Adaptive reweighting of synaptic and intrinsic excitability by deep brain stimulation in a dystonia model

PURPOSE: Deep brain stimulation (DBS) is a standard treatment for movement disorders like dystonia or Parkinson's Disease. Although its clinical effectiveness is established, the mechanisms by which DBS influences neural motor networks are not fully understood. This study explores the development of adaptive network mechanisms. METHODS: hamster model, an in vivo model exhibiting dystonic episodes, and used mathematical modelling to gauge the functional impact of these changes. RESULTS: In this electrophysiological and modelling study, we found 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. Both short- and long-term DBS prolonged miniature excitatory postsynaptic currents (mEPSC) intervals, but only short-term DBS reduced mean frequency. Acetylcholine application reversed this effect, restoring mEPSC frequency more efficiently in tissue subjected to short-term DBS compared to long-term DBS. SIGNIFICANCE: These observations indicate that DBS benefits in dystonia involve immediate and adaptive mechanisms, which have implications for improving stimulation parameters and treatment protocols. The findings reveal the temporal specificity of DBS effects and highlight the importance of understanding synaptic mechanisms to enhance therapeutic outcomes for dystonia patients.