# Emergence of task-specific neuronal ensembles in human motor and premotor cortex with learning using a brain-computer interface

> **NIH NIH F31** · BROWN UNIVERSITY · 2021 · $24,506

## Abstract

PROJECT SUMMARY
 Stroke frequently causes significant long-term motor impairment, and minimizing this impairment is a
major focus of stroke rehabilitation. Research in animal models and non-invasive imaging studies in humans
suggest that decreases in variability within motor cortex are associated with improvements in skill performance.
However, the changes at the level of single neurons that underly human motor learning beyond motor cortex
are not well understood. A better understanding of the neurophysiologic basis of motor skill acquisition may
inform improved neurorehabilitation strategies.
 Intracortical brain-computer interfaces (iBCIs) can record activity at the level of single neurons, and
offer a unique opportunity to study the neural correlates of movement in humans. In this study, I propose to use
an iBCI framework to track the evolution of task-relevant ensembles of neurons in motor cortex, and determine
the relationship between motor and premotor cortex during learning. To do this, participants in an ongoing pilot
clinical trial will learn to modulate the firing rate of one (target) neuron in order to control the movement of a
cursor on a screen.
 In Aim 1, I will quantify changes within human motor cortex at the level of single neurons as a person
learns a novel motor task. In Aim 2, I will assess changes between motor and premotor cortex with learning.
This will provide the first human-specific information on motor learning at the neuronal level, and will clarify
how the network evolves over the course of learning. In Aim 3, I will change the target neuron and assess how
the network reorganizes to accommodate a new skill. This will allow me to probe how well the pattern of skill
learning is conserved, and may be particularly informative for stroke treatment as stroke recovery involves
network reorganization and relearning.
 This research will develop a framework for studying motor learning in humans at the level of single
neurons. Results from this study will provide novel information about how neural activity changes with motor
skill learning across brain regions, and may provide insight for the rational development of stroke treatments.
 This fellowship will also support the technical and academic training and professional development of
the applicant, including advanced training in neuroengineering; general neuroscience training; formal and
informal training in written and oral scientific communication, including writing manuscripts and attendance at
conferences; teaching and mentoring training; and job market preparation. This research will be conducted in
the highly inter-disciplinary and supportive research environment at Brown University, and in collaboration with
Massachusetts General Hospital and the Providence Veterans’ Affairs Medical Center.

## Key facts

- **NIH application ID:** 10086002
- **Project number:** 5F31NS115379-02
- **Recipient organization:** BROWN UNIVERSITY
- **Principal Investigator:** Kaitlin Wilcoxen
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $24,506
- **Award type:** 5
- **Project period:** 2020-02-01 → 2021-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10086002

## Citation

> US National Institutes of Health, RePORTER application 10086002, Emergence of task-specific neuronal ensembles in human motor and premotor cortex with learning using a brain-computer interface (5F31NS115379-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10086002. Licensed CC0.

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