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Brickwedde M, Anders P, Kühn AA, Lofredi R, Holtkamp M, Kaindl AM, Grent-'t-Jong T, Krüger P, Sander T, Uhlhaas PJ. Applications of OPM-MEG for translational neuroscience: a perspective. Transl Psychiatry 2024; 14:341. [PMID: 39181883 PMCID: PMC11344782 DOI: 10.1038/s41398-024-03047-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 06/25/2024] [Accepted: 08/01/2024] [Indexed: 08/27/2024] Open
Abstract
Magnetoencephalography (MEG) allows the non-invasive measurement of brain activity at millisecond precision combined with localization of the underlying generators. So far, MEG-systems consisted of superconducting quantum interference devices (SQUIDS), which suffer from several limitations. Recent technological advances, however, have enabled the development of novel MEG-systems based on optically pumped magnetometers (OPMs), offering several advantages over conventional SQUID-MEG systems. Considering potential improvements in the measurement of neuronal signals as well as reduced operating costs, the application of OPM-MEG systems for clinical neuroscience and diagnostic settings is highly promising. Here we provide an overview of the current state-of-the art of OPM-MEG and its unique potential for translational neuroscience. First, we discuss the technological features of OPMs and benchmark OPM-MEG against SQUID-MEG and electroencephalography (EEG), followed by a summary of pioneering studies of OPMs in healthy populations. Key applications of OPM-MEG for the investigation of psychiatric and neurological conditions are then reviewed. Specifically, we suggest novel applications of OPM-MEG for the identification of biomarkers and circuit deficits in schizophrenia, dementias, movement disorders, epilepsy, and neurodevelopmental syndromes (autism spectrum disorder and attention deficit hyperactivity disorder). Finally, we give an outlook of OPM-MEG for translational neuroscience with a focus on remaining methodological and technical challenges.
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Affiliation(s)
- Marion Brickwedde
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Department of Child and Adolescent Psychiatry, 13353, Berlin, Germany.
- Physikalisch-Technische Bundesanstalt, Berlin, Germany.
| | - Paul Anders
- Physikalisch-Technische Bundesanstalt, Berlin, Germany
| | - Andrea A Kühn
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Sektion für Bewegungsstörungen und Neuromodulation, Klinik für Neurologie und Experimentelle Neurologie, 10117, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Humboldt-Universität, Berlin, Germany
- NeuroCure, Exzellenzcluster, Charité-Universitätsmedizin Berlin, Berlin, Germany
- DZNE, German center for neurodegenerative diseases, Berlin, Germany
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Roxanne Lofredi
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Sektion für Bewegungsstörungen und Neuromodulation, Klinik für Neurologie und Experimentelle Neurologie, 10117, Berlin, Germany
- Berlin Institute of Health, Berlin, Germany
| | - Martin Holtkamp
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Department of Neurology, Epilepsy-Center Berlin-Brandenburg, 10117, Berlin, Germany
| | - Angela M Kaindl
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Department of Pediatric Neurology, 13353, Berlin, Germany
- Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Center for Chronically Sick Children, 13353, Berlin, Germany
- Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Institute of Cell Biology and Neurobiology, 10117, Berlin, Germany
| | - Tineke Grent-'t-Jong
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Department of Child and Adolescent Psychiatry, 13353, Berlin, Germany
- Institute for Neuroscience and Psychology, Glasgow University, Scotland, United Kingdom
| | - Peter Krüger
- Physikalisch-Technische Bundesanstalt, Berlin, Germany
| | | | - Peter J Uhlhaas
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Department of Child and Adolescent Psychiatry, 13353, Berlin, Germany
- Institute for Neuroscience and Psychology, Glasgow University, Scotland, United Kingdom
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Mellor S, Timms RC, O'Neill GC, Tierney TM, Spedden ME, Brookes MJ, Wagstyl K, Barnes GR. Combining OPM and lesion mapping data for epilepsy surgery planning: a simulation study. Sci Rep 2024; 14:2882. [PMID: 38311614 PMCID: PMC10838931 DOI: 10.1038/s41598-024-51857-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 01/10/2024] [Indexed: 02/06/2024] Open
Abstract
When planning for epilepsy surgery, multiple potential sites for resection may be identified through anatomical imaging. Magnetoencephalography (MEG) using optically pumped sensors (OP-MEG) is a non-invasive functional neuroimaging technique which could be used to help identify the epileptogenic zone from these candidate regions. Here we test the utility of a-priori information from anatomical imaging for differentiating potential lesion sites with OP-MEG. We investigate a number of scenarios: whether to use rigid or flexible sensor arrays, with or without a-priori source information and with or without source modelling errors. We simulated OP-MEG recordings for 1309 potential lesion sites identified from anatomical images in the Multi-centre Epilepsy Lesion Detection (MELD) project. To localise the simulated data, we used three source inversion schemes: unconstrained, prior source locations at centre of the candidate sites, and prior source locations within a volume around the lesion location. We found that prior knowledge of the candidate lesion zones made the inversion robust to errors in sensor gain, orientation and even location. When the reconstruction was too highly restricted and the source assumptions were inaccurate, the utility of this a-priori information was undermined. Overall, we found that constraining the reconstruction to the region including and around the participant's potential lesion sites provided the best compromise of robustness against modelling or measurement error.
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Affiliation(s)
- Stephanie Mellor
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK.
| | - Ryan C Timms
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - George C O'Neill
- Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Tim M Tierney
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - Meaghan E Spedden
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Konrad Wagstyl
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
- UCL Great Ormond Street Institute for Child Health, University College London, 30 Guilford St, London, WC1N 1EH, UK
| | - Gareth R Barnes
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
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