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12 - Neuroimaging of mood disorders: commentary

from Section II - Mood Disorders

Published online by Cambridge University Press:  10 January 2011

Paul E. Holtzheimer III
Affiliation:
Department of Psychiatry and Behavioral Sciences Emory University School of Medicine Atlanta, GA, USA
Helen S. Mayberg
Affiliation:
Department of Psychiatry and Behavioral Sciences Emory University School of Medicine Atlanta, GA, USA
Martha E. Shenton
Affiliation:
VA Boston Healthcare System and Brigham and Women's Hospital, Harvard Medical School
Bruce I. Turetsky
Affiliation:
University of Pennsylvania
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Summary

Introduction

Over the past several decades, intensive effort has been devoted to the neurobiological investigation of mood disorders, with the goal of improving the prevention and management of these conditions through biologically based interventions. This work has been revolutionized by the advance of neuroimaging methods that allow highly detailed study of the structure and function of the brain in normal and pathological states. The six chapters in this section provide a comprehensive review of the field, highlighting how this larger body of work has contributed to, and largely defined, how we conceptualize the structural and functional neuroanatomy of mood disorders.

In this chapter, we will summarize and synthesize these various findings in an attempt to highlight what has been learned and where future research might be directed. First, the clear variance between study findings will be addressed. This variability is at times striking and potentially argues for a rather skeptical view of the field. However, there are also many reasons for optimism going forward, despite this variability (and possibly because of it). At the very least, it appears that a highly consistent network of brain regions involved in mood regulation is emerging, even if the varied interactions among these regions remain poorly understood. Utilizing this neural network framework – along with continued developments in neuroimaging methods and data analysis – provides a convenient starting point for future mood disorders imaging research.

Type
Chapter
Information
Understanding Neuropsychiatric Disorders
Insights from Neuroimaging
, pp. 197 - 204
Publisher: Cambridge University Press
Print publication year: 2010

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References

Behrens, T E, Berg, H J, Jbabdi, S, et al. 2007. Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? Neuroimage 34, 144–55.Google Scholar
Calhoun, V, Adali, T, Liu, J, et al. 2006. A feature-based approach to combine functional MRI, structural MRI and EEG brain imaging data. Conf Proc IEEE Eng Med Biol Soc 1, 3672–5.Google Scholar
Cho, R Y, Ford, J M, Krystal, J H, et al. 2005. Functional neuroimaging and electrophysiology biomarkers for clinical trials for cognition in schizophrenia. Schizophr Bull 31, 865–9.Google Scholar
Craddock, R C, Holtzheimer, P E, Hu, X P, et al. 2009. Disease state prediction from resting state functional connectivity. Magn Reson Med 62, 1619–28.Google Scholar
Farrow, T F, Whitford, T J, Williams, L M, et al. 2005. Diagnosis-related regional gray matter loss over two years in first episode schizophrenia and bipolar disorder. Biol Psychiatry 58, 713–23.Google Scholar
Fu, C H, Mourao-Miranda, J, Costafreda, S G, et al. 2008. Pattern classification of sad facial processing: Toward the development of neurobiological markers in depression. Biol Psychiatry 63, 656–62.Google Scholar
Jack, C R, Bernstein, M A, Fox, N C, et al. 2008. The Alzheimer's Disease Neuroimaging Initiative (ADNI): MRI methods. J Magn Reson Imaging 27, 685–91.Google Scholar
James, G A, Kelley, M E, Craddock, R C, et al. 2009. Exploratory structural equation modeling of resting-state fMRI: Applicability of group models to individual subjects. Neuroimage 45, 778–87.Google Scholar
Koob, G F and Moal, M. 2001. Drug addiction, dysregulation of reward, and allostasis. Neuropsychopharmacology 24, 97–129.Google Scholar
Lozano, A M, Mayberg, H S, Giacobbe, P, et al. 2008. Subcallosal cingulate gyrus deep brain stimulation for treatment-resistant depression. Biol Psychiatry 64, 461–7.Google Scholar
Mayberg, H S. 2003. Modulating dysfunctional limbic-cortical circuits in depression: Towards development of brain-based algorithms for diagnosis and optimised treatment. Br Med Bull 65, 193–207.Google Scholar
Mayberg, H S, Lozano, A M, Voon, V, et al. 2005. Deep brain stimulation for treatment-resistant depression. Neuron 45, 651–60.Google Scholar
McEwen, B S. 1998. Stress, adaptation, and disease. Allostasis and allostatic load. Ann N Y Acad Sci 840, 33–44.Google Scholar
Phillips, M L, Drevets, W C, Rauch, S L, et al. 2003. Neurobiology of emotion perception II: Implications for major psychiatric disorders. Biol Psychiatry 54, 515–28.Google Scholar
Robinson, R G, Starr, L B, Kubos, K L, et al. 1983. A two-year longitudinal study of post-stroke mood disorders: Findings during the initial evaluation. Stroke 14, 736–41.Google Scholar
Seminowicz, D A, Mayberg, H S, McIntosh, A R, et al. 2004. Limbic–frontal circuitry in major depression: A path modeling metanalysis. Neuroimage 22, 409–18.Google Scholar
Sheline, Y I, Gado, M H, Kraemer, H C, et al. 2003. Untreated depression and hippocampal volume loss. Am J Psychiatry 160, 1516–8.Google Scholar

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