Deep brain stimulation and lag synchronization in a memristive two-neuron network.

Journal: Neural networks : the official journal of the International Neural Network Society
PMID:

Abstract

In the pursuit of potential treatments for neurological disorders and the alleviation of patient suffering, deep brain stimulation (DBS) has been utilized to intervene or investigate pathological neural activities. To explore the exact mechanism of how DBS works, a memristive two-neuron network considering DBS is newly proposed in this work. This network is implemented by coupling two-dimensional Morris-Lecar neuron models and using a memristor synaptic synapse to mimic synaptic plasticity. The complex bursting activities and dynamical effects are revealed numerically through dynamical analysis. By examining the synchronous behavior, the desynchronization mechanism of the memristor synapse is uncovered. The study demonstrates that synaptic connections lead to the appearance of time-lagged or asynchrony in completely synchronized firing activities. Additionally, the memristive two-neuron network is implemented in hardware based on FPGA, and experimental results confirm the abundant neuronal electrical activities and chaotic dynamical behaviors. This work offers insights into the potential mechanisms of DBS intervention in neural networks.

Authors

  • Xihong Yu
    School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213159, PR China.
  • Han Bao
    Department of Computer Science, The University of Tokyo, Japan; Center for Advanced Intelligence Project, RIKEN, Japan. Electronic address: tsutsumi@ms.k.u-tokyo.ac.jp.
  • Quan Xu
    State Key Laboratory of Stress Cell Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian 361102, P.R. China.
  • Mo Chen
    School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, 710121 Xi'an, Shaanxi, China.
  • Bocheng Bao