Mathematical modeling for description of oscillation suppression induced by deep brain stimulation

Chen Liu, Changsong ZHOU*, Jiang Wang, Kenneth A. Loparo

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

A mathematical modeling for description of oscillation suppression by deep brain stimulation (DBS) is explored in this paper. High-frequency DBS introduced to the basal ganglia network can suppress pathological neural oscillations that occur in the Parkinsonian state. However, selecting appropriate stimulation parameters remains a challenging issue due to the limited understanding of the underlying mechanisms of the Parkinsonian state and its control. In this paper, we use a describing function analysis to provide an intuitive way to select the optimal stimulation parameters based on a biologically plausible computational model of the Parkinsonian neural network. By the stability analysis using the describing function method, effective DBS parameter regions for inhibiting the pathological oscillations can be predicted. Additionally, it is also found that a novel sinusoidal-shaped DBS may become an alternative stimulation pattern and expends less energy, but with a different mechanism. This paper provides new insight into the possible mechanisms underlying DBS and a prediction of optimal DBS parameter settings, and even suggests how to select novel DBS wave patterns for the treatment of movement disorders, such as Parkinson's disease.

Original languageEnglish
Article number8404106
Pages (from-to)1649-1658
Number of pages10
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume26
Issue number9
DOIs
Publication statusPublished - Sep 2018

Scopus Subject Areas

  • Internal Medicine
  • Neuroscience(all)
  • Biomedical Engineering

User-Defined Keywords

  • basal ganglia
  • deep brain stimulation
  • describing function
  • Oscillations suppression
  • Parkinsonian state

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