# Using Direct Brain Stimulation to Study Cognitive Electrophysiology

> **NIH NIH U01** · UNIVERSITY OF PENNSYLVANIA · 2022 · $1,347,596

## Abstract

Project Abstract
 Our project aims to form a multi-site consortium that will carry out fundamental exper-
iments to elucidate the mesoscopic and microscopic neural dynamics underlying human
memory and use direct brain stimulation as a manipulative tool to study those dynamics.
Additionally, we seek to create a dynamical timeseries model that predicts the evolution
of brain activity during cognitive tasks and incorporates the e ects of stimulation-induced
perturbations on the system. We will collect recording and stimulation data from 250 pa-
tient volunteers as they perform carefully-matched verbal and spatial memory tasks. Dur-
ing non-stimulation sessions, we will measure correlative neural biomarkers of memory
encoding and retrieval using standard clinical depth electrodes and microwire recordings.
To test the causal role of these biomarkers, we will employ direct brain stimulation to
disrupt or upregulate neural activity, and measure ensuing changes in behavioral perfor-
mance. With a set of causal biomarkers and predictive models in hand, we will finally
ask whether model-driven stimulation paradigms o er us the ability to reliably modulate
neural activity, and consequent behavior, in real-time.

## Key facts

- **NIH application ID:** 10475807
- **Project number:** 5U01NS113198-04
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Michael Jacob Kahana
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $1,347,596
- **Award type:** 5
- **Project period:** 2019-09-15 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10475807

## Citation

> US National Institutes of Health, RePORTER application 10475807, Using Direct Brain Stimulation to Study Cognitive Electrophysiology (5U01NS113198-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10475807. Licensed CC0.

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