# Impact of Multisensory Function on Symptomatology in Young Children with ASD

> **NIH NIH K01** · SAN DIEGO STATE UNIVERSITY · 2021 · $195,916

## Abstract

Project Summary/Abstract
Atypical responses to sensory stimuli are highly prevalent in autism spectrum disorders (ASD). Somatosensory
sensitivities in particular occur prominently and with high frequency in the disorder. While core symptomatology is
comprised of both sensory dysfunctions and sociocommunicative deficits, the impact of aberrant somatosensory and
multisensory processing on sociocommunication abilities remains unknown. It is not well-understood how sensory
discrimination anomalies predict later sociocommunicative impairment, or which manifestations of sensory abnormalities
result in more severe outcomes. Thus, the objective of this proposal is to investigate the behavioral and neural patterns
underlying somatosensory and multisensory discrimination abnormalities longitudinally in young children with ASD
compared to TD peers at 4-5 years and 6-7 years of age and identify potential patterns of developmental causality between
sensory and sociocommunicative impairments. We theorize that behavioral dysfunction and disruptions in functional and
structural connectivity between neural systems in ASD interfere with normative development. Within this theoretical
framework, we make three key predictions regarding sensory processing in ASD: (1) Behavioral manifestations of
sensory discrimination anomalies in ASD will be objectively observable and quantifiable; (2) functional and structural
connectivity patterns within and between sensory and multisensory networks will be atypical; and (3) these atypical
network connections will be linked to behavioral manifestations of sensory abnormalities, and combined will predict later
sociocommunicative impairments. To examine these hypotheses, we propose a longitudinal and multimodal approach,
including behavioral measures, task-based functional magnetic resonance imaging (fMRI), resting state functional
connectivity MRI (fcMRI), diffusion weighted imaging (DWI), and neuropsychological indices, along with machine-
learning methods, which will be able to reveal distinct patterns within and across modalities, and pinpoint patterns that
may most heavily impact autism symptomatology in young children. The distinct strengths of this proposal lie in the
application of quantitative behavioral measures to examine sensory discrimination thresholds in young developmental
populations, in combination with the use of advanced neuroimaging tools to measure functional activity and (functional
and structural) network connectivity between multiple brain systems and the implementation of machine-learning
predictive approaches.
 The proposed training plan incorporates analytic approaches to multimodal neuroimaging and machine-learning,
as well as training in neuropsychological evaluation and assessment, which are essential to the applicant's research goals
of investigating sensory abnormalities in, and atypical development of, the brain and behavior. This career development
award will permit her to develop new expertise nece...

## Key facts

- **NIH application ID:** 10205977
- **Project number:** 5K01MH113819-04
- **Recipient organization:** SAN DIEGO STATE UNIVERSITY
- **Principal Investigator:** R. Joanne Jao Keehn
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $195,916
- **Award type:** 5
- **Project period:** 2018-06-01 → 2023-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10205977

## Citation

> US National Institutes of Health, RePORTER application 10205977, Impact of Multisensory Function on Symptomatology in Young Children with ASD (5K01MH113819-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10205977. Licensed CC0.

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