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Combining magnetoencephalography with telemetric streaming of intracranial recordings and deep brain stimulation—A feasibility study

Hnazaee, Mansoureh Fahimi; Sure, Matthias; O’Neill, George C; Leogrande, Gaetano; Schnitzler, Alfons; Florin, Esther; Litvak, Vladimir; (2023) Combining magnetoencephalography with telemetric streaming of intracranial recordings and deep brain stimulation—A feasibility study. Imaging Neuroscience , 1 pp. 1-22. 10.1162/imag_a_00029. Green open access

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Abstract

The combination of subcortical Local Field Potential (LFP) recordings and stimulation with Magnetoencephalography (MEG) in Deep Brain Stimulation (DBS) patients enables the investigation of cortico-subcortical communication patterns and provides insights into DBS mechanisms. Until now, these recordings have been carried out in post-surgical patients with externalised leads. However, a new generation of telemetric stimulators makes it possible to record and stream LFP data in chronically implanted patients. Nevertheless, whether such streaming can be combined with MEG has not been tested. In the present study, we tested the most commonly implanted telemetric stimulator—Medtronic Percept PC with a phantom in three different MEG systems: two cryogenic scanners (CTF and MEGIN) and an experimental Optically Pumped Magnetometry (OPM)-based system. We found that when used in combination with the new SenSight segmented leads, Percept PC telemetric streaming only generates band-limited interference in the MEG at 123 Hz and harmonics. However, the “legacy streaming mode” used with older lead models generates multiple, dense artefact peaks in the physiological range of interest (below 50 Hz). The effect of stimulation on MEG critically depends on whether it is done in bipolar (between two contacts on the lead) or monopolar (between a lead contact and the stimulator case) mode. Monopolar DBS creates severe interference in the MEG as previously reported. However, we found that the OPM system is more resilient to this interference and could provide artefact-free measurements, at least for limited frequency ranges. A resting measurement in the MEGIN system from a Parkinson’s patient implanted with Percept PC and subthalamic SenSight leads revealed artefact patterns consistent with our phantom recordings. Moreover, analysis of LFP-MEG coherence in this patient showed oscillatory coherent networks consistent in their frequency and topography with those described in published group studies done with externalised leads. In conclusion, Percept PC telemetric streaming with SenSight leads is compatible with MEG. Furthermore, OPM sensors could provide additional new opportunities for studying DBS effects.

Type: Article
Title: Combining magnetoencephalography with telemetric streaming of intracranial recordings and deep brain stimulation—A feasibility study
Open access status: An open access version is available from UCL Discovery
DOI: 10.1162/imag_a_00029
Publisher version: http://dx.doi.org/10.1162/imag_a_00029
Language: English
Additional information: Copyright © 2023 Massachusetts Institute of Technology. Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. For a full description of the license, please visit https://creativecommons.org/licenses/by/4.0/legalcode.
Keywords: Coherence, oscillations, STN, human, neuromodulation
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
URI: https://discovery.ucl.ac.uk/id/eprint/10185726
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