{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T05:11:39Z","timestamp":1788844299838,"version":"build-2803163510"},"reference-count":80,"publisher":"IOP Publishing","issue":"5","license":[{"start":{"date-parts":[[2024,2,22]],"date-time":"2024-02-22T00:00:00Z","timestamp":1708560000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2024,2,22]],"date-time":"2024-02-22T00:00:00Z","timestamp":1708560000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/iopscience.iop.org\/info\/page\/text-and-data-mining"}],"funder":[{"name":"JSPS","award":["KAKENHI 21H04956"],"award-info":[{"award-number":["KAKENHI 21H04956"]}]}],"content-domain":{"domain":["iopscience.iop.org"],"crossmark-restriction":false},"short-container-title":["Phys. Med. Biol."],"published-print":{"date-parts":[[2024,3,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    <jats:italic>Objective<\/jats:italic>\n                    . Electroencephalograms (EEGs) are often used to monitor brain activity. Several source localization methods have been proposed to estimate the location of brain activity corresponding to EEG readings. However, only a few studies evaluated source localization accuracy from measured EEG using personalized head models in a millimeter resolution. In this study, based on a volume conductor analysis of a high-resolution personalized human head model constructed from magnetic resonance images, a finite difference method was used to solve the forward problem and to reconstruct the field distribution.\n                    <jats:italic>Approach<\/jats:italic>\n                    . We used a personalized segmentation-free head model developed using machine learning techniques, in which the abrupt change of electrical conductivity occurred at the tissue interface is suppressed. Using this model, a smooth field distribution was obtained to address the forward problem. Next, multi-dipole fitting was conducted using EEG measurements for each subject (\n                    <jats:italic>N<\/jats:italic>\n                    = 10 male subjects, age: 22.5 \u00b1 0.5), and the source location and electric field distribution were estimated.\n                    <jats:italic>Main results.<\/jats:italic>\n                    For measured somatosensory evoked potential for electrostimulation to the wrist, a multi-dipole model with lead field matrix computed with the volume conductor model was found to be superior than a single dipole model when using personalized segmentation-free models (6\/10). The correlation coefficient between measured and estimated scalp potentials was 0.89 for segmentation-free head models and 0.71 for conventional segmented models. The proposed method is straightforward model development and comparable localization difference of the maximum electric field from the target wrist reported using fMR (i.e. 16.4 \u00b1 5.2 mm) in previous study. For comparison, DUNEuro based on sLORETA was (EEG: 17.0 \u00b1 4.0 mm). In addition, somatosensory evoked magnetic fields obtained by Magnetoencephalography was 25.3 \u00b1 8.5 mm using three-layer sphere and sLORETA.\n                    <jats:italic>Significance<\/jats:italic>\n                    . For measured EEG signals, our procedures using personalized head models demonstrated that effective localization of the somatosensory cortex, which is located in a non-shallower cortex region. This method may be potentially applied for imaging brain activity located in other non-shallow regions.\n                  <\/jats:p>","DOI":"10.1088\/1361-6560\/ad25c3","type":"journal-article","created":{"date-parts":[[2024,2,2]],"date-time":"2024-02-02T18:04:50Z","timestamp":1706897090000},"page":"055013","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":19,"title":["High-resolution EEG source localization in personalized segmentation-free head model with multi-dipole fitting"],"prefix":"10.1088","volume":"69","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8336-1140","authenticated-orcid":true,"given":"Akimasa","family":"Hirata","sequence":"first","affiliation":[{"name":"Nagoya Institute of Technology"},{"name":"Nagoya Institute of Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Masamune","family":"Niitsu","sequence":"additional","affiliation":[{"name":"Nagoya Institute of Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chun Ren","family":"Phang","sequence":"additional","affiliation":[{"name":"Nagoya Institute of Technology"},{"name":"Nagoya Institute of Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6595-0742","authenticated-orcid":true,"given":"Sachiko","family":"Kodera","sequence":"additional","affiliation":[{"name":"Nagoya Institute of Technology"},{"name":"Nagoya Institute of Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tetsuo","family":"Kida","sequence":"additional","affiliation":[{"name":"Department of Functioning and Disability, Institute for Developmental Research, Aichi Developmental Disability Center, Kasugai 480-0392,"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6571-9807","authenticated-orcid":true,"given":"Essam A","family":"Rashed","sequence":"additional","affiliation":[{"name":"University of Hyogo"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Masaki","family":"Fukunaga","sequence":"additional","affiliation":[{"name":"National Institute for Physiological Sciences"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Norihiro","family":"Sadato","sequence":"additional","affiliation":[{"name":"National Institute for Physiological Sciences"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Toshiaki","family":"Wasaka","sequence":"additional","affiliation":[{"name":"Nagoya Institute of Technology"},{"name":"Nagoya Institute of Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2024,2,22]]},"reference":[{"key":"pmbad25c3bib1","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/j.knosys.2015.08.004","type":"journal-article","article-title":"Application of entropies for automated diagnosis of epilepsy using EEG signals: a review","volume":"88","author":"Acharya","year":"2015","journal-title":"Knowl.-Based Syst."},{"key":"pmbad25c3bib2","doi-asserted-by":"crossref","first-page":"2465","DOI":"10.1093\/brain\/114.6.2465","type":"journal-article","article-title":"Potentials evoked in human and monkey cerebral cortex by stimulation of the median nerve: a review of scalp and intracranial recordings","volume":"114","author":"Allison","year":"1991","journal-title":"Brain"},{"key":"pmbad25c3bib3","doi-asserted-by":"publisher","first-page":"711","DOI":"10.1152\/jn.1989.62.3.711","type":"journal-article","article-title":"Human cortical potentials evoked by stimulation of the median nerve: II. 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