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Visual Fixation Patterns During Viewing of Naturalistic Social Situations as Predictors of Social Competence in Individuals With Autism
Ami Klin, PhD;
Warren Jones, BA;
Robert Schultz, PhD;
Fred Volkmar, MD;
Donald Cohen, MD
Arch Gen Psychiatry. 2002;59:809-816.
ABSTRACT
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Background Manifestations of core social deficits in autism are more pronounced
in everyday settings than in explicit experimental tasks. To bring experimental
measures in line with clinical observation, we report a novel method of quantifying
atypical strategies of social monitoring in a setting that simulates the demands
of daily experience. Enhanced ecological validity was intended to maximize
between-group effect sizes and assess the predictive utility of experimental
variables relative to outcome measures of social competence.
Methods While viewing social scenes, eye-tracking technology measured visual
fixations in 15 cognitively able males with autism and 15 age-, sex-, and
verbal IQ–matched control subjects. We reliably coded fixations on 4
regions: mouth, eyes, body, and objects. Statistical analyses compared fixation
time on regions of interest between groups and correlation of fixation time
with outcome measures of social competence (ie, standardized measures of daily
social adjustment and degree of autistic social symptoms).
Results Significant between-group differences were obtained for all 4 regions.
The best predictor of autism was reduced eye region fixation time. Fixation
on mouths and objects was significantly correlated with social functioning:
increased focus on mouths predicted improved social adjustment and less autistic
social impairment, whereas more time on objects predicted the opposite relationship.
Conclusions When viewing naturalistic social situations, individuals with autism
demonstrate abnormal patterns of social visual pursuit consistent with reduced
salience of eyes and increased salience of mouths, bodies, and objects. Fixation
times on mouths and objects but not on eyes are strong predictors of degree
of social competence.
INTRODUCTION
ADVANCES IN psychological research of the core social deficits in autism
have increasingly focused on disruptions in early-emerging skills that seem
to derail the processes of socialization.1
Typically developing infants show preferential attention to social rather
than inanimate stimuli,2 and they also prefer
to focus on the more socially revealing features of the face, such as the
eyes rather than the mouth3; in contrast, individuals
with autism seem to lack these early social predispositions.4-8
This attenuation to the social world is accompanied by documented abnormalities
in face perception, both in face recognition and in identification of facial
expressions.9-12
In addition, individuals with autism use atypical strategies when performing
such tasks, relying on individual pieces of the face rather than on the overall
configuration.5, 8 Alongside these
perceptual anomalies, individuals with autism have deficits in conceiving
other people's mental states (in having a "theory" that other people have
minds and then using this knowledge to predict their social behavior).13
Although these findings offer specific hypotheses for the profound impairment
in social adjustment exhibited by individuals with autism, there is no performance-based
method for directly quantifying the impact of these underlying processes on
social functioning in everyday situations. For an individual with autism,
the real world is fraught with social challenges and ambiguities that are
largely minimized within the narrow parameters of experimental situations.
Individuals with autism encounter greater difficulty when trying to spontaneously
impose social meaning onto what they see than they do when solving explicit
tasks.14 This is particularly evident in cognitively
able individuals, who may use their visual-perceptual or language abilities
to scaffold their performance, thus achieving relatively high scores on a
given task but doing so in ways that differ from normative strategies.15 This hypothesis was recently substantiated in a neurofunctional
study16 of face perception in autism in which
adequate task performance was accompanied by abnormal ventral temporal cortical
activity, which in turn suggested that participants had "treated" faces as
objects.
The development of more naturalistic paradigms that capitalize on the
challenging nature of open-ended social scenarios for individuals with autism
could result in several advantages. First, the effect size of between-group
findings may increase, bringing experimentally measured abnormalities in autism
to a level more commensurate with clinical observations of social impairment.
Second, by placing a performance-based method into the context of naturalistic
social functioning, there is increased likelihood that the experimental method
will better predict level of social competence. Abnormal performance on social
tasks in autism is typically reported as a group finding relative to a control
sample, with little attempt to use the given measure as a predictor of level
of social adjustment or of level of social impairment. The lack of quantifiable
indices of social competence that could define a spectrum of social outcomes,
from normality to varying manifestations of autism, hinders genetic and neurofunctional
research, which partially rely on such indices for interpretation of heritability
and neuroimaging data.17-18
To create an experimental paradigm to measure social functioning in
a context that more closely resembles social demands in naturalistic situations,
we used eye-tracking technology to study spontaneous viewing patterns of cognitively
able individuals with autism and age- and verbal IQ–matched control
subjects. Previous work19-20 has
used static images to assess aspects of face scanning; to our knowledge, this
is the first study of eye tracking as a dynamic phenomenon. The paradigm involves
viewing digitized videotape clips of complex social situations while wearing
a noninvasive eye-tracking device that superimposes the viewer's point of
regard onto the viewed scenes. The resultant videotape can then be coded for
patterns of visual fixation that can be measured in terms of percentage of
viewing time spent on different aspects of the social scenes. For this exploratory
study, several lines of research guided our decision as to the scheme to use
for coding fixations. First, we were interested in the relative salience of
major components of the viewed scenes.4, 8, 14-15
Thus, we divided the total on-screen area into face, body, and object regions.
Second, given the research results suggesting that individuals with autism
have difficulty interpreting social information conveyed through the eyes,6-7 and that they focus preferentially
on mouths when performing face perception tasks,5
we subdivided the face into an eye region and a mouth region. The resultant
coding scheme, therefore, consisted of 4 clearly delineated viewing areas
of interest: mouth, eye, body, and objects (see the "Coding Procedures" subsection
for further details). We were also interested in exploring the relationship
between patterns of visual fixation and outcome measures of social competence.
We operationalized social competence in terms of level of real-life social
adjustment (as defined by scores on the socialization domain of the Vineland
Adaptive Behavior Scales, Expanded Edition [VABS-E]21)
and in terms of degree of autistic social symptoms (as defined by the social
domain of the Autism Diagnostic Observation Schedule [ADOS]22).
Whereas the VABS-E provides a measure of social ability (higher scores mean
higher levels of social adjustment), the ADOS provides a measure of social
impairment (higher scores mean higher levels of autistic social behaviors).
On the basis of the extant literature, we expected that individuals
with autism would preferentially focus on the mouth region rather than on
the eye region and on objects relative to controls. In addition, given the
normative pattern of preferentially using information gathered from the eyes
to understand others, we also predicted that within the autistic group, higher
percentage of viewing time on the eye region would be positively correlated
with level of social adjustment and negatively correlated with level of social
impairment.
PARTICIPANTS AND METHODS
PARTICIPANTS
Fifteen male adolescents and young adults with autism were recruited
through a large, federally funded research project on the neurobiology of
autism carried out in the developmental disabilities section of the Yale Child
Study Center. This project includes a 3-day protocol consisting of extensive
diagnostic, neuropsychological, neuroimaging, and genetic studies. Before
participation, all individuals or their legal guardians supplied written informed
consent. The protocol was approved by the Human Investigations Committee of
the Yale University School of Medicine. Diagnoses were assigned on the basis
of parental interview (Autism Diagnostic Interview–Revised23)
and direct observations of participants' social and communicative behaviors
(ADOS22). All participants with autism met DSM-IV24 diagnostic criteria
for autistic disorder as operationalized through standardized algorithms derived
from the Autism Diagnostic Interview–Revised and the ADOS. Intellectual
level was measured using the Wechsler Intelligence Scale for Children25 or the Wechsler Adult Intelligence Scale.26 All 15 participants with autism were cognitively
able and yet severely impaired in their social functioning, as measured using
the VABS-E19: a discrepancy of more than 3.5
SD was obtained between their verbal IQ and standard scores on the socialization
domain of the VABS-E (see Table 1
for a summary of participant characterization data). Participants with autism
were individually matched for chronological age and verbal IQ with a comparison
group of 15 adolescents and young adults recruited from the community and
screened for history of major neurological or psychiatric illness. Given the
typical variability in IQ profile in individuals with autism and the resultant
complications when making decisions on matching procedures in studies of social
functioning,27-28 we adopted what
is thought to be the most stringent approach to matching on the basis of verbal
IQ rather than full-scale IQ. None of the participants had visual acuity deficits
uncorrectable with eyeglasses.
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Table 1. Participant Characterization Data*
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DIGITIZED VIDEOTAPE CLIPS OF COMPLEX SOCIAL SITUATIONS
All participants watched 5 digitized clips from the 1967 film version
of Edward Albee's "Who's Afraid of Virginia Woolf?" This movie was chosen
because it displays the intense interaction of 4 protagonists involved in
a content-rich social situation likely to maximize viewers' monitoring of
each person's socially expressive actions as well as those characters' reactions
to the actions of others. The demanding social complexity in the movie mirrors
complicated social situations that individuals with autism may encounter in
everyday settings, such as a high-school cafeteria. This movie is also depleted
of nonessential objects and events that might distract a viewer's attention
from the social action. The clips ranged in length from 30 to 60 seconds depending
on the content and duration of each chosen scene. The clips were separated
from one another by 5 seconds of blank screen.
APPARATUS
Eye tracking was accomplished using a dark pupil-corneal reflection
video-oculography technique and hardware and software created by ISCAN Inc
(Burlington, Mass). The system was head mounted and used a novel target-tracking
method that enabled highly accurate eye tracking without having to restrain
the participant's head (accuracy within ±0.3° over a ±20°
horizontal and vertical range). The eye-tracking video equipment was mounted
unobtrusively on the bill of a baseball cap. The participant's left eye was
illuminated by a small, nonharmful infrared light–emitting diode. The
movements of this eye were filmed using miniature imaging optics and a dichroic
mirror. To obtain a frontal image of the eye without interfering with the
participant's view, the eye-imaging camera was mounted in the bill above,
facing downward and aimed at the angled dichroic mirror. The mirror, positioned
in front of and below the eye, acted as a bandpass filter, reflecting infrared
wavelengths (and thereby reflecting a frontal image of the participant's left
eye) while transmitting wavelengths of the visible spectrum (allowing the
participant a clear field of view). Directly underneath this mirror and in
line with the eye-imaging optics was a miniature camera capped by a red additive
filter. This camera filmed the scene in front of each participant. As the
eye camera tracked movements of the pupil and corneal reflection, the scene
camera recorded images of the participant's field of view. In a rectangular
configuration around the computer screen were 5 red light–emitting diodes
(1 at each of the screen's corners and 1 at the midpoint between the 2 upper
corners) that provided reference points by which image-processing hardware
(using data from the scene camera, aided by the red color filter mentioned
previously) could identify the position and orientation of the "scene plane"
even within a shifting field of view. In this way, the coordinates of the
plane of the computer screen could be continuously tracked (and then calibrated
with respect to the coordinates of the point of regard) despite any head or
body movements. Eye-tracking data were fed from the cameras through ISCAN
hardware at a rate of 60 samples per second and were recorded to videotape
at the standard rate of 30 frames per second.
EXPERIMENTAL SETTING AND PROCEDURES
Participants sat in a comfortable armchair, 63.5 cm from a 48.3-cm computer
screen mounted flush within a black wooden panel. The eye-tracking baseball
cap was adjusted for participant comfort and clarity of view, and a brief
calibration routine followed (consisting of having each participant look at
a series of 5 points). Lights in the room were dimmed so that only images
displayed on the screen could be easily seen, and the audio component was
played through a set of concealed speakers. Data recording began after each
participant reported an adequate level of comfort, an unobstructed view of
the screen, and a clearly audible soundtrack.
CODING PROCEDURES
Following each recording session, the videotape data were digitized
and archived on computer. Five videotape clips lasting a total of 2 minutes
42 seconds were coded for each participant. Each frame of video was coded
(30 frames per second, 4860 frames per participant). Figure 1 exemplifies a still image used for coding. For this illustration,
the points of regard of 2 participants (1 with autism and 1 control) are superimposed
onto a single frame. In practice, only one participant's data were coded at
a time by 2 raters who were blind to the diagnosis and identity of each participant.
Kappa coefficients29 and percentages of agreement
were calculated to assess interrater reliability, with  of 0.82 and
agreement of 87.2%, indicating "excellent agreement."30
Each rater also recoded approximately 20% of the scenes chosen at random after
at least 2 weeks. Test-retest reliability results were = 0.91 (agreement,
95.2%) and = 0.86 (agreement, 91.3%) for the 2 coders, indicating
excellent levels of coding stability.
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Figure 1. Representative still frame used
for coding of visual fixation patterns. The data of 2 participants are superimposed
on a single frame for the purpose of illustration; the focus of the view with
autism is marked in green and that of the typically developing viewer (control)
is in yellow. Coordinate data shown in the inset correspond to the typically
developing viewer's point of regard.
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For each frame, the location of a participant's point of regard was
coded as follows: a designation of "0" was assigned when the participant focused
on the mouth region of the face, "1" was recorded when he focused on the eye
region of the face, "2" was given when he focused on the body, and "3" was
recorded when he focused on an object. In the event that a participant's point
of regard was directly on the border between any 2 regions of interest, the
3 frames before and the 3 frames immediately after the frame in question were
evaluated. The frame was then coded in accordance with the region into which
the point of regard moved during the 7-frame sequence. To minimize such circumstances,
region-of-interest resolution was maximized: only those shots in which the
on-screen dimensions of the character's head were greater than or equal to
5° of the participant's field of view could be coded (this was the basis
for selecting the 2 minutes 42 seconds of codable videotape data from the
5 clips shown to each participant; long-range shots were excluded). This criterion
was used to ensure validity of the eye-tracking data coding, particularly
in relation to coding of the eye vs the mouth region (if an on-screen head
is smaller than 5° of the visual field, the system's margin of error is
large enough to potentially cause notable discrepancies in the coding of facial
feature preference). Finally, several scenes were discarded because there
were no actors facing the camera or because the actors, the camera action,
or both moved too rapidly for meaningful analysis of preferential viewing
patterns.
Some frames that were coded could not be coded as fixation data. These
included frames in which a participant blinked or made a saccadic shift. Blinks
were defined by a loss of point-of-regard coordinate data (which was superimposed
along with time code at the bottom of each picture) and then further verified
by an inset videotaped image of the participant's eye (in such a case revealing
closed lids). Initiation and completion of saccadic movements were defined
by a rotational velocity threshold of 30° per second,31
which translated in our experimental setting into a linear velocity of 15
or more pixels per frame (ie, d 15 pixels, where d =  (x2) + (y2), over the course of 1 frame [33 milliseconds]).
Saccadic movements were also confirmed by the inset eye image. In addition,
some frames could not be coded for the following reasons: off-screen fixations
(watches, hands, etc), rubbing of eyes, and obstruction of the scene view
camera (hand in front of face, nose rubbing, etc). These frames, recorded
as "no data," amounted to a mean (SD) 5.2% (6.6%) of total time for controls
and 15.6% (15.9%) of time for viewers with autism (P
= .03). Although this significant difference could be related to decreased
concentration and increased distractibility in participants with autism, we
cannot infer any specific conclusions from this statistical difference because
other, non–attention-related factors could also be at play, including,
for example, rubbing the eyes or sneezing. Future studies will need to pay
more attention to coding schema for characterization of lost data.
STATISTICAL ANALYSES
T tests with Bonferroni corrections for number
of between-group comparisons were used to test group differences in the percentage
of total viewing time spent on fixations on mouth, eye, body, and object regions
of the scene images. Pearson correlations were used to explore the degree
of the relationship between fixation patterns and the 2 measures of social
competence—level of social adjustment (operationalized as the age-equivalent
score on the socialization domain of the VABS-E) and degree of autistic social
impairment (operationalized as the total algorithm score on the social section
of the ADOS).
RESULTS
Consistent with our predictions, individuals with autism focused 2 times
more on the mouth region, 2 times less on the eye region, 2 times more on
the body region, and 2 times more on the object region relative to age- and
verbal IQ–matched controls (Table
2). Effect size was greatest for fixation on the eye region, making
it the best predictor of group membership (d = 3.19).
There were no significant correlations between any of the measures of fixation
time and chronological age or verbal IQ in the 2 groups except for a positive
significant correlation between percentage of fixation time on the mouth region
and age in the group with autism (r = 0.62; P = .01). When one outlier (a participant with autism aged
38 years) was removed from the sample, this correlation was no longer significant.
None of the other correlations were altered by excluding this person. As shown
in Figure 2, there was little overlap
in the measures of fixation time across the 2 groups, although there was some
variability within the groups, except for fixation on objects in the control
group.
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Table 2. Percentage of Viewing Time Spent Focused on Mouth, Eyes, Body,
and Object Regions*
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Figure 2. Box plot comparison of visual
fixation time on mouth, eyes, body, and object regions for 15 viewers with
autism and 15 typically developing viewers (controls). The upper and lower
boundaries of the standard boxplots are at the 25th and 75th percentiles.
The horizontal line across the box marks the median of the distribution, and
the vertical lines below and above the box extend to the minimum and maximum,
respectively.
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We next explored the association between fixation time measures and
measures of social competence. Contrary to our expectation, fixation time
on the eye region was not associated with either social adaptation (VABS-E
socialization scores) or social disability (ADOS social scores) (r = -0.20 and r = 0.14, respectively).
In contrast, fixation times on the mouth region (Figure 3) and on the object region (Figure 4) were strong predictors of social competence, albeit in
different directions. Fixation time on the mouth region was associated with
greater social adaptation (ie, more socially able) and lower autistic social
impairment (ie, less socially disabled). Going in the opposite direction,
fixation time on the object region was associated with lower social adaptation
and greater autistic social impairment. Fixation time on the body region followed
the same trend as for the object region, but the correlations were not significant
(r = -0.49 and r =
0.34 for social adaptation and social disability, respectively). When the
outlier (a participant with autism aged 38 years) was excluded from correlational
analyses, none of the measures of association were altered except the positive
correlation between fixation time on objects and the measure of social adaptation,
which was previously significant at P<.10 and
was now significant at P<.05.
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Figure 3. Correlation of mouth fixation
time and outcome measures of social adaptation (A) and social disability (B)
in 15 viewers with autism. VABS-E indicates Vineland Adaptive Behavior Scales,
Expanded Edition; ADOS, Autism Diagnostic Observation Schedule.
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Figure 4. Correlation of object fixation
time and outcome measures of social adaptation (A) and social disability (B)
in 15 viewers with autism. VABS-E indicates Vineland Adaptive Behavior Scales,
Expanded Edition; ADOS, Autism Diagnostic Observation Schedule.
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COMMENT
We found significant differences in percentages of visual fixation time
on mouth, eye, body, and object regions when viewing naturalistic social situations
among cognitively able adolescents and young adults with autism relative to
age- and verbal IQ–matched controls. The best predictor of group membership
was percentage of fixation time on the eye region: the control group visually
fixated on the eye region 2 times more than did the group with autism, and
there was no overlap in the distribution of results. However, within the group
with autism, this variable was unrelated to outcome measures of social competence.
In contrast, percentages of fixation time on the mouth and object regions
were strong predictors of social competence measures, with higher mouth fixation
time associated with higher levels of social adaptation and lower levels of
autistic social impairment, and object fixation time associations going in
the opposite direction.
This study shows the utility of developing performance-based paradigms
capable of quantifying social functioning under more naturalistic conditions.
The effect sizes obtained for between-group comparisons were markedly larger
relative to experimental studies32 of social
functioning in autism and more comparable to the few studies14
available that focused on spontaneous responses rather than explicit problem-solving
tasks. Similarly, the enhanced ecological validity aimed for in the present
study also led to stronger associations between performance-based experimental
measures and outcome measures of social competence, an important goal to be
achieved in the search for dimensional endophenotypes for genetic research.17 More generally, the paradigm presented herein provides
a valuable window into the ways individuals with autism search for meaning
when confronted with complex social situations.
Given that this is the first study of its kind, comparisons with other
studies can only be indirect. Nevertheless, the small number of available
studies is generally supportive of our findings. For example, some studies
have suggested increased reliance on mouths rather than eyes when individuals
with autism are required to perform face perception tasks,5-6
great difficulty in "reading" the meaning of eye expressions,7
and increased orientation to objects relative to people.4, 8
A recent study by Joseph33 addressed the differential
reliance on eyes and mouths in autism more directly than previous studies.
When 10- to 12-year-old, cognitively able individuals with autism were asked
to perform a match-to-sample face recognition task in which faces varied as
a function of eye or mouth changes, they exhibited a selective advantage for
mouths.
Although the present study was not designed to explore the factors underlying
visual fixation patterns in autism, the strong predictive association between
mouth and object, but not eye fixations and outcome measures of social competence,
suggests that specific hypotheses need to be pursued in future, more-refined
studies. The finding that a higher percentage of mouth fixation time predicted
a higher level of social competence is as intriguing as it is counterintuitive,
and, therefore, it deserves special attention. Given the well-known association
between level of verbal skills and better outcome in autism,34
it is possible that the participants in our study were focusing on mouths
because that is where speech comes from. By concentrating their efforts on
something that they can understand, they might attain better understanding
of social situations. Nevertheless, such a compensatory strategy is not without
its limitations given that the meaning of language is often modified by nonverbal
social cues such as eye expressions. The fact that percentage of time focused
on eyes was unrelated to measures of social competence suggests the possibility
that for individuals with autism, looking at eyes does not accrue considerable
advantages in their efforts to understand social situations, or, in other
words, that the eyes are not meaningful to them.7, 34
The hypothesis that increased fixation on mouths results from concentration
on speech needs to be further refined on the basis of what we know about visual
attention to facial regions in speech perception tasks.35
Whereas audiovisual speech perception (like the stimuli in the present study)
draws gaze toward the talker's eyes,36 speech
reading (ie, seeing someone speak with no accompanying audio) is more likely
to draw gaze toward the talker's mouth.37 However,
visual fixations in speech reading depend on the nature of the task. If participants
are asked to perform a segmental speech perception task (ie, to guess what
the talker is saying), the viewer is more likely to focus on the mouth region.36-38 However, if participants
are asked to perform a prosodic speech perception task (ie, to guess the inflection
of the talker's voice, eg, sad, happy, or mad), then the viewer is more likely
to focus on the upper region of the face (eyes and eyebrows).37
On the basis of this literature, our visual fixation results could suggest
that our participants were not only focusing on the verbal content of speech
but were also ignoring paralinguistic cues such as prosody,39
which are usually essential to understanding nonliteral aspects of social
situations such as intentions and attitudes.40
In other words, our findings could be related to the overreliance of individuals
with autism on the literal aspects of speech at the expense of intonational
cues associated with social meaning.41 By pairing
speech perception tasks with eye-tracking measures,37
these relationships are likely to be clarified.
Another line of inquiry for future studies relates to the possibility
that increased fixation on mouths and decreased fixation on eyes indicate
that individuals with autism may acquire a degree of perceptual expertise
on mouths but not on eyes. Findings of the previously described study by Joseph33 seem to point in this direction. When the face recognition
task was presented in the form of inverted faces, children with autism did
not show the typical decrement in performance42
(the so-called inversion effect43) in the eye
condition, but did so in the mouth condition. Given that an increase in the
magnitude of the inversion effect and associated transition from feature-based
to configural processing marks the development of perceptual expertise relative
to a class of objects,44-47
the findings of Joseph raise the possibility that children with autism have
expertise when recognizing faces that vary in mouth features but not when
they vary in eye features. Future studies that could manipulate these variables
more explicitly in still (ie, photographs) and dynamic (ie, videotape) stimuli
might clarify these issues. Also, given the recent surge of neuroimaging research
on the brain circuitry involved in the acquisition of perceptual expertise,47 the coregistration of neurofunctional and eye-tracking
data might prove to be particularly useful in elucidating the unusual patterns
of behavioral and brain functioning in regard to face perception in autism.16, 18, 48
A final line of inquiry suggested by our results concerns the need to
explore the association between more fixation time on objects and decreased
social competence in participants with autism. This finding is consistent
with the notion that focus on objects means reduced salience of social stimuli4, 15 and, therefore, decreased likelihood
of understanding the social situation. The percentage of fixation time on
objects was small relative to fixation time on the face (mouth and eyes).
This is not surprising given that our videotape clips were deliberately chosen
to minimize inanimate distractions. Future studies may maximize the predictive
utility of the association between fixation on objects and outcome measures
of social competence by manipulating the prominence of inanimate stimuli (eg,
by making objects move or by using objects known to attract the attention
of individuals with autism). Clinical observations have shown the devastating
impact of object-rich environments on the ability of children with autism
to focus on socially meaningful aspects of educational environments.49
The present study has several limitations. First, although close to
three quarters of all individuals with autism have a degree of mental retardation,50 we studied more cognitively able individuals with
autism. We do not know if these results will extend to participants with lower
IQs. Neither do we know what trends to expect in younger children with autism
or in individuals with milder manifestations of the condition (eg, Asperger
syndrome and Pervasive Developmental Disorder–Not Otherwise Specified
[also called "atypical autism"]). Second, our design does not rule out possible
contributions from abnormal functioning in areas other than social visual
pursuit (eg, underlying attentional or perceptual abnormalities).51-52 The use of more traditional eye-tracking
protocols focused on the integrity of brain mechanisms associated with eye
movement53 alongside our novel application
of this technology will be necessary to rule out explanations other than the
ones explored in this study. Third, although the measures reported in this
study were informative, they are unlikely to be the most sensitive indicators
of abnormalities in social visual pursuit in autism. In a case study reported
elsewhere,54 we illustrate a series of social
visual tracking phenomena that seem to capture the abnormalities in autism
in a much more dynamic and stark fashion than summaries of visual fixation
times. The moment-by-moment visual traces left behind by the saccadic movements
and fixations of individuals with autism illustrate more vividly their atypical
attempts to create social meaning out of what they see. Perhaps paradigms
capable of quantifying the subtleties of such data will soon emerge from these
as-yet only heuristic approaches.
AUTHOR INFORMATION
Submitted for publication June 14, 2001; final revision received October
10, 2001; accepted October 24, 2001.
This work was partly supported by grants P01 HD 03008 and P01 HD/DC35482
from the National Institute of Child Health and Human Development, Bethesda,
Md, and by a grant from the National Alliance for Autism Research, Princeton,
NJ.
This study was presented in part at the annual meeting of the National
Institute of Child Health and Human Development, Collaborative Projects of
Excellence in Autism, New Haven, Conn, May 2, 2001.
We thank the participants and their families; Elizabeth Levitan, BA,
Tammy Babitz, MA, Sanno Zack, BA, Catalina Hooper, BA, Amy Augustyn, BA, and
Christopher Abildgaard, BA, for their assistance with this study; and Katarzyna
Chawarska, PhD, for her contribution to interpretation of findings. We also
thank Warner Bros, Elizabeth Taylor, George Segal, and the estates of Sandy
Dennis and Richard Burton for permission to use their images.
This article is dedicated to the memory of our mentor, collaborator,
and colleague, Donald Cohen, MD, whose legacy embodies the best in clinical
services, public advocacy, clinical science, bioethics, and mentoring.
Corresponding author and reprints: Ami Klin, PhD, Yale Child Study
Center, 230 S Frontage Rd, New Haven, CT 06520 (e-mail: ami.klin{at}yale.edu).
From the Yale Child Study Center, Yale University, New Haven, Conn.
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