Cingulate prediction of response to antidepressant and cognitive behavioral therapies for depression: Meta-analysis and empirical application

Aromataris, E., & Pearson, A. (2014). The systematic review: an overview. AJN The American Journal of Nursing, 114(3), 53.

Google Scholar 

Beck, A., Steer, R., & Brown, G. (1996). Manual for the Beck depression inventory-II (BDI-II). https://www.scienceopen.com/document?vid=9feb932d-1f91-4ff9-9d27-da3bda716129

Beck, A. T., Rush, J., Shaw, A., B. F., & Emery, G. (1979). Cognitive therapy of Depression. Guilford Press.

Brown, C., Schulberg, H. C., & Madonia, M. J. (1995). Assessment depression in primary care practice with the Beck Depression Inventory and the Hamilton Rating Scale for Depression. Psychological Assessment, 7(1), 59–65.

Google Scholar 

Button, K. S., Ioannidis, J. P. A., Mokrysz, C., Nosek, B. A., Flint, J., Robinson, E. S. J., & Munafò, M. R. (2013). Power failure: why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience, 14(5), 365–376.

Google Scholar 

Carter, C. S., Lesh, T. A., & Barch, D. M. (2016). Thresholds, Power, and sample sizes in clinical neuroimaging. Biological Psychiatry Cognitive Neuroscience and Neuroimaging, 1(2), 99–100.

Google Scholar 

Chen, C. H., Ridler, K., Suckling, J., Williams, S., Fu, C. H. Y., Merlo-Pich, E., & Bullmore, E. (2007). Brain imaging correlates of depressive symptom severity and predictors of symptom improvement after antidepressant treatment. Biological Psychiatry, 62(5), 407–414.

Google Scholar 

Cohen, S. E., Zantvoord, J. B., Wezenberg, B. N., Bockting, C. L. H., & van Wingen, G. A. (2021). Magnetic resonance imaging for individual prediction of treatment response in major depressive disorder: a systematic review and meta-analysis. Translational Psychiatry, 11(1), 168.

Google Scholar 

Costafreda, S. G., Khanna, A., Mourao-Miranda, J., & Fu, C. H. Y. (2009). Neural correlates of sad faces predict clinical remission to cognitive behavioural therapy in depression. Neuroreport, 20(7), 637–641.

Google Scholar 

Cremers, H. R., Wager, T. D., & Yarkoni, T. (2017). The relation between statistical power and inference in fMRI. PloS One, 12(11), e0184923.

Google Scholar 

Delgado, M. R., Miller, M. M., Inati, S., & Phelps, E. A. (2005). An fMRI study of reward-related probability learning. Neuroimage, 24(3), 862–873.

Google Scholar 

Delgado, M. R., Stenger, V. A., & Fiez, J. A. (2004). Motivation-dependent responses in the human caudate nucleus. Cerebral Cortex, 14(9), 1022–1030.

Google Scholar 

DeRubeis, R. J., Siegle, G. J., & Hollon, S. D. (2008). Cognitive therapy versus medication for depression: treatment outcomes and neural mechanisms. Nature Reviews Neuroscience, 9(10), 788–796.

Google Scholar 

Dichter, G. S., Felder, J. N., & Smoski, M. J. (2010). The effects of brief behavioral activation therapy for Depression on cognitive control in affective contexts: an fMRI investigation. Journal of Affective Disorders, 126(1–2), 236–244.

Google Scholar 

Doerig, N., Krieger, T., Altenstein, D., Schlumpf, Y., Spinelli, S., Späti, J., Brakowski, J., Quednow, B. B., Seifritz, E., & Holtforth, M. G. (2016). Amygdala response to self-critical stimuli and symptom improvement in psychotherapy for depression. The British Journal of Psychiatry: The Journal of Mental Science, 208(2), 175–181.

Google Scholar 

Dozois, D. J. A., Dobson, K. S., & Ahnberg, J. L. (1998). A psychometric evaluation of the Beck Depression Inventory–II. Psychological Assessment, 10(2), 83.

Google Scholar 

Dunlop, B. W., Rajendra, J. K., Craighead, W. E., Kelley, M. E., McGrath, C. L., Choi, K. S., Kinkead, B., Nemeroff, C. B., & Mayberg, H. S. (2017). Functional connectivity of the Subcallosal Cingulate Cortex and Differential Outcomes to Treatment with cognitive-behavioral therapy or antidepressant medication for major depressive disorder. The American Journal of Psychiatry, 174(6), 533–545.

Google Scholar 

First, M. B., Spitzer, R. L., Gibbon, M., & Williams, J. B. W. (1995). Structured Clinical Interview for DSM-IV Axis I Disorders (SCID). New York, New York State Psychiatric Institute. Biometrics Research.

Fonseka, T. M., MacQueen, G. M., & Kennedy, S. H. (2018). Neuroimaging biomarkers as predictors of treatment outcome in major depressive disorder. Journal of Affective Disorders, 233, 21–35.

Google Scholar 

Forbes, E. E., Olino, T. M., Ryan, N. D., Birmaher, B., Axelson, D., Moyles, D. L., & Dahl, R. E. (2010). Reward-related brain function as a predictor of treatment response in adolescents with major depressive disorder. Cognitive Affective & Behavioral Neuroscience, 10(1), 107–118.

Google Scholar 

Fu, C. H. Y., Williams, S. C. R., Cleare, A. J., Scott, J., Mitterschiffthaler, M. T., Walsh, N. D., Donaldson, C., Suckling, J., Andrew, C., Steiner, H., & Murray, R. M. (2008). Neural responses to sad facial expressions in major depression following cognitive behavioral therapy. Biological Psychiatry, 64(6), 505–512.

Google Scholar 

Fu, Steiner, H., & Costafreda, S. G. (2013). Predictive neural biomarkers of clinical response in depression: a meta-analysis of functional and structural neuroimaging studies of pharmacological and psychological therapies. Neurobiology of Disease, 52, 75–83.

Google Scholar 

Godlewska, B. R., Browning, M., Norbury, R., Igoumenou, A., Cowen, P. J., & Harmer, C. J. (2018). Predicting Treatment Response in Depression: the role of Anterior Cingulate Cortex. The International Journal of Neuropsychopharmacology / Official Scientific Journal of the Collegium Internationale Neuropsychopharmacologicum, 21(11), 988–996.

Google Scholar 

Greenberg, T., Fournier, J. C., Stiffler, R., Chase, H. W., Almeida, J. R., Aslam, H., Deckersbach, T., Cooper, C., Toups, M. S., Carmody, T., Kurian, B., Peltier, S., Adams, P., McInnis, M. G., Oquendo, M. A., Fava, M., Parsey, R., McGrath, P. J., Weissman, M., & Phillips, M. L. (2020). Reward related ventral striatal activity and differential response to sertraline versus placebo in depressed individuals. Molecular Psychiatry, 25(7), 1526–1536.

Google Scholar 

Hagen, B. (2007). Measuring melancholy: a critique of the Beck Depression Inventory and its use in mental health nursing. International Journal of Mental Health Nursing, 16(2), 108–115.

Google Scholar 

Hamilton, Etkin, A., Furman, D. J., Lemus, M. G., Johnson, R. F., & Gotlib, I. H. (2012). Functional neuroimaging of major depressive disorder: a meta-analysis and new integration of base line activation and neural response data. The American Journal of Psychiatry, 169(7), 693–703.

Google Scholar 

Hamilton, J. P., Hamilton, P., Glover, J., Hsu, G. H., Johnson, J. J., R. F., & Gotlib, I. H. (2010). Modulation of subgenual anterior cingulate cortex activity with real-time neurofeedback. Human Brain Mapping, 32(1), 22–31.

Google Scholar 

Hamilton, M. (1960). A rating scale for depression. Journal of Neurology Neurosurgery and Psychiatry, 23, 56–62.

Google Scholar 

Harmer, C. J. (2014). Neural predictors of treatment response in Depression. Current Behavioral Neuroscience Reports, 1(3), 125–133.

Google Scholar 

Hollon, S. D., Thase, M. E., & Markowitz, J. C. (2002). Treatment and Prevention of Depression. Psychological Science in the Public Interest: A Journal of the American Psychological Society, 3(2), 39–77.

Google Scholar 

Insel, T. R. (2014). The NIMH Research Domain Criteria (RDoC) Project: precision medicine for psychiatry. The American Journal of Psychiatry, 171(4), 395–397.

Google Scholar 

Janiri, D., Moser, D. A., Doucet, G. E., Luber, M. J., Rasgon, A., Lee, W. H., Murrough, J. W., Sani, G., Eickhoff, S. B., & Frangou, S. (2019). Shared Neural Phenotypes for Mood and Anxiety Disorders: A Meta-analysis of 226 Task-Related Functional Imaging Studies.JAMA Psychiatry,1–8.

Jarrett, R. B., Minhajuddin, A., Gershenfeld, H., Friedman, E. S., & Thase, M. E. (2013). Preventing depressive relapse and recurrence in higher-risk cognitive therapy responders: a randomized trial of continuation phase cognitive therapy, fluoxetine, or matched pill placebo. JAMA Psychiatry, 70(11), 1152–1160.

Google Scholar 

Kang, S. G., & Cho, S. E. (2020). Neuroimaging biomarkers for Predicting Treatment Response and recurrence of major depressive disorder. International Journal of Molecular Sciences, 21(6), https://doi.org/10.3390/ijms21062148.

Langenecker, S. A., Crane, N. A., Jenkins, L. M., Phan, K. L., & Klumpp, H. (2018). Pathways to Neuroprediction: Opportunities and challenges to prediction of treatment response in depression. Current Behavioral Neuroscience Reports, 5(1), 48–60.

Google Scholar 

Makovac, E., Fagioli, S., Rae, C. L., Critchley, H. D., & Ottaviani, C. (2020). Can’t get it off my brain: Meta-analysis of neuroimaging studies on perseverative cognition. In Psychiatry Research: Neuroimaging (Vol. 295, p. 111020). https://doi.org/10.1016/j.pscychresns.2019.111020

Marwood, L., Wise, T., Perkins, A. M., & Cleare, A. J. (2018). Meta-analyses of the neural mechanisms and predictors of response to psychotherapy in depression and anxiety. Neuroscience and Biobehavioral Reviews, 95, 61–72.

Google Scholar 

Mayberg, H. S., Brannan, S. K., Mahurin, R. K., Jerabek, P. A., Brickman, J. S., Tekell, J. L., Silva, A., McGinnis, J., Glass, S., Martin, T. G., C. C., & Fox, P. T. (1997). Cingulate function in depression. Neuroreport, 8(4), 1057–1061.

Google Scholar 

Miller, J. M., Schneck, N., Siegle, G. J., Chen, Y., Ogden, R. T., Kikuchi, T., Oquendo, M. A., Mann, J. J., & Parsey, R. V. (2013). fMRI response to negative words and SSRI treatment outcome in major depressive disorder: a preliminary study. Psychiatry Research, 214(3), 296–305.

Google Scholar 

Morere, J. F. (2012). Oncology in 2012: from personalized medicine to precision medicine. Targeted Oncology, 7(4), 211–212.

Google Scholar 

Nolen-Hoeksema, S. (1991). Responses to depression and their effects on the duration of depressive episodes. Journal of Abnormal Psychology, 100(4), 569–582.

Google Scholar 

Nord, C. L., Barrett, L. F., Lindquist, K. A., Ma, Y., Marwood, L., Satpute, A. B., & Dalgleish, T. (2021). Neural effects of antidepressant medication and psychological treatments: a quantitative synthesis across three meta-analyses. The British Journal of Psychiatry: The Journal of Mental Science, 219(4), 546–550.

Google Scholar 

Owen, A. M. (1992). National adult reading test, 2nd Edition. Hazel E. Nelson with Jonathan Willison. 1991, NFER-Nelson. Price: £45 VAT. No. of pages: 23. In International Journal of Geriatric Psychiatry (Vol. 7, Issue 7, pp. 533–533). https://doi.org/10.1002/gps.930070713

Picó-Pérez, M., Radua, J., Steward, T., Menchón, J. M., & Soriano-Mas, C. (2017). Emotion regulation in mood and anxiety disorders: a meta-analysis of fMRI cognitive reappraisal studies. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 79(Pt B), 96–104.

Google Scholar 

Pizzagalli. (2011). Frontocingulate dysfunction in depression: toward biomarkers of treatment response. Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology, 36(1), 183–206.

Google Scholar 

Pizzagalli, D. A., Holmes, A. J., Dillon, D. G., Goetz, E. L., Birk, L., Bogdan, R., Dougherty, D. D., Iosifescu, D. V., Rauch, S. L., & Fava, M. (2009). Reduced caudate and nucleus accumbens response to rewards in unmedicated individuals with major depressive disorder. The American Journal of Psychiatry, 166(6), 702–710.

Google Scholar 

Pizzagalli, Pascual-Marqui, R. D., Nitschke, J. B., Oakes, T. R., Larson, C. L., Abercrombie, H. C., Schaefer, S. M., Koger, J. V., Benca, R. M., & Davidson, R. J. (2001). Anterior cingulate activity as a predictor of degree of treatment response in major depression: evidence from brain electrical tomography analysis. The American Journal of Psychiatry, 158(3), 405–415.

Google Scholar 

Poldrack, R. A., Baker, C. I., Durnez, J., Gorgolewski, K. J., Matthews, P. M., Munafò, M. R., Nichols, T. E., Poline, J. B., Vul, E., & Yarkoni, T. (2017). Scanning the horizon: towards transparent and reproducible neuroimaging research. Nature Reviews Neuroscience, 18(2), 115–126.

Google Scholar 

Queirazza, F., Fouragnan, E., Steele, J. D., Cavanagh, J., & Philiastides, M. G. (2019). Neural correlates of weighted reward prediction error during reinforcement learning classify response to cognitive behavioral therapy in depression. Science Advances, 5(7), eaav4962.

Google Scholar 

Ritchey, M., Dolcos, F., Eddington, K. M., Strauman, T. J., & Cabeza, R. (2011). Neural correlates of emotional processing in depression: changes with cognitive behavioral therapy and predictors of treatment response. Journal of Psychiatric Research, 45(5), 577–587.

Google Scholar 

Roy, M., Harvey, P. O., Berlim, M. T., Mamdani, F., Beaulieu, M. M., Turecki, G., & Lepage, M. (2010). Medial prefrontal cortex activity during memory encoding of pictures and its relation to symptomatic improvement after citalopram treatment in patients with major depression. Journal of Psychiatry & Neuroscience: JPN, 35(3), 152–162.

Google Scholar 

Ruhé, H. G., Booij, J., Veltman, D. J., Michel, M. C., & Schene, A. H. (2012). Successful pharmacologic treatment of major depressive disorder attenuates amygdala activation to negative facial expressions: a functional magnetic resonance imaging study. The Journal of Clinical Psychiatry, 73(4), 451.

Google Scholar 

Rush, A. J., Carmody, T. J., Ibrahim, H. M., Trivedi, M. H., Biggs, M. M., Shores-Wilson, K., Crismon, M. L., Toprac, M. G., & Kashner, T. M. (2006). Comparison of self-report and clinician ratings on two inventories of depressive symptomatology. Psychiatric Services, 57(6), 829–837.

Google Scholar 

Sankar, A., Melin, A., Lorenzetti, V., Horton, P., Costafreda, S. G., & Fu, C. H. Y. (2018). A systematic review and meta-analysis of the neural correlates of psychological therapies in major depression. Psychiatry Research Neuroimaging, 279, 31–39.

Google Scholar 

Siegle, G. J., Carter, C. S., & Thase, M. E. (2006). Use of FMRI to predict recovery from unipolar depression with cognitive behavior therapy. The American Journal of Psychiatry, 163(4), 735–738.

Google Scholar 

Siegle, G. J., Thompson, W. K., Collier, A., Berman, S. R., Feldmiller, J., Thase, M. E., & Friedman, E. S. (2012). Toward clinically useful neuroimaging in depression treatment: prognostic utility of subgenual cingulate activity for determining depression outcome in cognitive therapy across studies, scanners, and patient characteristics. Archives of General Psychiatry, 69(9), 913–924.

Google Scholar 

Smoski, M. J., Felder, J., Bizzell, J., Green, S. R., Ernst, M., Lynch, T. R., & Dichter, G. S. (2009). fMRI of alterations in reward selection, anticipation, and feedback in major depressive disorder. Journal of Affective Disorders, 118(1–3), 69–78.

Google Scholar 

Spielberger, C. D. (2010). State-Trait anxiety inventory. The Corsini Encyclopedia of Psychology. https://onlinelibrary.wiley.com/doi/abs/10.1002/9780470479216.corpsy0943

Spies, M., Kraus, C., Geissberger, N., Auer, B., Klöbl, M., Tik, M., Stürkat, I. L., Hahn, A., Woletz, M., Pfabigan, D. M., Kasper, S., Lamm, C., Windischberger, C., & Lanzenberger, R. (2017). Default mode network deactivation during emotion processing predicts early antidepressant response.Translational Psychiatry, 7(1), e1008.

Straub, J., Plener, P. L., Sproeber, N., Sprenger, L., Koelch, M. G., Groen, G., & Abler, B. (2015). Neural correlates of successful psychotherapy of depression in adolescents. Journal of Affective Disorders, 183, 239–246.

Google Scholar 

Sundermann, B., Beverborg, M. O. L., & Pfleiderer, B. (2014). Toward literature-based feature selection for diagnostic classification: a meta-analysis of resting-state fMRI in depression. In Frontiers in Human Neuroscience (Vol. 8). https://doi.org/10.3389/fnhum.2014.00692

Victor, T. A., Furey, M. L., Fromm, S. J., Öhman, A., & Drevets, W. C. (2013). Changes in the neural correlates of implicit emotional face processing during antidepressant treatment in major depressive disorder. The International Journal of Neuropsychopharmacology / Official Scientific Journal of the Collegium Internationale Neuropsychopharmacologicum, 16(10), 2195–2208.

Google Scholar 

Wang, Y. P., & Gorenstein, C. (2013). Psychometric properties of the Beck Depression Inventory-II: a comprehensive review. Revista Brasileira de Psiquiatria (Sao Paulo Brazil: 1999), 35(4), 416–431.

Google Scholar 

Watson, D., Weber, K., Assenheimer, J. S., Clark, L. A., Strauss, M. E., & McCormick, R. A. (1995). Testing a tripartite model: I. evaluating the convergent and discriminant validity of anxiety and

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