Visual social attention in autism spectrum disorder: Insights from eye tracking studies

Accepted Manuscript Title: Visual social attention in Autism Spectrum Disorder: insights from eye tracking studies Author: Quentin Guillon Nouchine Hadjikhani Sophie Baduel Bernadette Rog´e PII: DOI: Reference:

S0149-7634(14)00068-2 http://dx.doi.org/doi:10.1016/j.neubiorev.2014.03.013 NBR 1919

To appear in: Received date: Revised date: Accepted date:

22-2-2013 15-3-2014 22-3-2014

Please cite this article as: Guillon, Q., Hadjikhani, N., Baduel, S., Rog´e, B.,Visual social attention in Autism Spectrum Disorder: insights from eye tracking studies, Neuroscience and Biobehavioral Reviews (2014), http://dx.doi.org/10.1016/j.neubiorev.2014.03.013 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

VISUAL SOCIAL ATTENTION IN ASD

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Visual social attention in Autism Spectrum Disorder: insights from eye tracking studies

URI Octogone-CERPP, University of Toulouse, 5 allée Antonio Machado, 31058 Toulouse

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Quentin Guillona *, Nouchine Hadjikhanib,c, Sophie Baduela, and Bernadette Rogéa

Cedex9, France

Harvard Medical School / MGH / MIT, Martinos Center for Biomedical Imaging, Building

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Gillberg Neuropsychiatry Center, Gothenburg University, Sweden

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75, 3rd Avenue, Charlestown, MA 02129, USA

E-mail addresses: [email protected], [email protected], [email protected], [email protected]

* Corresponding author: Tel: +335 61 50 24 25; e-mail: [email protected]

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Abstract We review different aspects of visual social attention in autism spectrum disorders (ASD) from infancy to adulthood in light of the eye-tracking literature. We first assess the

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assumption that individuals with ASD demonstrate a deficit in social orienting together with decreased attention to socially relevant stimuli such as faces compared to TD individuals.

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Results show that social orienting is actually not qualitatively impaired and that decreased

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attention to faces does not generalized across contexts. We also assess the assumption that individuals with ASD demonstrate excess mouth and diminished eye gaze compared to TD

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individuals. We find that this assumption receives little support across ages and discuss some factors that might have initially lead to this conjecture. We report that the assessment of the

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ability to follow the direction of another person's gaze needs to be further examined and that eye-tracking studies add to the evidence that individuals with ASD demonstrate difficulties in

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interpreting gaze cues. Finally, we highlight innovative data acquisition and analyses that are

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increasingly shedding light on the more subtle nature of the profound social difficulties

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experienced by individuals with ASD.

Keywords: autism spectrum disorder; autism; eye-tracking; visual social attention

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Visual social attention in Autism Spectrum Disorder: insights from eye tracking studies

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1. Introduction There has been an explosion of eye tracking studies in autism spectrum disorders (ASD)

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during the last decade, partly due to the increase of unobtrusive eye-tracking systems

accessibility (Sasson and Elison, 2012), and also because eye-tracking technology offers a

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direct measure of visual social attention (Frank et al., 2012; Klin et al., 2002a). Visual social attention refers to the overt attentional bias to orient to and look at other people, notably their

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face and eyes, as well as to where they direct their attention (Birmingham and Kingstone, 2009; Birmingham et al., 2008). Of particular interest to researchers are how individuals with

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ASD orient to and engage attention to faces, as well as how they visually explore faces and whether they make use of gaze information. One of the core symptoms of ASD is indeed the

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presence of early and persistent deficits in social interaction and social communication, and

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individuals with ASD experience difficulties in establishing and maintaining eye contact as

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well as in processing others’ facial information and intentions to regulate social interactions (APA, 2013).

Visual social attention in ASD has been investigated in many different ways depending primarily on the age of participants, but also on the specific aspect of visual social attention to be studied. For instance, retrospective analyses of home videotapes have provided a direct and ecological measure of social orienting to faces in infants. However, this methodology has some important limits, including great variations in settings and poor accuracy in the spatial and temporal domains for estimating what exactly the infant is looking at and for how long (Zwaigenbaum et al., 2007). In contrast, computerized laboratory experiments have provided indirect measures of the different aspects of visual social attention in older populations with a

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better temporal and spatial precision, but at the expense of ecological validity (e.g., Moore et al., 2012; Rutherford et al., 2007). In that context, eye-tracking technology has a number of advantages for investigating

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visual social attention in ASD. It allows researchers to measure with high precision and accuracy what a participant is looking at and for how long, and it offers the optimal balance

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between ecological validity and methodological constraints. Eye tracking is thus a unique

method to detect and characterize the subtle variations in the spontaneous viewing patterns of

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individuals with ASD (Klin et al., 2002a; Klin et al., 2003). Moreover, eye-tracking

technology can be used with virtually all population, from infants to adults, regardless of their

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level of non-verbal and verbal functioning. This means that the different aspects of visual social attention can be investigated in similar ways across ages and participants. In addition,

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eye-tracking technology provides measures more closely related to the social phenotype of

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1.1. Aims of the present paper

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individuals with ASD than conventional tasks (Klin et al., 2002a).

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The main purpose of the present paper is to systematically review eye-tracking studies that have examined the different aspects of visual social attention in ASD from infancy to adulthood and to highlight new opportunities given by eye tracking technology to further investigate visual social attention in ASD (readers interested in eye tracking in young children with autism can also refer to Falck-Ytter et al., 2013). We start by reviewing eye-tracking studies providing insight into the ability of individuals with ASD to initially orient to (attention-orienting or attention-getting mechanism) and subsequently engaged attention (attention-holding mechanism, see Cohen, 1972) towards social stimuli. A number of authors have indeed posited that the socio-communicative deficits encountered by individuals with ASD could primarily result from a failure to orient and engage attention to socially relevant stimuli such as faces early in life (Dawson et al., 2005;

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Elsabbagh et al., 2011; Johnson, 2005; Sasson, 2006; Schultz, 2005). Results from retrospective analyses of home videotapes for instance, indicate that infants later diagnosed with ASD orient less frequently towards people and faces during the first two years of life

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(Maestro et al., 2002; Mars et al., 1998; Osterling and Dawson, 1994; Osterling et al., 2002). Prospective studies of high-risk infants and studies of young children have also documented

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reduced social orienting, both in response to social bids (Dawson et al., 1998; Leekam et al.,

2000; Leekam and Ramsden, 2006) and spontaneously (Ozonoff et al., 2010; Swettenham et

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al., 1998), as well as reduced gaze duration towards others (Bhat et al., 2010, Swettenham et al., 1998). In older populations, results from well-controlled experimental tasks suggest that

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faces do not attract the attention of high functioning individuals with ASD to the same extent as that of typically developing (TD) individuals (Moore et al., 2012; Kikuchi et al., 2009;

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Riby et al., 2012). Altogether, these results suggest that individuals with ASD from an early age demonstrate a deficit in social orienting and decreased attention to socially relevant

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stimuli such as faces compared to TD individuals. We assess this assumption in light of the

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objects and social contexts.

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eye tracking literature and further discuss the results in terms of the influence of competing

We next turn to the way individuals with ASD visually explore faces. In one previous review of eye tracking studies in ASD, Falck-Ytter and von Hofsten (2011) examined the postulate that individuals with ASD exhibit excess mouth/diminished eye gaze compared to TD individuals. This view is indeed partly supported by the face-processing literature showing that high functioning individuals with ASD have difficulties to discriminate the eyes and rely preferentially on mouth information to process faces (Joseph & Tanaka, 2003; Rutherford et al., 2007; Spezio et al., 2007; Wolfe et al., 2008). It has also been supported by one of the first eye-tracking studies in ASD (Klin et al., 2002b). Yet, Falck-Ytter and von Hofsten (2011) concluded that this assumption could not be generalized across ages and contexts. Notably, they found little evidence of excess mouth/diminished eye gaze in children

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and only partial evidence in older population. Since this initial review, several papers have been published, extending the age of participants and providing additional information with regards to the complex interrelationship between face scanning, phenotypic features and

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contexts. We reexamine the assumption of excess mouth and diminished eye gaze in ASD in light of this new literature and further discuss the role of phenotypic features and stimuli

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content in causing the discrepancies initially noted by Falck-Ytter and von Hofsten (2011). The third aspect of visual social attention we examine refers to the attentional bias for

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people to follow others’ gaze/head-turn direction and to make use of this information (Birmingham and Kingstone, 2009; Fletcher-Watson et al., 2008; Langton et al., 2006;

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Langton et al., 2000). In young children with ASD, several studies have suggested that the ability to follow the gaze of another person is impaired. A prospective study of infants at risk

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for ASD reported deficits in gaze following abilities at 15 months, as indicated by a lower accuracy with which these infants located the gazed-at object compared to a group of low risk

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infants (Yoder et al., 2009). During the preschool period, children with ASD are also less

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likely to correctly orient towards the target (Chawarska et al., 2003; Dawson et al., 2004;

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Leekam et al., 2000). With age however, results become less consistent among individuals with ASD and verbal mental age appears to have a moderating effect on gaze/head following. For instance, in 8 year-old children, gaze/head-turn following was found relatively preserved for those with verbal mental age over 48 months, while for those with a lower verbal mental age, gaze/head-turn following was impaired (Leekam et al., 1998). Eye tracking technology has been successfully used to investigate gaze following performance in TD children and adults (Fletcher-Watson et al., 2008; Gredebäck et al., 2008; Senju and Csibra, 2008; von Hofsten et al., 2005) and there are now several studies that have examined this ability in individuals with ASD. We review these studies and highlight how eye tracking technology enables a more detailed analysis of gaze/head-turn following characteristics in ASD and provides additional measures of the referential understanding of another person’s gaze.

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The use of eye tracking technology not only provides an alternative way to investigate visual social attention but also enables researcher to tackle new topics that were left unexplored with other methodologies. In this paper, we also present studies investigating how

properties of stimuli) impact gaze behaviors of individuals with ASD.

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individuals with ASD monitor social interaction and how bottom-up influences (i.e., low level

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Finally, we consider the limits of current eye-tracking systems for studying visual social attention and discuss preliminary studies that have used an alternative eye-tracking system.

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First, we provide the reader a brief introduction to eye-tracking technology (for a comprehensive review of eye tracking technology and methodology see Holmqvist et al.,

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2011).

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1.2. Eye-tracking technology

Most of the eye-trackers used to record gaze behaviors for studying the different aspects

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of visual social attention are non-invasive, remote table-mounted video-based eye-tracking

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systems. These systems rely on the pupil/corneal reflection technique for estimating the point

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of gaze (POG). Typically, an invisible infrared light source directed to the eyes creates reflection patterns that are subsequently captured via optical sensors. The sampling rate of the optical sensors ranges from 50 to 500 Hz. Contrary to the pupil reflection, which moves along with gaze displacement, the corneal reflection remains relatively stable and can therefore be used as the reference marker to estimate gaze location. Once the geometrical center of both reflections is estimated, via sets of image-processing algorithm, the gaze location can be computed based on the position of the center of the pupil reflection relative to the center of the corneal reflection. To map the gaze location onto the viewing scene coordinates (i.e., the screen monitor), a calibration is carried out prior to the eye-tracking test. The calibration procedure consists of fixating points of known coordinates in the viewing scene. The eye-tracking software then

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applies a function to transform the absolute gaze location into the scene-viewing x and y coordinates system and finally generate output gaze data file. This file provides raw data samples, which basically consist of the x-y coordinates of every measured POG with

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associated timestamp, pupil size and validity code. Outcome measures can then be computed through a fixation detection algorithm, which aims to detect oculomotor events from raw data

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sample (Salvucci and Goldberg, 2000). However, some concerns may arise when applying

these fixation detection algorithms to data from infants, toddlers or preschoolers. Accuracy

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can indeed be lower in these populations due to head movements and less exhaustive calibration. Raw gaze data are also more likely to contain periods during which no data are

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collected due to a loss of the pupil and/or the corneal reflection. To counterbalance these issues, researchers usually compute the cumulative time spent looking at predefined areas of

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interest (AOI) of the scene. In addition, to compensate for poor data quality, a new fixation detection algorithm has been developed that provides better fixation duration estimates (Wass

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children (Frank et al., 2012).

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et al., 2012). Finally, off-line calibration can also be used to improve data quality in young

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Outcome measures are typically proportions of looking-time spent within AOIs (i.e., the person, the face, the eyes, the mouth). This AOI-based approach is used to quantify the spatial distribution of visual attention across the scene and therefore, determine which AOIs attract and hold the participant’s visual attention (Klin et al., 2002a). A number of studies have used different approaches to analyze gaze behaviors relying on different outcome measures such as blinks (Shultz et al., 2011), the number of transitions between AOIs (Shic et al., 2007) or predictive saccades (Falck-Ytter, 2010). These studies yield complementary results to those delivered by the AOI-based approach, notably with respect to the temporal aspects of gaze behaviors (Falck-ytter et al., 2013a) (see section 5 for a further discussion of these studies).

1.3. Study selection and inclusion/exclusion criteria

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We used the PubMed database to select articles focusing on eye movements in ASD between 2002 and January 2014. Search criteria were “ASD”, “autism”, “eye movement”, and “eye-tracking”. Only studies using strict diagnostic criteria (ADI-R and/or ADOS-G and/or

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DSM-IV) were included. Because we were interested in visual social attention specifically we excluded studies that did not used socially meaningful stimuli (e.g. geometric figure only).

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Finally, because we were only interested in spontaneous visual social attention, we also

excluded studies in older children, adolescents and adults that recorded gaze behavior while

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these participants were performing a task (e.g. emotion recognition). By doing so, we ensured a homogenous set of articles reporting spontaneous gaze behaviors in individuals with ASD.

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Studies of infants at risk for ASD were included when the clinical outcome was reported or when a follow-up study was subsequently done (i.e., Merin et al., 2007; Young et al., 2009).

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Additional conference papers, which meet the above mention criteria, were included after

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al., 2007; Shic et al., 2008).

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inspection of references content of the previously identified articles (Shic et al., 2006; Shic et

2. Assumption #1: Individuals with demonstrate a deficit in social orienting and decreased attention to socially relevant stimuli such as faces compared to TD individuals (Table 1)

2.1. Evidence supporting assumption #1 2.1.1. Infants and young children

Chawarska et al., (2013) presented a continuous video clip depicting an actress engaged in different activities varying in their social content and found that, regardless of the context, 6 month-old infants who will receive a diagnosis of ASD during the third years of life demonstrated decreased attention to social scenes and to faces. Using the same video clip with 21 month-old toddlers, Chawarska et al. (2012) found similar results but only during episodes

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involving direct dyadic cues. During these episodes, toddlers with ASD spent less time looking at the scene than TD and developmentally delayed (DD) toddlers. Furthermore, decreased attention to the face in toddlers with ASD occurred during dyadic bids episodes

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when the actress looks straight into the camera and speaks to the child. A further examination of these data revealed that this difference at the group level might result from a subgroup of

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toddlers clearly demonstrating a reduced attention towards the scene and the face (Campbell et al., 2014). During joint attention episodes, toddlers with ASD looked less to the face but

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only when compared to DD children. During episodes involving limited social content, no difference was found between groups. In another study, Shic et al. (2011) noted that 20

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month-old toddlers with ASD looked less at the heads than TD and DD toddlers while watching a 30-second video clip of a naturalistic play interaction between a woman and a

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toddler. In addition, the group of children with ASD was found to monitor less the play activity, another socially meaningful aspect of the actual scene, than both control groups. Von

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Hofsten et al. (2009) compared the viewing patterns of 5 year-old children with ASD to 1 and

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3 year-old TD children and found that both TD groups spent more time looking at faces than

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the ASD group during the observation of a conversation between two women. In two other studies, using short video clips of social scenes taken from TV program or a film for young children and including one to several persons, Nakano et al., (2010) and Hosozawa et al. (2012) also found that 5 year-old children with ASD spent less time looking at faces in comparison to TD children whose chronological age was matched to the developmental age of those with ASD (3 years) and 30 month-old children with specific language impairment (SLI). Studies using a preferential looking paradigm also indicate that young children do not look preferentially towards social stimuli. Klin et al. (2009) studied biological motion perception and found that 24 month-old children with ASD, unlike TD and DD children, did not look preferentially towards the side of the screen depicting a point-light animation of

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biological motion. In addition to the absence of preferential looking towards biological motion in toddlers with ASD, the authors also found that their viewing patterns correlated with the level of audio-visual synchrony (AVS) contained in the stimulus. In contrast, the

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viewing patterns of TD children were not related to AVS. To disentangle the influence of biological motion and AVS on gaze performance, Falck-Ytter et al. (2013b) manipulated

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specifically AVS and showed that 40 month-old children with ASD did not look

preferentially towards biological motion, thus replicating the findings of Klin et al. (2009).

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The authors also found that children with ASD did not look preferentially towards AVS, in contrast to TD children. This latter result argues against the conclusion of Klin et al., (2009)

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that toddlers with ASD give preferential attention to physical contingencies rather than to biological signals. However, both these studies clearly demonstrate that toddlers with ASD do

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not look preferentially towards social stimuli. Using also a preferential looking paradigm, Pierce et al. (2011) presented 26 month-old toddlers with ASD with social animations on one

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side of a screen and repetitive geometric patterns on the other. As a group, toddlers with ASD

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were found to look more at the geometric patterns than a group of TD toddlers and a group of

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DD toddlers. However, at the individual level, results showed that 60% of the toddlers with ASD spent more time on social than on non-social stimuli as TD and DD toddlers, suggesting that the between-group difference might result from a subgroup of toddlers with ASD focusing exclusively on the geometric patterns. Sasson and Touchstone (2013) used stimuli consisting of a picture of face paired with an object, either related or unrelated to circumscribed interests (e.g. trains, clocks vs. plants, clothing). The authors found a decreased fixation time on the face but only when the face was presented along with an object related to circumscribed interest. Similarly, when 43 month-old children with ASD looked at arrays of pictures containing faces and objects, they spent less time on faces than on objects, particularly when the array contained objects related to circumscribed interest (Sasson et al., 2011).

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Sasson and Touchstone (2013) also measured orienting to faces by computing the latency it takes to first fixate the face. They found that for young children with ASD this latency was greater than that of TD peers when the face was paired with an object related to

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circumscribed interest. When the face was paired with an object not related to circumscribed

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interest no between-group difference was found.

2.1.2. Older children, adolescents and adults

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Consistent with the eye tracking literature in infants and young children, several studies report that older children, adolescents and adults demonstrate decreased attention to faces.

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Riby and Hancock (2009a) presented video clips of natural social interactions between actors as well as cartoon movies of social interactions to 13 year-old adolescents with ASD and two

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control groups matched on chronological age (CA) and on non-verbal (NV) ability, respectively. Regardless of the nature of the stimuli, adolescents with ASD spent less time

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looking at faces compared to both control groups. In adults, Bird et al. (2011) computed a

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face/non-face ratio (i.e., ratio of the total time spent fixating the face compared to non-face

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areas) and found that this measure differed significantly between high functioning adults with ASD and their CA matched peers: participants with ASD attended less towards faces. Moreover, while TD individuals demonstrated a strong gaze bias towards faces, individuals with ASD showed no preference, neither for faces or non-face objects. In studies using pictures of social scenes, including two or more interacting persons

embedded in a naturalistic environment, Wilson et al. (2010) also computed a face/non-face ratio and, similarly to Bird et al., (2011), found that looking time was evenly distributed across faces and non-face objects in 10 year-old children with ASD, whereas CA-matched control children preferentially looked at faces. Riby and Hancock (2008) found that 13 yearold adolescents with ASD spent less time looking at faces compared to TD adolescents matched on CA and TD children matched on NV ability (the same sample of adolescents as

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Riby and Hancock, 2009a). In another study, Hanley et al. (2013) used a set of pictures varying in terms of social content (i.e. faces presented in isolation vs. faces embedded in social scenes) and context (i.e. natural faces and scenes vs. acted faces and scenes) and found

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that 20 year-old individuals with ASD spent less time looking at the face only when viewing scenes depicting a natural interaction.

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With respect to orienting to faces, a number of studies have reported that high

functioning adolescents and adults with ASD were slower to direct their visual attention

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towards faces compared to controls. Freeth et al. (2010) presented images depicting everyday indoor settings with one model to 14 year-old adolescents and found that those with a

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diagnosis of ASD were slower in their first fixation to the face compared to their TD peers. Inversely, adolescents with ASD were quicker to first fixate one main object of the scene.

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Wilson et al. (2010) reported similar results for the latency to look at people but, in contrast to Freeth et al. (2010), found no between-group difference regarding the latency to fixate an

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object. In another study, Riby and Hancock (2009b) found that 12 year-old adolescents with

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ASD took longer to make a fixation on a face that was either embedded into a landscape or

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randomly located among distractors in a 3x3 grid. In addition, the authors noted that adolescents with ASD looked at the face on fewer trials compared to TD adolescents. Sasson et al. (2008) reported that relative to 10 year-old TD children, those with ASD explored fewer social images, especially when the stimuli contained object related to their circumscribed interest.

2.2. Evidence against assumption #1 2.2.1. Infants and young children There is little evidence arguing against assumption #1 in infants and young children. Nevertheless, during episodes with limited social content (i.e. making sandwich and moving toys episodes), Chawarska et al. (2012) did not find any between-group difference regarding

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the time spent looking at the actress’ face in 21 month-old toddlers. Moreover, a cluster analysis performed on gaze performance of toddlers with ASD during dyadic bids episodes revealed that a number of these children were likely to attend to the face comparably to TD

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children; direct statistical comparison was however not performed in this study (Campbell et al., 2013).

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In a study using arrays of 5 pictures, including a face, as stimuli, Elsabbagh et al. (2013c) found that infants later diagnosed with ASD spent a similar proportion of time

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looking at the face than low risk infants as well as high risk infants not diagnosed with ASD at the ages of 7 and 14 months. In 45 month-old children, Sasson and Touchstone (2013) did

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not report any between-group difference when the face was paired with an object not related to circumscribed interest.

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These two studies also examined orienting to faces, but used different measures. Elsabbagh et al. (2013c) relied on the proportion of trials in which infants looked first towards

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the face and compared it against chance level. They found that all infants, regardless of

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clinical outcome, demonstrated a face pop-out effect, indicating that those later diagnosed

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with ASD initially fixated the face more frequently than would be expected by chance. Sasson and Touchstone (2013) found that 46 month-old children with ASD and TD controls had a similar latency to first fixate the face, but only when the face was paired with an object not related to circumscribed interest (e.g. plants, clothing). In another study, Sasson et al. (2011) reported that the number of social images and non-social images (either images of objects related to circumscribed interest or images of objects not related to circumscribed interest) viewed was not different between a group of 43 month-old children with ASD and their TD peers matched on CA.

2.2.2. Older children, adolescents and adults

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Nakano et al. (2010), used the same video clips as with children in a group of adults and did not find any between-group difference in the proportion of looking time to faces. Interestingly, Kuhn et al. (2010) tested the hypothesis that high functioning adults with ASD

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would be less susceptible to a “magical trick” (the vanishing ball illusion) because it mostly relies on the misdirecting of attention through social cues by the magician. Unexpectedly, the

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authors found the opposite results: adults with ASD were more susceptible to the illusion than the control group. Gaze behavior analyses revealed no between-group difference in looking

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time to the head, the eyes and the hand of the magician but control participants were found to pay more attention to the ball than individuals with ASD. The authors argue that the fact that

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the ASD group spent less time looking at the ball may be related to problems in timing the allocation of attention, which ultimately may account for the higher level of deception in

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ASD.

In studies using static pictures, Freeth et al. (2010) computed the proportion of looking

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time to the top and lower parts of faces in high functioning adolescents. They found no effect

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of face region nor region x diagnosis interaction suggesting that overall, adolescents with

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ASD and TD adolescents spent a similar proportion of time looking at faces. In this study, two different presentation durations were used (5 and 3 seconds), but this did not affect the results. In another study, Hanley et al. (2013) did not find any between-group differences for acted social scenes, but did find a difference for natural social scenes. In a visual paired comparison paradigm, Fletcher-Watson et al. (2009) presented stimuli

where a person-present scene was displayed on one side of a screen and a person-absent scene on the other side to 19 year-old high functioning individuals with ASD and TD individuals. Both groups spent more time looking at the person-present scene relative to the person-absent scene and both groups preferentially attended to the person. The authors also analyzed the direction of the first fixation. Again, both groups preferentially looked first to the person-present scene. However, a between-group comparison

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revealed that TD participants were more likely to look first towards the person-present scene compared to participants with ASD, who inversely were more likely to look first towards the person-absent scene relative to controls. Furthermore, when TD participants looked first at the

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person-present scene, they preferentially first fixated the person, whereas participants with ASD equally directed their first fixation towards the person and the background, making it

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unclear what initially attracted their attention. This study therefore suggests that young adults with high functioning ASD seem to preferentially look first towards a person-present scene

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but to a lesser degree than TD participants. In another study, Wilson et al. (2010) compared the proportion of trials on which people were fixated before the objects. On average, 10

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years–old children with ASD looked first at people in 71% of the trials and TD children looked first at people in 77% of the trials. This difference was not statistically significant.

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Finally, using a “gap-overlap” paradigm, Fischer et al. (2013) specifically investigated social orienting by measuring saccadic reaction times for trials in which the peripheral target was a

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social or a non-social image. Both, 9 year-old high functioning children with ASD and their

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controls peers matched on CA and performance intellectual quotient (PIQ) demonstrated

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faster saccadic reaction times when the peripheral target was a social image, and no betweengroup difference was present.

2.3. Conclusion about assumption #1 In infants later diagnosed with ASD results are inconsistent. Chawarska et al. (2013) have reported decreased looking time to the scene and the face of an actress at 6 months. In contrast, Elsabbagh et al. (2013c) have found no between-group difference. This discrepancy likely results from difference in the nature of stimuli (dynamic vs. static). Indeed, the face displayed in the Chawarska et al. (2013) study was dynamic and at some times directly addressed the viewer which might have caused TD infants to increase their looking time on the face. In contrast, the lack of communicative intent in the static faces used in the Elsabbagh

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et al. (2013c) study might have led TD infants to spent relatively less time looking at the face, resulting in the absence of between-group difference found by the authors. In toddlers and young children, the vast majority of eye-tracking studies indicate that

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those with ASD demonstrate decreased looking-time to social stimuli relative to TD children. Only two studies challenge this view and give a more nuanced picture with respect to faces

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(Campbell et al., 2013, Chawarska et al., 2012). Although these studies need to be replicated, they suggest that decreased looking-time to faces cannot be generalized across contexts but

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likely emerges during complex social situations involving child directed speech for instance (Chawarska et. al, 2012) and that not all toddlers with ASD demonstrate decreased looking-

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time to faces in these situations (Campbell et al., 2013).

In older children, adolescents and adults, two out of five studies using pictures found that

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participants with ASD and TD controls spent a similar proportion of time looking at the face (Fletcher-Watson et al., 2009; Freeth et al., 2010; see also Hanley et al., 2013). These studies

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used stimuli involving only one person. In contrast, when the set of stimuli included pictures

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of at least two persons interacting, participants were found to look less at faces than TD

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controls (Riby and Hancock, 2008; Wilson et al., 2008; see also Hanley et al., 2013). Three studies have used video-clips of social interactions, two of which have reported decreased looking-time to faces in participants with ASD (Bird et al., 2011; Riby and Hancock, 2011). On the contrary, Nakano et al. (2010) have found similar looking-time to faces across groups, but their set of stimuli varied a lot with some video clips only including one person while others depicted a group of people. In TD adults, increasing the social content of the stimuli (e.g., number of people) leads to increased fixation time on faces and eyes (Birmingham et al., 2008). Thus, it is likely that using stimuli involving more than one person increases the likelihood of decreased looking-time to faces in individuals with ASD relative to TD controls. Future studies should further examine the influence of social content on viewing patterns of individuals with ASD by systematically varying the number of person displayed as well as the

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context in which the persons appears (e.g., two or more people interacting vs. not interacting with each other, see Birmingham et al., 2008). It is also worth noting that a number of studies have reported increased looking-time to

ip t

non-social aspects of the scenes in children with ASD (e.g., Klin et al., 2009; Pierce et al., 2011; Shic et al., 2011; Shultz et al., 2011). However whether this is due to increased saliency

cr

of objects for children with ASD or whether it is a simple byproduct of increased saliency of social stimuli for TD children remains unknown and should be the object of future studies

us

(e.g. Chawarska et al., 2013; Wilson et al., 2010; see also Bird et al., 2011 in adults). Moreover, there is also evidence that in children with ASD attention to face pictures may be

an

modulated by the salience of competing objects (Sasson et al., 2013; Sasson et al., 2011). Future studies should also test this hypothesis in more naturalistic contexts.

M

With respect to the ability of individuals with ASD to orient towards social stimuli, an interesting pattern of results emerges. When social orienting was assessed through the

d

direction of the first fixation, studies have reported a preserved social orienting ability in

te

individuals with ASD (Elsabbagh et al., 2013c; Fletcher-Watson et al., 2009; Wilson et al.,

Ac ce p

2010). In contrast, studies measuring the latency to first fixate social stimuli (in all studies social stimuli were faces), have almost consistently reported a greater latency in individuals with ASD (Freeth et al., 2010; Riby and Hancock, 2009b; Wilson et al., 2010). These studies have used pictures where faces were embedded into a complex scene involving several competing objects. In contrast, a gap-overlap study has reported faster saccadic reaction time in response to face relative to non-face peripheral targets, both in high functioning ASD and TD children and no between-group difference (Fischer et al., 2013). Altogether, these studies suggest that the basic ability to orient towards faces is not qualitatively impaired in individuals with ASD. According to Johnson (2014) these results, along with others, argue against the view that ASD might be caused by an early deficit in an automatic face processing subcortical pathway (see Johnson, 2005) resulting in poor orienting towards faces. The

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current results rather suggest that it is the ability to orient towards other’s face in an effective manner (e.g. ignoring competing non-social objects, see Sasson et al., 2013; Sasson et al., 2011) that seems to be affected in ASD, as indicated by a greater latency to first fixate a face

ip t

in complex displays (see Freeth et al., 2010; Riby and Hancock, 2009b; Wilson et al., 2010). Lewis and Edmonds (2003) have suggested that face detection occurs at a pre-attentive stage

cr

and have demonstrated that TD adults are slower to fixate the face when the eyes are removed or when the contrast and clarity of the pictures is reduced. Future studies should explore the

us

influence of these factors on the ability of individuals with ASD to orient towards faces as both these face manipulation may tap into different mechanisms subtending face orienting

an

ability.

Several studies have suggested that individuals with ASD demonstrate a deficit in

M

attentional disengagement (Elison et al., 2013; Elsabbagh et al., 2009; Elsabbagh et al., 2013b; Kawakubo et al., 2007; Landry and Bryson, 2004; for a review see Keehn et al.,

d

2013). However, the results of Fischer et al. (2013) challenge this view. According to the

te

authors, the discrepancy between results may lay on a number of differences in experiments

Ac ce p

design and data analyses. For instance, they noted that Elsabbagh et al. (2009, 2013b) presented the same peripheral target on every trial or used dynamic stimuli as the central stimuli, which might have interacted with disengagement.

3. Assumption #2: Individuals with ASD exhibit excess mouth and diminished eye gaze compared to TD individuals (Table 2) 3.1. Evidence supporting assumption #2 3.1.1. Infants and young children Only one study has found diminished eye and excess mouth gaze in toddlers with ASD compared to TD toddlers. Jones et al. (2008) presented short video-clips of an actress trying to engage the observing child in childhood games (e.g. pat-a-cake). They found that 24

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month-old toddlers with ASD spent more time looking at the mouth and inversely, less time looking at the eyes than TD and DD toddlers. In toddlers with ASD, increased eye gaze was associated with better social competence, as indicated by the ADOS social score. No

ip t

correlation was found between measures of verbal and non-verbal functioning and looking time to the eyes or the mouth in all three groups. According to the authors the preference for

cr

the mouth in toddlers with ASD likely resulted from a preference for its physically contingent

us

properties (i.e., AVS).

3.1.2. Older children, adolescents and adults

an

Only one study has reported diminished eye and excess mouth gaze in high functioning verbally able adolescents with ASD. Klin et al. (2002b) presented video clips of intense social

M

interactions between four characters taken from the movie “Who’s afraid of Virginia Woolf?”. Compared to a control group of TD adolescents matched on CA and verbal

d

intellectual quotient (VIQ), 15 year-old verbally able high functioning adolescents with ASD

te

spent less time looking at the eyes and focused more on the mouth. In this group of

Ac ce p

adolescents, looking time to the eyes was not associated with social competence, measured with the ADOS social score and VABS-II socialization scores. However, increased mouth looking was associated with better social competence, leading the authors to conclude that mouth looking is an adaptive and functional behavior in verbally able high functioning adolescents that might help them to achieve better understanding of complex social situations.

3.2. Evidence against assumption #2 3.2.1. Infants and young children Jones and Klin (2013) carried out a longitudinal prospective study of high-risk and lowrisk infants from 2 to 36 months of age. Gaze behaviors were recorded at 10 time points between the ages of 2 and 24 months while infants watched short video-clips of an actress

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engaging in childhood games and looking straight into the camera. The final sample of infants consisted of 11 boys who eventually received a diagnosis of ASD at 36 months and 25 TD boys from the initial low-risk sample. The specific design of the study allowed the authors to

ip t

model the developmental changes of social engagement occurring over the first two years of life. In infants with ASD, looking time to the eyes gradually decreased from 2 to 24 month-

cr

old and inversely, mouth looking increased, reaching its maximum at 18 months. Infants with ASD differed from TD infants over the first two years of life with respect to the change in

us

fixation to the eyes. However, at 2 months the authors noted that both TD and infants with ASD spent a similar proportion of time on the eyes. In infants with ASD, a greater decline of

an

eye looking was associated with more severe social disability at 24 months.

At 6 months, Merin et al. (2007) found that low-risk and high-risk infants allocated their

M

attention between the eyes and the mouth in a similar way during a still face experiment performed with their mother. Yet, they identified a subgroup of 11 infants of which 10 had an

d

older sibling with ASD that spent more time looking at the mouth during a still face episode,

te

while other infants focused almost exclusively on the eyes during this episode. However, the

Ac ce p

follow-up study of these infants revealed that none of the “mouth-lookers” received a diagnostic of ASD at 24 months. Instead, the amount of time spent looking at the mouth at 6 months predicted the level of expressive language skills at 24 months. Moreover, gaze behaviors of 6-month-old infants later diagnosed with ASD (N=3) did not differ from those of TD infants (Young et al., 2009). In another study, Chawarska et al. (2013) found that attention directed to the eyes and the mouth in 6 month-old infants did not predict clinical outcome at 24 and 36 months. Infants later diagnosed with ASD, though demonstrating reduced attention to scenes and faces (see section 2.1.1), did not differ from TD infants with respect to the proportion of time they spent looking at the eyes and the mouth. Shic et al. (2014) presented an image of a neutral female face, a video clip of a smiling female face and a video clip of a female reciting a nursery rhyme to 6 month-old infants. Infants later diagnosed with ASD

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demonstrated an overall reduction of attention towards all stimuli. However, when they looked at the face, they only demonstrated an atypical viewing pattern during the observation of the speaking face. In this condition, infants later diagnosed with ASD looked less at the

ip t

inner face features (i.e., eyes, nose and mouth) and more at the outer face features (i.e., skin, hair and body) than high-risk infants not developing ASD and low-risk infants. With respect

cr

to the proportion of looking time allocated to the eyes relative to the mouth, the authors noted that all groups modulated their attention relative to the context in which the face was

us

presented and found no between-group difference. Infants later diagnosed with ASD distributed their visual attention between these two face features in a typical manner.

an

Elsabbagh et al. (2013a) tested a number of hypotheses related to relationships that might exist between the scanning of the eyes and the mouth in infants at risk for ASD and different

M

outcome measures related to language and autistic symptomatology. Infants were seen twice, when they were 6- to 10-months old and 12- to 15- months old. They were presented with

d

video clips displaying an actress moving either her eyes (see also Elsabbagh et al., 2012), her

te

mouth, her hands or engaging in a peek-a-boo sequence. Consistent with others studies

Ac ce p

(Chawarska et al., 2013; Shic et al. 2014; Young et al., 2009), the authors found that during a communicative scene (i.e., peek-a-boo sequence) looking time between the eyes and the mouth at 6-10 months did not predict clinical outcome and receptive language skills but did predict expressive language skills at 36 months. Infants focusing more at the mouth than at the eyes had a better expressive language outcome. Looking time between the eyes and the mouth at 12-15 months was not related to clinical outcome, expressive or receptive language skills at 36 months. In addition, the study showed that superior expressive language skills at 36 months was only predicted by more looking to the mouth relative to the eyes in the peek-aboo sequence. Inversely, more looking to the mouth when only the mouth of the actress was moving predicted lower level of expressive language skills and was also associated with more severe emerging social and communication impairment.

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In toddlers aged 21 months, Chawarska et al. (2012) found that, as a group, toddlers with autism spent less time looking at the mouth of an actress engaged in child-directed speech than TD and DD toddlers. Less looking time to the mouth in this condition was related

ip t

to atypical language profiles. During joint attention episodes the between-group difference remains significant only between toddlers with autism and TD toddlers. During non-social

cr

episodes, involving the actress making a sandwich or moving toys, all groups allocated their

visual attention in a similar manner across the scene. A further investigation of toddlers with

us

autism revealed however that one subgroup demonstrated a clear preference for the mouth relative to the eyes, as TD toddlers, while looking time between the eyes and the mouth was

an

evenly distributed for another subgroup. Moreover, toddlers demonstrating increased mouth relative to eye looking made faster progress in formal language acquisition than toddlers who

M

did not preferentially attend to the mouth. However, the authors found that the rate of acquisition was not different with respect to its communicative use (Campbell et al., 2013).

d

In two others studies, the same 5 year-old children with ASD were found to look less at

te

the mouth than 3 year-old TD children matched on the developmental age of children with

Ac ce p

ASD (Nakano et al., 2010) and 30 month-old children with SLI (Hosozawa et al., 2012) while observing video-clips taken from a film or TV program for young children. A number of studies also used static face pictures as stimuli. Chawarska and Shic

(2009) found that 26 and 46 month-old children with ASD looked less at the mouth than CAmatched TD peers, while attending in a similar way towards the eyes. In a sub-sample of these children, Shic et al. (2008) used transition matrix entropy measures to estimate the exploratory activity across different regions of the face. Contrary to TD children, whose gaze behavior became increasingly exploratory in the scanning of socio-communicative areas (i.e., eyes and mouth) with age, viewing patterns of children with ASD towards these areas remained fixed. de Wit et al. (2008) presented 5 year-old children with positive and negative emotional faces and found that viewing patterns of children with ASD were similar to those

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of TD children. In addition, both groups were found to look more at the eyes for negative emotions compared to positive ones. Falck-Ytter et al. (2010) also found no between-group difference with respect to looking time to the eyes and to the mouth in 5 year-old children

ip t

(this study also included silent video-clips of facial expression as stimuli). However, the authors showed that children with ASD, who were better in the non-verbal communication

cr

domain than in the socio emotional domain of the ADI-R, tended to look more at the mouth

than at the eyes. Inversely, those with better performance in the socio-emotional domain than

an

3.2.2. Older children, adolescents and adults

us

in the non-verbal communication domain tended to look more at the eyes than at the mouth.

Rice et al. (2012) presented two video clips chosen to reflect age-appropriate social

M

interactions occurring within a group of children to 10 year-old children. Compared to TD children carefully matched on CA and intellectual functioning, children with ASD spent less

d

time looking at both the eyes and the mouth. The authors reported similar results when less

te

cognitively able children were included in the group of children with ASD. Taken advantage

Ac ce p

of this large sample of children (N=109), the authors further investigated the relationship between patterns of gaze behaviors and social phenotype and assessed the possible moderating effect of different cognitive profiles. They found that increased mouth looking was associated with better social ability (see also Klin et al., 2002b) but only in children with a verbal IQ advantage (17% of the sample). In contrast, in children, with an even IQ profile and with a FIQ greater than 98, increased mouth looking was associated with greater social disability. For these children however, looking more at the eyes was associated with better social ability, whereas for children demonstrating either a VIQ or a NVIQ advantage, the time spent looking at the eyes did not correlate with social disability. In another study, Norbury et al. (2009) distinguished high functioning adolescents with ASD presenting language impairment from those who had normal language skills (the groups did not differ in autistic

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symptomatology as indicated by the SCQ and ADOS scores) to further investigate the influence of different language profiles on viewing behaviors. Participants in this study were presented video clips of social interactions involving 2 to 3 persons. The authors reasoned that

ip t

since social impairments is common to all of their participants with ASD, they would observe decreased fixation time to the eyes in both groups of ASD. They predicted however that

cr

looking time to the mouth and the relationship between viewing the mouth and adaptive skills would differ between the two ASD groups. Yet, they found that adolescents with ASD with

us

no associated language impairment looked less at the eyes than adolescents with ASD with associated language impairment and TD adolescents matched on CA and NV ability. These

an

latter groups did not differ in their viewing behaviors. With respect to mouth looking, neither group of individuals with ASD differed from TD participants, a discrepancy from the study of

M

Klin et al. (2002) the authors interpreted as the result of less complex stimuli. Moreover, regardless of group membership, increased fixation time to the eyes in individuals with ASD

d

was associated with lower communicative competence, while increased mouth-looking was

te

associated with better communicative competence, measured with the VABS-II

Ac ce p

communication subscale. Speer et al. (2007) used the same stimuli as Klin et al. (2002b) but did not replicate their findings. Instead they found that 14 year-old high functioning adolescents with ASD only demonstrated a decreased visual attention towards the eyes relative to TD controls. Moreover, in participants with ASD, decreased looking time to the eyes was associated with decreased social responsiveness measured by the Social Responsiveness Scale. In another study, Riby and Hancock (2009a) found that 13 year-old adolescents with autism spent less time looking at the eyes than CA-matched TD adolescents and 5 year-old TD children matched on NV ability when watching video-clips of natural interactions between adults as well as cartoon pictures. There was no between-group difference with respect to the time spent looking at the mouth region.

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In adults, Nakano et al. (2010) found that individuals with ASD look less at the eyes than controls during the observation of video clips taken from TV program or a film for young children. There was no difference with respect to the time spent looking at the mouth.

ip t

Bird et al. (2011) computed the ratio of eye to mouth fixation and found no significant between-group difference. However, while TD controls showed a preference for the eyes,

cr

individuals with ASD showed an even deployment of visual attention between the eyes and the mouth.

us

All studies using static pictures of social scenes failed to report excess mouth gaze along with reduced eye gaze in ASD compared to TD controls. Two studies noted reduced

an

eye gaze among participants with ASD (Hanley et al., 2013; Riby and Hancock, 2008). One study did not report any different with static stimuli (Speer et al., 2007).

M

For studies using isolated face pictures, while McPartland et al. (2011), Sepeta et al. (2012), van der Geest et al. (2002), and Wagner et al. (2013) did not find any between-group

d

difference in the deployment of visual attention to the eyes and the mouth, Corden et al.

te

(2008), Hernandez et al. (2009), Pelphrey et al. (2002), and Sterling et al. (2008) found

Ac ce p

reduced eye gaze in individuals with ASD. Interestingly, studies that found a difference included groups of participants whose mean age was above 20 years, while the other studies included young adolescents. Differences in the duration of stimuli presentation as well as differences in outcome measures (absolute vs. proportion of looking time) might also account for this discrepancy.

3.3. Conclusion about assumption #2 In line with Falck-Ytter and von Hofsten (2011), we found little evidence of excess mouth and diminished eye gaze in ASD. For instance, at 6 months, none of the studies have reported excess mouth and diminished eye gaze in infants later diagnosed with ASD. The deployment of visual attention across the eyes and the mouth during the observation of an

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interacting partner (engaging in a childhood game, reciting a nursery rhyme, or providing direct bids for dyadic engagement) do not predict clinical outcomes (Chawarska et al., 2013; Elsabbagh et al., 2013a; Merin et al., 2007; Shic et al., 2014; Young et al., 2009). Moreover,

ip t

increased scanning of the mouth is related to better expressive language outcome at 24 and 36 months regardless of clinical outcomes (Elsabbagh et al., 2013a; Young et al., 2009).

cr

To date, only two studies have reported excess mouth and diminished eye gaze in

toddlers and in verbally able high functioning adolescents with ASD compared to TD controls

us

(Jones et al., 2008; Klin et al., 2002b). In contrast, Chawarska et al. (2012) have found decreased mouth gaze in toddlers with autism relative to TD toddlers and no between-group

an

difference regarding the eyes (see also Nakano et al., 2010). A number of factors have been proposed to account for the discrepancy between the studies of Jones et al. (2008) and

M

Chawarska et al. (2012) including the age of participants (2.3 years vs. 1.8 years respectively), or the degree of symptoms severity (ASD vs. autism) (Chawarska et al., 2012).

d

Another important factor that may have contributed to this discrepancy is the content of the

te

stimuli. Indeed, if we look at the gaze behaviors of TD toddlers across the two studies, we

Ac ce p

find an opposite distribution of visual attention, with the eyes being looked at in the Jones et al. (2008) study for 54.2% of the time allocated to the screen vs. 14.9% in the Chawarska et al. (2012) study and with the mouth being looked at for 23.6% vs. 52.2% respectively. One important aspect to be considered here is that gazing at the mouth in typical development is thought to be a functional and adaptive behavior providing access to audiovisual cues which may ultimately help the child to process language information (e.g. Lewkowicz and HansenTift, 2012; Falck-Ytter and von Hofsten, 2011; Frank et al., 2012; Tenenbaum et al., 2012; Vatikiotis-Bateson et al., 1998). Thus, when observing an actress engaged in a familiar childhood game (e.g. pat-a-cake) as in the study of Jones et al. (2008), it is likely that TD toddlers pay little attention to the mouth because they do not need to rely on audiovisual information to understand the situation, and instead attend to the most communicative face

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feature, which in that context happens to be the eyes. In contrast, in Chawarska et al. (2012) the stimulus was more complex and direct bids for dyadic engagement occur briefly between other types of activity (i.e., moving toys, making sandwich). In this context, it is likely that

ip t

TD toddlers strongly rely on the mouth because audiovisual information may help them adjust to the situation. Interestingly, the cluster analysis performed by Campbell et al. (2014)

cr

indicates that a subgroup of young children with ASD also demonstrate a preference for the

mouth relative to the eyes during these dyadic bids episodes. Moreover, this subgroup shows

us

a rapid rate of language acquisition relative to the other children and the authors postulate that the functional role of mouth looking in TD children might also be in play in this subgroup.

an

There is no unique answer to the question of whether toddlers with ASD demonstrate excess mouth and diminished eye gaze relative to TD toddlers. This particular pattern of

M

result may be observed in some specific circumstances that specifically cause TD children to increase looking time to the eyes (e.g. childhood games). This interpretation fits well with the

d

ideas that individuals with ASD may not be interested and have difficulties in using

te

information coming from the eyes or that the eyes may be aversive stimuli for them (Corden

Ac ce p

et al., 2008; Dalton et al., 2005; Spezio et al., 2007; Zürcher et al., 2013) and potentially from a very early age (Jones and Klin, 2013). This interpretation also argues against the role of AVS in guiding the gaze behaviors of toddlers with ASD (see also Falck-Ytter et al., 2013b) since excess mouth in ASD in these conditions would be somewhat considered as a byproduct of the gaze behavior of TD children rather than as a specific gaze signature of toddlers with ASD. Moreover, in situations where mouth looking would be helpful to better understand the interaction, some toddlers with ASD would instead demonstrate decreased mouth gaze relative to TD toddlers (Chawarska et al. 2012; Nakano et al., 2010), while others would increase mouth looking as TD toddlers would do (Campbell et al., 2014). Future studies should further investigate the ability of toddlers with ASD to modulate their attention in

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response to different social contexts systematically varying in their communicative intent (e.g., childhood games vs. direct bids for dyadic engagement vs. reciting a monologue). In adolescents, only Klin et al. (2002b) have reported excess mouth and diminished eye

ip t

gaze in verbally able high functioning adolescents with ASD relative to TD controls. Speer et al. (2007), who used the same stimuli, have failed to replicate this finding with a sample of

cr

younger adolescents. Participants with ASD in that study only demonstrated diminished eye gaze relative to TD controls. It is worth noting here that Speer et al. (2007) have used the

us

mean total fixation duration as their outcome variables, in contrast to Klin et al. (2002b) who have relied on the proportion of fixation time. Obviously, this difference in outcome measures

an

prevents the direct comparison between these two studies. However, other studies that have used video-clips have also failed to replicate the findings of Klin et al. (2002b) (e.g., Nakano

M

et al., 2010; Norbury et al., 2009; Rice et al., 2012). Klin et al. (2002b) have argued that increased mouth looking is a compensatory strategy that might help high functioning

d

adolescents with ASD to achieve better understanding of complex social situations. This

te

conclusion was based on their analysis of the relationship between fixation patterns and social

Ac ce p

phenotype, showing that gazing at the eyes was not associated with social competence in contrast to mouth gaze. Rice et al. (2012) have also reported this relationship in a number of high-functioning adolescents with ASD (17% of the sample) showing a verbal IQ advantage, suggesting that this relationship might be specific to a specific subgroup for which mouthlooking is a functional and adaptive behavior, particularly when facing complex social situations. There is no other study reporting that increased mouth looking is associated with better social competence in ASD. Instead, mouth looking has been found to be associated with communicative abilities in individuals with ASD (e.g., Falck-Ytter et al., 2010; Norbury et al., 2009) and eye looking with social abilities (e.g. Falck-Ytter et al., 2010; Jones et al., 2008; Speer et al., 2007; Rice et al., 2012). In addition, it should also be noted that Rice et al. (2012) failed to find an excess mouth and diminished eye gaze in the subgroup demonstrating

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a verbal IQ advantage and whose mouth gaze was associated with social competence, which suggest that the initial results of Klin et al. (2002) might also be in part related to the stimuli properties they used (see Norbury et al., 2009). While Rice et al., (2012) have employed

ip t

video-clips that reflected age-appropriate social interactions between school-aged children, Klin et al. (2002) have used video-clips depicting two couples engaged in complex social

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4. Gaze following and referential understanding of gaze

cr

interactions, that unlikely reflected the every day experience of their participants.

In infants and young children, gaze following has been assessed in eye tracking studies

an

using video-clips displaying two or three objects on a table and an actress that first looks straight into the camera, so as to establish an eye contact with the observing child and then

M

turns her head towards one of the objects (Senju and Csibra, 2008). Bedford et al. (2012) recorded the gaze behaviors of high-risk and low-risk infants at two time points, when they

d

were 6-10 months and 11-18 months. They found that infants later diagnosed with ASD, at

te

both ages, demonstrated the same ability to look at the gaze-at object as infants at-risk than

Ac ce p

did not develop ASD and low risk infants. However, the authors found a between-group difference with respect to the time 11-18 months old infants spent looking at the gaze-at object: infants later diagnosed with ASD or with another developmental concern looked less at this specific object than TD low-risk and high-risk infants. This measure is thought to reflect that the child understands the meaning of another’s person gaze by attributing an enhanced social value to the gaze-at object (i.e., referential understanding of another’s person gaze, see Butler et al., 2000; Brooks and Meltzoff, 2005; Caron et al., 2002). This study therefore suggests that infants with socio-communicative difficulties, including ASD, do not understand the referential nature of gaze during their second year of life. In another study, including 6 year-old children, Falck-Ytter et al. (2012) tested the hypothesis that gaze following would be more closely related to adaptive communication skills than social skills or

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the degree of autistic symptomatology. They found that children with autistic disorder were less accurate in gaze following (as indicated by the number of correct minus incorrect gaze shifts) and made less correct gaze shifts than TD children. In children with autistic disorder,

ip t

communication skills, assessed with the VABS-II communication subscale, predicted accuracy of gaze following. Gaze performance of children with pervasive developmental

cr

disorder not otherwise specified (PDD-NOS) did not differ from that of TD children and no

relationship was found between gaze performance and any clinical measure. The authors also

us

computed the latency to look at the gaze-at object and found that children with ASD were slower than TD children. The latency of correct gaze shift was only related to verbal IQ in

an

ASD. Finally, the time spent looking at the gaze-at object did not differ between groups. The results of this study indicate that gaze following may be impaired only in a subgroup of

M

children with ASD, those formerly diagnosed with autistic disorder, for whom the ability to follow another person’s gaze is closely related to communicative skills. Gillespie-Lynch et al.

d

(2013) found less accurate gaze following ability in a group of 56 month-old children with

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ASD (12 with autistic disorder and 9 with PDD-NOS) compared to CA-matched TD children

Ac ce p

and TD children matched on non-verbal mental age. Interestingly, the authors also reported that gaze following occurred less frequently during an eye tracking assessment than during an in-person assessment of gaze following. In older population, Freeth et al. (2011) used images depicting everyday indoor setting with one model looking either towards an object or straight into the camera. They found that 14 year-old high-functioning adolescents with ASD and their TD peers matched on CA and IQ made more saccades between the model’s eyes and the objects and spent more time looking at the gaze-at objects when the model looked at the object. However, an exploratory analysis on the time course of following gaze direction revealed that while the speed of gaze direction cuing was similar across groups, the time course of looking time to gaze-at objects followed a different pattern between groups. In TD adolescents, looking time to gaze-at

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objects increased immediately, reflecting the increased social salience acquired by the objects being fixated. In contrast, in adolescents with ASD, looking time to gaze-at objects followed the same time course than in the condition where the model did not look at any objects,

ip t

suggesting that gaze-at objects did not acquire the same social relevance for adolescents with ASD. In a study that specifically assessed subsequent attentional engagement to the gaze-at

cr

object by presenting the children with video-clips displaying the face of a model looking first straight into the camera and then shifting her gaze either towards the object (congruent

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condition) or away from it (incongruent condition), Swanson et al. (2013) found that 7 yearold children with ASD and their TD peers spent more time looking at the object during the

an

congruent than the incongruent condition and more time looking at the model’s face during the incongruent than the congruent condition. However, with respect to the duration of the

M

first fixation to the object, only TD children demonstrated longer first fixation duration during the congruent relative to incongruent condition. For children with ASD, first fixation duration

d

to the object was similar across conditions, suggesting again that children with ASD may fail

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to attribute a social value to gaze-at objects relative to non-gaze-at objects. In another study,

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Riby et al. (2013) found that 11 year-old children with ASD spent less time looking at the face, the eyes and the gaze-at object than their TD peers matched on non-verbal ability. In addition, the authors manipulated the spatial distribution of the object within the scene to create “plausible” gaze-at objects (i.e., objects in the model’s line of sight). They found that participants with ASD also spent less time looking at these objects. In contrast, they attended more to the “implausible” gaze-at objects than TD controls. Interestingly, the authors also recorded gaze behaviors while participants were explicitly asked to identify the gaze-at object. Between-group comparison lead to a similar pattern of results and the authors noted that children with ASD were less accurate at naming the gaze-at objects than controls. Within-group comparison revealed that even when cued, children with ASD did not increase looking time to the gaze-at and “plausible” gaze-at objects. In adults, Fletcher-Watson et al.

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(2009) reported that in high functioning participants with ASD gaze-at objects were not fixated more than randomly expected while TD controls demonstrated a clear preference for these objects.

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In summary, gaze following might not be impaired in infants later diagnosed with ASD (Bedford et al., 2012). This result needs however to be replicated with a larger group of

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infants with ASD in order to establish whether a subgroup of infants would demonstrate early difficulties in gaze following. Indeed, Falck-Ytter et al. (2012) have found reduced gaze

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following accuracy in a subgroup of young children with ASD diagnosed with autistic disorder. In this sample gaze following accuracy was closely related to communicative skills.

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Overall, when children with PDD-NOS and autistic disorder were grouped, no difference was found. In contrast, Gillepsie-Lynch et al. (2013) have reported reduced gaze following ability

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in a group of young children with ASD, including both children with autistic disorder and children with PDD-NOS. In older participants, researchers have mainly focused on the

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subsequent attentional engagement to the gaze-at object, a measure of the referential

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understanding of another’s person gaze. To date, studies have consistently reported that

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individuals with ASD spend less time looking at gaze-at objects than TD individuals, adding to the evidence that the referential nature of gaze is not well understood in ASD (Freeth et al., 2011; Riby et al., 2013; Fletcher-Watson et al. 2009, see also Bedford et al., 2012).

5. Social interactions monitoring The majority of eye-tracking studies in ASD have relied on the analysis of the macrostructure of gaze behaviors (i.e., the proportion of time a participant looks at a specific region of the scene over the whole trial duration). This likely fails to capture more subtle differences in viewing patterns that might exit on a moment-by-moment basis. Falck-Ytter et al. (2013a) have emphasized the need to investigate the microstructure of gaze behavior in ASD. They introduced a measuring index of “event-related gaze behavior”, distance to

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reference point (D2R), aimed at exploring the spatiotemporal distribution of fixations relative to a predetermined key area of the stimuli. They found that right after a non-verbal request for a toy, TD children shifted their visual attention towards the person holding the toy, (i.e., the

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person whose reaction will determine the next course of events). In 6 year-old children with ASD, the same shift of visual attention was less obvious, particularly for those with severe

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verbal and communicative impairments (assessed with the WPPSI-III verbal scale and the

VABS-II communication scale). Nakano et al. (2010) used a similar approach and identified

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key moments of social interactions during which young children and adults with ASD and their respective TD controls differed significantly in their viewing patterns. For instance,

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during a video-clip of two boys talking in turn, while TD participants followed the conversation by shifting their gaze back and forth between them, young children and adults

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with ASD disengaged their attention from the speaker before TD participants and did not necessarily fixate to the next speaker. Although these studies are still exploratory, their results

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indicate that children with ASD differ from TD controls at some specific time points, when

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2002a).

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social cues are critical for adequate interpretation of social situations (see also Klin et al.,

Von Hofsten et al. (2009) analyzed the number of predictive saccades made by young children while observing a conversation between two women. They found that unlike 3 yearold TD children, who look at the next speaker more than 60% of the turns, 5 year-old children with ASD and 1 year-old TD children performed in a similar way and failed to anticipate the next turn in the conversation. Interestingly, in a turn-taking object condition, no betweengroup difference was found and only 3 year-old TD children made more predictive saccades during the observation of the conversation. In another study, Falck-Ytter (2010) studied predictive saccades in response to the observation of a goal directed action (i.e., grasping an object and placing it into a box) in 5 year-old children with and without ASD and TD adults. All three groups performed similarly and used predictive saccades in a human-agent

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condition. In contrast, in a self-propelled object condition, all three groups made reactive saccades. Altogether, these two studies suggest that the absence of anticipation of social events does not result from impairment in making predictive saccades during action

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observation, but on the contrary support the idea that young children with ASD exhibit specific impairments to anticipate social events in complex situations. This conclusion is

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consistent with a study by Shultz et al. (2011), who presented video clip of two children arguing about a toy-wagon door to 2 year-old children. They related the timing of blink

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inhibition to the occurrence of purely physical or socio-affective events and found that toddlers with ASD failed to inhibit their blinks in anticipation of socio-affective events, while

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the timing of blink inhibition was similar across toddlers with and without ASD in anticipation of purely physical events.

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The use and development of innovative eye-tracking measures, such as D2R or blinks inhibition, is increasingly revealing the nature of the profound deficits of children with ASD

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when facing with complex social situations. Adequate social interaction monitoring is critical

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for understanding social situations (Klin et al., 2002a). However, results suggest that children

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with ASD fail to monitor social interaction adequately and likely experience difficulties in forming expectations about the social world (see also Klin et al., 2003).

6. Bottom-up visual influences on gaze behaviors Visual attention is affected by both top-down (i.e., motivations, expectations, interests) and bottom-up factors (i.e., low level stimulus properties) (Hayhoe and Ballard, 2005; Mackay et al., 2012; Schütz et al., 2011). In TD individuals, it has been shown that bottom-up factors have little effect on spontaneous gaze behaviors in the presence of social stimuli. Even when the face was not the most visually salient region of the scene participants fixated exclusively on the face and ignored the most visually salient regions (Birmingham et al., 2009). Given the atypical viewing patterns reported in response to social stimuli in ASD, a

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number of studies have investigated possible differences in bottom-up visual influence on gaze behaviors across groups. These studies relied on a computational approach of visual attention to generate predictions based on elementary features (i.e., orientation, intensity,

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colors) of when and where participants would look within the stimuli (Itti et al., 1998; Itti and Koch, 2001). The authors then measured how well the predictions fit with the gaze

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trajectories of the participants. Fletcher-Watson et al. (2009) found that the gaze behaviors of individuals with ASD and controls were similarly predicted by low-level properties of the

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stimuli, thus arguing against a possible effect of bottom-up factors on atypical viewing patterns in ASD. Note however, that this study found little difference between groups in terms

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of viewing patterns (see section 2.2.2). Freeth et al. (2011) replicated these findings and found no difference in mean saliency at fixation between high-functioning adolescents with ASD

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and TD controls. Nevertheless, they noted that when the face was visually salient, participants with ASD were slower to fixate the face (one fixation later than TD adolescents), a difference

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the authors did not find when the face was not visually salient. In young children, Amso et al.

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(2013) used a similar paradigm and found that the viewing patterns of 41 month-old children

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with ASD were best predicted by bottom-up factors than those of TD children, notably during the first second of presentation and regardless of whether the face was the most salient region of the scene or not. Whereas the aforementioned studies used images of social scene, Shic et al. (2007) presented 42 month-old children with ASD with video clips of a natural free play interaction between a child and an adult. In addition to the basic elementary features (i.e., intensity, orientation and colors), they also computed motion information from the stimuli and found that children with ASD used less motion and more intensity information than TD children. Although it is still too early to draw conclusions about the possible differences in bottomup visual influence across groups, these studies nevertheless underline the importance of controlling for low-level information. Moreover, the analysis of bottom-up influences on

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viewing patterns provides complementary information to the AOI-based approach and adds to the range of eye-tracking data analyses available for researchers (see also Shic et al., 2006).

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7. Limits of remote eye tracking systems to investigate visual social attention The studies reviewed in this paper recorded gaze behaviors in laboratory settings and

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whether the findings of these studies generalize to real life situations remains to a large extent unknown. Even when video-clips of social interactions (i.e., Klin et al. 2002b, Nakano et al.,

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2010, Rice et al. 2012) or of an actress engaging the child (i.e., Chawarska et al., 2012; Jones et al., 2008) are used as stimuli, participants are passive and the scenes usually depict a

an

restricted and static field-of-view. Some attempts have been made to circumvent these limitations (e.g. Aslin, 2009; Merin et al., 2007). For instance, Merin et al. (2007) used a

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display-based live mother-child interaction setting allowing the mother and the child to adjust

a still face paradigm.

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their behaviors relative to the other’s reactions during the pre- and post- still face episodes of

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To date, two head-mounted eye-tracking systems have been developed to record gaze

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behaviors of young children in real-life settings (Franchak et al., 2011; Noris et al., 2011). The one developed by Noris et al. (2011) (WearCam) has been successfully tested with young children with ASD (Magrelli et al. 2013; Noris et al., 2012). Noris et al. (2012) found that 5 year-old children with ASD tended to have a similar field of view to that of TD children but with a decreased looking-time to faces in central vision during structured play tasks. Furthermore, while the frequency of face gaze episodes did not differ between groups, the duration of these episodes was shorter in children with ASD. The authors also noted an increased number of lateral and downward gazes across the broad field of view in children with ASD. They argued that these kinds of gaze behaviors might result from a hypersensitivity to visual stimuli, leading them to adopt a regulatory strategy to limit a sensorial overload and filter high frequency signals. Magrelli et al. (2013) in addition noted

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that children with ASD were slower to orient towards the person interacting with them when she started to speak than TD children. This difference was absent in response to a facial expression from the adult suggesting that social orienting may be more severely affected in

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response to speech in young children with ASD (see also Shic et al., 2014). Though head mounted eye-tracking systems are more widespread for older populations,

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only one study have used such a device in adults with ASD. Falkmer et al. (2011) investigated the influences of static versus interactive dynamic facial stimuli (i.e. a dialogue between the

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participant and one investigator) on gaze behaviors and concluded that the context had little influence on gaze behaviors among individuals with ASD and TD controls. Notably, even

an

though the authors did not perform between-group comparisons, they nevertheless noted that both groups, during the interaction, tended to make fewer fixations on the mouth.

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It is worth noting that these systems have some drawbacks relative to remote eye trackers including more complex data handling. They are also less easy to use, notably with young

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children who might hardly tolerate wearing the head mounted system. Nevertheless,

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preliminary results indicate that gaze behaviors captured in laboratory settings with remote

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eye trackers are to some extent consistent with those of real life situations both in young children and adults (Falkmer et al. 2011; Margrelli et al. 2013). Moreover, while visual scanning of faces in older populations have been mainly studied during the observation of social interactions with remote eye trackers (e.g. Klin et al., 2002b; Norbury et al., 2009; Rice et al., 2012), head mounted systems provide researchers the opportunity to record viewing patterns during a direct interaction with a partner, in a similar way as a number of studies in infants and young children (e.g., Chawarska et al., 2012; Jones et al., 2008; Merin et al., 2007). In addition, head-mounted eye trackers may reveal new atypicalities in the gaze behaviors of individuals with ASD. For instance, the increased number of lateral and downward gazes reported by Noris et al. (2012) has never been observed in studies using remote table eye-trackers. If faces and eyes were to be aversive stimuli for a number of

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individuals with ASD (see Corden et al., 2008; Dalton et al., 2005; Joseph et al., 2008; Kylliänen and Hietanen, 2006; Zürcher et al., 2013), real life situations would be more likely

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to uncover this in their gaze behaviors than screen displays.

8. Conclusion

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More than a decade has passed since eye tracking was first used to investigate the viewing patterns of individuals with ASD in response to social stimuli. Eye tracking has become one

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of the most popular tools in the field of autism research interesting in visual social attention and it has been successfully used from early infancy to adulthood. The main purpose of this

an

review was to examine visual social attention in ASD in light of the eye tracking literature. First, we assessed the assumption that individuals with ASD demonstrate a deficit in

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social orienting and decreased attention to socially relevant stimuli such as faces compared to TD individuals. We found that, overall, the majority of eye tracking studies indicate that

d

individuals with ASD demonstrate decreased visual attention to social stimuli relative to TD

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individuals. However, a further examination of the results revealed that this does not

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generalize across contexts. Especially, we found that increasing the social content, either by including child directed speech or by including several persons interacting with each other, increases the likelihood of reporting decreased attention to faces in participants with ASD. This implies that individuals with ASD do not demonstrate a generalized deficit in attentional engagement towards faces but that it is context-dependent (e.g., Chawarska et al., 2012). We found inconsistencies among studies investigating the ability of individuals with ASD to orient to faces. While they may be as likely as TD individuals to look first towards faces, they are found to be slower to do so when presented with pictures. This pattern of results argue for the view that basic social orienting ability in ASD is not qualitatively impaired in ASD but appears to be less efficient (see Johnson, 2014).

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Second, we reviewed and discussed eye-tracking studies primarily interested in visual scanning of faces. Following Falck-Ytter and von Hofsten (2011), we noted that the excess mouth and diminished eye gaze hypothesis receive little support both in young children and

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older population. We claimed that in young children with ASD, excess mouth and diminished eye gaze should be interpreted in relation to the gaze behavior of TD children in response to

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some specific events inducing increased eye looking. In older participants, though the functional role of mouth looking has been confirmed in high-functioning individuals

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demonstrating a verbal IQ advantage, excess mouth and diminished eye gaze appear to be rather stimulus-specific in this subgroup and might only emerge while observing complex

an

social interactions.

Third, we reviewed eye tracking studies assessing gaze following and referential

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understanding of another person’s gaze. We concluded that more studies are needed in infants and young children with ASD before eye-tracking studies can lead to some significant

d

conclusions on their ability to follow others’ gaze. In older populations there is clear evidence

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of a difficulty in interpreting gaze cue.

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We also covered studies investigating social interaction monitoring, bottom-up influences on gaze behaviors and the use of head-mounted eye tracking systems. These three developing fields of eye tracking research in ASD take full advantage of eye tracking technology and are increasingly revealing the more subtle nature of the profound social difficulties experienced by individuals with ASD in everyday life.

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Acknowledgments This work was supported by a doctoral scholarship to QG from the Fondation Orange, by the

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ESF COST Action BM1004 Enhancing the scientific study of Early Autism (ESSEA) and by a Chaire d’Excellence Pierre de Fermat to NH. The authors would like to thank M.H. Afzali

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te

d

M

an

us

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and three anonymous reviewers for their helpful comments.

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Highlights Findings of eye-tracking studies investigating visual social attention in ASD are reviewed. A generalized deficit in social orienting and engagement with face is not supported. The excess mouth and diminished eye gaze hypothesis is not supported. Interpretation of gaze cues is problematic in ASD. ASD research is benefitting from novel approaches in data acquisition and analyses.

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Table(s)

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VISUAL SOCIAL ATTENTION IN ASD

Age

Matching

12 22 15 35

0.5 0.5 0.5 0.5

CA, VDQ, NVDQ, gender

Falck-Ytter et al. (2013b)

AD TD

10 14

3.4 3.5

CA

Klin et al. (2009)

ASD TD DD

21 39 16

2.2 2.0 2.0

CA, NVMA CA, VMA

25 25 16

4.8 3.1 2.5

d

ep te

ASD TD SLI

Pierce et al. (2010)

ASD TD DD

37 51 22

2.3 1.9 2.1

Shic et al. (2011)

ASD TD DD

28 34 16

1.9 1.7 1.6

Ac c

Nakano et al. (2010), Hosozawa et al. (2012)

Nature of stimuli

an

N

DA

CA CA, VDQ, NVDQ

CA CA, VDQ,

Main results

Dynamic stimuli with child-directed speech, joint attention, making sandwich and moving toys episodes

 Infants later diagnosed with ASD look less at the scene, and when they do so they pay less attention to the person and the face than control groups.

Dynamic point-light displays

 Young children with AD do not look preferentially towards biological motion and audio-visual synchrony.

Dynamic point-light displays

 Toddlers with ASD do not look preferentially towards biological motion contrary to both control groups.  The viewing patterns of toddlers with ASD are correlated with the level of audio-visual synchrony contained in the stimuli.

Dynamic stimuli with speech including social interactions and persons addressing the audience

 Young children with ASD look less at faces than both SLI and TD children.

Dynamic social and geometric stimuli

 As a group, toddlers with ASD spend more time looking at dynamic geometric images than both control groups during a preferential looking paradigm.  60% of ASD spend the same amount of time as TD and DD watching dynamic socially image.

Dynamic stimuli with social interactions and speech (naturalistic play

 Toddlers with ASD look less at the face and at the activity than both controls groups.

M

Study Groups Infants and young children Pros Chawarska et al., ASD (2013) HR-ATYP HR-TYP TD

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Table 1 Assumption #1 Individuals with ASD demonstrate a deficit in social orienting and decreased attention to socially relevant stimuli such as faces compared to TD individuals: Pros and Cons.

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Mixed Chawarska et al. (2012), Campbell et al., 2013)

AD TD DD

54 48 20

1.8 1.7 1.7

Sasson et al. (2011)

AD TD

Sasson and Touchstone (2013)

ASD TD

15 15

3.8 3.3

T1 HR-ASD HR-ATYP

17 12

0.6 0.6

ip t NA

Dynamic stimuli with social interactions and speech (conversation between two women)

 Young children with ASD look less at the speaker than 3-year-old TD children and less at faces in general than both control groups.

Dynamic stimuli with child-directed speech, joint attention, making sandwich and moving toys episodes

 Toddlers with AD look less at the face than both control groups during child-directed speech episodes.  In contrast, the distribution of attention in toddlers with AD does not differ from that in both control groups when looking at non-social scenes.  A cluster analysis (N=65) identifies three subgroups of toddlers with ASD differing in their viewing patterns in response to child-directed speech, including one group with an overall decreased attention to the scene and the face.

Arrays of social and object pictures

 Young children with AD look less at social stimuli than objects only when objects are related to circumscribed interests.

Faces and objects

 Young children with ASD look less at a face than TD children only when the face is paired with an object related to circumscribed interests.  The latency to look at the face is greater in young children with ASD only when the face is paired with an object related to circumscribed interests.

Arrays of face and object pictures

 All infants demonstrate a face pop out effect at T1 and T2, and spend a similar proportion of time on faces, regardless of clinical outcomes.

us

4.7 1.0 3.0

CA CA, VMA, NVMA

an

10 12 12

interaction between an adult and a child)

M

ASD TD group1 TD group2

NVDQ

Cons Elsabbagh et al. (2013c)

ep te

d

Von Hofsten et al. (2009)

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VISUAL SOCIAL ATTENTION IN ASD

3.6 3.3

Ac c

9 13

CA

CA, gender

CA

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T2 HR-ASD HR-ATYP HR-TYP TD

17 12 22 47

1.2 1.2 1.2 1.2

Older children, adolescents and adults Pros Bird et al. (2011) ASD 13 TD 13

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0.6 0.6

an

21 50

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HR-TYP TD

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VISUAL SOCIAL ATTENTION IN ASD

Dynamic stimuli with speech including social interactions and persons addressing the audience

 Adults with ASD show no preference for faces relative to non-social stimuli.  Adults with ASD are less likely to attend to faces than TD controls.  Adolescents with AD look less at faces than TD controls.

CA NV ability

Dynamic stimuli with social interaction and speech

 Adolescents with AD look less at faces than TD controls.  Adolescents with AD are slower to direct their attention towards faces.

CA, IQ

20 20 20

13.0 13.0 5.0

CA NV ability

20 20 20

13.0 13.0 5.0

AD TD group1 TD group2

Static pictures of social interactions

Riby and Hancock (2009a)

AD TD group1 TD group2

Riby and Hancock (2009b)

AD TD

24 24

12.3 13.0

NV ability

Static pictures with embedded faces

Sasson et al. (2008)

ASD

29 24

9.5 9.5

CA

Arrays of social and object pictures

 Children with ASD explore fewer images, spend more time per image explored and make more fixations per image explored than TD children for both social and object array.

24

13.8

Static pictures of indoor scenes containing one

 Adolescents with ASD and TD controls spend a similar looking time to faces.

Mixed Freeth et al. (2010)

Ac c

Riby and Hancock (2008)

ep te

d

40.5 32.8

Exp1 ASD

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ip t

14

CA, IQ

22 22

14.9 14.7

CA, VIQ

Hanley et al. (2013)

ASD TD

14 14

20.5 20.3

CA, gender, IQ

Wilson et al. (2010)

ASD TD

13 14

10.1 10.7

CA

Cons Fletcher-Watson et al. (2009)

ASD TD

12 15

18.8 21.5

CA

Fisher et al. (2013)

ASD TD

44 40

9.2 8.6

CA, NVIQ

Kuhn et al. (2010)

ASD TD

19 21

CA, IQ

ASD TD

27 27

29.5 32.1

NA

Nakano et al. (2010)

person

us

24

 Adolescents with ASD are slower in their first fixation to faces than TD controls.

Static pictures of scenes containing one to several persons

 Children with ASD demonstrate an evenly distributed pattern of attention across faces and objects, while TD control demonstrate a preference for faces.  Children with ASD and TD controls have a similar latency to look at people.

Static pictures of personpresent and person-absent scenes

 Adults with ASD, as TD controls, preferentially look at a present-person scene.  Adults with ASD, as TD controls, preferentially look first at the person-present scene.

Faces and objects

 Children with ASD and TD children demonstrate faster saccadic reaction times when the peripheral target is a face than when it is an object in a gap/overlap paradigm.

15 18

Dynamic isolated magician

 Adults with ASD look first at the face.  Adults with ASD and TD controls demonstrate a similar looking-time to the face.

Dynamic stimuli with speech including social interactions and persons addressing the audience

 Adults with ASD and TD controls demonstrate a similar looking time to faces.

d

M

an

 Adults with ASD only show decreased attention to faces when presented with social scenes. No between-group difference is found for isolated face pictures.

Ac c

Static isolated emotional face pictures and social scenes

ep te

TD Exp2 ASD TD

cr

VISUAL SOCIAL ATTENTION IN ASD

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ip t cr

VISUAL SOCIAL ATTENTION IN ASD

us

Note. Age mean is expressed in years; AD, autistic disorder; ASD, autism spectrum disorder; CA, group matching on Chronological Age; DA, group matching on Developmental Age; DD, developmental delay; HR-ASD, infants at-risk for ASD with ASD outcome; HR-ATYP, infants at-

an

risk for ASD with other developmental concerns at outcome; HR-TYP, infants at risk for ASD with typical outcome; IQ, group matching on Intelligence Quotient; NA, data not available; NV ability, group matching on non-verbal ability; NVDQ, group matching on Non-Verbal

M

Developmental Quotient; NVMA, group matching on Non-Verbal Mental Age; PIQ, group matching on Performance IQ; SLI, specific language impairment; T1, time of first examination; T2, time of second examination; TD, typically developing; VDQ, group matching on Verbal

Ac c

ep te

d

Developmental Quotient; VIQ, group matching on verbal IQ; VMA, group matching on Verbal Mental Age.

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ip t

Table(s)

cr

VISUAL SOCIAL ATTENTION IN ASD

Chawarska et al. (2012), Campbell et al. (2013)

Chawarska et al., (2013)

AD TD DD

HR-ASD HR-ATYP HR-TYP TD

15 36 15

2.3 2.0 2.1

CA, NVMA CA, VMA

14 30 15 15

2.3 3.8 2.2 3.8

54 48 20

1.8 1.7 1.7

12 22 15 35

0.5 0.5 0.5 0.5

Nature of stimuli

an

Matching

Dynamic stimuli with child-directed speech (e.g. pat-a-cake)

M d

ASD group1 ASD group2 TD group1 TD group2

Age

CA CA, VMA, NVMA

CA, VDQ, NVDQ, gender

Main results  Toddlers with ASD look less at the eyes and more at the mouth in comparison to both control groups.  Looking at the eyes predict the level of social impairment in toddlers with ASD.

Static isolated neutral face pictures

 Young children with ASD look less at internal facial features, especially the mouth.  No between-group difference is found regarding the eyes.

Dynamic stimuli with child-directed speech, joint attention, making sandwich and moving toys episodes

 Toddlers with AD look less at the mouth than both control groups during child-directed speech episodes.  There is no between-group difference for the eyes.  Decreased attention to the speaker’s face and her mouth is associated with atypical language profiles in AD.  A cluster analysis (N=65) identifies three subgroups of toddlers with ASD differing in their viewing patterns in response to child-directed speech, including one group with increased mouth-looking relative to eye-looking, and one group with no preference either for the mouth or the eyes.

Dynamic stimuli with child-directed speech, joint attention, making sandwich and moving toys episodes

 At 6 months, high-risk infants later diagnosed with ASD do not differ from control groups in attention directed to the eyes and the mouth.

CA CA

Ac c

Cons Chawarska and Shic (2009)

N

ep te

Study Groups Infants and young children Pros Jones et al. (2008) ASD TD DD

us

Table 2 Assumption #2: Individuals with ASD exhibit excess mouth and diminished eye gaze compared to TD individuals: Pros and Cons.

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T1 HR-ASD HR-ATYP HR-TYP TD

17 12 24 50

0.6 0.6 0.6 0.6

T2 HR-ASD HR-ATYP HR-TYP TD

17 12 23 48

1.2 1.2 1.2 1.2

ASD TD

15 15

5.2 4.9

Jones and Klin (2013)

Merin et al. (2007), Young et al. (2009)

Ac c

Falck-Ytter et al. (2010)

ip t  Young children with ASD and TD controls show similar patterns of attention to the eyes and the mouth.

Dynamic stimuli including a peek-a-boo sequence, an eyes moving episode, a mouth moving episode and a hand moving episode

 Infants later diagnosed with ASD and other infants have similar patterns of attention towards the eyes and the mouth during the peek-a-boo sequence.  Increased mouth looking at 7 months predicts superior expressive language outcome at 36 months in all groups.  This relationship appears to be context-dependent. The opposite relationship is found during mouth moving episode.  In high-risk infants, increased mouth looking is associated with increased severity of symptoms during mouth moving episode.

Dynamic emotional face stimuli without speech and static isolated emotional face pictures

 Young children with ASD and TD controls show similar patterns of attention to the eyes and the mouth.  Young children with ASD who are better at socio-emotional behaviors than non-verbal communication look more at the eyes relative to the mouth.  Young children with the opposite clinical profile look more at the mouth relative to the eyes.

CA, gender

Dynamic stimuli with child-directed speech (e.g. pat-a-cake)

 Infants later diagnosed with ASD demonstrate significant decline in looking time to the eyes from 2 to 6 months of age  At 2 months, infants later diagnosed with ASD and TD infants have similar looking time to the eyes.  In infants later diagnosed with ASD, steeper decline in eyelooking is associated with more sever social disability.

CA

Dynamic stimuli with child-directed speech (live)

 Ten out of 11 infants who pay less attention to their mother’s eyes relative to her mouth have an older sibling with ASD.  None of those toddlers receive a diagnosis of ASD at 24 months.

NA

us

Elsabbagh et al. (2013a)

Static isolated emotional face pictures

CA

an

5.2 4.9

M

13 14

d

ASD TD

ep te

De Wit et al. (2008)

cr

VISUAL SOCIAL ATTENTION IN ASD

ASD TD

11 25

From 2 to 24 months

ASD-sibs TD-sibs

31 24

0.5 0.5

CA

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25 25 16

4.8 3.2 2.5

Shic et al. (2013)

HR-ASD HR-ATYP HR-TYP TD

12 29 16 42

0.5 0.5 0.5 0.5

ip t Dynamic stimuli with speech including social interactions and persons addressing the audience

an

ASD TD SLI

DA

ep te

Ac c

Older children, adolescents and adults Pros Klin et al. (2002b) ASD 15 TD 15

Cons Bird et al. (2011)

ASD TD

d

M

Nakano et al. (2010), Hosozawa et al. (2012)

us

cr

VISUAL SOCIAL ATTENTION IN ASD

13 13

CA, VDQ, NVDQ, gender

15.4 17.9

VIQ

40.5 32.8

CA, IQ

 Those who received a diagnosis of ASD demonstrate typical eye gaze at 6 months.  Increased mouth looking at 6 months predicts better expressive language development.  Relative to the time spent looking at the scene, young children with ASD spend less time looking at the eyes than TD children.  They also spend less time looking at the mouth than both TD and SLI children.  Relative to the time spent looking at the face, young children with ASD spend more time looking at the eyes than SLI children and less time looking at the mouth.

Facial close-up dynamic stimuli with speech, static isolated emotional and neutral face pictures

 The distribution of attention to the eyes relative to the mouth is similar across groups and do not predict clinical outcome.  During a speech condition, infants later diagnosed with ASD demonstrate decreased attention towards inner features and increased fixation towards outer regions of the face.

Dynamic stimuli with social interaction and speech

 Verbally able high-functioning adolescents with ASD demonstrate look more at the mouth and less at the eyes than TD controls.  Increased mouth looking is associated with better social competence.

Dynamic stimuli with speech including social interactions and persons addressing the audience

 Adults with ASD look less at the eyes, but their eye:mouth ratio is similar to that of TD controls.  Adults with ASD do not show any preference for either the mouth or the eyes, whereas TD controls preferentially attend

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ip t cr

VISUAL SOCIAL ATTENTION IN ASD

Corden et al. (2008)

AS TD

18 17

32.9 31.9

Hanley et al. (2013)

ASD TD

14 14

20.5 20.3

Hernandez et al. (2009)

AD TD

11 22

24.1 22.7

McPartland et al. (2011)

ASD TD

17 15

14.5 14.5

CA, IQ

Nakano et al. (2010)

ASD TD

27 27

29.5 32.1

NA

14 14 18

14.9 14.9 14.5

AD-NL AD-IL TD

an

Static isolated emotional face pictures

NA

CA, NV ability

 Adults with ASD look less at the eyes than TD controls, regardless of emotion.  Adults with ASD tend to look more at the mouth but this does not reach significance.  Neither the time spent looking at the eyes nor the mouth is associated with the severity of autistic symptomatology.

Static isolated emotional face and social scenes pictures

 Adults with ASD look less at the eyes than TD controls when presenting with static social scenes but not with static isolated faces.  There is no between-group difference for the mouth.

Static isolated emotional face pictures and neutral avatars

 Adults with AD look less at the eyes than TD controls, regardless of emotion or stimuli.  There is no between-group difference for the mouth.

Static isolated neutral face pictures

 Adolescents with ASD and TD controls have similar patterns of attention towards the eyes and the mouth.

Dynamic stimuli with speech including social interactions and persons addressing the audience

 Relative to the time spent looking at the scene, adults with ASD look less at the eyes than TD controls.  Relative to the time spent looking at the face, adults with ASD look more at the mouth than TD controls.

Dynamic stimuli with social interaction and speech

 Adolescents with ASD with language impairments and TD controls have similar patterns of attention towards the eyes and the mouth.  Adolescents with ASD without language impairments look less at the eyes than TD controls.  In both groups of ASD, increased looking time to the eyes is associated with decreased communication skills, on the contrary to looking time to the mouth, which is associated

M

d

CA, gender, IQ

ep te

Ac c

Norbury et al. (2009)

CA, gender, IQ

us

to the eyes.

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ip t cr

VISUAL SOCIAL ATTENTION IN ASD

us

with better communication skills.

AD TD

5 5

25.2 28.2

NA

Static isolated emotional face pictures

 Adults with AD look less at inner features of faces, especially the eyes than TD controls.

Sepeta et al. (2012)

ASD TD

20 18

12.4 13.7

CA, PIQ

Static isolated emotional face pictures

 Adolescents with ASD and TD controls have similar patterns of attention towards the eyes and the mouth.

AD TD

12 12

13.6 13.3

Dynamic stimuli with social interaction and speech and static isolated emotional faces pictures

 Adolescents with AD look less at the eyes for social-dynamic stimuli.  There is no between group difference with respect to the eyes and mouth for isolated-dynamic faces, social-static scenes and isolated-static faces.  Looking time to the eyes is associated with social responsiveness.

Static isolated neutral face pictures

 Adults with ASD look less at the eyes than TD controls.  There is no between group difference for the mouth.

Static pictures of social interactions

 Adolescents with AD less at the eyes than both TD controls.  There is no between-group difference for the mouth.

Dynamic stimuli with social interaction and speech

 Adolescents with AD less at the eyes than both TD controls.  There is no between group difference for the mouth.

Dynamic stimuli with social interaction and speech

 Children with ASD look less at the eyes and at the mouth than TD controls.  IQ profile has a moderating effect on attention towards the mouth in children with ASD.

Static isolated emotional face pictures

 Children with AD and TD controls have similar patterns of attention towards the eyes and the mouth.

M

CA, IQ

ASD TD

Riby and Hancock, (2008)

AD TD group1 TD group2

Riby and Hancock, (2009a) Rice et al. (2012)

Van der Geest et al. (2002)

17 18

23.5 24.2

20 20 20

13.0 13.0 5.0

AD TD group1 TD group2

20 20 20

13.0 13.0 5.0

ASD TD

37 26

10.0 9.5

ASD

72

10.2

CA, gender, IQ Non-matched

AD TD

17 17

10.6 10.1

CA, IQ

Ac c

Sterling et al. (2008)

ep te

d

Speer et al. (2007)

an

Pelphrey et al. (2002)

CA, IQ

CA NV ability

Page 63 of 64

18 20

17.0 17.9

ip t Static isolated emotional face pictures

us

ASD TD

CA

 Adolescents with ASD and TD controls have similar patterns of attention towards the eyes and the mouth.

an

Wagner et al. (2013)

cr

VISUAL SOCIAL ATTENTION IN ASD

Note. Age mean is expressed in years; AD, autistic disorder; AD-IL, autistic disorder with language impairment; AD-NL, autistic disorder with

M

normal language; AS, Asperger syndrome; ASD, autism spectrum disorder; CA, group matching on Chronological Age; DA, group matching on Developmental Age; DD, developmental delay; HR-ASD, infants at-risk for ASD with ASD outcome; HR-ATYP, infants at-risk for ASD with

d

other developmental concerns at outcome; HR-TYP, infants at risk for ASD with typical outcome; IQ, group matching on Intelligence Quotient;

ep te

NA, data not available; NV ability, group matching on non-verbal ability; NVDQ, group matching on Non-Verbal Developmental Quotient; NVMA, group matching on Non-Verbal Mental Age; PIQ, group matching on Performance IQ; SLI, specific language impairment; T1, time of first examination; T2, time of second examination; TD, typically developing; VDQ, group matching on Verbal Developmental Quotient; VMA,

Ac c

group matching on Verbal Mental Age.

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