{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T19:20:47Z","timestamp":1792783247483,"version":"4.5.0"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61471263 61872267"],"award-info":[{"award-number":["61471263 61872267"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006606","name":"Natural Science Foundation of Tianjin Municipality","doi-asserted-by":"publisher","award":["x 16JCZDJC31100"],"award-info":[{"award-number":["x 16JCZDJC31100"]}],"id":[{"id":"10.13039\/501100006606","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Tianjin University Innovation Foundation","award":["x 2021XZC-0024"],"award-info":[{"award-number":["x 2021XZC-0024"]}],"id":[{"id":"https:\/\/ror.org\/012tb2g32","id-type":"ROR","asserted-by":"crossref"}]},{"name":"Foundation of State Key Laboratory of Ultrasound in Medicine and Engineering","award":["2022KFKT004"],"award-info":[{"award-number":["2022KFKT004"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Brain Imaging and Behavior"],"DOI":"10.1007\/s11682-026-01202-1","type":"journal-article","created":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T06:59:20Z","timestamp":1790837960000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["From voxels to models: a multi-center voxel-based morphometry study identifying robust biomarkers for deep learning classification of schizophrenia"],"prefix":"10.1007","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0374-5847","authenticated-orcid":false,"given":"Mohammed Jajere","family":"Adamu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Qiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Charles Okanda","family":"Nyatega","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,10,1]]},"reference":[{"key":"1202_CR1","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2023.1188603","volume":"14","author":"MJ Adamu","year":"2023","unstructured":"Adamu, M. J., Qiang, L., Nyatega, C. O., Younis, A., Kawuwa, H. B., Jabire, A. H., & Saminu, S. (2023). Unraveling the pathophysiology of schizophrenia: Insights from structural magnetic resonance imaging studies. Frontiers in Psychiatry, 14, Article 1188603. https:\/\/doi.org\/10.3389\/fpsyt.2023.1188603","journal-title":"Frontiers in Psychiatry"},{"issue":"1","key":"1202_CR2","doi-asserted-by":"publisher","DOI":"10.1007\/s10571-025-01660-z","volume":"46","author":"MJ Adamu","year":"2026","unstructured":"Adamu, M. J., Qiang, L., Nyatega, C. O., Fahad, M., Younis, A., Jabire, A. H., Zakariyya, R. S., & Kawuwa, H. B. (2026). Explainable hybrid deep learning framework integrating MobileNetV2, EfficientNetV2B0, and KNN for MRI-based brain tumor classification. Cellular and Molecular Neurobiology, 46(1), Article 40. https:\/\/doi.org\/10.1007\/s10571-025-01660-z","journal-title":"Cellular and Molecular Neurobiology"},{"key":"1202_CR3","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1016\/j.neuroimage.2016.02.079","volume":"145","author":"MR Arbabshirani","year":"2017","unstructured":"Arbabshirani, M. R., Plis, S., Sui, J., & Calhoun, V. D. (2017). Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls. NeuroImage, 145, 137\u2013165. https:\/\/doi.org\/10.1016\/j.neuroimage.2016.02.079","journal-title":"NeuroImage"},{"issue":"1","key":"1202_CR4","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1016\/j.neuroimage.2007.07.007","volume":"38","author":"J Ashburner","year":"2007","unstructured":"Ashburner, J. (2007). A fast diffeomorphic image registration algorithm. Neuroimage, 38(1), 95\u2013113. https:\/\/doi.org\/10.1016\/j.neuroimage.2007.07.007","journal-title":"Neuroimage"},{"issue":"12","key":"1202_CR5","doi-asserted-by":"publisher","first-page":"727","DOI":"10.1038\/nrn.2017.125","volume":"18","author":"R Birnbaum","year":"2017","unstructured":"Birnbaum, R., & Weinberger, D. R. (2017). Genetic insights into the neurodevelopmental origins of schizophrenia. Nature Reviews Neuroscience, 18(12), 727\u2013740. https:\/\/doi.org\/10.1038\/nrn.2017.125","journal-title":"Nature Reviews Neuroscience"},{"issue":"7810","key":"1202_CR6","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1038\/s41586-020-2314-9","volume":"582","author":"R Botvinik-Nezer","year":"2020","unstructured":"Botvinik-Nezer, R., Holzmeister, F., Camerer, C. F., Dreber, A., Huber, J., Johannesson, M., Kirchler, M., Iwanir, R., Mumford, J. A., Adcock, R. A., Avesani, P., Baczkowski, B. M., Bajracharya, A., Bakst, L., Ball, S., Barilari, M., Bault, N., Beaton, D., Beitner, J., \u2026 Schonberg, T. (2020). Variability in the analysis of a single neuroimaging dataset by many teams. Nature, 582(7810), 84\u201388. https:\/\/doi.org\/10.1038\/s41586-020-2314-9","journal-title":"Nature"},{"key":"1202_CR7","doi-asserted-by":"publisher","unstructured":"Brisch, R., Saniotis, A., Wolf, R., Bielau, H., Bernstein, H. G., Steiner, J., Bogerts, B., Braun, A. K., Jankowski, Z., Kumaritlake, J., Henneberg, M., & Gos, T. (2014). The Role of Dopamine in Schizophrenia from a Neurobiological and Evolutionary Perspective: Old Fashioned, but Still in Vogue. Frontiers in Psychiatry, 5,. https:\/\/doi.org\/10.3389\/fpsyt.2014.00047","DOI":"10.3389\/fpsyt.2014.00047"},{"issue":"3","key":"1202_CR9","doi-asserted-by":"publisher","first-page":"230","DOI":"10.1016\/j.bpsc.2015.12.005","volume":"1","author":"VD Calhoun","year":"2016","unstructured":"Calhoun, V. D., & Sui, J. (2016). Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 1(3), 230\u2013244. https:\/\/doi.org\/10.1016\/j.bpsc.2015.12.005","journal-title":"Biological Psychiatry: Cognitive Neuroscience and Neuroimaging"},{"key":"1202_CR10","unstructured":"COBRE. (nd). Retrieved June 21 (2026). from http:\/\/fcon_1000.projects.nitrc.org\/indi\/retro\/cobre.html"},{"key":"1202_CR8","unstructured":"C, G., Pm, R. D., T., F, K., E, L., & None, T. A. (2024). D. N. I. CAT: A computational anatomy toolbox for the analysis of structural MRI data. PubMed. https:\/\/pubmed.ncbi.nlm.nih.gov\/39102518\/"},{"issue":"1","key":"1202_CR11","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1038\/s41591-018-0316-z","volume":"25","author":"A Esteva","year":"2019","unstructured":"Esteva, A., Robicquet, A., Ramsundar, B., Kuleshov, V., DePristo, M., Chou, K., Cui, C., Corrado, G., Thrun, S., & Dean, J. (2019). A guide to deep learning in healthcare. Nature Medicine, 25(1), 24\u201329. https:\/\/doi.org\/10.1038\/s41591-018-0316-z","journal-title":"Nature Medicine"},{"issue":"8","key":"1202_CR12","doi-asserted-by":"publisher","first-page":"1510","DOI":"10.1038\/s41386-021-01020-7","volume":"46","author":"C Flint","year":"2021","unstructured":"Flint, C., Cearns, M., Opel, N., Redlich, R., Mehler, D. M. A., Emden, D., Winter, N. R., Leenings, R., Eickhoff, S. B., Kircher, T., Krug, A., Nenadic, I., Arolt, V., Clark, S., Baune, B. T., Jiang, X., Dannlowski, U., & Hahn, T. (2021). Systematic misestimation of machine learning performance in neuroimaging studies of depression. Neuropsychopharmacology, 46(8), 1510\u20131517. https:\/\/doi.org\/10.1038\/s41386-021-01020-7","journal-title":"Neuropsychopharmacology"},{"issue":"1\u20133","key":"1202_CR15","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1016\/j.schres.2008.12.011","volume":"108","author":"A Fornito","year":"2009","unstructured":"Fornito, A., Y\u00fccel, M., Patti, J., Wood, S. J., & Pantelis, C. (2009). Mapping grey matter reductions in schizophrenia: An anatomical likelihood estimation analysis of voxel-based morphometry studies. Schizophrenia Research, 108(1\u20133), 104\u2013113. https:\/\/doi.org\/10.1016\/j.schres.2008.12.011","journal-title":"Schizophrenia Research"},{"issue":"2","key":"1202_CR16","doi-asserted-by":"publisher","DOI":"10.1093\/schbul\/sbaf078","volume":"52","author":"M Franz","year":"2026","unstructured":"Franz, M., Kebets, V., Berg, X., Georgiadis, F., Milano, B. A., Burrer, A., Brakowski, J., Kaiser, S., Seifritz, E., Homan, P., Walton, E., Van Erp, T. G. M., Turner, J. A., Misic, B., Valk, S. L., Yeo, B. T. T., Bernhardt, B. C., & Kirschner, M. (2026). Orbitofrontal thickness and network associations as transdiagnostic signature of amotivation along the bipolar-schizophrenia spectrum. Schizophrenia Bulletin, 52(2), Article sbaf078. https:\/\/doi.org\/10.1093\/schbul\/sbaf078","journal-title":"Schizophrenia Bulletin"},{"issue":"9","key":"1202_CR17","doi-asserted-by":"publisher","first-page":"774","DOI":"10.1016\/j.biopsych.2008.03.031","volume":"64","author":"DC Glahn","year":"2008","unstructured":"Glahn, D. C., Laird, A. R., Ellison-Wright, I., Thelen, S. M., Robinson, J. L., Lancaster, J. L., Bullmore, E., & Fox, P. T. (2008). Meta-Analysis of Gray Matter Anomalies in Schizophrenia: Application of Anatomic Likelihood Estimation and Network Analysis. Biological Psychiatry, 64(9), 774\u2013781. https:\/\/doi.org\/10.1016\/j.biopsych.2008.03.031","journal-title":"Biological Psychiatry"},{"issue":"5","key":"1202_CR18","doi-asserted-by":"publisher","first-page":"869","DOI":"10.1038\/s41386-018-0175-9","volume":"44","author":"Q Gong","year":"2019","unstructured":"Gong, Q., Scarpazza, C., Dai, J., He, M., Xu, X., Shi, Y., Zhou, B., Vieira, S., McCrory, E., Ai, Y., Yang, C., Zhang, F., Lui, S., & Mechelli, A. (2019). A transdiagnostic neuroanatomical signature of psychiatric illness. Neuropsychopharmacology, 44(5), 869\u2013875. https:\/\/doi.org\/10.1038\/s41386-018-0175-9","journal-title":"Neuropsychopharmacology"},{"issue":"4","key":"1202_CR19","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1001\/jamapsychiatry.2014.2206","volume":"72","author":"M Goodkind","year":"2015","unstructured":"Goodkind, M., Eickhoff, S. B., Oathes, D. J., Jiang, Y., Chang, A., Jones-Hagata, L. B., Ortega, B. N., Zaiko, Y. V., Roach, E. L., Korgaonkar, M. S., Grieve, S. M., Galatzer-Levy, I., Fox, P. T., & Etkin, A. (2015). Identification of a common neurobiological substrate for mental illness. JAMA Psychiatry, 72(4), 305. https:\/\/doi.org\/10.1001\/jamapsychiatry.2014.2206","journal-title":"JAMA Psychiatry"},{"issue":"1","key":"1202_CR20","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1111\/bdi.12362","volume":"18","author":"LC Hanford","year":"2016","unstructured":"Hanford, L. C., Nazarov, A., Hall, G. B., & Sassi, R. B. (2016). Cortical thickness in bipolar disorder: A systematic review. Bipolar Disorders, 18(1), 4\u201318. https:\/\/doi.org\/10.1111\/bdi.12362","journal-title":"Bipolar Disorders"},{"issue":"4","key":"1202_CR13","doi-asserted-by":"publisher","first-page":"932","DOI":"10.1038\/mp.2017.73","volume":"23","author":"DP Hibar","year":"2018","unstructured":"Hibar, D. P., Westlye, L. T., Doan, N. T., Jahanshad, N., Cheung, J. W., Ching, C. R. K., Versace, A., Bilderbeck, A. C., Uhlmann, A., Mwangi, B., Kr\u00e4mer, B., Overs, B., Hartberg, C. B., Ab\u00e9, C., Dima, D., Grotegerd, D., Sprooten, E., B\u00f8en, E., Jimenez, E., \u2026 Andreassen, O. A. (2018). Cortical abnormalities in bipolar disorder: An MRI analysis of 6503 individuals from the ENIGMA Bipolar Disorder Working Group. Molecular Psychiatry, 23(4), 932\u2013942. https:\/\/doi.org\/10.1038\/mp.2017.73","journal-title":"Molecular Psychiatry"},{"issue":"12","key":"1202_CR21","doi-asserted-by":"publisher","first-page":"2233","DOI":"10.1176\/appi.ajp.162.12.2233","volume":"162","author":"R Honea","year":"2005","unstructured":"Honea, R., Crow, T. J., Passingham, D., & Mackay, C. E. (2005). Regional deficits in brain volume in schizophrenia: A meta-analysis of voxel-based morphometry studies. American Journal of Psychiatry, 162(12), 2233\u20132245. https:\/\/doi.org\/10.1176\/appi.ajp.162.12.2233","journal-title":"American Journal of Psychiatry"},{"issue":"5","key":"1202_CR22","doi-asserted-by":"publisher","first-page":"542","DOI":"10.1016\/j.bpsc.2020.01.010","volume":"5","author":"C-C Huang","year":"2020","unstructured":"Huang, C.-C., Luo, Q., Palaniyappan, L., Yang, A. C., Hung, C.-C., Chou, K.-H., Zac Lo, C.-Y., Liu, M.-N., Tsai, S.-J., Barch, D. M., Feng, J., Lin, C.-P., & Robbins, T. W. (2020). Transdiagnostic and illness-specific functional dysconnectivity across schizophrenia, bipolar disorder, and major depressive disorder. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 5(5), 542\u2013553. https:\/\/doi.org\/10.1016\/j.bpsc.2020.01.010","journal-title":"Biological Psychiatry: Cognitive Neuroscience and Neuroimaging"},{"issue":"4","key":"1202_CR23","doi-asserted-by":"publisher","first-page":"395","DOI":"10.1176\/appi.ajp.2014.14020138","volume":"171","author":"TR Insel","year":"2014","unstructured":"Insel, T. R. (2014). The NIMH research domain criteria (RDoC) project: Precision medicine for psychiatry. American Journal of Psychiatry, 171(4), 395\u2013397. https:\/\/doi.org\/10.1176\/appi.ajp.2014.14020138","journal-title":"American Journal of Psychiatry"},{"issue":"1","key":"1202_CR24","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1176\/appi.ajp.2010.09101522","volume":"168","author":"R Jardri","year":"2011","unstructured":"Jardri, R., Pouchet, A., Pins, D., & Thomas, P. (2011). Cortical Activations During Auditory Verbal Hallucinations in Schizophrenia: A Coordinate-Based Meta-Analysis. American Journal of Psychiatry, 168(1), 73\u201381. https:\/\/doi.org\/10.1176\/appi.ajp.2010.09101522","journal-title":"American Journal of Psychiatry"},{"issue":"10323","key":"1202_CR25","doi-asserted-by":"publisher","first-page":"473","DOI":"10.1016\/S0140-6736(21)01730-X","volume":"399","author":"S Jauhar","year":"2022","unstructured":"Jauhar, S., Johnstone, M., & McKenna, P. J. (2022). Schizophrenia. The Lancet, 399(10323), 473\u2013486. https:\/\/doi.org\/10.1016\/S0140-6736(21)01730-X","journal-title":"The Lancet"},{"key":"1202_CR26","doi-asserted-by":"publisher","first-page":"1074","DOI":"10.1016\/j.neuroimage.2015.09.003","volume":"124","author":"DB Keator","year":"2016","unstructured":"Keator, D. B., Van Erp, T. G. M., Turner, J. A., Glover, G. H., Mueller, B. A., Liu, T. T., Voyvodic, J. T., Rasmussen, J., Calhoun, V. D., Lee, H. J., Toga, A. W., McEwen, S., Ford, J. M., Mathalon, D. H., Diaz, M., O\u2019Leary, D. S., Bockholt, J., Gadde, H., Preda, S., & Potkin, A., S. G (2016). The Function Biomedical Informatics Research Network Data Repository. Neuroimage, 124, 1074\u20131079. https:\/\/doi.org\/10.1016\/j.neuroimage.2015.09.003","journal-title":"Neuroimage"},{"issue":"5","key":"1202_CR27","doi-asserted-by":"publisher","first-page":"1261","DOI":"10.1038\/mp.2017.170","volume":"23","author":"S Kelly","year":"2018","unstructured":"Kelly, S., Jahanshad, N., Zalesky, A., Kochunov, P., Agartz, I., Alloza, C., Andreassen, O. A., Arango, C., Banaj, N., Bouix, S., Bousman, C. A., Brouwer, R. M., Bruggemann, J., Bustillo, J., Cahn, W., Calhoun, V., Cannon, D., Carr, V., Catts, S., \u2026 Donohoe, G. (2018). Widespread white matter microstructural differences in schizophrenia across 4322 individuals: Results from the ENIGMA Schizophrenia DTI working group. Molecular Psychiatry, 23(5), 1261\u20131269. https:\/\/doi.org\/10.1038\/mp.2017.170","journal-title":"Molecular Psychiatry"},{"key":"1202_CR28","doi-asserted-by":"publisher","unstructured":"Lee, P. H., Anttila, V., Won, H., Feng, Y.-C., Rosenthal, J., Zhu, Z., Tucker-Drob, E. M., Nivard, M. G., Grotzinger, A. D., Posthuma, D., Wang, M.-J., Yu, D., Stahl, E. A., Walters, R. K., Anney, R. J. L., Duncan, L. E., Ge, T., Adolfsson, R., Banaschewski, T., \u2026 Smoller, J. W. (2019). Genomic relationships, novel loci, and pleiotropic mechanisms across eight psychiatric disorders. Cell, 179(7), 1469-1482e.e11. https:\/\/doi.org\/10.1016\/j.cell.2019.11.020","DOI":"10.1016\/j.cell.2019.11.020"},{"key":"1202_CR29","unstructured":"MATLAB. (nd). Retrieved June 21 (2026). from https:\/\/de.mathworks.com\/products\/matlab.html"},{"issue":"2","key":"1202_CR30","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1001\/jamapsychiatry.2019.3360","volume":"77","author":"RA McCutcheon","year":"2020","unstructured":"McCutcheon, R. A., Reis Marques, T., & Howes, O. D. (2020). Schizophrenia\u2014an overview. JAMA Psychiatry, 77(2), 201. https:\/\/doi.org\/10.1001\/jamapsychiatry.2019.3360","journal-title":"JAMA Psychiatry"},{"key":"1202_CR31","unstructured":"NITRC: SchizConnect: Large-Scale Schizophrenia Neuroimaging Data Mediation & Federation: Tool\/Resource Info. (nd). Retrieved June 21 (2026). from https:\/\/www.nitrc.org\/projects\/schizconnect\/"},{"key":"1202_CR32","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2022.1054380","volume":"13","author":"C Okanda Nyatega","year":"2022","unstructured":"Okanda Nyatega, C., Qiang, L., Jajere Adamu, M., & Bello Kawuwa, H. (2022). Altered striatal functional connectivity and structural dysconnectivity in individuals with bipolar disorder: A resting state magnetic resonance imaging study. Frontiers in Psychiatry, 13, Article 1054380. https:\/\/doi.org\/10.3389\/fpsyt.2022.1054380","journal-title":"Frontiers in Psychiatry"},{"key":"1202_CR33","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2014.00229","author":"SM Plis","year":"2014","unstructured":"Plis, S. M., Hjelm, D. R., Salakhutdinov, R., Allen, E. A., Bockholt, H. J., Long, J. D., Johnson, H. J., Paulsen, J. S., Turner, J. A., & Calhoun, V. D. (2014). Deep learning for neuroimaging: A validation study. Frontiers in Neuroscience. https:\/\/doi.org\/10.3389\/fnins.2014.00229","journal-title":"Frontiers in Neuroscience"},{"key":"1202_CR34","doi-asserted-by":"publisher","first-page":"116956","DOI":"10.1016\/j.neuroimage.2020.116956","volume":"218","author":"J Radua","year":"2020","unstructured":"Radua, J., Vieta, E., Shinohara, R., Kochunov, P., Quid\u00e9, Y., Green, M. J., Weickert, C. S., Weickert, T., Bruggemann, J., Kircher, T., Nenadi\u0107, I., Cairns, M. J., Seal, M., Schall, U., Henskens, F., Fullerton, J. M., Mowry, B., Pantelis, C., Lenroot, R., & Pineda-Zapata, J. (2020). Increased power by harmonizing structural MRI site differences with the ComBat batch adjustment method in ENIGMA. Neuroimage, 218, 116956. https:\/\/doi.org\/10.1016\/j.neuroimage.2020.116956","journal-title":"Neuroimage"},{"issue":"6","key":"1202_CR14","doi-asserted-by":"publisher","first-page":"900","DOI":"10.1038\/mp.2016.60","volume":"22","author":"L Schmaal","year":"2017","unstructured":"Schmaal, L., Hibar, D. P., S\u00e4mann, P. G., Hall, G. B., Baune, B. T., Jahanshad, N., Cheung, J. W., Van Erp, T. G. M., Bos, D., Ikram, M. A., Vernooij, M. W., Niessen, W. J., Tiemeier, H., Hofman, A., Wittfeld, K., Grabe, H. J., Janowitz, D., B\u00fclow, R., Selonke, M., \u2026 Veltman, D. J. (2017). Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group. Molecular Psychiatry, 22(6), 900\u2013909. https:\/\/doi.org\/10.1038\/mp.2016.60","journal-title":"Molecular Psychiatry"},{"key":"1202_CR35","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2016.00050","author":"HG Schnack","year":"2016","unstructured":"Schnack, H. G., & Kahn, R. S. (2016). Detecting neuroimaging biomarkers for psychiatric disorders: Sample size matters. Frontiers in Psychiatry. https:\/\/doi.org\/10.3389\/fpsyt.2016.00050","journal-title":"Frontiers in Psychiatry"},{"issue":"9","key":"1202_CR36","doi-asserted-by":"publisher","first-page":"775","DOI":"10.1016\/j.biopsych.2012.04.020","volume":"72","author":"AM Shepherd","year":"2012","unstructured":"Shepherd, A. M., Matheson, S. L., Laurens, K. R., Carr, V. J., & Green, M. J. (2012). Systematic Meta-Analysis of Insula Volume in Schizophrenia. Biological Psychiatry, 72(9), 775\u2013784. https:\/\/doi.org\/10.1016\/j.biopsych.2012.04.020","journal-title":"Biological Psychiatry"},{"key":"1202_CR37","unstructured":"SPM - Statistical Parametric Mapping. (nd). Retrieved June 21, (2026). from https:\/\/www.fil.ion.ucl.ac.uk\/spm\/"},{"issue":"9","key":"1202_CR38","doi-asserted-by":"publisher","first-page":"644","DOI":"10.1016\/j.biopsych.2018.04.023","volume":"84","author":"TGM Van Erp","year":"2018","unstructured":"Van Erp, T. G. M., Walton, E., Hibar, D. P., Schmaal, L., Jiang, W., Glahn, D. C., Pearlson, G. D., Yao, N., Fukunaga, M., Hashimoto, R., Okada, N., Yamamori, H., Bustillo, J. R., Clark, V. P., Agartz, I., Mueller, B. A., Cahn, W., De Zwarte, S. M. C., Hulshoff Pol, H. E., \u2026 Orhan, F. (2018). Cortical brain abnormalities in 4474 individuals with schizophrenia and 5098 control subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) Consortium. Biological Psychiatry, 84(9), 644\u2013654. https:\/\/doi.org\/10.1016\/j.biopsych.2018.04.023","journal-title":"Biological Psychiatry"},{"issue":"1","key":"1202_CR39","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1093\/schbul\/sby189","volume":"46","author":"S Vieira","year":"2020","unstructured":"Vieira, S., Gong, Q., Pinaya, W. H. L., Scarpazza, C., Tognin, S., Crespo-Facorro, B., Tordesillas-Gutierrez, D., Ortiz-Garc\u00eda, V., Setien-Suero, E., Scheepers, F. E., Van Haren, N. E. M., Marques, T. R., Murray, R. M., David, A., Dazzan, P., McGuire, P., & Mechelli, A. (2020). Using machine learning and structural neuroimaging to detect first episode psychosis: Reconsidering the evidence. Schizophrenia Bulletin, 46(1), 17\u201326. https:\/\/doi.org\/10.1093\/schbul\/sby189","journal-title":"Schizophrenia Bulletin"},{"issue":"1346","key":"1202_CR40","doi-asserted-by":"publisher","first-page":"1495","DOI":"10.1098\/rstb.1996.0135","volume":"351","author":"DR Weinberger","year":"1996","unstructured":"Weinberger, D. R., & Berman, K. F. (1996). Prefrontal function in schizophrenia: Confounds and controversies. Philosophical Transactions of the Royal Society of London Series B: Biological Sciences, 351(1346), 1495\u20131503. https:\/\/doi.org\/10.1098\/rstb.1996.0135","journal-title":"Philosophical Transactions of the Royal Society of London Series B: Biological Sciences"},{"issue":"4","key":"1202_CR41","doi-asserted-by":"publisher","first-page":"611","DOI":"10.1007\/s13244-018-0639-9","volume":"9","author":"R Yamashita","year":"2018","unstructured":"Yamashita, R., Nishio, M., Do, R. K. G., & Togashi, K. (2018). Convolutional neural networks: An overview and application in radiology. Insights into Imaging, 9(4), 611\u2013629. https:\/\/doi.org\/10.1007\/s13244-018-0639-9","journal-title":"Insights into Imaging"}],"container-title":["Brain Imaging and Behavior"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11682-026-01202-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11682-026-01202-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11682-026-01202-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T06:59:26Z","timestamp":1790837966000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11682-026-01202-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,1]]},"references-count":41,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2026,10]]}},"alternative-id":["1202"],"URL":"https:\/\/doi.org\/10.1007\/s11682-026-01202-1","relation":{},"ISSN":["1931-7565"],"issn-type":[{"value":"1931-7565","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,1]]},"assertion":[{"value":"6 November 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 September 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 October 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"this study is based on fully de-identified, publicly available MRI data sets (COBRE, FBIRN, SLIM via SchizConnect). The original acquisitions were approved by the local institutional review board of each contributing site. All subjects took part after written informed consent was given in accordance with the Declaration of Helsinki. The present analysis is a secondary analysis of totally-de-identified public data and did not involve new acquisition of data or contact with subjects and thus, under institutional policy, was exempt from other ethics review.","order":1,"name":"Ethics","label":"Ethics approval and consent to participate","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All human subjects who took part in the original COBRE, FBIRN, and SLIM studies gave their written informed consent prior to participation. No new consent was required for this secondary analysis of public de-identified data.","order":2,"name":"Ethics","label":"Consent to participate","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":3,"name":"Ethics","label":"Clinical trial number","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"134"}}