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Editorial

How could brain fingerprinting lead to the early detection of mental illness in adolescents and what are the next steps?

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Pages 567-570 | Received 29 Jan 2023, Accepted 14 Jun 2023, Published online: 19 Jun 2023

References

  • Miranda-Dominguez O, Mills BD, Carpenter SD, et al. Connectotyping: model based fingerprinting of the functional connectome. PLoS One. 2014;9(11):e111048. doi: 10.1371/journal.pone.0111048
  • Finn ES, Shen X, Scheinost D, et al. Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity. Nat Neurosci. 2015;18(11):1664–1671. doi: 10.1038/nn.4135
  • Kaufmann T, Alnæs D, Doan NT, et al. Delayed stabilization and individualization in connectome development are related to psychiatric disorders. Nat Neurosci. 2017;20(4):513–515. doi: 10.1038/nn.4511
  • Shan ZY, Mohamed AZ, Schwenn P, et al. A longitudinal study of functional connectome uniqueness and its association with psychological distress in adolescence. Neuroimage. 2022;258:119358.
  • Suhrcke M, Pillas D, Selai C. Economic aspects of mental health in children and adolescents. In: Social cohesion for mental wellbeing among adolescents. Geneva: Copenhagen, WHO Regional Office for Europe; 2008. p. 43–64. https://apps.who.int/iris/handle/10665/345359
  • Erskine HE, Moffitt TE, Copeland WE, et al. A heavy burden on young minds: the global burden of mental and substance use disorders in children and youth. Psychol Med. 2015;45(7):1551–1563. doi: 10.1017/S0033291714002888
  • Paus T, Keshavan M, Giedd JN. Why do many psychiatric disorders emerge during adolescence? Nat Rev Neurosci. 2008;9(12):947–957. doi: 10.1038/nrn2513
  • Beaudequin D, Schwenn P, McLoughlin LT, et al. Using measures of intrinsic homeostasis and extrinsic modulation to evaluate mental health in adolescents: preliminary results from the longitudinal adolescent brain study (LABS). Psychiatry Res. 2020;285:112848. doi: 10.1016/j.psychres.2020.112848
  • Volkow ND, Koob GF, Croyle RT, et al. The conception of the ABCD study: from substance use to a broad NIH collaboration. Dev Cogn Neurosci. 2018;32:4–7. doi: 10.1016/j.dcn.2017.10.002
  • Rahman MM, Mahmood U, Lewis N, et al. Interpreting models interpreting brain dynamics. Sci Rep. 2022;12(1):12023. doi: 10.1038/s41598-022-15539-2
  • Van De Ville D, Farouj Y, Preti MG, et al. When makes you unique: temporality of the human brain fingerprint. Sci Adv. 2021;7(42):eabj0751. doi: 10.1126/sciadv.abj0751
  • Department of Aged Care. 2022. National bowel cancer screening program. Ed. Australian Government. https://www.health.gov.au/our-work/national-bowel-cancer-screening-program
  • Janssen RJ, Mourão-Miranda J, Schnack HG. Making individual prognoses in psychiatry using neuroimaging and machine learning. Biol Psychiatry Cogn Neurosci Neuroimag. 2018;3(9):798–808. doi: 10.1016/j.bpsc.2018.04.004
  • Sui J, Jiang R, Bustillo J, et al. Neuroimaging-based individualized prediction of cognition and behavior for mental disorders and health: methods and promises. Biol Psychiatry. 2020;88(11):818–828. doi: 10.1016/j.biopsych.2020.02.016
  • Kaufmann T, Alnæs D, Brandt CL, et al. Stability of the brain functional connectome fingerprint in individuals with schizophrenia. JAMA Psychiatry. 2018;75(7):749–751. doi: 10.1001/jamapsychiatry.2018.0844
  • Baker JT, Dillon DG, Patrick LM, et al. Functional connectomics of affective and psychotic pathology. Proc Natl Acad Sci U S A. 2019;116(18):9050–9059. doi: 10.1073/pnas.1820780116
  • Yeh F-C, Vettel JM, Singh A, et al. Quantifying differences and similarities in whole-brain white matter architecture using local connectome fingerprints. PLoS Comput Biol. 2016;12(11):e1005203. doi: 10.1371/journal.pcbi.1005203
  • Yamada T, Hashimoto RI, Yahata N, et al. Resting-state functional connectivity-based biomarkers and functional MRI-based neurofeedback for psychiatric disorders: a challenge for developing theranostic biomarkers. Int J Neuropsychopharmacol. 2017;20(10):769–781. doi: 10.1093/ijnp/pyx059
  • Geethanath S, Vaughan JT Jr. Accessible magnetic resonance imaging: a review. J Magn Reson Imaging. 2019;49(7):e65–e77. doi: 10.1002/jmri.26638
  • Knierim MT, Bleichner MG, Reali P. A systematic comparison of high-end and low-cost EEG amplifiers for concealed, around-the-ear EEG recordings. Sens (Basel). 2023;23(9):4559. doi: 10.3390/s23094559
  • Doubt AL, The Algorithm. On the partial accounts of machine learning. Theory Cult Soc. 2019;36(6):147–169. doi: 10.1177/0263276419851846
  • Abrol A, Fu Z, Salman M, et al. Deep learning encodes robust discriminative neuroimaging representations to outperform standard machine learning. Nat Commun. 2021;12(1):353. doi: 10.1038/s41467-020-20655-6

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