For more than 30 years, deep brain stimulation (DBS) has been used to target the
symptoms of a number of neurological disorders and in particular movement disorders
such as Parkinson’s disease (PD) and essential tremor (ET). It is known that the loss
of dopaminergic neurons in the substantia nigra leads to PD, while the exact ...
For more than 30 years, deep brain stimulation (DBS) has been used to target the
symptoms of a number of neurological disorders and in particular movement disorders
such as Parkinson’s disease (PD) and essential tremor (ET). It is known that the loss
of dopaminergic neurons in the substantia nigra leads to PD, while the exact impact
of this on the brain dynamics is not fully understood, the presence of beta-band
oscillatory activity is thought to be pathological. The cause of ET, however, remains
uncertain, however pathological oscillations in the thalamocortical-cerebellar network
have been linked to tremor. Both of these movement disorders are treated with DBS,
which entails the surgical implantation of electrodes into a patient’s brain. While DBS
leads to an improvement in symptoms for many patients, the mechanisms underlying
this improvement is not clearly understood, and computational modeling has been used
extensively to improve this. Many of the models used to study DBS and its effect on
the human brain have mainly utilized single neuron and single axon biophysical models.
We have previously shown in separate models however, that the use of population
models can shed much light on the mechanisms of the underlying pathological neural
activity in PD and ET in turn, and on the mechanisms underlying DBS. Together,
this work suggested that the dynamics of the cerebellar-basal ganglia thalamocortical
network support oscillations at frequency range relevant to movement disorders. Here,
we propose a new combined model of this network and present new results that
demonstrate that both Parkinsonian oscillations in the beta band and oscillations in the
tremor frequency range arise from the dynamics of such a network. We find regions in
the parameter space demonstrating the different dynamics and go on to examine the
transition from one oscillatory regime to another as well as the impact of DBS on these
different types of pathological activity. This work will allow us to better understand the
changes in brain activity induced by DBS, and allow us to optimize this clinical therapy,
particularly in terms of target selection and parameter setting.