Analysis of simultaneous visual and complex neural dynamics during cognitive learning to diagnose ASD

Area of Science:

• Neuroscience
• Cognitive Science
• Biomedical Engineering

Background:

• Cognition is mediated by the interaction between gaze processing and neural activities.
• Understanding visual and neural dynamics is crucial for characterizing cognitive behavior in Autism Spectrum Disorder (ASD).

Purpose of the Study:

• To identify the involvement of visual and neural dynamics in shaping cognitive behavior in ASD.
• To compare cognitive processing, gaze measures, and neural network dynamics between individuals with ASD and typically developing (TD) individuals.

Main Methods:

• Recorded Electroencephalogram (EEG) and eye-tracker signals from ASD and TD participants during a maze task.
• Analyzed performance metrics, Visibility Graph (VG) algorithm-derived neural measures, and eye-tracker data.
• Examined reaction time, accuracy, saccades, fixation duration, blink rate, and VG-based metrics (e.g., average weighted degree, global efficiency).

Main Results:

• Individuals with ASD exhibited higher reaction times, poorer accuracy, increased fixation duration, higher saccadic amplitude, and elevated blink rates.
• ASD participants showed reduced VG metrics like average weighted degree and global efficiency, alongside increased path length and eigenvector centrality.
• Despite poorer cognitive improvement, visual and neural network dynamics indicated Cognitive Learning (CL) activation in ASD.

Conclusions:

• Cognitive deficits in ASD stem from declined mutual interaction between brain regions, rather than impaired individual brain region functioning.
• Visual-neural dynamics are integral to understanding cognitive behavior and social cognition in ASD.
• Correlation of EEG-gaze measures with Autism Diagnostic Observation Schedule (ADOS) scores suggests a link to social behavior.