Changes in Neuronal Entropy in a Network Model of the Cortico-Basal Ganglia during Deep Brain Stimulation

Abstract

Neuronal entropy changes are observed in the basal ganglia circuit in Parkinson's disease (PD). These changes are observed in both single unit recordings from globus pallidus (GP) neurons and in local field potential (LFP) recordings from the subthalamic nucleus (STN). These changes are hypothesized as representing changes in the information coding capacity of the network, with PD resulting in a reduction in the coding capacity of the basal ganglia network. Entropy changes in the LFP and in single unit recordings are investigated in a detailed physiological model of the cortico-basal ganglia network during STN deep brain stimulation (DBS). The model incorporates extracellular stimulation of STN afferent fibers, with both orthodromic and antidromic activation, and simulation of the LFP detected at a differential recording electrode. LFP sample entropy and beta-band oscillation power were found to be altered following the application of DBS. The firing pattern entropy of GP neurons in the network were observed to decrease during high frequency stimulation and increase during low frequency stimulation. Simulation results were consistent with experimentally reported changes in neuronal entropy during DBS.

Stimulation-induced changes at the electrode–tissue interface and their influence on deep brain stimulation

“…Axon collaterals were positioned within the STN, parallel to one another, and orientated to project in the direction. The axon and collateral model was based on that used previously by Lowery and Kang [27,38] with membrane parameters based on an experimental study in mice developed by Foust et al [39]. This model captures the threshold of activation of the axon and collateral by considering the properties of the model neuron along with the electrode geometry, the ETI, and the heterogeneity and electrical properties of brain tissue incorporated in the rat DBS FEM model.…”

Closed-Loop Deep Brain Stimulation with Reinforcement Learning and Neural Simulation

“…Additionally, a BGT-Gym framework is provided, allowing for modifications to action and state spaces, reward design, etc. The chosen feature extraction methods, validated in extracellular electrophysiological signals (as seen in literature [26]- [30], etc. ), imply their feasibility for future deployment.…”

“…A lower entropy value indicates a higher degree of self-similarity in the dataset, reflecting lower complexity and irregularity, which is often observed in PD cases. In the context of subthalamic nucleuslocal field potential (STN-LFP) signals, neuronal entropy exhibited a progressive increase with the rise of DBS amplitude, coinciding with the suppression of beta band oscillation-a characteristic that can be interpreted as an inverse indicator [30]. In figure 5, scaled values of the above feature extraction methods are depicted for both synaptic signal, S GP i from the BGT environment and the EEG dataset from [31] across PD and control (healthy) states.…”

Functional Neural Changes after Low-Frequency Bilateral Globus Pallidus Internus Deep Brain Stimulation for Post-Hypoxic Cortical Myoclonus: Voxel-Based Subtraction Analysis of Serial Positron Emission

“…In previous studies, PET results indicated that PHM is associated with changes in metabolic activity of the Gpi [ 26 , 27 ], especially because the Gpi is considered vulnerable to hypoxic brain damage [ 28 , 29 ]. It is known that globus pallidus (GP) neurons in the network decrease during high-frequency stimulation and increase during low frequency stimulation [ 30 ]. Although high-frequency stimulation targeting the Gpi has been reported in a few studies, in the present study, an increase in myoclonus ratings at high stimulation frequencies was observed, which is not in line with previous findings.…”