Voluntary task switching under load: contribution of top-down and bottom-up factors in goal-directed behavior.

Abstract

The present study investigated the relative contribution of bottom-up and top-down control to task selection in the voluntary task-switching (VTS) procedure. In order to manipulate the efficiency of top-down control, a concurrent working memory load was imposed during VTS. In three experiments, bottom-up factors, such as stimulus repetitions, repetition of irrelevant information, and stimulus-task associations, were introduced in order to investigate their influence on task selection. We observed that the tendency to repeat tasks was stronger under load, suggesting that top-down control counteracts the automatic tendency to repeat tasks. The results also indicated that task selection can be guided by several elements in the environment, but that only the influence of stimulus repetitions depends on the efficiency of top-down control. The theoretical implications of these findings are discussed within the interplay between top-down and bottom-up control that underlies the voluntary selection of tasks.

Full text

Page 1

Many researchers assume that goal-directed behavior
relies on the intentional and controlled activation of task
goals (Baddeley, 1992; Logan & Gordon, 2001; Miller
& Cohen, 2001). However, several studies have demon-
strated that task goals can also be activated automatically
by information in the environment (e.g., Mattler, 2003;
Mayr & Bryck, 2007; Verbruggen & Logan, 2009) or by
the retrieval of previously formed associations between a
stimulus and a particular goal (e.g., Verbruggen & Logan,
2008; Waszak, Hommel, & Allport, 2003). In the pres-
ent study, we examined the contribution of top-down
and bottom-up activation of task goals in voluntary task
switching (VTS).
In VTS, participants switch between cognitive tasks.
They are free to select the task to perform, as long as
each task is selected an approximately equal number of
times and participants do not follow a predictable pat-
tern of task selection (Arrington, 2008; Arrington &
Logan, 2004, 2005; Liefooghe, Demanet, & Vandieren-
donck, 2009; Mayr & Bell, 2006). A general finding is
that participants repeat tasks more often than they switch
(Arrington & Logan, 2005). This task-repetition bias has
been linked to the efficiency of top-down control pro-
cesses involved in the voluntary selection of task goals.
For example, Mayr and Bell argued that participants tend
to repeat tasks because the task on the previous trial is
still the most active one when a new task is selected. In
order to overcome this bias, the activated task has to be
inhibited. Thus, selection of tasks would depend on top-
down control processes (see also Arrington & Logan,
2004, 2005). However, several studies have shown that
bottom-up processes also contribute to task selection in
VTS (e.g., Arrington, 2008), and Mayr and Bell observed
that the task-repetition bias was stronger when the stimu-
lus of the previous trial was repeated than when the stim-
ulus alternated. This stimulus-repetition effect suggests
that voluntary task selection is not completely immune to
bottom-up priming effects.
In the present study, we focused on the contribution
of top-down control and bottom-up priming in volun-
tary task selection. Studies in several paradigms have
shown that bottom-up factors contribute more to behav-
ior in cognitively demanding situations (for a review,
see Lavie, 2005). A manipulation that is often used to
reduce the efficiency of top-down control is a concur-
rent working memory (WM) load (e.g., Logan, 2007). To
test the relative contribution of bottom-up and top-down
processes in task selection, we manipulated WM load in
the VTS paradigm in three experiments. Each experi-
ment consisted of two conditions: a load condition and a
no-load condition (see Logan, 2007). In the load condi-
tion, participants were shown six letters that they had
to remember (study phase), followed by 13 voluntary
switch trials (VTS phase), followed by a recall phase, in
which participants had to indicate which letters they had
been shown in the study phase. In the no-load condition,
the study phase was immediately followed by the recall
phase, which, in turn, was followed by the VTS phase, so
that there was no concurrent memory load during the test
phase. We predicted that bottom-up control would con-
387 © 2010 The Psychonomic Society, Inc.
Voluntary task switching under load:
Contribution of top-down and
bottom-up factors in goal-directed behavior
Jelle Demanet, FreDerick Verbruggen,
baptist lieFooghe, anD anDré VanDierenDonck
Ghent University, Ghent, Belgium
The present study investigated the relative contribution of bottom-up and top-down control to task selection
in the voluntary task-switching (VTS) procedure. In order to manipulate the efficiency of top-down control, a
concurrent working memory load was imposed during VTS. In three experiments, bottom-up factors, such as
stimulus repetitions, repetition of irrelevant information, and stimulus–task associations, were introduced in
order to investigate their influence on task selection. We observed that the tendency to repeat tasks was stronger
under load, suggesting that top-down control counteracts the automatic tendency to repeat tasks. The results also
indicated that task selection can be guided by several elements in the environment, but that only the influence of
stimulus repetitions depends on the efficiency of top-down control. The theoretical implications of these find-
ings are discussed within the interplay between top-down and bottom-up control that underlies the voluntary
selection of tasks.
Psychonomic Bulletin & Review
2010, 17 (3), 387-393
doi:10.3758/PBR.17.3.387
J. Demanet, jelle.demanet@ugent.be

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388 Demanet, Verbruggen, Liefooghe, anD VanDierenDonck
item per second (500 msec on, 500 msec off). In the recall phase,
participants had to recall the memorized items in the correct order
and type the items on the keyboard. There were no time constraints
in the recall phase. In the VTS phase, participants categorized a
stimulus as being smaller or larger than 5 (magnitude task) or odd
or even (parity task). We used digits 1 through 9, excluding 5. The
magnitude task (smaller, left-outer button; larger, left-inner button)
and the parity task (odd, right-inner button; even, right-outer but-
ton) were mapped on a different hand. The task-to-hand assignment
was counterbalanced across participants. There were 13 trials in the
VTS phase. Each trial started with the presentation of a stimulus.
When a response was executed or the maximal response time (RT)
of 3,000 msec had elapsed, a fixed response–stimulus interval of
100 msec started. The first trial was a filler; of the remaining 12
trials, 4 (25%) were stimulus repetitions. The experimental session
started with three practice blocks, in which participants practiced
(1) the study and recall phases separately, (2) the VTS phase sepa-
rately, and (3) the combination of the three phases. Before the prac-
tice blocks, we presented Arrington and Logan’s (2004) instructions
(in Dutch) on the screen and paraphrased them when necessary. The
practice trials were followed by the experimental session, which con-
sisted of 20 lists per condition: load condition, study–test–recall;
no-load condition, study–recall–test. The order of the conditions
was counterbalanced across participants. The experimental session
lasted approximately 30 min.
Experiment 2 was identical to Experiment 1, except that, in the
VTS phase, stimulus repetitions were excluded. Instead, we pre-
sented a task-irrelevant shape on each trial. The target stimulus ap-
peared inside one of four white, nonfilled shapes (circle, triangle,
hexagon, square; each shape 5 5.9 cm2). On 25% of the trials, the
shape of the previous trial was repeated.
In Experiment 3, participants performed either an animacy task
(nonliving or living) or a size task (smaller or larger than a basket-
ball) on nouns. We selected 128 nouns on the bases of word fre-
quency (average frequency 5 11.0 per million) and word length
(average length 5 5.6 letters). For every participant, three differ-
ent stimulus sets of 32 nouns were selected (matched for frequency
and word length). All sets consisted of 8 large living, 8 small liv-
ing, 8 large nonliving, and 8 small nonliving stimuli. Before the
experimental session, participants performed a training session of
16 single-task blocks (640 min). In the training session, the first
stimulus set was always used for the animacy task, and the second
stimulus set was always used for the size task. Participants practiced
one task in the odd-numbered blocks and one in the even-numbered
blocks. Task-to-block mapping was counterbalanced. Each training
block consisted of 32 trials, and each item of the relevant set was
presented once. All of the trials in the training session started with
the presentation of a noun in the center of the screen. This stimulus
remained on the screen for 1,000 msec, regardless of the RT. The
maximal RT was 4,000 msec, and the response–stimulus interval
was 750 msec. The participants responded orally by saying [bu:] for
tribute more to task selection in the load condition than
in the no-load condition. The results of Experiment 1
confirmed this prediction and showed that the stimulus-
repetition effects and the task-repetition bias were stron-
ger in the load condition than in the no-load condition.
In Experiments 2 and 3, we further tested how stimulus
repetitions affected task-selection processes. We propose
three accounts for the stimulus-repetition effect. First,
the effect could be caused by the repetition of visual in-
formation on the screen, which could prime the decision
to repeat the task (see also Arrington & Logan, 2005).
Second, the effect could be caused by the retrieval of as-
sociations formed between the stimulus and the task ex-
ecuted on the previous trial. When the stimulus repeats,
this association is retrieved, and the task goal of the
previous trial is primed (see, e.g., Verbruggen & Logan,
2008). Third, the effect could be due to the retrieval of
associations between the stimulus and the task- execution
response (see, e.g., Hommel, 1998; Soetens, 1998).
When the stimulus repeats, the task-execution response
of the previous trial is also repeated. This suggests that
participants would not select a new task first; instead,
they would directly execute a response. Experiments 2
and 3 were designed to test these accounts by including
repetitions of task-irrelevant features in Experiment 2
and forming strong stimulus–task associations in a train-
ing phase in Experiment 3.
MethoD
Participants and Materials
Eighty students from Ghent University participated for course
requirements and credit (in Experiment 1, N 5 24; in Experiment 2,
N 5 24; in Experiment 3, N 5 32). The participants were tested in-
dividually by means of a Pentium III personal computer with a 17-in.
color monitor running Tscope (Stevens, Lammertyn, Verbruggen,
& Vandierendonck, 2006). We used an external response box with
four buttons to register responses in the VTS phase and a QWERTY
keyboard to register responses in the recall phase.
Procedure
The experimental session of Experiment 1 consisted of a study
phase, a recall phase, and a VTS phase. In the study phase, we pre-
sented six different low-interconfusable consonants (for details, see
Vandierendonck, De Vooght, & Van der Goten, 1998). The conso-
nants were presented in the center of the screen at a rate of one
table 1
task-Repetition Proportions As a Function of Load,
trial type, and task transition for experiments 1 and 2
No Load
Task
Repetitions
Trial Type
M SE
Load
Task
Switches
M SE
Task
Repetitions
M
Task
Switches
M SESE
Experiment 1
.04
.02
Stimulus repetitions
Stimulus alternations
.48
.48
.52
.52
.04
.02
.62
.54
.04
.02
.38
.46
.04
.02
Experiment 2
.02 Shape repetitions
Shape alternations
.55.45.02 .59.03.41.03
.51 .03 .49 .03 .55 .02 .45 .02

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VoLuntary task switching unDer LoaD 389
SE 5 .029) [comparison .50: t(23) 5 2.68, p 5 .01] than
in the no-load condition (M 5 .483, SE 5 .026) [compari-
son .50: t(23) 5 20.66, p 5 .51]. These results confirm
the hypothesis that top-down control is needed to counter-
act the tendency to repeat tasks (e.g., Mayr & Bell, 2006).
The absence of a tendency (in comparison with .50) to
repeat tasks in the no-load condition is probably due to
the length of the sequences. This result converges with the
findings of Rapoport and Budescu (1997), indicating that,
in random selection of events, there is a greater tendency
to alternate for shorter sequences.
It is important to note that we observed a stimulus-
repetition effect in the load condition, but not in the no-
load condition, of Experiment 1 (see Tables 1 and 3).
Simple main effects showed that the effect of trial type
was significant in the load condition [F(1,23) 5 4.93,
MSe 5 .0163, η2p 5 .18], but not in the no-load condi-
tion (F , 1). This suggests that bottom-up control con-
tributes more to task selection in cognitively demanding
situations (i.e., the load condition) than in less demand-
ing situations (i.e., the no-load condition). The complete
absence of a stimulus-repetition effect in the no-load
condition is probably due to the relatively low number
of stimulus repetitions (see also Experiments 3 and 4 in
Arrington & Logan, 2005).
The data from Experiment 2 were analyzed by means of a
repeated measures ANOVA with load (no load vs. load) and
trial type (shape repetition vs. shape alternation) as factors.
The analyses showed that tasks were repeated more often
in the load condition (M 5 .570, SE 5 .024) [comparison
.50: t(23) 5 2.91, p 5 .01] than in the no-load condition
(M 5 .532, SE 5 .023) [comparison .50: t(23) 5 1.41, p 5
.17]. Furthermore, tasks were repeated more often on shape
repetitions (M 5 .569, SE 5 .022) than on shape alterna-
tions (M 5 .534, SE 5 .024), which suggests that repeating
visual information can prime task repetitions. However, the
size of the shape-repetition effect was comparable for the
load and the no-load conditions (see Table 1). The absence
of an interaction suggests that the stimulus-repetition effect
observed in Experiment 1 was not simply caused by the
repetition of visual information on the screen.
The data from Experiment 3 were analyzed in two
steps. First, we examined whether task selections were
influenced by the training phase by means of a repeated
measures ANOVA with load and stimulus set (animacy vs.
size vs. neutral set) as factors. We focused on the propor-
tions of the animacy task; we would get symmetrical re-
sults if the focus was on the size task. The analysis showed
that there was a strong learning effect (see Table 2). Con-
trasts showed that the animacy task was selected more
often for the animacy set (M 5 .554, SE 5 .012) than
for the neutral set (M 5 .501, SE 5 .010) [F(1,31) 5
10.31, MSe 5 .0088 , η2p 5 .25] or the size set (M 5 .458,
SE 5 .011) [F(1,31) 5 28.57, MSe 5 .0104, η2p 5 .48].
The difference between the size and neutral sets was also
significant [F(1,31) 5 7.94, MSe 5 .0074, η2p 5 .20],
which suggests that participants tended to choose the size
task for the size set. Combined, these findings suggest
that learned stimuli primed the selection of the task they
were associated with in the training phase. However, this
living, [bi:] for nonliving, [ba:] for small, and [bo:] for large. The
structure of the experimental phase of Experiment 3 was similar to
that of Experiment 1. Because VTS stimuli were words, the WM
load consisted of six different numbers (range 5 1–9). There were
no other differences in the study or recall phase. In the VTS phase,
the animacy task was performed with one hand (nonliving, left-outer
button; living, left-inner button) and the size task with the other hand
(small, right-inner button; large, right-outer button). Eight lists of
VTS trials were used in both load conditions. In each VTS phase,
12 stimuli were presented: 4 stimuli of the animacy set, 4 stimuli of
the size set, and 4 stimuli of the third stimulus set (i.e., the neutral
set, which was not used in the training phase). The maximal RT in
the VTS trials was 5,000 msec because the tasks were more difficult
than those in Experiments 1 and 2.
ResuLts AnD DisCussion
The first trial of each VTS phase and the trials follow-
ing an error were discarded (for Experiment 1, data loss 5
12.8%; for Experiment 2, data loss 5 11.5%; for Experi-
ment 3, data loss 5 12.3%). In this study, we were inter-
ested in the processes involved in the voluntary selection
of tasks. Therefore, in the Results section, we will focus
on task-choice data only. Analyses of response latencies
are presented in the Appendix. The task-selection propor-
tions appear in Tables 1 and 2. Analysis results appear in
Tables 3 and 4.
The data from Experiment 1 were analyzed by means of
a repeated measures ANOVA with load (no load vs. load)
and trial type (stimulus repetition vs. stimulus alternation)
as factors, performed on the task-repetition proportions.
When relevant, individual t tests were performed to test
whether proportions were different from .50. As is shown
in Tables 1 through 4, participants repeated the task of the
previous trial more often in the load condition (M 5 .579,
table 2
task-selection Proportions As a Function of Load,
trial type, and task for experiment 3
No Load
Animacy
TaskSize Task
Trial Type
M SE
M
Animacy.54.02.46
Size.46.02.54
Neutral .51 .02 .49 .02 .49 .01 .51 .01
Load
Animacy
Task
M
.57
.46

Size Task
M
.43
.54
SE
.02
.02
SE
.02
.02
SE
.02
.02
table 3
outcome of the AnoVAs Conducted on the selection
Proportions of task Repetitions for experiments 1 and 2
Factor
MSe

df F
η2p
Experiment 1
.0118
.0254
.0034
Load
Trial type
Load 3 trial type
1,23
1,23
1,23
18.70*
1.41
12.96*
.45
.06
.36
Experiment 2
.0045
.0027
Load
Trial type
1,23
1,23
7.46*
10.84*
.24
.32
Load 3 trial type.00251,230.00.00
*p , .05.

Page 4

390 Demanet, Verbruggen, Liefooghe, anD VanDierenDonck
thus reduces the tendency to repeat tasks (Mayr & Bell,
2006; see also Lien & Ruthruff, 2008).
In Experiment 1, we found that stimulus repetitions elic-
ited more task repetitions in the load than in the no-load
condition. This observation seems to support the idea that
bottom-up control contributes more to task selection in
cognitively demanding situations (for a similar idea, see
Arrington, 2008; Lavie, 2005). In Experiments 2 and 3,
however, we observed priming effects of repeating shapes
and acquired stimulus–task associations, but these effects
did not interact with load. This suggests that some bottom-
up-driven effects occur independently of the cognitive de-
mands of the situation. Furthermore, the results of Experi-
ments 2 and 3 suggest that the stimulus-repetition effect,
which was observed in Experiment 1 and interacted with
load, was not caused by the repetition of visual informa-
tion or the retrieval of stimulus–task associations. Instead,
we propose that the stimulus-repetition effect is caused by
the retrieval of associations between the stimulus and the
task-execution response. When the stimulus is repeated, the
task-execution response of the previous trial is activated
and executed again. Interestingly, this suggests that, on a
proportion of the trials, a response is executed without ad-
vance selection of a new task. The interaction with load in
Experiment 1 suggests that there are more nonselection tri-
als when top-down control is degraded in highly demanding
situations. In less demanding situations, however, top-down
processes can counteract this response-repetition tendency.
This suggests that an important function of top-down con-
trol in VTS is to protect task selection from automatically
triggered responses. This function of top-down control can
be related to the response-inhibition account of Hübner
and Druey (2006), which states that, in a task-switching
context, a response has to be inhibited in order to avoid its
automatic reexecution on the following trial (for a similar
idea, see Logan & Gordon, 2001). In this perspective, the
present study contributes by showing that, when a response
is inhibited less efficiently in a high-demanding situation,
the chance to reexecute this response on the next trial is
increased on stimulus repetitions. In sum, the present study
shows that different bottom-up factors can guide task selec-
tion and that top-down control is necessary to shield task se-
lection from the effects of stimulus–response associations
and to counteract the tendency to perseverate tasks.
In conclusion, the data of the present study also al-
lowed us to formulate an answer to the question, What is
really voluntary or intentional in the VTS paradigm? We
obtained convincing evidence for the ideas that task goals
are automatically triggered by factors in the environment
(e.g., Waszak et al., 2003) and that participants can inhibit
recently activated task goals and suppress automatically
triggered responses to protect intentional goal-directed
behavior. Thus, perhaps the intentional or voluntary act
in VTS is not to activate what is “willed” but to suppress
what is “unwilled.”
AuthoR note
F.V. is a postdoctoral fellow of the Research Foundation Flanders
(FWO-Vlaanderen). We thank the reviewers for their comments on a
stimulus- priming effect was similar in the no-load and
load conditions (Table 2). The absence of an interaction
shows that stimulus–task associations did not cause the
priming effect seen in Experiment 1.
In a second step, we examined whether there was an
influence of load on the general task-repetition bias, as
was the case in the other experiments. We analyzed task-
repetition proportions with a one-way ANOVA with load
as the only factor. Consistent with the findings in Ex-
periments 1 and 2, tasks were repeated more often in the
load (M 5 .517, SE 5 .021) [comparison .50: t(32) 5
0.81, p 5 .42] than in the no-load (M 5 .472, SE 5 .020)
[comparison .50: t(32) 5 21.44, p 5 .16; F(1,31) 5 6.55,
MSe 5 .0050, η2p 5 .17] condition. Again, this finding
shows task-repetition bias to be stronger in cognitively
demanding situations.
Recall Phase
The proportions of correct recall represent the probabil-
ity that a particular item was remembered correctly in the
correct order. We analyzed the proportions by means of a
simple main effects ANOVA with load as the only factor.
As shown in Table 5, proportions were higher in the no-
load than in the load condition, which can be explained by
the different order of the VTS and recall phases.
Conclusion
In the present study, we examined how bottom-up and
top-down processes contribute to voluntary selection of
tasks in situations that are cognitively demanding. In Ex-
periment 1, we found that participants repeated tasks more
often in the load (demanding) condition than in the no-
load (nondemanding) condition. We replicated this load
effect in Experiments 2 and 3. The effect of load on the
task-repetition bias was consistent with the idea that top-
down processes are necessary to overcome the tendency
to repeat the same task. It also fits with the idea that top-
down control inhibits the most recently executed task, and
table 4
outcome of the AnoVAs Conducted
on the Animacy task-selection Proportions for experiment 3
Factor Wilks
Load.9986
Trial type.5204
Load 3 trial type.9390

df

F
η2p
.00
.48
.06
1,31
2,30
2,30
0.04
13.83*
0.98

*p , .05.
table 5
Mean Proportions of Correct Recall in the no-Load
and Load Conditions and the Results of the Main effect
AnoVAs on these Proportions With Load As the only Factor
No LoadLoad
Experiment M SE M SE
1 .93.1 .84
2 .91.1 .84
3 .97.1 .83
Main Effect Load
F
42.80*
31.74*
27.36*
df MSe η2p
.0025
.0020
.0101
.2
.2
.3
1,23
1,23
1,31
.65
.58
.47
*p , .05.

Page 5

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392 Demanet, Verbruggen, Liefooghe, anD VanDierenDonck
APPenDix
The mean RTs and analyses are presented in Tables A1 through A4. Error rates were very low (Experiment 1 5 3.6%; Ex-
periment 2 5 3.1%; Experiment 3 5 4.6%) and were not further analyzed.
We analyzed the mean RTs of Experiments 1 and 2 with a repeated measures ANOVA with the factors load (no load vs.
load), trial type, and task transition (task repetition vs. task switch). In both experiments, we found main effects of load [RT (no
load) , RT(load)] and task transition [RT(repetition) , RT(switch)]. The main effect of trial type was also significant, in-
dicating that repetitions of stimuli or shapes induced faster responses than did alternations. In Experiment 1, the interaction
between trial type and task transition was reliable, indicating that the switch cost was smaller on stimulus repetitions than on
stimulus alternations (see Allport & Wylie, 2000). The interaction between load and task transition was significant, indicating
that the switch cost was smaller in the load than in the no-load condition. A contrast showed that this was especially due to
marginally slower task repetitions in the load than in the no-load condition [F(1,23) 5 3.75, MSe 5 9,861, η2p 5 .14] and not
by faster switches (F , 1) (for similar results, see Liefooghe, Vandierendonck, Muyllaert, Verbruggen, & Vanneste, 2005).
In Experiment 2, the interaction between load and task transition was not significant. This difference between Experiments 1
and 2 is possibly due to the inclusion of stimulus repetitions in Experiment 1.
We analyzed mean RTs from Experiment 3 with a mixed ANOVA with the factors load, trial type (animacy vs. size vs.
neutral stimulus set), task transition, and task. We found main effects of load [RT(no load) , RT(load)] and task transition
[RT(repetition) , RT(switch)]. Also, the main effect of trial type was significant. Contrasts showed that responses to neutral
stimuli were slower than responses to stimuli of the size stimulus set [F(1,31) 5 17.12, MSe 5 18,931, η2p 5 .36]. The differ-
ences between neutral and animacy were not significant [F(1,31) 5 1.61, MSe 5 34,019, η2p 5 .05]. The differences between
animacy and size were not significant either [F(1,31) 5 2.64, MSe 5 42,558, η2p 5 .08]. The interaction between trial type and
task was significant, indicating that performing a task on a stimulus that is associated with that same task leads to better per-
formance than does performing another task. Contrasts confirmed this for both the animacy [F(1,31) 5 18.19, MSe 5 39,806,
η2p 5 .37] and size stimulus [F(1,31) 5 17.43, MSe 5 21,759, η2p 5 .36] sets, but not for the neutral stimulus (F , 1) set.
table A1
Mean Response times (in Milliseconds) As a Function
of Load, trial type, and task transition for experiments 1 and 2
No Load
Task
RepetitionsSwitches
Trial Type
M SE
Load
Task Task
Repetitions
M
Task
Switches
MM SE
SE
SE
Experiment 1
31889
25 940
Stimulus repetitions
Stimulus alternations
624
831
29
27
656
877
32
33
849
965
33
34
Experiment 2
35930Shape repetitions
Shape alternations
79845 796 31989 39
809 41 962 46 837 35 1,010 42
table A2
Mean Response times (in Milliseconds) As a Function of Load, trial type, task transition, and task for experiment 3
No Load
Task RepetitionsTask Switches
Animacy
Task Size TaskTaskSize Task
Type
M SE
M SE
M SE
M
Animacy97452 1,06362 1,15552 1,233
Size1,042 581,006 621,145 461,091
Neutral 1,054 59 1,112 69 1,228 54 1,177 43 1,097 58 1,137 53 1,244 51 1,267 59
Load
Task Repetitions
Animacy
Task
M SE
1,000 52
1,138 63
Task Switches
Animacy
Task
M SE
1,233 55
1,286 59

Stimulus
Animacy
Size Task
M
1,165
1,066

Size Task
M
1,327
1,140
SE
62
39
SE
68
50
SE
77
55

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VoLuntary task switching unDer LoaD 393
table A3
outcome of the AnoVAs Conducted
on the Response times for experiments 1 and 2
Factors
MSe

df F
η2p
Experiment 1
Load
Trial type
Task transition
Load 3 trial type
Load 3 task transition
Trial type 3 task transition
Load 3 trial type 3 task transition
16,665
16,818
30,245
8,087
5,549
7,083
3,836
1,23
1,23
1,23
1,23
1,23
1,23
1,23
0.72
63.04*
42.59*
2.31
4.76*
28.73*
2.00
.03
.73
.65
.09
.17
.56
.08
Experiment 2
Load
Trial type
Task transition
Load 3 trial type
Load 3 task transition
Trial type 3 task transition
Load 3 trial type 3 task transition
*p , .05.
31,502
4,213
15,822
1,901
4,970
4,059
2,700
1,23
1,23
1,23
1,23
1,23
1,23
1,23
1.67
7.89*
80.79*
0.55
3.88
0.00
1.89
.07
.26
.78
.02
.14
.00
.08
table A4
outcome of the AnoVAs Conducted
on the Response times for experiment 3
Factors Wilks
.8501
.6417
.4100
.9712
.9387
.9878
.8244
.9997
.4647
.8849
.9999
.8751
.9992
.9959
.8699
df

F
η2p
.15
.36
.59
.03
.06
.01
.18
.00
.54
.12
.00
.12
.00
.00
.13
Load
Trial type
Task transition
Task
Load 3 trial type
Load 3 task transition
Trial type 3 task transition
Load 3 task
Trial type 3 task
Task transition 3 task
Load 3 trial type 3 task transition
Load 3 trial type 3 task
Load 3 task transition 3 task
Trial type 3 task transition 3 task
Four-way interaction
1,31
2,30
1,31
1,31
2,30
1,31
2,30
1,31
2,30
1,31
2,30
2,30
1,31
2,30
2,30
5.47*
8.37*
44.60*
0.92
0.98
0.38
3.20
0.01
17.28*
4.03
0.00
2.14
0.03
0.06
2.24
*p , .05.
(Manuscript received August 21, 2009;
revision accepted for publication December 22, 2009.)
APPenDix (Continued)