Computational modeling and neuroimaging techniques for targeting during deep brain stimulation

Jennifer A. Sweet, Jonathan Pace, Fady Girgis, Jonathan P. Miller

Research output: Contribution to journalReview article

10 Scopus citations

Abstract

Accurate surgical localization of the varied targets for deep brain stimulation (DBS) is a process undergoing constant evolution, with increasingly sophisticated techniques to allow for highly precise targeting. However, despite the fastidious placement of electrodes into specific structures within the brain, there is increasing evidence to suggest that the clinical effects of DBS are likely due to the activation of widespread neuronal networks directly and indirectly influenced by the stimulation of a given target. Selective activation of these complex and inter-connected pathways may further improve the outcomes of currently treated diseases by targeting specific fiber tracts responsible for a particular symptom in a patient-specific manner. Moreover, the delivery of such focused stimulation may aid in the discovery of new targets for electrical stimulation to treat additional neurological, psychiatric, and even cognitive disorders. As such, advancements in surgical targeting, computational modeling, engineering designs, and neuroimaging techniques play a critical role in this process. This article reviews the progress of these applications, discussing the importance of target localization for DBS, and the role of computational modeling and novel neuroimaging in improving our understanding of the pathophysiology of diseases, and thus paving the way for improved selective target localization using DBS.

Original languageEnglish (US)
Article number71
JournalFrontiers in Neuroanatomy
Volume10
Issue numberJUNE
DOIs
StatePublished - Jun 30 2016
Externally publishedYes

Keywords

  • Computational modeling
  • Deep brain stimulation
  • Neuroimaging
  • Targeting
  • Tractography

ASJC Scopus subject areas

  • Anatomy
  • Neuroscience (miscellaneous)
  • Cellular and Molecular Neuroscience

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