# Human Cerebellar Function in Multiple Task Domains

> **NIH NIH R35** · UNIVERSITY OF CALIFORNIA BERKELEY · 2023 · $85,552

## Abstract

Abstract
While it is well-known that healthy aging has deleterious effects on sensorimotor control, the impact of aging on
sensorimotor adaptation remains controversial. We attribute the ambiguous picture that emerges from prior studies to two
methodological issues. First, conventional motor adaptation tasks conflate multiple learning processes and may mask the
effect of aging on component processes such as implicit recalibration or explicit re-aiming. Second, the use of limited sample
sizes and tendency to treat age as a binary variable (“young” vs “old”) have made it difficult to precisely determine the
impact of aging across the lifespan. The goal of this R35 research supplement addresses these issues by using novel
analytical tasks that isolate implicit recalibration (Aim 1) and explicit re-aiming (Aim 2) to better understand how aging
affects each learning process. To obtain a detailed characterization of how these processes evolve throughout adulthood, a
large sample will be recruited using a novel web-based crowd-sourcing approach, allowing us to treat age as a continuous
variable (Aim 1 & 2). Building on computational models that specify component operations underlying recalibration and
re-aiming, we will investigate how aging mechanistically affects each process. In addition, we will compare natural and
pathological aging by testing individuals with cerebellar degeneration in parallel experiments. In summary, this supplement
will not only contribute to the parent R35 by deepening our mechanistic understanding of how natural and pathological
aging of the cerebellum impact sensorimotor learning but also provide valuable open-source normative data that may inform
interventions designed to improve clinical outcomes for individuals with cerebellar pathology and offset the deleterious
effects of aging on motor control.

## Key facts

- **NIH application ID:** 10842004
- **Project number:** 3R35NS116883-04S1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA BERKELEY
- **Principal Investigator:** RICHARD IVRY
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $85,552
- **Award type:** 3
- **Project period:** 2020-05-01 → 2028-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10842004

## Citation

> US National Institutes of Health, RePORTER application 10842004, Human Cerebellar Function in Multiple Task Domains (3R35NS116883-04S1). Retrieved via AI Analytics 2026-06-11 from https://api.ai-analytics.org/grant/nih/10842004. Licensed CC0.

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