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Suicide attempt history, childhood trauma, and functional brain network alterations in major depressive disorder: a resting-state functional connectivity-based multivariate pattern analysis

Abstract

A history of suicide attempts is one of the strongest predictors of future suicidal behavior in major depressive disorder (MDD). However, the resting-state functional connectivity (rs-FC) alterations that specifically differentiate MDD patients with a suicidal attempt history (SD) from those without (NSD) remain poorly understood. This study aimed to identify suicide attempt–specific rs-FC alterations using a two-stage multivariate pattern analysis (MVPA) framework—first contrasting the MDD group with the healthy control (HC) group, then directly comparing the SD group with the NSD group—and to examine whether the identified FC features were related to suicidal ideation or childhood trauma. Rs-FC data were collected from 204 adults (61 SD, 62 NSD, 81 HCs). Significant clusters from each MVPA were used as regions of interest (ROIs) for follow-up ROI-to-ROI and seed-to-voxel analyses, and associations with the Beck Scale for Suicide Ideation (SSI) and Childhood Trauma Questionnaire (CTQ) scores were examined. FC patterns that distinguished the SD group from the NSD group consistently involved visual network regions. The SD group showed lower FC between visual areas and prefrontal regions. Among ROI-level differences, the right intracalcarine cortex–right inferior temporal gyrus FC showed a negative correlation with CTQ–physical neglect subscale scores in the SD group (r = –0.427, pFDR = 0.017). Seed-to-voxel analyses revealed that lower visual–frontal FC was associated with greater suicidal ideation in the MDD group (e.g., left cuneus–left frontal pole, r = –0.341, pFDR = 0.023). These findings suggest a dysfunctional brain network linking childhood trauma, disrupted sensory–cognitive integration, and suicide attempt risk in MDD.

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Fig. 1: Functional connectivity patterns differentiating MDD and HC were identified via fc-MVPA, and seed-to-voxel FC differences between SD and NSD using these clusters as seeds.
Fig. 2: Functional connectivity differences between the SD and NSD groups were identified via fc-MVPA, ROI-to-ROI, and seed-to-voxel analyses.
Fig. 3: Association analyses of FC features derived from SD–NSD differences: ROI-to-ROI FC associated with childhood trauma and seed-to-voxel FC associated with suicidal ideation.

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Data availability

Due to ethics restrictions, the data supporting the results of this study are not publicly available, but they are available to the applicant upon reasonable request to the corresponding author: han272@korea.ac.kr, hambj@korea.ac.kr.

References

  1. World Health Organization. Suicide. 2021. https://www.who.int/news-room/fact-sheets/detail/suicide. Accessed 21 April 2025.

  2. GBD 2021 Diseases and Injuries Collaborators. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. Lancet. 2024;403:2133–61.

  3. GBD 2019 Mental Disorders Collaborators. Global, regional, and national burden of 12 mental disorders in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Psychiatry. 2022;9:137–50.

    Article  Google Scholar 

  4. Cai H, Xie XM, Zhang Q, Cui X, Lin JX, Sim K, et al. Prevalence of suicidality in major depressive disorder: a systematic review and meta-analysis of comparative studies. Front Psychiatry. 2021;12:690130.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Ferrari AJ, Charlson FJ, Norman RE, Patten SB, Freedman G, Murray CJ, et al. Burden of depressive disorders by country, sex, age, and year: findings from the Global Burden of Disease Study 2010. PLoS Med. 2013;10:e1001547.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Almeida OP, Draper B, Snowdon J, Lautenschlager NT, Pirkis J, Byrne G, et al. Factors associated with suicidal thoughts in a large community study of older adults. Br J Psychiatry. 2012;201:466–72.

    Article  PubMed  Google Scholar 

  7. Chesney E, Goodwin GM, Fazel S. Risks of all-cause and suicide mortality in mental disorders: a meta-review. World Psychiatry. 2014;13:153–60.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Bryant RA, Breukelaar IA, Williamson T, Felmingham K, Williams LM, Korgaonkar MS. The neural connectome of suicidality in adults with mood and anxiety disorders. Nat Ment Health. 2024;2:1342–49.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Kaiser RH, Andrews-Hanna JR, Wager TD, Pizzagalli DA. Large-scale network dysfunction in major depressive disorder: a meta-analysis of resting-state functional connectivity. JAMA Psychiatry. 2015;72:603–11.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Jung J, Choi S, Han KM, Kim A, Kang W, Paik JW, et al. Alterations in functional brain networks in depressed patients with a suicide attempt history. Neuropsychopharmacology. 2020;45:964–74.

    Article  PubMed  Google Scholar 

  11. Kang Y, Shin D, Kim A, Tae WS, Ham BJ, Han KM. Resting-state functional connectivity is correlated with peripheral inflammatory markers in patients with major depressive disorder and healthy controls. J Affect Disord. 2025;370:207–16.

    Article  PubMed  CAS  Google Scholar 

  12. Auerbach RP, Pagliaccio D, Allison GO, Alqueza KL, Alonso MF. Neural correlates associated with suicide and nonsuicidal self-injury in youth. Biol Psychiatry. 2021;89:119–33.

    Article  PubMed  Google Scholar 

  13. Ho TC, Walker JC, Teresi GI, Kulla A, Kirshenbaum JS, Gifuni AJ, et al. Default mode and salience network alterations in suicidal and non-suicidal self-injurious thoughts and behaviors in adolescents with depression. Transl Psychiatry. 2021;11:38.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Rai S, Griffiths KR, Breukelaar IA, Barreiros AR, Chen W, Boyce P, et al. Default-mode and fronto-parietal network connectivity during rest distinguishes asymptomatic patients with bipolar disorder and major depressive disorder. Transl Psychiatry. 2021;11:547.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Schimmelpfennig J, Topczewski J, Zajkowski W, Jankowiak-Siuda K. The role of the salience network in cognitive and affective deficits. Front Hum Neurosci. 2023;17:1133367.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Sheline YI, Barch DM, Price JL, Rundle MM, Vaishnavi SN, Snyder AZ, et al. The default mode network and self-referential processes in depression. Proc Natl Acad Sci USA. 2009;106:1942–47.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. Ambrosi E, Curtis KN, Goli P, Patriquin MA, Arciniegas DB, Simonetti A, et al. Resting-state functional connectivity of the anterior cingulate cortex among persons with mood disorders and suicidal behaviors. J Neuropsychiatry Clin Neurosci. 2024;36:143–50.

    Article  PubMed  Google Scholar 

  18. Zahid Z, McMahon L, Lynch M. Neural activity across the dorsolateral prefrontal cortex and risk for suicidal ideation and self-injury. Arch Suicide Res. 2022;26:187–207.

    Article  PubMed  Google Scholar 

  19. Paolini M, Harrington Y, Colombo F, Bettonagli V, Poletti S, Carminati M, et al. Hippocampal and parahippocampal volume and function predict antidepressant response in patients with major depression: a multimodal neuroimaging study. J Psychopharmacol. 2023;37:1070–81.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. Schmaal L, van Harmelen AL, Chatzi V, Lippard ETC, Toenders YJ, Averill LA, et al. Imaging suicidal thoughts and behaviors: a comprehensive review of 2 decades of neuroimaging studies. Mol Psychiatry. 2020;25:408–27.

    Article  PubMed  Google Scholar 

  21. Nieto-Castanon A. Brain-wide connectome inferences using functional connectivity MultiVariate Pattern Analyses (fc-MVPA). PLoS Comput Biol. 2022;18:e1010634.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Karavallil Achuthan S, Stavrinos D, Holm HB, Anteraper SA, Kana RK. Alterations of functional connectivity in autism and attention-deficit/hyperactivity disorder revealed by multi-voxel pattern analysis. Brain Connect. 2023;13:528–40.

    Article  PubMed  Google Scholar 

  23. Guell X, Arnold Anteraper S, Gardner AJ, Whitfield-Gabrieli S, Kay-Lambkin F, Iverson GL, et al. Functional connectivity changes in retired Rugby League players: a data-driven functional magnetic resonance imaging study. J Neurotrauma. 2020;37:1788–96.

    Article  PubMed  Google Scholar 

  24. Kim HE, Kim JJ, Seok JH, Park JY, Oh J. Resting-state functional connectivity and cognitive performance in aging adults with cognitive decline: a data-driven multivariate pattern analysis. Compr Psychiatry. 2024;129:152445.

    Article  PubMed  Google Scholar 

  25. Philip NS, Barredo J, van ‘t Wout-Frank M, Tyrka AR, Price LH, Carpenter LL. Network mechanisms of clinical response to transcranial magnetic stimulation in posttraumatic stress disorder and major depressive disorder. Biol Psychiatry. 2018;83:263–72.

    Article  PubMed  Google Scholar 

  26. Pastrnak M, Klirova M, Bares M, Novak T. Distinct connectivity patterns in bipolar and unipolar depression: a functional connectivity multivariate pattern analysis study. BMC Neurosci. 2024;25:46.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Ho TC, King LS. Mechanisms of neuroplasticity linking early adversity to depression: developmental considerations. Transl Psychiatry. 2021;11:517.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Bjorkenstam C, Kosidou K, Bjorkenstam E. Childhood adversity and risk of suicide: cohort study of 548 721 adolescents and young adults in Sweden. BMJ. 2017;357:j1334.

    Article  PubMed  Google Scholar 

  29. Steine IM, Nielsen B, Porter PA, Krystal JH, Winje D, Gronli J, et al. Predictors and correlates of lifetime and persistent non-suicidal self-injury and suicide attempts among adult survivors of childhood sexual abuse. Eur J Psychotraumatol. 2020;11:1815282.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Teicher MH, Samson JA, Anderson CM, Ohashi K. The effects of childhood maltreatment on brain structure, function and connectivity. Nat Rev Neurosci. 2016;17:652–66.

    Article  PubMed  CAS  Google Scholar 

  31. Yu M, Linn KA, Shinohara RT, Oathes DJ, Cook PA, Duprat R, et al. Childhood trauma history is linked to abnormal brain connectivity in major depression. Proc Natl Acad Sci USA. 2019;116:8582–90.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Gerin MI, Viding E, Herringa RJ, Russell JD, McCrory EJ. A systematic review of childhood maltreatment and resting state functional connectivity. Dev Cogn Neurosci. 2023;64:101322.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Wislowska-Stanek A, Kolosowska K, Maciejak P. Neurobiological basis of increased risk for suicidal behaviour. Cells. 2021;10:2519.

  34. Galber M, Anett Nagy S, Orsi G, Perlaki G, Simon M, Czeh B. Depressed patients with childhood maltreatment display altered intra- and inter-network resting state functional connectivity. Neuroimage Clin. 2024;43:103632.

    Article  PubMed  PubMed Central  Google Scholar 

  35. First MB, Williams JB, Karg RS, Spitzer RL. User’s guide for the SCID-5-CV structured clinical interview for DSM-5® disorders: clinical version. American Psychiatric Publishing: Washington, DC; 2016.

  36. Blumberger DM, Vila-Rodriguez F, Thorpe KE, Feffer K, Noda Y, Giacobbe P, et al. Effectiveness of theta burst versus high-frequency repetitive transcranial magnetic stimulation in patients with depression (THREE-D): a randomised non-inferiority trial. Lancet. 2018;391:1683–92.

    Article  PubMed  Google Scholar 

  37. Cole EJ, Phillips AL, Bentzley BS, Stimpson KH, Nejad R, Barmak F, et al. Stanford neuromodulation therapy (SNT): a double-blind randomized controlled trial. Am J Psychiatry. 2022;179:132–41.

    Article  PubMed  Google Scholar 

  38. Sforzini L, Worrell C, Kose M, Anderson IM, Aouizerate B, Arolt V, et al. A Delphi-method-based consensus guideline for definition of treatment-resistant depression for clinical trials. Mol Psychiatry. 2022;27:1286–99.

    Article  PubMed  CAS  Google Scholar 

  39. Talishinsky A, Downar J, Vértes PE, Seidlitz J, Dunlop K, Lynch CJ, et al. Regional gene expression signatures are associated with sex-specific functional connectivity changes in depression. Nat Commun. 2022;13:5692.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  40. Compère L, Siegle GJ, Lazzaro S, Riley E, Strege M, Canovali G, et al. Amygdala real-time fMRI neurofeedback upregulation in treatment-resistant depression: proof of concept and dose determination. Behav Res Ther. 2024;176:104523.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960;23:56.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Beck AT, Steer RA. Beck scale for suicide ideation: manual. Psychological Corporation: San Antonio, TX; 1991.

  43. Kim D, Park S-C, Yang H, Oh DH. Reliability and validity of the Korean version of the childhood trauma questionnaire-short form for psychiatric outpatients. Psychiatry Investig. 2011;8:305.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Bernstein DP, Fink L. Childhood trauma questionnaire: a retrospective self-report manual. The Psychological Corporation: San Antonio, TX; 1998.

  45. Weisman AD, Worden JW. Risk-rescue rating in suicide assessment. Arch Gen Psychiatry. 1972;26:553–60.

    Article  PubMed  CAS  Google Scholar 

  46. Raimondo L, Heij J, Priovoulos N, Kundu P, Leoni RF, van der Zwaag W. Advances in resting state fMRI acquisitions for functional connectomics. Neuroimage. 2021;243:118503.

    Article  PubMed  CAS  Google Scholar 

  47. Birn RM, Molloy EK, Patriat R, Parker T, Meier TB, Kirk GR, et al. The effect of scan length on the reliability of resting-state fMRI connectivity estimates. Neuroimage. 2013;83:550–58.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Kumar V, Lee J, Liu H-L, Allen J, Filippi C, Holodny A, et al. Recommended resting-state fMRI acquisition and preprocessing steps for preoperative mapping of language and motor and visual areas in adult and pediatric patients with brain tumors and epilepsy. Am J Neuroradiol. 2024;45:139–48.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  49. Bergé D, Lesh TA, Smucny J, Carter CS. Improvement in prefrontal thalamic connectivity during the early course of the illness in recent-onset psychosis: a 12-month longitudinal follow-up resting-state fMRI study. Psychol Med. 2022;52:2713–21.

    Article  PubMed  Google Scholar 

  50. Fang J, Rong P, Hong Y, Fan Y, Liu J, Wang H, et al. Transcutaneous vagus nerve stimulation modulates the default mode network in major depressive disorder. Biol Psychiatry. 2016;79:266–73.

    Article  PubMed  Google Scholar 

  51. Nieto-Castanon A, Whitfield-Gabrieli S. CONN functional connectivity toolbox (RRID: SCR_009550), version 22. 2022.

  52. Penny WD, Friston KJ, Ashburner JT, Kiebel SJ, Nichols TE. Statistical parametric mapping: the analysis of functional brain images. Academic Press: London; 2007.

    Google Scholar 

  53. Nieto-Castanon A. A handbook of functional connectivity magnetic resonance imaging methods in CONN. Hilbert Press: Boston, MA; 2020.

  54. Andersson JL, Hutton C, Ashburner J, Turner R, Friston K. Modeling geometric deformations in EPI time series. Neuroimage. 2001;13:903–19.

    Article  PubMed  CAS  Google Scholar 

  55. Friston KJ, Ashburner J, Frith CD, Poline JB, Heather JD, Frackowiak RS. Spatial registration and normalization of images. Hum Brain Mapp. 1995;3:165–89.

    Article  Google Scholar 

  56. Hallquist MN, Hwang K, Luna B. The nuisance of nuisance regression: spectral misspecification in a common approach to resting-state fMRI preprocessing reintroduces noise and obscures functional connectivity. Neuroimage. 2013;82:208–25.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Kelly E, Meng F, Fujita H, Morgado F, Kazemi Y, Rice LC, et al. Regulation of autism-relevant behaviors by cerebellar–prefrontal cortical circuits. Nat Neurosci. 2020;23:1102–10.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  58. Takamiya A, Kishimoto T, Hirano J, Nishikata S, Sawada K, Kurokawa S, et al. Neuronal network mechanisms associated with depressive symptom improvement following electroconvulsive therapy. Psychol Med. 2021;51:2856–63.

    Article  PubMed  Google Scholar 

  59. Gálber M, Nagy SA, Orsi G, Perlaki G, Simon M, Czéh B. Depressed patients with childhood maltreatment display altered intra-and inter-network resting state functional connectivity. Neuroimage Clin. 2024;43:103632.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Muehlhan M, Alexander N, Trautmann S, Weckesser LJ, Vogel S, Kirschbaum C, et al. Cortisol secretion predicts functional macro-scale connectivity of the visual cortex: a data-driven Multivoxel Pattern Analysis (MVPA). Psychoneuroendocrinology. 2020;117:104695.

    Article  PubMed  CAS  Google Scholar 

  61. Byun J-I, Cha KS, Kim M, Lee W-J, Lee HS, Sunwoo J-S, et al. Altered insular functional connectivity in isolated REM sleep behavior disorder: a data-driven functional MRI study. Sleep Med. 2021;79:88–93.

    Article  PubMed  Google Scholar 

  62. Upton S, Froeliger B. Regulation of craving and underlying resting-state neural circuitry predict hazard of smoking lapse. Transl Psychiatry. 2025;15:101.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Ouyang X, Long Y, Wu Z, Liu D, Liu Z, Huang X. Temporal stability of dynamic default mode network connectivity negatively correlates with suicidality in major depressive disorder. Brain Sci. 2022;12:1263.

  64. Mulders PC, van Eijndhoven PF, Schene AH, Beckmann CF, Tendolkar I. Resting-state functional connectivity in major depressive disorder: a review. Neurosci Biobehav Rev. 2015;56:330–44.

    Article  PubMed  Google Scholar 

  65. Grill-Spector K, Malach R. The human visual cortex. Annu Rev Neurosci. 2004;27:649–77.

    Article  PubMed  CAS  Google Scholar 

  66. DiCarlo JJ, Zoccolan D, Rust NC. How does the brain solve visual object recognition?. Neuron. 2012;73:415–34.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  67. Kravitz DJ, Saleem KS, Baker CI, Ungerleider LG, Mishkin M. The ventral visual pathway: an expanded neural framework for the processing of object quality. Trends Cogn Sci. 2013;17:26–49.

    Article  PubMed  Google Scholar 

  68. Vuilleumier P, Sagiv N, Hazeltine E, Poldrack RA, Swick D, Rafal RD, et al. Neural fate of seen and unseen faces in visuospatial neglect: a combined event-related functional MRI and event-related potential study. Proc Natl Acad Sci USA. 2001;98:3495–500.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  69. Kosslyn SM, Ganis G, Thompson WL. Neural foundations of imagery. Nat Rev Neurosci. 2001;2:635–42.

    Article  PubMed  CAS  Google Scholar 

  70. Sulpizio V, Teghil A, Ruffo I, Cartocci G, Giove F, Boccia M. Unveiling the neural network involved in mentally projecting the self through episodic autobiographical memories. Sci Rep. 2025;15:12781.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  71. Norberg J, McMains S, Persson J, Mitchell JP. Frontotemporal contributions to social and non-social semantic judgements. J Neuropsychol. 2024;18:66–80.

    Article  PubMed  Google Scholar 

  72. Ralph MAL, Jefferies E, Patterson K, Rogers TT. The neural and computational bases of semantic cognition. Nat Rev Neurosci. 2017;18:42–55.

    Article  PubMed  CAS  Google Scholar 

  73. Dobbertin M, Blair KS, Carollo E, Blair JR, Dominguez A, Bajaj S. Neuroimaging alterations of the suicidal brain and its relevance to practice: an updated review of MRI studies. Front Psychiatry. 2023;14:1083244.

    Article  PubMed  PubMed Central  Google Scholar 

  74. Zhang Z, Zhang Y, Wang H, Lei M, Jiang Y, Xiong D, et al. Resting-state network alterations in depression: a comprehensive meta-analysis of functional connectivity. Psychol Med. 2025;55:e63.

    Article  PubMed  PubMed Central  Google Scholar 

  75. Chi S, Mok YE, Lee JH, Suh SI, Han C, Lee MS. Functional connectivity and network analysis in adolescents with major depressive disorder showing suicidal behavior. J Affect Disord. 2023;343:42–49.

    Article  PubMed  Google Scholar 

  76. Wang Q, He C, Wang Z, Fan D, Zhang Z, Xie C, et al. Connectomics-based resting-state functional network alterations predict suicidality in major depressive disorder. Transl Psychiatry. 2023;13:365.

    Article  PubMed  PubMed Central  Google Scholar 

  77. Hanson JL, Adluru N, Chung MK, Alexander AL, Davidson RJ, Pollak SD. Early neglect is associated with alterations in white matter integrity and cognitive functioning. Child Dev. 2013;84:1566–78.

    Article  PubMed  PubMed Central  Google Scholar 

  78. Tendolkar I, Mårtensson J, Kühn S, Klumpers F, Fernández G. Physical neglect during childhood alters white matter connectivity in healthy young males. Hum Brain Mapp. 2018;39:1283–90.

    Article  PubMed  Google Scholar 

  79. Lim L, Radua J, Beyh A. Structural connectivity abnormalities in suicidal thoughts and behaviours: a meta-analysis. Transl Psychiatry. 2025;15:480.

    Article  PubMed  PubMed Central  Google Scholar 

  80. Mitchell O, Roddy DW, Connaughton M. Early life adversity and white matter microstructural organization—a systematic review. Brain Imaging Behav. 2025;19:785–799.

  81. Olson EA, Overbey TA, Ostrand CG, Pizzagalli DA, Rauch SL, Rosso IM. Childhood maltreatment experiences are associated with altered diffusion in occipito-temporal white matter pathways. Brain Behav. 2020;10:e01485.

    Article  PubMed  Google Scholar 

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Funding

This work was supported by the National Research Foundation of Korea (NRF)—Korean government (Ministry of Science and ICT [MSIT]) (grant no: RS-2025-00523110) and the NRF [Korea-UK (MRC) Cooperative Development Program]—Korean government (MSIT) in 2023 (grant no: RS-2023-00303461).

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Concept and design: Kyu-Man Han and Byung-Joo Ham. Acquisition, curation, and provision of data: Byung-Joo Ham, Kyu-Man Han, Youbin Kang. Analysis and visualization: Minjee Jung, Jihoon Park, and Kyu-Man Han. Drafting of the manuscript: Minjee Jung, Jihoon Park, and Kyu-Man Han. Revision of the manuscript: Minjee Jung, Jihoon Park, and Kyu-Man Han. Methodological support: Youbin Kang, Daun Shin, June Kang, Hyuk-June Moon, and JeYoung Jung. Critical review and supervision: Marcus Kaiser and Dorothee Auer. Funding acquisition and overall supervision: Kyu-Man Han and Byung-Joo Ham.

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Jung, M., Park, J., Kang, Y. et al. Suicide attempt history, childhood trauma, and functional brain network alterations in major depressive disorder: a resting-state functional connectivity-based multivariate pattern analysis. Neuropsychopharmacol. 51, 759–768 (2026). https://doi.org/10.1038/s41386-025-02307-9

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