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Human anterior thalamic stimulation evoked cortical potentials align with intrinsic functional connectivity

Authors :
Di Wu
Frederic L.W.V.J. Schaper
Guangyuan Jin
Lei Qi
Jialin Du
Xiaopeng Wang
Yuke Wang
Cuiping Xu
Xueyuan Wang
Tao Yu
Michael D. Fox
Liankun Ren
Source :
NeuroImage, Vol 277, Iss , Pp 120243- (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

Characterizing human thalamocortical network is fundamental for understanding a vast array of human behaviors since the thalamus plays a central role in cortico-subcortical communication. Over the past few decades, advances in functional magnetic resonance imaging have allowed for spatial mapping of intrinsic resting-state functional connectivity (RSFC) between both cortical regions and in cortico-subcortical networks. Despite these advances, identifying the electrophysiological basis of human thalamocortical network architecture remains challenging. By leveraging stereoelectroencephalography electrodes temporarily implanted into distributed cortical regions and the anterior nucleus of the thalamus (ANT) of 10 patients with refractory focal epilepsy, we tested whether ANT stimulation evoked cortical potentials align with RSFC from the stimulation site, derived from a normative functional connectome (n = 1000). Our study identifies spatial convergence of ANT stimulation evoked cortical potentials and normative RSFC. Other than connections to the Papez circuit, the ANT was found to be closely connected to several distinct higher-order association cortices, including the precuneus, angular gyrus, dorsal lateral prefrontal cortex, and anterior insula. Remarkably, we found that the spatial distribution and magnitude of cortical-evoked responses to single-pulse electrical stimulation of the ANT aligned with the spatial pattern and strength of normative RSFC of the stimulation site. The present study provides electrophysiological evidence that stimulation evoked electrical activity flows along intrinsic brain networks connected on a thalamocortical level.

Details

Language :
English
ISSN :
10959572 and 87374439
Volume :
277
Issue :
120243-
Database :
Directory of Open Access Journals
Journal :
NeuroImage
Publication Type :
Academic Journal
Accession number :
edsdoj.3d87374439564512a23ee5e3fc11adc6
Document Type :
article
Full Text :
https://doi.org/10.1016/j.neuroimage.2023.120243