Stability Analysis and Neural Control of Subcortical Oscillations in Parkinson's Excitatory-Inhibitory Network

Abstract: Freezing of gait (FoG) is a common and disabling symptom of Parkinson’s disease (PD),characterized by impaired motor control due to altered oscillatory activity and disruptedsynchronization within the cortico-subcortical basal ganglia-thalamus network. Currenttherapeutic strategies, including deep brain stimulation, often fail to fully alleviate FoG,highlighting the need for innovative approaches to better understand and manage thiscomplex symptom. This study investigates the steady-state dynamics underlying FoG byemploying equilibrium point analysis of the physiologically connected network in bothhealthy and PD configurations. An artificial neural network (ANN) controller, adapted fromexisting designs with modifications, is used to restore stability in the PD network dynamics.Using a Kuramoto model, we examined the synchronization behaviour of interconnectednuclei constrained by excitation-inhibition communication, focussing on phase balancedynamics through stability analysis of equilibrium points. The simulations indicate thatthe adaptive ANN controller can modulate these phase dynamics by targeting either thesubthalamic nucleus (STN) and substantia nigra pars reticulata (SNr) or the STN and globuspallidus pars interna (GPi), leading to improved control of substantia nigra pars compacta (SNc) synchronization within the network. This research enhances the theoreticalunderstanding of the mechanisms underlying the functional architecture, specifically theexcitatory-inhibitory network involved in FoG. It also demonstrates that a modified neuralcontrol approach, which targets the minimal number of nuclei and adapts internally without reliance on external sensory feedback, indicates the potential to modulate networkdynamics in a theoretical setting.link to the article: https://doi.org/10.1080/21642583.2025.2587812