Hostname: page-component-cd9895bd7-gvvz8 Total loading time: 0 Render date: 2024-12-24T20:18:24.714Z Has data issue: false hasContentIssue false
  • English
  • Français

Individual differences in rumination in healthy and depressive samples: association with brain structure, functional connectivity and depression

Published online by Cambridge University Press:  29 July 2015

K. Wang ,
D. Wei ,
J. Yang ,
P. Xie ,
X. Hao  and
J. Qiu
K. Wang
Affiliation:
Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China Department of Psychology, Southwest University, Chongqing, China
D. Wei
Affiliation:
Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China Department of Psychology, Southwest University, Chongqing, China
J. Yang
Affiliation:
Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China Department of Psychology, Southwest University, Chongqing, China
P. Xie
Affiliation:
Neuroscience Center, Chongqing Medical University, Chongqing, China
X. Hao
Affiliation:
State Key Laboratory of Cognitive Neuroscience, Beijing Normal University, Beijing, China
J. Qiu*
Affiliation:
Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, China Department of Psychology, Southwest University, Chongqing, China
*
*Address for correspondence: Dr J. Qiu, Department of Psychology, Southwest University, Chongqing 400715, China. (Email: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Background.

Rumination is an important cognitive risk factor for onset and relapse of depression. However, no studies have employed a dimensional approach in investigating the neural correlates of rumination and the relationship with depression.

Method.

Non-clinical healthy subjects (n = 306), who completed the classical rumination and depression scales, were studied using voxel-based morphometry and regional homogeneity (ReHo). Subsequently, mediation analysis was conducted to examine the influence of rumination on the relationship between brain structure and depression. Moreover, depressive patients (n = 60) and a control group (n = 63) of comparable age and education were studied with regions of interest that were identified in the healthy individuals.

Results.

For healthy individuals, regional grey-matter volume (rGMV) of dorsolateral prefrontal cortex (DLPFC) and parahippocampal gyrus (PHG) were positively correlated with rumination. In addition, rumination had a mediating effect on the relationship between the DLPFC and PHG and depression. Moreover, ReHo analysis showed that rumination had a significantly negative correlation with functional homogeneity of DLPFC. However, compared to the control group, depressed patients showed significant decrease of rGMV in the DLPFC and PHG and there was a significant negative correlation between DLPFC volume and depressive rumination.

Conclusions.

Increased DLPFC volume (decreased ReHo) in healthy individuals while decreased in depression indicated the trend of DLPFC from inefficient inhibition (‘overload state’) to impaired regulatory mechanism (‘paralysis state’). This finding might elucidate when and why healthy individuals would develop sustained negative mood and depression eventually.

Keywords

Depressiondorsolateral prefrontal cortexgray matter volumemediationrumination
Type
Original Articles
Information
Psychological Medicine , Volume 45 , Issue 14 , October 2015 , pp. 2999 - 3008
Copyright
Copyright © Cambridge University Press 2015 

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

Argall, BD, Saad, ZS, Beauchamp, MS (2006). Simplified intersubject averaging on the cortical surface using SUMA. Human Brain Mapping 27, 14–27.CrossRefGoogle ScholarPubMed
Ashburner, J, Friston, KJ (2000). Voxel-based morphometry – the methods. Neuroimage 11, 805–821.CrossRefGoogle ScholarPubMed
Ashburner, J, Friston, KJ (2005). Unified segmentation. Neuroimage 26, 839–851.CrossRefGoogle ScholarPubMed
Beck, AT, Ward, C, Mendelson, M (1961). Beck Depression Inventory (BDI). Archives of General Psychiatry 4, 561–571.CrossRefGoogle Scholar
Botvinick, MM, Cohen, JD, Carter, CS (2004). Conflict monitoring and anterior cingulate cortex: an update. Trends in Cognitive Sciences 8, 539–546.CrossRefGoogle ScholarPubMed
Buckner, RL, Sepulcre, J, Talukdar, T, Krienen, FM, Liu, H, Hedden, T, Andrews-Hanna, JR, Sperling, RA, Johnson, KA (2009). Cortical hubs revealed by intrinsic functional connectivity: mapping, assessment of stability, and relation to Alzheimer's disease. Journal of Neuroscience 29, 1860–1873.CrossRefGoogle ScholarPubMed
Cuijpers, P, Smit, F (2004). Subthreshold depression as a risk indicator for major depressive disorder: a systematic review of prospective studies. Acta Psychiatrica Scandinavica 109, 325–331.CrossRefGoogle ScholarPubMed
de Kwaasteniet, B, Ruhe, E, Caan, M, Rive, M, Olabarriaga, S, Groefsema, M, Heesink, L, van Wingen, G, Denys, D (2013). Relation between structural and functional connectivity in major depressive disorder. Biological Psychiatry 74, 40–47.CrossRefGoogle ScholarPubMed
Demeyer, I, De Lissnyder, E, Koster, EH, Raedt, R (2012). Rumination mediates the relationship between impaired cognitive control for emotional information and depressive symptoms: a prospective study in remitted depressed adults. Behaviour Research and Therapy 50, 292–297.CrossRefGoogle ScholarPubMed
Denson, TF, Pedersen, WC, Ronquillo, J, Nandy, AS (2009). The angry brain: neural correlates of anger, angry rumination, and aggressive personality. Journal of Cognitive Neuroscience 21, 734–744.CrossRefGoogle ScholarPubMed
De Raedt, R, Koster, EH (2010). Understanding vulnerability for depression from a cognitive neuroscience perspective: a reappraisal of attentional factors and a new conceptual framework. Cognitive, Affective, and Behavioral Neuroscience 10, 50–70.CrossRefGoogle Scholar
Derakshan, N, Ansari, TL, Hansard, M, Shoker, L, Eysenck, MW (2009). Anxiety, inhibition, efficiency, and effectiveness. Experimental Psychology 56, 48–55.CrossRefGoogle ScholarPubMed
Ekkers, W, Korrelboom, K, Huijbrechts, I, Smits, N, Cuijpers, P, van der Gaag, M (2011). Competitive Memory Training for treating depression and rumination in depressed older adults: a randomized controlled trial. Behaviour Research and Therapy 49, 588–596.CrossRefGoogle ScholarPubMed
Fales, CL, Barch, DM, Rundle, MM, Mintun, MA, Snyder, AZ, Cohen, JD, Mathews, J, Sheline, YI (2008). Altered emotional interference processing in affective and cognitive-control brain circuitry in major depression. Biological Psychiatry 63, 377–384.CrossRefGoogle ScholarPubMed
Fischl, B, Rajendran, N, Busa, E, Augustinack, J, Hinds, O, Yeo, BT, Mohlberg, H, Amunts, K, Zilles, K (2008). Cortical folding patterns and predicting cytoarchitecture. Cerebral Cortex 18, 1973–1980.CrossRefGoogle ScholarPubMed
Greicius, MD, Supekar, K, Menon, V, Dougherty, RF (2009). Resting-state functional connectivity reflects structural connectivity in the default mode network. Cerebral Cortex 19, 72–78.CrossRefGoogle ScholarPubMed
Hagmann, P, Cammoun, L, Gigandet, X, Meuli, R, Honey, CJ, Wedeen, VJ, Sporns, O (2008). Mapping the structural core of human cerebral cortex. PLoS Biology 6, e159.CrossRefGoogle ScholarPubMed
Harvey, P-O, Fossati, P, Pochon, J-B, Levy, R, LeBastard, G, Lehéricy, S, Allilaire, J-F, Dubois, B (2005). Cognitive control and brain resources in major depression: an fMRI study using the n-back task. Neuroimage 26, 860–869.CrossRefGoogle ScholarPubMed
Hayakawa, YK, Sasaki, H, Takao, H, Mori, H, Hayashi, N, Kunimatsu, A, Aoki, S, Ohtomo, K (2013). Structural brain abnormalities in women with subclinical depression, as revealed by voxel-based morphometry and diffusion tensor imaging. Journal of Affective Disorders 144, 263–268.CrossRefGoogle ScholarPubMed
Honey, C, Sporns, O, Cammoun, L, Gigandet, X, Thiran, J-P, Meuli, R, Hagmann, P (2009). Predicting human resting-state functional connectivity from structural connectivity. Proceedings of the National Academy of Sciences USA 106, 2035–2040.CrossRefGoogle ScholarPubMed
Honey, CJ, Thivierge, J-P, Sporns, O (2010). Can structure predict function in the human brain? Neuroimage 52, 766–776.CrossRefGoogle ScholarPubMed
Hooker, CI, Gyurak, A, Verosky, SC, Miyakawa, A, Ayduk, Ö (2010). Neural activity to a partner's facial expression predicts self-regulation after conflict. Biological Psychiatry 67, 406–413.CrossRefGoogle ScholarPubMed
Huffziger, S, Ebner-Priemer, U, Koudela, S, Reinhard, I, Kuehner, C (2012). Induced rumination in everyday life: advancing research approaches to study rumination. Personality and Individual Differences 53, 790–795.CrossRefGoogle Scholar
Joormann, J, Yoon, KL, Zetsche, U (2007). Cognitive inhibition in depression. Applied and Preventive Psychology 12, 128–139.CrossRefGoogle Scholar
Kühn, S, Vanderhasselt, M-A, De Raedt, R, Gallinat, J (2012). Why ruminators won't stop: the structural and resting state correlates of rumination and its relation to depression. Journal of Affective Disorders 141, 352–360.CrossRefGoogle ScholarPubMed
Kross, E, Davidson, M, Weber, J, Ochsner, K (2009). Coping with emotions past: the neural bases of regulating affect associated with negative autobiographical memories. Biological Psychiatry 65, 361–366.CrossRefGoogle ScholarPubMed
Kuehner, C, Weber, I (1999). Responses to depression in unipolar depressed patients: an investigation of Nolen-Hoeksema's response styles theory. Psychological Medicine 29, 1323–1333.CrossRefGoogle ScholarPubMed
Kuhn, S, Vanderhasselt, MA, De Raedt, R, Gallinat, J (2012). Why ruminators won't stop: the structural and resting state correlates of rumination and its relation to depression. Journal of Affective Disorders 141, 352–60.CrossRefGoogle ScholarPubMed
Langenecker, SA, Kennedy, SE, Guidotti, LM, Briceno, EM, Own, LS, Hooven, T, Young, EA, Akil, H, Noll, DC, Zubieta, J-K (2007). Frontal and limbic activation during inhibitory control predicts treatment response in major depressive disorder. Biological Psychiatry 62, 1272–1280.CrossRefGoogle ScholarPubMed
Li, W, Li, X, Huang, L, Kong, X, Yang, W, Wei, D, Li, J, Cheng, H, Zhang, Q, Qiu, J (2014). Brain structure links trait creativity to openness to experience. Social Cognitive and Affective Neuroscience 41, 1–8.Google Scholar
Lo, C, Ho, S, Hollon, SD (2008). The effects of rumination and negative cognitive styles on depression: a mediation analysis. Behaviour Research and Therapy 46, 487.CrossRefGoogle ScholarPubMed
Lyubomirsky, S, Nolen-Hoeksema, S (1995). Effects of self-focused rumination on negative thinking and interpersonal problem solving. Journal of Personality and Social Psychology 69, 176–176.CrossRefGoogle ScholarPubMed
MacDonald, AW, Cohen, JD, Stenger, VA, Carter, CS (2000). Dissociating the role of the dorsolateral prefrontal and anterior cingulate cortex in cognitive control. Science 288, 1835–1838.CrossRefGoogle ScholarPubMed
Mansouri, FA, Buckley, MJ, Tanaka, K (2007). Mnemonic function of the dorsolateral prefrontal cortex in conflict-induced behavioral adjustment. Science 318, 987–990.CrossRefGoogle ScholarPubMed
Marcoulides, GA, Hershberger, SL (1997). Multivariate Statistical Methods: A First Course. Psychology Press: East Sussex, UK.Google Scholar
Nolen-Hoeksema, S (1991). Responses to depression and their effects on the duration of depressive episodes. Journal of Abnormal Psychology 100, 569–582.CrossRefGoogle ScholarPubMed
Nolen-Hoeksema, S (2000). The role of rumination in depressive disorders and mixed anxiety/depressive symptoms. Journal of Abnormal Psychology 109, 504–511.CrossRefGoogle ScholarPubMed
Phillips, ML, Drevets, WC, Rauch, SL, Lane, R (2003). Neurobiology of emotion perception I: the neural basis of normal emotion perception. Biological Psychiatry 54, 504–514.CrossRefGoogle ScholarPubMed
Preacher, KJ, Hayes, AF (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods 40, 879–891.CrossRefGoogle ScholarPubMed
Putnam, KM, McSweeney, LB (2008). Depressive symptoms and baseline prefrontal EEG alpha activity: a study utilizing Ecological Momentary Assessment. Biological Psychology 77, 237–240.CrossRefGoogle ScholarPubMed
Radloff, LS (1977). The CES-D scale a self-report depression scale for research in the general population. Applied Psychological Measurement 1, 385–401.CrossRefGoogle Scholar
Robinson, MS, Alloy, LB (2003). Negative cognitive styles and stress-reactive rumination interact to predict depression: a prospective study. Cognitive Therapy and Research 27, 275–291.CrossRefGoogle Scholar
Roelofs, J, Muris, P, Huibers, M, Peeters, F, Arntz, A (2006). On the measurement of rumination: a psychometric evaluation of the ruminative response scale and the rumination on sadness scale in undergraduates. Journal of Behavior Therapy and Experimental Psychiatry 37, 299–313.CrossRefGoogle ScholarPubMed
Spasojević, J, Alloy, LB (2001). Rumination as a common mechanism relating depressive risk factors to depression. Emotion 1, 25–37.CrossRefGoogle ScholarPubMed
Treynor, W, Gonzalez, R, Nolen-Hoeksema, S (2003). Rumination reconsidered: a psychometric analysis. Cognitive Therapy and Research 27, 247–259.CrossRefGoogle Scholar
Vanderhasselt, M-A, Baeken, C, Van, SP, Luypaert, R, De, MJ, De, RR (2013). How brooding minds inhibit negative material: an event-related fMRI study. Brain and Cognition 81, 352–359.CrossRefGoogle ScholarPubMed
Wagner, M, Rihs, TA, Mosimann, UP, Fisch, HU, Schlaepfer, TE (2006). Repetitive transcranial magnetic stimulation of the dorsolateral prefrontal cortex affects divided attention immediately after cessation of stimulation. Journal of Psychiatric Research 40, 315–321.CrossRefGoogle ScholarPubMed
Webb, CA, Weber, M, Mundy, EA, Killgore, WD (2014). Reduced gray matter volume in the anterior cingulate, orbitofrontal cortex and thalamus as a function of mild depressive symptoms: a voxel-based morphometric analysis. Psychological Medicine 44, 1–11.CrossRefGoogle ScholarPubMed
Wei, D, Yang, J, Li, W, Wang, K, Zhang, Q, Qiu, J (2014). Increased resting functional connectivity of the medial prefrontal cortex in creativity by means of cognitive stimulation. Cortex 51, 92–102.CrossRefGoogle ScholarPubMed
Wolkenstein, L, Plewnia, C (2013). Amelioration of cognitive control in depression by transcranial direct current stimulation. Biol Psychiatry 73, 646–51.CrossRefGoogle ScholarPubMed
Zang, Y, Jiang, T, Lu, Y, He, Y, Tian, L (2004). Regional homogeneity approach to fMRI data analysis. Neuroimage 22, 394–400.CrossRefGoogle ScholarPubMed
Zhang, H, Xu, Y (2010). Reliability and validity of the chinese short rumination responses scale (SRRS) in Chinese undergraduates. Psychological Research 3, 34–39.Google Scholar
Zung, WW (1965). A self-rating depression scale. Archives of General Psychiatry 12, 63–70.CrossRefGoogle ScholarPubMed
Zuo, X-N, Xu, T, Jiang, L, Yang, Z, Cao, X-Y, He, Y, Zang, Y-F, Castellanos, FX, Milham, MP (2013). Toward reliable characterization of functional homogeneity in the human brain: preprocessing, scan duration, imaging resolution and computational space. Neuroimage 65, 374–386.CrossRefGoogle ScholarPubMed
Supplementary material: File

Wang supplementary material

Wang supplementary material 1

Download Wang supplementary material(File)
File 32.7 KB