# Motor cortex network dynamics driving stroke recovery

> **NIH NIH K08** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2021 · $213,840

## Abstract

PROJECT SUMMARY
Ischemic stroke is the most common cause of disability in US, with motor impairment being the most common
form of disability. Rehabilitation therapies remain a mainstay treatment during recovery, but are not very effective
for those with moderate to severe upper extremity weakness. Physical and pharmacologic interventions could
become more effective if recovery mechanisms were better understood. The studies proposed here will use
cutting-edge techniques to dissect the mechanisms of post-stroke recovery at the level of cortical neuronal
networks. The principal investigator (PI) is a board-certified neurologist, and has extensive training in
neuroscience, stroke neurobiology, and clinical management of patients with neurological diseases. The long-
term goal is to understand relationships between the cortical neural network and the motor behaviors with a
focus on motor recovery. The proposed research and career development plans will provide the necessary
training, mentorship and experience to launch the PI’s career as a successful, R01-funded clinician-scientist.
The PI has recently developed deep learning (a branch of machine learning) tools for automated and unbiased
analysis of animal behavioral imaging data. Preliminary data demonstrate that, by using these automated tools,
3D kinematics of paw movements can be obtained during a food pellet reaching task in a head-fixed mouse,
distinct neural activity patterns emerge in the primary motor cortex (M1) during motor learning of the skilled
reaching, and stroke induces changes in the kinematics of the reaching behavior. In the proposed studies, the
following specific hypotheses will be tested: stable neuronal network activity patterns emerge in M1 during motor
learning (Aim-1); these M1 activity patterns destabilize after a stroke and sensorimotor disconnection (Aim-2);
and new M1 activity patterns emerge after post-stroke task-specific rehabilitation (Aim-3). The PI will use, and
be further trained on state-of-the-art techniques to record neural population activity (two-photon calcium
imaging), to label and silence projection neurons (retro-AAVs and designer-receptors exclusively activated by
designer drugs), and to analyze the kinematics of the behavior (deep learning tools). For this purpose, he has
assembled a strong mentorship team with experts in their respective fields: Primary mentor Dr. Peyman Golshani
(two-photon calcium imaging and analysis in behaving animals), as well as co-mentors, Dr. S. Thomas
Carmichael (stroke recovery research), Dr. Jonathan Kao (neural dynamics analysis in motor cortex), and
clinically, Dr. Bruce Dobkin (translational neurorehabilitation). The mentored research will be complemented with
course work on state-space methods, biostatistics, bioethics, deep learning, responsible conduct of research,
and grant writing; as well as improvement of professional skills by publishing manuscripts, presenting at
meetings, and participating in workshops on lead...

## Key facts

- **NIH application ID:** 10237248
- **Project number:** 5K08NS109315-04
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Ahmet ARAC
- **Activity code:** K08 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $213,840
- **Award type:** 5
- **Project period:** 2018-09-01 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10237248

## Citation

> US National Institutes of Health, RePORTER application 10237248, Motor cortex network dynamics driving stroke recovery (5K08NS109315-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10237248. Licensed CC0.

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