# Individualized Closed Loop TMS for Working Memory Enhancement

> **NIH NIH R01** · UNIVERSITY OF PENNSYLVANIA · 2022 · $728,261

## Abstract

ABSTRACT
The proposed project is designed to increase precision and responsiveness in transcranial magnetic
stimulation therapies across the neuropsychiatric spectrum and specifically in working memory deficits which
are common across a variety of neuropsychiatric conditions. Cutting edge functional imaging studies suggest
that using multiple types of imaging datasets yield more reliable estimates of brain network communication.
Our methods yield a combined resting and task fMRI functional network mapping individualized for each
participant that will allow precise identification of brain stimulation targets associated with optimal working
memory performance (Aim 1). To close the loop in designing TMS protocols that respond to an individual
person's brain activation state, we will also develop and test a real-time brain decoder to determine when
optimal working memory states are online (Aim 2). By iteratively testing excitatory neuromodulation
frequencies at this stimulation site and capturing the relative movement of brain states towards or away from
optimal working memory states, we will settle on the optimal frequency for augmenting working memory
performance in each individual (Aim 3). We will validate this approach by administering either the `best' or
`worst' (random assignment to each participant) neuromodulation protocol across several days then testing
working memory performance and brain activation in a final MRI scan session. The multi-modal based TMS
targeting and individualized frequency optimization techniques will be based on our findings and packaged into
a combined software suite in Docker containers made available to the scientific and clinical community at the
conclusion of this project (Aim 4).

## Key facts

- **NIH application ID:** 10417107
- **Project number:** 5R01MH120811-04
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Yong Fan
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $728,261
- **Award type:** 5
- **Project period:** 2019-09-01 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10417107

## Citation

> US National Institutes of Health, RePORTER application 10417107, Individualized Closed Loop TMS for Working Memory Enhancement (5R01MH120811-04). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10417107. Licensed CC0.

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