Hostname: page-component-8448b6f56d-tj2md Total loading time: 0 Render date: 2024-04-24T06:55:21.976Z Has data issue: false hasContentIssue false

Cognitive remediation therapy modulates intrinsic neural activity in patients with major depression

Published online by Cambridge University Press:  16 September 2019

Isabella Schneider*
Affiliation:
Department of General Psychiatry, Center for Psychosocial Medicine, University of Heidelberg, Heidelberg Germany, Voßstr. 4, 69115Heidelberg, Germany
Mike M. Schmitgen
Affiliation:
Department of General Psychiatry, Center for Psychosocial Medicine, University of Heidelberg, Heidelberg Germany, Voßstr. 4, 69115Heidelberg, Germany
Claudia Bach
Affiliation:
Department of General Psychiatry, Center for Psychosocial Medicine, University of Heidelberg, Heidelberg Germany, Voßstr. 4, 69115Heidelberg, Germany
Lena Listunova
Affiliation:
Department of General Psychiatry, Center for Psychosocial Medicine, University of Heidelberg, Heidelberg Germany, Voßstr. 4, 69115Heidelberg, Germany
Johanna Kienzle
Affiliation:
Department of General Psychiatry, Center for Psychosocial Medicine, University of Heidelberg, Heidelberg Germany, Voßstr. 4, 69115Heidelberg, Germany
Fabio Sambataro
Affiliation:
Department of Neuroscience (DNS), University of Padova, Padua, Italy
Malte S. Depping
Affiliation:
Department of General Psychiatry, Center for Psychosocial Medicine, University of Heidelberg, Heidelberg Germany, Voßstr. 4, 69115Heidelberg, Germany
Katharina M. Kubera
Affiliation:
Department of General Psychiatry, Center for Psychosocial Medicine, University of Heidelberg, Heidelberg Germany, Voßstr. 4, 69115Heidelberg, Germany
Daniela Roesch-Ely
Affiliation:
Department of General Psychiatry, Center for Psychosocial Medicine, University of Heidelberg, Heidelberg Germany, Voßstr. 4, 69115Heidelberg, Germany
Robert C. Wolf
Affiliation:
Department of General Psychiatry, Center for Psychosocial Medicine, University of Heidelberg, Heidelberg Germany, Voßstr. 4, 69115Heidelberg, Germany
*
Author for correspondence: I. Schneider, E-mail: isabella.schneider@med.uni-heidelberg.de

Abstract

Background

Cognitive impairment is a core feature of major depressive disorder (MDD). Cognitive remediation may improve cognition in MDD, yet so far, the underlying neural mechanisms are unclear. This study investigated changes in intrinsic neural activity in MDD after a cognitive remediation trial.

Methods

In a longitudinal design, 20 patients with MDD and pronounced cognitive deficits and 18 healthy controls (HC) were examined using resting-state functional magnetic resonance imaging. MDD patients received structured cognitive remediation therapy (CRT) over 5 weeks. The whole-brain fractional amplitude of low-frequency fluctuations was computed before the first and after the last training session. Univariate methods were used to address regionally-specific effects, and a multivariate data analysis strategy was employed to investigate functional network strength (FNS).

Results

MDD patients significantly improved in cognitive function after CRT. Baseline comparisons revealed increased right caudate activity and reduced activity in the left frontal cortex, parietal lobule, insula, and precuneus in MDD compared to HC. In patients, reduced FNS was found in a bilateral prefrontal system at baseline (p < 0.05, uncorrected). In MDD, intrinsic neural activity increased in right inferior frontal gyrus after CRT (p < 0.05, small volume corrected). Left inferior parietal lobule, left insula, left precuneus, and right caudate activity showed associations with cognitive improvement (p < 0.05, uncorrected). Prefrontal network strength increased in patients after CRT, but this increase was not associated with improved cognitive performance.

Conclusions

Our findings support the role of intrinsic neural activity of the prefrontal cortex as a possible mediator of cognitive improvement following CRT in MDD.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2019

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

Allen, EA, Erhardt, EB, Damaraju, E, Gruner, W, Segall, JM, Silva, RF, Havlicek, M, Rachakonda, S, Fries, J, Kalyanam, R, Michael, AM, Caprihan, A, Turner, JA, Eichele, T, Adelsheim, S, Bryan, AD, Bustillo, J, Clark, VP, Feldstein Ewing, SW, Filbey, F, Ford, CC, Hutchison, K, Jung, RE, Kiehl, KA, Kodituwakku, P, Komesu, YM, Mayer, AR, Pearlson, GD, Phillips, JP, Sadek, JR, Stevens, M, Teuscher, U, Thoma, RJ and Calhoun, VD (2011) A baseline for the multivariate comparison of resting-state networks. Frontiers in Systems Neuroscience 5, 2.CrossRefGoogle ScholarPubMed
Aron, AR, Robbins, TW and Poldrack, RA (2014) Inhibition and the right inferior frontal cortex: one decade on. Trends in Cognitive Science 18, 177185.CrossRefGoogle Scholar
Arsalidou, M, Duerden, EG and Taylor, MJ (2013) The centre of the brain: topographical model of motor, cognitive, affective, and somatosensory functions of the basal ganglia. Human Brain Mapping 34, 30313054.CrossRefGoogle ScholarPubMed
Baune, BT and Renger, L (2014) Pharmacological and non-pharmacological interventions to improve cognitive dysfunction and functional ability in clinical depression – a systematic review. Psychiatry Research 219, 2550.CrossRefGoogle ScholarPubMed
Brakowski, J, Spinelli, S, Dörig, N, Bosch, OG, Manoliu, A, Holtforth, MG and Seifritz, E (2017) Resting state brain network function in major depression – depression symptomatology, antidepressant treatment effects, future research. Journal of Psychiatry Research 92, 147159.CrossRefGoogle ScholarPubMed
Brett, M, Anton, JL, Valabregue, R and Poline, JB (2002) Region of interest analysis using an SPM toolbox (abstract). Presented at the 8th International Conference on Functional Mapping of the Human Brain, June 2–6, 2002, Sendai, Japan. Available on CD-ROM in NeuroImage, Vol 16, No 2.Google Scholar
Chen, B, Xu, T, Zhou, C, Wang, L, Yang, N, Wang, Z, Dong, HM, Yang, Z, Zang, YF, Zuo, XN and Weng, WC (2015) Individual variability and test-retest reliability revealed by ten repeated resting-state brain scans over one month. PLoS ONE 10, e0144963.CrossRefGoogle ScholarPubMed
Diener, C, Kuehner, C, Brusniak, W, Ubl, B, Wessa, M and Flor, H (2012) A meta-analysis of neurofunctional imaging studies of emotion and cognition in major depression. Neuroimage 61, 677685.CrossRefGoogle ScholarPubMed
Dilling, H, Mombour, W, Schmidt, MH and Schulte-Markwort, E (2011) Internationale Klassifikation psychischer Störungen. ICD-10 Kapitel V (F). Diagnostische Kriterien für Forschung und Praxis. 5 ed. Bern: Huber.Google Scholar
Dolan, RJ, Bench, CJ, Brown, RG, Scott, LC and Frackowiak, RS (1994) Neuropsychological dysfunction in depression: the relationship to regional cerebral blood flow. Psychological Medicine 4, 849857.CrossRefGoogle Scholar
Dutta, A, McKie, S and Deakin, JF (2014) Resting state networks in major depressive disorder. Psychiatry Research 224, 139151.CrossRefGoogle ScholarPubMed
Fahmy, R, Wasfi, M, Mamdouh, R, Moussa, K, Wahba, A, Schmitgen, MM, Kubera, KM, Wolf, ND, Sambataro, F and Wolf, RC (2019) Mindfulness-based therapy modulates default-mode network connectivity in patients with opioid dependence. European Neuropsychopharmacology 29, 662671.CrossRefGoogle ScholarPubMed
Garrett, A, Kelly, R, Gomez, R, Keller, J, Schatzberg, AF and Reiss, AL (2011) Aberrant brain activation during a working memory task in psychotic major depression. American Journal of Psychiatry 168, 173182.CrossRefGoogle ScholarPubMed
Gasquoine, PG (2014) Contributions of insula to cognition and emotion. Neuropsychology Review 24, 7787.CrossRefGoogle ScholarPubMed
Gotlib, IH and Joormann, J (2010) Cognition and depression: current status and future directions. Annual Review of Clinical Psychology 6, 285312.CrossRefGoogle ScholarPubMed
Grodd, W and Beckmann, CF (2014) Resting state functional MRI of the brain. Nervenarzt 85, 690700.CrossRefGoogle ScholarPubMed
Guy, W and Bonato, RR (1970) Manual for the ECDEU assessment battery. US Department of Health, Education, and Welfare, National Institute of Mental Health.Google Scholar
Han, K, Martinez, D, Chapman, SB and Krawczyk, DC (2018) Neural correlates of reduced depressive symptoms following cognitive training for chronic traumatic brain injury. Human Brain Mapping 39, 29552971.CrossRefGoogle ScholarPubMed
Hautzinger, M, Keller, F and Kühner, C (2006) Beck Depressions-Inventor (BDI-II). Revision. Frankfurt am Main: Harcourt Test Services.Google Scholar
Himberg, J, Hyvarinen, A and Esposito, F (2004) Validating the independent components of neuroimaging time series via clustering and visualization. Neuroimage 22, 12141222.CrossRefGoogle ScholarPubMed
Huang, M, Lu, S, Yu, L, Li, L, Zhang, P, Hu, J, Zhou, W, Hu, S, Wei, N, Huang, J, Weng, J and Xu, Y (2017) Altered fractional amplitude of low frequency fluctuation associated with cognitive dysfunction in first-episode drug-naïve major depressive disorder patients. BMC Psychiatry 17, 11.CrossRefGoogle ScholarPubMed
Jing, B, Liu, CH, Ma, X, Yan, HG, Zhuo, ZZ, Zhang, Y, Wang, SH, Li, HY and Wang, CY (2013) Difference in amplitude of low-frequency fluctuation between currently depressed and remitted females with major depressive disorder. Brain Research 1540, 7483.CrossRefGoogle ScholarPubMed
Kim, EJ, Bahk, YC, Oh, H, Lee, WH, Lee, JS and Choi, KH (2018) Current status of cognitive remediation for psychiatric disorders: a review. Frontiers in Psychiatry 9, 461.CrossRefGoogle ScholarPubMed
Kringelbach, ML and Rolls, ET (2004) The functional neuroanatomy of the human orbitofrontal cortex: evidence from neuroimaging and neuropsychology. Progress in Neurobiology 72, 341372.CrossRefGoogle ScholarPubMed
Lai, CH and Wu, YT (2015) The patterns of fractional amplitude of low-frequency fluctuations in depression patients: the dissociation between temporal regions and fronto-parietal regions. Journal of Affective Disorders 175, 441445.CrossRefGoogle ScholarPubMed
Lehrl, S (2005) Mehrfachwahl-Wortschatz-Intelligenztest: MWT-B. Göttingen: Hogrefe.Google Scholar
Li, Z, Kadivar, A, Pluta, J, Dunlop, J and Wang, Z (2012) Test-retest stability analysis of resting brain activity revealed by blood oxygen level-dependent functional MRI. Journal of Magnetic Resonance Imaging 36, 344354.CrossRefGoogle ScholarPubMed
Lin, C, Lee, SH, Huang, CM, Chen, GY, Ho, PS, Liu, HL, Chen, YL, Lee, TM and Wu, SC (2019) Increased brain entropy of resting-state fMRI mediates the relationship between depression severity and mental health-related quality of life in late-life depressed elderly. Journal of Affective Disorders 250, 270277.CrossRefGoogle ScholarPubMed
Listunova, L, Roth, C, Bartolovic, M, Kienzle, J, Bach, C, Weisbrod, M and Roesch-Ely, D (2018) Cognitive impairment along the course of depression: non-pharmacological treatment options. Psychopathology 51, 295305.CrossRefGoogle ScholarPubMed
Liu, F, Guo, W, Liu, L, Long, Z, Ma, C, Xue, Z, Wang, Y, Li, J, Hu, M, Zhang, J, Du, H, Zeng, L, Liu, Z, Wooderson, SC, Tan, C, Zhao, J and Chen, H (2013) Abnormal amplitude low-frequency oscillations in medication-naive, first-episode patients with major depressive disorder: a resting-state fMRI study. Journal of Affective Disorders 146, 401406.CrossRefGoogle ScholarPubMed
Liu, CH, Ma, X, Song, LP, Fan, J, Wang, WD, Lv, XY, Zhang, Y, Li, F, Wang, L and Wang, CY (2015) Abnormal spontaneous neural activity in the anterior insular and anterior cingulate cortices in anxious depression. Behavioural Brain Research 281, 339347.CrossRefGoogle ScholarPubMed
Liu, CH, Ma, X, Yuan, Z, Song, LP, Jing, B, Lu, HY, Tang, LR, Fan, J, Walter, M, Liu, CZ, Wang, L and Wang, CY (2017) Decreased resting-state activity in the precuneus is associated with depressive episodes in recurrent depression. Journal of Clinical Psychiatry 78, e372e382.CrossRefGoogle ScholarPubMed
Maldjian, JA, Laurienti, PJ, Burdette, JB and Kraft, RA (2003) An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets. Neuroimage 19, 12331239.CrossRefGoogle ScholarPubMed
Maldjian, JA, Laurienti, PJ and Burdette, JH (2004) Precentral gyrus discrepancy in electronic versions of the Talairach atlas. Neuroimage 21, 450455.CrossRefGoogle ScholarPubMed
Meusel, LA, Hall, GB, Fougere, P, McKinnon, MC and MacQueen, GM (2013) Neural correlates of cognitive remediation in patients with mood disorders. Psychiatry Research 214, 142152.CrossRefGoogle ScholarPubMed
Motter, JN, Pimontel, MA, Rindskopf, D, Devanand, DP, Doraiswamy, PM and Sneed, JR (2016) Computerized cognitive training and functional recovery in major depressive disorder: a meta-analysis. Journal of Affective Disorders 189, 184191.CrossRefGoogle ScholarPubMed
Niemann, H, Sturm, W, Thoene-Otto, AI and Willmes, K (2008) California Verbal Learning Test; Deutsche Adaptation. Frankfurt am Main: Pearson.Google Scholar
Nuechterlein, KH, Green, MF, Kern, RS, Baade, LE, Barch, DM, Cohen, JD, Essock, S, Fenton, WS, Frese, FJ III, Gold, JM, Goldberg, T, Heaton, RK, Keefe, RS, Kraemer, H, Mesholan-Gately, R, Seidman, LJ, Stover, E, Weinberger, DR, Young, AS, Zalcman, S and Marder, SR (2008) The MATRICS consensus cognitive battery, part 1: test selection, reliability, and validity. American Journal of Psychiatry 165, 203213.CrossRefGoogle ScholarPubMed
Premi, E, Calhoun, VD, Garibotto, V, Turrone, R, Alberici, A, Cottini, E, Pilotto, A, Gazzina, S, Magoni, M, Paghera, B, Borroni, B and Padovani, A (2017) Source-based morphometry multivariate approach to analyze [123I]FP-CIT SPECT imaging. Molecular Imaging and Biology 19, 772778.CrossRefGoogle ScholarPubMed
Rock, PL, Roiser, JP, Riedel, WJ and Blackwell, AD (2014) Cognitive impairment in depression: a systematic review and meta-analysis. Psychological Medicine 44, 20292040.CrossRefGoogle ScholarPubMed
Rogers, MA, Bradshaw, JL, Pantelis, C and Phillips, JG (1998) Frontostriatal deficits in unipolar major depression. Brain Research Bulletin 47, 297310.CrossRefGoogle ScholarPubMed
Schuhfried (2008) CogniPlus. [Training Kognitiver Funktionen]. Mödling: Schuhfried GmbH.Google Scholar
Schuhfried (2012) Wiener Testsystem. Mödling: Schuhfried GmbH.Google Scholar
Seeberg, I, Kjaerstad, HL and Miskowiak, KW (2018) Neural and behavioral predictors of treatment efficacy on mood symptoms and cognition in mood disorders: a systematic review. Frontiers in Psychiatry 9, 337.CrossRefGoogle ScholarPubMed
Sheehan, DV, Lecrubier, Y, Sheehan, KH, Amorim, P, Janavs, J, Weiller, E, Hergueta, T, Baker, R and Dunbar, GC (1998) The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. Journal of Clinical Psychiatry 59(suppl. 20), 2233, quiz 34-57.Google ScholarPubMed
Sundermann, B, Olde Lütke Beverborg, M and Pfleiderer, B (2014) Toward literature-based feature selection for diagnostic classification: a meta-analysis of resting-state fMRI in depression. Frontiers in Human Neuroscience 8, 692.CrossRefGoogle ScholarPubMed
Tadayonnejad, R, Yang, S, Kumar, A and Ajilore, O (2015) Clinical, cognitive, and functional connectivity correlations of resting-state intrinsic brain activity alterations in unmedicated depression. Journal of Affective Disorders 172, 241250.CrossRefGoogle ScholarPubMed
Tzourio-Mazoyer, N, Landeau, B, Papathanassiou, D, Crivello, F, Etard, O, Delcroix, N, Mazoyer, B and Jolijot, M (2002) Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 15, 273289.CrossRefGoogle ScholarPubMed
Vianin, P, Urben, S, Magistretti, P, Marquet, P, Forari, E and Jaugey, L (2014) Increased activation in broca's area after cognitive remediation in schizophrenia. Psychiatry Research 221, 204209.CrossRefGoogle Scholar
Vilberg, KL and Rugg, MD (2008) Memory retrieval and the parietal cortex: a review of evidence from dual-process perspective. Neuropsychologia 46, 17871799.CrossRefGoogle ScholarPubMed
Wang, L, Dai, W, Su, Y, Wang, G, Tan, Y, Jin, Z, Zeng, Y, Yu, X, Chen, W, Wang, X and Si, T (2012) Amplitude of low-frequency oscillations in first-episode, treatment-naive patients with major depressive disorder: a resting-state functional MRI study. PLoS ONE 7, e48658.CrossRefGoogle ScholarPubMed
Wittchen, HU, Wunderlich, U, Gruschitz, S and Zaudig, M (1997) Strukturiertes Klinisches Interview für DSM IV, Achse I (SKID-I). Goettingen: Hogrefe.Google Scholar
Wolf, RC, Nolte, HM, Hirjak, D, Hofer, S, Seidl, U, Depping, MS, Stieltjes, B, Maier-Hain, K, Sambataro, F and Thomann, PA (2016) Structural network changes in patients with major depression and schizophrenia treated with electroconvulsive therapy. European Neuropsychopharmacology 26, 14651474.CrossRefGoogle ScholarPubMed
Xu, L, Groth, KM, Pearlson, G, Schretlen, DJ and Calhoun, VD (2009) Source-based morphometry: the use of independent component analysis to identify gray matter differences with application to schizophrenia. Human Brain Mapping 30, 711724.CrossRefGoogle Scholar
Yan, C and Zang, Y (2010) DPARSF: a MATLAB toolbox for ‘pipeline’ data analysis of resting-state fMRI. Frontiers in Systems Neuroscience 4, 13.Google Scholar
Yan, CG, Wang, XD, Zuo, XN and Zang, YF (2016) DPABI: Data Processing & Analysis for (resting-state) Brain Imaging. Neuroinformatics 14, 339351.CrossRefGoogle ScholarPubMed
Zhong, X, Pu, W and Yao, S (2016) Functional alterations of fronto-limbic circuit and default mode network systems in first-episode, drug-naïve patients with major depressive disorder: a meta-analysis of resting-state fMRI data. Journal of Affective Disorders 206, 280286.CrossRefGoogle ScholarPubMed
Zou, QH, Zhu, CZ, Yang, Y, Zuo, XN, Long, XY, Cao, QJ, Wang, YF and Zang, YF (2008) An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: fractional ALFF. Journal of Neuroscience Methods 172, 137141.CrossRefGoogle ScholarPubMed
Zuo, X-N and Xing, XX (2014) Test-retest reliabilities of resting-state fMRI measurements in human brain functional connectomics: a systems neuroscience perspective. Neuroscience & Biobehavioral Reviews 45, 100118.CrossRefGoogle ScholarPubMed