# The Role of Autonomic Regulation of Attention in the Emergence of ASD

> **NIH NIH R01** · UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA · 2024 · $735,147

## Abstract

PROJECT SUMMARY
Disrupted attention is among the earliest-emerging, lifelong features of autism spectrum disorder (ASD) and
research suggests a critical point in the neonatal and early infant period at which disrupted attention may be
detectable. The timing of this disruption aligns with key maturational shifts in neurodevelopment, but the
neurobiological mechanisms associated with disrupted attention in ASD remain elusive. One neurobiological
system that regulates attention from early infancy is the autonomic nervous system (ANS). Broad ANS
dysfunction is observed in older children already diagnosed with ASD, but whether and when ANS dysfunction
contributes to attention abnormalities in ASD remains unknown. The overall goal of this study is to examine
how atypical autonomic regulation of attention may be associated with the emergence of ASD symptoms. A
key marker of autonomic regulation of attention is heart defined attention. Accordingly, maturation of heart
defined attention in the early infant period and the developmental consequences therein for the emergence of
interactive behaviors and ASD symptoms will be examined. A critical innovation of this study is leveraging a
three-group design in which infants who experience elevated ASD symptoms (infant siblings of children with
ASD; ASIBs) will be compared to typically developing (TD) and preterm (PT) control groups. Infants born
preterm experience broad ANS dysfunction from birth and comparing ASIBs to PTs will help delineate how
attention-specific ANS dysfunction predicts the emergence of ASD-specific symptoms. Aim 1 will compare the
emergence of autonomic regulation of attention during a very critical period of neurodevelopment (1-3 months)
across ASIBs, PT infants, and TD infants. Aim 2 will quantify the association between heart defined attention
and interactive behavior on a moment-to-moment basis at 6, 9, and 12 months, and compare across the three
groups. Aim 3 will utilize machine learning techniques to predict ASD symptoms at age 3 years from early
autonomic and attentional features (from Aims 1-2). Determining the specificity of autonomic regulation of
attention as a key, early emerging feature associated with ASD, has significant translational potential for a
cost-effective biomarker. This work will inform developmental models of ASD wherein disrupted autonomic
regulation of attention has proximal effects on real-world interactions that may interfere with learning and have
cascading effects on long-term outcomes.

## Key facts

- **NIH application ID:** 10877908
- **Project number:** 5R01MH132925-02
- **Recipient organization:** UNIVERSITY OF SOUTH CAROLINA AT COLUMBIA
- **Principal Investigator:** Jessica Bradshaw
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $735,147
- **Award type:** 5
- **Project period:** 2023-07-01 → 2028-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10877908

## Citation

> US National Institutes of Health, RePORTER application 10877908, The Role of Autonomic Regulation of Attention in the Emergence of ASD (5R01MH132925-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10877908. Licensed CC0.

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