Utilising activity patterns of a complex biophysical network model to optimise intra-striatal deep brain stimulation

Abstract

AO_SCPLOWBSTRACTC_SCPLOWIn this study, we develop a large-scale biophysical network model for the isolated striatal body to optimise potential intrastriatal deep brain stimulation applied in, e.g. obsessive-compulsive disorder by using spatiotemporal patterns produced by the network. The model uses modified Hodgkin-Huxley models on small-world connectivity, while the spatial information, i.e. the positions of neurons, is obtained from a detailed human atlas. The model produces neuronal activity patterns segregating healthy from pathological conditions. Three indices were used for the optimisation of stimulation protocols regarding stimulation frequency, amplitude and localisation: the mean activity of the entire network, the mean activity of the ventral striatal area (emerging as a defined community using modularity detection algorithms), and the frequency spectrum of the entire network activity. By minimising the deviation of the aforementioned indices from the normal state, we guide the optimisation of deep brain stimulation parameters regarding position, amplitude and frequency.