Document Type
Article
Publication Date
12-1-2023
Abstract
Closed-loop direct brain stimulation is a promising tool for modulating neural activity and behavior. However, it remains unclear how to optimally target stimulation to modulate brain activity in particular brain networks that underlie particular cognitive functions. Here, we test the hypothesis that stimulation's behavioral and physiological effects depend on the stimulation target's anatomical and functional network properties. We delivered closed-loop stimulation as 47 neurosurgical patients studied and recalled word lists. Multivariate classifiers, trained to predict momentary lapses in memory function, triggered the stimulation of the lateral temporal cortex (LTC) during the study phase of the task. We found that LTC stimulation specifically improved memory when delivered to targets near white matter pathways. Memory improvement was largest for targets near white matter that also showed high functional connectivity to the brain's memory network. These targets also reduced low-frequency activity in this network, an established marker of successful memory encoding. These data reveal how anatomical and functional networks mediate stimulation's behavioral and physiological effects, provide further evidence that closed-loop LTC stimulation can improve episodic memory, and suggest a method for optimizing neuromodulation through improved stimulation targeting.
Recommended Citation
Ezzyat, Youssef; Kragel, James E>; Solomon, Ethan A.; Lega, Bradley C.; Aronson, Joshua P.; Jobst, Barbara C.; Gross, Robert E.; Sperling, Michael R.; Worrell, Gregory A.; Sheth, Sameer A.; Wanda, Paul A.; Rizzuto, Daniel S.; and Kahana, Michael J., "Functional and Anatomical Connectivity Predict Brain Stimulation’s Mnemonic Effects" (2023). Department of Neurology Faculty Papers. Paper 345.
https://jdc.jefferson.edu/neurologyfp/345
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
PubMed ID
38041253
Language
English
Comments
This article is the author's final published version in Cerebral Cortex, Volume 34, Issue 11, January 2024, Article number bhad427.
The published version is available at https://doi.org/10.1093/cercor/bhad427. Copyright © The Author(s) 2023. Published by Oxford University Press.