

automatic detection,

to

beneficial

effects

of

cate-

gorization

on

controlled search,

or to

some combina-

tion

of

these

factors.

Note

that

the

slope reductions

for

visual set-size

functions

normally should

be

taken

as

evidence

of

automatic detection.

That

is, in a

controlled search

one

would expect

a

serial

comparison process

to

be

needed

to

compare

the

memorized

category

against

the

category

of

each displayed item. How-

ever,

it was

seen

in our VM

'data

from

Part

I/

Experiment

2

that

a

reduction

of

slope occurred

when

M was

equal

to 1 and F

varied,

and we

sug-

gested

that

a

"controlled parallel search" might

be

responsible

for

this result.

A

similar argument might

be

made

to

explain

the

slope reductions

in the

above

visual

search studies.

We do not

particularly

favor

such

an

explanation because

it

does

not

explain

why

normal

set-size

functions

are

found

in

visual

search

studies that

do not use

categories

(e.g.,

Atkinson,

Holmbren,

&

Juola,

1969).

A

finding

those

from

studies

using

categories

in

visual search

is

that

of De

Rosa

and

Morin

(1970)

in a

memory search study. They

showed

that

when

the

memory

set

consisted

of

consecutive

digits, then both

the

positive

and

nega-

tive reaction times increased

as a

function

of the

numerical

closeness

of the

displayed item

to the

boundaries

of the

consecutive memory set.

The CM

procedure

was

used with small amounts

of

practice,

so

it is

again

difficult

to

ascertain whether such

effects

were

due to the

action

of

automatic detection

or

to

some controlled search facilitation allowed

by

the

categorical character

of

the

memory set.

PERCEPTUAL

LEARNING

AND

AUTOMATIC ATTENDING

145

set

item. Smith

(1962)

and

Green

and

Ander-

son

(1956)

carried

out

similar

studies

in

which

a field of

colored two-digit numbers

was

pre-

sented

and the

subject

was

asked

to

search

for

a

particular two-digit number

in a

par-

ticular

color.

The

results

showed

that

search

rate depended much more

on the

number

of

items

in the

designated color

than

on the

total

number

of

items presented, though both

effects

were

present.

A VM

procedure

was

utilized

in

their studies

so

that

automatic

detection

could

not

have been used

to

restrict

search

to the

items

of a

particular color.

Probably

a

two-phase

controlled

search

was

utilized

in

this situation.

First,

a

rather fast

serial

search

was

probably

carried

out to

locate

the

next item

of the

designated color;

then

a

slow comparison

of

that

two-digit

number

was

probably made

to

determine

whether

it was the

target.

This

explanation

is

supported

by the

fact

that searching took

a

long time

(up to 20

sec),

so

that

a

30-40

msec

search rate

for

color could have accounted

for

the

increases

in

response time

as

total

size

increased. These increases were small

only

in

comparison with

the

larger

within-

category

effects.

The

main conclusion

to be

drawn

from

the

studies reported

in

this section, based

on re-

peated

findings, is

that

the

presence

of

cate-

gories

in

search tasks

can be

used

to

facilitate,

benefit,

and

modify

controlled search.

III. Experiments

on

Focused Attention

In

part

I we

made

the

case

that

the

processes

utilized

in

attention

experiments

and

those utilized

in

search

and

detection experi-

ments

are

often

the

same.

In

fact,

in

many

cases

it is

purely arbitrary whether

a

given

study

is

referred

to as an

"attention,"

"search,"

or

"detection"

study. Experiment

1

in

Part

I

could

be

described

as a

divided-

attention study

in

which attention

had to

be

divided among

M

memory-set items

and

F

frame

items during each

frame.

The

results

showed

tremendous

deficits

in

dividing

at-

tention

in the VM

conditions,

and

virtually

no

deficit

in

dividing attention

in the CM

conditions.

The

results

of

Experiment

2 of

Part

I, and the fit of the

quantitative model

to

both studies, showed

that

divided-atten-

tion

deficits

in

these paradigms

are due to

the

limitations

of

controlled

processes,

in

particular,

to the

limited rate

of

short-term

search.

Thus,

all our

comments

and

conclusions

concerning search

and

detection

apply

equally

well

to

attention studies.

In

particular,

CM

training should

lead

to the

development

of

automatic detection

that

shoulld bypass

divided-attention

limitations,

while

VM

training should cause controlled search that

should

severely

limit

the

ability

to

divide

attention.

In

discussing

the

development

of

automatic

detection

we

have proposed

that

an

auto-

matic-attention

response

is

learned

in re-

sponse

to the

unchanging members

of the

memory ensemble.

The

present

study

will

test this hypothesis.

The

test

(Experiment

4d)

will

entail asking

the

subject

to

ignore

certain locations

and

then inserting

in

those

locations items

that

subjects

had

been pre-

viously

trained

to

respond

to as CM

targets

(to see

whether these targets attract

atten-

tion).

These studies

will

also answer

the

following

question:

To

what degree

can the

subject

focus

attention

on a

specified

subset

of the

inputs without distraction

from

the

remain-

ing

(irrelevant) inputs. Such studies

are

usually termed

focused-attention

studies,

in

contrast

to the

studies

of

Part

I and

Experi-

ments

1 to 3 of the

present article,

studies

that

would

be

appropriately termed divided-

attention

studies,

A.

Terminology

There

is a

problem

of

terminology

in the

studies

of

this section

that

is

best solved

by

the

introduction

of the

following definitions:

1.

A

foil

refers

to any

input

that

appears

in

a

to-be-ignored display location, whereas

a

distractor

refers

to a

nontarget

that

appears

in

to-be-attended display location.

2.

A CM

foil

is a

foil

that

has

previously

been

used

in CM

training

as a

memory-set

item.

3. A CM

target

foil

is a CM

foil

that

would

have been

a

target requiring

a

positive

re-

sponse

if it had

appeared

in a

to-be-attended

146

RICHARD

M.

SHIFFRIN

AND

WALTER

SCHNEIDER

100

eo

40

20

F-2

F-4/diagonal

F-4

M

~ 0 I I 0 I 2 4

|

I

SPACING

OF 2

TARGETS

|

NUMBER

OF

TARGETS

Figure

8.

Data

from

Experiment

4a.

Estimated per-

centage

of

detection

as a

function

of

number

and

spacing

of

targets

in a VM

procedure with

frame

time

equal

to 200

msec.

The

spacing

0

points

are

non-

identical

targets, while

the

spacings

of

1,

2, and 4 are

identical

targets.

(F

=

frame

size.)

display location (although

it

appears

in

fact

in

a

to-be-ignored display

location).

It is a

member

of the

current memory set.

4. A VM

foil

is a

foil

that

has

previously

served

as

both

a

target

and

distractor

in VM

conditions.

5.

A VM

target

foil

is a VM

foil

that

would

have been

a

target

requiring

a

positive

re-

sponse

if it had

appeared

in a

to-be-attended

display location.

It is a

member

of the

cur-

rent

memory set.

6.

Valid

positions

or

characters

are

to-be-

attended positions

or

characters. Invalid

positions

or

characters

are

to-be-ignored posi-

tions

or

characters.

7.

FII

denotes

a

trial

in

which

two

identical

memory-set

items appear,

one in a

to-be-at-

tended

display position,

and one in a

to-be-

ignored

display position.

8.

FNI

denotes

a

trial

in

which

two

dif-

ferent

memory-set items appear,

one in a to-

be-attended display position,

and one in a

to-be-ignored

position.

B.

Focusing

Attention

in a VM

Multiple-

Frame Task

The first

study

in the

present series

of

experiments

is

designed

to

show

that

"con-

trolled

search"

is not a

misnomer,

that

sub-

jects

can

control their search

to the

extent

that

VM

foils

can be

ignored,

and

that

search

can be

carried

out

through

the

valid display

positions without decrement caused

by the

foils.

1.

Met

hod

The

paradigm

utilizes

the

multiple-target, multiple-

frame

VM

procedure.

There

are

three

main

con-

ditions:

(a)

M

= 2, F = 2; (b) M = 2, F = 4; (c)

M

= 2, F

=

4,

diagonal. Condition (c),

denoted

"diagonal,"

was

designed

so

that

one of the di-

agonals

of the

display

was

always

valid

(to-be-

attended),

and the

other diagonal

was

always

in-

valid

(to-be-ignored).

In

this

condition four

char-

acters were presented

on

each frame,

two

valid,

and two

invalid

foils.

We

expected

that

this diagonal

condition

would elicit performance similar

to

that

for

the M = 2, F = 2

condition,

and

better

than

that

of the

M

= 2, F = 4

condition.

The

four

subjects

in

this study were

the

same

as

those used

as in

Experiment

3 of

Part

I. In

the

diagonal condition, only

the

upper-left

and

lower-right

frame

positions ever contained

a

target.

The

subjects

were

fully

instructed regarding

this

fact

and

were instructed

to

ignore

the

invalid

diagonal.

For

each subject,

the

blocks

of

trials

utilizing

the

diagonal procedure were

run

after

the

other conditions were completed.

The

M

= 2, F = 2

condition

had 14

blocks

per

subject;

the M

=

2,

F

= 4

condition

had 11

blocks

per

subject;

the

diagonal

condition

had 16

blocks

per

subject,

the

first

4

of

which were practice blocks.

There

were

120

test trials

per

block, plus

an

additional

30

trials

of

practice

for the first

block

of a

session

and

15

trials

of

practice

for

each subsequent block

in

a

session.

The

procedure used

in

this study

differed

some-

what

from

that

of

Part

I/Experiment

3 and

from

the

other multiple-target

tasks

reported

in

this

article.

The

primary

difference

lay in the

relation

of

target

similarity

to

spacing.

The

spacing

0

con-

dition utilized

NI

targets

only,

and the

spacing

1,

2,

and 4

conditions utilized

II

targets

only.

In

addition,

the

present experiment allowed

targets

to

reoccur

in the

same frame positions

if

they

were

not

in

successive frames. Also,

in the

present

study,

the

subjects

pushed

a

single response button each time

they thought they detected

the

target.

The

responses

were

to be

made when

the

targets

appeared

rather

than

at the

trial's end.

2.

Results

and

Discussion

On

about

1%

of the

trials

in

each condition

a

response

was

made

before

the

target

ap-

peared,

and

these responses were

not

counted.

The

results

are

presented

in

Figure

8. The

results

of the F = 2 and

diagonal conditions

obviously

do not

differ,

but

results

of

both

conditions

are

clearly superior

to

those

of the

F

= 4

condition. These results were expected

on

the

supposition

that

the

subject should

PERCEPTUAL LEARNING

AND

AUTOMATIC ATTENDING

147

have been able

to

control

his

processing

in

the

diagonal condition

so

that

comparisons

would

occur only

for the

characters

on the

valid diagonal.

The

peculiar relationship

of

spacing

to

target similarity

in

this study caused

the

shape

of the

spacing

functions

to

appear

to

differ

from

those

in

previous multiple-target

studies.

In

fact,

however,

the

corresponding

points

from

the

present study

and

Part

I/

Experiment

3 are

quite close

in

value.

It is

interesting

to

note

the

subject's comments

at the end of the

experiment. They noticed

an

excess number

of II

conditions overall,

but

none

noticed

that

the II

pairs

were

not

tested

at

spacing

0, nor

that

the

NI

pairs were

not

tested

at the

longer spacings.

The

implications

of

this study

are

straight-

forward.

Subjects

can

control their search

in

VM

situations

at

least

to the

degree

that

comparisons

can be

limited

to a

specified

diagonal.

It is

possible

that

characters

on the

invalid

diagonal

are

sometimes compared,

but

not

until

the

valid diagonal

is

searched

first

(if

time were taken

to

compare

foils

during

the

search

of the

valid diagonal, then per-

formance

would

be

worse).

Of

course, this

study demonstrates only

a

minimum amount

of

subject control.

In

future

studies

it

would

be

desirable

to

explore this matter more

thoroughly.

For

example,

we

might ask:

Can

search

alternate

between diagonals

in

successive

frames?

Can

search order

be

cued

individually

for

each

frame?

C.

Distraction Caused

by

"Targets"

During

VM

Search

Experiment

4a

showed

no

distracting

effect

of

VM

foils

(on the

invalid diagonal). How-

ever,

none

of

these

foils

was in

fact

identical

to any

member

of the

memory set.

The

present study, then,

is

designed

to

determine

the

distracting

effect

of VM

target

foils:

To

what extent

can

members

of the

memory

set

be

ignored when they appear

in

invalid dis-

play locations?

1.

Method

The

paradigm

is

similar

in

general outline

to

that

of the VM

conditions

of

Part

I/Experiment

3.

g

H

O

UJ

H

UJ

0

1

—

UJ

cc

\-

UJ

o:

UJ

IUU

90

80

70

en

-

*v

0

Q

0

N.

/

^V

o

—

o

FII

•—•FNI

i

ii

i

-I

+1

+4

NUMBER

OF

FRAMES FROM

TARGET

TO

FOIL

Figure

9.

Data

from

Experiment

4b. FII =

target

foil

identical

to

target;

FNI

=

target

foil

nonidentical

to

target. Percentage

of

target detection

as a

function

of

the

spacing

and the

similarity between

the

target

and the

target

foil.

Varied-mapping procedures were

used,

and

frame

time

was 200

msec.

The

peculiarities

of

Experiment

4a

were eliminated.

The

multiple-frame procedure

was

utilized with

M

= 2 and F = 4. The

upper-left, lower-right

diagonal

was

valid,

and the

other

diagonal

was

invalid. Either zero

or one

targets appeared

on

the

valid

diagonal,

and an

appropriate

binary

re-

sponse

was

required.

A VM

task

was

utilized

on

the

valid diagonal,

and the

foils

on the

invalid

diagonal

were

chosen

from

the

distractor

set for the

valid

diagonal.

In

addition, there

was on

every

trial exactly

one VM

target

foil

(i.e.,

a

member

of

the

memory set)

on the

invalid diagonal.

On

one-third

of the

trials,

only

a VM

target

foil

appeared,

always

on

frames

8-13.

On

two-thirds

of

the

trials both

a

target

foil

and

target appeared;

on

one-half

of

these trials

the

target

and

target

foil

were identical

(FII),

and on

one-half

of

these

trials

the

target

and

target

foil

were

different

(FNI).

Finally,

the

target appeared

on any of

frames

8-13,

and the

target

foil

appeared equally often

on

frames

—4,

—1,

+1,

and +4

with

respect

to the

target

frame.

That

is, the

spacing between

the

target

and

target

foil

was

systematically varied. Thus,

the

target-foil-only

trials occurred with

a

probability

of

J,

and

each

of the

other eight conditions occurred

with

a

probability

of 8 X i = A. All

these

trials

were

randomly

intermixed within each block.

Each block contained

144

test

trials

preceded

by

15

practice trials. Each subject

ran

through

a

total

of

12 or 13

blocks

in

four

sessions.

2.

Results

and

Discussion

The

results

are

shown

in

Figure

9. The

figure

gives

the

percentage

of

hits

as a

func-

tion

of the

spacing between

the

target

and

148

RICHARD

M.

SHIFFRIN

AND

WALTER SCHNEIDER

the

target

foil,

when

the

target

foil

is

iden-

tical

(FIX)

and

nonidentical

(FNI)

to the

target.

The

correct rejection rate when

no

target

was

present

was

91%.

The

results

may

be

summarized

briefly:

The

target

foil

had

no

effect

on the hit

rate except when

it was

different

from

the

target

(FNI)

and

preceded

the

target

by 1

frame,

in

which case detec-

tion

probability

was

decreased

by

.11.

In the

present study

a

target

foil

reduced

performance

when

it

preceded,

but not

when

it

followed,

the

target, Suppose

that

this

re-

duction

is due to the

same factors

that

pro-

duce decrements

in

multiple-target

detection

in

VM

conditions (Experiment

3,

Part

I).

Then

one

target probably inhibits detection

of

a

subsequent target,

but not of an

anteced-

ent

target.

That

is, the

reduced detection

at

spacing

1

seen

in the VM

conditions

of

Part

I/Experiment

3 and

also seen

in

Figure

4

and 6 of the

present paper, could have been

caused

by

either

of the two

targets' reducing

detection

of the

other.

The

present results

provide some reason

to

argue

that

it is the

first

of

two

successive

targets

that

reduces

detection

of the

second.

Let us

assume

that

the

decrement

in

per-

centage

of

detection

of two

targets

in VM

paradigms

is in

fact

a

decrement

in

detection

of

the

second

target.

Then

it is

possible

to

compare

the

magnitude

of the

decrements

in

the

multiple-target studies (e.g., Experi-

ment

3,

Part

I) and the

present study.

In

fact,

the

decrements

are

much larger

in the

earlier studies

in

which

all

display locations

were

valid.

For

example,

the

difference

in

detection between spacing

1 and

spacing

4

in

Part

I/Experiment

3 was 30% in the

NI

condition

and

8%

in the II

condition;

the

comparable decrements

in the

present study

are

\\%

and

0%.

Thus

a

target

foil

reduces

detection

of a

target

in the

but

the

reduction

is

much smaller than

that

caused

by an

actual target.

How

can the

present

findings be

reconciled

with those

of

Experiment

4a in

which foils

did

not

impair performance?

The

pattern

of

findings

would

be

explicable

if the

valid

diagonal were always searched

first and

then,

whenever

that

search

finished

early,

one or

more

characters

on the

invalid diagonal were

inadvertently

checked

in

addition.

In

this

event, target

foils

would occasionally

be

noticed

and

might harm subsequent detection

in

a

fashion similar

to

that

caused

by

true

target detection.

Of

course, this hypothesis

is

speculative

and

other explanations

are

undoubtedly

available.

Whatever

the

explanations

for the

details

of

the

results,

it is

safe

to

summarize

the

results

of

Experiments

4a and 4b as

follows:

Subjects

are

able

to

control their search

in

varied-mapping paradigms.

The

degree

of

their control

is

sufficient

to

eliminate

any

distracting

effect

of

nontarget

foils

and to

reduce

the

distracting

effect

of

target

foils

well

below

the

level caused

by

other targets.

Thus, attention

focusing

is

quite successful:

VM

foils

have,

at

most,

a

small distracting

effect

when they appear

in

to-be-ignored

locations

during controlled search.

D. The

Distracting

Effect

of

"Targets"

During

CM

Search

Experiments

4a and 4b

examined

the

ability

to

focus

attention during controlled

search.

We

next ask:

To

what degree does

attention

focusing

affect

automatic detec-

tion?

Our

previous studies have demonstrated

that

automatic

detection

is not

affected

by

frame

size,

so

there would

be no

point

in

carrying

out a CM

counterpart

of

Experiment

4a in

which

the

invalid diagonal would con-

tain distractors only.

We

decided

to

carry

out

a

counterpart

to

Experiment

4b to find out

whether

a CM

target

foil

would interfere

with

automatic target detection

on the

valid

diagonal.

M and F

were

set

equal

to 2.

During each

frame,

each diagonal contained

one

mask

and

one

character.

One

diagonal

was

always

valid,

the

other invalid.

On

every trial

a CM

target

foil

appeared

on the

invalid diagonal

in

exactly

one

frame.

A CM

target appeared

on

the

valid diagonal

on

two-thirds

of the

trials;

on

one-half

of

these

trials

the

target

and

target

foil

were identical

(FII)

and on

one-half,

nonidentical

(FNI).

In

each

of

these cases,

the

target

foil

occurred either

four

frames

before,

in the

same

frame

with,

or

four frames after

the

target

(-J

probability

PERCEPTUAL

LEARNING

AND

AUTOMATIC

ATTENDING

149

each).

There were

162

trials

per

block

and 6

blocks

per

each

1-hour

session.

Two

sessions

were

run

with

frame

time equal

to 60

msec

and two

sessions were then

run

with

frame

time

equal

to 30

msec.

The

results

are

shown

in

Table

2. The

only

significant

effect

was a

slight drop

in

performance

(about

4%)

in the

FII

condition

at / = 60

msec with simultaneous target

and

foil

(0

=

4.45,

p<.QOQl);

performance

dropped considerably when

/

dropped

to

30

msec,

but all

conditions became roughly

equal.

The

results

of

this study demonstrate

that

a

target

foil

hinders detection

of an

identical

simultaneous

target.

The

magnitude

of the

effect

is

small,

but so is the

magnitude

of

the

decrement

that

occurs when

two

simul-

taneous

CM

targets

are

presented.

In

fact

these

decrements

are not

much

different

at

the

equivalent

frame

times

(4% vs.

&%).

It

seems reasonable

to

assume

that

the

same

mechanism

is

causing both

effects.4

It is

interesting

to

compare these

findings

to

those

of

Eriksen

and

Eriksen

(1974).

In

our

terminology, they used

a

single-frame

CM

task with

M — 2, F = 1, and

they used

reaction

time

as the

dependent measure.

However,

the

distractor

set and the

memory

ensemble

were both

of

size

2 and

were con-

sistently mapped across trials,

so

that

an

equally strong

but

opposite tendency

to

auto-

matically respond

to the

members

of the two

sets

was

probably learned.

(In our CM

studies, only

the

memory-set items

can

come

to

elicit

automatic responses, because dis-

tractors

are

presented

on

every trial.

The

only

exception

in our

studies occurred when

F

= 1 in the

single-frame

paradigm

of

Part

I,

and

even then

the

distractor

set was

always

larger than

the

memory set.)

In the

Eriksen

and

Eriksen study,

the

relevant item always

appeared directly above

the fixation

point,

but

three invalid items were placed

on

each

side

of the

relevant item.

The

nature

and

distance

of

these invalid items were varied.

When

the

distance

to the

nearest item reached

1

°

of

visual angle,

the

invalid characters

had

little

effect

on

reaction time.

At

closer dis-

tances,

all

reaction times were slowed,

but

flanking

distractors produced

the

greatest

Table

2

Effect

of

Distraction

on A

utomatic

Detection: Experiment

4c

Variable

Session

1

60-msec

frame

time

FII

FNI

FII

FNI

FII

FNI

Session

2

60-msec

frame time

FII

FNI

FII

FNI

FII

FNI

Session

3

30-msec

frame

time

FII

FNI

FII

FNI

FII

FNI

Session

4

30-msec

frame time

FII

FNI

FII

FNI

FII

FNI

Spacing

(target

to

foil)

-4

0

+4

-4

0

+4

-4

0

+4

-4

0

+4

%

hits

91.9

94.2

89.4

95.6

96.1

95.

1

95.4

93.5

90.7

93.8

92.8

95.6

75.7

79.1

74.5

77.6

77.1

80.1

77.3

78.9

80.3

81.0

78.7

78.2

%

correct

rejections

90.0

91.2

75.2

71.5

Note.

FII

=

trial

in

which

two

identical memory-set

items

appear,

one in a

to-be-attended display position,

and one in a

to-be-ignored display position.

FNI

•=

trial

in

which

two

dif-

ferent

memory-set

items

appear,

one in a

to-be-attended

posi-

tion,

and one in a

to-be-ignored position.

slowing

(since

they automatically produced

a

competing

response);

flanking

characters

that were

not

distractors

or

memory-set

items produced

a

moderate

slowing

(regard-

4

The

results

in

Table

2

give some indications

that

the

disrupting

effect

may

change

with

practice.

Over

the

four

sessions,

the

differences between

FII

and

FNI at

spacing

0

was, respectively, 6.2%, 3.1%,

3.1%,

and

.7%.

If

this trend actually exists,

it may

be

caused

by the

development

of a new

automatic

response

that

restricts search

to the

valid

diagonal.

That

is,

position-specific information might govern

the

automatic-attention response; such

an

auto-

matic process could

be

learned because

the

valid

diagonal never changes over trials.

It

would

be

interesting

in

future

investigations

to

compare per-

formance

in

this condition

with

performance

in a

condition

that

alternates

the

valid

diagonal

from

trial

to

trial,

since

alternation

should

prevent

the

long-term learning

of

position-specific encoding.

150

RICHARD

M.

SHIFFRIN

AND

WALTER SCHNEIDER

90

o

LU

r~

80

LU

Q

cr

LU

o

OL

LU

0.

70

60

50

NO

FOIL-

-I 0

+1

NUMBER

OF

FRAMES FROM

TARGET

TO

FOIL

Figure

10.

Data

from

Experiment

4d.

Percentage

of

target

detection

in a

varied-mapping procedure

as a

function

of the

spacing

between

the

target

and the

target

foil,

when

subjects

had

previously

been

trained

to

respond

to the

foil

as a

consistent-mapping target.

Frame

time

was 200

msec.

less

of

their visual similarity

to

either set),

and flanking

targets, whether identical

or

nonidentical, produced

the

least

slowing

(since they automatically produced

a

com-

patible

response).

Both

the

Eriksen

and

Eriksen

(1974)

study

and our

study suggest

that

CM

target

foils

can

neither

be

excluded

from

processing

nor

prevented

from

affecting

performance.

In

addition, however,

the

Eriksen

and

Eriksen

result suggests

that

the

spatial

configuration

of

the

inputs

can

determine

the

magnitude

of

these

effects

(see Footnote

4 for a

discus-

sion

of

location-specific automatic

detection).

E. The

Distraction

of

Controlled Search

by

Automatic

Detection

Controlled search depends

on an

apparently

serial process

that

should easily

be

disturbed

if

an

automatic-attention response occurs

that draws attention

to an

invalid location.

Such

a

rationale suggests

a

paradigm

for

our

next study

in

which

CM

foils

appear

on

the

invalid diagonal while

a

controlled search

occurs

on the

valid diagonal.

This

study

is

probably

the

most important

in

this series

(4a-4d)

because

it

provides

a

test

of the

hypothesis

that

an

automatic-

attention response

to

consistently trained

targets

is

learned.

1.

Method

Each

frame

contained

4

characters.

The

upper-

left

to

lower-right diagonal

was

valid. Memory-set

size

was 2, and the VM

conditions were utilized.

Search

on the

valid diagonal

was for

consonants

in

consonants

(or

digits

in

digits

for

other sub-

jects).

The

foils

on the

invalid diagonal were

chosen

from

the

distractor

set

used

for the

valid

diagonal,

except

for the CM

foil.

When

a CM

foil

appeared

it was

chosen

from

the set

that

had

served

as the CM

memory

ensemble

in all

for

that subject. Thus,

if

consonants were being

used

on the

valid diagonal,

a CM

foil

would

be a

digit,

and

vice versa.

On

one-sixth

of the

trials, neither

a

target

nor a

CM

foil

appeared;

on

one-sixth

of the

trials only

a

target appeared;

on

one-sixth

of the

trials only

a CM

foil

and no

target appeared;

on

one-half

of

the

trials both

a

target

and a CM

foil

appeared,

with

the

spacing between them

equally

likely

to

be

—1,

0,

+1.

Each block

of

trials

contained

144

test

trials.

The

first

block

of

each session

had

IS

practice trials

and the

other three blocks

had 5

practice

trials.

Two

sessions were

run for

each

of

the

four

subjects (the same subjects

as

those used

in

Experiments

4a-4c.)

The

frame

time

was 200

msec.

2.

Results

and

Discussion

The

results

are

shown

in

Figure

10.

Each

percentage

is

based

on

7,68 observations.

When

no CM

foil

or

target appeared

the

false

alarm rate

was

4%.

When only

a CM

foil

appeared

the

fajse

alarm rate

was

again

4%.

Thus,

in the

absence

of an

actual target

the

presence

of a CM

foil

caused

no

increase

in

false

alarms.

Since

the

appearance

of CM

foils

was

highly

correlated

with

the ap-

pearance

of

targets,

one

might have supposed

that

a

bias

or

guessing strategy would arise,

such

that

subjects would more often guess

that

targets were present

if a CM

foil

was

seen.

The

present

data

argue against such

a

bias

(as do the

data

discussed below).

The hit

rate when

a

target

but no CM

foil

was

present

was

84%.

The

distraction caused

by a CM

foil

may be

determined through

comparison with

this

performance level.

When

the CM

foil

preceded

the

target

by one

frame

the hit

rate

was

&2<fc,

not

significantly

PERCEPTUAL LEARNING

AND

AUTOMATIC ATTENDING

151

lower

than

the 84%

base

rate. When

the

target

and CM

foil

were presented simul-

taneously,

the hit

rate dropped

to

62%.

And

when

the CM

foil

followed

the

target

by one

frame

the hit

rate rose

to

77%,

a figure

still

significantly

lower statistically than

the

84%

hit

rate

when

no CM

foil

was

present.

In

short,

a CM

foil

provides

little

hindrance

to

the

detection

of a VM

target presented

in

the

following

frame,

greatly hinders detection

of

a VM

target presented simultaneously,

and

even reduces slightly

the

detection

of a VM

target presented

in the

preceding

frame.

The

simplest interpretation

of

these

re-

sults

is

that

a CM

foil

interrupts

the

ongoing

controlled

search

and

causes

a

loss

of

process-

ing

time, thereby reducing target detection.

The

interruption

is

caused

by

what

we

have

termed

an

automatic-attention response

to

the CM

foil.

We

have argued that subjects

have been trained

to

respond

to CM

targets

with

an

automatic-attention response. Even

when

such

a

target appears

on a

to-be-ignored

display diagonal,

it

apparently causes

an at-

tention

response

that

interrupts

processing

along

the

valid diagonal

and

directs attention

to the

invalid diagonal.

The

time lost

before

attention

is

returned

to the

valid diagonal

and

the

search

is

resumed causes

a

consider-

able decrement

in

performance

if the

target

is

in

fact

on the

valid diagonal during

that

frame.

Since

target detection

in a

frame

following

a CM

foil

is not

hindered,

the

recovery

from

the

distraction caused

by a CM

foil

must

be

quite

rapid;

that

is,

recovery must take place

in

a

time period under

200

msec. Further-

more,

the

automatic-attention response must

occur

fairly

rapidly, since

a CM

foil

even

reduces

detection

of a

target

in the

preceding

frame.

Perhaps

the

processing

of one

frame

occasionally

overlaps

the

start

of the

next;

for

example,

a

comparison initiated

but not

completed

before

termination

of a

frame

may

be

completed

before

controlled processing

of

the

begins. Occasionally,

a

target

might

be the

character undergoing compari-

son

when

the

subsequent

frame

begins,

and

a CM

foil

in

that

could interrupt

comparison

of the

target

and

thereby impair

performance.

The

primary

finding of the

present study

is the

demonstration

that

the

responses

to

CM

targets

are

both

well

learned

and

auto-

matic.

CM

targets cannot

be

ignored, even

when

they

are

known

to be

irrelevant

and

occur

in

consistently invalid display loca-

tions

and

even when subjects

are

instructed

to

ignore them.

Our

results,

of

course,

do not

establish

that

it is

impossible

to

control

the

detection

processes

that

we

have labeled

"automatic."

In

fact,

Sperling (Note

1,

Note

2) has re-

ported

some

findings

that

do

tend

to

show

that

at

least some amount

of

control over

some

aspects

of the

search process

in CM

multiple-frame

tasks

is

possible. However,

the

degree

of

control over,

and the

ability

to

ignore,

stimuli

that

subjects have been

trained

to see as

targets

in CM

situations

are

clearly much less than

in VM

situations.

Thus,

for the

processing mode

in the CM

conditions

of the

present tasks,

we

prefer

the

possibly slightly inaccurate,

but de-

scriptive, term automatic

to the

logically

more

accurate,

but

less

descriptive,

term

systemic, which

was

used

in

Shiffrin

(197Sa)

to

refer

to the

same type

of

processing.

F.

Limitations

on the

Ability

to

Focus

Attention

The

present series

of

studies

(4a-4d)

ex-

amined

the

subjects' ability

to

focus

atten-

tion. Experiment

4a

showed

that

attention

during

controlled search could

be

focused

on

specified

spatial locations. Experiment

4b

showed

that

the

focusing

is not

complete,

because

certain types

of

stimuli

in

to-be-

ignored

locations

are

sometimes processed

and

when processed,

can

reduce target detec-

tion. Experiment

4c

showed

that

a CM

target

in a

to-be-ignored

location

hinders

automatic

deletion

by a

small amount.

Ex-

periment

4d

showed

that

attention

is

greatly

distracted

from

the

relevant locations when

a CM

target appears

in a

to-be-ignored loca-

tion

during

a VM

search

task.

This

last

find-

ing

is

particularly interesting because

the

distracting stimulus

differs

from

the

relevant

stimuli

not

only

in

spatial

location

but

also

in

category.

152

RICHARD

M.

SHIFFRIN

AND

WALTER SCHNEIDER

These

findings are

particularly important

because previous demonstrations

of

difficul-

ties

in

focusing attention have usually utilized

incompatible responses.

That

is, a

stimulus

in

response

to

which

a

subject

has

been

trained

to

emit

response

x is

presented

in a

to-be-

ignored

location

in

conjunction with

a

stimulus

requiring

a

response

y

that

is

incompatible

with

x. In the

Stroop

Color-Word

Inter-

ference

Test

(1935),

for

example,

the

sub-

ject must read names

of

colors

that

are

printed

in ink

colors

that

do not

correspond

to the

names. Reading speed

is

greatly slowed

in

this case (see Jensen

&

Rohwer, 1966).

Keele

(1972)

showed

that

decrements

in

processing stimuli resulted when

a

similar

color-name

incompatibility

was

present.

The

Eriksen

and

Eriksen

(1974)

study discussed

above also showed

that

response time

was

dependent

on the

compatibility

of

responses

between

stimuli

to be

attended

to and

those

to

be

ignored.

Many other examples

of

this

kind

can be

found

in the

literature,

but our

demonstra-

tions

differ

in one

very important respect.

Namely,

the

distracting stimulus

in our

stud-

ies

hurts

performance even

though

subjects

have been trained

to

respond

to it in

exactly

the

same

way as to the

target

stimulus. Both

types

of

studies demonstrate

that

the

to-be-

ignored

stimulus receives processing,

but the

studies utilizing incompatible responses

do

not

demonstrate

any

processing interaction

short

of the

motor responses themselves.

On

the

other hand,

our

studies suggest

that

the

focused-attention

deficit

results

from

a di-

version

of

attention

and an

accompanying

loss

of

processing time, since there

is no re-

sponse incompatibility.

Our

studies have shown

that

focused-at-

tention

deficits

can

arise

due to

distraction

by

either

CM or VM

items

in

appropriate

contexts,

though probably

due to

rather dif-

ferent

mechanisms

in the two

cases.

In

many

studies

in the

literature

that

have shown

focused-attention

deficits,

it is not

clear which

factor

is

responsible.

For

example,

in

shadow-

ing

tasks

the

listener repeats aloud

a

desig-

nated message (usually

in one

ear) while

other

distracting messages

are

also presented.

The

early studies showed

that

distracting

messages barely harm shadowing performance

when

they

are

distinguishable

by an

obvious

physical characteristic (such

as

spatial

origin;

see

Cherry, 1953; Cherry

&

Taylor, 1954).

These

studies

are

probably like

our

Experi-

ment

4a in

which

one

diagonal

is

relevant

during

VM

search

and the

other

can be

ignored.

A

result related

to

Experiment

4b

can be

found

in

studies

by

Treisman

(1964a,

1964c)

in

which items

of

some possible

relevance

are

presented

in the

nonshadowed

ear

(similar

to our

target

foils).

For

example,

if

the

distracting message

is in the

same

voice,

but in

French,

a

considerable distrac-

tion occurs. Many studies have shown

that

the

message

in the

nonshadowed

ear is an-

alyzed

to

some considerable depth (e.g.,

Lewis,

1970; Treisman, 1960, 1964b).

In

these studies

it is not

clear which type

of

processing causes

the

analysis,

but in

other

studies

it is

clear

that

automatic processing

is

responsible

for the

analysis

that

occurs

(Corteen

&

Wood,

1972;

Von

Wright, Ander-

son,

&

Stenman,

1975).

Further reviews

of

such studies will

not

be

undertaken here because

of the

difficulty

in

ascertaining

whether

focused-attention

deficits

are

caused

by

controlled processing

of

invalid

items

or by

automatic processing

of

invalid

items.5

If

nothing else,

our

results

strongly suggest

that

future

research

on

focused

attention should include controls

to

differentiate

deficits

caused

by

controlled

and

automatic processing.

In

summary,

we

have seen

that

subjects

can

divide attention almost without

deficit

when

automatic detection

is

utilized

(Part

I/

6

Controlled

processing

might

be

given

to oc-

casional

inputs

in an

irrelevant

ear,

because

ear of

origin

is a

fairly

difficult

cue to

utilize (compared

with

spatial location

in a

visual task,

for

example).

Whether

automatic

processing

or

controlled proc-

essing

is

used

to

restrict analysis

to the

desired ear,

occasional

failures

of

selection

are to be

expected,

failures

that

will

cause

occasional

items

in the

to-be-

ignored

ear to be

given

controlled

processing.

In

addition,

'Controlled

processing

of

items

in the

to-be-

ignored

ear may

occur

on

occasion when processing

of

the

items

in the

valid

ear is

completed

and a

brief

interval

occurs

before

the

next valid input

arrives

(an

argument similar

to

this

is

used

in the

discussion

of

Experiment

4b).

PERCEPTUAL

LEARNING

AND

AUTOMATIC ATTENDING

153

Experiments

1 and 2, CM

conditions,

see

Figure

2) and

cannot divide attention with-

out

deficit

when controlled search

is

utilized

(Part

I/Experiments

1 and 2, VM

conditions,

see

Figure

2).

Focused-attention

deficits

are

quite substantial when caused

by

automatic

responses

to

to-be-ignored items (Experi-

ment

4d and

Figure

10) but are

quite

a bit

smaller

when

caused

by

controlled processing

of

to-be-ignored

items,

since

the

subjects'

control

is

usually adequate

to

prevent such

processing (Experiments

4a and 4b, and

Figures

8 and

9).

One

implication

is the

pre-

diction

that

the

type

of

training

procedures,

VM

or CM,

will

determine whether divided-

or

focused-attention

deficits

will occur.

G. The

Nature

of

Automatic

Detection

The

reversal studies, Experiments

1 and 2,

and the

category study, Experiment

3,

make

it

clear

that

long-term learning

is

responsible

for

the

phenomenon

of

automatic detection

that

is

seen

in the CM

conditions.

The

lengthy

training period required

for

acquisition,

and

the

even longer training periods required

to

alter

the

detection process once learned,

testify

to the

permanent nature

of the

learn-

ing. Furthermore,

the

phenomenon

is

power-

ful

enough

to

transcend

the

laboratory

context. Subjects given

CM

training

on

one

group

of

letters

as

memory-set items with

another group

as

distractors,

as in

Experi-

ments

1 and 3,

report

effects

on

reading out-

side

the

laboratory. Despite

the

fact

that

all

the

letters

used

in the

experiments were

capitalized,

the

subjects reported

that

the

memory-set items

from

the CM

conditions

tended

to

"jump out"

from

the

page during

normal reading.

This

effect

was

distracting

enough

that

one

subject would

not

attempt

to

read

for an

hour

or

more

after

an

experi-

mental session.

It is

clear then

that

automatic detection

reflects

a

powerful

long-term process.

We now

ask: What

is it

that

is

learned? Experiments

4a-4d

imply

that

an

attention response

is

learned,

but

many details

of the

automatic

detection

process

remain

to be

specified.

It is our

feeling

that

several factors con-

tribute

to the

process

that

has

been termed

automatic detection.

First

there

is an

auto-

matic-attention response

to the

features

that

are

encoded

from

an

input target;

this

re-

sponse directs attention

to the

representation

in

short-term memory

of the

relevant visual

input

and

also

to the

representation

in

mem-

ory of the

appropriate member

of the

memory

set. Second,

in

addition,

an

automatic "tar-

get" response

is

learned

that

tells

the

subject

that

a

target

is

among

the

inputs. Third,

in

addition,

in

some

situations

an

automatic

overt motor response (such

as a

button press)

is

learned

in

response

to a

target.

The

third factor,

an

automatically pro-

duced

overt

motor

response,

is

probably

limited

to

special situations

in

which

the

same completely consistent response

to all

targets

is

immediately required.

Our

reaction

time

study

(Part

I,

Experiment

2)

may

rep-

resent such

a

situation,

but our

multiple-

frame

tasks

do

not.

In the

multiple-frame

tasks,

no

overt response

is

required until

the

trial's

end.

In

addition, some

of the

tasks

in

our

studies require

that

the

number

of

targets

be

counted, rather than

that

a re-

sponse

be

made

to

each target

as it

appears.

Finally,

the

tasks

in

Experiment

4

occa-

sionally

present

target

foils

in

to-be-ignored

locations,

and the

subject

has

little

difficulty

suppressing

responses

to

such

targets.

Thus,

we

feel

that

automatic overt responses

can

be

learned

but are

probably

not a

major

contributor

to

performance

in

most

of our

tasks.

The first two

factors,

the

occurrence

of

automatic

"attention"

and

"target"

responses,

undoubtedly

play

a

major

role

in our

tasks.

However, such responses must

be

followed

by

some

sort

of

controlled process

or

controlled

decision

to

generate

the

required overt

re-

sponse.

A

number

of

controlled processes

may be

used.

In

most

of our

studies

it

would

not

have been

sufficient

to

simply

use the

occurrence

of an

automatic

"attention"

or

"target"

response

as a

basis

for a

decision

to

respond.

For one

thing, some

of our

studies

require

responses

to be

counted;

for

another,

some

of our

studies present target

foils

to

which responses must

be

withheld. Further-

more,

in

Experiment

3 we saw

that

the

mem-

ory and

distractor

sets

could

be so

confus-

able

that

automatic responses could

not be

154

RICHARD

M.

SHIFFRIN

AND

WALTER SCHNEIDER

learned

in a

perfectly accurate manner,

so

that

a

switch

to a

controlled item mode

was

necessary

to

check

the

accuracy

of

automatic

responses.

For all of

these reasons,

we

propose

that

following

the

occurrence

of an

automatic-

attention

or

target response,

the

subject

en-

gages

in the

minimal controlled processing

necessary

to

satisfy

the

task

requirements.

Such

controlled

processes

might

consist

of

comparing

the

memory representations

to

which

attention

has

been drawn, counting

the

target instances,

and

checking

the

spatial

location

of

located targets

to see

whether

they

are

foils

or

valid targets.

Before

concluding

this

discussion,

it is

useful

to

consider

briefly

a few

supplementary

hypotheses regarding

the

automatic detec-

tion

process.

Each

of

these hypotheses

as-

sumes

the

occurrence

of an

automatic-atten-

tion response.

First,

consider

the

possibility

that

atten-

tion

is

drawn automatically

to the

representa-

tion

of the

relevant visual input, which

is

then compared serially

to the

memory set.

This

hypothesis

is

easily rejected since

it

implies,

contrary

to

fact,

that

memory-set

size

will have

a

large

effect

under

CM

con-

ditions.

Second,

consider

the

possibility that

an at-

tention

response directs

the

subject

to the

relevant visual input, whose category

is

then

compared

in one

step

to the

category

of the

memory set.

This

hypothesis

is

testable

in

any of

several ways

but is

difficult

to

reject

on

the

basis

of

present evidence.

A

tentative

inference

from

Experiment

3

suggested

that

automatic detection

for

items

in a

four-letter

set

developed much

faster

than category

learning

for

that

set.

If so,

then this category

hypothesis could

be

ruled

out

(because

the

M

= 2 and M = 4 CM

functions converged

quickly

in the

mixed condition

of

Experiment

3).

Nevertheless, additional research

will

be

needed

to

test this hypothesis conclusively.

Assuming

that

an

automatic-attention

re-

sponse underlies automatic detection,

it

seems

clear

why

automatic detection does

not de-

velop

in VM

situations:

An

attention

or

overt

response

that

is

helpful

on one

trial

(when

the

producing stimulus

is a

target) will

be

harmful

on

another (when

the

producing

stimulus

is a

distractor).

A

subject cannot

learn both

an

attending

and a

nonattending

response

to the

same stimulus. While this

argument

seems clear,

an

important theo-

retical question remains. What

is the

under-

lying

mechanism

that

inhibits

the

learning

of

an

automatic-attention response

in the

VM

search situation?

Suppose

that

a

Learning

event

takes

place

each time

a

target

is

found

correctly

and is

therefore

reinforced.

In

consistent (CM)

paradigms there will

be no

impediment

to

the

learning

of

attention responses.

In VM

paradigms,

the

outcome

is

less clear.

It

might

be

supposed

that

every item, whether cur-

rently

a

memory-set item

or a

distractor,

comes

to

elicit attention responses

due to

those trials

on

which

it is a

target. There

are

then several possibilities:

(a)

Learning con-

tinues

until

all

items have acquired attention

responses

of

roughly equal strength. Because

the

responses

are of

equal strength, they tend

to

cancel each other,

and

controlled search

must

be

utilized. Later,

if a

switch

is

made

to a CM

paradigm,

the

strength

of the re-

sponses

to the fixed

memory-set items

be-

comes

greater than

that

for the

distractor

items,

(b) As an

attention response begins

to

develop

it

starts

to

occur

on

trials when

the

input

is a

distractor. Because attention

is

directed

to the

wrong

input, performance

suffers,

and the

response

is

therefore

in-

hibited,

(c)

Each

time

a

distractor

is

com-

pared during

a

controlled search, whether

or

not an

attention response occurs, inhibition

of

any

previously

reinforced

attention

re-

sponse

may

take

place because

a

comparison

is

carried

out but not

reinforced. According

to

explanations

(b) and

(c),

the

inhibition

cancels

any

learning

that

would otherwise

occur,

so

that

attention responses

to any of

the

items never develop

to

significant

degrees.

We

prefer

hypotheses

(b) or

(c),

or any

similar

proposal

that

implies

that

attention

responses

do not

develop

in VM

paradigms.

Is

there

any

evidence

to

distinguish

these

views

from

hypothesis

(a)?

Only indirect

evidence

is

available

at

present,

but the

models

are

easy

to

test.

For

example,

after

VM

training

one

could introduce

new

items

PERCEPTUAL LEARNING

AND

AUTOMATIC

ATTENDING

155

as

targets, with other

new

items

as

distrac-

tors,

or

with

the

previously

trained

VM

items

as

distractors.

The old VM

distractors

should severely hinder performance

if

they

elicit attention responses developed during

tests

could

also

be

carried out,

but a

definitive

answer

is not yet

available

at the

time

of

this writing.

IV. A

Framework

for

Information Processing

This

section

of the

paper

will

be

organized

as

follows.

Section

A

will present

an

overview

of

the

system

and an

overview

of the

role

of

controlled

and

automatic processing. Section

B

will elaborate

on the

fundamental nature

of

controlled

and

automatic processing. Sec-

tion

C

will present

a

framework

for

search,

detection,

and

attention. Section

D

will dis-

cuss

how

automatic

and

controlled processing

are

utilized

in

memory storage

and

retrieval.

A. An

Outline

of a

General Theory

Memory

is

conceived

to be a

large

and

permanent

collection

of

nodes, which become

complexly

and

increasingly interassociated

and

interrelated through learning. Most

of

these nodes

are

normally passive

and

inactive

and

termed long-term

store,

or

LTS, when

in

the

inactive

state.

The set of

currently

ac-

tivated

nodes

is

termed short-term

store,

or

STS.

LTS is

thus

a

permanent, passive repos-

itory

for

information.

STS is a

temporary

state;

information

in STS is

said

to be

lost

or

forgotten when

it

reverts

from

an

active

to an

inactive phase. Control

of the

informa-

tion-processing system

is

carried

out

through

a

manipulation

of the flow of

information

into

and out of

STS.

These

control processes

include

decisions

of all

sorts, rehearsal, cod-

ing,

and

search

of

short-

and

long-term

store.

LTS

contains learned sequences

of

informa-

tion

processing which

may be

initiated

by a

control process

or by

environmental

or in-

ternal

information

input,

but are

then

ex-

ecuted

automatically with

few

demands

on

the

capacity

of

STS.

1.

Long-Term Structure

The

structure

of the

nodes making

up LTS

will

be

treated

as a

very general graph with

complex

interrelations among nodes.

An in-

dividual node

may

consist

of a

complex

set

of

information

elements,

including associa-

tive connections, programs

for

responses

or

actions,

and

directions

for

other types

of

information

processing. What then

sets

off

one

node

from

a

group

of

nodes?

One

node

is

distinguishable

from

a

group

of

nodes

be-

cause

it is

unitized,

that

is,

when

any of its

elements

are

activated (i.e., placed

in

STS),

all of

them

are

activated.

One

activated node

may of

course activate another node,

but it

does

not do so in all

situations, only when

the

context

or the

state

of the

information-

processing system

is

appropriate.

2.

Structural Levels

It

seems likely

that

the

structure

of

long-

term

store,

at

least

in

part,

is

arranged

in

levels (perhaps sometimes

in a

hierarchical

tree

structure).

By

levels

we

refer

to a

tem-

poral directionality

of

processing such

that

certain nodes activate other nodes

but not

vice

versa.

In

sensory processing, there

is a

tendency

for

increasing information reduction

as

successive levels

are

activated. Thus,

a

visually presented word could

first be

pro-

cessed

as a

pattern

of

contrast regions, colors,

regular

variations,

and so

forth; then

lines,

angles,

and

other similar features could

be

activated; then letters

and

letter names

and

verbal

or

articulatory codes; then

the

word's

verbal code;

and finally, the

meaning

and

semantic correlates

of the

word.

This

se-

quence

is

meant

as an

example,

and we do

not

wish

to

imply

that

these

are the

relevant

features,

that

this

is the

only possible order-

ing,

or

that

this listing

is

exhaustive. Such

a

sequence

of

feature

encoding should occur

automatically

to a

normally skilled reader.

3.

Automatic

Processes

An

automatic process

can be

defined

within

this

system

as a

sequence

of

nodes

that

nearly

always becomes active

in

response

to a

par-

ticular input configuration, where

the

inputs

may be

externally

or

internally generated

and

include

the

general situational context,

and

where

the

sequence

is

activated without

the

156

RICHARD

M.

SHIFFRIN

AND

WALTER SCHNEIDER

necessity

of

active control

or

attention

by

the

subject.

An

automatic sequence

differs

from

a

single

node

because

it is not

necessarily unitized.

The

same nodes

may

appear

in

different

automatic sequences, depending

on the

con-

text.

For

example,

a red

light might elicit

a

braking response when

the

perceiver

is in

a

car,

and

elicit

a

walking, halting,

or

traffic-

scanning response when

the

perceiver

is a

pedestrian.

Since

an

automatic process utilizes

a

rela-

tively

permanent

set of

associative connec-

tions

in

long-term store, most automatic

processes

will

require

an

appreciable amount

of

training

to

develop

fully.

Furthermore,

once

learned,

an

automatic process will

be

difficult

to

suppress

or to

alter.

When

an

automatic sequence

is

initiated,

its

nodes

are

activated

and

hence

the as-

sociative information enters STS.

This

fact

does

not, however, mean

that

the

various

elements

of the

automatic process must

be

available

to

consciousness

or

recallable

at a

later

time.

The

activation

in STS

could

be

extremely

brief

(in

msec, say)

and

unless

attention

is

directed

to the

process

when

it

occurs

or

unless

the

sequence includes

an

automatic attention-calling response, then

the

information

may be

immediately lost

from

STS,

and the

subject

may be

quite

un-

aware

that

the

process took place. Even

when

an

automatic-attention response

is

part

of

the

sequence,

it

will

not

necessarily

affect

ongoing

controlled processing unless

the

strength

of the

attention response

is

suffi-

ciently

high.

4.

Thresholds

of

Activation

However

an

automatic process

is

initiated,

whether

by

internal

or

external input

or by a

control

process,

it is

presumed

that

the

prob-

ability

that

the

process will

run to

comple-

tion

depends

on the

strength

of the

initiating

stimulation.

The

simplest

and

most common

examples

are

seen

in

studies

of

psychophysical

thresholds.

If a

letter,

for

example,

is

visually

presented

at a

low-enough

intensity

or a

short-enough

duration, then

it may be en-

coded

not as a

letter

but as a

partial

collec-

tion

of

line-like features.

At

lower durations

or

intensities even these features will

not be

activated.

Although

we

have described automatic

processes

as

largely beyond subject control,

some

indirect control

is

possible through

ma-

nipulation

of the

activation threshold

for

auto-

matic processes.

In

particular, according

to

what

we

shall

call

the

contextual

hypothesis,

the

activation threshold

can be

lowered

by

the

inclusion

of

information

in STS (at the

time

of

presentation

of the

activating input)

that

is

associatively related

to the

nodes

making

up the

automatic

sequence.6

Note

that

a

lowering

of the

threshold does

not

imply

that

the

quality

of

processing

is

improved.

One

result

of

threshold lowering

is

that

the

automatic process will

be

triggered

by

inputs

that

normally would

and

should

not do so. For

example,

the

feature

"horse"

might

be

incorrectly triggered

by the

input

"house"

if the

threshold

for

"horse"

is

lowered

sufficiently.

S.

Controlled Processes

A

controlled process utilizes

a

temporary

sequence

of

nodes

activated

under

control

of,

and

through attention

by, the

subject;

the

sequence

is

temporary

in the

sense

that

each

activation

of the

sequence

of

nodes requires

anew

the

attention

of the

subject. Because

active attention

by the

subject

is

required,

only

one

such sequence

at a

time

may be

con-

trolled without interference, unless

two se-

quences each requires such

a

slow sequence

of

activations

that

they

can be

interwoven

serially.

Controlled processes

are

therefore

tightly

capacity-limited,

but the

cost

of ca-

pacity limitations

is

balanced

by the

benefits

deriving

from

the

ease

with which such

processes

may be set up,

altered,

and

applied

in

novel situations

for

which automatic

se-

6

It may

also

be

possible

to

lower

the

threshold

by a

.recent

activation

of the

same automatic

se-

quence.

However, this hypothesis

is

difficult

to

distinguish

from

the

contextual one,

because

an

activation

of a

sequence

is

usually accomplished

by

the

prior,

.recent

presentation

of

information

as-

sociatively

sequence,

and

this

is

still likely

to be in STS at the

time

of

test.

PERCEPTUAL LEARNING

AND

AUTOMATIC ATTENDING

157

quences have never been learned. Controlled

processing operations utilize short-term store,

so the

nature

of

their limitations

is

deter-

mined

at

least

in

part

by the

capacity

limita-

tions

of

STS.

6.

Short-Term

Store (STS)

Short-term store

is the

labile

form

of the

memory system

and

consists

of the set of

concurrently activated nodes

in

memory.

The

phenomenological

feeling

of

conscious-

ness

may lie in a

subset

of

STS, particularly

in

the

subset

that

is

attended

to and

given

controlled

processing.7

The

capacity

of STS is

determined sto-

chastically (see

Shiffrin

&

Cook, Note

3)

so

that

a

large amount

of

information

may

be

present (activated)

at any one

moment,

but

only

a

small amount

of

information will

persist

for an

appreciable time period

of

several seconds

or

more. Forgetting

or

loss

from

STS is

simply

the

reversion

of

cur-

rently active

information

to an

inactive

state

in

LTS.

What

determines

the

loss rate?

We

sup-

pose

that

the

rate

of

loss

of any

informational

element

or

node

in STS

depends

on the

num-

ber of

similar elements simultaneously active

in

STS.

By

similarity

we

refer

not

only

to

formal

physical similarity

but

also

to

sim-

ilarity

of

features

at

comparable levels

of

processing (e.g.,

the

typeface

of a

printed

word

will

be

less likely

than

the

word itself

to

cause forgetting

of a

verbally encoded

second word

in

memory).

When

a

large

amount

of

similar information

is

present,

the

loss

rate

will

be

rapid

but

will slow

as the

amount

of

active information decreases.

To

give

an

example, when

a

complicated visual

scene

is

presented

to a

subject

briefly

in a

tachistoscope,

a flood of

visual information

enters

STS

and

initiates

a

series

of

chains

of

automatic processing

that

result

in

higher

level features' also entering STS. However,

most

of the

activated

information

will

have

decayed

and

will

be

lost

from

STS in

just

a few

hundred milliseconds

after

physical

offset

of the

scene (see Sperling

1960);

just

a few of the

features, perhaps

at

higher levels,

will

remain present longer than

a few

seconds.

STS has two

somewhat distinct roles.

The

first

is

the

provision

of a

temporary store-

house

for

information currently important

to

the

organism.

That

is, it

acts

as a

selective

window

on LTS to

reduce

the

amount

of

information

for

processing

to

manageable

proportions.

The

second role

of STS is the

provision

of a

work space

for

decision making,

thinking,

and

control processes

in

general.

7.

Learning:

Transfer

to LTS

Consider

first

what

is

meant

by

transfer

from

STS to

LTS. Transfer implies

the

for-

mation

in

permanent memory

of

information

not

previously

there.

To be

precise,

this

con-

sists

of the

association

(in a new

relation-

ship)

of

information

structures

already

in

LTS.

A

minimal requirement

for

this

new

associative structure

is the

simultaneous

presence

in STS of the

separate

elements

to

be

associated

or

related.

That

is, the

various

nodes

to be

linked

in a new

relationship must

be

activated

in

STS.

Thus,

transfer

to LTS

does

not

imply

the

removal

of the

transferred

information

from

STS,

nor the

placing

of

new

"subunits"

in LTS

that

do not

already

exist

in

either

LTS or

STS. Rather, transfer

means

the

formation

of new

associations

(or

the

strengthening

of old

associations)

be-

tween

information structures

or

nodes

not

previously associated

(or

strengthened)

in

LTS. Most

new

associative structures

will

include

as a

component

the

context

in STS

at the

time

of the

transfer.

The

above remarks specify

the

nature

of

new

learning

in STS but not the

cause under-

lying

the

storage mechanism.

It has

been

7

An

alternative formulation, closer

to

that

sug-

gested

by

Atkinson

and

Shiffrin

(1968),

would

use

the

term

STS to

refer

to

those nodes

that

are

given

attention

and

controlled processing. Other

activated nodes would

be

referred

to by

another

term, such

as

"sensory

register"

in

Atkinson

and

Shiffrin's

terminology.

At

such

a

general level

of

discussion,

it is

doubtful

that

there

are

substantive

differences

between

the two

approaches—versions

of

each could

be

constructed

to be

identical

to

each

other. Each approach

has its own

heuristic

ad-

vantages,

but a

theory

is

better judged

in

terms

of

its

detailed assumptions

and

predictions than

by

its

choice

of

either

type

of

terminology.

158

RICHARD

M.

SHIFFRIN

AND

WALTER

SCHNEIDER

shown

that

rehearsal (and coding rehearsal)

are

strongly implicated

in

learning (see

Shiffrin,

197Sb,

for a

discussion).

We

prefer

an

extension

of the

rehearsal hypothesis.

We

assume

that

what

is

stored

is

what

is at-

tended

to and

given controlled processing.

Rote rehearsal

is

just

one

form

that

attention

can

take.

In

fact, maintenance rehearsal

may

result

in

storage

of

low-level auditory

or

verbal codes

not

helpful

for

long-term recall,

(but

helpful

for

long-term

recognition),

while

coding

rehearsal

may

result

in

storage

of

high-level

codes

useful

for

recall. This model

suggests

that

some degree

of

attention

or

controlled

processing

is a

prerequisite

for

storage.

Thus,

incidental learning situations,

in

which

no

extended rehearsal takes place,

will

still result

in

some learning

to the

degree

that

the

input items

are

attended

to

during

presentation.

These

hypotheses

that

controlled processing

will

underlie learning apply

of

course

to the

development

of

automatic processing,

and

in

particular,

to the

development

of

auto-

matic detection studied

in the

search

and

detection paradigms earlier

in

this paper

and

in

Part

I. In

those paradigms

it was

seen

that

automatic

detection

developed

only with

consistent training. Consistent training

is

crucial

when

the

learned sequences

in LTS

contains

an

internal

or

overt response

that

will

be

harmful

to

performance

on

trials

that

are

inconsistent.

For

example,

an

attention

response

to an

item will harm performance

on

trials when

that

item

is a

distractor. Purely

informational

sequences (i.e., sequences

that

do

not

include responses

that

direct internal

processes

or

overt actions) will

be

stored

in

LTS

when attended

to,

regardless

of

con-

sistency

of

training.

In all

cases,

however,

consistent training

and

large numbers

of

repetitions

should lead

to

stronger automatic

encodings

and

processes.

An

implication

of the

hypothesis

that

trans-

fer

to LTS is

engendered

by

controlled pro-

cessing

is the

important

concept

that

con-

trolled

processing,

and

hence attentional

limitations,

will

be

involved during

the ac-

quisition

of

automatic processing.

We

have

largely

been

identifying

attentional limita-

tions

with controlled processing (e.g., con-

trolled search)

and

have shown

how

auto-

matic processing (e.g., automatic detection)

can

bypass attentional limitations.

It

should

not

be

overlooked

that

the

initial learning

of

automatic processing

may

require

a

variety

of

control processes

and

hence

will

be

sub-

ject

to

various limitations

that

may

dis-

appear when learning

has

progressed

to a

high

level.8

8.

Retrieval

of

Information

from

Short-Term

Store

Several retrieval modes

from

STS are

pos-

sible.

An

automatic process might direct

the

retrieval process

to

just

a

subset

of the ac-

tivated information (e.g., only

the

letters,

not

the

masks,

are

compared

in our VM

search

studies).

The

various controlled search strategies

that

are

available

are

normally serial

in na-

ture

but a

variety

of

search orders

is

possible.

Search

order

may

depend upon instructions,

strength

of

short-term traces,

the

nature

of

categories

of the

traces,

the

modality

of the

information,

and the

structure

of

STS.

This

last

point

is

worth emphasizing: Since

STS

is

embedded

in

LTS,

it

partakes

of the

struc-

ture

of LTS and is not a

totally

undiffer-

entiated mass

of

information.

Thus

the

order-

ing

of a

search

can

utilize

this

existent struc-

ture.

In

addition,

the

comparison process

may

be

exhaustive

or

terminating,

and the in-

formation

located

in one

phase

of the

search

can

be

used

to

redirect

a

later

phase

of the

search.

It is the

control

of

search order

that

is

responsible

for

many

of the

selective atten-

tion

effects

that

are

observed. Information

in

locations

to

which attention

is first

directed

(i.e.,

the first

locations

searched)

will

in

general

receive

faster

and

more accurate

processing

for the

obvious reasons.

8

This distinction

is

helpful

in

understanding

the

relation

of our

work

to

studies

of

attention

in

infrahuman

organisms:

the

traditional

studies

of at-

tention

in

discrimination

learning

and

blocking (e.g.

see

Mackintosh,

1975)

are

involved with those

limitations

that

occur

during

acquisition, while

a

number

of

newer studies

are

involved with limita-

tions

in

steady state situations when learning

is not

possible

(e.g.

see

Riley

and

Leith,

1976).

PERCEPTUAL LEARNING

AND

AUTOMATIC ATTENDING

159

9.

Retrieval

of

Information from Long-Term

Store

Both automatic

and

controlled processing

are

utilized

in

long-term retrieval.

In

gen-

eral,

an

automatic

associative

mechanism will

cause currently inactive

information

in LTS

to

become active when associatively related

information

is in

STS.

The

simplest example

is

the

perceptual encoding process

by

which

information concerning environmental inputs

is

located

in

LTS.

As

each feature

is

acti-

vated,

it can

serve

as a

base

for

further

acti-

vation

of

features

associatively related

to it

and to

other previously activated features.

This

same principle

applies

to

long-term

retrieval

of

higher order information.

It

should

be

noted well

that

information

once activated automatically

from

LTS

will

then

be in STS and may

have

to be

located

through

use of any of the

short-term retrieval

mechanisms discussed above.

How

does

the

subject exert control over

LTS

retrieval?

The

subject

can

utilize

re-

hearsal

and

selective processes

to

raise

the

strength

of

certain

information

in STS

above

the

strength

of

other

information.

Then

the

activated

and

retrieved

information

from

LTS

will tend

to be

information related

to

the

selectively accentuated subset,

In

Shiffrin's

(1970)

paper

the

details

of

the

controlled

LTS

search were presented

at

length.

In

summary,

the

controlled search

process

is a

series

of

cycles.

On

each cycle

(a) the

subject generates probe information

and

places

it in

STS;

(b) the

probe informa-

tion, along with

the

general contextual

infor-

mation

presently

in

STS, activates associated

information

from

LTS, called

the

search

set;

(c)

the

subject searches

the STS

search set;

(d)

the

subject decides whether

the

appro-

priate

information

has

been

found

and

whether

the

search

is

over.

The

process then

continues cycling.

Note

that

step

(c) is a

retrieval

from

STS,

so

that

one

phase

of

con-

trolled

LTS

retrieval

may be STS

retrieval.

10.

Long-Term Forgetting

The

forgetting

of

information

in LTS is,

by

definition

in the

present theory,

a

question

of

retrieval

failure.

The

retrieval

processes

discussed

in the

preceding sections

are by

their nature imprecise

and

fallible. When

retrieval

fails,

perhaps temporarily, then

we

say

forgetting

has

occurred.

The

causes

of

such

failure

are

somewhat

to the

side

of the

main

interests

of

this paper

but may be

sum-

marized

briefly

as

follows.

First,

the

probe

cues

used

to

activate related information

in

LTS may be

ineffective,

either

because

the

subject

chooses them incorrectly

or

because

the

general context

in STS at the

moment

is

dissimilar

to

that

stored with

the

desired

in-

formation

in

LTS. Second,

the

process

of

retrieval

itself

may

harm

additional

retrieval

attempts, especially

if the

probe cues

are

not

altered

from

one

cycle

of the

search

to

the

next. Third,

the

search

may

fail

due to

premature termination;

that

is, it may

fail

due

to a

decision

that

further

retrievals

are

not

worth

the

effort,

or due to the

reaching

of

some sort

of

time limit available

for

search. (See

Shiffrin,

1970, 1976,

for a

fuller

discussion

of

these matters.)

B.

The

Characteristics

of

Controlled

and

Automatic Processing

In

capsule

form,

we

have covered

the

major

phases

of the

information-processing system.

We

shall

now

attempt

to

define

and

out-

line

the

characteristics

of

automatic

and

con-

trolled processing

in a

more

precise

fashion.

1.

Controlled Processing

It is

important

to

note

that

not all

control

processes

are

available

to

conscious

percep-

tion,

and not all

control processes

can be

manipulated through verbal instruction.

It is

therefore

convenient

to

divide control pro-

cesses into

two

classes:

accessible

and

veiled.

Accessible

control

processes

are

those

like

rote rehearsal

or

alphabetic search

of LTS

that

can be

instituted

and

modified

by in-

struction.

These

are

generally slow processes

that

are

easily perceived

by the

subject.

Veiled

control

processes

are

those

like

the

serial comparison

of

items

in

short-term store

that

are

difficult

to

modify

through instruc-

tion.

They

are not

easy

to

perceive through

introspection because they

take

place

so

quickly.

Both classes

of

control processes have

the

160

RICHARD

M.

SHIFFRIN

AND

WALTER SCHNEIDER

following

general properties:

(a)

They

are

limited-capacity processes

requiring

attention.

Because

these limitations prevent multiple

control

processes

from

occurring simulta-

neously,

these processes

often

consist

of the

stringing

together

in

time

of a

series

of

singly

controlled unitary

operations,

(b) The

limitations

of

control

processes

are

based

on

those

of STS

(such

as the

limited-comparison

rate

and the

limited amount

of

information

that

can be

maintained without

loss),

(c)

Control

processes

can be

adopted

quickly,

without

extensive training,

and

modified

fairly

easily (though

not

always

by

verbal

instruction),

(d)

Control processes

can be

used

to

control

the flow of

information within

and

between levels,

and

between

STS and

LTS.

In

particular, they

can be

utilized

to

cause permanent learning (i.e.,

transfer

to

LTS)

both

of

automatic sequences

and of in-

formation

in

general,

(e)

Control processes

show

a

rapid development

of

asymptotic per-

formance.

For a

given control process,

if

automatic processing does

not

develop (due,

say,

to

varied-mapping procedures)

and if

the

constituent elements

of the

process

do

not

otherwise change

due to

long-term learn-

ing,

then performance level will stabilize very

quickly

at an

asymptotic value. When per-

formance

improves over trials,

it

does

so be-

cause

the

control process

is

changed,

or be-

cause automatic processing develops,

or be-

cause

the

constituent nodes

that

are

linked

by the

control process

are

themselves altered

by

long-term learning.

Common

examples

of

control processes

in-

clude

maintenance

or

rote rehearsal, coding

rehearsal, serial search, long-term memory

search,

and

decisions

and

strategies

of all

kinds.

These

will

be

discussed

in

more detail

in

the

sections below.

2.

Automatic

Processing

Automatic processes have

the

following

properties,

(a)

They

are not

hindered

by the

capacity limitations

of STS and do not re-

quire

attention.

Thus

automatic processes

often

appear

to act in

parallel with

one an-

other

and

sometimes

appear

to be

indepen-

dent

of

each

other,

(b)

Some automatic

processes

may be

initiated under subject con-

trol,

but

once initiated

all

automatic processes

run

to

completion automatically (though

some

indirect control

is

possible through

manipulation

of the

contents

of STS at the

time

of the

inciting

input),

(c)

They

require

considerable

training

to

develop

and are

most

difficult

to

modify,

once

learned,

(d)

Their

speed

and

automaticity

will

usually

keep

their constituent elements hidden

from

con-

scious

perception,

(e)

They

do not

directly

cause

new

learning

in LTS

(though they

can

indirectly

affect

learning through forced

al-

location

of

controlled

processing),

(f)

Per-

formance

levels

will

gradually improve over

trials

as the

automatic sequence

is

learned.

In

many

cases

asymptotic

performance

levels

may not be

reached

for

thousands

of

trials.

It is

particularly important

to

specify

care-

fully

what

we

mean when

we say

that

an

automatic process does

not

partake

of the

capacity limitations

of

STS.

To

make this

clear,

let us

suppose

that

X, Y, and Z are

nodes

that

are

automatically activated

in

turn

by

input

I in the

presence

of

general

context

nodes

C. We may

depict

the

sequence

as

follows:

C C

As

each

of X, Y, and Z is

activated,

it

enters

STS and its

future

residence

in STS

will

be

affected

by the

limitations

of

STS.

In

fact,

if

the

nodes

X, Y, and Z do not

include

an

attention-attracting response, then

it is

quite

conceivable

that

all

three

nodes will

decay

and be

lost

within

a few

hundred milliseconds,

and

the

subject

will

be

quite unaware

that

such

an

automatic sequence ever occurred.

Nevertheless,

the

sequence itself

is not

governed

by the

limitations

of STS in the

sense that

the

probability

of its

being

ac-

tivated

and the

rate

of its

occurrence

will

not

be

affected

by

other concurrent automatic

and

conrolled processes taking place

in STS

(at

least

if

context

C is

present

and the

other concurrent processes

do not

also utilize

nodes

X, Y, or

Z).

3. The

Development

oj

Automatic

Processing

The

tendency

for one

node

to

activate

another will

be

increased

if

both nodes

are

PERCEPTUAL LEARNING

AND

AUTOMATIC ATTENDING

161

present simultaneously

in STS and if a

con-

trol process

and

attention

are

directed toward

these nodes, thereby increasing their salience

in

STS.

Before

we can

describe

efficacious

training

conditions,

we

must distinguish between

two

types

of

automatic processes.

One

type

of

automatic sequence

may be

called

actional,

because

it

includes

phases

that

direct internal

processes (like calls

for

attention)

or

phases

that

produce overt responses (such

as

button

presses).

A

second type, called

informational,

contains

no

directions

for

actions.

The

dis-

tinction

is

crucial because

an

informational

sequence strengthened

on one

trial will

not

have deleterious consequences

for

perform-

ance

on

other types

of

trials.

On the

other

hand

an

actional sequence

may

give rise

to

a

response antagonistic

to a

response

re-

quired

on

another trial.

Thus,

to be

useful

in

a

given task, actional sequences require

special, consistent, training conditions.

To

make this point clear, suppose

that

node

B

produces

a

response antagonistic

to

that produced

by

node

C,

while nodes

D and

E

produce

no

responses.

If any of

A-B, A-C,

A-D,

or

A-E

is

trained alone, then

that

sequence

can be

learned.

If

training

on A-D

is

mixed

from

trial

to

trial with training

on

A-E, then

A

will come

to

elicit

both

D and E.

However,

if A-B

trials

are

mixed with

A-C

trials then learning

of

both

will

be

impossible,

since

A

cannot lead simultaneously

to two

antagonistic responses.

The

automatic

de-

tection

system discussed

at

length

in

this

paper

is

just

an

actional sequence, since

an

automatic-attention response

to one

stimulus

is

incompatible with

a

simultaneous atten-

tion

response

to

another stimulus; therefore

automatic detection requires consistent train-

ing

to

develop.

Thus,

in the

varied-mapping

conditions

of any of our

studies automatic

detection could

not

develop

and

controlled

processing

had to be

utilized.

4.

Combinations

of

Automatic

and

Controlled

Processing

Although

sensory inputs

are first

encoded

with

the

automatic processing system, with

the

results being made available

to

con-

trolled

processing,

it

must

not be

concluded

that

automatic processing invariably precedes

controlled

processing.

In

fact,

automatic

and

controlled processes

can

proceed

in

parallel

with

one

another

(as in

Experiment

4d

when

automatic processing

of the

elements

on the

invalid diagonal proceeded

in

parallel

with

controlled processing

of the

valid

diagonal).

Even more important, controlled processing

is

often

used

to

initiate automatic processing.

Particularly

in

complex processing situations,

(such

as

reading),

an

ongoing mixture

of

con-

trolled

and

automatic processing

is

utilized.

The

in the

serial, controlled

processing sequence

are

based

on the

output

of

automatic processes initiated earlier; then

new

automatic sequences

are

initiated

and

these

run to

completion

in

parallel with

the

ongoing

controlled processing.

5.

The

Benefits

of

Automatic

and

Controlled

Processing

A

system based

on the two

basic processing

modes

with

the

characteristics

we

have

de-

scribed

has

many advantages.

In

novel situa-

tions

or in

situations requiring moment-to-

moment

decisions, controlled processing

may

be

adopted

and

used

to

perform

accurately,

though slowly.

Then

as the

situations become

familiar,

always requiring

the

same sequence

of

processing operations, automatic processing

will

develop, attention demands

will

be

eased,

other controlled operations

can be

carried

out in

parallel with

the

automatic processing,

and

performance will improve. Some

of the

advantages

of

such

a

system

are (a) It

allows

the

organism

to

make

efficient

use of a

limited-capacity processing

system.

The de-

velopment

of

automatic processing allows

the

limited-capacity system

to be

cleared

and

devoted

to

other types

of

processing neces-

sary

for new

tasks,

(b) It

allows attention

to be

directed (through automatic-attention

responses)

to

important stimulation, what-

ever

the

nature

of the

ongoing controlled

processing,

(c) It

allows

the

organism

to

adjust

to

changes

in the

environment

that

make previously learned

activity

patterns

useless

or

harmful,

(d) It

allows

the

organism

to

deal with novel situations

for

which auto-

162

RICHARD

M.

SHIFFRIN

AND

WALTER SCHNEIDER

Long

term store

s

N

S

0

R

Y

I

N

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U

T

S

Short

term store

Level

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i

i~

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Level

Automatic

2

Encoding

v~

^f

s*

Automatic

attention

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4

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—

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omatic

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0

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E

P

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0

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C

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0

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T

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Figure

11.

A

model

for

automatic

and

controlled processing during tasks requiring detection

of

certain input stimuli. Short-term store

is the

activated subset

of

long-term store.

N

levels

of

auto-

matic encoding

are

shown,

the

activated nodes being depicted within each level.

The

dashed arrows

going

from

higher

to

lower levels indicate

the

possibility that higher level features

can

sometimes

influence

the

automatic

processing

of

lower level features.

The

solid arrow

from

a

node

in

Level

2

to the

attention system indicates that this node

has

produced

an

automatic-attention response,

and

the

large arrow

from

the

attention system

to

Level

2

indicates that

the

attention system

has

responded.

The

arrow

from

level

N to the

Response Production indicates

that

this node

has

called

for

an

automatic overt response, which will shortly

be

executed.

The

arrow

from

Controlled

Processing

to the

Response Production indicates

the

normal mode

of

responding

in

which

the

response

is

based

on

controlled comparisons

and

decisions. Were

it not for the

automatic responses

indicated, detection would have proceeded

in a

serial, controlled search

of

nodes

and

levels

in an

order chosen

by the

subject.

matic

sequences have

not

previously been

learned,

(e) It

allows

the

organism

to

learn

increasingly complex modes

of

processing

by

building

upon automatically learned sub-

systems.

C.

A

Framework

jor

Processing

in

Detection,

Search,

and

Attention

Tasks

The

framework

we

have

in

mind

is

built

within

the

general theory already presented.

It is

illustrated

in

Figures

11

and

12.

When

a

set of

inputs

is

presented (let

us

suppose

for

convenience

that

the

inputs

are

visual)

then each begins

to

undergo automatic

processing.

The

system automatically encodes

each stimulus input

in a

series

of

stages

and

activates

a

series

of

features

in the

process.

For

example,

the

letter

"M" may first be

encoded

in

features indicating contrast,

color,

and

position; then curvature, con-

vexity,

and

angles; then

a

visual letter

code

and a

verbal,

acoustic-articulatory

code,

then

the

codes

"letter,"

"consonant,"

"capital;"

and finally,

perhaps,

semantic

and

conceptual codes like "followed

by

'N',"

"middle

of the

alphabet,"

and the

like.

(We

do

not

necessarily

imply

that

these

features

are

correct

or

exhaustive;

if,

say, amplitude

components

of the

spatial-frequency analysis

of

the

inputs prove

to be

relevant

features

encoded

by the

system,

the

theory

we de-

scribe

would

be

unchanged

in all

important

respects.) What features

will

become

ac-

tivated depends

on the

physical nature

of the

nervous

system

that

was

predetermined gen-

PERCEPTUAL

LEARNING

AND

AUTOMATIC

ATTENDING

163

etically,

the

degree

and

type

of

prior

learning,

the

physical characteristics

of the

display

(like

duration

and

contrast),

and the

general

context, both

that

in the

environment

and

that generated

in STS by the

subject.

To the

extent

that

the

subject directs

the

sensory

receptor orientation

and to the

extent

that

internally generated information

can

alter

the

context

in

STS,

the

subject will have

at

least

some

indirect

control

over

automatic

sensory

coding.

The

automatic

processing

as

described

above

takes

place

in

parallel

for

each

of the

input stimuli.

The

processing

of

each stimulus

is

often

independent, except

for

lateral

and

temporal interactions

at

early stages, called

masking,

and

except

for

learned relationships

between

items

that

may

affect

processing

at

later

stages

(if

adjacent

letters

form

a

word,

for

example).

The

various features

that

are

activated

are all

placed

thereby

in STS

where

they reside

for a

short period

before

being

lost

(i.e.,

before

returning

to an in-

active

state

in

LTS).

We

propose

that

some

of the

features

or

nodes

that

are

automatically

activated

may

initiate

a

response

that

will direct subsequent

processing

or

subsequent

actions.

For ex-

ample,

an

attention response might

be ac-

tivated

by a

feature;

the

attention response

might direct controlled processing

to the

cor-

responding

set of

features representing

that

input stimulus,

so

long

as

other

competing

attention responses

do not

occur simulta-

neously.

As

another

example,

an

overt

re-

sponse might

be

engendered

by a

particular

stimulus

(such

as a

startle

response

to a

sudden loud noise,

a

galvanic skin response

to

an

aversively conditioned word,

a

ducking

response

to a

missile thrown

at the

head).

If

the set of

inputs contains

a

target stimulus

that

gives rise

to a

relevant

nonconflicting

attention response,

or to an

overt response,

then

we say

that

automatic

detection

is

operating. Note

that

the

attention response

could

be

attached

to

features

at any

level

of

processing

and to

more than

one

feature

at a

time.

In

Figure

12, as an

example,

at-

tention

responses

are

attached both

to the

feature

"8" and to the

feature "number."

Inputs

^\

IV

h"\S

I

Visual

featuresVisual

character

code

category

code

representing

a set of

letters

is

often

compared

in

preference

to

(and prior

to)

individual

letter codes,

as

shown

in

Experi-

ment

3.

Furthermore,

the

order

of

search

and the

placement

of

decisions within

the

search

are

also controlled

in an

attempt

to

increase

efficiency.

To

give

an

example, com-

parisons

in our

studies

in

Part

I

took place

in

an

order

that cycled through

the

frame

for

a

given memory-set item

before

switching

to a new

memory-set item,

and a

matching

decision

was

made

after

every comparison.

To

give another example, matching decisions

in

many memory search studies

(M

varying,

F

—

1)

are

withheld until

all

comparisons

are

completed (Sternberg,

1975).

Note

finally

that

many attention tasks

utilize

search

or

detection paradigms. When-

ever

this

is the

case,

the

framework

described

here applies equally

to

attention

tasks.

Divided-attention

tasks

study

the

increments

in

performance

that

may

occur when

the

load

is

decreased. Decreased loads

are

usually

specified

through advance instructions

that

certain inputs

are

irrelevant, thereby

de-

creasing

the

size

of the

memory set,

the

frame

set,

or

both.

According

to our

framework,

experiments

that

do not

show dividing attention

to re-

duce

performance

fall

into

two

classes.

One

class includes those studies

in

which auto-

matic detection

is

operating. These

are

usually

studies

utilizing

a CM

paradigm

and

high

degrees

of

practice. Divided-attention deficits

will

not be

seen because

the

target

stimulus

will

be

detected automatically,

in

parallel

with

the

other stimuli,

and

often

indepen-

dently

of

other stimuli.

An

exception

to

this

general

rule

may

apply when

two (or

more)

targets

are

presented simultaneously

on a

trial.

Even

if

both targets generate attention

responses, there

may be a

difficulty

in

dis-

criminating

a

double

from

a

single occurrence.

In

such

an

event,

the

controlled comparison

system

may

have

to be

called into

play

to

count

the

targets.

(A

detection decrement

may

then occur, because

the

second item

may

have decayed

from

STS by the

time

the

comparison

of the first

item

is

complete;

see

Moray,

1975,

Shiffrin,

1976,

and the

discussion

of the 0

spacing

effect

in the CM

condition

of

Experiment

3,

Part

I.)

The

second

class

of

studies

in

which

di-

vided-attention

deficits

do not

occur

is

that

in

which controlled search

is

utilized

but the

capacity

of STS is not

stressed. Examples

are

seen

in the

series

of

studies

by

Shiffrin

and his

colleagues, summarized

in

Shiffrin's

(1975a)

article.

In

such studies either

the

load

in STS is

kept low,

or a cue

informing

the

subject

which input

is

relevant appears

at

about

the

same time

as the

inputs.

It is,

however,

only

in

specially

designed

situations that capacity limits

are not

stressed.

In

most studies requiring controlled search,

the

extra time required

to

search

a

larger

number

of

relevant inputs will impair per-

formance,

whether measured

by

reaction

time

or

accuracy. This

was the

case

in the

PERCEPTUAL

LEARNING

AND

AUTOMATIC ATTENDING

165

VM

conditions

of the

experiments reported

in

this paper,

and in

Part

I: In all

these

cases increases

in

load reduced performance.

There

are two

basic reasons

for the

perform-

ance

reduction

in

controlled search studies.

First,

some

of the

features

in STS may

decay

and

revert

to LTS

before

the

comparison

process reaches them. Second,

new

inputs

may

arrive

and

require processing,

forcing

the

comparison process

to

switch away

from

the

previous inputs.

Probably

only

this

second

factor

operated

in the

studies

we

have

re-

ported

in

this paper.

For

either

of

these

reasons, divided-attention

deficits

can be ex-

pected

in

detection tasks requiring controlled

search.

The

situation

is

quite

different,

however,

in

focused-attention studies.

In

these studies,

certain inputs

are

known

to be

relevant,

and

others

are to be

ignored.

If

controlled search

is

being utilized, there

is

little reason

to ex-

pect

that

any

substantial

deficit

will

be

caused

by the

presence

of

to-be-ignored stim-

uli,

at

least

if it is

clear

to the

subject well

in

advance which stimuli

and

locations

are

relevant

and if

there

are no

location con-

fusions.

In

such cases

the

subjects should

direct

the

search order

so

that

the

relevant

locations

are

searched

first;

thus

perform-

ance deficits should

not

arise.

Evidence sup-

porting these propositions

is

found

in

Experi-

ment

4a:

Subjects were able

to

search

one

diagonal

and

ignore

the

other.

The

tasks

in

which large

deficits

in

focus-

ing

attention will occur

are

those

in

which

irrelevant items give rise

to

attention

re-

sponses during automatic encoding.

In

such

cases, attention will

be

attracted

to the to-

be-ignored

item

and a

loss

of

time will occur

before

the

controlled search

can be

redirected

to the

relevant inputs.

The

time lost will

impair

performance. Such focused-attention

deficits

were seen

in the

reversal results

of

Experiments

1 and 2, and in the

attention

results

of

Experiment

4.

Thus,

our

framework

can be

applied

to a

wide

variety

of

search, detection,

and at-

tention

tasks, although additional assump-

tions

must

be

made

to

generate

precise

models

to

deal with

the

particulars

of

each task.

In

Part

I we

presented

a

quantitative serial,

terminating

search model

and

discussed

some

alternative models.

Our

discussion

was

limited,

however,

to our

basic

single

or

multiple-frame

search task with small values

of

M and

F.

We

will

now

consider

a few

alternative paradigms, along with special

assumptions they might require.

1.

Tasks Utilizing Large Memory Sets

Suppose

there

are too

many items

in the

memory

set to be

maintained

in

STS.

Of

course, then,

the

memory

set

must

be

learned

in

LTS in

advance

of the

test.

There

are

then

two

basic search modes.

In the first,

the

test item

is

automatically encoded

and

accesses

a

node

in

memory

that

contains

the

desired

information.

For

example,

in

deciding

whether

an

item

is any

word,

the

input item,

if

a

word,

is

encoded

to the

nodes represent-

ing

the

word

and the

information

in

those

nodes

is

usually

sufficient

to

classify

the

item

as a

word;

on the

other hand,

a

non-

word

obeying appropriate orthographic con-

straints

is

encoded

to a

lesser degree

and the

failure

of the

automatic

encoding

process

could

itself

serve

as a cue for

"nonwordness."

The

second type

of

search mode would con-

sist

of

entering successive parts

of the

mem-

ory set

from

LTS

into STS, using controlled

search

to

examine

each

subset

in

STS.

For

example,

if

asked whether there

is a flower,

country,

or first

name whose

fourth

letter

is

"u"

a

subject might successively generate

members

of

each category

and

serially check

them.

The

above comments make

it

clear

that

the

case

of

large memory sets

is not

different

in

principle

from

the

cases

in

which

the

memory

set may be

held

in

STS,

though

the

models

may

need additional assump-

tions.

For

example, Atkinson

and

Juola

(1974)

carried

out a

study

in

which sub-

jects

had a

large memorized

set in

LTS.

They

proposed

a

hybrid

model

in

which

a

judgment

based

on

familiarity enabled

the

subject

to

decide

on

some trials without

a

search

that

the

test item

was

definitely

in,

or

definitely

not in, the

memorized set.

On

trials

when

this

initial familiarity judgment

was

ambiguous, then

a

controlled search

through

the set was

made.

166

RICHARD

M.

SHIFFRIN

AND

WALTER SCHNEIDER

2.

Large Display Sets

When large numbers

of

items

appear

in the

display, then

it may

turn

out

that

acuity

varies considerably across

the

display

for a

given

fixation

point.

In

turn, acuity changes

are

likely

to

lead

the

subject

to

adopt

a

strategy

in

which

eye

movements

are

used

to

bring subsets

of the

display successively

into

a

high-acuity region.

The

location

of

each

new fixation can be

governed

by a

controlled

search

strategy

or by an

automatic

process,

but in

either event

the

necessity

of

obtaining good acuity will

force

this process

to be

serial across successive

eye

movements.

Within

each

fixation,

furthermore, either

automatic detection

or

controlled search could

be

utilized.

The

search studies

in

which sub-

jects scan rows

of

characters

for

targets

have

shown

both modes

of

search.

For

example,

the

Neisser

(1963)

results, reviewed

in

Part

I,

showed

that

automatic detection developed

for

subjects well trained

in

responding

to

letter

sets

presented

in CM

fashion

(memory-

set

size

had no

effect),

while controlled search

was

utilized

for

sets

that

had

been given

only small amounts

of

training.

An

interest-

ing

intermediate case occurred when

the

sub-

ject

was

instructed

to

locate

a row of

char-

acters

that

did not

contain

a

given character.

In

this

case,

even with

CM

training,

the

task

proved quite

difficult.

In our

view

the

sub-

ject would have

to

adopt

a

serial process

from

row to row

(rather than

from

fixation

to fixation).

Within each

row

automatic

de-

tection might

be

used

to

locate

the key

character,

but

then

a

decision would have

to be

made

before

the

could

be

considered.

3.

Categorical Partitioning

oj

Display Sets

Partitioning

of the

display

set has

usually

been accomplished

by a

categorization

de-

pendent

on a

relatively gross simple physical

feature,

such

as

color, shape,

or

size. When

displays

are

segregated into

two or

more

groups

by

such features, processing

may be

affected

in two

ways.

First,

the

patterning

of

the

input

can

govern

the

nature

of

auto-

matic

processing—controlled

processing

may

be

directed automatically

to a

subset

of the

inputs (assuming

that

one

particular subset

is

consistently

relevant).

Second,

the

per-

ceptual categorization could

influence

the

order

and

perhaps

the

nature

of

controlled

search.

To

give

one

simple example,

a

dis-

play arranged

in two

separate rows will tend

to

be

processed

one row at a

time,

in

reading

order.

A

second example occurs

in

situations

where

controlled processing

can

enable

one

to

more quickly decide about

the

category

of

the

input than about

the

memory-set

membership

of the

input.

In

these cases

a

two-phase controlled search might

be

adopted,

with

the first

phase locating

the

relevant

inputs

by

category,

and the

second phase

matching these inputs

to the

memory set.

This

is

illustrated

by

Green

and

Anderson's

(1956)

and

Smith's

(1962)

studies

in

which

a

two-digit number

of a

particular color

had

to be

found

in a

display

of

many two-digit

numbers

of

differing

colors.

Automatic processing based

on

perceptual

categorization

may

have played

an

important

role

in the

studies

of

search

and

detection

reported

in

this paper.

We

have assumed

throughout

that

only

the

display positions

with

characters,

and not

those with masks,

are

considered

in the

search.

How is

search

restricted

to

character positions?

It is

con-

ceivable that

a

preliminary controlled search

is

used

to

identify

character positions,

but

the

results

of

Experiment

4a

argue against

such

a

view—knowing

the

relevant diagonal

of

a

four-character

frame

leads

to

perform-

ance identical

to

that

seen when

two

masks

and two

characters appear randomly

on

each

frame.

Thus,

a

preliminary controlled search

would

have

to be

extremely

fast

relative

to

the

time

for

each character comparison. More

likely,

an

automatic process develops

that

directs

the

controlled search away

from

mask

positions

and

toward character positions.

Since

such

a

response would

be

consistently

trained

and

reinforced,

it

should

be

learned

in

a

fashion similar

to

that

for

automatic-

attention responses.

It

should

be

noted

that

the

development

of

automatic responses

to

direct controlled

search

is

very similar

to the

process termed

by

Neisser

(1967)

as

"pre-attentive."

Neisser

was

trying

to

explain

how

search could

be

PERCEPTUAL LEARNING

AND

AUTOMATIC ATTENDING

167

directed

to a

perceptually segregated subset

of

the

inputs.

We are

suggesting

that

an

automatic process might develop

and

direct

the

search

in

situations where

the

search-

directing response

is

consistently trained

(as

is

usually

true

in

such

studies).

We do not

feel,

however,

that

the

segregation

of the

relevant inputs must

be

based

on

simple

physical

features.

With

enough

consistent

training,

an

automatic search-directing

re-

sponse could develop

for a set of

stimuli

defined

by

quite complex features.

For ex-

ample, Gould

and Cam

(1973)

reported

results suggesting

that

an

automatic process

was

directing

search

to the

locations

of

items

from

a set of 10

potentially relevant letters

and

away

from

the

locations

of

items

from

a

set of 8

other

letters

that

never included

a

target. (Any target

was

always drawn

from

the

potentially relevant

set of 10

letters,

but

on

most

trials

distractors

were chosen

from

this

set of 10 as

well

as

from

the set of

8).

Although

the

evidence

is not yet

available,

we

raise

the

possibility

that

the

converse

of

the

argument

in the

preceding paragraph

might also hold: Even with perceptual seg-

regation

of the

display

into categories deter-

mined

by

simple physical

features,

auto-

matic restriction

of the

search

to the

relevant

category might

not be

possible unless

the

relevant category

is

consistent across trials.

4.

Attention

Tasks

The

models applying

in

attention studies

that

utilize

detection

or

search

paradigms

are

just those discussed

in the

preceding

sections.

The

general

rule

is

that

instructional

manipulations

affect

the

order

of

controlled

search; increases

in

load cause

the

time

needed

for

controlled search

to

increase;

and

consistent

training

leads

to the

development

of

automatic responses

that

allow attentional

limitations

to be

bypassed.

We

will

say a few

words, however, con-

cerning

attention studies that

do not

utilize

detection

or

search paradigms.

One

class

of

studies

utilizes

a

memory paradigm.

The

inputs

are

manipulated

in

ways similar

to

those used

in

detection studies,

but the

sub-

ject

is

asked

to

recall

or

recognize

the

items

at

some time

after

presentation.

One

example

is

the

"split-span"

technique

reviewed

by

Broadbent

(19S8, 1971). Other examples

are

reported

by

Sperling (1960)

and Von

Wright

(1970),

who

studied cued partial

report following

tachistoscopic

exposure

of

character displays.

In

these memory paradigms, essentially

the

same underlying mechanisms

apply

as

in

the

detection paradigms, though memory

storage rather than detection

is the

processing

goal. When

controlled

processing

is

utilized,

the

subject

has

considerable control over

storage:

The

items

that

are

rehearsed

or

coded

are the

items

that

will

be

recalled.

If

an

input

is

presented

that

generates

an

automatic-attention response, then this

in-

put

will receive

attention

and

tend

to be

recalled

regardless

of the

nature

of the

con-

trolled process utilized

to

store

the

other

items.

An

excellent

demonstration

of

these

points

may be

found

in

Kahneman

(197S).

5.

Threshold

Detection

Tasks

An

input

in a

threshold

detection

task,

by

definition,

is

presented

in

such

a way

that

automatic encoding

on

most

trials

will

be

incomplete

and

therefore ambiguous.

That

is,

in

Section IV.A.4

we

discussed

the

fact

the

input stimulation must

be

above some thresh-

old

level

for

automatic encoding

to run to

completion

in an

accurate

fashion.

In

Figure

12,

for

example,

the

"M,"

if

presented

near

threshold, might cause activation

of

some

of

the

features

at the

visual

feature

level,

but

no

features

at

higher

levels.

This

set of

partial features

will

in

general

be

ambiguous

—several

letters

and

numbers might

be

con-

sistent

with

the

activated

feature set.

Thus,

a

target will

on

some trials give rise

to

feature

sets consistent with either targets

or

distrac-

tors.

Similarly,

distractors

will

on

some

trials

give

rise

to

feature

sets consistent with either

targets

or

distractors. Under these conditions

it is

clear

even

in CM

situations

that

auto-

matic-attention

responses

and

automatic

de-

tection

can

only develop very slowly,

if at

all,

because

the

internal

representations

of

targets

and

distractors will

be

mapped con-

sistently

to

responses only

on

those

few

trials

when

the

encoding

happens

to be

complete.

168

RICHARD

M.

SHIFFRIN

AND

WALTER SCHNEIDER

A

similar argument applies

if

encoding

is in-

accurate

rather

than

incomplete.

Even

in CM

threshold

tasks,

therefore,

the

subject

will

be

forced

to

adopt controlled

search

on

most

of the

trials,

namely

the

trials

on

which encoding

is

incomplete.

On

such

trials

a

serial comparison process

will

be

necessary

to

match

the

activated features

against

the

features

of the

members

of the

memory

set. Occasionally, however, auto-

matic encoding will manage

to

process

the

target completely. Suppose

that

almost

al-

ways, those stimuli

that

are

completely

processed

will

be

encoded correctly. Suppose

also

that

a CM

procedure

is

being utilized

in

the

task.

In

these

special

conditions,

an at-

tention response

can be

learned

that

might

be

utilized

on

those trials when complete

encoding

of the

target

happens

to

occur.

A

model very similar

to

this

was

used

by

Shiffrin

and

Geisler

(1973)

to fit the

results

from

a

threshold detection study

by

Estes

(1972).

In

that model, stimuli automatically

processed

to a final,

incomplete result were

called "component

detections"

and

stimuli

automatically processed

to the

complete

(letter)

level were called

"letter

recogni-

tions."

The

model proposed

a

two-part con-

trolled

search

in

which

the

letter recognitions

were

searched

first (in

parallel through mem-

ory,

but

serially through

the

display),

and

then

the

component detections were matched

serially,

feature

by

feature, against

the

mem-

bers

of the

memory set.

In

light

of the

present work,

we

would like

to

propose

for

consideration

an

alternative

but

similar

model

in

which

the

letter recognitions result

in

an

automatic-attention response,

so

that

controlled

search

need

be

utilized only

if the

target

is not

among

the

letter recognitions.

In

practice,

the

predictions

of

these

two

models would

not

differ

greatly.

In

summary,

it

seems clear that controlled

search, whether

at the

feature

or

character

level,

is

bound

to be the

predominant

de-

tection

mechanism

in all

threshold detection

tasks,

but

there

is a

possibility

in CM

para-

digms

that automatic detection

can be

util-

ized

on a

subset

of the

trials when

the

target

happens

to be

encoded relatively

completely.

Our

general view

of

processing,

in

threshold

detection tasks

as

well

as

many others,

can

be

summarized briefly

in the

following man-

ner: Sensory inputs

are

encoded auto-

matically, resulting

in

states

of

evidence

(consisting

of

feature

sets)

that

the

subject

utilizes

in

subsequent controlled processing.

While

generally accurate, this view

is too

simple

in

several respects.

First,

it

must

not

be

assumed

that

there

is

ever

one

moment

in

time

at

which

all

activated features

are

simultaneously present

and

available

to the

subject

for

controlled processing. Rather

it

will

usually

be the

case

that

some features

will

still

be

undergoing

the

process

of en-

coding

(and hence

will

not yet be

activated)

while

other features have already been acti-

vated

and are in the

process

of

being for-

gotten. Second,

it

must

not be

assumed

that

controlled processing will follow

automatic

processing

in

time. Such

an

assumption

is a

fairly

accurate simplification when used

in

models

for

certain

tasks

including

threshold

detection. However,

it is an

inherent feature

of

our

theory

that

automatic

and

controlled

processing

can

often

operate

in

parallel,

so

that

controlled processing

can

begin while

automatic processing

is

still progressing.

This

point becomes crucial

in

situations

in

which

the

subject

is

required

to

give extremely fast

responses (including those paradigms pre-

senting

above-threshold stimuli), since

a

very

fast

response might have

to be

based

on

the

features available

at a

certain point

in

time, even though better features might

be

available

at a

later point

in

time.

D.

Automatic

and

Controlled Processing

in

Memory Storage

and

Retrieval

In

this section

we

shall review

briefly

how

automatic

and

controlled processing might

be

involved

in

short-term retention, learning,

and in

long-term retrieval.

1.

Maintenance

of

Information

in

Active

Memory

We

suggest

that

the

control process most

evident

to

introspection

is

rehearsal. Atkinson

and

Shiffrin

(1968) studied many tasks

in

which

subjects

utilized

a

continually updated

rehearsal "buffer"

to aid

their memory sys-

PERCEPTUAL

LEARNING

AND

AUTOMATIC

ATTENDING

169

tern.

Rote rehearsal

is of

course only

one of

many control processes

that

cause items

to

have

an

extended residence

in

STS; coding,

deciding, retrieving,

and the

like also cause

a

categories

in the VM

condition).

Evidence

of a

rather

different

sort

is

found

in

reading

tasks.

If

automatic processing does

not

lead

to

retention,

then

it

might

be ex-

pected

that

a

skilled reader

who

automatically

processes

surface-structure features

and who

gives

controlled processing

to

conceptual

properties

of a

passage

would

retain

little

information

regarding

the

surface-structure

170

RICHARD

M.

SHIFFRIN

AND

WALTER

SCHNEIDER

details. Bransford

and

Franks

(1971)

have

collected

data

that

may be

interpreted

in

this fashion.

Of

course,

if

controlled process-

ing

is

directed toward levels

of

analysis

normally carried

out

automatically, then

the

features

attended

to

will

be

remembered (see

Postman

&

Senders,

1946).

To

summarize, whether

or not

some

nominal

storage manages

to be

eked

out in

the

absence

of

controlled

or

attentive process-

ing,

it

seems clear

that

any

phenomenon

that

would

be

appropriately called

"automatic

storage"

is a far

less important determinant

of

LTS

learning than controlled processing.

Before

leaving

the

general topic

of

learn-

ing

it is

interesting

to

speculate

on the de-

velopment

of

complex information-processing

skills.

Since controlled processing

is

limited,

only

a

small part

of the

memory system

can

be

modified

at any one

time.

After

invariant

relations

are

learned

at one

stage,

the

pro-

cessing becomes automatic

and

controlled

processing

can be

allocated

to

higher levels

of

processing.

For

example,

the

child learning

to

read

would

first

give control processing

and

then

give

automatic processing

to

various units

of

information,

The

sequence

of

automatically

learned units might

be

foreground-back-

ground,

features, shapes,

letters,,

words,

and

meanings

of

phrases

or

sentences.

The

child

would

be

utilizing controlled processing

to

lay

down

"stepping

stones"

of

automatic

processing

as he

moves

on to

more

and

more

difficult

levels

of

learning.

The

transition

from

controlled

to

automatic processing

at

each stage would result

in

reduced discrimina-

tion

time, more attention

to

higher order

features,

and

ignoring

of

irrelevant

infor-

mation.

Gibson (1969, chap.

20)

describes

these

effects

to be

three

of the

major trends

in

perceptual

development.

In

short,

the

staged development

of

skilled automatic per-

formance

can be

interpreted

as a

sequence

of

transitions

from

controlled

to

automatic

processing.

3.

Retrieval from

LTS

Retrieval

from

LTS has a

large automatic

component. Sensory

inputs

result

in an

auto-

matic series

of

stages

of

encoding

that

ac-

tivate many features (and perhaps responses)

and

place them

in

STS. Internally generated

inputs

also

tend automatically

to

activate

associated information

in LTS and to

place

it in

STS.

In

general,

the two

primary controlled

phases

of LTS

retrieval consist

of the

pro-

cesses

the

subject uses

to

search

and

process

the

information

in STS

that

has

just been

activated,

and the

processes used

to

alter

the

probe information

from

step

to

step

of the

LTS

search.

It is

important

to

note

that

the

selection

of

probe information

is not

entirely under

subject

control.

In

fact,

the

probe

informa-

tion includes

the

general

contextual

informa-

tion

present

in STS at the

time

of

retrieval,

in

addition

to the

specific

cues

the

subject

manipulates

to

facilitate retrieval.

The

gen-

eral context

is

only

partly

under subject con-

trol,

since much

of it is

environmentally

de-

termined

and

even

the

internally generated

context (e.g., what

the

subject

is

currently

"thinking

about")

may be

difficult

to

alter

radically. Thus, changes

in

probe cues will

be

under subject control

to

only

a

degree,

and

this

fact

is one of the

factors underlying

retrieval

failure.

This

extremely brief

and

superficial over-

view

should

not be

allowed

to

give

the

reader

an

impression

that

distinguishing

the

auto-

matic

and

controlled phases

of

retrieval

is

generally

a

simple

matter.

Furthermore,

the

controlled

phase

can be a

most complex

and

many-faceted

process.

To

give just

one ex-

ample,

Anderson

and

Bower

(1973)

consider

how

subjects compare test sentences with

stored

sentences

in

long-term memory.

In

our

model, there

are two

phases

to

this

ex-

periment:

(a) a

retrieval

of the

appropriate

informational

nexus

from

long-term memory

through

the use of

probe information (in-

cluding

the

test question)

and (b) a

com-

parison

in

short-term memory

of the

test

question

and the

retrieved search set.

The

Anderson

and

Bower model,

in the

present

view,

is

primarily

a

model

of the

second

of

these

processes—the

comparison within

short-term memory

of the

test sentence

and

the

retrieved information.

See

Shiffrin's

(1970,

1975b, 1976) studies

for a

more

PERCEPTUAL LEARNING

AND

AUTOMATIC ATTENDING

171

elaborate

discussion

of

long-term

retrieval

processes.

V.

Models

of

Search

and

Detection

In

this

section

the

theory

we

have

pro-

posed will

be

compared with some

of the

previous models

that

have been proposed

for

detection

and

search

tasks.

A.

The

Sternberg

Model:

Serial, Exhaustive

Search

The

serial, exhaustive search model

is

pre-

sented

in

Sternberg (1966). Extensions,

further

evidence,

and

reviews

of the

litera-

ture

are

given

in

Sternberg (1969a, 1969b,

197S).

This

model

is

meant

to

apply

to

memory

search tasks

(F —

1,

M

varies)

with

small memory-set sizes.

It has

been

confirmed

impressively

often

but is

limited

in

scope,

as it is

meant

to

apply only

to a

small range

of

paradigms.

In our

present

theory, serial, exhaustive search

is

considered

to be one of the

controlled

search

strategies,

one

that

is

very commonly adopted.

The

factors

that

lead subjects

in our

situ-

ation

to

adopt terminating, controlled search

remain uncertain

at

present. Possibly

the

much

larger

search

loads

in our

study

led to

a

terminating strategy.

One

other minor

dis-

crepancy

in

results

involves

the

Sternberg

(1966)

finding

apparently showing

fixed

sets

(CM)

and

varied sets

(VM)

to

give equiva-

lent set-size

functions.

In

retrospect

we can

see

that

Sternberg's subjects

in the fixed set

procedure were given

far too

little

training,

and the fixed

sets

were

varied

too

often

for

automatic detection

to

have developed.

1.

The

Relation

Between

Sternberg's Model

and

Our

Framework

Reaction time

was

proposed

by

Sternberg

(1969a,

1969b)

to be the sum of

motor

re-

sponse time

and the

times

for

four

additive

stages:

(a)

encoding

(affected

by

stimulus

legibility),

(b)

serial comparison

(affected

by

size

of the

memory

set),

(c)

binary

de-

cision

(affected

by

whether

a

positive

or

negative

trial

has

occurred),

(d)

translation

and

response organization

(affected

by

rela-

tive

frequency

of

positive

and

negative

trials).

In

Figure

11,

in

which

our

more

general

framework

is

depicted, these

stages

proposed

by

Sternberg

may be

placed

as

follows:

"Encoding"

is

equivalent

to

auto-

matic encoding;

"serial

comparison

and bi-

nary decision" both

are

part

of

controlled

processing;

"response

organization

and mo-

tor

response execution"

are

part

of

response

production.

In

conclusion, then,

the

Stern-

berg model

differs

from

the

detailed quan-

titative model

we fit to our

data

in

Part

I,

but

nevertheless

may be

viewed

as a

special

case

of our

general framework.

2.

Problems

for the

Serial, Exhaustive

Comparison

Model

and

Their

Resolution

The

serial, exhaustive model

is

particu-

larly

important

on

account

of the

research

it

has

generated

that

give results

not

consistent

with

the

theory

in its

simplest

form.

These

inconsistencies have

led to

many

new

models,

some

of

which will

be

discussed below.

The

apparent

inconsistencies

include

the

follow-

ing

results.

1.

Reaction times depend

on the

serial

presentation position

of the

tested item

within

the

memory

set (in VM

procedures

with

memory sets changing every trial).

The

most pronounced

effects

occur when

the

memory-set items

are

presented quickly

and

the

display item

is

presented very soon

after

the

last

memory-set items (Burrows

&

Okada,

1971;

Clifton

&

Birenbaum,

1970;

Corballis,

1967;

Klatzky,

Juola,

&

Atkin-

son,

1971;

Klatzky

&

Smith,

1972).

2.

Reaction times depend

on the

relative

frequency

of

presentation

of

items within

the

memory

set in CM

procedures

(see Bie-

derman

&

Stacy;

Krueger,

1970;

Miller

&

Pachella,

1973;

Shiffrin

&

Schneider,

1974;

Theios

et

al.,

1973).

3.

Reaction times

can be

speeded

for

cued

items

in VM

paradigms (Klatzky

&

Smith,

1972)

or

speeded

for

expected items

in CM

paradigms

(Shiffrin

&

Schneider,

1974;

but

note

that

the fixed

sets

changed

every

1,60

trials

so

that

only

low

degrees

of

practice

were

involved),

or

speeded

in a VM

para-

digm

for an

item repeated during

the

pre-

172

RICHARD

M.

SHIFFRIN

AND

WALTER SCHNEIDER

sentation

of the

memory

set

(Baddeley

&

Ecob,

1973).

4. The

outcomes

in CM

paradigms

often

differ

in

fundamental ways

from

those

in

VM

paradigms,

especially when some simple

physical

basis

separates

the

memory

and

dis-

tractor

sets,

or

when

the

degree

of

training

is

high. Many such

findings

have been dis-

cussed extensively

in

earlier sections

of

this

paper

and

will

not be

reviewed again here.

5.

Subjects typically give incorrect

re-

sponses

on

1-10%

of the

trials, depending

upon

the

condition.

The

serial search models

do

not

generally posit explicit mechanisms

to

predict errors.

Before

turning

to

alternative models,

it is

useful

to

consider

how

these phenomena

are

dealt with

in the

framework

of our

theory,

and

also

to see how

Sternberg explains

the

results.

The

various

findings in CM

paradigms

are

easiest

to

explain: Automatic detection

de-

velops

that

enables

the

serial search

to be

bypassed. Much

of the

research

in

this

paper

was

directed toward establishing this fact.

Sternberg

(1975)

is

less

specific

but

also

sug-

gests

that

some alternative, more

efficient,

search process

is

used

in

such situations.

Within varied-mapping paradigms,

re-

course

to the

hypothesis

of

automatic detec-

tion cannot

be

used

to

explain

the

results.

It

would

be

parsimonious

if

each

of the

above

findings

(1)

to

(3)

proved

to be the

result

of a

common mechanism.

Shiffrin

and

Schneider

(1974)

proposed

one

possible mech-

anism—namely,

that

when

information

con-

cerning

test

probabilities

is

available

to the

subject, then

one

item

is

placed

in a

special

state prior

to

each

test

display (called

a

state

of

"expectancy"),

and

that

a

test

of

the

expected item results

in a

faster

response

time than

tests

of

nonexpected items. Stimu-

lus

probability, serial position, cueing, stim-

ulus repetition,

or

differential

importance

could

all be

expected

to

determine

the

prob-

ability with which stimuli will

be

expected.

The

effects

of

expectancy could possibly

act at

several

different

stages

en

route

to the

execution

of the

response.

One

possibility,

also mentioned

by

Sternberg

(1975),

is

that

the

comparison process

is

carried

out in a

speeded

fashion

for an

expected item.

An-

other possibility

is

that

the

encoding process

or

the

response production stage

is

speeded

when

an

expected item

is

tested.

Shiffrin

and

Schneider

(1974)

attempted

to

carry

out a

test discriminating among

the

possible mod-

els. While

the

general notion

of

expectancy

was

supported

by the

results,

the

study

was

not

conclusive

in

determining which version

of

the

model

was to be

preferred.

The

important point

to be

emphasized

is

that

we

(and Sternberg also) suggest

that

findings

(1)

to (3)

listed above

are not in-

compatible with

a

controlled search process

that

is

serial

and

exhaustive.

We

suggest these

findings can be

explained

by

factors

that

af-

fect

other stages

of the

response process

than

the

comparison stage

or

perhaps

by a

factor

that

affects

the

comparison process only

on

certain trials. Many other researchers have

preferred

to

discard

the

hypothesis

of a

serial,

exhaustive

comparison process. Some

of the

models

proposed

as

alternatives will

be

dis-

cussed

below.

The final

problem

for the

serial, exhaustive

search

model

is

posed

by the

occurrence

of

errors.

The

explanations

of

controlled search

processes

by

Sternberg (and

by us) for re-

action time tasks

do not

propose

an

explicit

mechanism

by

which errors

may

occur. Many

investigators have simply ignored errors

as

long

as the

error rate

rate

is

low, under

5%,

say.

This

is

perhaps justifiable

if

errors

are

anomalous

events

that

do not

interact with

any of the

other variables being studied.

In-

deed

the

stability

of findings

across numerous

studies that

do not

attempt

to fix

error rates

at any

given value

and

that

vary consider-

ably

in the

observed

rates

(in the

range

0-

10%)

lends some support

to the

view

that

ignoring

errors will

not

distort

the

conclusions

drawn

from

the

reaction time

data.

In

principle, however, error rates cannot

be

ignored. Pachella

(1974)

has

shown

that

instructions used

to

change error rates

by

just

a few

percent

can

cause considerable

changes

in the

level

and

pattern

of

reaction

times. There

are

many ways

in

which error-

producing

mechanisms

can be

appended

to

controlled search models.

Two of the

most

PERCEPTUAL LEARNING

AND

AUTOMATIC ATTENDING

173

important

are as

follows:

First,

the

subject

might terminate,

or be

forced

to

terminate,

the

controlled search

before

the

search

is

completed.

Then

a

response would have

to

be

made

as a

guess based

on

partial

informa-

tion

at

most,

or

perhaps

no

response

at all

would

be

made

(an

omission).

These

types

of

error resulting

from

early search termina-

tion account

for

almost

all

errors

in

search

and

attention

tasks

using above-threshold

stimuli with accuracy

as a

measure;

in

par-

ticular, most

of the

errors

in the

accuracy

tasks

reported

in the

present paper

and in

Part

I are

errors

of the

type. Second,

the

search process might

be

carried

out

incor-

rectly;

that

is, a

comparison might

be

car-

ried

out

incorrectly owing

to

confusions

among

items, forgetting, misperception,

and

the

like. When error mechanisms

are ap-

pended

to the

basic search model

a new ex-

panded theory results, which must

be

tested

through joint consideration

of

error

data

and

reaction time

data.

Two

basic

approaches

may be

utilized

to

test

search theories incorporating error pre-

dictions.

One

approach involves manipulat-

ing

the

error rate systematically within each

condition;

the

manipulation

may be

carried

out

through instruction, deadline training,

or

signals-to-respond

(Reed,

1973).

This

ap-

proach

has the

advantage

of

making

full

use

of

both

the

error

and

reaction time

data

from

a

single experiment.

It has the

dis-

advantage

that

the

manipulations

of

error

rates

may

affect

the

nature

of the

controlled

search strategy adopted

by the

subject.

For

example, Reed (1976) carried

out a

remark-

able series

of

tests

of a

wide variety

of

models

using

data

collected

in the

signal-to-respond

procedure.

Unfortunately, though

one

model

could

be

singled

out in

preference

to the

others,

the

basic

data

differed

in

important

respects

from

those ordinarily

found

in the

simpler version

of the

same paradigm.

The

alternative approach involves carrying

out

two

separate studies involving

the

same

subjects.

One

study utilizes

the

usual

re-

action time methodology, with instructions

to

keep error rates low.

The

second study

utilizes

a

paradigm

in

which

the

available

search time

is

systematically varied

and the

error

rates corresponding

to

each amount

of

available search time

are

collected.

The

model

derived

from

one

study

can

then

be

used

to

predict

the

results

of the

other.

This

is the

method

that

was

adopted

in

Experiments

1

and

2 of

Part

I.

This

approach

has the ad-

vantage

of

relating

two fields of

inquiry

that

are

normally treated separately.

In the

present paper,

for

example, attention tasks

using

accuracy

as a

measure were linked

to

search tasks

using

reaction time

as a

measure.

It

should

be

noted,

by the

way,

that

the

type

of

error predicted

for the

results

of

Part

I/Experiment

1 is

that

caused

by

premature

termination

of

controlled search whose char-

acteristics were derived

from

the

reaction

time

results

of

Part

I/Experiment

2.

How-

ever,

the

errors seen

in

Part

I/Experiment

2

were

not

necessarily caused

by the

same

mechanism.

In

fact

many,

if not

most,

of

them

may

have resulted

from

confusions,

forgetting,

or

anomalous condition-indepen-

dent factors.

B. The

Theios

Model

There

are

really

two

separate

treatments

to

be

discussed here:

the

specific

micromodel

used

by

Theios

et

al.

(1973)

to

predict

re-

sults

that

would

otherwise

be fit by a

serial,

exhaustive

model,

and the

general theory

used

by

Theios (1973, 197S)

to

describe

the

production

of

response times

in a

variety

of

tasks.

1.

Serial, Terminating Search Through

a

List

of

Memory

Items

and

Distractors

In

this model

a

list

is

constructed

in

mem-

ory,

a

list

on

which appear

all

items

that

might

be

displayed

for

test.

Each

of

these

items

has an

associated response

cue

(posi-

tive

or

negative) attached

to it. The

memory-

set

items

and

distractors

may in

general

be

intermingled

in

this list,

but a

variety

of

Controlled and automatic human information processing: II. Perceptual learning, automatic attending and a general theory

Abstract and Figures