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Poster B95 in Poster Session B - Thursday, August 8, 2024, 1:30 – 3:30 pm, Johnson Ice Rink
A computational principle trades-off inference and adaptation dynamics
Oded Wertheimer1,2 (), Yuval Hart1; 1Edmond and Lily Safra Center for Brain Science, The Hebrew University of Jerusalem, 2Department of Psychology, The Hebrew University of Jerusalem
The dynamic range of a sensory system reflects the signal levels for which the system is responsive. We propose that dynamic range trades-off between inference (e.g. accuracy, encoding capacity) and dynamic features (e.g. adaptation and updating rates) of the neural computation. We take Autism Spectrum Disorder (ASD), which displays distinct neural and behavioral characteristics compared to the neurotypical (NT) population and show how known results, such as slower environmental adaptability, altered decision-making processes, and altered sensory encoding can be explained by the computational principle of increased dynamic range.
Keywords: Computational principle Trade-off neural encoding autism