Nada Yousif,
Peter Bain,
Dipankar Nandi,
Roman Borisyuk
https://meet.google.com/wpp-stff-der
The presence of neural oscillations is thought to be a hallmark of two of the most common movement disorders, Parkinson’s disease (PD) and Essential tremor (ET). The symptoms of PD are tremor, slowness of movement and stiffness (Parkinson’s UK, 2019) and is caused by the loss of dopaminergic neurons in the substantia nigra. Although the pathological changes in the basal ganglia network are not yet fully understood, it is widely accepted that beta-band (15-30 Hz) oscillations play a role. Essential tremor (ET) affects up to one percent of adults over 40 years of age, and is characterized by an uncontrollable shaking of the affected body part (Louis, Ottman, and Hauser 1998; Brin and Koller 1998; Deuschl, Bain, and Brin 1998a). The neurophysiological basis of ET remains unknown, but pathological neural oscillations in the thalamocortical-cerebellar network are also implicated in generating symptoms.
In our previous network study of PD, we studied how a multi-channel model of Wilson-Cowan oscillators representing the STn-GPe behaved in healthy and Parkinsonian conditions. We found that oscillations exist for a much wider range of parameters in the Parkinsonian case and demonstrated how an input representing DBS caused the oscillations to become chaotic and flattened the power spectrum. Looking at ET, we again used a mean- field approach combined with intraoperative local field potential recordings from the Vim via DBS electrodes, and simultaneous electromyographic activity from the contralateral affected limb(s). We used the Wilson-Cowan approach to model the thalamocortical-cerebellar network implicated in ET. We found that the network exhibited oscillatory behaviour within the tremor frequency range of 4-5 Hz, as did our electrophysiological data. Applying a DBS-like input to the modelled network had the effect of suppressing these oscillations. Our two previous studies therefore show that the dynamics of the cerebellar-basal ganglia thalamocortical network support oscillations at frequency ranges relevant to movement disorders. The application of a DBS-like input into the modelled networks disrupts such pathological activity. We believe that this is an important way to study the impact of DBS on the human brain and should be used in conjunction with experimental recordings of neural activity as well as with single neuron biophysical modelling work.
In this work we present new results from a combined model which exhibits Parkinsonian oscillations in the beta band, oscillations in the tremor frequency range, as well as oscillations in the gamma band which we term healthy (Beudal et. al, 2015; Fischer et al, 2017). We find critical boundaries in the parameter space of the model separating regions with different dynamics. We go on to examine the transition from one oscillatory regime to another behavior and the impact of DBS on these two types of pathological activity. This approach will not only allow us to better understand the mechanisms of DBS, but allow us to optimize the lengthy and difficult clinical process of parameter setting via trial and error, upon which the cited improvement in symptoms is reliant (Rizzone et al. 2001; Moro et al. 2002). Furthermore, with the advent of electrodes with more contacts this process is becoming increasingly difficult. Hence the need for a theoretical understanding of DBS is particularly important at present.
