Improved emotion differentiation under reduced acoustic variability of speech in autism.

Researchers studied how autistic children recognize emotions in voices compared to typical children. They found that autistic children had trouble understanding emotions in natural human voices, but did much better when listening to computer-generated voices that had less variation in sound. Brain activity patterns were different between the two groups. This suggests that reducing the complexity of sounds might help autistic children better understand emotions in speech.

This controlled study of 80 children (40 autistic, mean age 9.7 years) investigated emotion recognition from speech prosody using EEG measurements. Autistic children showed impaired emotion differentiation when listening to natural human voices but improved performance when acoustic variability was reduced through synthesized voices. Neural patterns differed between autistic and neurotypical children, suggesting different perceptual mechanisms. The findings align with Bayesian theories of autism, where oversensitivity to environmental variability impairs perception.

Visual task performance confirmed that autistic children struggle with high sensory variability. Results suggest that reducing acoustic complexity in emotional speech may enhance emotion recognition abilities in autism.

Acoustically modified speech with reduced variability shows promise for improving emotion recognition in autistic children. Findings support developing intervention tools that control acoustic complexity. Neural differences suggest need for individualized approaches to emotion recognition training.

Study limited to children aged 9.7 years average, unclear generalizability to other age groups. Specific sample characteristics beyond autism diagnosis not fully detailed. Laboratory-based findings may not translate directly to real-world settings.

Socio-emotional impairments are among the diagnostic criteria for autism spectrum disorder (ASD), but the actual knowledge has substantiated both altered and intact emotional prosodies recognition. Here, a Bayesian framework of perception is considered suggesting that the oversampling of sensory evidence would impair perception within highly variable environments. However, reliable hierarchical structures for spectral and temporal cues would foster emotion discrimination by autistics. Event-related spectral perturbations (ERSP) extracted from electroencephalographic (EEG) data indexed the perception of anger, disgust, fear, happiness, neutral, and sadness prosodies while listening to speech uttered by (a) human or (b) synthesized voices characterized by reduced volatility and variability of acoustic environments.

The assessment of mechanisms for perception was extended to the visual domain by analyzing the behavioral accuracy within a non-social task in which dynamics of precision weighting between bottom-up evidence and top-down inferences were emphasized. Eighty children (mean 9.7 years old; standard deviation 1.8) volunteered including 40 autistics. The symptomatology was assessed at the time of the study via the Autism Diagnostic Observation Schedule, Second Edition, and parents' responses on the Autism Spectrum Rating Scales. A mixed within-between analysis of variance was conducted to assess the effects of group (autism versus typical development), voice, emotions, and interaction between factors.

A Bayesian analysis was implemented to quantify the evidence in favor of the null hypothesis in case of non-significance. Post hoc comparisons were corrected for multiple testing. Autistic children presented impaired emotion differentiation while listening to speech uttered by human voices, which was improved when the acoustic volatility and variability of voices were reduced. Divergent neural patterns were observed from neurotypicals to autistics, emphasizing different mechanisms for perception.

Accordingly, behavioral measurements on the visual task were consistent with the over-precision ascribed to the environmental variability (sensory processing) that weakened performance. Unlike autistic children, neurotypicals could differentiate emotions induced by all voices. This study outlines behavioral and neurophysiological mechanisms that underpin responses to sensory variability. Neurobiological insights into the processing of emotional prosodies emphasized the potential of acoustically modified emotional prosodies to improve emotion differentiation by autistics.

BioMed Central ISRCTN Registry, ISRCTN18117434. Registered on September 20, 2020.