Sunday, Jul 23: 8:00 AM - 9:15 AM
Deep brain stimulation (DBS) has been successfully applied in various neurodegenerative diseases as an effective symptomatic treatment. However, its mechanisms of action within the brain network are still poorly understood. Many virtual DBS models analyze a subnetwork around the basal ganglia and its dynamics as a spiking network with their details validated by experimental data. However, connectomic evidence shows widespread effects of DBS affecting many different cortical and subcortical areas. From a clinical perspective, various effects of DBS besides the motoric impact have been demonstrated.
We will introduce the neuroinformatics platform The Virtual Brain (TVB), which has previously been used to model pharmacological effects and virtual transcranial direct current stimulation (tDCS). TVB offers a modeling framework allowing us to virtually perform stimulation, including DBS, and forecast the outcome from a dynamic systems perspective prior to invasive surgery with DBS lead placement. For an accurate prediction of the effects of DBS, we implement a detailed spiking model of the basal ganglia, which we combine with TVB via our previously developed co-simulation environment. This multiscale co-simulation approach builds on the extensive previous literature of spiking models of the basal ganglia while simultaneously offering a whole-brain perspective on widespread effects of the stimulation going beyond the motor circuit.
In this first demonstration of our model, we show that virtual DBS can move the firing rates of a Parkinson's disease patient's thalamus - basal ganglia network towards the healthy regime while, at the same time, altering the activity in distributed cortical regions with a pronounced effect in frontal regions. Thus, we provide proof of concept for virtual DBS in a co-simulation environment with TVB.
Furthermore, we will show first successful validation steps of our multiscale model using multimodal data of individual whole-brain functional MRI BOLD signals and subthalamic nucleus local field potential data recorded by the DBS lead of Parkinson’s disease patients, both in DBS ON and OFF stimulation states. The developed modeling approach has the potential to optimize DBS lead placement and configuration and forecast the success of DBS treatment for individual patients. Further, we will give an outlook on our ongoing non-invasive stimulation modeling work of virtual tDCS and transcranial magnetic stimulation (TMS) using TVB.