# Atypical Development in Infants and Toddlers: Computational Attentional Signatures through Mobile Eye Tracking

> **NIH NIH R01** · SEATTLE CHILDREN'S HOSPITAL · 2024 · $887,117

## Abstract

PROJECT SUMMARY/ABSTRACT
This heterogeneity of autism spectrum disorder (ASD) results in challenges to developing diagnostic,
prognostic, and treatment strategies applicable across the autism spectrum. A search has been underway for
decades to identify promising biomarkers, i.e. objectively measured indicators of typical or atypical biology or
response to therapy, for ASD. While progress is promising, one major limitation to this search is the bottleneck
of laboratory resources to conduct studies at sufficient scale to sustain the iterative development, evaluation,
and refinement needed to bring biomarkers to practical fruition. For studies of neurodevelopmental disorders,
the barriers are particularly challenging, as heterogeneity of behavioral presentation interacts with extensive
developmental variability leading to a need for massive resources just to establish baselines across protracted
periods of early childhood. One promising biomarker technology that has been noted as being potentially
highly scalable is eye tracking. Eye tracking offers a non-invasive, easily tolerated method for directly
characterizing child attentional processes. These attentional processes, in turn, are a moment-by-moment
account of visual information gathering strategies that are driven by more fundamental reflex and cognition.
Unfortunately, research-grade eye tracking is out of reach for the average end user: technically, operationally,
and financially. However, astonishing advances in computer vision have now made it possible to consider
bringing eye tracking not just into laboratories at low costs, but into clinics, communities, and homes.
 This study creates infrastructure for large-scale computer-vision-based eye-tracking data collection from
mobile tablet devices. Building upon existing, already-proven, mobile data collection methods designed, tested,
and deployed by the study team, this project seeks to develop a general-purpose research tool that is also
end-user-focused, with broad appeal, usability, and streamlined utility. The platform launches with a battery of
eye-tracking measures optimized for mobile device deployment and designed to probe mechanistic constructs
associated with non-social information preferences in toddlers with ASD. This battery will be tested in the lab in
2-year-old toddlers with and without ASD, with both mobile- and laboratory-based eye tracking designed to
validate the mobile adaptation and provide routes for subsequent optimization. A parallel remote-only sample
will also participate. Both in-lab and remote-only samples will be evaluated again at 36-months-old to confirm
developmental outcomes. A large community sample will be recruited to fill in the battery’s developmental
profile from 3-to-36-months of age. This study thus builds, validates, and improves upon novel remote eye-
tracking data collection infrastructure, but will also apply this technology to fill in mechanistic gaps in our
knowledge regarding atypical attentio...

## Key facts

- **NIH application ID:** 10825845
- **Project number:** 1R01MH135568-01
- **Recipient organization:** SEATTLE CHILDREN'S HOSPITAL
- **Principal Investigator:** FREDERICK SHIC
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $887,117
- **Award type:** 1
- **Project period:** 2023-12-07 → 2028-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10825845

## Citation

> US National Institutes of Health, RePORTER application 10825845, Atypical Development in Infants and Toddlers: Computational Attentional Signatures through Mobile Eye Tracking (1R01MH135568-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10825845. Licensed CC0.

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