Skip to main content Accessibility help

Amygdala functional connectivity in major depression – disentangling markers of pathology, risk and resilience

  • Carolin Wackerhagen (a1), Ilya M. Veer (a1), Susanne Erk (a1), Sebastian Mohnke (a1), Tristram A. Lett (a1) (a2), Torsten Wüstenberg (a1), Nina Y. Romanczuk-Seiferth (a1), Kristina Schwarz (a3), Janina I. Schweiger (a3), Heike Tost (a3), Andreas Meyer-Lindenberg (a3), Andreas Heinz (a1) and Henrik Walter (a1)...



Limbic-cortical imbalance is an established model for the neurobiology of major depressive disorder (MDD), but imaging genetics studies have been contradicting regarding potential risk and resilience mechanisms. Here, we re-assessed previously reported limbic-cortical alterations between MDD relatives and controls in combination with a newly acquired sample of MDD patients and controls, to disentangle pathology, risk, and resilience.


We analyzed functional magnetic resonance imaging data and negative affectivity (NA) of MDD patients (n = 48), unaffected first-degree relatives of MDD patients (n = 49) and controls (n = 109) who performed a faces matching task. Brain response and task-dependent amygdala functional connectivity (FC) were compared between groups and assessed for associations with NA.


Groups did not differ in task-related brain activation but activation in the superior frontal gyrus (SFG) was inversely correlated with NA in patients and controls. Pathology was associated with task-independent decreases of amygdala FC with regions of the default mode network (DMN) and decreased amygdala FC with the medial frontal gyrus during faces matching, potentially reflecting a task-independent DMN predominance and a limbic-cortical disintegration during faces processing in MDD. Risk was associated with task-independent decreases of amygdala-FC with fronto-parietal regions and reduced faces-associated amygdala-fusiform gyrus FC. Resilience corresponded to task-independent increases in amygdala FC with the perigenual anterior cingulate cortex (pgACC) and increased FC between amygdala, pgACC, and SFG during faces matching.


Our results encourage a refinement of the limbic-cortical imbalance model of depression. The validity of proposed risk and resilience markers needs to be tested in prospective studies. Further limitations are discussed.

  • View HTML
    • Send article to Kindle

      To send this article to your Kindle, first ensure is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

      Note you can select to send to either the or variations. ‘’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

      Find out more about the Kindle Personal Document Service.

      Amygdala functional connectivity in major depression – disentangling markers of pathology, risk and resilience
      Available formats

      Send article to Dropbox

      To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

      Amygdala functional connectivity in major depression – disentangling markers of pathology, risk and resilience
      Available formats

      Send article to Google Drive

      To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

      Amygdala functional connectivity in major depression – disentangling markers of pathology, risk and resilience
      Available formats


This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike licence (, which permits non-commercial re-use, distribution, and reproduction in any medium, provided the same Creative Commons licence is included and the original work is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use.

Corresponding author

Author for correspondence: Carolin Wackerhagen, E-mail:


Hide All
Amico, F (2011) Structural MRI correlates for vulnerability and resilience to major depressive disorder. Journal of Psychiatry & Neuroscience 36, 1522.
Amunts, K, Kedo, O, Kindler, M, Pieperhoff, P, Mohlberg, H, Shah, NJ, Habel, U, Schneider, F and Zilles, K (2005) Cytoarchitectonic mapping of the human amygdala, hippocampal region and entorhinal cortex: intersubject variability and probability maps. Anatomy and Embryology 210, 343352.
Beck, A, Wüstenberg, T, Genauck, A, Wrase, J, Schlagenhauf, F, Smolka, MN, Mann, K and Heinz, A (2012) Effect of brain structure, brain function, and brain connectivity on relapse in alcohol-dependent patients. Archives of General Psychiatry 69, 842852.
Bzdok, D, Langner, R, Schilbach, L, Engemann, DA, Laird, AR, Fox, PT and Eickhoff, S (2013) Segregation of the human medial prefrontal cortex in social cognition. Frontiers in Human Neuroscience 7, 232.
Costa, PT and McCrae, RR (1992) Normal personality assessment in clinical practice: the NEO personality inventory. Psychological Assessment 4, 513.
Disner, SG, Beevers, CG, Haigh, EAP and Beck, AT (2011) Neural mechanisms of the cognitive model of depression. Nature Reviews Neuroscience 12, 467477.
Doucet, GE, Bassett, DS, Yao, N, Glahn, DC and Frangou, S (2017) The role of intrinsic brain functional connectivity in vulnerability and resilience to bipolar disorder. The American Journal of Psychiatry 174, 12141222.
Eickhoff, SB, Stephan, KE, Mohlberg, H, Grefkes, C, Fink, GR, Amunts, K and Zilles, K (2005) A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data. NeuroImage 25, 13251335.
Erk, S, Meyer-Lindenberg, A, Schmierer, P, Mohnke, S, Grimm, O, Garbusow, M, Haddad, L, Poehland, L, Mühleisen, TW, Witt, SH, Tost, H, Kirsch, P, Romanczuk-Seiferth, N, Schott, BH, Cichon, S, Nöthen, MM, Rietschel, M, Heinz, A and Walter, H (2014) Hippocampal and frontolimbic function as intermediate phenotype for psychosis: evidence from healthy relatives and a common risk variant in CACNA1C. Biological Psychiatry 76, 466475.
Etkin, A, Egner, T and Kalisch, R (2011) Emotional processing in anterior cingulate and medial prefrontal cortex. Trends in Cognitive Sciences 15, 8593.
Fitzgerald, PB, Laird, AR, Maller, J and Daskalakis, ZJ (2008) A meta-analytic study of changes in brain activation in depression. Human Brain Mapping 29, 683695.
Fornito, A and Bullmore, ET (2012) Connectomic intermediate phenotypes for psychiatric disorders. Frontiers in Neuropsychiatric Imaging and Stimulation 3, 32.
Franke, GH (2002) Symptom-Checkliste von L.R. Derogatis (SCL-90-R) – Deutsche Version 2. vollständig überarbeitete und neu normierte Auflage. Beltz Test: Göttingen.
Friston, KJ, Buechel, C, Fink, GR, Morris, J, Rolls, E and Dolan, RJ (1997) Psychophysiological and modulatory interactions in neuroimaging. NeuroImage 6, 218229.
GBD 2016 DALYs and HALE Collaborators (2017) Global, regional, and national disability-adjusted life-years (DALYs) for 333 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet (London, England) 390, 12601344.
Gorgolewski, KJ, Varoquaux, G, Rivera, G, Schwarz, Y, Ghosh, SS, Maumet, C, Sochat, VV, Nichols, TE, Poldrack, RA, Poline, J-B, Yarkoni, T and Margulies, DS (2015) a web-based repository for collecting and sharing unthresholded statistical maps of the human brain. Frontiers in Neuroinformatics 9, 8.
Gottesman, II and Gould, TD (2003) The endophenotype concept in psychiatry: etymology and strategic intentions. American Journal of Psychiatry 160, 636645.
Graham, J, Salimi-Khorshidi, G, Hagan, C, Walsh, N, Goodyer, I, Lennox, B and Suckling, J (2013) Meta-analytic evidence for neuroimaging models of depression: state or trait? Journal of Affective Disorders 151, 423431.
Hariri, AR, Bookheimer, SY and Mazziotta, JC (2000) Modulating emotional responses: effects of a neocortical network on the limbic system. Neuroreport 11, 4348.
Hariri, AR, Mattay, VS, Tessitore, A, Kolachana, B, Fera, F, Goldman, D, Egan, MF and Weinberger, DR (2002) Serotonin transporter genetic variation and the response of the human amygdala. Science 297, 400403.
Hautzinger, M, Bailer, M, Worrall, H and Keller, F (1994) Beck-Depressions-InveBeck-Depressions-Inventar (BDI). Bearbeitung der deutschen Ausgabe. Testhandbuch. Bern, Göttingen, Toronto, Seattle: Huber.
Havlík, M, Kozáková, E and Horáček, J (2017) Why and how. The future of the central questions of consciousness. Frontiers in Psychology 8, 1797.
Heinz, A, Braus, DF, Smolka, MN, Wrase, J, Puls, I, Hermann, D, Klein, S, Grüsser, SM, Flor, H, Schumann, G, Mann, K and Büchel, C (2005) Amygdala-prefrontal coupling depends on a genetic variation of the serotonin transporter. Nature Neuroscience 8, 2021.
Ho, TC, Zhang, S, Sacchet, MD, Weng, H, Connolly, CG, Henje Blom, E, Han, LKM, Mobayed, NO and Yang, TT (2016) Fusiform gyrus dysfunction is associated with perceptual processing efficiency to emotional faces in adolescent depression: a model-based approach. Frontiers in Psychology 7, 40.
Kaiser, RH, Andrews-Hanna, JR, Wager, TD and Pizzagalli, DA (2015) Large-scale network dysfunction in major depressive disorder: a meta-analysis of resting-state functional connectivity. JAMA Psychiatry 72, 603611.
Kalisch, R, Baker, DG, Basten, U, Boks, MP, Bonanno, GA, Brummelman, E, Chmitorz, A, Fernàndez, G, Fiebach, CJ, Galatzer-Levy, I, Geuze, E, Groppa, S, Helmreich, I, Hendler, T, Hermans, EJ, Jovanovic, T, Kubiak, T, Lieb, K, Lutz, B, Müller, MB, Murray, RJ, Nievergelt, CM, Reif, A, Roelofs, K, Rutten, BPF, Sander, D, Schick, A, Tüscher, O, Diest, IV, van Harmelen, A-L, Veer, IM, Vermetten, E, Vinkers, CH, Wager, TD, Walter, H, Wessa, M, Wibral, M and Kleim, B (2017) The resilience framework as a strategy to combat stress-related disorders. Nature Human Behaviour 1, 784790.
Kessler, H, Traue, H and Wiswede, D (2011) Why we still don't understand the depressed brain – not going beyond snapshots. GMS Psycho-Social-Medicine 8, 16.
Klein, DN, Glenn, CR, Kosty, DB, Seeley, JR, Rohde, P and Lewinsohn, PM (2013) Predictors of first lifetime onset of major depressive disorder in young adulthood. Journal of abnormal psychology 122, 16.
Kozák, LR, van Graan, LA, Chaudhary, UJ, Szabó, ÁG and Lemieux, L (2017) ICN_atlas: automated description and quantification of functional MRI activation patterns in the framework of intrinsic connectivity networks. NeuroImage 163, 319341.
Lai, C-H (2014) Patterns of cortico-limbic activations during visual processing of sad faces in depression patients: a coordinate-based meta-analysis. The Journal of Neuropsychiatry and Clinical Neurosciences 26, 3443.
Laux, L, Glanzmann, P, Schaffner, P and Spielberger, CD (1981) STAI State-Trait-Angstinventar, 1st Edn. Beltz Test: Weinheim.
Lehrl, S, Triebig, G and Fischer, B (1995) Multiple choice vocabulary test MWT as a valid and short test to estimate premorbid intelligence. Acta Neurologica Scandinavica 91, 335345.
Li, X, Sundquist, K, Hemminki, K and Sundquist, J (2008) Familial risks for depression among siblings based on hospitalizations in Sweden. Psychiatric Genetics 18, 8084.
Marchetti, I, Koster, EHW, Sonuga-Barke, EJ and Raedt, RD (2012) The default mode network and recurrent depression: a neurobiological model of cognitive risk factors. Neuropsychology Review 22, 229251.
Mayberg, HS (1997) Limbic-cortical dysregulation: a proposed model of depression. The Journal of Neuropsychiatry and Clinical Neurosciences 9, 471481.
McLaren, DG, Ries, ML, Xu, G and Johnson, SC (2012) A generalized form of context-dependent psychophysiological interactions (gPPI): a comparison to standard approaches. NeuroImage 61, 12771286.
Meyer-Lindenberg, A and Weinberger, DR (2006) Intermediate phenotypes and genetic mechanisms of psychiatric disorders. Nature Reviews Neuroscience 7, 818827.
Motzkin, JC, Philippi, CL, Wolf, RC, Baskaya, MK and Koenigs, M (2015) Ventromedial prefrontal cortex is critical for the regulation of amygdala activity in humans. Biological Psychiatry 77, 276284.
Munafò, MR, Brown, SM and Hariri, AR (2008) Serotonin transporter (5-HTTLPR) genotype and amygdala activation: a meta-analysis. Biological Psychiatry 63, 852857.
Pezawas, L, Meyer-Lindenberg, A, Drabant, EM, Verchinski, BA, Munoz, KE, Kolachana, BS, Egan, MF, Mattay, VS, Hariri, AR and Weinberger, DR (2005) 5-HTTLPR polymorphism impacts human cingulate-amygdala interactions: a genetic susceptibility mechanism for depression. Nature Neuroscience 8, 828834.
Phillips, ML, Ladouceur, CD and Drevets, WC (2008) A neural model of voluntary and automatic emotion regulation: implications for understanding the pathophysiology and neurodevelopment of bipolar disorder. Molecular Psychiatry 13, 833857.
Sacher, J, Neumann, J, Fünfstück, T, Soliman, A, Villringer, A and Schroeter, ML (2012) Mapping the depressed brain: a meta-analysis of structural and functional alterations in major depressive disorder. Journal of Affective Disorders 140, 142148.
Schardt, DM, Erk, S, Nüsser, C, Nöthen, MM, Cichon, S, Rietschel, M, Treutlein, J, Goschke, T and Walter, H (2010) Volition diminishes genetically mediated amygdala hyperreactivity. NeuroImage 53, 943951.
Singh, MK, Leslie, SM, Bhattacharjee, K, Gross, M, Weisman, EF, Soudi, LM, Phillips, OR and Onopa, A (2018 a) Vulnerabilities in sequencing and task switching in healthy youth offspring of parents with mood disorders. Journal of Clinical and Experimental Neuropsychology 40, 606618.
Singh, MK, Leslie, SM, Packer, MM, Weisman, EF and Gotlib, IH (2018 b) Limbic intrinsic connectivity in depressed and high-risk youth. Journal of the American Academy of Child & Adolescent Psychiatry 57, 775785.e3.
Sullivan, PF, Neale, MC and Kendler, KS (2000) Genetic epidemiology of major depression: review and meta-analysis. American Journal of Psychiatry 157, 15521562.
Trevino, K, McClintock, SM, McDonald Fischer, N, Vora, A and Husain, MM (2014) Defining treatment-resistant depression: a comprehensive review of the literature. Annals of Clinical Psychiatry 26, 222232.
Wackerhagen, C, Wüstenberg, T, Mohnke, S, Erk, S, Veer, IM, Kruschwitz, JD, Garbusow, M, Romund, L, Otto, K, Schweiger, JI, Tost, H, Heinz, A, Meyer-Lindenberg, A, Walter, H and Romanczuk-Seiferth, N (2017) Influence of familial risk for depression on cortico-limbic connectivity during implicit emotional processing. Neuropsychopharmacology 42, 17291738.
Wilde, A, Chan, H-N, Rahman, B, Meiser, B, Mitchell, PB, Schofield, PR and Green, MJ (2014) A meta-analysis of the risk of major affective disorder in relatives of individuals affected by major depressive disorder or bipolar disorder. Journal of Affective Disorders 158, 3747.
Wittchen, H-U, Wunderlich, U, Gruschwitz, S and Zaudig, M (1997) SKID I. Strukturiertes Klinisches Interview für DSM-IV. Achse I: Psychische Störungen. Interviewheft und Beurteilungsheft. Eine deutschsprachige, erweiterte Bearb. d. amerikanischen Originalversion des SKID I . Göttingen: Hogrefe.
Wolf, RC, Philippi, CL, Motzkin, JC, Baskaya, MK and Koenigs, M (2014) Ventromedial prefrontal cortex mediates visual attention during facial emotion recognition. Brain 137, 17721780.
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.
Zilles, K, Schleicher, A, Palomero-Gallagher, N and Amunts, K (2002) Quantitative analysis of cyto- and receptor architecture of the human brain. In Toga, AW and Mazziotta, JC (eds), Brain Mapping: The Methods, 2nd Edn. San Diego: Academic Press, pp. 573602.


Type Description Title
Supplementary materials

Wackerhagen et al. supplementary material
Wackerhagen et al. supplementary material

 Word (10.0 MB)
10.0 MB

Amygdala functional connectivity in major depression – disentangling markers of pathology, risk and resilience

  • Carolin Wackerhagen (a1), Ilya M. Veer (a1), Susanne Erk (a1), Sebastian Mohnke (a1), Tristram A. Lett (a1) (a2), Torsten Wüstenberg (a1), Nina Y. Romanczuk-Seiferth (a1), Kristina Schwarz (a3), Janina I. Schweiger (a3), Heike Tost (a3), Andreas Meyer-Lindenberg (a3), Andreas Heinz (a1) and Henrik Walter (a1)...


Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed