Back

Atypical Audio-Visual Neural Synchrony and Speech Processing in children with Autism Spectrum Disorder

Wang, X.; Bouton, S.; Kojovic, N.; Giraud, A.-L.; Schaer, M.

2024-04-19 neuroscience
10.1101/2024.04.19.590044 bioRxiv
Show abstract

BackgroundChildren with Autism Spectrum Disorders (ASD) often exhibit communication difficulties that may stem from basic auditory temporal integration impairment but also be aggravated by an audio-visual integration deficit, resulting in a lack of interest in face-to-face communication. This study addresses whether speech processing anomalies in young (mean age 3.09-year-old) children with ASD are associated with alterations of audio-visual temporal integration. MethodsWe used high-density electroencephalography (HD-EEG) and eye tracking to record brain activity and gaze patterns in 31 children (6 females) with ASD and 33 typically developing (TD) children (11 females), while they watched cartoon videos. Neural responses to temporal audio-visual stimuli were analyzed using Temporal Response Functions model and phase analyses for audiovisual temporal coordination. ResultsThe reconstructability of speech signals from auditory responses was reduced in children with ASD compared to controls, but despite more restricted gaze patterns in ASD it was similar for visual responses in both groups. Speech reception was most strongly affected when visual speech information was also present, an interference that was not seen in TD children. These differences were associated with a broader phase angle distribution (exceeding pi/2) in the EEG theta range in autistic children, signaling reduced reliability of audio-visual temporal alignment. ConclusionThese findings show that speech processing anomalies in ASD do not stand alone and that they are associated already at a very early development stage with audio-visual imbalance with lousier auditory response encoding and disrupted audio-visual temporal coordination.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.