A neural mass model to predict electrical stimulation evoked responses in human and non-human primate brain.

摘要: Objective Deep brain stimulation (DBS) is a valuable tool for ameliorating drug resistant pathologies such as movement disorders and epilepsy. DBS also being considered complex neuro-psychiatric disorders, which are characterized by high variability in symptoms slow responses that hinder setting optimization. The objective of this work was to develop an silico platform examine the effects electrical regions neighboring stimulated region. Approach We used Jansen-Rit neural mass model single coupled nodes simulate response train current pulses at different frequencies (10-160 Hz) local field potential recorded amygdala cortical structures human subjects non-human primate. Results found using node model, evoked could be accurately modeled following narrow range frequencies. Including second increased whose efficiently modeled. Furthermore, chronic recording from primate, features vivo remained consistent several weeks, suggesting re-parameterization protocols would infrequent. Significance Using population activity, we reproduced subcortical This modeling framework provides environment explore, safely rapidly, wide settings not possible studies. can trained on limited dataset optimal strategy individual patient.