Hostname: page-component-7bb8b95d7b-lvwk9 Total loading time: 0 Render date: 2024-09-27T21:58:23.705Z Has data issue: false hasContentIssue false
  • English
  • Français

Conflicting perspectives on neurobehavioral theories of the depressive disorders and drug actions

Published online by Cambridge University Press:  27 July 2016

Martin M. Katz
Martin M. Katz*
Affiliation:
Department of Psychiatry, University of Texas Health Science Center, San Antonio, TX, USA
*
Martin M. Katz, 6305 Walhonding Road, Bethesda, MD 20816, USA. Tel: +1 301 275 9826; Fax: +1 301 320 0357; E-mail: mkkatzmm@yahoo.com
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective

A prominent theory of depression focusses on neural plasticity and stress as central issues in seeking to develop a pattern of identifiable biological markers for the depressive disorders. Relative neglect, however, of clinical factors in that theory limits the uncovering of markers and opens to question their methodological approach. A conflicting theory, the ‘opposed neurobehavioral states’, based on dimensional analysis of monoamine neurotransmitter systems and behavioural factors is presented. This perspectives paper contrasts the two approaches viewing the biomarkers theory as premature at this point in the progress of depression research.

Method

Studies developed to support the biomarkers theory and the opposed neurobehavioral states theory are examined for their strengths and limitations in explaining the nature of the disorder and the actions of therapeutic drugs. Reference is made to reviews of the many studies on biomarkers and the recent work that supports the opposed neurobehavioral states theory.

Discussion

Main issue: the biomarkers theory sets important goals, but despite the many advances in the neural investigations of factors underlying depression, is still not successful in specifying markers. Thus, it is believed to be applying the wrong methodologic approach and premature in its claims. Perspective: the ‘opposed neurobehavioral’ theory is limited in its breadth of research. It applies, however, the dimensional approach to the clinical side of the problem, a methodological approach more likely to be effective in selecting the best clinical treatment and open to a more productive path to understanding of the nature of the disorder in future research.

Keywords

biomarkersclinical dimensionsdepressionneurobehavioral statestheoretical perspectives
Type
Perspectives
Information
Acta Neuropsychiatrica , Volume 28 , Issue 6 , December 2016 , pp. 311 - 314
Check for updates
Copyright
© Scandinavian College of Neuropsychopharmacology 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Schmidt, HD, Duman, RS. Peripheral BDNF produces antidepressant – like effects in cellular and behavioral models. Neuropsychopharmacology 2010;35:2378–2391.CrossRefGoogle ScholarPubMed
2. Pizzagalli, DA. Frontocingulate dysfunction in depression: toward biomarkers of treatment response. Neuropsychopharmacology 2011;36:183–206.CrossRefGoogle ScholarPubMed
3. Schmidt, HD, Shelton, RC, Duman, RS. Functional biomarkers of depression: diagnosis, treatment and pathophysiology. Neuropsychopharmacology 2011;12:2375–2394.CrossRefGoogle Scholar
4. Mayberg, HS, Brannan, SK, Mahurin, RK et al. The first functional neuroimaging study to show that increased resting cerebral blood flow in the rACC before treatment predicts favorable response to a variety of antidepressant drugs. NeuroReport 1997;8:1057–1061. CrossRefGoogle Scholar
5. Katz, MM, Maas, JW. Psychopharmacology and the etiology of psychopathologic states: are we looking in the right way? Neuropsychopharmacology 1994;10:1439–1447.CrossRefGoogle ScholarPubMed
6. Maas, JW, Koslow, S, Davis, J et al. Biological component of the NIMH-Clinical Research Branch Collaborative Program on the Psychobiology of Depression I. Background and theoretical considerations. Psychol Med 1980;10:7759–7763.CrossRefGoogle ScholarPubMed
7. Grinker, R, Miller, J, Shabsin, M, Nunn, R, Nunnally, JC. The Phenomena of Depression. New York: Hoeber, 1961.Google Scholar
8. Kendell, RE. The Classification of Depressive Illnesses. London: Oxford University Press, 1968.Google Scholar
9. Katz, MM, Houston, JP, Brannan, S et al. A multivantaged behavioral method for measuring onset and sequence of the clinical actions of antidepressants. Int J Neuropsychopharmacol 2006;7:471–479.CrossRefGoogle Scholar
10. Cuthbert, BN, Insel, T. Toward new approaches to psychotic disorders. The NIMH research domain project. Schizophr Bull 2010;36:1061–1062.CrossRefGoogle ScholarPubMed
11. Weinberger, D, Glick, ID, Klein, DF. Whither Research Domain Criteria (RDoC)? The good, the bad, and the ugly. JAMA Psychiatry 2015;72:1161–1162.CrossRefGoogle ScholarPubMed
12. Morilak, D, Frazer, A. Antidepressant brain monoaminergic systems: a dimensional approach to understanding their effects in depression and anxiety disorders. Int J Neuropsychopharmacol 2004;7:193–218.CrossRefGoogle ScholarPubMed
13. Bowden, CL, Koslow, S, Hanin, I, Davis, J, Robins, E. Effects of amitryptiline and imipramine on brain and neurotransmitter metabolites in cerebrospinal fluid. Clin Phrmacol Ther 1985;37:1193–1197.Google Scholar
14. Katz, MM, Maas, JW, Frazer, A et al. Drug-induced actions on brain neurotransmitter systems and change in the behaviors and emotions of depressed patients. Neuropsychopharmacology 1994;11:89–100.CrossRefGoogle ScholarPubMed
15. Katz, MM. Depression and Drugs: The Neurobehavioral Structure of a Psychological Storm. New York: Springer, 2013.CrossRefGoogle Scholar
16. Stassen, HH, Angst, J, Delini-Stula, A. Delayed onset of antidepressant drugs? Survey of recent results. Eur Psychiatry 1997;12:166–176.CrossRefGoogle ScholarPubMed
17. Szegedi, A, Jansen, WT, Van Wugenburg, AP. Early improvement in the first two weeks as predictors of treatment outcome in patients with major depressive disorders. J Clin Psychiatry 2009;70:344–353.CrossRefGoogle Scholar