# Cerebellar connectivity and error-based learning in infants at risk for autism

> **NIH NIH F31** · WASHINGTON UNIVERSITY · 2020 · $36,300

## Abstract

Project Summary
Autism Spectrum Disorder (ASD) is a heterogeneous disorder diagnosed on the basis of social impairment and
restricted, repetitive behaviors 7. To combat these behavioral liabilities, effective interventions are needed.
Early interventions appear particularly promising given evidence that engaging in therapies by 18-24 months
improves outcomes for individuals with ASD 8–11. However, prospective research in infants at high risk for ASD
has shown that the defining behavioral features of ASD are not present during the first year of life 12. Thus,
very early intervention will rely on the identification of reliable presymptomatic biomarkers. In service of this
objective, we propose to interrogate cerebellar functional connectivity and error-based learning (EBL)
impairment as developmentally-linked neural and physiological presymptomatic biomarkers, respectively, of
ASD. Converging evidence from multiple areas of research indicates a role for the cerebellum in ASD 13–15, a
role for the cerebellum in EBL 16–18, and a role for EBL in ASD 19,20. However, the directionality and timing of
early developmental relationships among these constructs remains poorly understood. This is a notable gap in
the literature, given that ASD is a neurodevelopmental disorder with defining behavioral features that emerge
and consolidate across the first 12 and 36 months of life 21. To test the hypothesis that cerebellar connectivity
and EBL contribute to the development of ASD, it is necessary to study infants prior to ASD diagnosis. To this
end, we propose to analyze previously-collected resting-state functional connectivity (fcMRI) and eye-tracking
(EBL) data from the Infant Brain Imaging Study (IBIS), a multisite study of brain and behavioral development in
infants at high and low risk for ASD. Specifically, we will evaluate cerebellar connectivity and EBL impairment
as longitudinal predictors of ASD diagnosis and severity, as well as dimensionally-measured ASD-associated
behaviors. Consistent with prior research 22, we will operationalize EBL as saccadic error (i.e., the frequency,
magnitude, and variability of eye movements that fall short of their intended targets). We hypothesize that
infant cerebellar connectivity (Aim 1) and EBL impairment (Aim 2) will predict later ASD diagnosis and severity.
Further, consistent with “cascade” models of brain-behavior development 23, we hypothesize that infant
cerebellar connectivity will influence infant EBL, with implications for ASD outcomes (Aim 3). Findings to
support our hypotheses would identify cerebellar functional connectivity and EBL impairment as
presymptomatic biomarkers for ASD, facilitating early diagnosis in ASD and helping to pave the way for
randomized control trials of presymptomatic interventions. Ultimately, my long-term career goal is to become
an independent academic researcher investigating the neural, physiological, and psychological factors that
contribute to the development of ASD. This pro...

## Key facts

- **NIH application ID:** 9987929
- **Project number:** 1F31MH120918-01A1
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Zoe Hawks
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $36,300
- **Award type:** 1
- **Project period:** 2020-07-01 → 2021-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9987929

## Citation

> US National Institutes of Health, RePORTER application 9987929, Cerebellar connectivity and error-based learning in infants at risk for autism (1F31MH120918-01A1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9987929. Licensed CC0.

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