Frequency-Specific Resting Connectome in Bipolar Disorder

An MEG Study

Bibliographic Data

ID15516568
AuthorsMasakazu Sunaga (0000-0002-2823-1324, Gunma University), Yuichi Takei (0000-0002-8080-3043, Gunma University, corresponding author), Yutaka Kato (0000-0001-7622-5001, Gunma University), Minami Tagawa (Gunma University), Tomohiro Suto, Naruhito Hironaga (Kyushu University), Takefumi Ohki (0000-0002-6850-047X, The University of Osaka), Yumiko Takahashi (0000-0002-4762-0982, Gunma University), Kazuyuki Fujihara (0000-0002-0596-6678, Gunma University), Noriko Sakurai (Gunma University), Koichi Ujita (Gunma University), Yoshito Tsushima (0000-0002-6889-1570, Gunma University), Masato Fukuda (Gunma University)
Year2020
Volume11
Pages597-597
Publication date2020-06-24
Open AccessYes
TypeARTICLE
VenueFrontiers in Psychiatry (JOURNAL)
Journal identifiersISSN: 1664-0640 • E-ISSN: 1664-0640
PublisherFrontiers Media (PUBLISHER • CH)
DOI10.3389/fpsyt.2020.00597
PMID32670117
OpenAlexW3037591192
LanguageEN
Citations received1
References cited69

We introduced graph theory into resting-state MEG studies to investigate the functional connectivity in patients with BD. To the best of our knowledge, this is a novel approach that may be beneficial in the diagnosis of BD. This study describes the spontaneous oscillatory brain networks that compensate for the time-domain issues associated with functional magnetic resonance imaging. These findings suggest that the connectivity of the LM at the beta band may be a good objective biological biomarker of the depressive symptoms associated with BD

Bipolar disorder · Connectome · Functional connectivity · Mood · Psychiatry · Resting state fMRI · Advanced MRI Techniques and Applications · Bipolar Disorder and Treatment · Functional Brain Connectivity Studies · Medicine · Neuroscience · Psychology

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