# Environmental Contributions to Disparities in Learning Disabilities: The Columbia Psychiatry, Psychology, and Public Health Collaborative Learning Disabilities Innovation Hub

> **NIH NIH P20** · NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC · 2022 · $610,551

## Abstract

The Columbia Psychiatry, Psychology, and Public Health Collaborative Learning Disabilities (LD)
Innovation Hub brings together experts from distinct fields–-LD and neuropsychology, child psychiatry,
cognitive neuroscience, public health and environmental science–-to improve our etiologic understanding of
environmentally-associated learning difficulties (LDiff), defined both dimensionally and categorically by
performance in the lowest quartile on standardized measures of reading and math. Our study includes Black
and Latinx children from economically disadvantaged families—populations at high risk for prenatal exposure
to neurotoxic chemicals and learning problems, who have historically been excluded from research. The Hub
will establish infrastructure to (a) foster innovative research into the complex etiology and neural underpinnings
of environmentally-associated LDiff in the context of economic adversity, and (b) train future interdisciplinary
LD scholars and leaders in cutting-edge neuroscience and to engage with the wider child educational
system. The Hub will document how prenatal environmental chemical exposures contribute to the achievement
gap in the United States. Long term, the Hub will help close the achievement gap by identifying behavioral and
neural pathways from prenatal exposures to LDiff—pathways that may be amenable to change.
The Embedded Research Project will identify neural and cognitive pathways through which prenatal exposure
to air pollution and early life stress (ELS) lead to LDiff in a sample of Black and Latinx children and
adolescents. We will use novel magnetic resonance imaging (MRI) of neuromelanin, a by-product of midbrain
dopamine, and model-based functional MRI to probe dopaminergic circuits and related inhibitory control (IC)
and reinforcement learning (RL) in relation to prenatal exposure. We hypothesize that midbrain dopamine
serves as a critical mechanism mediating air pollution and ELS effects on domain-general cognitive factors (IC
and RL) and LDiff. The Leadership Core will establish the Hub's administrative and training infrastructure and
foster the next generation of interdisciplinary LD researchers, trained in public health and LDiff through an
innovative program including neuroscience research experience, methodological and translational coursework,
mentoring and interdisciplinary practicum training in the educational setting. We continue our commitment to
the recruitment of early career scientists from underrepresented groups, preparing them for research and
leadership positions in LD. IMPACT: Through our innovative, high-risk project and integrated
training/mentorship opportunities we will identify novel circuits and potentially modifiable
environmental risk factors implicated in LDiff in children from economically disadvantaged families.
We will develop an intellectual and administrative infrastructure to serve as a foundation for a future
Center for Environmental LD Research, capable of translating...

## Key facts

- **NIH application ID:** 10533147
- **Project number:** 1P20HD109965-01
- **Recipient organization:** NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC
- **Principal Investigator:** AMY MARGOLIS
- **Activity code:** P20 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $610,551
- **Award type:** 1
- **Project period:** 2022-09-01 → 2026-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10533147

## Citation

> US National Institutes of Health, RePORTER application 10533147, Environmental Contributions to Disparities in Learning Disabilities: The Columbia Psychiatry, Psychology, and Public Health Collaborative Learning Disabilities Innovation Hub (1P20HD109965-01). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10533147. Licensed CC0.

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