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Neuroplasticity in cognitive and psychological mechanisms of depression: an integrative model

Abstract

Chronic stress and depressive-like behaviors in basic neuroscience research have been associated with impairments of neuroplasticity, such as neuronal atrophy and synaptic loss in the medial prefrontal cortex (mPFC) and hippocampus. The current review presents a novel integrative model of neuroplasticity as a multi-domain neurobiological, cognitive, and psychological construct relevant in depression and other related disorders of negative affect (e.g., anxiety). We delineate a working conceptual model in which synaptic plasticity deficits described in animal models are integrated and conceptually linked with human patient findings from cognitive science and clinical psychology. We review relevant reports including neuroimaging findings (e.g., decreased functional connectivity in prefrontal-limbic circuits), cognitive deficits (e.g., executive function and memory impairments), affective information processing patterns (e.g., rigid, negative biases in attention, memory, interpretations, and self-associations), and patient-reported symptoms (perseverative, inflexible thought patterns; inflexible and maladaptive behaviors). Finally, we incorporate discussion of integrative research methods capable of building additional direct empirical support, including using rapid-acting treatments (e.g., ketamine) as a means to test this integrative model by attempting to simultaneously reverse these deficits across levels of analysis.

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Fig. 1: Regions with prominent neuroplasticity deficits in animal models of depression [4, 5] (in green) and functionally interconnected regions within a cortico-mesolimbic circuit relevant to mood regulation (blue).

References

  1. Chisholm D, Sweeny K, Sheehan P, Rasmussen B, Smit F, Cuijpers P, et al. Scaling-up treatment of depression and anxiety: a global return on investment analysis. Lancet Psychiatry. 2016;3:415–24.

    PubMed  Google Scholar 

  2. Wang PS, Lane M, Olfson M, Pincus HA, Wells KB, Kessler RC. Twelve-month use of mental health services in the United States: results from the National Comorbidity Survey Replication. Arch Gen Psychiatry. 2005;62:629–40.

    PubMed  Google Scholar 

  3. Abdallah CG, Sanacora G, Duman RS, Krystal JH. Ketamine and rapid-acting antidepressants: a window into a new neurobiology for mood disorder therapeutics. Annu Rev Med. 2015;66:509–23.

    CAS  PubMed  Google Scholar 

  4. Duman RS, Aghajanian GK, Sanacora G, Krystal JH. Synaptic plasticity and depression: new insights from stress and rapid-acting antidepressants. Nat Med. 2016;22:238–49.

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Duman RS, Aghajanian GK. Synaptic dysfunction in depression: potential therapeutic targets. Science. 2012;338:68–72.

    CAS  PubMed  PubMed Central  Google Scholar 

  6. Kashdan TB, Rottenberg J. Psychological flexibility as a fundamental aspect of health. Clin Psychol Rev. 2010;30:865–78.

    PubMed  PubMed Central  Google Scholar 

  7. Joormann J. Cognitive inhibition and emotion regulation in depression. Curr Dir Psychol Sci. 2010;19:161–6.

    Google Scholar 

  8. Disner S, Beevers C, Haigh EAP, Beck AT. Neural mechanisms of the cognitive model of depression. Nat Rev Neurosci. 2011;12:467–77.

    CAS  PubMed  Google Scholar 

  9. Beck AT, Bredemeier K. A unified model of depression: integrating clinical, cognitive, biological, and evolutionary perspectives. Clin Psychol Sci. 2016;4:596–619.

    Google Scholar 

  10. Moda-Sava RN, Murdock MH, Parekh PK, Fetcho RN, Huang BS, Huynh TN, et al. Sustained rescue of prefrontal circuit dysfunction by antidepressant-induced spine formation. Science. 2019;364:eaat8078.

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Murrough JW, Iosifescu DV, Chang LC, Al Jurdi RK, Green CM, Perez AM, et al. Antidepressant efficacy of ketamine in treatment-resistant major depression: a two-site randomized controlled trial. Am J Psychiatry. 2013;170:1134–42.

    PubMed  PubMed Central  Google Scholar 

  12. Xu Y, Hackett M, Carter G, Loo C, Galvez V, Glozier N, et al. Effects of low-dose and very low-dose dose ketamine among patients with major depression: a systematic review and meta-analysis. Int J Neuropsychopharmacol. 2015;19:pyv124.

    PubMed Central  Google Scholar 

  13. Beurel E, Nemeroff CB. Interaction of stress, corticotropin-releasing factor, arginine vasopressin and behaviour. Curr Top Behav Neurosci. 2014;18:67–80.

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Luscher B, Fuchs T. GABAergic control of depression-related brain states. Adv Pharmacol. 2015;73:97–144.

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Waters RP, Rivalan M, Bangasser DA, Deussing JM, Ising M, Wood SK, et al. Evidence for the role of corticotropin-releasing factor in major depressive disorder. Neurosci Biobehav Rev. 2015;58:63–78.

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Fee C, Banasr M, Sibille E. Somatostatin-positive gamma-aminobutyric acid interneuron deficits in depression: cortical microcircuit and therapeutic perspectives. Biol Psychiatry. 2017;82:549–59.

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Wohleb ES, Franklin T, Iwata M, Duman RS. Integrating neuroimmune systems in the neurobiology of depression. Nat Rev Neurosci. 2016;17:497–511.

    CAS  PubMed  Google Scholar 

  18. McEwen BS, Nasca C, Gray JD. Stress effects on neuronal structure: hippocampus, amygdala, and prefrontal cortex. Neuropsychopharmacology. 2016;41:3–23.

    CAS  PubMed  Google Scholar 

  19. Anacker C, Hen R. Adult hippocampal neurogenesis and cognitive flexibility—linking memory and mood. Nat Rev Neurosci. 2017;18:335–46.

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Koo JW, Chaudhury D, Han MH, Nestler EJ. Role of mesolimbic brain-derived neurotrophic factor in depression. Biol Psychiatry. 2019;86:738–48.

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Cathomas F, Murrough JW, Nestler EJ, Han MH, Russo SJ. Neurobiology of Resilience: interface between mind and body. Biol Psychiatry. 2019;86:410–20.

    PubMed  PubMed Central  Google Scholar 

  22. Duman RS, Sanacora G, Krystal JH. Altered connectivity in depression: GABA and glutamate neurotransmitter deficits and reversal by novel treatments. Neuron. 2019;102:75–90.

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Arnone D. Functional MRI findings, pharmacological treatment in major depression and clinical response. Prog Neuropsychopharmacol Biol Psychiatry. 2019;91:28–37.

    CAS  PubMed  Google Scholar 

  24. Castrén E. Is mood Chem? Nat Rev Neurosci. 2005;6:241–6.

    PubMed  Google Scholar 

  25. Castren E, Hen R. Neuronal plasticity and antidepressant actions. Trends Neurosci. 2013;36:259–67.

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Changeaux JP, Danchin A. Selective stabilisation of developing synapses as a mechanism for the specification of neuronal networks. Nature. 1976;264:705–12.

    Google Scholar 

  27. Wang Q, Timberlake MA 2nd, Prall K, Dwivedi Y. The recent progress in animal models of depression. Prog Neuropsychopharmacol Biol Psychiatry. 2017;77:99–109.

    PubMed  PubMed Central  Google Scholar 

  28. Ota K, Liu R, Voleti B, Maldonado-Aviles J, Duric V, Iwata M, et al. REDD1 is essential for stress-induced synaptic loss and depressive behavior. Nat Med. 2014;20:531–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Wohleb ES, Terwilliger R, Duman CH, Duman RS. Stress-induced neuronal colony stimulating factor 1 provokes microglia-mediated neuronal remodeling and depressive-like behavior. Biol Psychiatry. 2018;83:38–49.

    CAS  PubMed  Google Scholar 

  30. Roozendaal B, McEwen BS, Chattarji S. Stress, memory and the amygdala. Nat Rev Neurosci. 2009;10:423–33.

    CAS  PubMed  Google Scholar 

  31. Patel D, Anilkumar S, Chattarji S, Buwalda B. Repeated social stress leads to contrasting patterns of structural plasticity in the amygdala and hippocampus. Behav Brain Res. 2018;347:314–24.

    CAS  PubMed  Google Scholar 

  32. Caddy C, Amit BH, McCloud TL, Rendell JM, Furukawa TA, McShane R, et al. Ketamine and other glutamate receptor modulators for depression in adults. Cochrane Database Syst Rev. 2015:CD011612.

  33. McCloud TL, Caddy C, Jochim J, Rendell JM, Diamond PR, Shuttleworth C, et al. Ketamine and other glutamate receptor modulators for depression in bipolar disorder in adults. Cochrane Database Syst Rev. 2015:CD011611.

  34. Zanos P, Moaddel R, Morris PJ, Georgiou P, Fischell J, Elmer GI, et al. NMDAR inhibition-independent antidepressant actions of ketamine metabolites. Nature. 2016;533:481–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Li N, Lee B, Liu RJ, Banasr M, Dwyer JM, Iwata M, et al. mTOR-dependent synapse formation underlies the rapid antidepressant effects of NMDA antagonists. Science. 2010;329:959–64.

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Liu RJ, Duman C, Kato T, Hare B, Lopresto D, Bang E, et al. GLYX-13 produces rapid antidepressant responses with key synaptic and behavioral effects distinct from ketamine. Neuropsychopharmacology. 2017;42:1231–42.

    CAS  PubMed  Google Scholar 

  37. Burgdorf J, Zhang XL, Nicholson KL, Balster RL, Leander JD, Stanton PK, et al. GLYX-13, a NMDA receptor glycine-site functional partial agonist, induces antidepressant-like effects without ketamine-like side effects. Neuropsychopharmacology. 2013;38:729–42.

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Newport DJ, Carpenter LL, McDonald WM, Potash JB, Tohen M, Nemeroff CB, et al. Ketamine and other NMDA antagonists: early clinical trials and possible mechanisms in depression. Am J Psychiatry. 2015;172:950–66.

    PubMed  Google Scholar 

  39. Abdallah C, Averill L, Gueorguieva R, Goktas S, Purohit P, Ranganathan M, et al. Rapamycin, an immunosuppressant and mTORC1 inhibitor, triples the antidepressant response rate to ketamine at two weeks following treatment. 2018. https://doi.org/10.1101/500959.

  40. Sen S, Duman R, Sanacora G. Serum brain-derived neurotrophic factor, depression, and antidepressant medications: meta-analyses and implications. Biol Psychiatry. 2008;64:527–32.

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Kang HJ, Voleti B, Hajszan T, Rajkowska G, Stockmeier CA, Licznerski P, et al. Decreased expression of synapse-related genes and loss of synapses in major depressive disorder. Nat Med. 2012;18:1413–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Price RB, Eldreth DA, Mohlman J. Deficient prefrontal attentional control in late-life generalized anxiety disorder: an fMRI investigation. Transl Psych. 2011;1:e46.

    CAS  Google Scholar 

  43. Price RB, Allen KB, Silk JS, Ladouceur CD, Ryan ND, Dahl RE, et al. Vigilance in the laboratory predicts avoidance in the real world: a dimensional analysis of neural, behavioral, and ecological momentary data in anxious youth. Dev Cogn Neurosci. 2016;19:128–36.

    PubMed  PubMed Central  Google Scholar 

  44. Siegle GJ, Thompson W, Carter CS, Steinhauer SR, Thase ME. Increased amygdala and decreased dorsolateral prefrontal BOLD responses in unipolar depression: related and independent features. Biol Psychiatry. 2007;61:198–209.

    PubMed  Google Scholar 

  45. Gotlib IH, Joormann J. Cognition and depression: current status and future directions. Annu Rev Clin Psychol. 2010;6:285–312.

    PubMed  PubMed Central  Google Scholar 

  46. Dozois D, Beck A. Cognitive schemas, beliefs and assumptions. In: Dobson K, Dozois D, editors. Risk factors in depression. Oxford, England: Elsevier/Academic Press; 2008, p. 121–43.

    Google Scholar 

  47. de Raedt R, Koster EHW. Understanding vulnerability for depression from a cognitive neuroscience perspective: a reappraisal of attentional factors and a new conceptual framework. Cogn Affect Behav Neurosci. 2010;10:50–70.

    PubMed  Google Scholar 

  48. Stange JP, Connolly SL, Burke TA, Hamilton JL, Hamlat EJ, Abramson LY, et al. Inflexible cognition predicts first onset of major depressive episodes in adolescence. Depress Anxiety. 2016;33:1005–12.

    PubMed  PubMed Central  Google Scholar 

  49. Schmaal L, Veltman DJ, van Erp TG, Samann PG, Frodl T, Jahanshad N, et al. Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group. Mol Psychiatry. 2016;21:806–12.

    CAS  PubMed  Google Scholar 

  50. Schmaal L, Hibar DP, Samann PG, Hall GB, Baune BT, Jahanshad N, et al. Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group. Mol Psychiatry. 2017;22:900–9.

    CAS  PubMed  Google Scholar 

  51. Chen G, Guo Y, Zhu H, Kuang W, Bi F, Ai H, et al. Intrinsic disruption of white matter microarchitecture in first-episode, drug-naive major depressive disorder: a voxel-based meta-analysis of diffusion tensor imaging. Prog Neuropsychopharmacol Biol Psychiatry. 2017;76:179–87.

    PubMed  Google Scholar 

  52. Park HJ, Friston K. Structural and functional brain networks: from connectionsto cognition. Science. 2013;342:1238411.

    PubMed  Google Scholar 

  53. Sporns O, Chialvo DR, Kaiser M, Hilgetag CC. Organization, development and function of complex brain networks. Trends Cogn Sci. 2004;8:418–25.

    PubMed  Google Scholar 

  54. Kaiser RH, Andrews-Hanna JR, Wager TD, Pizzagalli DA. Large-Scale network dysfunction in major depressive disorder: a meta-analysis of resting-state functional connectivity. JAMA Psychiatry. 2015;72:603–11.

    PubMed  PubMed Central  Google Scholar 

  55. Abdallah CG, Averill LA, Collins KA, Geha P, Schwartz J, Averill C, et al. Ketamine treatment and global brain connectivity in major depression. Neuropsychopharmacology. 2017;42:1210–9.

    PubMed  PubMed Central  Google Scholar 

  56. Hirshfeld-Becker DR, Gabrieli JDE, Shapero BG, Biederman J, Whitfield-Gabrieli S, Chai XJ. Intrinsic functional brain connectivity predicts onset of major depression disorder in adolescence: a pilot study. Brain Connect. 2019;9:388–98.

    PubMed  PubMed Central  Google Scholar 

  57. Jiang X, Shen Y, Yao J, Zhang L, Xu L, Feng R, et al. Connectome analysis of functional and structural hemispheric brain networks in major depressive disorder. Transl Psychiatry. 2019;9:136.

    PubMed  PubMed Central  Google Scholar 

  58. Greicius MD, Flores BH, Menon V, Glover GH, Solvason HB, Kenna H, et al. Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus. Biol Psychiatry. 2007;62:429–37.

    PubMed  PubMed Central  Google Scholar 

  59. Rive MM, van Rooijen G, Veltman DJ, Phillips ML, Schene AH, Ruhe HG. Neural correlates of dysfunctional emotion regulation in major depressive disorder. A systematic review of neuroimaging studies. Neurosci Biobehav Rev. 2013;37:2529–53.

    PubMed  Google Scholar 

  60. Carballedo A, Scheuerecker J, Meisenzahl E, Schoepf V, Bokde A, Moller HJ, et al. Functional connectivity of emotional processing in depression. J Affect Disord. 2011;134:272–9.

    PubMed  Google Scholar 

  61. Anand A, Li Y, Wang Y, Wu J, Gao S, Bukhari L, et al. Activity and connectivity of brain mood regulating circuit in depression: a functional magnetic resonance study. Biol Psychiatry. 2005;57:1079–88.

    PubMed  Google Scholar 

  62. Ochsner KN, Ray RD, Cooper JC, Robertson ER, Chopra S, Gabrieli JD, et al. For better or for worse: neural systems supporting the cognitive down- and up-regulation of negative emotion. Neuroimage. 2004;23:483–99.

    PubMed  Google Scholar 

  63. Zilverstand A, Parvaz MA, Goldstein RZ. Neuroimaging cognitive reappraisal in clinical populations to define neural targets for enhancing emotion regulation. A systematic review. Neuroimage. 2017;151:105–16.

    PubMed  Google Scholar 

  64. Pico-Perez M, Radua J, Steward T, Menchon JM, Soriano-Mas C. Emotion regulation in mood and anxiety disorders: a meta-analysis of fMRI cognitive reappraisal studies. Prog Neuropsychopharmacol Biol Psychiatry. 2017;79:96–104.

    PubMed  Google Scholar 

  65. Johnstone T, van Reekum CM, Urry HL, Kalin NH, Davidson RJ. Failure to regulate: counterproductive recruitment of top-down prefrontal-subcortical circuitry in major depression. J Neurosci. 2007;27:8877–84.

    CAS  PubMed  PubMed Central  Google Scholar 

  66. Thompson SM, Kallarackal AJ, Kvarta MD, Van Dyke AM, LeGates TA, Cai X. An excitatory synapse hypothesis of depression. Trends Neurosci. 2015;38:279–94.

    CAS  PubMed  PubMed Central  Google Scholar 

  67. Koechlin E. Prefrontal executive function and adaptive behavior in complex environments. Curr Opin Neurobiol. 2016;37:1–6.

    CAS  PubMed  Google Scholar 

  68. Wagner S, Muller C, Helmreich I, Huss M, Tadic A. A meta-analysis of cognitive functions in children and adolescents with major depressive disorder. Eur Child Adolesc Psychiatry. 2015;24:5–19.

    PubMed  Google Scholar 

  69. Wagner S, Doering B, Helmreich I, Lieb K, Tadic A. A meta-analysis of executive dysfunctions in unipolar major depressive disorder without psychotic symptoms and their changes during antidepressant treatment. Acta Psychiatr Scandinavica. 2012;125:281–92.

    CAS  Google Scholar 

  70. McClintock SM, Husain MM, Greer TL, Cullum CM. Association between depression severity and neurocognitive function in major depressive disorder: a review and synthesis. Neuropsychology. 2010;24:9–34.

    PubMed  Google Scholar 

  71. Roca M, Vives M, Lopez-Navarro E, Garcia-Campayo J, Gili M. Cognitive impairments and depression: a critical review. Actas Esp Psiquiatr. 2015;43:187–93.

    PubMed  Google Scholar 

  72. Smith EE, Jonides J. Storage and executive processes in the frontal lobes. Science. 1999;283:1657–61.

    CAS  PubMed  Google Scholar 

  73. Fuster JM. The prefrontal cortex. 3rd edn. Philadelphia, PA: Lippincott-Raven; 1997.

  74. Murrough JW, Iacoviello B, Neumeister A, Charney DS, Iosifescu DV. Cognitive dysfunction in depression: neurocircuitry and new therapeutic strategies. Neurobiol Learn Mem. 2011;96:553–63.

    CAS  PubMed  Google Scholar 

  75. Motter JN, Pimontel MA, Rindskopf D, Devanand DP, Doraiswamy PM, Sneed JR. Computerized cognitive training and functional recovery in major depressive disorder: a meta-analysis. J Affect Disord. 2016;189:184–91.

    PubMed  Google Scholar 

  76. Siegle GJ, Price RB, Jones N, Ghinassi F, Painter T, Thase ME. You gotta work at it: pupillary indices of task focus are prognostic for response to a neurocognitive intervention for depression. Clin Psychol Sci. 2014;2:455–71.

    Google Scholar 

  77. Zhou FC, Wang YY, Zheng W, Zhang Q, Ungvari GS, Ng CH,et al. Prospective memory deficits in patients with depression: a meta-analysis. J Affect Disord. 2017;220:79–85.

    PubMed  Google Scholar 

  78. Van Vreeswijk MF, De Wilde EJ. Autobiographical memory specificity, psychopathology, depressed mood and the use of the autobiographical memory test: a meta analysis. Behav Res Ther. 2004;42:731–43.

  79. Pollock LR, Williams JM. Effective problem solving in suicide attempters depends on specific autobiographical recall. Suicide Life Threat Behav. 2001;31:386–96.

    CAS  PubMed  Google Scholar 

  80. Williams JM, Ellis NC, Tyers C, Healy H, Rose G, MacLeod AK. The specificity of autobiographical memory and imageability of the future. Mem Cogn. 1996;24:116–25.

    CAS  Google Scholar 

  81. McEwen BS, Sapolsky RM. Stress and cognitive function. Curr Opin Neurobiol. 1995;5:205–16.

    CAS  PubMed  Google Scholar 

  82. Mathews A, MacLeod C. Cognitive vulnerability to emotional disorders. Annu Rev Clin Psychol. 2005;1:167–95.

    PubMed  Google Scholar 

  83. Peckham AD, McHugh RK, Otto MW. A meta-analysis of the magnitude of biased attention in depression. Depress Anxiety. 2010;27:1135–42.

    PubMed  Google Scholar 

  84. Gilboa-Schechtman E, Erhard-Weiss D, Jeczemien P. Interpersonal deficits meet cognitive biases: memory for facial expressions in depressed and anxious men and women. Psychiatry Res. 2002;113:279–93.

    PubMed  Google Scholar 

  85. Ridout N, Astell AJ, Reid IC, Glen T, O’Carroll RE. Memory bias for emotional facial expressions in major depression. Cogn Emot. 2003;17:101–22.

    PubMed  Google Scholar 

  86. Hirsch CR, Meeten F, Krahe C, Reeder C. Resolving ambiguity in emotional disorders: the nature and role of interpretation biases. Annu Rev Clin Psychol. 2016;12:281–305.

    PubMed  Google Scholar 

  87. Milders M, Bell S, Platt J, Serrano R, Runcie O. Stable expression recognition abnormalities in unipolar depression. Psychiatry Res. 2010;179:38–42.

    PubMed  Google Scholar 

  88. Persad SM, Polivy J. Differences between depressed and nondepressed individuals in the recognition of and response to facial emotional cues. J Abnorm Psychol. 1993;102:358–68.

    CAS  PubMed  Google Scholar 

  89. van Randenborgh A, Pawelzik M, Quirin M, Kuhl J. Bad roots to grow: deficient implicit self-evaluations in chronic depression with an early onset. J Clin Psychol. 2016;72:580–90.

    PubMed  Google Scholar 

  90. Franck E, De Raedt R, De Houwer J. Implicit but not explicit self-esteem predicts future depressive symptomatology. Behav Res Ther. 2007;45:2448–55.

    PubMed  Google Scholar 

  91. Phillips WJ, Hine DW, Thorsteinsson EB. Implicit cognition and depression: a meta-analysis. Clin Psychol Rev. 2010;30:691–709.

    PubMed  Google Scholar 

  92. Nock MK, Park JM, Finn CT, Deliberto TL, Dour HJ, Banaji MR. Measuring the suicidal mind: implicit cognition predicts suicidal behavior. Psychol Sci. 2010;21:511–7.

    PubMed  Google Scholar 

  93. Cha CB, Najmi S, Park JM, Finn CT, Nock MK. Attentional bias toward suicide-related stimuli predicts suicidal behavior. J Abnorm Psychol. 2010;119:616–22.

    PubMed  PubMed Central  Google Scholar 

  94. Barch DM, Pagliaccio D, Luking K. Mechanisms underlying motivational deficits in psychopathology: similarities and differences in depression and schizophrenia. Curr Top Behav Neurosci. 2016;27:411–49.

    PubMed  Google Scholar 

  95. Chen C, Takahashi T, Nakagawa S, Inoue T, Kusumi I. Reinforcement learning in depression: a review of computational research. Neurosci Biobehav Rev. 2015;55:247–67.

    PubMed  Google Scholar 

  96. Dombrovski AY, Szanto K, Clark L, Aizenstein HJ, Chase HW, Reynolds CF 3rd, et al. Corticostriatothalamic reward prediction error signals and executive control in late-life depression. Psychol Med. 2015;45:1413–24.

    CAS  PubMed  Google Scholar 

  97. Dombrovski AY, Szanto K, Clark L, Reynolds CF, Siegle GJ. Reward signals, attempted suicide, and impulsivity in late-life depression. JAMA Psychiatry. 2013;70:1020–30.

    Google Scholar 

  98. Gradin VB, Kumar P, Waiter G, Ahearn T, Stickle C, Milders M, et al. Expected value and prediction error abnormalities in depression and schizophrenia. Brain. 2011;134:1751–64.

    PubMed  Google Scholar 

  99. Kumar P, Waiter G, Ahearn T, Milders M, Reid I, Steele JD. Abnormal temporal difference reward-learning signals in major depression. Brain. 2008;131:2084–93.

    CAS  PubMed  Google Scholar 

  100. Dombrovski AY, Hallquist MN. The decision neuroscience perspective on suicidal behavior: evidence and hypotheses. Curr Opin Psychiatry. 2017;30:7–14.

    PubMed  PubMed Central  Google Scholar 

  101. Berridge KC. Motivation concepts in behavioral neuroscience. Physiol Behav. 2004;81:179–209.

    CAS  PubMed  Google Scholar 

  102. McGaugh JL. The amygdala modulates the consolidation of memories of emotionally arousing experiences. Annu Rev Neurosci. 2004;27:1–28.

    CAS  PubMed  Google Scholar 

  103. Cahill L, Alkire MT. Epinephrine enhancement of human memory consolidation: interaction with arousal at encoding. Neurobiol Learn Mem. 2003;79:194–8.

    CAS  PubMed  Google Scholar 

  104. Beevers CG, Clasen PC, Enock PM, Schnyer DM. Attention bias modification for major depressive disorder: effects on attention bias, resting state connectivity, and symptom change. J Abnorm Psychol. 2015;124:463–75.

    PubMed  PubMed Central  Google Scholar 

  105. White LK, Sequeira S, Britton JC, Brotman MA, Gold AL, Berman E, et al. Complementary features of attention bias modification therapy and cognitive-behavioral therapy in pediatric anxiety disorders. Am J Psychiatry. 2017;174:775–84.

    PubMed  PubMed Central  Google Scholar 

  106. Mathews A, MacLeod C. Cognitive approaches to emotion and emotional disorders. Annu Rev Psychol. 1994;45:25–50.

    CAS  PubMed  Google Scholar 

  107. MacLeod C. Cognitive bias modification procedures in the management of mental disorders. Curr Opin Psychiatry. 2012;25:114–20.

    PubMed  Google Scholar 

  108. Jones EB, Sharpe L. Cognitive bias modification: a review of meta-analyses. J Affect Disord. 2017;223:175–83.

    PubMed  Google Scholar 

  109. Harmer CJ, Goodwin GM, Cowen PJ. Why do antidepressants take so long to work? A cognitive neuropsychological model of antidepressant drug action. Br J Psychiatry. 2009;195:102–8.

  110. Association AP. Diagnostic and statistical manual of mental disorders. Arlington, VA: American Psychiatric Publishing; 2013.

    Google Scholar 

  111. Nolen-Hoeksema S, Morrow J, Fredrickson BL. Response styles and the duration of episodes of depressed mood. J Abnorm Psychol. 1993;102:20–8.

    CAS  PubMed  Google Scholar 

  112. McEvoy PM, Mahoney AEJ, Moulds ML. Are worry, rumination, and post-event processing one and the same? Development of the repetitive thinking questionnaire. J Anxiety Disord. 2010;24:509–19.

    PubMed  Google Scholar 

  113. Beck JG. Cognitive therapy: basics and beyond. New York, NY: The Guilford Press; 1995.

    Google Scholar 

  114. Beck AT, Dozois DJ. Cognitive therapy: current status and future directions. Annu Rev Med. 2011;62:397–409.

    CAS  PubMed  Google Scholar 

  115. Teasdale JD, Segal ZV, Williams JMG, Ridgeway VA, Soulsby JM, Lau MA. Prevention of relapse/recurrence in major depression by mindfulness-based cognitive therapy. J Consult Clin Psychol. 2000;68:615–23.

    CAS  PubMed  Google Scholar 

  116. Segal ZV, Walsh KM. Mindfulness-based cognitive therapy for residual depressive symptoms and relapse prophylaxis. Curr Opin Psychiatry. 2016;29:7–12.

    PubMed  PubMed Central  Google Scholar 

  117. Segal ZV, Teasdale JD, Williams JMG. Mindfulness-based cognitive therapy: theoretical rationale and empirical status. In: Folette SC, Linehan MM (eds.) Mindfulness and acceptance: Expanding the cognitive-behavioral tradition. New York, NY: Guilford Press; 2004.

  118. Davidson J, Turnbull CD. Diagnostic significance of vegetative symptoms in depression. Br J Psychiatry. 1986;148:442–6.

    CAS  PubMed  Google Scholar 

  119. Dimidjian S, Barrera M Jr., Martell C, Munoz RF, Lewinsohn PM. The origins and current status of behavioral activation treatments for depression. Annu Rev Clin Psychol. 2011;7:1–38.

    PubMed  Google Scholar 

  120. Ratcliffe M. Experiences of Depression: a study in phenomenology. Oxford, UK: Oxford University Press; 2015.

    Google Scholar 

  121. Martell CR, Dimidjian S, Herman-Dunn R. Behavioral activation for depression: a clinician’s guide. New York: The Guilford Press; 2010.

    Google Scholar 

  122. Dimidjian S, Hollon SD, Dobson KS, Schmaling KB, Kohlenberg RJ, Addis ME, et al. Randomized trial of behavioral activation, cognitive therapy, and antidepressant medication in the acute treatment of adults with major depression. J Consult Clin Psychol. 2006;74:658–70.

    PubMed  Google Scholar 

  123. Murrough JW, Collins KA, Fields J, DeWilde KE, Phillips ML, Mathew SJ, et al. Regulation of neural responses to emotion perception by ketamine in individuals with treatment-resistant major depressive disorder. Transl Psychiatry. 2015;5:e509.

    CAS  PubMed  PubMed Central  Google Scholar 

  124. Gartner M, Aust S, Bajbouj M, Fan Y, Wingenfeld K, Otte C, et al. Functional connectivity between prefrontal cortex and subgenual cingulate predicts antidepressant effects of ketamine. Eur Neuropsychopharmacol. 2019;29:501–8.

    PubMed  Google Scholar 

  125. Li CT, Chen MH, Lin WC, Hong CJ, Yang BH, Liu RS, et al. The effects of low-dose ketamine on the prefrontal cortex and amygdala in treatment-resistant depression: A randomized controlled study. Hum Brain Mapp. 2016;37:1080–90.

    PubMed  PubMed Central  Google Scholar 

  126. Ionescu DF, Felicione JM, Gosai A, Cusin C, Shin P, Shapero BG, et al. Ketamine-Associated Brain Changes: a review of the neuroimaging literature. Harv Rev Psychiatry. 2018;26:320–39.

    PubMed  PubMed Central  Google Scholar 

  127. Downey D, Dutta A, McKie S, Dawson GR, Dourish CT, Craig K, et al. Comparing the actions of lanicemine and ketamine in depression: key role of the anterior cingulate. Eur Neuropsychopharmacol. 2016;26:994–1003.

    CAS  PubMed  Google Scholar 

  128. Reed JL, Nugent AC, Furey ML, Szczepanik JE, Evans JW, Zarate CA, Jr. Ketamine normalizes brain activity during emotionally valenced attentional processing in depression. Neuroimage Clin. 2018;20:92–101.

    Google Scholar 

  129. Evans JW, Szczepanik J, Brutsche N, Park LT, Nugent AC, Zarate CA Jr. Default mode connectivity in major depressive disorder measured up to 10 days after ketamine administration. Biol Psychiatry. 2018;84:582–90.

    CAS  PubMed  PubMed Central  Google Scholar 

  130. Jett JD, Boley AM, Girotti M, Shah A, Lodge DJ, Morilak DA. Antidepressant-like cognitive and behavioral effects of acute ketamine administration associated with plasticity in the ventral hippocampus to medial prefrontal cortex pathway. Psychopharmacology. 2015;232:3123–33.

    CAS  PubMed  PubMed Central  Google Scholar 

  131. Nikiforuk A, Popik P. Ketamine prevents stress-induced cognitive inflexibility in rats. Psychoneuroendocrinology. 2014;40:119–22.

    CAS  PubMed  Google Scholar 

  132. Shiroma PR, Albott CS, Johns B, Thuras P, Wels J, Lim KO. Neurocognitive performance and serial intravenous subanesthetic ketamine in treatment-resistant depression. Int J Neuropsychopharmacol. 2014;17:1805–13.

    CAS  PubMed  Google Scholar 

  133. Permoda-Osip A, Kisielewski J, Bartkowska-Sniatkowska A, Rybakowski JK. Single ketamine infusion and neurocognitive performance in bipolar depression. Pharmacopsychiatry. 2015;48:78–9.

    CAS  PubMed  Google Scholar 

  134. Price RB, Iosifescu DV, Murrough JW, Chang LC, Al Jurdi RK, Iqbal SZ, et al. Effects of ketamine on explicit and implicit suicidal cognition: a randomized controlled trial in treatment-resistant depression. Depress Anxiety. 2014;31:335–43.

    CAS  PubMed  PubMed Central  Google Scholar 

  135. Price RB, Nock MK, Charney DS, Mathew SJ. Effects of intravenous ketamine on explicit and implicit measures of suicidality in treatment-resistant depression. Biol Psychiatry. 2009;66:522–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  136. Price RB, Kuckertz JM, Siegle GJ, Ladouceur CD, Silk JS, Ryan ND, et al. Empirical recommendations for improving the stability of the dot-probe task in clinical research. Psychol Assess. 2015;27:365–76.

    PubMed  Google Scholar 

  137. Price RB, Brown V, Siegle GJ. Computational modeling applied to the dot-probe task yields improved reliability and mechanistic insights. Biol Psychiatry. 2019;85:606–12.

    PubMed  Google Scholar 

  138. Rodebaugh TL, Scullin RB, Langer JK, Dixon DJ, Huppert JD, Bernstein A, et al. Unreliability as a threat to understanding psychopathology: the cautionary tale of attentional bias. J Abnorm Psychol. 2016;125:840–51.

    PubMed  PubMed Central  Google Scholar 

  139. Auxéméry Y. Post-traumatic psychiatric disorders: PTSD is not the only diagnosis. Presse Med. 2018;47:423–30.

    PubMed  Google Scholar 

  140. Williams LM. Precision psychiatry: a neural circuit taxonomy for depression and anxiety. Lancet Psychiatry. 2016;3:472–80.

    PubMed  PubMed Central  Google Scholar 

  141. Feder A, Parides MK, Murrough JW, Perez AM, Morgan JE, Saxena S, et al. Efficacy of intravenous ketamine for treatment of chronic posttraumatic stress disorder: a randomized clinical trial. JAMA Psychiatry. 2014;71:681–8.

    CAS  PubMed  Google Scholar 

  142. Glue P, Medlicott NJ, Harland S, Neehoff S, Anderson-Fahey B, Le Nedelec M, et al. Ketamine’s dose-related effects on anxiety symptoms in patients with treatment refractory anxiety disorders. J Psychopharmacol. 2017;31:1302–5.

    CAS  PubMed  Google Scholar 

  143. Price RB, Gates K, Kraynak TE, Thase ME, Siegle GJ. Data-driven subgroups in depression derived from directed functional connectivity paths at rest. Neuropsychopharmacology. 2017;42:2623–32.

    PubMed  PubMed Central  Google Scholar 

  144. Price RB, Lane S, Gates K, Kraynak TE, Horner MS, Thase ME, et al. Parsing heterogeneity in the brain connectivity of depressed and healthy adults during positive mood. Biol Psychiatry. 2017;81:347–57.

    PubMed  Google Scholar 

  145. Langenecker SA, Mickey BJ, Eichhammer P, Sen S, Elverman KH, Kennedy SE, et al. Cognitive control as a 5-HT1A-Based domain that is disrupted in major depressive disorder. Front Psychol. 2019;10:691.

    PubMed  PubMed Central  Google Scholar 

  146. Price RB, Rosen D, Siegle GJ, Ladouceur CD, Tang K, Allen KB, et al. From anxious youth to depressed adolescents: prospective prediction of 2-year depression symptoms via attentional bias measures. J Abnorm Psychol. 2015;125:267–78.

    PubMed  PubMed Central  Google Scholar 

  147. Fried EI, Nesse RM. Depression is not a consistent syndrome: an investigation of unique symptom patterns in the STAR*D study. J Affect Disord. 2014;172C:96–102.

    Google Scholar 

  148. Santarelli L, Saxe M, Gross C, Surget A, Battaglia F, Dulawa S, et al. Requirement of hippocampal neurogenesis for the behavioral effects of antidepressants. Science. 2003;301:805–9.

    CAS  PubMed  Google Scholar 

  149. Hoogendam JM, Ramakers GM, Di Lazzaro V. Physiology of repetitive transcranial magnetic stimulation of the human brain. Brain Stimul. 2010;3:95–118.

    PubMed  Google Scholar 

  150. Dukart J, Regen F, Kherif F, Colla M, Bajbouj M, Heuser I, et al. Electroconvulsive therapy-induced brain plasticity determines therapeutic outcome in mood disorders. Proc Natl Acad Sci USA. 2014;111:1156–61.

    CAS  PubMed  Google Scholar 

  151. Cassilhas RC, Tufik S, de Mello MT. Physical exercise, neuroplasticity, spatial learning and memory. Cell Mol Life Sci. 2016;73:975–83.

    CAS  PubMed  Google Scholar 

  152. Wilkinson S, Holtzheimer PE, Gao S, Kirwin D, Price R. Leveraging neuroplasticity to enhance adaptive learning: the potential for synergistic somatic-behavioral treatment combinations to improve clinical outcomes in depression. Biol Psychiatry. 2019;85:454–65.

    PubMed  Google Scholar 

  153. Cullen KR, Westlund MK, Klimes-Dougan B, Mueller BA, Houri A, Eberly LE, et al. Abnormal amygdala resting-state functional connectivity in adolescent depression. JAMA Psychiatry. 2014;71:1138–47.

    PubMed  PubMed Central  Google Scholar 

  154. Young KD, Zotev V, Phillips R, Misaki M, Drevets WC, Bodurka J. Amygdala real-time functional magnetic resonance imaging neurofeedback for major depressive disorder: a review. Psychiatry Clin Neurosci. 2018;72:466–81.

    PubMed  PubMed Central  Google Scholar 

  155. Young KD, Siegle GJ, Misaki M, Zotev V, Phillips R, Drevets WC, et al. Altered task-based and resting-state amygdala functional connectivity following real-time fMRI amygdala neurofeedback training in major depressive disorder. Neuroimage Clin. 2018;17:691–703.

    PubMed  Google Scholar 

  156. Dell’osso B, Camuri G, Castellano F, Vecchi V, Benedetti M, Bortolussi S, et al. Meta-review of metanalytic studies with repetitive transcranial magnetic stimulation (rTMS) for the treatment of major depression. Clin Pr Epidemiol Ment Health. 2011;7:167–77.

    Google Scholar 

  157. Derryberry D, Reed MA. Anxiety-related attentional biases and their regulation by attentional control. J Abnorm Psychol. 2002;111:225–36.

    PubMed  Google Scholar 

  158. Hsu KJ, Beard C, Rifkin L, Dillon DG, Pizzagalli DA, Bjorgvinsson T. Transdiagnostic mechanisms in depression and anxiety: the role of rumination and attentional control. J Affect Disord. 2015;188:22–7.

    PubMed  PubMed Central  Google Scholar 

  159. Sumner JA. The mechanisms underlying overgeneral autobiographical memory: an evaluative review of evidence for the CaR-FA-X model. Clin Psychol Rev. 2012;32:34–48.

    PubMed  Google Scholar 

  160. Hitchcock C, Werner-Seidler A, Blackwell SE, Dalgleish T. Autobiographical episodic memory-based training for the treatment of mood, anxiety and stress-related disorders: a systematic review and meta-analysis. Clin Psychol Rev. 2017;52:92–107.

    PubMed  Google Scholar 

  161. Clarke PJ, Notebaert L, Macleod C. Absence of evidence or evidence of absence: reflecting on therapeutic implementations of attentional bias modification. BMC Psychiatry. 2014;14:8.

    PubMed  PubMed Central  Google Scholar 

  162. Franklin JC, Fox KR, Franklin CR, Kleiman EM, Ribeiro JD, Jaroszewski AC, et al. A brief mobile app reduces nonsuicidal and suicidal self-injury: evidence from three randomized controlled trials. J Consult Clin Psychol. 2016;84:544–57.

    PubMed  Google Scholar 

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Acknowledgements

This project was supported in part by National Institute of Mental Health grant number R01MH113857 (RBP).

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Price, R.B., Duman, R. Neuroplasticity in cognitive and psychological mechanisms of depression: an integrative model. Mol Psychiatry 25, 530–543 (2020). https://doi.org/10.1038/s41380-019-0615-x

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