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2021, Number 1

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Rev Neurol Neurocir Psiquiat 2021; 49 (1)

Contributions of brain connectivity to the understanding and diagnosis of mental illness

Díaz-Soto CM, Vélez-Gómez P

Language: Spanish
References: 34
Page: 5-13
PDF size: 186.83 Kb.


ABSTRACT

Severe mental disorders continue to challenge and worry mental health professionals and researchers. The search for the underlying etiology, the fundamental pathophysiology, and the definitive treatment for these is still ongoing. Neuroimaging technologies contribute to the understanding of mental disorders and may emerge as a diagnostic tool. For this article, information on how severe mental illness has been studied using brain connectivity was tracked in the Web of Science database. After obtaining the results, the Tree of Science platform was used for bibliographic analysis. A general view of the topic of brain connectivity in mental illness was drawn, and some of the most critical findings in this search are presented. Some important aspects are discussed, such as the fact that the biological mechanisms that have been proposed to understand mental disorders, mainly mood disorders, generally had not included a neuropathological component. Finally, it is concluded that it is necessary to approach these disorders from transdisciplinary perspectives such as neuropsychiatry.


REFERENCES

  1. Charney D, Buxbaum J, Sklar P, Nestler E. Neurobiology of mental illness. 4th ed. New York: Oxford University Press; 2013.

  2. Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N et al. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage [Internet]. 2002; 15 (1): 273-289. Available in: http://www.ncbi.nlm.nih.gov/pubmed/11771995

  3. Biswal B, Zerrin Y, Haughton VM, Hyde JS. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med. 1995; 34 (4): 537-541.

  4. Friston KJ, Frith CD. Schizophrenia: a disconnection syndrome? Vol. 3. New York, N.Y.: Clinical Neuroscience; 1995. pp. 89-97.

  5. Robledo Giraldo S, Osorio Zuluaga GA, López Espinosa C. Networking en pequeña empresa: una revisión bibliográfica utilizando la teoría de grafos. Rev Vinculos. 2014; 6 (2): 6-16.

  6. Hirsch JE. An index to quantify an individual's scientific research output. Proc Natl Acad Sci U S A. 2005; 102 (46): 16569-16572.

  7. Insel T, Cuthbert B, Garvey M et al. Research domain criteria (RDoC): toward a new classification framework for research on mental disorders. Am J Psychiatry. 2010; 167 (7): 748-751.

  8. Buckner RL, Andrews-Hanna JR, Schacter DL. The brain's default network: anatomy, function, and relevance to disease. Ann N Y Acad Sci. 2008; 1124: 1-38.

  9. Walterfang M, Wood SJ, Velakoulis D, Pantelis C. Neuropathological, neurogenetic and neuroimaging evidence for white matter pathology in schizophrenia. Neurosci Biobehav Rev. 2006; 30 (7): 918-948.

  10. Buckholtz JW, Meyer-Lindenberg A. Psychopathology and the human connectome: toward a transdiagnostic model of risk for mental illness. Neuron. 2012; 74 (6): 990-1004. doi: 10.1016/j.neuron.2012.06.002.

  11. Anticevic A, Cole MW, Murray JD, Corlett PR, Wang XJ, Krystal JH. The role of default network deactivation in cognition and disease. Trends Cogn Sci [Internet]. 2012; 16 (12): 584-592. Available in: http://dx.doi.org/10.1016/j.tics.2012.10.008

  12. Anticevic A, Cole MW, Repovs G, Murray JD, Brumbaugh MS, Winkler AM et al. Characterizing thalamo-cortical disturbances in schizophrenia and bipolar illness. Cereb Cortex. 2014; 24 (12): 3116-3130.

  13. Lynall ME, Bassett DS, Kerwin R, McKenna PJ, Kitzbichler M, Muller U et al. Functional connectivity and brain networks in schizophrenia. J Neurosci [Internet]. 2010; 30 (28): 9477–9487. Available in: http://www.jneurosci.org/cgi/doi/10.1523/JNEUROSCI.0333-10.2010

  14. Baeken C, Marinazzo D, Everaert H, Wu GR, Van Hove C, Audenaert K et al. The impact of accelerated HF-rTMS on the subgenual anterior cingulate cortex in refractory unipolar major depression: Insights from 18FDG PET brain imaging. Brain Stimul [Internet]. 2015; 8 (4): 808-815. Available in: http://dx.doi.org/10.1016/j.brs.2015.01.415

  15. Pandya M, Altinay M, Malone DA, Anand A. Where in the brain is depression? Curr Psychiatry Rep. 2012; 14 (6): 634-642.

  16. Tang Y, Wang L, Cao F, Tan L. Identify schizophrenia using resting-state functional connectivity: an exploratory research and analysis. Biomed Eng Online [Internet]. 2012; 11: 50. Available in: http://www.embase.com/search/results?subaction=viewrecord&from=export&id=L366368941%0Ahttp://ad4mh3sr7v.search.serialssolutions.com?sid=EMBASE&issn=1475925X&id=doi:&atitle=Identify+schizophrenia+using+resting-state+functional+connectivity%3A+an+explorator

  17. Orban P, Desseilles M, Mendrek A, Bourque J, Bellec P, Stip E. Altered brain connectivity in patients with schizophrenia is consistent across cognitive contexts. J Psychiatry Neurosci. 2017; 42 (1): 17-26.

  18. Skåtun KC, Kaufmann T, Doan NT, Alnæs D, Córdova-Palomera A, Jönsson EG et al. Consistent functional connectivity alterations in schizophrenia spectrum disorder: a multisite study. Schizophr Bull. 2017; 43 (4): 914-924.

  19. Fryer SL, Roach BJ, Ford JM, Donaldson KR, Calhoun VD, Pearlson GD et al. Should I stay or should I go? FMRI study of response inhibition in early illness schizophrenia and risk for psychosis. Schizophr Bull. 2019; 45 (1): 158-168.

  20. Chen B. Abnormal cortical region and subsystem complexity in dynamical functional connectivity of chronic schizophrenia: a new graph index for fMRI analysis. J Neurosci Methods [Internet]. 2019; 311: 28-37. Available in: https://doi.org/10.1016/j.jneumeth.2018.10.011

  21. Thomason ME, Marusak HA, Tocco MA, Vila AM, McGarragle O, Rosenberg DR. Altered amygdala connectivity in urban youth exposed to trauma. Soc Cogn Affect Neurosci. 2015; 10 (11): 1460-1468.

  22. Benedetti F, Bollettini I, Radaelli D, Poletti S, Locatelli C, Falini A et al. Adverse childhood experiences influence white matter microstructure in patients with bipolar disorder. Psychol Med. 2015; 44 (14): 3069-3082.

  23. Davey CG, Whittle S, Harrison BJ, Simmons JG, Byrne ML, Schwartz OS et al. Functional brain-imaging correlates of negative affectivity and the onset of first-episode depression. Psychol Med. 2015; 45 (5): 1001-1009.

  24. Kaufmann T, Alnæs D, Brandt CL, Doan NT, Kauppi K, Bettella F et al. Task modulations and clinical manifestations in the brain functional connectome in 1615 fMRI datasets. Neuroimage [Internet]. 2017; 147: 243-252. Available in: http://dx.doi.org/10.1016/j.neuroimage.2016.11.073

  25. Boissoneault J, Letzen J, Lai S, Robinson ME, Staud R. Static and dynamic functional connectivity in patients with chronic fatigue syndrome: use of arterial spin labelling fMRI. Clin Physiol Funct Imaging. 2018; 38 (1): 128-137.

  26. Sigurdsson T, Duvarci S. Hippocampal-prefrontal interactions in cognition, behavior and psychiatric disease. Front Syst Neurosci. 2016; 9: 190.

  27. Harrison PJ. The neuropathology of primary mood disorder. Brain. 2002; 125 (7): 1428-1449.

  28. Hyman SE. The diagnosis of mental disorders: the problem of reification. T Annu Rev Clin Psychol. 2010; 6: 155-179.

  29. Elliott ML, Romer A, Knodt AR, Hariri AR. A connectome-wide functional signature of transdiagnostic risk for mental illness. Biol Psychiatry [Internet]. 2018; 84 (6): 452-459. Available in: https://doi.org/10.1016/j.biopsych.2018.03.012

  30. Allen P, Stephan KE, Mechelli A, Day F, Ward N, Dalton J et al. Cingulate activity and fronto-temporal connectivity in people with prodromal signs of psychosis. Neuroimage [Internet]. 2010; 49 (1): 947-955. Available in: http://dx.doi.org/10.1016/j.neuroimage.2009.08.038

  31. Anticevic A, Brumbaugh MS, Winkler AM, Lombardo LE, Barrett J, Corlett PR et al. Global prefrontal and fronto-amygdala dysconnectivity in bipolar I disorder with psychosis history. Biol Psychiatry. 2012; 73 (6): 565-573.

  32. Finn ES, Todd Constable R. Individual variation in functional brain connectivity: implications for personalized approaches to psychiatric disease. Dialogues Clin Neurosci. 2016; 18 (3): 277-287.

  33. Hiser J, Koenigs M. The multifaceted role of the ventromedial prefrontal cortex in emotion, decision making, social cognition, and psychopathology. Biol Psychiatry [Internet]. 2018; 83 (8): 638-6347. Available in: https://doi.org/10.1016/j.biopsych.2017.10.030

  34. Pasternak O, Kelly S, Sydnor VJ, Shenton ME. Advances in microstructural diffusion neuroimaging for psychiatric disorders. Neuroimage [Internet]. 2018; 182: 259-282. Available in: https://doi.org/10.1016/j.neuroimage.2018.04.051




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