Protocol for artificial intelligence-guided neural control using deep reinforcement learning and infrared neural stimulation.

Journal: STAR protocols
PMID: 39705145

Abstract

Closed-loop neural control is a powerful tool for both the scientific exploration of neural function and for mitigating deficiencies found in open-loop deep brain stimulation (DBS). Here, we present a protocol for artificial intelligence-guided neural control in rats using deep reinforcement learning (RL) and infrared neural stimulation (INS). We describe steps for integrating RL closed-loop control into neuroscience and neuromodulation studies. We then detail procedures for using and deploying infrared INS in chronic DBS applications. For complete details on the use and execution of this protocol, please refer to Coventry et al. and Coventry and Bartlett..

Authors

  • Brandon S Coventry
    Weldon School of Biomedical Engineering, the Center for Implantable Devices, and the Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN 47907, USA. Electronic address: coventry@wisc.edu.
  • Edward L Bartlett
    Weldon School of Biomedical Engineering, the Center for Implantable Devices, and the Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN 47907, USA; Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA. Electronic address: ebartle@purdue.edu.

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