P244 Multi-network Modeling of Parkinson’s Disease: Bridging Dopaminergic Modulation and Vibrotactile Coordinated Reset Therapy
Mariia Popova*1, Fatemeh Sadeghi2, Simone Zittel2, Claus C Hilgetag1,3
1Institute of Computational Neuroscience, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf (UKE), Hamburg University, Hamburg, Germany 2Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany 3Center for Biomedical AI, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
*Email: m.popova@uke.de Introduction
Computational models of Parkinson’s disease (PD) play an important role in understanding the complex neural mechanisms underlying motor symptoms, such as tremor, and in assessing novel treatment interventions. According to the “finger-dimmer-switch (FDS)” theory, tremor originates within the basal ganglia–thalamo-cortical (BTC) network, but subsequently spreads to the cerebello–thalamo-cortical (CTC) network through excessive inter-network synchronization [1]. One approach to manage severe PD tremor is to use deep brain stimulation (DBS). Recently, a new non-invasive approach of vibrotactile coordinated reset (vCR) stimulation was proposed as an alternative to DBS [2]. Here, we aimed to explore how vCR affects tremor in a computational model. Methods Building on the FDS, we developed a multi-network FDS model encompassing 700 neurons across 11 regions within the BTC, CTC, and thalamic networks. By modulating dopaminergic synaptic connections, we simulated the transition from a healthy state to a Parkinsonian state. Further adjustments of self-inhibition in thalamic nuclei drove tremor onset and offset. Results As hypothesized, dopaminergic restoration significantly reduced tremor amplitude and reinforced the thalamus as a pivotal hub for stabilizing neuronal activity. Next, we incorporated a variant of the model featuring spike-timing-dependent plasticity (STDP) to investigate vCR stimulation, a noninvasive therapy that applies patterned tactile pulses to disrupt pathological network synchronization. In line with previous theoretical findings, our simulations showed that vCR not only attenuated excessive beta-band oscillations but also unlearned maladaptive plasticity via STDP, suggesting a broader corrective effect on dysfunctional motor circuitry than dopaminergic interventions alone. Discussion These findings highlight the capacity of in silico models to guide therapeutic strategies, demonstrating that vCR may be of use in managing PD symptoms. Consequently, the parameter specifications of vCR should be investigated further in theoretical and clinical studies, as it may reduce patients’ reliance on pharmacological and surgical treatments.
Acknowledgements This study was funded by the EU project euSNN (MSCAITN-ETN H2020-860563) and Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—SFB 936—Project-ID 178316478-A1/Z3. References [1]https://doi.org/10.1016/j.nbd.2015.10.009 [2]https://doi.org/10.4103/1673-5374.329001
