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Tractography Analysis for Electroconvulsive Therapy

Authors: Stefanie Riel; Mohammad Bashiri; Werner Hemmert; Siwei Bai;

Tractography Analysis for Electroconvulsive Therapy

Abstract

Computational human head models have been used in electrophysiological studies, and they have been able to provide useful information that is unable or difficult to acquire from experimental or imaging studies. However, most of these models are purely volume conductor models that overlooked the electric excitability of axons in the white matter of the brain. This study combined a finite element (FE) model of electroconvulsive therapy (ECT) with a whole-brain tractography analysis as well as the cable theory of neuronal excitation. We have reconstructed a whole-brain tractogram with 500 neural fibres from the diffusion-weighted magnetic resonance scans, and extracted the information on electrical potential from the FE ECT model of the same head. We then calculated the first and second spatial derivatives of the electrical potential, which describes the activating function for homogenous axons and investigated sensitive regions of white matter activation.

Keywords

Brain, Humans, Electroconvulsive Therapy, Head

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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