{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,4]],"date-time":"2026-11-04T18:08:30Z","timestamp":1793815710210,"version":"4.6.1"},"reference-count":99,"publisher":"Cambridge University Press (CUP)","issue":"13","license":[{"start":{"date-parts":[[2022,11,4]],"date-time":"2022-11-04T00:00:00Z","timestamp":1667520000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["cambridge.org"],"crossmark-restriction":true},"short-container-title":["Psychol. Med."],"published-print":{"date-parts":[[2023,10]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec id=\"S0033291722003439_sec_a1\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Although aberrant brain regional responses are reported in social anxiety disorder (SAD), little is known about resting-state functional connectivity at the macroscale network level. This study aims to identify functional network abnormalities using a multivariate data-driven method in a relatively large and homogenous sample of SAD patients, and assess their potential diagnostic value.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"S0033291722003439_sec_a2\" sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Forty-six SAD patients and 52 demographically-matched healthy controls (HC) were recruited to undergo clinical evaluation and resting-state functional MRI scanning. We used group independent component analysis to characterize the functional architecture of brain resting-state networks (RSNs) and investigate between-group differences in intra-\/inter-network functional network connectivity (FNC). Furtherly, we explored the associations of FNC abnormalities with clinical characteristics, and assessed their ability to discriminate SAD from HC using support vector machine analyses.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"S0033291722003439_sec_a3\" sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      SAD patients showed widespread intra-network FNC abnormalities in the default mode network, the subcortical network and the perceptual system (i.e. sensorimotor, auditory and visual networks), and large-scale inter-network FNC abnormalities among those high-order and primary RSNs. Some aberrant FNC signatures were correlated to disease severity and duration, suggesting pathophysiological relevance. Furthermore, intrinsic FNC anomalies allowed individual classification of SAD\n                      <jats:italic>v.<\/jats:italic>\n                      HC with significant accuracy, indicating potential diagnostic efficacy.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"S0033291722003439_sec_a4\" sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>SAD patients show distinct patterns of functional synchronization abnormalities both within and across large-scale RSNs, reflecting or causing a network imbalance of bottom-up response and top-down regulation in cognitive, emotional and sensory domains. Therefore, this could offer insights into the neurofunctional substrates of SAD.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1017\/s0033291722003439","type":"journal-article","created":{"date-parts":[[2022,11,4]],"date-time":"2022-11-04T05:20:07Z","timestamp":1667539207000},"page":"6194-6204","update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":45,"title":["Large-scale brain functional network abnormalities in social anxiety 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The Author(s), 2022. 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