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The current mental health categorization is based primarily on symptoms and clinical course and is not biologically validated. Among multiple ongoing efforts, neurological observations alongside clinical evaluations are considered to be potential solutions to address diagnostic problems. The Bipolar\u2010Schizophrenia Network on Intermediate Phenotypes (B\u2010SNIP) has published multiple papers attempting to reclassify psychotic illnesses based on biological rather than symptomatic measures. However, the effort to investigate the relationship between this new categorization approach and other neuroimaging techniques, including resting\u2010state fMRI data, is still limited. This study focused on investigating the relationship between different psychotic disorders categorization methods and resting\u2010state fMRI\u2010based measures called dynamic functional network connectivity (dFNC) using state\u2010of\u2010the\u2010art artificial intelligence (AI) approaches. We applied our method to 613 subjects, including individuals with psychosis and healthy controls, which were classified using both the Diagnostic and Statistical Manual of Mental Disorders (DSM\u2010IV) and the B\u2010SNIP biomarker\u2010based (Biotype) approach. Statistical group differences and cross\u2010validated classifiers were performed within each framework to assess how different categories. Results highlight interesting differences in occupancy in both DSM\u2010IV and Biotype categorizations compared to healthy individuals, which are distributed across specific transient connectivity states. Biotypes tended to show less distinctiveness in occupancy level and included fewer cellwise differences. Classification accuracy obtained by DSM\u2010IV and Biotype categories were both well above chance. Results provided new insights and highlighted the benefits of both DSM\u2010IV and biology\u2010based categories while also emphasizing the importance of future work in this direction, including employing further data types.<\/jats:p>","DOI":"10.1002\/hbm.26273","type":"journal-article","created":{"date-parts":[[2023,3,15]],"date-time":"2023-03-15T09:29:43Z","timestamp":1678872583000},"page":"3180-3195","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Evaluation of boundaries between mood and psychosis disorder using dynamic functional network connectivity (<scp>dFNC<\/scp>) via deep learning classification"],"prefix":"10.1002","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2650-0156","authenticated-orcid":false,"given":"Hooman","family":"Rokham","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering Georgia Institute of Technology  Atlanta Georgia USA"},{"name":"Tri\u2010institutional Center of Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, and Emory University Georgia State University  Atlanta Georgia USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haleh","family":"Falakshahi","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering Georgia Institute of Technology  Atlanta Georgia USA"},{"name":"Tri\u2010institutional Center of Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, and Emory University Georgia State University  Atlanta Georgia USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zening","family":"Fu","sequence":"additional","affiliation":[{"name":"Tri\u2010institutional Center of Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, and Emory University Georgia State University  Atlanta Georgia USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Godfrey","family":"Pearlson","sequence":"additional","affiliation":[{"name":"Department of Psychiatry Yale University  New Haven Connecticut USA"},{"name":"Department of Neuroscience Yale University  New Haven Connecticut USA"},{"name":"Olin Neuropsychiatry Research Center Hartford Hospital  Hartford Connecticut USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vince D.","family":"Calhoun","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering Georgia Institute of Technology  Atlanta Georgia USA"},{"name":"Tri\u2010institutional Center of Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, and Emory University Georgia State University  Atlanta Georgia USA"},{"name":"Department of Psychiatry Yale University  New Haven Connecticut USA"},{"name":"Department of Computer Science Georgia State University  Atlanta Georgia USA"},{"name":"Department of Psychology Georgia State University  Atlanta Georgia USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2023,3,15]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-20655-6"},{"key":"e_1_2_9_3_1","doi-asserted-by":"crossref","unstructured":"Abrol A. 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