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Lookup NU author(s): Professor Tim GriffithsORCiD, Professor Christopher Petkov
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Background: Understanding brain function requires knowledge of how one brain region causally influences another. This information is difficult to obtain directly in the human brain, and is instead typically inferred from resting-state fMRI.New method: Here, we demonstrate the safety and scientific promise of a novel and complementary approach: concurrent electrical stimulation and fMRI (es-fMRI) at 3 T in awake neurosurgical patients with implanted depth electrodes.Results: We document the results of safety testing, actual experimental setup, and stimulation parameters, that safely and reliably evoke activation in distal structures through stimulation of amygdala, cingulate, or prefrontal cortex. We compare connectivity inferred from the evoked patterns of activation with that estimated from standard resting-state fMRI in the same patients: while connectivity patterns obtained with each approach are correlated, each method produces unique results. Response patterns were stable over the course of 11 min of es-fMRI runs. Comparison with existing method: es-fMRI in awake humans yields unique information about effective connectivity, complementing resting-state fMRI. Although our stimulations were below the level of inducing any apparent behavioral or perceptual effects, a next step would be to use es-fMRI to modulate task performances. This would reveal the acute network-level changes induced by the stimulation that mediate the behavioral and cognitive effects seen with brain stimulation.Conclusions: es-fMRI provides a novel and safe approach for mapping effective connectivity in the human brain in a clinical setting, and will inform treatments for psychiatric and neurodegenerative disorders that use deep brain stimulation. (C) 2016 Elsevier B.V. All rights reserved.
Author(s): Oya H, Howard MA, Magnotta VA, Kruger A, Griffiths TD, Lemieux L, Carmichael DW, Petkov CI, Kawasaki H, Kovach CK, Sutterer MJ, Adolphs R
Publication type: Article
Publication status: Published
Journal: Journal of Neuroscience Methods
Year: 2017
Volume: 277
Pages: 101-112
Print publication date: 01/02/2017
Online publication date: 21/12/2016
Acceptance date: 20/12/2016
ISSN (print): 0165-0270
ISSN (electronic): 1872-678X
Publisher: Elsevier BV
URL: https://doi.org/10.1016/j.jneumeth.2016.12.014
DOI: 10.1016/j.jneumeth.2016.12.014
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