Evoked resonant neural activity long-term dynamics can be reproduced by a computational model with vesicle depletion.

ABSTRACT: Subthalamic deep brain stimulation (DBS) robustly generates high-frequency oscillations known as evoked resonant neural activity (ERNA). Recently the importance of ERNA has been demonstrated through its ability to predict the optimal DBS contact in the subthalamic nucleus in patients with Parkinson's disease. However, the underlying mechanisms of ERNA are not well understood, and previous modelling efforts have not managed to reproduce the wealth of published data describing the dynamics of ERNA. Here, we aim to present a minimal model capable of reproducing the characteristics of the slow ERNA dynamics published to date. We make biophysically-motivated modifications to the Kuramoto model and fit its parameters to the slow dynamics of ERNA obtained from data. Our results demonstrate that i

SUBMITTER: Sermon JJ 

PROVIDER: S-EPMC11300885 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature