{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:49:45Z","timestamp":1760237385924,"version":"build-2065373602"},"reference-count":42,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2020,5,9]],"date-time":"2020-05-09T00:00:00Z","timestamp":1588982400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100011676","name":"Elekta","doi-asserted-by":"publisher","award":["MEGACLIN"],"award-info":[{"award-number":["MEGACLIN"]}],"id":[{"id":"10.13039\/100011676","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007357","name":"Fondation Nanosciences","doi-asserted-by":"publisher","award":["ICOBI-CE"],"award-info":[{"award-number":["ICOBI-CE"]}],"id":[{"id":"10.13039\/100007357","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003136","name":"Edmond J. Safra Philanthropic Foundation","doi-asserted-by":"publisher","award":["unrestricted grant"],"award-info":[{"award-number":["unrestricted grant"]}],"id":[{"id":"10.13039\/501100003136","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Brain source imaging and time frequency mapping (TFM) are commonly used in magneto\/electro encephalography (M\/EEG) imaging. However, these methods suffer from important limitations. Source imaging is based on an ill-posed inverse problem leading to instability of source localization solutions, has a limited capacity to localize high frequency oscillations and loses its robustness for induced responses (ill-defined trigger). The drawback of TFM is that it involves independent analysis of signals from a number of frequency bands, and from co-localized sensors. In the present article, a regression-based multi-sensor space\u2013time\u2013frequency analysis (MSA) approach, which integrates co-localized sensors and\/or multi-frequency information, is proposed. To estimate task-specific brain activations, MSA uses cross-validated, shifted, multiple Pearson correlation, calculated from the time\u2013frequency transformed brain signal and the binary signal of stimuli. The results are projected from the sensor space onto the cortical surface. To assess MSA performance, the proposed method was compared to the weighted minimum norm estimate (wMNE) source imaging method, in terms of spatial selectivity and robustness against an ill-defined trigger. Magnetoencephalography (MEG) recordings were performed in fourteen subjects during two motor tasks: finger tapping and elbow flexion\/extension. In particular, our results show that the MSA approach provides good localization performance when compared to wMNE and statistically significant improvement of robustness against ill-defined trigger.<\/jats:p>","DOI":"10.3390\/s20092706","type":"journal-article","created":{"date-parts":[[2020,5,11]],"date-time":"2020-05-11T12:26:30Z","timestamp":1589199990000},"page":"2706","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Space\u2013Time\u2013Frequency Multi-Sensor Analysis for Motor Cortex Localization Using Magnetoencephalography"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6385-3233","authenticated-orcid":false,"given":"Vincent","family":"Auboiroux","sequence":"first","affiliation":[{"name":"Univ. Grenoble Alpes, CEA, LETI, CLINATEC, MINATEC Campus, F-38000 Grenoble, France"}]},{"given":"Christelle","family":"Larzabal","sequence":"additional","affiliation":[{"name":"Univ. Grenoble Alpes, CEA, LETI, CLINATEC, MINATEC Campus, F-38000 Grenoble, France"}]},{"given":"Lilia","family":"Langar","sequence":"additional","affiliation":[{"name":"CHU Grenoble Alpes, CLINATEC, F-38000 Grenoble, France"}]},{"given":"Victor","family":"Rohu","sequence":"additional","affiliation":[{"name":"Univ. Grenoble Alpes, CEA, LETI, CLINATEC, MINATEC Campus, F-38000 Grenoble, France"}]},{"given":"Ales","family":"Mishchenko","sequence":"additional","affiliation":[{"name":"Univ. Grenoble Alpes, CEA, LETI, CLINATEC, MINATEC Campus, F-38000 Grenoble, France"}]},{"given":"Nana","family":"Arizumi","sequence":"additional","affiliation":[{"name":"Univ. Grenoble Alpes, CEA, LETI, CLINATEC, MINATEC Campus, F-38000 Grenoble, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8680-7213","authenticated-orcid":false,"given":"Etienne","family":"Labyt","sequence":"additional","affiliation":[{"name":"Univ. Grenoble Alpes, CEA, LETI, CLINATEC, MINATEC Campus, F-38000 Grenoble, France"}]},{"given":"Alim-Louis","family":"Benabid","sequence":"additional","affiliation":[{"name":"Univ. Grenoble Alpes, CEA, LETI, CLINATEC, MINATEC Campus, F-38000 Grenoble, France"}]},{"given":"Tetiana","family":"Aksenova","sequence":"additional","affiliation":[{"name":"Univ. Grenoble Alpes, CEA, LETI, CLINATEC, MINATEC Campus, F-38000 Grenoble, France"}]}],"member":"1968","published-online":{"date-parts":[[2020,5,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1038\/nn.4504","article-title":"Magnetoencephalography for brain electrophysiology and imaging","volume":"20","author":"Baillet","year":"2017","journal-title":"Nat. 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