Determining the 'speed thresholds' that autistic and non-autistic individuals attribute to emotional expressions

Autism spectrum disorder (ASD) is clinically characterised by difficulties in social communication and restricted and repetitive interests (American Psychiatric Association, 2013). Despite mixed findings, a large body of research suggests that autistic individuals have difficulties recognising the emotion of other individuals from their facial expressions (see Keating & Cook, 2020 , Uljarevic & Hamilton, 2013 and Harms, Martin & Wallace, 2010 for reviews). Importantly, many of these empirical studies indicate that autistic individuals exhibit emotion-specific difficulties in static emotion recognition, with some studies claiming that the recognition of anger is particularly challenging for autistic individuals (Ashwin, Chapman, Colle & Baron-Cohen, 2006; Bal et al., 2009; Brewer et all., 2016; Song & Hakoda, 2017; Leung et al., 2019). Indeed, more support for this idea comes from meta-analytic evidence, which suggests that there are greater ASD-control group differences in the recognition of angry than happy and sad expressions (Lozier et al., 2014). This is interesting since recent evidence indicates that autistic individuals (relative to non-autistic individuals) require angry, but not happy or sad, expressions to have higher emotional intensity in order for them to be correctly identified (Song & Hakoda, 2018). In this study, static photographic stimuli at varying expressive intensities (constructed by repeatedly morphing a full expression with a neutral expression to result in 9 intensity levels for each emotion) were used to identify the ‘discrimination threshold’ (the intensity at which an expression is identified correctly on two consecutive trials) for autistic and control participants. This study identified that, compared to control participants, autistic individuals had a significantly higher discrimination threshold for angry expressions, meaning that a higher intensity was necessary before an expression could be correctly identified as angry. Importantly, this study also found no significant group-differences in discrimination thresholds for happiness or sadness (Song & Hakoda, 2018). Since these findings suggest that autistic individuals have a different discrimination threshold for static angry expressions, perhaps the same could be true for dynamic angry expressions; however to date, no studies have attempted to test this idea. In our recent study, we used point-light displays (a series of dots that convey biological motion) of the face (point light faces; PLFs) to compare the emotion recognition of autistic and neurotypical individiuals. In the study, the PLFs had been manipulated to achieve three spatial levels, ranging from reduced to increased spatial movement (S1 – 50% spatial; S2 – 100%; S3 – 150%), and three kinematic levels, ranging from reduced to increased speed (K1 – 50% speed; K2 – 100%; K3 – 150%; as in Sowden et al., under review). There were two key findings of our recent study (Keating et al., in prep). Firstly, the autistic participants (relative to controls who were matched on age, gender, non-verbal reasoning and alexithymia) had significantly lower emotion recognition accuracy for dynamic angry (but not happy or sad) expressions moving at a normal (K2 – 100%) speed and with normal (S2- 100%) level of spatial movement. Secondly, whilst for controls, recognition accuracy increased when angry expressions were sped up from 50% to 100% speed and from 100% to 150% speed, the recognition accuracy of autistic participants only increased from 100% to 150% (and not from 50% to 100%). Hence, these findings suggest that just as autistic participants may have difficulties with static angry expressions, they may also have difficulties recognising dynamic angry expressions. Moreover, these findings highlight the possibility that autistic individuals may have a different ‘speed threshold’ for dynamic angry expressions (i.e. an angry expression has to be moving relatively more quickly before it is labelled angry for ASD participants) in addition to differing thresholds for static angry expressions. Therefore, the present study will utilise dynamic PLF stimuli to identify whether autistic and neurotypical individuals possess different speed thresholds for dynamic emotional expressions. One reason that autistic individuals, relative to controls, may have particular difficulty with angry expressions is due to differences in preferential looking. There is some evidence to suggest that autistic individuals tend to avoid looking at the eye region of the face, and instead preferentially look at the mouth region (Klin, Jonres, Schultz, Volkmar & Cohen, 2002; Riby, Doherty-Sneddon & Bruce, 2009; Rutherford, Clements, & Sekluer, 2007; Wolf et al., 2008). Since the majority of the expressive information for angry faces is thought to be conveyed in the upper half of the face (Calder, Young, Keane, & Dean, 2000; Smith & Cottrell, 2005), this could explain why autistic individuals may have particular difficulty with angry expressions. In order to explore whether autistic and neurotypical individuals possess different speed thresholds for the eye and mouth regions respectively, we will also include stimuli displaying just the eye and just the mouth regions (in addition to full face PLF stimuli). Alexithymia When examining the emotion recognition ability of autistic individuals, it is crucial to also consider the role of alexithymia. Alexithymia is a subclinical condition characterised by difficulties identifying, differentiating and expressing emotions (Kooiman, Spinhoven & Trijsburg, 2002). The incidence of alexithymia is high in the autistic population, with 40-65% of autistic adults reaching criteria (Berthoz & Hill, 2005; Berthoz & Frith, 2004) compared to just 13% of the general population (Salminen et al., 1999). The “alexithymia hypothesis” (Bird and Cook, 2013) proposes that difficulties in emotion-processing (including emotion recognition) in ASD are caused by co-occurring alexithymia, rather than ASD itself (Bird & Cook, 2013). There are mixed findings relating to this hypothesis, with some studies finding that there are no group-differences in static facial expression recognition (Cook, Brewer, Shah & Bird, 2013), and others finding that group-differences remain for dynamic expressions (Keating et al., in prep) when autistic and neurotypical participants are matched on alexithymia. Nevertheless, in this study we will aim to match participants groups on alexithymia to ensure that any group-differences that we discover are related to autistic (and not alexithymic) characteristics. The current study Participants will first complete various questionnaires including the Autism Quotient (AQ; Baron-Cohen, et al., 2006), and the Toronto Alexithymia Scale (TAS; Bagby, et al., 1994). Next, participants will complete the PLF slider task. This involves participants moving a slider to manipulate the speed of a PLF video (which either displays the full face, the eye region or the mouth region) until it matches what they perceieve as the speed of a typical angry, happy or sad expression. This task will allow us to identify whether a ‘speed threshold’ exists for dynamic facial expression and compare the thresholds of autistic and control individuals. Finally, participants will complete the Matrix Reasoning Item Bank (MaRs-IB; Chierchia et al. 2019), which assesses non-verbal reasoning.

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