Function follows form: activation of shape and function features during object identification.

Abstract

Most theories of semantic memory characterize knowledge of a given object as comprising a set of semantic features. But how does conceptual activation of these features proceed during object identification? We present the results of a pair of experiments that demonstrate that object recognition is a dynamically unfolding process in which function follows form. We used eye movements to explore whether activating one object's concept leads to the activation of others that share perceptual (shape) or abstract (function) features. Participants viewed 4-picture displays and clicked on the picture corresponding to a heard word. In critical trials, the conceptual representation of 1 of the objects in the display was similar in shape or function (i.e., its purpose) to the heard word. Importantly, this similarity was not apparent in the visual depictions (e.g., for the target Frisbee, the shape-related object was a triangular slice of pizza, a shape that a Frisbee cannot take); preferential fixations on the related object were therefore attributable to overlap of the conceptual representations on the relevant features. We observed relatedness effects for both shape and function, but shape effects occurred earlier than function effects. We discuss the implications of these findings for current accounts of the representation of semantic memory.

Full text

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Journal of Experimental Psychology: General
Function Follows Form: Activation of Shape and Function
Features During Object Identification
Eiling Yee, Stacy Huffstetler, and Sharon L. Thompson-Schill
Online First Publication, March 21, 2011. doi: 10.1037/a0022840
CITATION
Yee, E., Huffstetler, S., & Thompson-Schill, S. L. (2011, March 21). Function Follows Form:
Activation of Shape and Function Features During Object Identification. Journal of
Experimental Psychology: General. Advance online publication. doi: 10.1037/a0022840

Page 2

Function Follows Form: Activation of Shape and Function Features During
Object Identification
Eiling Yee, Stacy Huffstetler, and Sharon L. Thompson-Schill
University of Pennsylvania
Most theories of semantic memory characterize knowledge of a given object as comprising a set of
semantic features. But how does conceptual activation of these features proceed during object identifi-
cation? We present the results of a pair of experiments that demonstrate that object recognition is a
dynamically unfolding process in which function follows form. We used eye movements to explore
whether activating one object’s concept leads to the activation of others that share perceptual (shape) or
abstract (function) features. Participants viewed 4-picture displays and clicked on the picture correspond-
ing to a heard word. In critical trials, the conceptual representation of 1 of the objects in the display was
similar in shape or function (i.e., its purpose) to the heard word. Importantly, this similarity was not
apparent in the visual depictions (e.g., for the target Frisbee, the shape-related object was a triangular
slice of pizza, a shape that a Frisbee cannot take); preferential fixations on the related object were
therefore attributable to overlap of the conceptual representations on the relevant features. We observed
relatedness effects for both shape and function, but shape effects occurred earlier than function effects.
We discuss the implications of these findings for current accounts of the representation of semantic
memory.
Keywords: semantic memory, semantic features, semantic attributes, spoken word recognition, eye
movements
Look around you. You are likely faced with numerous and
various objects, most of which you know quite a bit about. For
example, there might be a plate with a slice of pizza on it left over
from dinner. If asked, you would be able to easily retrieve a great
deal of semantic information about pizza (e.g., its shape, color,
smell, what it is used for, how it is cooked). In fact, these attributes
might be considered to constitute the concept “pizza.” Broadly
speaking, different attributes of objects can be classified into those
that are perceptual (e.g., round, red, hot) and those that are abstract
(e.g., food, Italian, cheap). However, when one looks at an object
like pizza, there is a further distinction, in that one has access to
both the immediate sensory perceptual information (reflecting the
current input to one’s senses) and the long-term (i.e., conceptual)
knowledge about an object’s typical perceptual features (which are
generalized across different experiences with that object). Thus,
the slice of pizza across the room may be triangular, red, and
greasy, but from this sensory information one can retrieve not only
the abstract knowledge that it is a food (knowledge that is ab-
stracted across the various contexts in which pizzas are experi-
enced) but also the long-term perceptual knowledge that pizza is
usually round (a feature that is often, but not currently, grounded
in sensory experience). The focus of the current work is on this
long-term conceptual knowledge (both perceptual and abstract)
about concrete objects.
One consequence of the description of concepts as including a
set of independent attributes (or features) is that it allows for the
possibility that they can have different time courses of activation.
For example, when identifying that the thing on the plate across the
room is leftover pizza, the initial input is primarily sensory; if the
activation of the concept “pizza” begins with sensory input, it may
spread to long-term perceptual information more quickly than to
more dissimilar abstract features. In the current work, we contrast
perceptual with more abstract features to explore whether different
attributes of an object have distinct time courses of activation
during object identification. Finding that perceptual and abstract
information become available over different time courses would
indicate that these features are at least partially distinct compo-
nents of semantic knowledge. It would also have interesting and
perhaps surprising implications. Although people typically think
about their mental representation of concrete objects as static
(there is something that pizza means, and this does not vary), if
there are differences in the time course over which different
conceptual features of pizza are activated, then in a sense, pizza
Eiling Yee, Stacy Huffstetler, and Sharon L. Thompson-Schill, Depart-
ment of Psychology, University of Pennsylvania.
This research was supported by National Institutes of Health Grant
R01MH70850 to Sharon L. Thompson-Schill and by a Ruth L. Kirschstein
National Research Service Award Postdoctoral Fellowship (F32HD051364)
from the National Institute of Child Health and Human Development
awarded to Eiling Yee. Portions of this research were presented at the 15th
Annual Meeting of the Cognitive Neuroscience Society, San Francisco,
CA, April 2008. We are grateful to Jason Taylor, Katherine White, Gerry
Altmann, and Jesse Hochstadt for enormously helpful discussions and
comments. We also thank Eve Overton, Amir Francois, and Emily Mc-
Dowell for assistance with data collection.
Correspondence concerning this article should be addressed to Eiling
Yee, who is now at the Basque Center on Cognition, Brain and Language,
Paseo Mikeletegi 69, Planta 2, 20009 San Sebastian, Spain. E-mail:
eiling.yee@gmail.com
Journal of Experimental Psychology: General
2011, Vol. ●●, No. ●, 000–000
© 2011 American Psychological Association
0096-3445/11/$12.00 DOI: 10.1037/a0022840
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can mean something different as the process of object identifica-
tion unfolds. In other words, in an architecture in which different
attributes are activated at different times, conceiving of a concept
is a dynamically unfolding process.
Using Eye Movements to Explore Semantic Activation
During Object Identification
Recently, eye movements in the visual world paradigm have
been used to explore semantic activation. In visual world paradigm
studies, participants are typically presented with a multipicture
display, one of the objects is named, and participants are asked to
touch (or click on) the named object (the target). If the target is
semantically related to one of the other objects, participants are
more likely to fixate on this related object than on unrelated
objects (Huettig & Altmann, 2005; Yee & Sedivy, 2001). For
example, when instructed to click on the lock, one is more likely
to fixate on a picture of a key than on unrelated objects. This effect
cannot be attributed solely to visual confusability, simple lexical
co-occurrence, or attention being drawn to objects in the display
that are related (irrespective of the acoustic input).
Why then do participants fixate on semantically related objects?
To answer this question, it may be useful to provide a step-by-step
account of what one assumes is occurring when semantic effects
are observed in the visual world paradigm. When a display ap-
pears, participants scan all the depicted objects and begin to
identify them. During this process, many different attributes be-
come active. Continuing with the lock–key example, if the key is
depicted in gold and in a P shape, then upon seeing that object, the
remainder of its semantic representation, including nondepicted
perceptual features (e.g., hard, flat) and abstract features (e.g., used
for security), becomes active. Later, when a target word is heard
(e.g., lock), its semantic representation, including its various per-
ceptual and abstract features (e.g., shiny, hard, used for security),
also becomes active. Participants’ visual attention is drawn to a
picture to the extent that there is a match between any of the
currently active attributes of that picture and the semantic repre-
sentation of the target (cf. Altmann & Kamide, 2007). Thus, if
there is a key in the display and the target word is lock, and if
abstract information about key (e.g., used for security) has become
active, visual attention will be drawn to the key (due to the
similarity between the abstract features of lock and key). This
sensitivity to overlap on even nondepicted semantic features
makes the visual world paradigm an excellent candidate for ex-
ploring the activation of conceptual features during object identi-
fication.
Studies using eye movements to explore the activation of se-
mantic information have provided evidence that partial semantic
overlap between a heard word and a displayed object is sufficient
to draw visual attention to the displayed object (Huettig & Alt-
mann, 2005; Yee & Sedivy, 2001), and also that the degree of
semantic overlap predicts how much visual attention is drawn
(Huettig & Altmann, 2005; Huettig et al., 2006; Mirman & Mag-
nuson, 2009). However, these initial studies made no attempt to
explore which of the shared semantic attributes produced that
partial activation (e.g., if lock activates key, is this due to overlap
on the perceptual feature “hard,” the abstract feature “used for
security,” or both?). By explicitly manipulating the semantic rela-
tionship between the target and the related object, it is possible to
use eye movements to reveal whether and when a particular
semantic attribute is activated during object identification. Criti-
cally, for the purposes of the current work, by isolating different
semantic relationships, it is possible to test whether different kinds
of semantic attributes are activated differentially during object
identification.
A few studies have begun to explore specific semantic relation-
ships. These studies have demonstrated that visual attention is
drawn to objects whose sensory shapes match the long-term (here-
after conceptual) shape properties of a spoken word’s referent
(e.g., visual attention is drawn to a picture of a rope when the word
snake is heard; Dahan & Tanenhaus, 2005; Huettig & Altmann,
2007; Huettig & McQueen, 2007; cf. Myung, Blumstein, & Se-
divy, 2006, for an investigation of conceptual activation of a
different perceptual feature, manipulation). This finding provides
additional evidence that visual attention is drawn to a picture when
there is a match between the currently active attributes of that
picture and the (conceptual) semantic representation activated by
the heard word (in this case, there is a match in shape, rather than
the undifferentiated semantics in the lock–key example). However,
from these studies it is not possible to determine whether partici-
pants fixated on, for example, the rope when searching for a snake
because the long-term shape knowledge activated by the word
snake matched the depicted shape of the rope, or whether they
fixated on the rope because of the match with the conceptual shape
of rope (i.e., independent of its current sensory instantiation). That
is, it is unclear whether the displayed object’s conceptual shape
played any role in the diversion of visual attention (see Huettig &
Altmann, 2011, for evidence that this depicted versus conceptual
distinction is significant).
In the current work, we explicitly manipulated the semantic
relationship between the target word and the displayed related
object to independently explore the activation of two types of
semantic features during object identification: a perceptual feature
(shape) and a more abstract feature (function). We use the term
function because it is the most specific way to refer to the abstract
feature (i.e., purpose of use) we test. Our intent is not to make
claims about function in particular, in contrast to other abstract
features that might be correlated with function (e.g., functionally
related pairs are often also members of the same taxonomic cate-
gory and thus might also be called semantically or conceptually
related). Instead, we aim to distinguish between semantic features
that can be apprehended through a single perceptual modality (like
shape) and those that cannot (i.e., between sensorimotor-based
features and abstract features). We use the term function, rather
than conceptual or semantic because, as demonstrated above,
semantic and conceptual may be considered umbrella terms that
can comprise both abstract and perceptual features—the very
things we are distinguishing between.
We had two goals: (a) to determine whether similarity in con-
ceptual shape can affect visual attention and (b) if it can, to
determine whether it is possible to dissociate the time course of
shape’s activation from that of a more abstract feature (function).
For example, when one is faced with a triangular slice of pizza,
does information about its conceptual shape (round) become active
before information about its purpose of use (food)? To address this
second question, we manipulated the amount of time that partici-
pants had to identify the objects in the display prior to hearing the
target word. If abstract and perceptual information become avail-
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able over different time courses, this would suggest that these
features are at least partially distinct components of semantic
knowledge. It would also indicate that conceiving of an object is a
dynamically unfolding process.
Experiment 1
In Experiment 1 we used the visual world paradigm described
above to test whether hearing the name of an object draws visual
attention to objects that share a perceptual feature (shape) and/or
an abstract feature (function). For example, for function, because
tape and glue are both used for sticking things together, a function-
related display might include pictures of glue and tape as well as
two unrelated objects. Preferential fixations on the glue when the
word tape is heard would indicate that information about the
function of glue is active. Using pictures to investigate shape is
more complicated. To demonstrate that fixations on the shape-
related object are a consequence of partial activation of that object
due to conceptual overlap on shape, it is necessary to avoid
depicting the shape similarity between the target and the related
object. For example, to avoid the possibility that hearing Frisbee
causes participants to fixate on a picture of a pizza because the
feature (round) activated by Frisbee matches the roundness of the
pizza pie in the display, it is necessary for the pizza to be depicted
in a nonround shape. That is, pizza must be depicted in a shape that
a Frisbee cannot take (e.g., a triangle). Thus, an increase in
fixations to the triangular slice of pizza upon hearing the word
Frisbee must reflect the similarity between the conceptual repre-
sentations of Frisbees and (typical) pizzas.
Method
Participants.
from the University of Pennsylvania were tested after giving
informed consent. All participants were native speakers of English
and had normal or corrected-to-normal vision and no reported
hearing deficits. They were given course credit or paid a rate of
$10/hr for participating.
Apparatus.
An SR EyeLink II head-mounted eye tracker (SR
Research, Kanata, Canada) was used to monitor participants’ eye
movements. A camera imaged the participant’s right eye at 250
Hz. Stimuli were presented with PsyScript, a freely available
language for scripting psychology experiments (Bates &
Thirty-eight male and female undergraduates
D’Oliveiro, 2003), on a 15-in. (38.1-cm) Elo touch-sensitive mon-
itor (Elo TouchSystems, Menlo Park, CA).
Materials.
As we describe below, materials were carefully
selected to ensure that any preferential fixations on related objects
would be due to conceptual overlap on shape or function.
Stimulus selection and norming.
of over 100 pairs of objects that have similar shapes or similar
functions but that do not share other characteristics. Each pair
(presented as words) was rated on a 7-point scale for similarity of
shape, function, color, or manipulation (see Table 1 for rating
instructions). Although color and manipulation similarity are not
examined in the current work, we control for them because ma-
nipulation information has been found to be activated during
concept retrieval (Myung et al., 2006), and we are currently
exploring the possibility that color is as well (cf. Huettig &
Altmann, 2011). Ratings were obtained from at least 12 partici-
pants per attribute (each participant rated only one attribute), none
of whom participated in the eye-tracking experiments. On the basis
of these ratings, we selected 24 shape-related and 32 function-
related pairs. Table 1 shows mean attribute ratings for these two
conditions.
These ratings provide a measure of how similar the conceptual
representations of the paired objects are on the attributes of inter-
est. However, as noted above, because the objects during the
eye-tracking experiments were depicted as pictures, we must also
be concerned about the immediate sensory similarity of the paired
objects, which we refer to as the picture-based visual similarity.
Ensuring that the particular pictures used to represent the objects
are not visually confusable will allow us to attribute any related-
ness effects to conceptual, rather than picture-based, visual simi-
larity. We controlled for picture-based similarity in two ways.
First, as described above, in constructing the shape-related pairs,
we selected only those for which one of the objects could be
presented (and easily recognized) in a way that the other object
could not be represented (e.g., for the pair Frisbee–pizza, pizza can
be represented as a triangular slice, but a Frisbee cannot be
triangular). Second, we gathered picture-based visual similarity
ratings for all pairs. We return to these ratings, which were
collected in such a way as to take into account the experiment’s
design, after we introduce the design below.
Association between words in related pairs was very low ac-
cording to University of South Florida free association norms
We constructed initial lists
Table 1
Mean Relatedness Ratings for Pairs Used in Experiments 1 and 2
Condition
Number of
pairs
Shape
similarity
Function
similarity
Color
similarity
Manipulation
similarity
M SDM SDM SDMSD
Shape
Function
24
32
6.2
1.7
0.8
0.9
1.1
6.3
0.3
0.7
2.8
4.0
1.4
1.7
2.0
4.0
0.9
1.3
Note.
to how likely they are to be the same shape”; function: “Rate the following pairs of objects according to how
similar their functions (i.e., purposes) are”; color: “Picture the objects that the words refer to and rate them
according to how likely they are to be the same color”; manipulation: “Consider the typical movements you make
when you use these objects and rate how similar the movements are.”
Instructions were as follows: shape: “Picture the things that the words refer to and rate them according
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(Nelson, McEvoy, & Schreiber, 1998): For shape-related pairs,
average association equals 0.0% in both the forward and backward
directions (data were unavailable for five of our 24 shape pairs).
For function-related pairs, average forward association equals
0.3% and an average backward association equals 0.4% (data were
unavailable for 10 of the 32 function pairs). By comparison, in a
visual world paradigm study that did not attempt to minimize
association of semantically related pairs, association values were
much higher, with a mean forward association of 14.5% and
backward association of 12.7% (Yee & Sedivy, 2006).
Two lists, each 88 trials long, were created. Related object pairs
appeared together as target and related object on one list and as
objects unrelated to the target on the other (see Appendices A and
B). Each participant was presented with only one list so that no
participant saw or heard any object more than once. Figures 1A
and 1B show sample displays. A female speaker (Eiling Yee), in a
quiet room, recorded each target word in isolation. For the dis-
plays, we selected color line drawings from a commercial clip art
collection and from a collection based on the black-and-white
Snodgrass picture library (Rossion & Pourtois, 2004; based on
Snodgrass & Vanderwart, 1980).
Shape condition.
In the shape-related condition, one of the
objects in the display was related in shape to the target (e.g., pizza
was related in shape to the target Frisbee). As described above,
this shape-related object was represented in a shape in which the
target cannot be represented (e.g., pizza was presented as a trian-
gular slice, a shape that a Frisbee cannot take). The other two
objects (e.g., pitcher and thimble) were semantically and phono-
logically unrelated to the target. The name of one of these unre-
lated objects was matched for frequency with the shape-related
object (e.g., pitcher was frequency-matched with pizza). The name
of the other unrelated object was frequency-matched with the
target (e.g., thimble was matched with the target Frisbee). The
same displays that were used in the shape-related condition in
one list appeared in the shape-control condition on the other list
(and vice versa), but the target in the control condition was the
object that was frequency-matched with the target in the shape-
related condition (e.g., in Figure 1A, the target in the shape-control
condition was thimble). Average number of syllables and duration
of targets were also similar across shape-related and control con-
ditions (2.0 and 592 ms vs. 2.0 and 583 ms, respectively).
Because the same displays were used (between subjects) in both
the shape-related and the shape-control conditions, one of the
nontarget objects in the control condition served as the related
object in the shape-related condition. This made it possible to
determine whether the images that served as related objects drew
fixations regardless of their relationship to the target (e.g., because
the pictures were more inherently interesting than the others in the
display). Another benefit of this design was that in the control
condition, although two of the objects in the display were related
to each other (albeit in conceptual, not depicted, shape), neither
one was related to the target. Therefore, if any participants noticed
that some of the objects were related, they could not then predict
over the course of the experiment that the target would be one of
the related objects. Of the 88 total trials in each list, in 12 the target
was related in shape to one of the objects in the display, and in 12
two objects in the display were related to each other, but neither
one was the target. Of the remaining 64 trials, 16 were function
related and 16 were function-control (conditions described below),
and 32 were fillers in which no objects in the display were related
in any way. Object positions were balanced so that each object
type was equally likely to appear in each corner of the display.
Function condition.
The function condition was analogous to
the shape condition. In the function-related condition one of the
objects in the display was related in function to the target (e.g.,
glue was related in function to the target tape). The other two
objects were semantically and phonologically unrelated to the
target. Object names were frequency-matched in the same way as
in the shape condition. Likewise, as in the shape condition, the
same displays that were used in the function-related condition in
one list appeared in the function-control condition in the other list
(and vice versa), but the target in the control condition was the
Figure 1.
or tape) is related in shape or function to one of the other objects in the display (pizza or glue). The other two
objects are semantically and phonologically unrelated to the target and the related object.
Example displays from Experiments 1 and 2: shape (A) and function (B). The target word (Frisbee
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object that was frequency-matched with the target in the function-
related condition. Average number of syllables and duration of
targets were also similar (1.7 and 581 ms in related vs. 2.0 and 571
ms in control). Thus, of the 88 total trials in each list, in 16 the
target was related in function to one of the objects in the display,
and in 16 two objects in the display were related to each other in
function, but neither one was the target.
Picture-based visual similarity ratings.
1 provide a measure of how similar the conceptual representations
of the paired objects are on the attributes of interest. However,
because the objects were depicted as pictures, we must also be
concerned about picture-based visual similarity. Carefully control-
ling for picture-based visual similarity allows us to attribute any
relatedness effects to conceptual, rather than picture-based, visual
similarity. Although we took great care to avoid picture-based
visual similarity in the construction of shape-related pairs (as
described above, shape-related stimuli were limited to pairs in
which the competitor object could be presented in a way that the
target object could not be represented), in the interest of prudence,
we also gathered picture-based visual similarity ratings for both
the function- and the shape-related conditions.
We presented 24 participants (who did not participate in the
eye-tracking experiments) with the name of the target object from
either the related or the control condition and then the picture of
the related object or its control. For example, for the display that
included the shape-related pair Frisbee–pizza, we obtained visual
similarity ratings for the target-related object pair Frisbee–
pizza, the control target-related object pair thimble–pizza, and
the target-control object pair Frisbee–pitcher. The instructions
were as follows:
The ratings in Table
You will see a word on the screen. Form a mental image of the object
that the word refers to. Next you will see a picture. Rate the picture’s
shape according to how similar it is to the mental image you formed.
The word appeared on the screen for 1 s before the picture,
and both remained on the screen until the participant responded.
Ratings were from 1 (very different) to 7 (very similar). There
were three lists, and no participant saw any word or picture
more than once. Presentation order was randomized for each
participant.
For both the shape and the function conditions, picture-based
visual similarity ratings for targets and related objects were low
(means of 2.8 and 2.3, respectively, for shape and function),
indicating that the selected pairs of objects were not visually
similar. Problematically, though, ratings for control target-
related object pairs were even lower (1.2 and 1.3 for shape and
function, respectively), as were ratings for target-control object
pairs (1.3 for both conditions). Further, the difference between
the ratings for the related and the unrelated pairs was highly
significant (p ? .001) in both cases. To adjust for this disparity,
we use these ratings as covariates in our analyses. It is impor-
tant to note, however, that despite the instruction to perform the
ratings with respect to the shapes of the specific pictures being
displayed, it is possible that participants’ knowledge of a pair’s
conceptual (shape or function) similarity affected their ratings.
If true, these ratings overestimate the picture-based visual sim-
ilarity of related pairs, which would mean that including them
as a covariate is overly conservative. In other words, if long-
term knowledge about an object’s shape or function leaks into
the ratings, then when covarying these ratings out, some of the
effects of function or shape will be covaried out. Because there
is no perfect solution, in the text and figures we report the more
conservative data set, that is, with picture-based similarity
covaried out and for the subset of items for which picture-based
similarity was perfectly matched. For completeness, in Footnote
2, we also report results of analyses that do not include the
covariate.
Procedure. To ensure that participants knew what the pictures
were supposed to represent, they completed a picture-labeling
phase immediately before the eye-tracking experiment.
Picture labeling.
Each picture’s label appeared alone on the
screen for 300 ms before the picture appeared above the label.
After reading the label and looking at the picture, participants
pressed a key to go on to the next label and picture. All pictures
that would appear in the eye-tracking phase were presented, in-
cluding those from filler trials.
Eye tracking.
Participants were presented with a 3 ? 3 array
with four pictures on it, one in each corner (see Figure 1). Each cell
in the array was approximately 2 ? 2 in. (5.08 ? 5.08 cm).
Participants were seated at a comfortable distance (about 18 in.
[45.72 cm]) from a touch-sensitive monitor, with the monitor at
eye height. Therefore, each cell in the grid subtended about 6.4° of
visual angle. (The eye tracker is accurate to less than 1° of visual
angle.) One thousand milliseconds after the display appeared, a
sound file named one of the objects in the display. This exposure
duration was selected because pilot work with the same configu-
ration of objects suggested that 1,000 ms gives participants just
enough time to scan the objects. After the participant selected one
of the pictures by touching it on the screen, the trial ended and
the screen went blank. The experimenter continuously monitored
the calibration and recalibrated between trials as necessary. There
were two practice trials. Trial order was randomized for each
participant.
Eye movements were recorded starting from when the array
appeared and ending when the participant touched the screen to
select a picture. Only fixations that were initiated after target word
onset were included in the analyses (i.e., fixations that were
already ongoing at target word onset were not included). We
defined four regions, each corresponding to a 2 ? 2-in. (5.08 ?
5.08-cm) corner cell in the array. The EyeLink software parses the
eye movement data into fixations, blinks, and saccades. We de-
fined a fixation on a particular region as starting with the begin-
ning of the saccade that moved into that region and ending with the
beginning of the saccade that exited that region. (Therefore, any
region-internal saccades that occurred in the interim were counted
as part of a single fixation on that region.) As is customary in
visual world paradigm studies, the eyes had to remain on an object
for at least 100 ms for a fixation to be judged to have occurred.
Fixations under 100 ms were treated as continuations of prior
fixations.
Results and Discussion
We analyze the results of the shape and function conditions
separately for ease of exposition. Analyzing them separately
has another advantage: Although ratings of shape similarity for
shape pairs were very similar to ratings of function similarity
for function pairs, because the ratings are on different attri-
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butes, it may not be appropriate to equate them. Although we
ultimately include the two attributes in a single analysis, we
limit our interpretation to how they are differently impacted by
time, rather than comparing their relative sizes.
Shape.
In all trials the correct picture was selected. Seven
percent of trials did not provide any data because there were no eye
movements after the onset of the target word (most of these were
trials in which the participant was already fixating on the picture of
the target at word onset). For the remaining trials, we computed the
proportions (across trials) of fixations on each picture type (e.g.,
target, shape related, control) over time in 100-ms bins. Fixations
anywhere inside the cell that contained a picture were counted as
fixations on that picture. Fixation proportions more than 2.5 stan-
dard deviations from the mean (across subjects and items) for a
given time bin in a given condition were replaced with the mean of
the remaining fixation proportions for that bin of that condition
(3.5% by participants, 2.4% by items).
Figure 2A plots the mean proportion (over time) of fixations on
the shape-related object and on the same object in the shape-
control condition (for the picture-based similarity matched subset
of items [see below]). For the purpose of analyzing the data, we
defined a trial as starting at 200 ms after target onset (because it
takes an average of about 180 ms to initiate a saccade to a target
in response to linguistic input when the specific target is not
known ahead of time but the possible locations of the target are
known; Altmann & Kamide, 2004) and ending at the point at
which the probability of fixating on the target reached asymptote
(operationally defined as the first of two 100 ms bins in a row in
which looks to target increased by 1% or less). In these data the
end of the trial occurred at about 1,000 ms after target onset.
We submitted the binned data (the eight bins corresponding to
time slices 200–900 ms after target onset in Figure 2A) to a
repeated measures analysis of variance (ANOVA), with condition
(related or unrelated) and time bin as the repeated measures, and
with the picture-based visual similarity ratings difference between
the target-related object pair and the control target-related object
pair as the covariate. When the assumption of sphericity was
violated, a Geisser–Greenhouse correction was applied, in this and
all analyses reported in this article. (Main effects of time bin were
obtained in all the analyses that we report. This is unsurprising
because the heard word continues to unfold as eye movements are
recorded; hence eye movements in early bins reflect the processing
of only a small amount of the acoustic input, whereas eye move-
ments later in the trial converge on the target object. We therefore
limit our discussion to main effects of condition and to Condi-
tion ? Time interactions.)
This analysis revealed a significant effect of relatedness, with
more fixations on the shape-related object compared with the same
object in the control condition (related: M ? 0.090, SE ? 0.008;
control: M ? 0.065, SE ? 0.008), F(1, 21) ? 14.0, p ? .001,
?p
shape-related object and the control object as the conceptual shape
effect.) There was only a trend toward an effect of the picture-
based visual similarity covariate, F(1, 21) ? 2.9, p ? .10, ?p
.09. There was a Condition ? Time interaction, F(3.7, 78.1) ? 4.0,
p ? .01, ?p
in the middle time bins. We also measured the shape effect by
comparing fixations on the related object with fixations on the
control picture in the same display (M ? 0.060, SE ? 0.007). This
2? .29.1(We refer to this difference between fixations on the
2?
2? .12, reflecting that the effect of condition is larger
comparison yielded a very similar pattern: a conceptual shape
effect, F(1, 21) ? 8.5, p ? .01, ?p
effect of the picture-based visual similarity covariate, F(1, 21) ?
2.3, p ? .15, ?p
was not significant. Next, we tested whether the conceptual shape
effect also appeared in the subset of items (12 in the between-trial
comparison, eight in the within-trial comparison) for which
picture-based visual similarity was perfectly matched. These anal-
yses revealed the same pattern: There was a significant conceptual
shape effect when fixations on the shape-related object were
compared with the same object in a different trial (related: M ?
0.093, SE ? 0.010; control: M ? 0.056, SE ? 0.007), F1(1, 37) ?
10.5, p ? .01; F2(1, 11) ? 7.6, p ? .02, ?p
compared with the control object in the same trial (related: M ?
0.100, SE ? 0.013; control: M ? 0.047, SE ? 0.008), F1(1, 37) ?
10.4, p ? .01; F2(1, 7) ? 11.7, p ? .01, ?p
A posttest questionnaire explicitly asked whether participants
noticed any relationships between the objects in any of the displays
and, if so, what relationships were noticed. Responses indicated
that most participants (29 of 38) did not notice any relationships at
all. Nine participants did report noticing that some objects were
related (six noticed function, two shape, and one both), but the
pattern of results was unchanged when these participants were
removed from the analysis.
These results indicate that pictures of objects that are related in
shape to a heard word draw more fixations than pictures of
unrelated objects. Unlike the visual world paradigm shape effects
reported previously (Dahan & Tanenhaus, 2005; Huettig & Alt-
mann, 2007; Huettig & McQueen, 2007), the shape effect in this
study occurs when the shape-related object was depicted in a shape
that the target could not take. The control condition ruled out a
possible alternative explanation for the results; the same pictures
were fixated on more frequently when they were related to the
target in shape than when they were not related to the target,
indicating that the pictures we used to represent the shape-related
objects were not inherently more interesting than other pictures in
the display.
In the analyses described so far, shape similarity was treated as
a binary variable: Pairs were either similar (shape-related condi-
tion) or not (shape-control condition). However, one might predict
a more continuous relationship. We tested whether the degree of
shape relatedness (according to the conceptual shape-relatedness
ratings obtained during stimuli selection) was predictive of the
shape effect. The dependent variable was the average (over the
entire trial) probability of fixating on the shape-related object or its
control (in a different trial), and the predictor was the similarity in
(conceptual) shape of the target and the related object or control.
This regression revealed that after covarying out picture-based
visual similarity, F(1, 45) ? 1, conceptual shape similarity ratings
accounted for 16% of the variability in fixations on the shape-
related object relative to the control, F(1, 44) ? 8.3, R2? .16, p ?
.01. This relationship provides additional support for attributing
the preference for shape-related objects to their similarity in shape
with the target.
2? .34, and a nonsignificant
2? .11. The interaction of time with relatedness
2? .22; and also when
2? .22.
1Ratings for one shape-related object pair were not collected due to
experimenter error.
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The partial activation of the shape-related object demonstrates
that when searching for a named object, the (undepicted) concep-
tual shape of a shape-related object can divert visual attention.
Hence in a context that is similar to many real life scenarios, visual
attention can be diverted by long-term knowledge about an (oth-
erwise dissimilar) object’s typical shape. More generally, the par-
tial activation of the shape-related object is consistent with theories
of semantic memory that predict that objects that share shape
should have overlapping representations.
Function.
Data were analyzed in the same way as for the
shape condition. In all trials the correct picture was selected. Ten
percent of trials did not provide any data because there were no eye
movements after the onset of the target word (as for shape, most of
these were trials in which the participant was already fixating on
the target).
Figure 2B plots the mean proportion of trials across time that
contained a fixation on the function-related object and on the same
object in the function-control condition (for the picture-based
similarity matched subset of items). The repeated measures
ANOVA (as for shape, incorporating all items, and with picture-
based visual similarity as a covariate) revealed that when fixations
on the function-related object were compared with the same object
in the function-control condition (related: M ? 0.089, SE ? 0.007;
control: M ? 0.070, SE ? 0.006), the function effect was not
significant, F(1, 30) ? 1, and there was a significant effect of the
picture-based visual similarity covariate, F(1, 30) ? 6.9, p ? .01,
?p
compared with the control object in the same trial (M ? 0.055,
SE ? 0.006), however, the function effect was reliable, F(1, 30) ?
7.4, p ? .01, ?p
similarity covariate was not significant, F(1, 30) ? 1.5, p ? .23,
?p
with relatedness. As we did for shape, we also tested for a function
effect in the subset of items (19 in the between-trial comparison,
19 in the within-trial comparison) for which picture-based visual
similarity was perfectly matched. These analyses revealed the
same pattern: There was no function effect when function-related
objects were compared with the same object in a different trial
(related: M ? 0.076, SE ? 0.008; control: M ? 0.071, SE ? 0.007;
Fs ? 1), but there was an effect when fixations on the function-
2? .19. When fixations on the function-related object were
2? .19, and the effect of the picture-based visual
2? .05. In neither comparison was there an interaction of time
related object were compared with the control object in the same
trial (related: M ? 0.078, SE ? 0.008; control: M ? 0.051, SE ?
0.004), F1(1, 37) ? 9.6, p ? .01, ?p
.02, ?p
noticing that some of the objects were related had no effect on the
pattern of results.
Because the function-related object does not reliably draw more
fixations than the same object in a different trial, we must consider
the possibility that there is something more interesting about the
pictures we used to depict functionally related objects than the
distractor objects. However, it is also possible that the intrinsic
dependency between looks to the related object and the control
object in the same trial simply makes this within-trial comparison
more sensitive than the between-trial comparison. To help distin-
guish between these two possibilities, we tested whether (as for the
shape effect) the degree of function relatedness was predictive of
the function effect. If the source of the function effect is the
inherent interest of the pictures rather than function relatedness,
then the degree of function relatedness between the target and the
related picture should not predict the extent to which it is fixated.
As for shape, the dependent variable was the average probability of
fixating on the function-related object or its control (in a different
trial), and the predictor was the similarity in function of the target
and the related object or control. This regression revealed that after
covarying out picture-based visual similarity, F(1, 62) ? 3.3, R2?
.05, p ? .07, function similarity ratings accounted for only an
additional 2% of the variability in fixations on the function-related
object relative to control, F(1, 61) ? 1.5, R2? .02, p ? .23. This
suggests that factors other than similarity in function with the
target object may contribute to the preference to fixate on the
function-related object over the control object in the same display.
Given the observed shape-relatedness effect, the observation of
a weak (or even absent) function-relatedness effect is on the
surface a somewhat surprising result: Intuitively, tape and glue
seem more clearly related than Frisbee and pizza. However, one
account for the apparent weakness of the function effect is that, as
hypothesized in the introduction, function information becomes
available later than shape information. Our initial assumption was
that any time course difference would lead to differences in the
timing of function- and shape-relatedness effects within a trial. Yet
2? .21; F2(1, 18) ? 6.4, p ?
2? .26. Excluding the nine participants who reported
Figure 2.
over time on the (A) shape- or (B) function-related object versus the same object in the control condition (when
it is not related to the target).
Experiment 1 (1,000-ms exposure), picture-based similarity matched items. Proportion of fixations
7
FUNCTION FOLLOWS FORM

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if we consider our earlier account of what leads to semantic effects
in the visual world paradigm, it is clear that activation of function
information about both the displayed function-related object and
the heard target word is required to observe function-relatedness
effects. This raises the possibility that being exposed to the four
objects for only 1,000 ms prior to the target word (leaving, on
average, only 250 ms for each object—and that is before consid-
ering the duration of saccades between objects) may not have been
long enough for function information about all the objects to
become detectably active.
That a function-relatedness effect would eventually emerge
seems especially plausible because prior studies that explored
nonspecific semantic relatedness in the visual world paradigm did
include pairs that we would define as function related and did
observe relatedness effects (e.g., Huettig & Altmann, 2005; Yee &
Sedivy, 2006). Importantly, however, in these prior studies the
exposure durations were longer than 1 s (but cf. Huettig & Mc-
Queen, 2007, which we return to in the General Discussion).
Experiment 2
The goal of Experiment 2 was to test whether, during object
identification, information about an object’s function becomes
active after (long-term conceptual) knowledge about its shape. We
therefore lengthened the amount of time that the display appears
prior to hearing the target word, hypothesizing that this manipu-
lation may allow us to measure the activation of the objects at a
time when function information is more prominent, leading to a
function effect.
Method
The method was identical to that in Experiment 1 except that
the display appeared for 2,000 ms (rather than 1,000 ms) before
the sound file naming one of the objects was played. A different
set of 38 male and female undergraduates from the University
of Pennsylvania participated. We chose a 2,000-ms exposure
duration because pilot work using the same configuration of
objects indicated that function relatedness would be detectable
with this timing.
Results and Discussion
Shape.
Seven percent of trials did not provide any data because there were
no eye movements after the onset of the target word.
Figure 3A plots the mean proportion of trials over time that
contained a fixation on the shape-related object and on the same
object in the shape-control condition (for the picture-based simi-
larity matched subset of items). The repeated measures ANOVA
revealed that the effect of shape relatedness was not reliable
(related: M ? 0.076, SE ? 0.009; control: M ? 0.058, SE ?
0.008), F(1, 21) ? 2.8, p ? .11, ?p
of the picture-based visual similarity, F(1, 21) ? 1. There was also
no interaction of time with relatedness. When fixations on the
shape-related object were compared with the control object in the
same trial (M ? 0.069, SE ? 0.006), the pattern was the same:
The shape effect was not significant, F(1, 21) ? 1.3, p ? .27,
?p
covariate, F(1, 21) ? 1, and there was no interaction of time with
relatedness. As before, we also analyzed the subset of items for
which picture-based visual similarity ratings were perfectly
matched. This analysis showed the same pattern: When fixations
on the shape-related object were compared with the same object in
the function-control condition (related: M ? 0.071, SE ? 0.007;
control: M ? 0.052, SE ? 0.008), the shape effect was only
marginally significant by subjects, F1(1, 37) ? 3.8, p ? .06, ?p
.09, and was not significant by items, F2(1, 11) ? 1.9, p ? .20,
?p
control object in the same trial (related: M ? 0.066, SE ? 0.009;
control: M ? 0.045, SE ? 0.007), F1(1, 37) ? 3.2, p ? .08, ?p
.08; F2(1, 7) ? 1.4, p ? .28, ?p
1, we tested whether the degree of shape relatedness was predictive
of the shape effect. This regression revealed that after covarying
out picture-based visual similarity, F(1, 45) ? 1, conceptual
shape similarity ratings accounted for 7% of the variability in
fixations on the shape-related object relative to the control, F(1,
44) ? 3.4, R2? .07, p ? .07.
These analyses reveal that in contrast to Experiment 1, in which
there was a strong conceptual shape effect, in Experiment 2 the
In all shape trials the correct picture was selected.
2? .11, and there was no effect
2? .06, nor was the effect of the picture-based visual similarity
2?
2? .14. The same pattern appeared in the comparison to the
2?
2? .16. Finally, as in Experiment
Figure 3.
over time on the (A) shape- or (B) function-related object versus the same object in the control condition (when
it is not related to the target).
Experiment 2 (2,000-ms exposure), picture-based similarity matched items. Proportion of fixations
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YEE, HUFFSTETLER, AND THOMPSON-SCHILL

Page 10

effect of conceptual shape is not statistically significant. We con-
sider reasons for this difference in the General Discussion.
Function.
Five trials (0.4%) were not included in the analysis
because the wrong picture was selected. Eight percent of trials did
not provide any data because there were no eye movements after
the onset of the target word.
Figure 3B plots the mean proportion of trials across time that
contained a fixation on the related object and on the same object
in the function-control condition (for the picture-based similar-
ity matched subset of items). The repeated measures ANOVA
revealed that when fixations on the function-related object were
compared with the same object in the function-control condition
(related: M ? 0.096, SE ? 0.006; control: M ? 0.067, SE ?
0.005), there was a significant effect of function relatedness,
F(1, 30) ? 8.5, p ? .01, ?p
picture-based visual similarity covariate, F(1, 30) ? 1. There
was also a significant interaction of relatedness with time,
F(3.9, 117.7) ? 4.1, p ? .01, ?p
relatedness effect was larger in the middle time bins. Similarly,
when fixations on the function-related object were compared
with a different object in the same trial (M ? 0.050, SE ?
0.006), there was a significant effect of function relatedness,
F(1, 30) ? 22.0, p ? .01, ?p
based visual similarity covariate, F(1, 30) ? 1; and a significant
2? .22, and no effect of the
2? .12, reflecting that the
2? .42; no effect of the picture-
interaction of relatedness with time, F(2.9, 87.8) ? 2.9, p ?
.04, ?p
appeared in the subset of 19 items for which picture-based
visual similarity ratings were perfectly matched. This analysis
revealed the same pattern: The function effect remained signif-
icant when fixations on the function-related object were com-
pared with the same object in a different trial (related: M ?
0.096, SE ? 0.010; control: M ? 0.065, SE ? 0.007), F1(1,
37) ? 9.4, p ? .01, ?p
.28; and when they were compared with the control object in the
same trial (related: M ? 0.081, SE ? 0.007; control: M ?
0.035, SE ? 0.005), F1(1, 37) ? 26.7, p ? .01, ?p
18) ? 23.2, p ? .01, ?p
Finally, we tested whether the degree of function relatedness
was predictive of the function effect. This regression revealed that
after covarying out picture-based visual similarity, F(1, 62) ? 3.1,
R2? .05, p ? .08, function similarity ratings accounted for an
additional 12% of the variability in the fixations on the function-
related object relative to the control, F(1, 61) ? 9.1, R2? .12, p ?
.01. This relationship provides further evidence that the preference
for the function-related object was due to its similarity in function
with the target. Figure 4 displays the scatterplots from the regres-
sions when using function or (conceptual) shape similarity ratings
to predict the probability of fixating on objects (after covarying out
2? .09. We also tested whether the function effect
2? .20; F2(1, 18) ? 6.9, p ? .02, ?p
2?
2? .42; F2(1,
2? .56.
Figure 4.
the probability of fixating on the object (after covarying out picture-based visual similarity) for Experiment 1 (A,
B) and Experiment 2 (C, D). Each point is an item, averaged across subjects.
Relationship between the rated conceptual similarity between target and related or control object and
9
FUNCTION FOLLOWS FORM

Page 11

picture-based visual similarity) for Experiment 1 (Figures 4A and
4B) and Experiment 2 (Figures 4C and 4D).
It is important to note that the function effect cannot be ex-
plained by participants’ noticing that objects in the display were
occasionally related and therefore strategically attending to them.
There are several reasons for this. First, when the target was
unrelated to two function-related objects in the same display, these
related objects were not preferentially fixated. Second, the same
posttest questionnaire used in Experiment 1—which explicitly
asked whether participants noticed any relationships between the
objects in the displays and, if so, how often and what—indicated
that most participants (29 of 38) were completely unaware of the
manipulation. Nine participants did report noticing that some ob-
jects were related (seven noticed function, one shape, and one
both), but the pattern of results was unchanged with these partic-
ipants removed. Importantly, these numbers were almost identical
to those obtained in Experiment 1 (six function, two shape, one
both), and yet Experiment 2 produced a completely different
pattern. Third, because any strategy would not be expected to have
an influence in the experiment’s initial trials (before participants
had an opportunity to notice that objects were sometimes related),
we tested whether the magnitude of the function effect increased as
the experiment proceeded by dividing the function-related condi-
tion into four quartiles (containing four items each). We found no
effect of trial order, F(3, 111) ? 1.2, p ? .32, ?p
effect: Q1? .06, Q2? .02, Q3? .04, Q4? .05).
Experiment 2 shows that when searching for a named object,
visual attention is drawn to objects that share its purpose. This
suggests that objects that have similar functions have overlapping
representations. In contrast to Experiment 1, in Experiment 2 the
effect of function remains robust across all comparisons.2The
difference between the two experiments suggests that, at least in
this context, information about an object’s function may become
available after information about its form. In the next section, we
describe the crucial test of the hypothesis that these two effects are
dissociable; namely, we test the interaction of attribute and expo-
sure duration.
2? .03 (function
Comparing the Time Course of Function and Shape
Experiments 1 and 2 differed only in the amount of time that the
displays were available prior to the presentation of the target word,
yet we observed complementary patterns for function and shape in
these two experiments. Specifically, the shape effect was reliable
in all comparisons in Experiment 1 but not in any in Experiment 2.
The function effect, in contrast, was reliable in only one compar-
ison in Experiment 1 but was reliable in all comparisons in
Experiment 2.
To address the critical question of whether exposure duration
has reliably different effects on the activation of shape and func-
tion information, we conducted an ANOVA on the shape and
function effects (i.e., the difference between related and control
objects averaged across the entire trial) in the subset of items that
were perfectly matched for picture-based visual similarity. When
shape and function effects were computed relative to the same
object in the control condition, this test revealed no effect of
exposure duration or attribute (all Fs ? 1). Importantly, however,
there was a significant interaction between exposure duration and
attribute, F1(1, 74) ? 3.9, p ? .05; F2(1, 29) ? 5.8, p ? .02. Hence
these analyses indicate that shape and function effects were reli-
ably different at the two exposure durations (see Figure 5). The
same analysis was conducted on shape and function effects com-
puted relative to the control object in the same trial. Results were
the same: no effect of exposure duration or attribute (Fs ? 1) but
an interaction between exposure duration and attribute, F1(1,
74) ? 5.0, p ? .03; F2(1, 25) ? 7.7, p ? .01. Pairwise compar-
isons indicated that, as Figure 5 suggests, this interaction was
driven by the shape effect decreasing with a longer exposure
2We repeated all analyses without including the picture-based visual
similarity covariate. The pattern of results remained the same except that
when the covariate was not included, the relatedness effects were stronger
for function in Experiment 1 and (less so) for shape in Experiment 2. (If
picture-based similarity did direct some amount of visual attention to
related objects, it is unsurprising that relatedness effects would be larger
when picture-based shape is allowed to play a role. Moreover, because the
function-related pairs were not expressly created to control for picture-
based shape, it may have artificially increased the size of the function effect
in particular. Further, given that shape similarity effects appear to occur at
shorter exposures, the increase might be expected to be largest in the
short-exposure condition.) In Experiment 1, for shape, there was a signif-
icant conceptual shape effect when fixations on the shape-related object
were compared with the same object in the control condition (related: M ?
0.084, SE ? 0.006; control: M ? 0.066, SE ? 0.005), F1(1, 37) ? 6.2, p ?
.02; F2(1, 23) ? 7.7, p ? .01; and also when fixations on the related object
were compared with fixations on the control picture in the same display
(M ? 0.061, SE ? 0.006), F1(1, 37) ? 6.7, p ? .01; F2(1, 23) ? 6.1, p ?
.02. For function in Experiment 1, there was a significant function effect by
subjects when fixations on the function-related object were compared with
the same object in the control condition and a marginally significant effect
by items (related: M ? 0.086, SE ? 0.008; control: M ? 0.066, SE ?
0.006), F1(1, 37) ? 5.9, p ? .02; F2(1, 31) ? 4.2, p ? .05. When fixations
on the function-related object were compared with the control picture in the
same display (M ? 0.054, SE ? 0.004), the effect of function was
significant by both subjects and items, F1(1, 37) ? 14.7, p ? .001; F2(1,
31) ? 15.8, p ? .001. In Experiment 2, for shape, by subjects there was a
significant conceptual shape effect when fixations on the shape-related
object were compared with the same object in the control condition
(related: M ? 0.079, SE ? 0.006; control: M ? 0.056, SE ? 0.006), F1(1,
37) ? 12.0, p ? .001, but by items this difference only approached
significance, F2(1, 23) ? 2.9, p ? .10. There was no effect when fixations
on the shape-related object were compared with the control picture in the
same display (M ? 0.069, SD ? 0.005), F1(1, 37) ? 1.8, p ? .19; F2(1,
23) ? 1. For function in Experiment 2, there was a significant function
effect when fixations on the function-related object were compared with
the same object in the control condition (related: M ? 0.098, SE ? 0.007;
control: M ? 0.067, SE ? 0.005), F1(1, 37) ? 15.3, p ? .001; F2(1, 31) ?
14.2, p ? .001; and also when fixations on the function-related object were
compared with fixations on the control picture in the same display (related:
M ? 0.098, SE ? 0.007; control: M ? 0.050, SE ? 0.006), F1(1, 37) ?
43.7, p ? .001; F2(1, 31) ? 34.4, p ? .001. Testing the interaction between
exposure duration and attribute revealed that when compared with the same
object in the control condition, the interaction was not significant, F1? 1;
F2(1, 54) ? 1.2, p ? .27. However, when compared with the control
picture in the same display, the interaction between exposure duration and
attribute approached significance by subjects, F1(1, 74) ? 3.3, p ? .08, and
was significant by items F2(1, 54) ? 5.4, p ? .02. Hence, even when
differences between exposure durations are presumably dampened (due to
disproportionate augmentation of the short-exposure function effect), the
interaction pattern between exposure duration and attribute noted in the
main text is still present.
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duration and the function effect increasing: for shape, same trial
control object comparison, t(7) ? 3.0, p ? .02, and same object
control trial comparison, t(11) ? 1.6, p ? .14; for function, same
trial control object comparison, t(18) ? 2.2, p ? .045, and same
object control trial comparison, t(18) ? 2.3, p ? .03. Importantly,
the presence of an interaction in the absence of a main effect of
exposure duration (i.e., in the absence of a main effect of partic-
ipant group) also mitigates the potential concern that differences
between the two experiments could have been due to accidental
baseline differences between participant groups.
General Discussion
In two experiments, we used the visual world paradigm to
investigate the activation of two semantic features during object
recognition: one perceptual (shape) and one abstract (function).
Because we explicitly manipulated the attribute that the target and
the related object shared, we were able to explore the activation of
these attributes independently. We observed relatedness effects for
both shape and function. However, these two attributes have
different time courses of activation. Below we discuss the theo-
retical and methodological implications of these findings.
Why Does Function Follow Form?
Why do we observe what appears to be a difference between the
activation time courses of shape and function information, with
shape information becoming less prominent over time and function
information becoming more prominent? One possibility is that
conceptual knowledge that is built from information that can be
directly perceived through an individual sense is represented dif-
ferently than conceptual knowledge that must be acquired through
a more complex process. For instance, in recent years numerous
studies have demonstrated that sensory and motor brain regions
that are active when perceiving or interacting with an object also
become active when conceiving of it, particularly when thinking
about its perceptual features (see Thompson-Schill, 2003, for a
review). This suggests that long-term perceptual knowledge may
be encoded in (or near) sensorimotor brain regions. More abstract
information (such as an object’s function, i.e., purpose of use), on
the other hand, cannot be directly perceived through any individual
sense, leading some theories to posit that abstract information
is stored in brain regions that integrate information over multiple
sensory modalities (e.g., Patterson, Nestor, & Rogers, 2007). If
similar neural substrates support both sensory and conceptual
shape, then viewing an object may activate its conceptual shape
relatively directly; in contrast, higher level attributes such as
purpose might be activated more indirectly, and hence more
slowly, during object recognition. Notably, when there is less
overlap of sensory input and conceptual shape (e.g., when access-
ing concepts from written words rather than images), form might
not precede function information. In the next section we describe
data from the semantic priming paradigm that suggests that chang-
ing the access modality may indeed alter form’s activation.
But why then does shape become less active later? One possi-
bility is that although apprehending a triangular piece of pizza, for
example, will initially activate other conceptual information about
pizzas, including their roundness, the direct perceptual information
received about the (triangular) sensory shape allows it to win out
over the conflicting (round) conceptual shape. A related possibility
is that the time course difference between function and shape
indicates the existence of competition between semantic features,
perhaps due to limitations in our ability to maintain the activation
of numerous semantic features about multiple objects simultane-
ously. If true, shape may rapidly decay (or be inhibited) in favor of
function because though shape is critical for recognizing an object,
once an object is recognized, other attributes, such as what it is
used for, are typically more relevant (after recognizing that the
thing across the room is pizza, what is usually relevant next is what
one wants to do with it). In fact, this kind of account would suggest
that the features that will become more prominent over time are
whatever features (abstract or perceptual) are typically more rele-
vant once the object at hand has been recognized. Hence, although
function may be critical for many man-made objects, there are also
objects for which shape is likely to be more important. Indeed, for
some animals (e.g., starfish) it is hard to identify a function as we
define it here. If a feature’s importance affects its time course of
activation, for objects such as starfish conceptual shape activation
may remain prominent. This suggests that a fruitful topic for future
research will be to manipulate task relevance, as well as to explore
how task relevance interacts with the relative informativeness of
features for individual objects.
The Role of Context
The accounts raised above have a common feature: They as-
sume that when identifying objects, the extent to which a particular
type of information is activated may be contextually dependent,
either on short-term, task-related factors (i.e., how relevant is
conceptual shape for the current task?) or on long-term, object-
related factors (i.e., is shape relevant in general for identifying this
object?), or on some combination of both. The idea that there is a
role for context (which we define broadly to include not only what
the participant is currently attending to but also the stimulus by
which the concept is accessed, and the goals of the participant)
raises an important question. Did conceptual shape information
(whatever its time course) become active because it is a compul-
sory component of concept retrieval or because shape information
is essential for the task of visual object identification? That is, did
Figure 5.
(i.e., the difference between related and control objects, averaged across
the entire trial), picture-based similarity matched items. Shape effect de-
creases over time, whereas function effect increases.
Interaction of time with shape- and function-relatedness effects
11
FUNCTION FOLLOWS FORM

Page 13

conceptual shape precede function in our study because of the
modality through which the concepts were retrieved?
To address this question, we turn to related work using the
semantic priming paradigm. A small number of priming studies
have tested whether responses to a written target word are facili-
tated when preceded by a shape-related prime word. An influential
early set of priming studies (Flores d’Arcais, Schreuder, & Gla-
zenborg, 1985; Schreuder et al., 1984; cf. Taylor, 2005) did obtain
evidence of shape priming. Of interest, this work also included
abstractly related prime-target pairs and found evidence that ab-
stract priming emerges more reliably at long than at short inter-
stimulus intervals, whereas perceptual priming was larger at short
than long interstimulus intervals (Flores d’Arcais et al., 1985;
Schreuder, 1985). This may indicate that because perceptual in-
formation is dominant during the extremely frequent behavior of
object recognition, it has developed a default early time course.3
However, these early studies were criticized on methodological
grounds (Moss, Ostrin, Tyler, & Marslen-Wilson, 1995; Pecher,
Zeelenberg, & Raaijmakers, 1998). When they were repeated with
more standard methodology, only one study reported priming for
perceptually related pairs (Taylor, 2005), and others found no
priming (Kellenbach, Wijers, & Mulder, 2000; Pecher et al., 1998,
Experiments 1, 2, 3, and 5; but see below). The difficulty of
detecting shape priming thus suggests that task relevance does play
a role in the activation of shape information: When conceptual
shape information is not relevant to the task at hand (e.g., when
reading or performing lexical decisions), it is extremely difficult to
detect behaviorally (but it may still be active; two studies record-
ing event-related brain potentials did obtain a perceptual priming
effect in N400s; Kellenbach et al., 2000; Taylor, 2005). Signifi-
cantly, one priming study (Pecher et al., 1998, Experiments 4 and
6) provided further evidence of the importance of context: If, prior
to a priming task, participants first made perceptual judgments
about the objects to which the words referred, shape priming was
subsequently observed.
One of the visual world paradigm studies discussed earlier also
speaks to the role of context. In Huettig and McQueen (2007)
effects of semantic and shape relatedness (e.g., looks to an image
of a kidney or a straw upon hearing arm) that were observed when
displays contained only pictures were not observed when these
pictures were replaced with printed words. Instead visual attention
was drawn only to printed words that overlapped phonologically
with the spoken word (e.g., the printed word artichoke, upon
hearing arm), presumably because matching auditory to written
words emphasizes phonological information. (Notably, this study
also varied the duration of prior exposure to the display, and
although this had no influence when the visual display contained
printed words, with pictures semantic-relatedness effects were
robust at the longer exposure duration but not reliable at the shorter
exposure duration—consistent with our own findings.) These data
support Pecher et al.’s (1998) suggestion that “what features of a
word are activated is not static, but instead can be dynamically
affected by the context in which the word occurs” (p. 415).
Context dependence can also include sensitivity to properties of
copresent stimuli. In our studies, a triangular slice of pizza, for
example, was present in the context of a round Frisbee. It is
conceivable that the roundness of the Frisbee, being directly avail-
able, enhanced the activation of the conceptual roundness of the
pizza. Such priming could explain why conceptual shape appeared
to become available more quickly than conceptual function. Yet,
regardless of whether the conceptual shape of the pizza is en-
hanced by the shape of the Frisbee, the fact remains that the pizza’s
conceptual shape becomes less active over time, following a dif-
ferent trajectory than its function. Hence our results demonstrate
that even with a static visual context, the features of a concept that
are active are not static. It remains to be seen whether the time
courses of these features can be influenced by the context of the
other objects in the display.
Earlier, when discussing reasons for why conceptual shape
information may become less accessible over time, we suggested
that this might reflect the dynamically changing aims of object
identification, with shape becoming less relevant as object identi-
fication proceeds and function becoming more relevant. But unlike
shape, function was not required for performing the task we
employed. Therefore, the fact that we nonetheless observed func-
tion effects may indicate that the activation of function information
is a compulsory (rather than context-dependent) component of
visual object recognition. However, if our task were even more
shape-centric (e.g., picking out objects on the basis of their shapes
rather than their names), perhaps shape activation would persist,
and the function effect would never emerge (or would be weaker).
Such context effects would support Pecher et al.’s (1998) claim
and would also be consistent with those that have been demon-
strated in research on sentence comprehension showing that, for
example, if pizza is mentioned in a sentence about delivering it,
one might access how heavy it is (cf. Barclay, Bransford, Franks,
McCarrell, & Nitsch, 1974). They would also be consistent with
the more recently demonstrated compatibility effects in which
sentence context (e.g., Glenberg & Kaschak, 2002), or even the
context provided by an individual word (van Dam, Rueschemeyer,
Lindemann, & Bekkering, 2010), influences the kind of action
information that is activated by subsequent language. A benefit of
a semantic memory architecture that allows attention to be focused
on specific features is that activation can be dynamic; such an
architecture therefore naturally accommodates effects that are sen-
sitive to the task at hand (see Patterson et al., 2007).
Implications for the Organization of Semantic
Memory
The coactivation of objects sharing shape or function is consis-
tent with models in which semantic memory is organized such that
objects that share these features have overlapping representations.
The observed time course difference between shape and function
also has implications for the organization of semantic knowledge.
First, because the features follow different time courses of activa-
tion, it suggests that shape and function are distinct components of
semantic knowledge. Although we have suggested that the time
course differences we observed are due to differences in the
features themselves (or their relevance in a given context), another
possibility is that the differences are due to the specificity of the
features. It has been proposed by Rogers and Patterson (2007) that
semantic memory is organized such that specific information about
3Compare Moss, McCormick, and Tyler (1997), who explored the time
course of perceptual and abstract relationships but defined these relation-
ships somewhat differently.
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Page 14

an object (information that can distinguish among objects in the
same semantic neighborhood; e.g., the property “yellow” distin-
guishes between lemons and limes) becomes available later than
more general information (information that does not help in dis-
tinguishing among objects in the same neighborhood; e.g., the
property “can be eaten” is shared by most fruit). It is interesting,
however, that the patterns that we observed for function and shape
do not appear to be consistent with the specificity hypothesis: We
find that the arguably more specific feature, shape, becomes avail-
able earlier than the arguably more general feature, function. The
time course differences we observed, therefore, appear to be due to
the content of the features (or perhaps the interaction of that
content with the task at hand), rather than their usefulness for
distinguishing between semantic neighbors.
Because shape is a sensorimotor feature, the findings for shape
in particular provide important evidence for one of the predictions
of sensorimotor-based distributed models of semantic memory: If
one’s knowledge of objects is distributed across a set of semantic
features that are situated in the neural substrates that are respon-
sible for perceiving and interacting with these objects (e.g., All-
port, 1985; Barsalou, 1999; Warrington & McCarthy, 1987), then
the conceptual representations of objects that share a perceptual
feature such as shape must have overlapping representations. Yet,
until now, behavioral evidence in support of this prediction has
been scarce. In contrast to shape, information about an object’s
purpose is unlikely to be a unitary sensorimotor-based feature;
although function information is related to an object’s shape, size,
and the way it is manipulated, an object’s function cannot reliably
be predicted from any individual perceptual feature. Thus, the
finding for function demonstrates that representations cannot be
entirely sensorimotor based. Most sensorimotor theories, however,
do suggest that more abstract, higher order relationships (e.g.,
function) can either be represented in an amodal association area
or emerge as a result of similarity between multiple sets of features
(e.g., Damasio, 1989; Humphreys & Forde, 2001; Rogers et al.,
2004; Simmons & Barsalou, 2003).
We have discussed our results in the context of distributed
models because these models very naturally accommodate the
findings. However, there are alternative models of semantic mem-
ory. One prominent alternative is the domain-specific category-
based model (Caramazza & Shelton, 1998). According to this
model, concepts are represented according to a few innately spec-
ified categories (e.g., animals, fruits and vegetables, conspecifics,
and tools) that have evolutionary significance, and objects from
different categories (e.g., Frisbees and pizzas) have distinct, non-
overlapping representations. Because we observed relatedness ef-
fects for shape-related pairs that contained items from different
categories (20 of 24 pairs are indisputably cross-category, and the
pattern of results is unchanged when the remaining four pairs are
removed), the current results are inconsistent with this category-
based model. A recent elaboration of this model (e.g., Mahon &
Caramazza, 2003) is partially distributed in that it allows for
representations to be distributed over different sensory modalities.
However, within each modality, the representations of different
categories (e.g., tools and food) remain distinct. Hence even this
partially distributed category-based model would be inconsistent
with the shape-based cross-category coactivation that we observed
in Experiment 1. To accommodate the cross-category shape effect
under a category-based account would require positing an addi-
tional (extrarepresentational) process that operates across catego-
ries. However, such an explanation would be difficult to reconcile
with the fact that the shape effect emerges prior to the predomi-
nantly within-category function effect and becomes smaller over
time. If additional processing were responsible, one would expect
the shape effect to grow over time. A category-based model
therefore appears incompatible with the pattern we observed. An-
other alternative to distributed models is a localist model in which
activation spreads over propositional (i.e., featural) links between
concepts (e.g., “is round” or “sticks things together”). A version of
the model that allows for different propositions to be activated
over different time courses (e.g., Collins & Loftus, 1975) would be
consistent with the time course differences we observed. However,
to fully accommodate the current findings, such a model would
also need to posit that information contained in these links can also
deactivate over different time courses. Note that if these compo-
nents (connections that explicitly represent featural information
and that have distinct time courses of activation and deactivation)
are assumed, the predictions of localist and distributed models
essentially converge.
Methodological Implications
That there were differences between the results of Experiments
1 and 2 has methodological implications for using the visual world
paradigm to study semantic relatedness. As the differences be-
tween Experiments 1 and 2 demonstrate, there is no logical neces-
sity for all the information required to observe semantic-
relatedness effects to be available when one begins to observe a
preference for the target. This means that if a particular semantic
attribute is slow to become active, and the amount of time provided
to view the objects is short, then there is no reason to expect a
relatedness effect based on that particular attribute. Therefore,
when relying on relatedness effects to reveal the activation of
specific semantic attributes, it may be necessary to vary exposure
duration to obtain a full picture of their activation. Hence the visual
world paradigm can provide information about both the activation
dynamics of objects in the display and the processing of the heard
word, but the processing that can be detected at a given time is
limited by their shared activation. This is an important method-
ological implication, because most prior researchers have not
considered that preview time may critically influence the visual
world paradigm’s sensitivity to different relatedness effects.
Conclusions
The present findings suggest that during object identification,
long-term knowledge about an object’s perceptual (shape) and
abstract (function) features becomes active along different time
courses, with function following form. The fact that these two
components of semantic knowledge can have distinct time courses
demonstrates that semantic memory is organized such that they are
at least partially independent. Further, the coactivation of shape- or
function-related objects suggests that semantic memory is orga-
nized such that concepts that share these features have overlapping
representations. The observed coactivation of shape-related objects
from different categories is difficult to reconcile with a category-
based model (e.g., Caramazza & Shelton, 1998). Instead the find-
ings for shape are easy to accommodate in models that suggest that
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FUNCTION FOLLOWS FORM

Page 15

object meanings are represented (at least in part) as distributed
patterns of activation because these models allow for independent
activation. The findings for function (an abstract feature that
cannot be directly observed through a single sensory modality)
make it clear that models of semantic memory must include a
mechanism for representing abstract as well as sensorimotor-based
features (see Patterson et al., 2007, for a review). Finally, the
results demonstrate that conceiving of an object is a dynamically
unfolding process in which the meaning of an object evolves as
object identification proceeds.
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