31893
Heart Rate Variability and Psychopathology Influences on Face Recognition in People with and without ASD
A significant body of research has examined face recognition in individuals with ASD and while this research suggests that they often exhibit deficits, studies have demonstrated important variability. However, most previous studies have compared average performance between an ASD group and a control group, ignoring the important heterogeneity occurring within ASD. It is well known that there is a high prevalence of comorbid psychopathology in ASD, such as anxiety and depression, and that individuals with anxiety and depression also experience face processing dysregulation. Moreover, research suggests sympathetic over- arousal, parasympathetic underactivity, or atypical interaction of both systems in ASD and literature in the general population shows that greater arousal, shown by lower heart rate variability, affects cognitive skills such as facial emotion processing. We hypothesised that autistic trait severity, anxiety, depression and ANS arousal together may negatively impact face recognition performance in individuals with and without ASD.
Objectives:
(1) Evaluate if autistic, social anxiety, anxiety and depression traits are correlated with face-recognition performance; (2) Assess if HRV is linked to face recognition; and (3) Determine which factors emerge as significant predictors of face recognition performance.
Methods:
Participants were 30 adults (21 typically developing, 9 with ASD) aged 18 to 59 years (M = 31.93, SD = 12.5 years). Participants undertook a face recognition task and completed online questionnaires evaluating autistic traits (abridged Adult Autism Spectrum Quotient; AQ-short), anxiety and depression (Hospital Anxiety and Depression Scale; HADS) and social anxiety (Severity Measure for Social Anxiety Disorder; SMSAD). Heart rate variability (RMSSD) during baseline and while performing the task was collected and analysed. According to the literature age, non-verbal intelligence (WASI-II) and gender can impact on face recognition, thus these variables were controlled for when examining performance. We utilised 5000 bootstrapped samples for correlation and regression analyses examining the relationship between face recognition variables, diagnosis, psychopathology scales, autistic traits and HRV.
Results:
Face recognition accuracy (A prime) was negatively associated with SMSAD BCa 95% [-.79;-.07] and task_RMSSD r=-.455, BCa 95% [-.72;-.12]. Response bias was associated with task_RMSSD r=.411, BCa 95% [-.76;-.07]. Hit rate correlated with HADS_ Anxiety r=-.459, BCa 95% [-.75;-.09] and task_RMSSD r=-.509, BCa 95% [-.75;-.22]. Finally, false alarm rate was associated with diagnosis r=.445, BCa 95% [.08;.76]. Regression analyses showed that task-RMSSD emerged as unique significant predictor for A prime (β=-.39, BCa 95% [-.004;-.001]) and response bias (β=.41, BCa 95% [.001;.014]). However, for hit rate both HADS_Anxiety (β=-.38, BCa 95% [-.285;-.026]) and Task-RMSSD (β=-.49, BCa 95% [-.073;-.016]) emerged as unique predictors, while age was a unique predictor (β=.40, BCa 95% [.021; .253]) for false alarm rate.
Conclusions:
These results suggest that levels of social anxiety, general anxiety and HRV affect face recognition above ASD traits or diagnosis. These results also demonstrate that distinct psychopathology symptoms affect different face recognition variables and could explain the important heterogeneity within the ASD population. Findings emphasise the need to evaluate individual differences (psychopathology, arousal) and their impact on cognition.