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A Multimodal Framework for Understanding Perceptual Segmentation of Natural Scenes In Autism

Williams, D. K. A.; Biswas, T. K.; Brusco, C.; Molholm, S.; Coen-Cagli, R.

2025-12-18 neuroscience
10.64898/2025.12.17.695033 bioRxiv
Show abstract

Understanding how individuals segment complex natural scenes into perceptual segments is essential for explaining both typical and atypical sensory processing. In Autism Spectrum Disorder (ASD), differences in visual segmentation and integration are widely documented. However, existing paradigms often rely on simplified stimuli and do not capture the dynamic, naturalistic processes underlying real world scene segmentation. To overcome those limitations, in this work we present a novel, multimodal experimental framework. The framework combines precisely timed, trial-based perceptual measurements with electroencephalography (EEG) to examine how neural activity aligns temporally with segmentation decisions and with eye-tracking to examine visual exploration strategies and attention allocation. Neurotypical (NT) participants and participants with ASD aged 16 years and above viewed natural scenes and textures and indicated whether two cued image regions belonged to the same or different perceptual segments. Responses to multiple pairs of cues enabled the estimation of subjectively perceived segmentation maps and the associated uncertainty. Across NT and ASD populations, we analyzed segmentation maps, reaction time distributions, gaze profiles, and trial-aligned neural responses. Behavioral results revealed slower and more idiosyncratic segmentation patterns in ASD. Eye-tracking analyses also demonstrated distinct gaze patterns suggesting broader exploration of the images during early viewing. EEG analyses demonstrated delayed and more diffuse occipital activation in ASD, accompanied by reduced global field power at several key time windows spanning stimulus presentation. Together, these findings establish a reproducible method for studying the temporal and spatial components of natural scene segmentation and indicate meaningful behavioral and neural distinctions in ASD. This framework provides a methodological bridge between controlled experimental stimuli and real-world perception in both neurotypical and neurodivergent populations.

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