Computational Neuromodulation: Future Challenges for Deep Brain Stimulation [Life Sciences]

Konstantinos P. Michmizos, Blerta Lindqvist, Stephen Wong, Eric L. Hargreaves, Konstantinos Psychas, Georgios D. Mitsis, Shabbar F. Danish, Konstantina S. Nikita

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Over the past two decades, deep brain stimulation (DBS) has been leading a renaissance of neurosurgical treatments for neurological and neuropsychiatric disorders. DBS has become an established adjunct therapy for movement and mood disorders that, despite maximal medical treatment, remain sufficiently debilitating to warrant the risks of brain surgery [1]. The procedure has been approved by the U.S. Food and Drug Administration (FDA) for essential tremor (ET), Parkinson's disease (PD), dystonia, and obsessive compulsive disorder, and the growing spectrum of treatable conditions is expanding to pain and major depression, among others. Interestingly, the large phenomenological variance of the treatable symptoms that span the motor and affective domains is addressed by the same therapeutic principle: similarly to how a cardiac pacemaker works, a medical device called a neurostimulator sends frequent (50-250 Hz) electrical pulses to electrodes implanted into a subcortical nucleus associated with the disorder. Despite its simplicity, the procedure, when applied accurately, may alleviate symptoms of complicated diseases.

Original languageEnglish (US)
Article number7872538
Pages (from-to)114-119
Number of pages6
JournalIEEE Signal Processing Magazine
Volume34
Issue number2
DOIs
StatePublished - Mar 2017

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

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