Deep brain stimulation (DBS) is emerging as a viable treatment option for selected patients with dystonia. Intraoperative extracellular microelectrode recordings (MER) are considered as the standard electrophysiological method for the precise positioning of the DBS electrode into the target brain structure. Accurate targeting of the permanent stimulation electrode into the Globus Pallidus internus (GPi) is key to positive long-term effects. The suitability of the location is peroperatively assessed by microelectrodes that register single-unit neuronal activity. The aim of this article is to analyse electrophysiological recordings of patient's neuronal activity with a focus on the identification of markers relevant to the patient's clinical state.

In this study, 13 patients chronically treated with double-sided DBS GPi were examined with a microrecording. The signal (24 kHz) processing, included bandpass filtering (0.5–5 kHz), automated detection of artefacts and feature extraction. Pre-processed signals were analysed by means of statistical learning.

The results show that the GPi was distinguished from its vicinity with p < 0.001 and 3 machine learning models AUCs had an accuracy of higher than 0.87. The observed biomarker, Hjort mobility, additionally correlated with the long-term neuromodulation effect (rho = −0.4; p < 0.05). Furthermore, we revealed a change of neural activity associated with the active distal DBS contact localization along the medio-lateral direction.

This paper demonstrates the quantitative relationship between electrophysiological findings and the clinical effects of pallidal stimulation in dystonia and suggested objectification predictors of the effectiveness of this therapy.