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 language||English (US)|
|Title of host publication||2015 7th International IEEE/EMBS Conference on Neural Engineering, NER 2015|
|Publisher||IEEE Computer Society|
|Number of pages||4|
|State||Published - Jul 1 2015|
|Event||7th International IEEE/EMBS Conference on Neural Engineering, NER 2015 - Montpellier, France|
Duration: Apr 22 2015 → Apr 24 2015
|Name||International IEEE/EMBS Conference on Neural Engineering, NER|
|Other||7th International IEEE/EMBS Conference on Neural Engineering, NER 2015|
|Period||4/22/15 → 4/24/15|
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© 2015 IEEE.