Memory Enhancement in Aging With Closed-Loop tACS

Aging, Memory, Noninvasive Brain Stimulation

This project optimizes high-resolution tACS to improve memory in healthy older adults, advancing drug-free approaches for ADRD. We test stimulation schedules and develop an adaptive, brain-guided tACS system to strengthen memory-supporting networks.

Cognitive decline, especially in memory and executive control, poses an escalating public health challenge as the population ages, contributing to loss of independence, reduced quality of life, and increased healthcare costs associated with Alzheimer's disease and related dementias (ADRD). Despite decades of research, there are few effective, non-pharmacological interventions capable of slowing or reversing these cognitive losses. Transcranial alternating current stimulation (tACS) has recently emerged as a promising, safe, and non-invasive technique for modulating neural rhythms that support memory. However, existing approaches remain limited by one-size-fits-all stimulation schedules that fail to account for individual brain connectivity patterns or dynamic fluctuations in cognitive state. This project aims to advance precision neuromodulation for cognitive aging by optimizing and personalizing high-resolution tACS protocols to enhance memory in older adults. Building on strong pilot data demonstrating the feasibility of personalized and adaptive stimulation, we will use multimodal imaging (EEG and fMRI) to track changes in frontotemporal synchrony, specifically theta-gamma phase-amplitude coupling and theta phase synchronization, that are known to support memory formation and retrieval. Aim 2 will develop and test a connectivity-guided closed-loop tACS system that continuously monitors neural synchronization in the frontotemporal network and adjusts stimulation parameters in real time. This adaptive framework is designed to tailor stimulation to each participant's evolving brain state, enabling more efficient and individualized cognitive enhancement than static approaches. By integrating behavioral, electrophysiological, and neuroimaging measures with adaptive control algorithms, this research will identify reliable biomarkers of responsiveness, elucidate causal mechanisms linking neural synchrony to memory, and yield a new class of personalized, connectivity-guided interventions for cognitive decline. The findings will lay a foundation for scalable, non-invasive, and mechanism-driven treatments for ADRD and age-related memory loss, advancing the broader NIH mission of promoting healthy cognitive aging.

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