1. High-resolution virtual brain modeling personalizes deep brain stimulation for treatment-resistant depression: Spatiotemporal response characteristics following stimulation of neural fiber pathways.
- Author
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An S, Fousek J, Kiss ZHT, Cortese F, van der Wijk G, McAusland LB, Ramasubbu R, Jirsa VK, and Protzner AB
- Subjects
- Electroencephalography, Gyrus Cinguli physiopathology, Humans, Implantable Neurostimulators, Neural Pathways physiology, Precision Medicine, Spatio-Temporal Analysis, Cerebral Cortex physiopathology, Deep Brain Stimulation, Depressive Disorder, Treatment-Resistant physiopathology, Depressive Disorder, Treatment-Resistant therapy, Evoked Potentials physiology, Nerve Net physiopathology
- Abstract
Over the past 15 years, deep brain stimulation (DBS) has been actively investigated as a groundbreaking therapy for patients with treatment-resistant depression (TRD); nevertheless, outcomes have varied from patient to patient, with an average response rate of ∼50%. The engagement of specific fiber tracts at the stimulation site has been hypothesized to be an important factor in determining outcomes, however, the resulting individual network effects at the whole-brain scale remain largely unknown. Here we provide a computational framework that can explore each individual's brain response characteristics elicited by selective stimulation of fiber tracts. We use a novel personalized in-silico approach, the Virtual Big Brain, which makes use of high-resolution virtual brain models at a mm-scale and explicitly reconstructs more than 100,000 fiber tracts for each individual. Each fiber tract is active and can be selectively stimulated. Simulation results demonstrate distinct stimulus-induced event-related potentials as a function of stimulation location, parametrized by the contact positions of the electrodes implanted in each patient, even though validation against empirical patient data reveals some limitations (i.e., the need for individual parameter adjustment, and differential accuracy across stimulation locations). This study provides evidence for the capacity of personalized high-resolution virtual brain models to investigate individual network effects in DBS for patients with TRD and opens up novel avenues in the personalized optimization of brain stimulation., Competing Interests: Declaration of Competing Interest The authors declare no competing interest., (Copyright © 2021. Published by Elsevier Inc.)
- Published
- 2022
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