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    • In the current study we examined ensemble perception of

    2018-10-25

    In the current study, we examined ensemble perception of emotions in autistic children and adolescents, and contrasted these with typical children, adolescents and adults. Autism is a highly heterogeneous neurodevelopmental condition known for difficulties in social interaction and communication. However, autism is also characterised by atypicalities in sensation and perception (DSM-5; American Psychiatric Association, 2013; see Simmons et al., 2009; for review). Many studies have focused on the processing of social stimuli and of faces in particular. This literature presents a confusing picture. While many studies have reported that autistic children present pervasive difficulties in emotion discrimination (see Uljarevic and Hamilton, 2012; for review), other studies have found such difficulties specifically for negative or more complex emotions (Jones et al., 2011) or no difficulties at all (Ozonoff et al., 1990; Tracy et al., 2011). Prominent theories have suggested difficulties in social perception might be driven by fundamental problems in global processing (weak central coherence; Happé and Frith, 2006) or a local-processing bias that leads to strengths in the processing of simple stimuli and to weaknesses in the processing of more complex stimuli (Mottron et al., 2006). We have suggested that the unique perceptual experiences of individuals with autism might be accounted for by attenuated prior knowledge within a Bayesian computational model of perceptual inference (Pellicano and Burr, 2012). This metforman posits limitations in the abilities of individuals with autism to derive, maintain and/or use efficiently summary statistics representations for the recent history of sensory input. Such limitations lead to a processing style where sensory input is modulated to a lesser extent by norms derived from prior sensory experience. Karaminis et al. (2016) have recently demonstrated this account formally, in the context of temporal reproduction, using a Bayesian computational model for central tendency (Cicchini et al., 2012), which suggested that the phenomenon reflects the integration of noisy temporal estimates with prior knowledge representations of a mean temporal stimulus. Karaminis et al. (2016) contrasted the predictions of this ideal-observer model with data from autistic and typical children completing a time interval reproduction task (measuring central tendency) and a temporal discrimination task (evaluating temporal resolution). The simulations suggested that central tendency in autistic children was much less than predicted by computational modelling, given their poor temporal resolution. Pellicano and Burr’s (2012) hypothesis has also received empirical support from studies showing diminished adaptation in the processing of face (e.g., Pellicano et al., 2007; Pellicano et al., 2013) and non-face stimuli (e.g., Turi et al., 2015; van Boxtel et al., 2016). Such findings appear to generalise to ensemble perception, i.e., summary statistics representations derived on a trial-by-trial basis from stimuli presented simultaneously and for brief time intervals. Rhodes et al. (2015) have developed a child-appropriate version of a paradigm for ensemble perception of face-identity (Neumann et al., 2013), which they administered to 9 autistic children and adolescents and 17 age- and ability-matched typical children. These authors found reduced recognition of averaged identity in autistic participants. In the current study, we evaluated two predictions, based on Pellicano and Burr (2012), for the patterns of performance of autistic and typical children and adolescents (aged between 6 and 18 years; hereafter ‘children’) by developing a developmentally-appropriate version of Haberman and Whitney (2007)’s paradigm for ensemble perception of emotions. First, we predicted that autistic children should present difficulties in Task 1 assessing average emotion discrimination (see Fig. 1), evidenced by lower precision than typical children in the average relative to the baseline emotion discrimination task (as autistic children/adolescents might present general difficulties in emotion discrimination; Uljarevic and Hamilton, 2012). We further tested this prediction using computational modelling and eye-tracking methodologies. Computational simulations (akin to Sweeny et al., 2014) should suggest a weaker ensemble coding advantage and fewer items sampled in autistic children compared to typical children. Eye-tracking data could also reveal atypicalities in the ways autistic children attended to the stimuli (e.g., in the number of faces sampled).