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Connectomic Deep Brain Stimulation for Obsessive-Compulsive Disorder

Authors :
Philip E. Mosley
Daniel Huys
Barbara Hollunder
Ningfei Li
Suzanne N. Haber
Tim A. M. Bouwens van der Vlis
Albert F.G. Leentjens
Valerie Voon
Sameer A. Sheth
Juan Carlos Baldermann
Andreas Horn
Kara A. Johnson
Martijn Figee
Linda Ackermans
Sina Kohl
Michael T. Barbe
Thomas Schüller
Veerle Visser-Vandewalle
Christopher R. Butson
Jens Kuhn
Source :
Biological Psychiatry. 90:678-688
Publication Year :
2021
Publisher :
Elsevier BV, 2021.

Abstract

Obsessive-compulsive disorder is among the most disabling psychiatric disorders. Although deep brain stimulation is considered an effective treatment, its use in clinical practice is not fully established. This is, at least in part, due to ambiguity about the best suited target and insufficient knowledge about underlying mechanisms. Recent advances suggest that changes in broader brain networks are responsible for improvement of obsessions and compulsions, rather than local impact at the stimulation site. These findings were fueled by innovative methodological approaches using brain connectivity analyses in combination with neuromodulatory interventions. Such a connectomic approach for neuromodulation constitutes an integrative account that aims to characterize optimal target networks. In this critical review, we integrate findings from connectomic studies and deep brain stimulation interventions to characterize a neural network presumably effective in reducing obsessions and compulsions. To this end, we scrutinize methodologies and seemingly conflicting findings with the aim to merge observations to identify common and diverse pathways for treating obsessive-compulsive disorder. Ultimately, we propose a unified network that-when modulated by means of cortical or subcortical interventions-alleviates obsessive-compulsive symptoms. https://doi.org/10.1016/j.biopsych.2021.07.010

Details

ISSN :
00063223
Volume :
90
Database :
OpenAIRE
Journal :
Biological Psychiatry
Accession number :
edsair.doi.dedup.....aa6670535f2139a07fa37c8f18c99fcc