{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T06:34:28Z","timestamp":1793860468625,"version":"4.6.1"},"reference-count":89,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2023,3,15]],"date-time":"2023-03-15T00:00:00Z","timestamp":1678838400000},"content-version":"vor","delay-in-days":6,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"Agency for Medical Research and Development","award":["JP18dm0307001"],"award-info":[{"award-number":["JP18dm0307001"]}]},{"name":"Agency for Medical Research and Development","award":["JP18dm0307004"],"award-info":[{"award-number":["JP18dm0307004"]}]},{"name":"Agency for Medical Research and Development","award":["JP19dm0207069"],"award-info":[{"award-number":["JP19dm0207069"]}]},{"name":"Agency for Medical Research and Development","award":["JPMJMS2021"],"award-info":[{"award-number":["JPMJMS2021"]}]},{"name":"Agency for Medical Research and Development","award":["JP18K15491"],"award-info":[{"award-number":["JP18K15491"]}]},{"name":"Agency for Medical Research and Development","award":["JP20KK0193"],"award-info":[{"award-number":["JP20KK0193"]}]},{"name":"Agency for Medical Research and Development","award":["JP21H02851"],"award-info":[{"award-number":["JP21H02851"]}]},{"name":"Agency for Medical Research and Development","award":["JP21H05324"],"award-info":[{"award-number":["JP21H05324"]}]},{"name":"xsInternational Research Center for Neurointelligence","id":[{"id":"https:\/\/ror.org\/05t86na81","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,7,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background and Hypothesis<\/jats:title>\n                    <jats:p>Dynamics of the distributed sets of functionally synchronized brain regions, known as large-scale networks, are essential for the emotional state and cognitive processes. However, few studies were performed to elucidate the aberrant dynamics across the large-scale networks across multiple psychiatric disorders. In this paper, we aimed to investigate dynamic aspects of the aberrancy of the causal connections among the large-scale networks of the multiple psychiatric disorders.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Study Design<\/jats:title>\n                    <jats:p>We applied dynamic causal modeling (DCM) to the large-sample multi-site dataset with 739 participants from 4 imaging sites including 4 different groups, healthy controls, schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BD), to compare the causal relationships among the large-scale networks, including visual network, somatomotor network (SMN), dorsal attention network (DAN), salience network (SAN), limbic network (LIN), frontoparietal network, and default mode network.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Study Results<\/jats:title>\n                    <jats:p>DCM showed that the decreased self-inhibitory connection of LIN was the common aberrant connection pattern across psychiatry disorders. Furthermore, increased causal connections from LIN to multiple networks, aberrant self-inhibitory connections of DAN and SMN, and increased self-inhibitory connection of SAN were disorder-specific patterns for SCZ, MDD, and BD, respectively.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>DCM revealed that LIN was the core abnormal network common to psychiatric disorders. Furthermore, DCM showed disorder-specific abnormal patterns of causal connections across the 7 networks. Our findings suggested that aberrant dynamics among the large-scale networks could be a key biomarker for these transdiagnostic psychiatric disorders.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/schbul\/sbad022","type":"journal-article","created":{"date-parts":[[2023,2,18]],"date-time":"2023-02-18T14:39:51Z","timestamp":1676731191000},"page":"933-943","source":"Crossref","is-referenced-by-count":47,"title":["Aberrant Large-Scale Network Interactions Across Psychiatric Disorders Revealed by Large-Sample Multi-Site Resting-State Functional Magnetic Resonance Imaging Datasets"],"prefix":"10.1093","volume":"49","author":[{"given":"Takuya","family":"Ishida","sequence":"first","affiliation":[{"name":"Center for Evolutionary Cognitive Sciences, Graduate School of Art and Sciences, The University of Tokyo , Tokyo , Japan"},{"name":"Department of Neuropsychiatry, Graduate School of Wakayama Medical University , Wakayama , 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