Suppressing epileptic activity in a neural mass model using a closed-loop proportional-integral controller

Junsong Wang, Ernst Niebur, Jinyu Hu, Xiaoli Li

Research output: Contribution to journalArticle

Abstract

Closed-loop control is a promising deep brain stimulation (DBS) strategy that could be used to suppress high-amplitude epileptic activity. However, there are currently no analytical approaches to determine the stimulation parameters for effective and safe treatment protocols. Proportional-integral (PI) control is the most extensively used closed-loop control scheme in the field of control engineering because of its simple implementation and perfect performance. In this study, we took Jansen's neural mass model (NMM) as a test bed to develop a PI-type closed-loop controller for suppressing epileptic activity. A graphical stability analysis method was employed to determine the stabilizing region of the PI controller in the control parameter space, which provided a theoretical guideline for the choice of the PI control parameters. Furthermore, we established the relationship between the parameters of the PI controller and the parameters of the NMM in the form of a stabilizing region, which provided insights into the mechanisms that may suppress epileptic activity in the NMM. The simulation results demonstrated the validity and effectiveness of the proposed closed-loop PI control scheme.

Original languageEnglish (US)
Article number27344
JournalScientific reports
Volume6
DOIs
StatePublished - Jun 7 2016

ASJC Scopus subject areas

  • General

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