Hostname: page-component-cd9895bd7-7cvxr Total loading time: 0 Render date: 2024-12-23T23:33:55.741Z Has data issue: false hasContentIssue false

When less is more: a functional magnetic resonance imaging study of verbal working memory in remitted depressed patients

Published online by Cambridge University Press:  19 July 2013

R. Norbury*
Affiliation:
Department of Psychology, Whitelands College, University of Roehampton, Holybourne Avenue, London, UK
B. Godlewska
Affiliation:
University Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK
P. J. Cowen
Affiliation:
University Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK
*
*Address for correspondence: R. Norbury, Department of Psychology, Whitelands College, University of Roehampton, Holybourne Avenue, London SW15 4JD, UK. (Email: [email protected])

Abstract

Background

Patients with depression show abnormalities in the neural circuitry supporting working memory. However, it is unclear if these abnormalities are present in unmedicated remitted depressed patients. To address this question, the current study employed functional magnetic resonance imaging (fMRI), in combination with a simple verbal n-back task, in a cohort of unmedicated remitted depressed patients.

Method

We studied 15 healthy control subjects (HC) and 15 unmedicated remitted depressed patients (rMDD). Participants performed a verbal working memory task of varying cognitive load (n-back) while undergoing fMRI. We used multiple regression analyses to assess overall capacity (1-, 2-, 3-back versus 0-back) as well as quadratic modulation of cognitive demand.

Results

Performance accuracy and response latency did not differ between groups, and overall capacity was similar. However, rMDD showed a positive quadratic load response in the bilateral hippocampus; the converse was true for HC.

Conclusions

Our data suggest that remitted depression was associated with a perturbed pattern of activation in the bilateral hippocampus during a verbal working memory task. We propose that a reduced ability to dampen task-irrelevant activity may reflect a neurobiological risk factor for recurrent depression.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2013 

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

APA (1995). Diagnostic and Statistical Manual of Mental Disorders, 4th edn. American Psychiatric Association: Washington, DC.Google Scholar
Beck, AT, Ward, CH, Mendelson, M, Mock, J, Erbaugh, J (1961). An inventory for measuring depression. Archives of General Psychiatry 4, 561571.Google Scholar
Cao, X, Liu, Z, Xu, C, Li, J, Gao, Q, Sun, N, Xu, Y, Ren, Y, Yang, C, Zhang, K (2012). Disrupted resting-state functional connectivity of the hippocampus in medication-naive patients with major depressive disorder. Journal of Affective Disorders 14, 194203.Google Scholar
Cousijn, H, Rijpkema, M, Qin, S, van Wingen, GA, Fernandez, G (2012). Phasic deactivation of the medial temporal lobe enables working memory processing under stress. Neuroimage 59, 11611167.Google Scholar
Elliott, R, Baker, SC, Rogers, RD, O'Leary, DA, Paykel, ES, Frith, CD, Dolan, RJ, Sahakian, BJ (1997). Prefrontal dysfunction in depressed patients performing a complex planning task: a study using positron emission tomography. Psychological Medicine 27, 931942.Google Scholar
Fitzgerald, PB, Srithiran, A, Benitez, J, Daskalakis, ZZ, Oxley, TJ, Kulkarni, J, Egan, GF (2008). An fMRI study of prefrontal brain activation during multiple tasks in patients with major depressive disorder. Human Brain Mapping 29, 490501.Google Scholar
Greicius, M (2008). Resting-state functional connectivity in neuropsychiatric disorders. Current Opinion Neurology 21, 424430.Google Scholar
Greicius, MD, Flores, BH, Menon, V, Glover, GH, Solvason, HB, Kenna, H, Reiss, AL, Schatzberg, AF (2007). Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus. Biological Psychiatry 62, 429437.Google Scholar
Harvey, PO, Fossati, P, Pochon, JB, Levy, R, Lebastard, G, Lehericy, S, Allilaire, JF, Dubois, B (2005). Cognitive contol and brain resources in major depression: an fMRI study using the n-back task. Neuroimage 26, 860869.Google Scholar
Jenkinson, M, Bannister, P, Brady, M, Smith, S (2002). Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage 17, 825841.Google Scholar
Jenkinson, M, Smith, S (2001). A global optimisation method for robust affine registration of brain images. Medical Image Analysis 5, 143156.Google Scholar
Mannie, ZN, Harmer, CJ, Cowen, PJ, Norbury, R (2010). A functional magnetic resonance imaging study of verbal working memory in young people at increased familial risk of depression. Biological Psychiatry 67, 471477.Google Scholar
Marazziti, D, Consoli, G, Picchetti, M, Carlini, M, Faravelli, L (2010). Cognitive impairment in major depression. European Journal of Pharmacology 626, 8386.Google Scholar
Matsuo, K, Glahn, DC, Peluso, MA, Hatch, JP, Monkul, ES, Najt, P, Sanches, M, Zamarripa, F, Li, J, Lancaster, JL, Fox, PT, Gao, JH, Soares, JC (2007). Prefrontal hyperactivation during working memory task in untreated individuals with major depressive disorder. Molecular Psychiatry 12, 158166.Google Scholar
McCabe, C, Mishor, Z, Filippini, N, Cowen, PJ, Taylor, MJ, Harmer, CJ (2011). SSRI administration reduces resting state functional connectivity in dorso-medial prefrontal cortex. Molecular Psychiatry 16, 592594.Google Scholar
McIntyre, RS, Cha, DS, Soczynska, JK, Woldeyohannes, HO, Gallaugher, LA, Kudlow, P, Alsuwaidan, M, Baskaran, A (2013). Cognitive deficits and functional outcome in major depression: determinents, substrates and treatment interventions. Depression and Anxiety 6, 515527.CrossRefGoogle Scholar
Millan, MJ, Agid, Y, Brune, M, Bullmore, ET, Carter, CS, Clayton, NS, Connor, R, Davis, S, Deakin, B, DeRubeis, RJ, Dubois, B, Geyer, MA, Goodwin, GM, Gorwood, P, Jay, TM, Joels, M, Mansuy, IM, Meyer-Lindenberg, A, Murphy, D, Rolls, E, Saletu, B, Spedding, M, Sweeney, J, Whittington, M, Young, LJ (2012). Cognitive dysfunction in psychiatric disorders: characteristics, causes and the quest for improved therapy. Nature Reviews in Drug Discovery 11, 141168.Google Scholar
Monkul, ES, Silva, LA, Narayana, S, Peluso, MA, Zamarripa, F, Nery, FG, Najt, P, Lancaster, JL, Fox, PT, Lafer, B, Soares, JC (2012). Abnormal resting state corticolimbic blood flow in depressed unmedicated patients with major depression: a 15O-H2O PET study. Human Brain Mapping 33, 272279.Google Scholar
Oakes, TR, Fox, AS, Johnstone, T, Chung, MK, Kalin, N, Davidson, RJ (2007). Integrating VBM into the General Linear Model with voxelwise anatomical covariates. Neuroimage 34, 500508.Google Scholar
Okada, G, Okamoto, Y, Morinobu, S, Yamawaki, S, Yokota, N (2003). Attenuated left prefrontal activation during a verbal fluency task in patients with depression. Neuropsychobiology 47, 2126.Google Scholar
Owen, MA, McMillan, KM, Laird, AR, Bullmore, ET (2005). N-Back working memory paradigm: a meta-analysis of normative functional neuroimaging studies. Human Brain Mapping 25, 4655.Google Scholar
Rose, EJ, Simonotto, E, Ebmeier, KP (2006). Limbic over-activity in depression during preserved performance on the n-back task. Neuroimage 29, 203215.Google Scholar
Schöning, S, Zwitserlood, P, Engelien, A, Behnken, A, Kugel, H, Schiffbauer, H, Lipina, K, Pachur, C, Kersting, A, Dannlowski, U, Baune, BT, Zwanzger, P, Reker, T, Heindel, W, Arolt, V, Konrad, C (2008). Working-memory fMRI reveals cingulate hyperactivation in euthymic major depression. Human Brain Mapping 30, 27462756.Google Scholar
Smith, S (2002). Fast robust automated brain extraction. Human Brain Mapping 17, 143155.CrossRefGoogle ScholarPubMed
Smith, S, Jenkinson, M, Woolrich, MW, Beckman, CF, Behrens, TE, Johansen-Berg, H, Bannister, PR, De Luca, M, Drobnjak, I, Flitney, D, Niazy, N, Saunders, J, Vickers, J, Zhang, Y, De Stefano, N, Brady, M, Mathews, PM (2004). Advances in functional and structral MR image analysis and implementation as FSL. Neuroimage 23, S208S219.CrossRefGoogle Scholar
Walsh, ND, Williams, SC, Brammer, MJ, Bullmore, ET, Kim, J, Suckling, J, Mitterschiffthaler, MT, Cleare, AJ, Pich, EM, Mehta, MA, Fu, CH (2007). A longitudinal functional magnetic resonance imaging study of verbal working memory in depression after antidepressant therapy. Biological Psychiatry 62, 12361243.Google Scholar
Walter, H, Wolf, RC, Spitzer, M, Vasic, N (2007). Increased left prefrontal activation in patients with unipolar depression: an event-related, parametric, performance-controlled fMRI study. Journal of Affective Disorders 101, 175185.Google Scholar
Wirth, M, Jann, K, Dierks, T, Federspiel, A, Wiest, R, Horn, H (2011). Semantic memory involvement in the default mode network: a functional neuroimaging study using independent component analysis. Neuroimage 54, 30573066.Google Scholar
Woolrich, MW, Behrens, TE, Beckmann, CF, Jenkinson, M, Smith, SM (2004). Multilevel linear modelling for FMRI group analysis using Bayesian inference. Neuroimage 21, 17321747.Google Scholar
Woolrich, MW, Ripley, BD, Brady, M, Smith, SM (2001). Temporal autocorrelation in univariate linear modeling of FMRI data. Neuroimage 14, 13701386.Google Scholar
Zhang, Y, Brady, M, Smith, S (2001). Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Transactions in Medical Imaging 20, 4557.Google Scholar
Supplementary material: PDF

Norbury supplementary material 1

Norbury supplementary material 1

Download Norbury supplementary material 1(PDF)
PDF 9.6 KB
Supplementary material: PDF

Norbury supplementary material 2

Norbury supplementary material 2

Download Norbury supplementary material 2(PDF)
PDF 9 KB