Using computer simulations for predicting interventions restoring healthy patterns of neural activity

In many neurological disorders, the neurons change how they respond. For example, in Parkinson’s disease, the neurons in brain regions involved in initiation of movements start to produce oscillations in their activity. These oscillations make transmission of information more difficult and some of them are causing shaking of hands. One treatment for Parkinson’s disease involves electrical stimulation of the brain through implanted electrodes. The research in our unit aims in refining treatments like this one by making the stimulation dependent of the ongoing pattern of neural activity. The aim of this research programme is to use computer simulations to investigate how and when (in relation to ongoing activity) to provide the electrical stimulation to minimize the symptoms of the disease. Through simulations and analyses of mathematical models of brain networks, we will suggest ways of stimulations, which will be subsequently tested. We hope that the developed methods could be also applied to other neurological disorders.

Many neurological disorders are characterized by abnormal patterns of oscillations in neural activity. However, due to the complexity of the circuits these oscillations originate from, it is often unclear how they are generated, and how to best control them. To understand dynamics of complex systems, mathematical and computational methods are routinely employed in more established areas of science and engineering, and they have been proved critical for developing effective mechanisms for control of oscillations. This programme will develop methodology for using computer simulations of neural circuits affected by neurological disorders to predict interventions optimally restoring healthy patterns of activity. It will initially focus on Parkinson’s disease, because the basal ganglia circuits producing abnormal activity in this disorder are relatively well understood. Computational models of the basal ganglia will be developed that will describe how it generates the pathological dynamics and how it responds to deep brain stimulation (DBS) and optogenetic stimulation. The unique aspect of these models is that they will be constrained by a wide range of the high quality experimental data directly available in the MRC Unit, and optimized to maximize their ability to predict responses to novel stimulation protocols. The models will be used to rapidly test candidate versions of closed-loop DBS in silico, and to identify how and when with respect to ongoing activity the stimulation should be provided to optimally restore neural activity normally present in healthy basal ganglia. The suggested closed-loop intervention protocols will be tested within the MRC Unit, and results will be iteratively used to further refine the procedure. Moreover, the programme will investigate how the developed methodology and theory can be generalized to other neurological disorders (e.g. essential tremor) and to other neural systems (e.g. hippocampus).