# Testing a computational model of neural responses in autism

> **NIH NIH R01** · UNIVERSITY OF WASHINGTON · 2020 · $681,490

## Abstract

PROJECT SUMMARY/ABSTRACT
This proposal will test a novel, computationally-motivated hypothesis about neural dysfunction in autism
spectrum disorder (ASD). ASD is a heterogeneous neurodevelopmental disorder of unknown etiology.
However, a unifying theme of numerous proposals is that there is a pervasive disruption of neural
excitatory/inhibitory (E/I) balance. A major limitation of the E/I hypothesis is that it describes a property of
individual neurons; how that property scales up to neural circuits and how it relates to behavior – the level at
which ASD is described – is not well specified. Neural computational models offer a way to bridge the divide
between single-unit properties and behavior, and bring the necessary specificity to test possible changes in E/I
in ASD. One well-established neural computation that directly relates to E/I is “divisive normalization”, a
computational framework that characterizes neural responses as the ratio of net excitatory relative to net
suppressive input. Here we aim to test the hypothesis that ASD involves disrupted divisive normalization using
vision as a model system. We will test two possible mechanisms of weakened divisive normalization. The first
is the traditionally posited disruption of local, within-area circuits that mediate suppressive drive. The second is
a novel hypothesis based on recent empirical findings in our lab. We have shown enhanced suppressive
feedback of responses from higher stages to lower stages of visual processing in individuals with ASD. We
suggest this enhanced suppressive feedback reduces responses of neurons that would otherwise participate in
divisive normalization. This hypothesis makes specific predictions about the conditions under which disrupted
divisive normalization will be observed in ASD. We will test these predictions using a combination of functional
MRI, ERP, and diffusion MRI.

## Key facts

- **NIH application ID:** 9982436
- **Project number:** 5R01MH118847-02
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** SCOTT O MURRAY
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $681,490
- **Award type:** 5
- **Project period:** 2019-08-01 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9982436

## Citation

> US National Institutes of Health, RePORTER application 9982436, Testing a computational model of neural responses in autism (5R01MH118847-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/9982436. Licensed CC0.

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