IMFAR 2016

I am excited about presenting this poster at the 2016 International Meeting for Autism Research (IMFAR):


The poster is based on these two papers:

Chita-Tegmark, M. (2016). Social attention in ASD: A review and meta-analysis of eye-tracking studies. Research in developmental disabilities48, 79-93.

Chita-Tegmark, M. (2016). Attention allocation in ASD: A review and meta-analysis of eye-tracking studies. Review Journal of Autism and Developmental Disorders, 1-15.

If you’d like to connect with me to ask me questions about this or other projects, or if you’d like to collaborate with me on a research project, you can find me on Research Gate or you can send me an e-mail at You can also find out more about my other research interests and projects here.

Below is a fairly technical abstract of my poster presentation. For a more accessible description check out my research page.

Social Attention in ASD: Meta-Analyses of Eye-Tracking Studies

Determining whether social attention is reduced or atypical in Autism Spectrum Disorder (ASD) and what factors influence social attention is important to our theoretical understanding of developmental trajectories of ASD and to designing targeted interventions for ASD. Eye-tracking technology has facilitated research of social attention and results from experimental studies correlate with measures of social impairment and with autism symptom severity. For example, studies have found that reduced attention to social stimuli or increased attention to non-social stimuli is correlated with behavioral measures of autism. (Bird, Press, & Richardson, 2011; Chawarska, Macari, & Shic, 2012; Klin, Jones, Schultz, Vokmar & Cohen, 2002, Shic, Bradshaw, Klin, Scassellati, & Chawarska, 2011).

However, so far no consensus has been reached on whether social attention is fundamentally reduced or absent in individuals with ASD, with some studies showing significantly diminished attention to social information in ASD compared to typically developing (TD) controls (Klin et al., 2002; Kirchner, Hatri, Heekeren & Dziobek, 2011; Riby & Hancock, 2009; Riby, Hancock, Jones, Hanley, 2013; Rice, Moruchi, Jones, Klin, 2012; Shi et al., 2015; Shic, Bradshaw, Klin, Scassellati, & Chawarska, 2011), while other studies show no differences (Birmingham, Cerf & Adolphs, 2011; Freeth, Chapman, Ropar & Mitchell, 2010; Freeth, Ropar, Mitchell, Chapman, & Loher, 2011; van der Geest, Kemner, Camfferman, Verbate & van Engeland, 2002; Kemner, van der Geest, Verbaten, van Engeland, 2007; Kuhn, Kourkoulou, & Leekam, 2010; Marsh, Pearson, Ropar & Hamilton, 2015; Nadig, Lee, Singh, Bosshart & Ozonoff, 2010; Parish-Morris, Chevallier, Tonge, Letzen, Pandey & Schultz, 2013).

Similarly, no consensus has been reached regarding whether attention is allocated atypically to social stimuli in ASD. Some eye-tracking studies have found that, relative to TD controls, individuals with ASD spend a reduced amount of time attending to the eyes area of interest (AOI; Auyeung et al., 2015; Dalton et al., 2005; Dalton, Nacewicz, Alexander, Davidson, 2007; Hanley, McPhillips, Mulhern, & Riby, 2013; Hernandez et al., 2009; Jones, Carr & Klin, 2008; Klin et al., 2002; Norbury et al., 2009; Rice et al., 2012; Speer et al., 2007; Sterling et al., 2008) while other studies have found no significant differences (Asberg Johnels, Gillberg, Flack-Ytter, & Miniscalco, 2014; Birmingham, Cerf & Adolphs, 2011; Fletcher-Watson, Leekam, Benson, Frank, & Findlay, 2009; Gastgeb, Wilkinson, Minshew, & Strauss, 2011; Grossman, Steinhart, Mitchell, & McIlvane, 2015; Kirchner, Hatri, Heekeren, & Dziobek, 2011; Kuhn, Kourkoulou, & Leekam, 2010; Rutheford & Towns, 2008; Sawyer, Williamson, & Young, 2012; Tenenbaum et al., 2014; van der Geest, Kember, Verbaten, & van Engeland, 2002; Wagner, Hirsch, Vogel-Farley, Redcay, & Nelson, 2013; Wilson, Palermo, & Brock, 2012; Zamzow et al., 2014). With regards to looking at mouths, studies have previously found both reduced looking time for individuals with ASD (Rice et al., 2012; Sterling et al., 2008), increased looking time for individuals with ASD (Asberg Johnels et al., 2014; Gastgeb et al, 2011; Grossman et al., 2015; Jones et al., 2008; Klin et al., 2002) and no statistically significant differences (Auyeung et al., 2015; Birmingham et al., 2011; Dalton et al., 2005; Kirchner et al., 2011; Rutheford et al., 2008; Sawyer et al., 2011; Tenenbaum et al., 2014; van der Geest et al., 2002; Wagner et al., 2013; Wilson et al., 2012; Zamzow et al., 2014). Studies have found both reduced attention to faces in ASD (e.g. Rice et al., 2012), and no significant differences (Birmingham et al, 2011; Dalton et al., 2005; Dalton et al., 2007; Gastgeb et al., 2011; Kuhn et al., 2010). With regards to the body AOI, results are again very mixed with studies finding reduced attention to the body (Fletcher-Watson et al., 2009), increased attention to the body (Hanley et al., 2013; Klin et al., 2002; Rice et al., 2012; Speer et al., 2007; Shic, Bradshaw, Klin, Scassellati, & Chawarska, 2011) and no significant differences (Birmingham et al, 2011; Jones et al., 2008; Norbury et al., 2009; Sasson et al., 2007). Mixed results are reported for looking time to non-social AOIs as well, some studies finding no differences between ASD and TD controls (Birmingham et al, 2011; Norbury et al., 2009) and others finding increased attention to non-social AOIs in ASD (Klin et al., 2002; Kuhn et al., 2010; Rice et al., 2012). Finally, some but not all studies have reported reduced attention to the screen overall (e.g. Shic, Chawarska, Bradshaw, & Scassellati, 2008).

I conducted two meta-analyses examining data from 38 and 68 papers respectively that used eye-tracking methods to compare individuals with ASD and TD controls. The goal of the first meta-analysis was to search for quantitative answers to the following two questions: 1) Do individuals with ASD show overall diminished social attention? and 2) What are the factors that affect how they distribute their attention between social and non-social stimuli? I examined the impact of eight factors on the difference in social attention between these two groups: age, non-verbal IQ matching, verbal IQ matching, motion, social content, ecological validity, audio input and attention bids.

The goal of the second meta-analysis was to investigate whether overall attention allocation in ASD is atypical, namely whether individuals with ASD distribute their attention to different parts of social stimuli (eyes, mouths, faces, bodies) in atypical ways and whether they attend atypically to non-social stimuli. This meta-analysis explores possible differences in overall attention allocation between individuals with ASD and TD controls for the following AOIs: eyes, mouth, face, body, non-social elements and the entire screen.

Results show that individuals with ASD spend less time attending to social stimuli than typically developing (TD) controls, with a mean effect size of 0.55. Also, social attention in ASD was most impacted when stimuli had a high social content (showed more than one person). Results also suggest the presence of atypical attention allocation in ASD, indicated by small but significant effect sizes: overall reduced attention to the eyes (d=0.33), mouth (d=0.25) and face (d=0.4), increased attention to the body (d=-0.48) and non-social elements (d=-0.34), and reduced attention to the screen (d=0.53). This pattern of findings suggests less accessing of social information by individuals with ASD.

These meta-analyses offer a birds-eye view of the attention allocation landscape in ASD and show that, overall, individuals with ASD allocate their attention to the world surrounding them in atypical ways, with reduced attention to areas high in social information. They also provide a detailed survey of the eye-tracking research on social attention in ASD, and provide the opportunity to outline potential future research directions, more specifically research of social attention in the context of stimuli with high social content.