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BGRL: Basal Ganglia inspired Reinforcement Learning based framework for deep brain stimulators.

Harsh Agarwal¹, Heena Rathore²

¹Department of Electrical and Computer Engineering, Indian Institute of Technology, India.

Artificial Intelligence in Medicine

|January 6, 2024

Summary

This summary is machine-generated.

A new Basal Ganglia inspired Reinforcement Learning (BGRL) method enhances Deep Brain Stimulation (DBS) by reducing neural synchrony. This closed-loop approach offers improved efficiency and suppression capabilities for neurological disorder treatment.

Keywords:

Actor–critic Basal ganglia Deep brain stimulators Neuro-inspired Reinforcement learning

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Area of Science:

Biomedical Engineering
Computational Neuroscience
Artificial Intelligence

Background:

Deep Brain Stimulation (DBS) is an implantable device for neurological disorders.
Current DBS devices use fixed stimulation frequencies, limiting personalized treatment effectiveness.
Optimizing stimulation parameters is key for successful DBS therapy.

Purpose of the Study:

To introduce a novel Basal Ganglia inspired Reinforcement Learning (BGRL) approach for DBS.
To incorporate a closed-loop feedback mechanism for suppressing neural synchrony.
To enhance the efficacy and efficiency of DBS treatment through personalized stimulation.

Main Methods:

Developed a Basal Ganglia inspired Reinforcement Learning (BGRL) algorithm.
Integrated an actor-critic architecture from reinforcement learning (RL).
Implemented a closed-loop feedback system to dynamically adjust stimulation parameters.

Main Results:

BGRL significantly reduced synchronous electrical pulses compared to standard RL algorithms.
BGRL demonstrated superior suppression capabilities and lower energy consumption.
Suppressed synchronous electrical pulses by 40% (regular), 146% (chaotic), and 40% (bursting) versus the soft actor-critic model.

Conclusions:

The BGRL approach shows significant promise for suppressing neural synchrony in DBS.
BGRL offers an efficient, closed-loop alternative to traditional open-loop DBS methodologies.
This method paves the way for more personalized and effective neurological disorder treatments.