Analysis of computational models of deep brain stimulation using spherical statistics

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Computational models of deep brain stimulation (DBS) have played a key role in investigating the mechanisms of action of DBS therapies. By estimating a volume of tissue directly modulated by DBS, one can relate the pathways within those volumes to the therapeutic efficacy of a particular DBS setting. With the advent of higher-density DBS electrode arrays, there is a growing need for a systematic method to quantify the morphology of the modulated volumes within the brain. In this study, we applied the tools of spherical statistics to quantify such morphologies through the application of a computational model of a directionally segmented DBS array. The same statistical techniques have broad applications to characterizing distributions of in-vivo electrophysiological recordings and histological labeling of neurons.

Original languageEnglish (US)
Title of host publication2015 7th International IEEE/EMBS Conference on Neural Engineering, NER 2015
PublisherIEEE Computer Society
Pages856-859
Number of pages4
ISBN (Electronic)9781467363891
DOIs
StatePublished - Jul 1 2015
Event7th International IEEE/EMBS Conference on Neural Engineering, NER 2015 - Montpellier, France
Duration: Apr 22 2015Apr 24 2015

Publication series

NameInternational IEEE/EMBS Conference on Neural Engineering, NER
Volume2015-July
ISSN (Print)1948-3546
ISSN (Electronic)1948-3554

Other

Other7th International IEEE/EMBS Conference on Neural Engineering, NER 2015
CountryFrance
CityMontpellier
Period4/22/154/24/15

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