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Spiliotis, K.

Publications and source records attributed to Spiliotis, K..

2 recordsLinked to original sources

Differential Effects of Short-term and Long-term Deep Brain Stimulation on Striatal Neuronal Excitability in a Dystonia Animal Model

Deep brain stimulation (DBS) is, by now, one of the standard treatment options for movement disorders like dystonia or Parkinsons Disease. Although its clinical effectiveness is established, the exact mechanisms by which DBS influences neural motor networks are not fully understood. The present study explores the development of adaptive network mechanisms with DBS in the dtsz hamster model, an in-vivo model exhibiting spontaneous dystonic episodes, by comparing functional impacts of short-term and long-term DBS on medium spiny neurons (MSNs) and synaptic transmission in the striatum. In this electrophysiological study, we uncovered contrasting changes in neuronal excitability and synaptic dynamics following short-term versus long-term DBS. Short-term DBS enhanced neuronal firing responses, while long-term DBS diminished them. Regarding synaptic alterations, both short-term and long-term DBS significantly shifted spontaneous EPSC occurrences to longer intervals, with this effect, however, being more pronounced in short-term DBS, leading to a significant decrease in mEPSC frequency. Notably, acetylcholine application effectively reversed this effect, restoring mEPSC frequency more efficiently again in tissue subjected to short-term DBS compared to long-term DBS. These observations indicate that the therapeutic benefits of DBS in dystonia may involve both immediate and adaptive mechanisms, which has implications for improving stimulation parameters and treatment protocols. The findings shed light on the temporal specificity of DBS effects and highlight the importance of understanding synaptic mechanisms to enhance therapeutic outcomes for dystonia patients.

neuroscience↗

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

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.

neuroscience↗