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Neither biological nor symptomatology reductionism: A call for integration in psychopathology research

Published online by Cambridge University Press:  06 March 2019

Benjamin C. Nephew ,
Marcelo Febo  and
Hudson P Santos Jr.
Benjamin C. Nephew
Affiliation:
Department of Biology and Biotechnology, Worcester Polytechnic Institute, Worcester, MA 01605. [email protected]://www.researchgate.net/profile/Benjamin_Nephe Department of Psychiatry, University of Massachusetts Medical School, Worcester, MA 01655
Marcelo Febo
Affiliation:
Department of Psychiatry, University of Florida College of Medicine, Gainesville, FL 32610. [email protected]://www.researchgate.net/profile/Marcelo_Febo
Hudson P Santos Jr.
Affiliation:
School of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599. [email protected]://www.researchgate.net/profile/Hudson_Santos_Jr
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Abstract

We agree with Borsboom et al. in challenging neurobiological reductionism, and underscore some specific strengths of a network approach. However, they do not acknowledge that a similar problem is present in current psychosocial frameworks. We discuss this challenge as well as describe valuable parallels between symptom and neurobiological network theories that will substantially augment psychopathological research when integrated.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 42 , 2019 , e17
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Copyright
Copyright © Cambridge University Press 2019 

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References

Borsboom, D. (2017) A network theory of mental disorders. World Psychiatry 16(1):5–13. doi:10.1002/wps.20375.Google Scholar
Drysdale, A. T., Grosenick, L., Downar, J., Dunlop, K., Mansouri, F., Meng, Y., Fetcho, R. N., Zebley, B., Oathes, D. J., Etkin, A., Schatzberg, A. F., Sudheimer, K., Keller, J., Mayberg, H. S., Gunning, F. M., Alexopoulos, G. S., Fox, M. D., Pascual-Leone, A., Voss, H. U., Casey, B. J., Dubin, M. J. & Liston, C. (2017) Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nature Medicine 23(1):28–38. doi:10.1038/nm.4246. Available at: https://www.nature.com/articles/nm.4246.Google Scholar
Fried, E. I. & Nesse, R. M. (2015) Depression is not a consistent syndrome: An investigation of unique symptom patterns in the STAR*D study. Journal of Affective Disorders 172:96–102.Google Scholar
Gong, Q. & He, Y. (2015) Depression, neuroimaging and connectomics: A selective overview. Biological Psychiatry 77(3):223–35. doi:10.1016/j.biopsych.2014.08.009.Google Scholar
Kambeitz, J., Kambeitz-Ilankovic, L., Cabral, C., Dwyer, D. B., Calhoun, V. D., van den Heuvel, M. P., Falkai, P., Koutsouleris, N. & Malchow, B. (2016) Aberrant functional whole-brain network architecture in patients with schizophrenia: A meta-analysis. Schizophrenia Bulletin 42(Suppl. 1):S13–S21. doi:10.1093/schbul/sbv174.Google Scholar
Kendler, K. S. (2008) Explanatory models for psychiatric illness. The American Journal of Psychiatry 165(6):695–702. doi:10.1176/appi.ajp.2008.07071061.Google Scholar
Lo, C.-Y. Z., Su, T.-W., Huang, C.-C., Hung, C.-C., Chen, W.-L., Lan, T.-H., Lin, C. P. & Bullmore, E. T. (2015) Randomization and resilience of brain functional networks as systems-level endophenotypes of schizophrenia. Proceedings of the National Academy of Sciences USA 112(29):9123. doi:10.1073/pnas.1502052112.Google Scholar
Nephew, B. C., Carini, L. M., Sallah, S., Cotino, C., Alyamani, R. A. S., Pittet, F., Bradburn, S. & Murgatroyd, C. (2017) Intergenerational accumulation of impairments in maternal behavior following postnatal social stress. Psychoneuroendocrinology 82:98–106. doi:10.1016/j.psyneuen.2017.05.011.Google Scholar
Ohashi, K., Anderson, C. M., Bolger, E. A., Khan, A., McGreenery, C. E. & Teicher, M. H. (2017) Childhood maltreatment is associated with alteration in global network fiber-tract architecture independent of history of depression and anxiety. NeuroImage 150:50–59. doi:10.1016/j.neuroimage.2017.02.037.Google Scholar
Olbert, C. M., Gala, G. J. & Tupler, L. A. (2014) Quantifying heterogeneity attributable to polythetic diagnostic criteria: Theoretical framework and empirical application. Journal of Abnormal Psychology 123(2):452–62.Google Scholar
Samek, D. R., Hicks, B. M., Keyes, M. A., Iacono, W. G. & McGue, M. (2017) Antisocial peer affiliation and externalizing disorders: Evidence for Gene × Environment × Development interaction. Development and Psychopathology 29(1):155–72. doi:10.1017/s0954579416000109.Google Scholar
Santos, H. Jr., Fried, E. I., Asafu-Adjei, J. & Ruiz, R. J. (2017) Network structure of perinatal depressive symptoms in Latinas: Relationship to stress and reproductive biomarkers. Research in Nursing and Health 40(3):218–28.Google Scholar
Suo, X., Lei, D., Li, K., Chen, F., Li, F., Li, L., Huang, X., Lui, S., Li, L., Kemp, G. J. & Gong, Q. (2015) Disrupted brain network topology in pediatric posttraumatic stress disorder: A resting-state fMRI study. Human Brain Mapping 36(9):3677–86. doi:10.1002/hbm.22871.Google Scholar
Wei, H. (2017) Construction of a hierarchical gene regulatory network centered around a transcription factor. Brief Bioinform 27:e4662947. doi: 10.1093/bib/bbx152. Available at: https://www.researchgate.net/publication/321318939_Construction_of_a_hierarchical_gene_regulatory_network_centered_around_a_transcription_factor.Google Scholar
Wittenborn, A. K., Rahmandad, H., Rick, J. & Hosseinichimeh, N. (2016) Depression as a systemic syndrome: Mapping the feedback loops of major depressive disorder. Psychological Medicine 46(3):551–62. doi:10.1017/s0033291715002044.Google Scholar
Woodward, N. D. & Cascio, C. J. (2015) Resting-state functional connectivity in psychiatric disorders. JAMA Psychiatry 72(8):743–44. doi:10.1001/jamapsychiatry.2015.0484.Google Scholar
Zhang, R., Geng, X. & Lee, T. M. C. (2017) Large-scale functional neural network correlates of response inhibition: An fMRI meta-analysis. Brain Structure and Function 222(9):3973–90. doi:10.1007/s00429-017-1443-x.Google Scholar