Autism spectrum disorder variation as a computational trade-off via dynamic range of neuronal population responses

Oded Wertheimer, Yuval Hart*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Individuals diagnosed with autism spectrum disorder (ASD) show neural and behavioral characteristics differing from the neurotypical population. This may stem from a computational principle that relates inference and computational dynamics to the dynamic range of neuronal population responses, reflecting the signal levels for which the system is responsive. In the present study, we showed that an increased dynamic range (IDR), indicating a gradual response of a neuronal population to changes in input, accounts for neural and behavioral variations in individuals diagnosed with ASD across diverse tasks. We validated the model with data from finger-tapping synchronization, orientation reproduction and global motion coherence tasks. We suggested that increased heterogeneity in the half-activation point of individual neurons may be the biological mechanism underlying the IDR in ASD. Taken together, this model provides a proof of concept for a new computational principle that may account for ASD and generates new testable and distinct predictions regarding its behavioral, neural and biological foundations.

Original languageEnglish
Article number5439
Pages (from-to)2476-2486
Number of pages11
JournalNature Neuroscience
Volume27
Issue number12
DOIs
StatePublished - Dec 2024

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© The Author(s) 2024.

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