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Neurostructural subgroup in 4291 individuals with schizophrenia identified using the subtype and stage inference algorithm

. 2024 Jul 17 ; 15 (1) : 5996. [epub] 20240717

Language English Country England, Great Britain Media electronic

Document type Journal Article

Links

PubMed 39013848
PubMed Central PMC11252381
DOI 10.1038/s41467-024-50267-3
PII: 10.1038/s41467-024-50267-3
Knihovny.cz E-resources

Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal 'trajectory' of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

Center for the Neurobiology of Learning and Memory University of California Irvine 309 Qureshey Research Lab Irvine CA USA

Centre for Addiction and Mental Health TO Canada

Centre for Mental Health and Brain Sciences School of Health Sciences Swinburne University MEL Australia

Centro de Investigación Biomédica en Red de Salud Mental Instituto de Salud Carlos 3 Madrid Spain

Chinese Institute for Brain Research Beijing PR China

Clinical Translational Neuroscience Laboratory Department of Psychiatry and Human Behavior University of California Irvine Irvine Hall room 109 Irvine CA USA

Department of Advanced Biomedical Sciences University Federico 2 Naples Italy

Department of Clinical Psychology 4th Military Medical University Xi'an PR China

Department of Computer Science University of Warwick Coventry UK

Department of Human Genetics and South Texas Diabetes and Obesity Institute School of Medicine University of Texas of the Rio Grande Valley Brownsville TX USA

Department of MRI The 1st Affiliated Hospital of Zhengzhou University Zhengzhou China

Department of Neurology Huashan Hospital Fudan University Shanghai China

Department of Neurology Jena University Hospital Jena Germany

Department of Pathology of Mental Diseases National Institute of Mental Health National Center of Neurology and Psychiatry Kodaira Japan

Department of Pediatrics University of California Irvine Irvine CA USA

Department of Psychiatry and Behavioral Sciences University of Minnesota Minneapolis MN USA

Department of Psychiatry and Human Behavior University of California Irvine Irvine CA USA

Department of Psychiatry and Psychotherapie and Center for Brain Behavior and Metabolism Lübeck University Lübeck Germany

Department of Psychiatry and Psychotherapy Jena University Hospital Jena Germany

Department of Psychiatry and Psychotherapy Philipps Universität Marburg Rudolf Bultmann Str 8 Marburg Germany

Department of Psychiatry Boston Children's Hospital Harvard Medical School Boston MA USA

Department of Psychiatry Division of Clinical Medicine Institute of Medicine University of Tsukuba Tsukuba Japan

Department of Psychiatry Jeonbuk National University Hospital Jeonju Korea

Department of Psychiatry Jeonbuk National University Medical School Jeonju Korea

Department of Psychiatry Psychotherapy and Psychosomatics Psychiatric Hospital University of Zurich Zurich Switzerland

Department of Psychiatry Psychotherapy and Psychosomatics Psychiatric University Hospital Zurich Zurich Switzerland

Department of Psychiatry Taipei Veterans General Hospital Taipei Taiwan

Department of Psychiatry Temerty Faculty of Medicine University of Toronto TO Canada

Department of Psychology University of Minnesota Minneapolis MN USA

Department of Psychology University of Oslo Oslo Norway

Division of Adult Psychiatry Department of Psychiatry University Hospitals of Geneva Geneva Switzerland

Douglas Mental Health University Institute Department of Psychiatry McGill University Montréal Canada

Ege University Institute of Health Sciences Department of Neuroscience Izmir Turkey

Ege University School of Medicine Department of Psychiatry SoCAT Lab Izmir Turkey

Experimental Psychopathology and Psychotherapy Department of Psychology University of Zurich Zurich Switzerland

Faculty of Electrical Engineering Czech Technical University Prague Prague Czech Republic

FIDMAG Germanes Hospitalàries Research Foundation Barcelona Spain

Fudan ISTBI ZJNU Algorithm Centre for Brain Inspired Intelligence Zhejiang Normal University Jinhua China

German Center for Mental Health Site Jena Magdeburg Halle Magdeburg Germany

High Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province Center for Information in Medicine University of Electronic Science and Technology of China Chengdu China

Imaging Genetics Center Stevens Neuroimaging and Informatics Institute Keck School of Medicine University of Southern California Los Angeles CA USA

Institute for Translational Neuroscience University of Münster Münster Germany

Institute for Translational Psychiatry University of Münster Münster Germany

Institute for Transnational Psychiatry and Otto Creutzfeldt Center for Behavioral and Cognitive Neuroscience University of Münster Münster Germany

Institute of Computer Science Czech Academy of Sciences Prague Czech Republic

Institute of Neuroscience National Yang Ming Chiao Tung University Taipei Taiwan

Institute of Science and Technology for Brain Inspired Intelligence Fudan University Shanghai China

Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence Ministry of Education Shanghai China

KG Jebsen Centre for Neurodevelopmental Disorders University of Oslo and Oslo University Hospital Oslo Norway

Lee Kong Chian School of Medicine Nanyang Technological University Singapore Singapore

Melbourne Neuropsychiatry Centre Department of Psychiatry University of Melbourne MEL Australia

Minneapolis VA Medical Center University of Minnesota Minneapolis MN USA

MOE Frontiers Center for Brain Science Fudan University Shanghai China

MR Unit Department of Diagnostic and Interventional Radiology Institute for Clinical and Experimental Medicine Prague Czech Republic

National Clinical Research Center for Mental Disorders Department of Psychiatry The 2nd Xiangya Hospital of Central South University Changsha Hunan PR China

National Institute of Mental Health Klecany Czech Republic

Neuropsychiatry Laboratory Department of Clinical Neuroscience and Neurorehabilitation IRCCS Santa Lucia Foundation Rome Italy

Neuroscience Center Zurich University of Zurich and Swiss Federal Institute of Technology Zurich Zurich Switzerland

NORMENT Centre Division of Mental Health and Addiction Oslo University Hospital and Institute of Clinical Medicine University of Oslo Oslo Norway

Olin Neuropsychiatry Research Center Institute of Living Hartford CT USA

Peking University Sixth Hospital Peking University Institute of Mental Health NHC Key Laboratory of Mental Health Beijing PR China

PKU IDG McGovern Institute for Brain Research Peking University Beijing PR China

Psychiatric Hospital University of Zurich Zurich Switzerland

Psychiatry and Behavioral Health Ohio State Wexner Medical Center Columbus OH USA

Research Institute of Clinical Medicine of Jeonbuk National University Biomedical Research Institute of Jeonbuk National University Hospital Jeonju Korea

Research Unit of NeuroInformation Chinese Academy of Medical Sciences Chengdu China

School of Clinical Medicine University of New South Wales SYD Australia

School of Data Science Fudan University Shanghai China

School of Psychology University of New South Wales SYD Australia

Section of Psychiatry Department of Neuroscience University Federico 2 Naples Italy

Shanghai Key Laboratory of Psychotic Disorders Shanghai Mental Health Center Shanghai Jiao Tong University School of Medicine Shanghai China

Shanghai Medical College and Zhongshan Hospital Immunotherapy Technology Transfer Center Shanghai China

The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for Neuroinformation School of life Science and technology University of Electronic Science and Technology of China Chengdu China

Tri institutional Center for Translational Research in Neuroimaging and Data Science [Georgia State University Georgia Institute of Technology Emory University] Atlanta GA USA

West Region Institute of Mental Health Singapore Singapore

Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore

Zhangjiang Fudan International Innovation Center Shanghai China

See more in PubMed

Organization W. H. The Global Burden Of Disease: 2004 Update. (World Health Organization, 2008).

Howes OD, Onwordi EC. The synaptic hypothesis of schizophrenia version III: a master mechanism. Mol. Psychiatry. 2023;28:1843–1856. doi: 10.1038/s41380-023-02043-w. PubMed DOI PMC

McCutcheon RA, Krystal JH, Howes OD. Dopamine and glutamate in schizophrenia: biology, symptoms and treatment. World Psychiatry. 2020;19:15–33. doi: 10.1002/wps.20693. PubMed DOI PMC

Wolfers T, et al. Mapping the heterogeneous phenotype of schizophrenia and bipolar disorder using normative models. JAMA Psychiatry. 2018;75:1146–1155. doi: 10.1001/jamapsychiatry.2018.2467. PubMed DOI PMC

Fusar-Poli P, et al. Heterogeneity of psychosis risk within individuals at clinical high risk: a meta-analytical stratification. JAMA Psychiatry. 2016;73:113–120. doi: 10.1001/jamapsychiatry.2015.2324. PubMed DOI

McCutcheon RA, et al. The efficacy and heterogeneity of antipsychotic response in schizophrenia: A meta-analysis. Mol. Psychiatry. 2021;26:1310–1320. doi: 10.1038/s41380-019-0502-5. PubMed DOI PMC

Collado-Torres L, et al. Regional heterogeneity in gene expression, regulation, and coherence in the frontal cortex and hippocampus across development and schizophrenia. Neuron. 2019;103:203–216 e208. doi: 10.1016/j.neuron.2019.05.013. PubMed DOI PMC

Brugger SP, Howes OD. Heterogeneity and homogeneity of regional brain structure in schizophrenia: a meta-analysis. JAMA Psychiatry. 2017;74:1104–1111. doi: 10.1001/jamapsychiatry.2017.2663. PubMed DOI PMC

Braff DL, Ryan J, Rissling AJ, Carpenter WT. Lack of use in the literature from the last 20 years supports dropping traditional schizophrenia subtypes from DSM-5 and ICD-11. Schizophr. Bull. 2013;39:751–753. doi: 10.1093/schbul/sbt068. PubMed DOI PMC

The L. ICD-11: a brave attempt at classifying a new world. Lancet. 2018;391:2476. doi: 10.1016/S0140-6736(18)31370-9. PubMed DOI

Oren O, Gersh BJ, Bhatt DL. Artificial intelligence in medical imaging: switching from radiographic pathological data to clinically meaningful endpoints. Lancet Digit Health. 2020;2:e486–e488. doi: 10.1016/S2589-7500(20)30160-6. PubMed DOI

Rajpurkar P, Chen E, Banerjee O, Topol EJ. AI in health and medicine. Nat. Med. 2022;28:31–38. doi: 10.1038/s41591-021-01614-0. PubMed DOI

Wen J, et al. Multi-scale semi-supervised clustering of brain images: deriving disease subtypes. Med Image Anal. 2022;75:102304. doi: 10.1016/j.media.2021.102304. PubMed DOI PMC

Lalousis PA, et al. Heterogeneity and classification of recent onset psychosis and depression: a multimodal machine learning approach. Schizophr. Bull. 2021;47:1130–1140. doi: 10.1093/schbul/sbaa185. PubMed DOI PMC

Chand GB, et al. Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning. Brain. 2020;143:1027–1038. doi: 10.1093/brain/awaa025. PubMed DOI PMC

Yang Z, et al. A deep learning framework identifies dimensional representations of Alzheimer’s Disease from brain structure. Nat. Commun. 2021;12:7065. doi: 10.1038/s41467-021-26703-z. PubMed DOI PMC

Dwyer DB, et al. Brain subtyping enhances the neuroanatomical discrimination of schizophrenia. Schizophr. Bull. 2018;44:1060–1069. doi: 10.1093/schbul/sby008. PubMed DOI PMC

Luo C, et al. Subtypes of schizophrenia identified by multi-omic measures associated with dysregulated immune function. Mol. Psychiatry. 2021;26:6926–6936. doi: 10.1038/s41380-021-01308-6. PubMed DOI

Young AL, et al. Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference. Nat. Commun. 2018;9:4273. doi: 10.1038/s41467-018-05892-0. PubMed DOI PMC

Vogel JW, et al. Four distinct trajectories of tau deposition identified in Alzheimer’s disease. Nat. Med. 2021;27:871–881. doi: 10.1038/s41591-021-01309-6. PubMed DOI PMC

Young AL, et al. Characterizing the clinical features and atrophy patterns of MAPT-related frontotemporal dementia with disease progression modeling. Neurology. 2021;97:e941–e952. doi: 10.1212/WNL.0000000000012410. PubMed DOI PMC

Jiang Y, et al. Neuroimaging biomarkers define neurophysiological subtypes with distinct trajectories in schizophrenia. Nat. Ment. Health. 2023;1:186–199. doi: 10.1038/s44220-023-00024-0. DOI

Jiang Y, et al. Identification of four biotypes in temporal lobe epilepsy via machine learning on brain images. Nat. Commun. 2024;15:2221. doi: 10.1038/s41467-024-46629-6. PubMed DOI PMC

van Erp TGM, et al. Cortical brain abnormalities in 4474 individuals with schizophrenia and 5098 control subjects via the enhancing neuro imaging genetics through meta analysis (ENIGMA) consortium. Biol. Psychiatry. 2018;84:644–654. doi: 10.1016/j.biopsych.2018.04.023. PubMed DOI PMC

van Erp TG, et al. Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium. Mol. Psychiatry. 2016;21:585. doi: 10.1038/mp.2015.118. PubMed DOI PMC

Okada N, et al. Subcortical volumetric alterations in four major psychiatric disorders: a mega-analysis study of 5604 subjects and a volumetric data-driven approach for classification. Mol. Psychiatry. 2023;28:5206–5216. doi: 10.1038/s41380-023-02141-9. PubMed DOI PMC

Koshiyama D, et al. White matter microstructural alterations across four major psychiatric disorders: mega-analysis study in 2937 individuals. Mol. Psychiatry. 2020;25:883–895. doi: 10.1038/s41380-019-0553-7. PubMed DOI PMC

Howes OD, Cummings C, Chapman GE, Shatalina E. Neuroimaging in schizophrenia: an overview of findings and their implications for synaptic changes. Neuropsychopharmacology. 2023;48:151–167. doi: 10.1038/s41386-022-01426-x. PubMed DOI PMC

Alnaes D, et al. Brain heterogeneity in schizophrenia and its association with polygenic risk. JAMA Psychiatry. 2019;76:739–748. doi: 10.1001/jamapsychiatry.2019.0257. PubMed DOI PMC

Howes OD, Kapur S. A neurobiological hypothesis for the classification of schizophrenia: type A (hyperdopaminergic) and type B (normodopaminergic) Br. J. Psychiatry. 2014;205:1–3. doi: 10.1192/bjp.bp.113.138578. PubMed DOI

Jiang Y, et al. Progressive reduction in gray matter in patients with schizophrenia assessed with mr imaging by using causal network analysis. Radiology. 2018;287:729. doi: 10.1148/radiol.2018184005. PubMed DOI

Kirschner M, et al. Orbitofrontal-striatal structural alterations linked to negative symptoms at different stages of the schizophrenia spectrum. Schizophr. Bull. 2021;47:849–863. doi: 10.1093/schbul/sbaa169. PubMed DOI PMC

Thompson PM, et al. Mapping adolescent brain change reveals dynamic wave of accelerated gray matter loss in very early-onset schizophrenia. Proc. Natl Acad. Sci. USA. 2001;98:11650–11655. doi: 10.1073/pnas.201243998. PubMed DOI PMC

Thompson PM, et al. Time-lapse mapping of cortical changes in schizophrenia with different treatments. Cereb. Cortex. 2009;19:1107–1123. doi: 10.1093/cercor/bhn152. PubMed DOI PMC

Fillman SG, et al. Elevated peripheral cytokines characterize a subgroup of people with schizophrenia displaying poor verbal fluency and reduced Broca’s area volume. Mol. Psychiatry. 2016;21:1090–1098. doi: 10.1038/mp.2015.90. PubMed DOI PMC

Crow TJ. Is schizophrenia the price that Homo sapiens pays for language? Schizophr. Res. 1997;28:127–141. doi: 10.1016/S0920-9964(97)00110-2. PubMed DOI

Palaniyappan L, Liddle PF. Does the salience network play a cardinal role in psychosis? An emerging hypothesis of insular dysfunction. J. Psychiatry Neurosci. 2012;37:17–27. doi: 10.1503/jpn.100176. PubMed DOI PMC

McGuire PK, Murray R, Shah G. Increased blood flow in Broca’s area during auditory hallucinations in schizophrenia. Lancet. 1993;342:703–706. doi: 10.1016/0140-6736(93)91707-S. PubMed DOI

Vercammen A, Knegtering H, den Boer JA, Liemburg EJ, Aleman A. Auditory hallucinations in schizophrenia are associated with reduced functional connectivity of the temporo-parietal area. Biol. Psychiatry. 2010;67:912–918. doi: 10.1016/j.biopsych.2009.11.017. PubMed DOI

Del Re EC, et al. Baseline cortical thickness reductions in clinical high risk for psychosis: brain regions associated with conversion to psychosis versus non-conversion as assessed at one-year follow-up in the shanghai-at-risk-for-psychosis (SHARP) study. Schizophr. Bull. 2021;47:562–574. doi: 10.1093/schbul/sbaa127. PubMed DOI PMC

Pantelis C, et al. Neuroanatomical abnormalities before and after onset of psychosis: a cross-sectional and longitudinal MRI comparison. Lancet. 2003;361:281–288. doi: 10.1016/S0140-6736(03)12323-9. PubMed DOI

Slifstein M, et al. Deficits in prefrontal cortical and extrastriatal dopamine release in schizophrenia: a positron emission tomographic functional magnetic resonance imaging study. JAMA Psychiatry. 2015;72:316–324. doi: 10.1001/jamapsychiatry.2014.2414. PubMed DOI PMC

Steen RG, Mull C, McClure R, Hamer RM, Lieberman JA. Brain volume in first-episode schizophrenia: systematic review and meta-analysis of magnetic resonance imaging studies. Br. J. Psychiatry. 2006;188:510–518. doi: 10.1192/bjp.188.6.510. PubMed DOI

Balu DT, et al. Multiple risk pathways for schizophrenia converge in serine racemase knockout mice, a mouse model of NMDA receptor hypofunction. Proc. Natl Acad. Sci. USA. 2013;110:E2400–E2409. doi: 10.1073/pnas.1304308110. PubMed DOI PMC

Kahn RS, Sommer IE. The neurobiology and treatment of first-episode schizophrenia. Mol. Psychiatry. 2015;20:84–97. doi: 10.1038/mp.2014.66. PubMed DOI PMC

Vita A, De Peri L, Deste G, Barlati S, Sacchetti E. The effect of antipsychotic treatment on cortical gray matter changes in schizophrenia: does the class matter? a meta-analysis and meta-regression of longitudinal magnetic resonance imaging studies. Biol. Psychiatry. 2015;78:403–412. doi: 10.1016/j.biopsych.2015.02.008. PubMed DOI

McCutcheon RA, Reis Marques T, Howes OD. Schizophrenia-an overview. JAMA Psychiatry. 2020;77:201–210. doi: 10.1001/jamapsychiatry.2019.3360. PubMed DOI

Brugger SP, et al. Heterogeneity of Striatal Dopamine Function in Schizophrenia: Meta-analysis of Variance. Biol. Psychiatry. 2020;87:215–224. doi: 10.1016/j.biopsych.2019.07.008. PubMed DOI

Chase HW, Loriemi P, Wensing T, Eickhoff SB, Nickl-Jockschat T. Meta-analytic evidence for altered mesolimbic responses to reward in schizophrenia. Hum. Brain Mapp. 2018;39:2917–2928. doi: 10.1002/hbm.24049. PubMed DOI PMC

Koch K, et al. Functional connectivity and grey matter volume of the striatum in schizophrenia. Br. J. Psychiatry. 2014;205:204–213. doi: 10.1192/bjp.bp.113.138099. PubMed DOI

Banaj N, et al. Cortical morphology in patients with the deficit and non-deficit syndrome of schizophrenia: a worldwide meta- and mega-analyses. Mol. Psychiatry. 2023;28:4363–4373. doi: 10.1038/s41380-023-02221-w. PubMed DOI PMC

Chand GB, et al. Schizophrenia imaging signatures and their associations with cognition, psychopathology, and genetics in the general population. Am. J. Psychiatry. 2022;179:650–660. doi: 10.1176/appi.ajp.21070686. PubMed DOI PMC

Mouchlianitis E, McCutcheon R, Howes OD. Brain-imaging studies of treatment-resistant schizophrenia: a systematic review. Lancet Psychiatry. 2016;3:451–463. doi: 10.1016/S2215-0366(15)00540-4. PubMed DOI PMC

Jiang Y, Duan M, He H, Yao D, Luo C. Structural and functional MRI brain changes in patients with schizophrenia following electroconvulsive therapy: a systematic review. Curr. Neuropharmacol. 2022;20:1241–1252. doi: 10.2174/1570159X19666210809101248. PubMed DOI PMC

Wang J, et al. ECT-induced brain plasticity correlates with positive symptom improvement in schizophrenia by voxel-based morphometry analysis of grey matter. Brain Stimul. 2019;12:319–328. doi: 10.1016/j.brs.2018.11.006. PubMed DOI

Jiang Y, et al. Insular changes induced by electroconvulsive therapy response to symptom improvements in schizophrenia. Prog. Neuropsychopharmacol. Biol. Psychiatry. 2019;89:254–262. doi: 10.1016/j.pnpbp.2018.09.009. PubMed DOI

Ho BC, Andreasen NC, Ziebell S, Pierson R, Magnotta V. Long-term antipsychotic treatment and brain volumes: a longitudinal study of first-episode schizophrenia. Arch. Gen. Psychiatry. 2011;68:128–137. doi: 10.1001/archgenpsychiatry.2010.199. PubMed DOI PMC

Lewandowski K. E., Bouix S., Ongur D., Shenton M. E. Neuroprogression across the Early Course of Psychosis. J Psychiatr Brain Sci 5, e200002 (2020). PubMed PMC

Tanaka SC, et al. A multi-site, multi-disorder resting-state magnetic resonance image database. Sci. Data. 2021;8:227. doi: 10.1038/s41597-021-01004-8. PubMed DOI PMC

Keator DB, et al. The function biomedical informatics research network data repository. Neuroimage. 2016;124:1074–1079. doi: 10.1016/j.neuroimage.2015.09.003. PubMed DOI PMC

Gollub RL, et al. The MCIC collection: a shared repository of multi-modal, multi-site brain image data from a clinical investigation of schizophrenia. Neuroinformatics. 2013;11:367–388. doi: 10.1007/s12021-013-9184-3. PubMed DOI PMC

Alpert K, Kogan A, Parrish T, Marcus D, Wang L. The northwestern university neuroimaging data archive (NUNDA) Neuroimage. 2016;124:1131–1136. doi: 10.1016/j.neuroimage.2015.05.060. PubMed DOI PMC

Kogan A, Alpert K, Ambite JL, Marcus DS, Wang L. Northwestern University schizophrenia data sharing for SchizConnect: A longitudinal dataset for large-scale integration. Neuroimage. 2016;124:1196–1201. doi: 10.1016/j.neuroimage.2015.06.030. PubMed DOI PMC

Poldrack RA, et al. A phenome-wide examination of neural and cognitive function. Sci. Data. 2016;3:160110. doi: 10.1038/sdata.2016.110. PubMed DOI PMC

Repovs G, Barch DM. Working memory related brain network connectivity in individuals with schizophrenia and their siblings. Front Hum. Neurosci. 2012;6:137. doi: 10.3389/fnhum.2012.00137. PubMed DOI PMC

Soler-Vidal J, et al. Brain correlates of speech perception in schizophrenia patients with and without auditory hallucinations. PLOS ONE. 2022;17:e0276975. doi: 10.1371/journal.pone.0276975. PubMed DOI PMC

Kay SR, Fiszbein A, Opler LA. The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophr. Bull. 1987;13:261–276. doi: 10.1093/schbul/13.2.261. PubMed DOI

Lindenmayer JP, Bernstein-Hyman R, Grochowski S. Five-factor model of schizophrenia. Initial validation. J. Nerv. Ment. Dis. 1994;182:631–638. doi: 10.1097/00005053-199411000-00006. PubMed DOI

Rolls ET, Huang C-C, Lin C-P, Feng J, Joliot M. Automated anatomical labelling atlas 3. Neuroimage. 2020;206:116189. doi: 10.1016/j.neuroimage.2019.116189. PubMed DOI

Pomponio R, et al. Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan. Neuroimage. 2020;208:116450. doi: 10.1016/j.neuroimage.2019.116450. PubMed DOI PMC

Desikan RS, et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage. 2006;31:968–980. doi: 10.1016/j.neuroimage.2006.01.021. PubMed DOI

Iglesias JE, et al. A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI. Neuroimage. 2015;115:117–137. doi: 10.1016/j.neuroimage.2015.04.042. PubMed DOI PMC

Saygin ZM, et al. High-resolution magnetic resonance imaging reveals nuclei of the human amygdala: manual segmentation to automatic atlas. Neuroimage. 2017;155:370–382. doi: 10.1016/j.neuroimage.2017.04.046. PubMed DOI PMC

Iglesias JE, et al. A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology. Neuroimage. 2018;183:314–326. doi: 10.1016/j.neuroimage.2018.08.012. PubMed DOI PMC

Iglesias JE, et al. Bayesian segmentation of brainstem structures in MRI. Neuroimage. 2015;113:184–195. doi: 10.1016/j.neuroimage.2015.02.065. PubMed DOI PMC

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