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Closed-loop controller based on reference signal tracking for absence seizures.

Hudong Zhang1, Yuting Chen1, Yan Xie1

  • 1School of Mathematics and Physics, Shanghai University of Electric Power, Shanghai, 201306, China.

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|April 26, 2022
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Summary
This summary is machine-generated.

This study introduces novel closed-loop deep brain stimulation (DBS) controllers for treating absent epilepsy. These controllers automatically adjust stimulation parameters, effectively eliminating spike-and-wave discharges and offering a promising new treatment strategy.

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Computational Neuroscience

Background:

  • Absent epilepsy is a refractory epilepsy characterized by specific electroencephalogram patterns.
  • Open-loop deep brain stimulation (DBS) targeting the thalamic reticular nucleus (TRN) can treat absent epilepsy.
  • Closed-loop DBS offers advantages over open-loop DBS, including better seizure inhibition and fewer side effects.

Purpose of the Study:

  • To design and evaluate novel closed-loop DBS controllers for absent epilepsy treatment.
  • To overcome the limitations of traditional trial-and-error methods for tuning DBS controller parameters.
  • To develop an automated system for adjusting DBS frequency and amplitude based on real-time neural activity.

Main Methods:

  • Designed two proportional integral (PI) controllers based on a basal ganglia-cortical-thalamic model.
  • Calculated PI controller parameters using the Routh-Hurwitz stability criterion applied to a linearized system.
  • Utilized controlled auto-regressive (CAR) and recursive least squares (RLS) methods for system identification and parameter calculation.
  • Simulated the closed-loop DBS system's response to absent epilepsy conditions.

Main Results:

  • The designed PI controllers effectively disrupted spike-and-wave discharges (SWDs) associated with absent epilepsy.
  • The controllers successfully restored cerebral cortex activity to normal discharge modes.
  • The system demonstrated automatic adjustment of DBS parameters based on detected neural firing rates from the substantia nigra pars reticulata (SNr).

Conclusions:

  • The developed closed-loop DBS controllers represent a promising strategy for treating absent epilepsy.
  • Automated parameter tuning based on system stability criteria enhances the efficacy and reduces reliance on empirical adjustments.
  • This approach offers a more effective and potentially safer treatment for refractory epilepsy.