2015
DOI: 10.1016/j.jneumeth.2015.08.001
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Spherical statistics for characterizing the spatial distribution of deep brain stimulation effects on neuronal activity

Abstract: Background Computational models of deep brain stimulation (DBS) have played a key role in understanding its physiological mechanisms. By estimating a volume of tissue directly modulated by DBS, one can relate the neuronal pathways within those volumes to the therapeutic efficacy of a particular DBS setting. New Method A spherical statistical framework is described to quantify and determine salient features of such morphologies using visualization techniques, empirical shape analysis, and formal hypothesis te… Show more

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Cited by 2 publications
(2 citation statements)
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References 64 publications
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“…They used mixtures of vMF to model their concept of selectivity profiles, each component of the mixture corresponding to a functional system concentrated about a favored direction on the sphere. Both rotationally and non-rotationally symmetric models are used in Xiao and Johnson (2015) in the study of neuronal population volumes. The objective was to fit the distribution of neuronal spike activity around one or more active electrodes.…”
Section: Motivationmentioning
confidence: 99%
“…They used mixtures of vMF to model their concept of selectivity profiles, each component of the mixture corresponding to a functional system concentrated about a favored direction on the sphere. Both rotationally and non-rotationally symmetric models are used in Xiao and Johnson (2015) in the study of neuronal population volumes. The objective was to fit the distribution of neuronal spike activity around one or more active electrodes.…”
Section: Motivationmentioning
confidence: 99%
“…In this way, the combined use of imaging techniques described in this study can assist in neurosurgical navigation of DBS targets in a given subject (Kamiryo and Laws, 1996 ; Dormont et al, 1997 ; Dipierro et al, 1999 ). Additionally, the segmented nuclei reconstructions can also aid in the development of more accurate computational models of DBS (Mcintyre et al, 2004 ; Kuncel et al, 2008 ; Keane et al, 2012 ; Zitella et al, 2013 ) to retrospectively quantify the neural pathways modulated by thalamic DBS therapy (Xiao and Johnson, 2015 ) or prospectively predict the stimulation settings necessary to target those pathways on a subject-specific basis (Xiao et al, 2016 ).…”
Section: Application To Dbs Targetingmentioning
confidence: 99%