2025-07-23 –, Main Room 2
We showcase Neuroblox.jl's capabilities for investigating Deep Brain Stimulation (DBS) effects on basal ganglia dynamics. This framework enables efficient and detailed simulation of neural circuits under various stimulation protocols, providing an intuitive platform for testing DBS parameters and exploring phenomena like Evoked Resonant Neural Activity (ERNA).
Deep Brain Stimulation (DBS) is a neurosurgical procedure involving the implantation of a "brain pacemaker" that delivers electrical impulses to specific brain regions. This therapeutic approach has become particularly important in treating Parkinson's disease (PD), which affects around 1% of people over 60. In PD patients, DBS electrodes target key structures within the basal ganglia - primarily the subthalamic nucleus (STN) or Globus pallidus internus (GPi) - to help restore normal motor function[1,2].
Despite its clinical success, DBS therapy faces several challenges. The stimulation protocols used are largely ad hoc, developed decades ago to accommodate hardware limitations rather than being based on underlying neurobiological mechanisms. While effective at treating motor symptoms, patients can experience adverse effects due to factors like electrode placement and suboptimal programming parameters[3,4]. Computational modeling offers a powerful approach to better understand these challenges and optimize treatment parameters.
We explore Neuroblox.jl's capabilities as a computational platform for DBS modeling. Our implementation incorporates detailed biophysical models of the basal ganglia circuit, with particular focus on STN-GPe network dynamics based on recently proposed models[4]. Additionally, we have developed a flexible DBS stimulation module that allows testing various stimulation protocols, enabling investigation of phenomena like Evoked Resonant Neural Activity (ERNA)[5,6].
This lightning talk will showcase how Neuroblox.jl, leveraging both its computational efficiency and intuitive approach to complex model construction, can serve as a valuable tool for investigating neural stimulation mechanisms and advancing our understanding of neuromodulation therapies.
References:
[1] McGregor MM, Nelson AB. Circuit Mechanisms of Parkinson's Disease. Neuron. 2019;101(6):1042-56.
[2] Herrington TM, Cheng JJ, Eskandar EN. Mechanisms of deep brain stimulation. J. Neurophysiol. 2016;115(1):19-38.
[3] Buhmann C, et al. Adverse events in deep brain stimulation: A retrospective long-term analysis of neurological, psychiatric and other occurrences. PLoS One. 2017;12(7):e0178984.
[4] Adam EM, et al. Deep brain stimulation in the subthalamic nucleus for Parkinson's disease can restore dynamics of striatal networks. Proc Natl Acad Sci U S A. 2022;119(19):e2120808119.
[5] Sinclair NC, et al. Deep brain stimulation for Parkinson's disease modulates high-frequency evoked and spontaneous neural activity. Neurobiol Dis. 2019;130:104522.
[6] Thevathasan W, et al. Tailoring Subthalamic Nucleus Deep Brain Stimulation for Parkinson's Disease Using Evoked Resonant Neural Activity. Front Hum Neurosci. 2020;14:71.
