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Combining Transcranial Magnetic Stimulation and fMRI to Examine the Default Mode Network
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Numerical optimization of coordinated reset stimulation for desynchronizing neuronal network dynamics.

Shigeru Kubota1, Jonathan E Rubin2

  • 1Graduate School of Science and Engineering, Yamagata University, 4-3-16 Jonan, Yonezawa, Yamagata, 992-8510, Japan. kubota@yz.yamagata-u.ac.jp.

Journal of Computational Neuroscience
|June 9, 2018
PubMed
Summary
This summary is machine-generated.

This study optimized energy-efficient electrical stimulation waveforms to desynchronize neural activity, a key goal for treating Parkinson's disease (PD). The findings highlight how network dynamics influence the effectiveness of coordinated reset (CR) neuromodulation.

Keywords:
Brain stimulationCoordinated resetNumerical optimizationParkinson’s diseaseSynchronization

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Area of Science:

  • Computational Neuroscience
  • Biomedical Engineering
  • Neuromodulation

Background:

  • Excessive neural synchronization is a hallmark of Parkinson's disease (PD).
  • Coordinated Reset (CR) neuromodulation uses multi-electrode stimulation to desynchronize neural populations, offering a potential PD treatment.

Purpose of the Study:

  • To determine the energy-optimal current waveform for CR neuromodulation.
  • To develop and apply a novel numerical optimization method for CR stimulation.

Main Methods:

  • A direct search optimization algorithm was employed.
  • Stimulating current was represented as a Fourier series, with coefficients and stimulation period optimized.
  • Network simulations evaluated the order parameter to quantify synchrony levels.

Main Results:

  • The optimization successfully identified energy-optimal waveforms for CR stimulation.
  • External oscillatory inputs and non-random network topology significantly influenced CR modulation efficacy.
  • The optimization method effectively accounted for network dynamical property changes.

Conclusions:

  • Brain stimulation effectiveness for neural desynchronization depends on factors modulating target network dynamics.
  • Results provide insights into optimizing CR neuromodulation for Parkinson's disease treatment.