ML-STIM: Machine learning for subthalamic nucleus intraoperative mapping.

Journal: Journal of neural engineering
Published Date: Jul 29, 2025

Abstract

OBJECTIVE: Deep Brain Stimulation (DBS) of the Subthalamic Nucleus (STN) is effective in alleviating motor symptoms in medication-refractory patients with Parkinson's Disease (PD). Intraoperative identification of the STN relies on MicroElectrode Recordings (MERs), typically analysed by trained operators. However, this approach is time-consuming and subject to variability. For this reason, this study proposes ML-STIM (Machine Learning for SubThalamic nucleus Intraoperative Mapping), a machine learning pipeline designed to automate STN classification from MERs, ensuring high accuracy and real-time performance.

Authors

  • Fabrizio Sciscenti
    Department of Electronics and Telecommunications, Politecnico di Torino, Corso Duca degli Abruzzi, 24, Turin, Turin, 10129, ITALY.
  • Valentina Agostini
    Department of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy.
  • Laura Rizzi
    Department of Neuroscience "Rita Levi Montalcini", University of Turin, Via Chierasco, 15, Turin, Piedmont, 10126, ITALY.
  • Michele Lanotte
    Department of Neuroscience "Rita Levi Montalcini", University of Turin, Via Chierasco, 15, Turin, Piedmont, 10126, ITALY.
  • Marco Ghislieri
    Department of Electronics and Telecommunications, Politecnico di Torino, Corso Castelfidardo 39, Turin, 10129, ITALY.

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