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Our study involved two large multi-center datasets, comprising 2424 patients with MDD and 2183 healthy controls. In patients, individualized ALFF abnormalities were derived through normative modeling and further deconstructed into differential factors using non-negative matrix factorization.<\/jats:p><\/jats:sec><jats:sec id=\"S0033291724002617_sec_a3\" sec-type=\"results\"><jats:title>Results<\/jats:title><jats:p>Two positive and two negative factors were identified. These factors were closely linked to clinical characteristics and explained group-level ALFF abnormalities in the two datasets. Moreover, these factors exhibited distinct associations with the distribution of neurotransmitter receptors\/transporters, transcriptional profiles of inflammation-related genes, and connectome-informed epicenters, underscoring their neurobiological relevance. Additionally, factor compositions facilitated the identification of four distinct depressive subtypes, each characterized by unique abnormal ALFF patterns and clinical features. Importantly, these findings were successfully replicated in another dataset with different acquisition equipment, protocols, preprocessing strategies, and medication statuses, validating their robustness and generalizability.<\/jats:p><\/jats:sec><jats:sec id=\"S0033291724002617_sec_a4\" sec-type=\"conclusions\"><jats:title>Conclusions<\/jats:title><jats:p>This research identifies shared differential factors underlying individual spontaneous neural activity abnormalities in MDD and contributes novel insights into the heterogeneity of spontaneous neural activity abnormalities in MDD.<\/jats:p><\/jats:sec>","DOI":"10.1017\/s0033291724002617","type":"journal-article","created":{"date-parts":[[2024,11,26]],"date-time":"2024-11-26T10:05:00Z","timestamp":1732615500000},"page":"4316-4334","update-policy":"https:\/\/doi.org\/10.1017\/policypage","source":"Crossref","is-referenced-by-count":3,"title":["Shared differential factors underlying individual spontaneous neural activity abnormalities 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