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Using model systems to understand errant plasticity mechanisms in psychiatric disorders

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Abstract

In vivo model systems are a critical tool for gaining insight into the pathology underlying psychiatric disorders. Although modern functional imaging tools allow study of brain correlates of behavior in clinical groups and genome-wide association studies are beginning to uncover the complex genetic architecture of psychiatric disorders, there is less understanding of pathology at intervening levels of organization. Several psychiatric disorders derive from pathological neural plasticity, and studying the mechanisms that underlie these processes, including reinforcement learning and spike-timing-dependent plasticity, requires the use of animals. It will be particularly important to understand how individual differences in plasticity mechanisms at a cellular level confer resilience on some but lead to disease in others.

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Figure 1: Reinstatement of fear following the retrieval–extinction procedure.
Figure 2: Reinstatement of nose-poke behavior following acquisition and extinction.
Figure 3: NMDAR antagonists in monkeys replicate both behavioral and neurophysiological features of cognitive deficits in patients with schizophrenia.

References

  1. Slifstein, M. et al. Deficits in prefrontal cortical and extrastriatal dopamine release in schizophrenia: a positron emission tomographic functional magnetic resonance imaging study. JAMA Psychiatry 72, 316–324 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Insel, T.R. From animal models to model animals. Biol. Psychiatry 62, 1337–1339 (2007).

    Article  PubMed  Google Scholar 

  3. Wong, A.H. & Josselyn, S.A. Caution when diagnosing your mouse with schizophrenia: the use and misuse of model animals for understanding psychiatric disorders. Biol. Psychiatry 79, 32–38 (2016).

    Article  PubMed  Google Scholar 

  4. Cosgrove, V.E., Kelsoe, J.R. & Suppes, T. Toward a valid animal model of bipolar disorder: how the research domain criteria help bridge the clinical-basic science divide. Biol. Psychiatry 79, 62–70 (2016).

    Article  PubMed  Google Scholar 

  5. Nestler, E.J. & Hyman, S.E. Animal models of neuropsychiatric disorders. Nat. Neurosci. 13, 1161–1169 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Campbell, I.L. & Gold, L.H. Transgenic modeling of neuropsychiatric disorders. Mol. Psychiatry 1, 105–120 (1996).

    CAS  PubMed  Google Scholar 

  7. Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature 511, 421–427 (2014).

  8. Insel, T.R. & Collins, F.S. Psychiatry in the genomics era. Am. J. Psychiatry 160, 616–620 (2003).

    Article  PubMed  Google Scholar 

  9. Gratten, J., Wray, N.R., Keller, M.C. & Visscher, P.M. Large-scale genomics unveils the genetic architecture of psychiatric disorders. Nat. Neurosci. 17, 782–790 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Sullivan, P.F., Daly, M.J. & O'Donovan, M. Genetic architectures of psychiatric disorders: the emerging picture and its implications. Nat. Rev. Genet. 13, 537–551 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Puzzo, D., Gulisano, W., Palmeri, A. & Arancio, O. Rodent models for Alzheimer's disease drug discovery. Expert Opin. Drug Discov. 10, 703–711 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Franco, R. & Cedazo-Minguez, A. Successful therapies for Alzheimer's disease: why so many in animal models and none in humans? Front. Pharmacol. 5, 146 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  13. Insel, T.R. Rethinking schizophrenia. Nature 468, 187–193 (2010).

    Article  CAS  PubMed  Google Scholar 

  14. Lieberman, J.A. & Stroup, T.S. The NIMH-CATIE schizophrenia study: what did we learn? Am. J. Psychiatry 168, 770–775 (2011).

    Article  PubMed  Google Scholar 

  15. Fernando, A.B. & Robbins, T.W. Animal models of neuropsychiatric disorders. Annu. Rev. Clin. Psychol. 7, 39–61 (2011).

    Article  CAS  PubMed  Google Scholar 

  16. Pine, D.S. & Leibenluft, E. Biomarkers with a mechanistic focus. JAMA Psychiatry 72, 633–634 (2015).

    Article  PubMed  Google Scholar 

  17. Albin, R.L., Young, A.B. & Penney, J.B. The functional anatomy of basal ganglia disorders. Trends Neurosci. 12, 366–375 (1989).

    Article  CAS  PubMed  Google Scholar 

  18. DeLong, M.R. Primate models of movement disorders of basal ganglia origin. Trends Neurosci. 13, 281–285 (1990).

    Article  CAS  PubMed  Google Scholar 

  19. Alexander, G.E., DeLong, M.R. & Strick, P.L. Parallel organization of functionally segregated circuits linking basal ganglia and cortex. Annu. Rev. Neurosci. 9, 357–381 (1986).

    Article  CAS  PubMed  Google Scholar 

  20. Cui, G. et al. Concurrent activation of striatal direct and indirect pathways during action initiation. Nature 494, 238–242 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Kravitz, A.V. et al. Regulation of parkinsonian motor behaviours by optogenetic control of basal ganglia circuitry. Nature 466, 622–626 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Bergman, H., Wichmann, T. & DeLong, M.R. Reversal of experimental parkinsonism by lesions of the subthalamic nucleus. Science 249, 1436–1438 (1990).

    Article  CAS  PubMed  Google Scholar 

  23. Obeso, J.A. et al. Surgical treatment of Parkinson's disease. Baillieres Clin. Neurol. 6, 125–145 (1997).

    CAS  PubMed  Google Scholar 

  24. Wichmann, T. & DeLong, M.R. Deep brain stimulation for movement disorders of basal ganglia origin: restoring function or functionality? Neurotherapeutics 13, 264–283 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Lees, A.J. Unresolved issues relating to the shaking palsy on the celebration of James Parkinson's 250th birthday. Mov. Disord. 22 (Suppl. 17), S327–S334 (2007).

    Article  PubMed  Google Scholar 

  26. Kapur, S., Phillips, A.G. & Insel, T.R. Why has it taken so long for biological psychiatry to develop clinical tests and what to do about it? Mol. Psychiatry 17, 1174–1179 (2012).

    Article  CAS  PubMed  Google Scholar 

  27. Kirov, G. et al. De novo CNV analysis implicates specific abnormalities of postsynaptic signalling complexes in the pathogenesis of schizophrenia. Mol. Psychiatry 17, 142–153 (2012).

    Article  CAS  PubMed  Google Scholar 

  28. Marenco, S. & Weinberger, D.R. The neurodevelopmental hypothesis of schizophrenia: following a trail of evidence from cradle to grave. Dev. Psychopathol. 12, 501–527 (2000).

    Article  CAS  PubMed  Google Scholar 

  29. Owen, M.J., O'Donovan, M.C., Thapar, A. & Craddock, N. Neurodevelopmental hypothesis of schizophrenia. Br. J. Psychiatry 198, 173–175 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  30. MacDonald, A.W. III & Chafee, M.V. Translational and developmental perspective on N-methyl-D-aspartate synaptic deficits in schizophrenia. Dev. Psychopathol. 18, 853–876 (2006).

    PubMed  Google Scholar 

  31. Burrows, E.L. & Hannan, A.J. Cognitive endophenotypes, gene-environment interactions and experience-dependent plasticity in animal models of schizophrenia. Biol. Psychol. 116, 82–89 (2016).

    Article  PubMed  Google Scholar 

  32. Crabtree, G.W. & Gogos, J.A. Synaptic plasticity, neural circuits, and the emerging role of altered short-term information processing in schizophrenia. Front. Synaptic Neurosci. 6, 28 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  33. MacDonald, A.W. III & Carter, C.S. Event-related fMRI study of context processing in dorsolateral prefrontal cortex of patients with schizophrenia. J. Abnorm. Psychol. 112, 689–697 (2003).

    Article  PubMed  Google Scholar 

  34. MacDonald, A.W. III et al. Specificity of prefrontal dysfunction and context processing deficits to schizophrenia in never-medicated patients with first-episode psychosis. Am. J. Psychiatry 162, 475–484 (2005).

    Article  PubMed  Google Scholar 

  35. Yoon, J.H. et al. Association of dorsolateral prefrontal cortex dysfunction with disrupted coordinated brain activity in schizophrenia: relationship with impaired cognition, behavioral disorganization, and global function. Am. J. Psychiatry 165, 1006–1014 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Millan, M.J. et al. Cognitive dysfunction in psychiatric disorders: characteristics, causes and the quest for improved therapy. Nat. Rev. Drug Discov. 11, 141–168 (2012).

    Article  CAS  PubMed  Google Scholar 

  37. Keefe, R.S. & Harvey, P.D. Cognitive impairment in schizophrenia. Handb. Exp. Pharmacol. 213, 11–37 (2012).

    Article  CAS  Google Scholar 

  38. Dayan, P. & Niv, Y. Reinforcement learning: the good, the bad and the ugly. Curr. Opin. Neurobiol. 18, 185–196 (2008).

    Article  CAS  PubMed  Google Scholar 

  39. Feldman, D.E. The spike-timing dependence of plasticity. Neuron 75, 556–571 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. LeDoux, J.E. Coming to terms with fear. Proc. Natl. Acad. Sci. USA 111, 2871–2878 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Romanski, L.M. & LeDoux, J.E. Equipotentiality of thalamo-amygdala and thalamo-cortico-amygdala circuits in auditory fear conditioning. J. Neurosci. 12, 4501–4509 (1992).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. LeDoux, J.E. Emotion circuits in the brain. Annu. Rev. Neurosci. 23, 155–184 (2000).

    Article  CAS  PubMed  Google Scholar 

  43. Herry, C. & Johansen, J.P. Encoding of fear learning and memory in distributed neuronal circuits. Nat. Neurosci. 17, 1644–1654 (2014).

    Article  CAS  PubMed  Google Scholar 

  44. Davis, M. The role of the amygdala in conditioned and unconditioned fear and anxiety. in The Amygdala (ed. Aggleton, J.P.) 213–288 (Oxford University Press, 2000).

  45. Quirk, G.J., Armony, J.L. & LeDoux, J.E. Fear conditioning enhances different temporal components of tone-evoked spike trains in auditory cortex and lateral amygdala. Neuron 19, 613–624 (1997).

    Article  CAS  PubMed  Google Scholar 

  46. Quirk, G.J., Repa, C. & LeDoux, J.E. Fear conditioning enhances short-latency auditory responses of lateral amygdala neurons: parallel recordings in the freely behaving rat. Neuron 15, 1029–1039 (1995).

    Article  CAS  PubMed  Google Scholar 

  47. Johansen, J.P. et al. Optical activation of lateral amygdala pyramidal cells instructs associative fear learning. Proc. Natl. Acad. Sci. USA 107, 12692–12697 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Nabavi, S. et al. Engineering a memory with LTD and LTP. Nature 511, 348–352 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Duvarci, S. & Pare, D. Amygdala microcircuits controlling learned fear. Neuron 82, 966–980 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Rescorla, R.A. & Wagner, A.R. A theory of Pavlovian conditioning: variations in the effectiveness of reinforcement and nonreinforcement. in Classical Conditioning II: Current Research and Theory (eds. Black, A.H. & Prokasy, W.F.) 64–99 (Appleton-Century-Crofts, New York, 1972).

  51. Clem, R.L. & Schiller, D. New learning and unlearning: strangers or accomplices in threat memory attenuation? Trends Neurosci. 39, 340–351 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Bouton, M.E. Context, ambiguity, and unlearning: sources of relapse after behavioral extinction. Biol. Psychiatry 52, 976–986 (2002).

    Article  PubMed  Google Scholar 

  53. Bouton, M.E. Context, time, and memory retrieval in the interference paradigms of Pavlovian learning. Psychol. Bull. 114, 80–99 (1993).

    Article  CAS  PubMed  Google Scholar 

  54. Duits, P. et al. Updated meta-analysis of classical fear conditioning in the anxiety disorders. Depress. Anxiety 32, 239–253 (2015).

    Article  PubMed  Google Scholar 

  55. Mineka, S. & Oehlberg, K. The relevance of recent developments in classical conditioning to understanding the etiology and maintenance of anxiety disorders. Acta Psychol. (Amst.) 127, 567–580 (2008).

    Article  Google Scholar 

  56. Kindt, M. A behavioural neuroscience perspective on the aetiology and treatment of anxiety disorders. Behav. Res. Ther. 62, 24–36 (2014).

    Article  PubMed  Google Scholar 

  57. Graham, B.M. & Milad, M.R. The study of fear extinction: implications for anxiety disorders. Am. J. Psychiatry 168, 1255–1265 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  58. Britton, J.C., Lissek, S., Grillon, C., Norcross, M.A. & Pine, D.S. Development of anxiety: the role of threat appraisal and fear learning. Depress. Anxiety 28, 5–17 (2011).

    Article  PubMed  Google Scholar 

  59. Delgado, M.R., Nearing, K.I., Ledoux, J.E. & Phelps, E.A. Neural circuitry underlying the regulation of conditioned fear and its relation to extinction. Neuron 59, 829–838 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. McTeague, L.M. & Lang, P.J. The anxiety spectrum and the reflex physiology of defense: from circumscribed fear to broad distress. Depress. Anxiety 29, 264–281 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Lang, P.J. & McTeague, L.M. Discrete and recurrent traumatization in PTSD: fear vs. anxious misery. J. Clin. Psychol. Med. Settings 18, 207–209 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  62. Pine, D.S. & Klein, R.G. Anxiety disorders. in Rutter's Child and Adolescent Psychiatry (eds. Thapar, A. et al.) 822–840 (John Wiley & Sons, New York, 2015).

  63. Arch, J.J. & Craske, M.G. First-line treatment: a critical appraisal of cognitive behavioral therapy developments and alternatives. Psychiatr. Clin. North Am. 32, 525–547 (2009).

    Article  PubMed  Google Scholar 

  64. Quirk, G.J. et al. Erasing fear memories with extinction training. J. Neurosci. 30, 14993–14997 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Rodrigues, H. et al. Does D-cycloserine enhance exposure therapy for anxiety disorders in humans? A meta-analysis. PLoS One 9, e93519 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  66. Bowers, M.E. & Ressler, K.J. An overview of translationally informed treatments for posttraumatic stress disorder: animal models of Pavlovian fear conditioning to human clinical trials. Biol. Psychiatry 78, E15–E27 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  67. Monfils, M.H., Cowansage, K.K., Klann, E. & LeDoux, J.E. Extinction-reconsolidation boundaries: key to persistent attenuation of fear memories. Science 324, 951–955 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Schiller, D. et al. Preventing the return of fear in humans using reconsolidation update mechanisms. Nature 463, 49–53 (2010).

    Article  CAS  PubMed  Google Scholar 

  69. Falls, W.A., Miserendino, M.J. & Davis, M. Extinction of fear-potentiated startle: blockade by infusion of an NMDA antagonist into the amygdala. J. Neurosci. 12, 854–863 (1992).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Walker, D.L., Ressler, K.J., Lu, K.T. & Davis, M. Facilitation of conditioned fear extinction by systemic administration or intra-amygdala infusions of D-cycloserine as assessed with fear-potentiated startle in rats. J. Neurosci. 22, 2343–2351 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Ressler, K.J. et al. Cognitive enhancers as adjuncts to psychotherapy: use of D-cycloserine in phobic individuals to facilitate extinction of fear. Arch. Gen. Psychiatry 61, 1136–1144 (2004).

    Article  PubMed  Google Scholar 

  72. Ori, R. et al. Augmentation of cognitive and behavioural therapies (CBT) with d-cycloserine for anxiety and related disorders. Cochrane Database Syst. Rev. 5, CD007803 (2015).

    Google Scholar 

  73. Sara, S.J. Retrieval and reconsolidation: toward a neurobiology of remembering. Learn. Mem. 7, 73–84 (2000).

    Article  CAS  PubMed  Google Scholar 

  74. Auber, A., Tedesco, V., Jones, C.E., Monfils, M.H. & Chiamulera, C. Post-retrieval extinction as reconsolidation interference: methodological issues or boundary conditions? Psychopharmacology (Berl.) 226, 631–647 (2013).

    Article  CAS  Google Scholar 

  75. Kredlow, M.A., Unger, L.D. & Otto, M.W. Harnessing reconsolidation to weaken fear and appetitive memories: A meta-analysis of post-retrieval extinction effects. Psychol. Bull. 142, 314–336 (2016).

    Article  PubMed  Google Scholar 

  76. Peters, J., Kalivas, P.W. & Quirk, G.J. Extinction circuits for fear and addiction overlap in prefrontal cortex. Learn. Mem. 16, 279–288 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  77. Belin, D., Jonkman, S., Dickinson, A., Robbins, T.W. & Everitt, B.J. Parallel and interactive learning processes within the basal ganglia: relevance for the understanding of addiction. Behav. Brain Res. 199, 89–102 (2009).

    Article  PubMed  Google Scholar 

  78. Di Chiara, G. Nucleus accumbens shell and core dopamine: differential role in behavior and addiction. Behav. Brain Res. 137, 75–114 (2002).

    Article  CAS  PubMed  Google Scholar 

  79. Wise, R.A. Dopamine and reward: the anhedonia hypothesis 30 years on. Neurotox. Res. 14, 169–183 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  80. Schultz, W. Getting formal with dopamine and reward. Neuron 36, 241–263 (2002).

    Article  CAS  PubMed  Google Scholar 

  81. Schultz, W., Dayan, P. & Montague, P.R. A neural substrate of prediction and reward. Science 275, 1593–1599 (1997).

    Article  CAS  PubMed  Google Scholar 

  82. Frank, M.J. Dynamic dopamine modulation in the basal ganglia: a neurocomputational account of cognitive deficits in medicated and nonmedicated Parkinsonism. J. Cogn. Neurosci. 17, 51–72 (2005).

    Article  PubMed  Google Scholar 

  83. Hollerman, J.R. & Schultz, W. Dopamine neurons report an error in the temporal prediction of reward during learning. Nat. Neurosci. 1, 304–309 (1998).

    Article  CAS  PubMed  Google Scholar 

  84. Redish, A.D. Addiction as a computational process gone awry. Science 306, 1944–1947 (2004).

    Article  CAS  PubMed  Google Scholar 

  85. Marks, K.R., Kearns, D.N., Christensen, C.J., Silberberg, A. & Weiss, S.J. Learning that a cocaine reward is smaller than expected: a test of Redish's computational model of addiction. Behav. Brain Res. 212, 204–207 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  86. Volkow, N.D., Fowler, J.S., Wang, G.J., Baler, R. & Telang, F. Imaging dopamine's role in drug abuse and addiction. Neuropharmacology 56 (Suppl. 1), 3–8 (2009).

    Article  CAS  PubMed  Google Scholar 

  87. Volkow, N.D., Wang, G.J., Fowler, J.S., Tomasi, D. & Baler, R. Food and drug reward: overlapping circuits in human obesity and addiction. Curr. Top. Behav. Neurosci. 11, 1–24 (2012).

    CAS  PubMed  Google Scholar 

  88. Belin, D., Belin-Rauscent, A., Murray, J.E. & Everitt, B.J. Addiction: failure of control over maladaptive incentive habits. Curr. Opin. Neurobiol. 23, 564–572 (2013).

    Article  CAS  PubMed  Google Scholar 

  89. Janak, P.H. & Tye, K.M. From circuits to behaviour in the amygdala. Nature 517, 284–292 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Namburi, P. et al. A circuit mechanism for differentiating positive and negative associations. Nature 520, 675–678 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Stuber, G.D. et al. Excitatory transmission from the amygdala to nucleus accumbens facilitates reward seeking. Nature 475, 377–380 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Britt, J.P. et al. Synaptic and behavioral profile of multiple glutamatergic inputs to the nucleus accumbens. Neuron 76, 790–803 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Tye, K.M., Stuber, G.D., de Ridder, B., Bonci, A. & Janak, P.H. Rapid strengthening of thalamo-amygdala synapses mediates cue-reward learning. Nature 453, 1253–1257 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. White, N.M. Addictive drugs as reinforcers: multiple partial actions on memory systems. Addiction 91, 921–949 discussion 951–965 (1996).

    Article  CAS  PubMed  Google Scholar 

  95. Belin-Rauscent, A., Fouyssac, M., Bonci, A. & Belin, D. How preclinical models evolved to resemble the diagnostic criteria of drug addiction. Biol. Psychiatry 79, 39–46 (2016).

    Article  PubMed  Google Scholar 

  96. Olmstead, M.C., Parkinson, J.A., Miles, F.J., Everitt, B.J. & Dickinson, A. Cocaine-seeking by rats: regulation, reinforcement and activation. Psychopharmacology (Berl.) 152, 123–131 (2000).

    Article  CAS  Google Scholar 

  97. Belin, D., Mar, A.C., Dalley, J.W., Robbins, T.W. & Everitt, B.J. High impulsivity predicts the switch to compulsive cocaine-taking. Science 320, 1352–1355 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Waselus, M. et al. Long-term effects of cocaine experience on neuroplasticity in the nucleus accumbens core of addiction-prone rats. Neuroscience 248, 571–584 (2013).

    Article  CAS  PubMed  Google Scholar 

  99. Flagel, S.B. et al. Genetic background and epigenetic modifications in the core of the nucleus accumbens predict addiction-like behavior in a rat model. Proc. Natl. Acad. Sci. USA 113, E2861–E2870 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Xue, Y.X. et al. A memory retrieval-extinction procedure to prevent drug craving and relapse. Science 336, 241–245 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Das, R.K., Freeman, T.P. & Kamboj, S.K. The effects of N-methyl D-aspartate and B-adrenergic receptor antagonists on the reconsolidation of reward memory: a meta-analysis. Neurosci. Biobehav. Rev. 37, 240–255 (2013).

    Article  CAS  PubMed  Google Scholar 

  102. Georgopoulos, A.P. et al. Synchronous neural interactions assessed by magnetoencephalography: a functional biomarker for brain disorders. J. Neural Eng. 4, 349–355 (2007).

    Article  PubMed  Google Scholar 

  103. Minzenberg, M.J. et al. Gamma oscillatory power is impaired during cognitive control independent of medication status in first-episode schizophrenia. Neuropsychopharmacology 35, 2590–2599 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  104. Spellman, T.J. & Gordon, J.A. Synchrony in schizophrenia: a window into circuit-level pathophysiology. Curr. Opin. Neurobiol. 30, 17–23 (2015).

    Article  CAS  PubMed  Google Scholar 

  105. Uhlhaas, P.J. & Singer, W. Oscillations and neuronal dynamics in schizophrenia: the search for basic symptoms and translational opportunities. Biol. Psychiatry 77, 1001–1009 (2015).

    Article  PubMed  Google Scholar 

  106. Hall, J., Trent, S., Thomas, K.L., O'Donovan, M.C. & Owen, M.J. Genetic risk for schizophrenia: convergence on synaptic pathways involved in plasticity. Biol. Psychiatry 77, 52–58 (2015).

    Article  CAS  PubMed  Google Scholar 

  107. Fromer, M. et al. De novo mutations in schizophrenia implicate synaptic networks. Nature 506, 179–184 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Malenka, R.C. & Nicoll, R.A. NMDA-receptor-dependent synaptic plasticity: multiple forms and mechanisms. Trends Neurosci. 16, 521–527 (1993).

    Article  CAS  PubMed  Google Scholar 

  109. Sekar, A. et al. Schizophrenia risk from complex variation of complement component 4. Nature 530, 177–183 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Goldman-Rakic, P.S. Working memory dysfunction in schizophrenia. J. Neuropsychiatry Clin. Neurosci. 6, 348–357 (1994).

    Article  CAS  PubMed  Google Scholar 

  111. Selemon, L.D., Kleinman, J.E., Herman, M.M. & Goldman-Rakic, P.S. Smaller frontal gray matter volume in postmortem schizophrenic brains. Am. J. Psychiatry 159, 1983–1991 (2002).

    Article  PubMed  Google Scholar 

  112. Ahn, S. & Phillips, A.G. Daily monitoring of dopamine efflux reveals a short-lasting occlusion of the dopamine agonist properties of d-amphetamine by dopamine transporter blockers GBR 12909 and methylphenidate. ACS Chem. Neurosci. 4, 817–824 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Preuss, T.M. Do rats have prefrontal cortex? The Rose-Woolsey-Akert program reconsidered. J. Cogn. Neurosci. 7, 1–24 (1995).

    Article  CAS  PubMed  Google Scholar 

  114. Goghari, V.M., Sponheim, S.R. & MacDonald, A.W. III. The functional neuroanatomy of symptom dimensions in schizophrenia: a qualitative and quantitative review of a persistent question. Neurosci. Biobehav. Rev. 34, 468–486 (2010).

    Article  PubMed  Google Scholar 

  115. Simen, A.A., DiLeone, R. & Arnsten, A.F. Primate models of schizophrenia: future possibilities. Prog. Brain Res. 179, 117–125 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Nuechterlein, K.H. et al. The MATRICS Consensus Cognitive Battery, part 1: test selection, reliability, and validity. Am. J. Psychiatry 165, 203–213 (2008).

    Article  PubMed  Google Scholar 

  117. Carter, C.S., Minzenberg, M., West, R. & Macdonald, A. III. CNTRICS imaging biomarker selections: Executive control paradigms. Schizophr. Bull. 38, 34–42 (2012).

    Article  PubMed  Google Scholar 

  118. Barch, D.M., Moore, H., Nee, D.E., Manoach, D.S. & Luck, S.J. CNTRICS imaging biomarkers selection: Working memory. Schizophr. Bull. 38, 43–52 (2012).

    Article  PubMed  Google Scholar 

  119. Butler, P.D. et al. Perceptual measurement in schizophrenia: promising electrophysiology and neuroimaging paradigms from CNTRICS. Schizophr. Bull. 38, 81–91 (2012).

    Article  PubMed  Google Scholar 

  120. Lee, J. & Park, S. Working memory impairments in schizophrenia: a meta-analysis. J. Abnorm. Psychol. 114, 599–611 (2005).

    Article  PubMed  Google Scholar 

  121. Goldman-Rakic, P.S. Cellular basis of working memory. Neuron 14, 477–485 (1995).

    Article  CAS  PubMed  Google Scholar 

  122. Funahashi, S., Bruce, C.J. & Goldman-Rakic, P.S. Mnemonic coding of visual space in the monkey's dorsolateral prefrontal cortex. J. Neurophysiol. 61, 331–349 (1989).

    Article  CAS  PubMed  Google Scholar 

  123. Chafee, M.V. & Goldman-Rakic, P.S. Matching patterns of activity in primate prefrontal area 8a and parietal area 7ip neurons during a spatial working memory task. J. Neurophysiol. 79, 2919–2940 (1998).

    Article  CAS  PubMed  Google Scholar 

  124. Funahashi, S., Bruce, C.J. & Goldman-Rakic, P.S. Dorsolateral prefrontal lesions and oculomotor delayed-response performance: evidence for mnemonic “scotomas”. J. Neurosci. 13, 1479–1497 (1993).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Chafee, M.V. & Goldman-Rakic, P.S. Inactivation of parietal and prefrontal cortex reveals interdependence of neural activity during memory-guided saccades. J. Neurophysiol. 83, 1550–1566 (2000).

    Article  CAS  PubMed  Google Scholar 

  126. Sawaguchi, T. & Goldman-Rakic, P.S. The role of D1-dopamine receptor in working memory: local injections of dopamine antagonists into the prefrontal cortex of rhesus monkeys performing an oculomotor delayed-response task. J. Neurophysiol. 71, 515–528 (1994).

    Article  CAS  PubMed  Google Scholar 

  127. Park, S., Holzman, P.S. & Goldman-Rakic, P.S. Spatial working memory deficits in the relatives of schizophrenic patients. Arch. Gen. Psychiatry 52, 821–828 (1995).

    Article  CAS  PubMed  Google Scholar 

  128. Driesen, N.R. et al. Impairment of working memory maintenance and response in schizophrenia: functional magnetic resonance imaging evidence. Biol. Psychiatry 64, 1026–1034 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  129. Eryilmaz, H. et al. Disrupted working memory circuitry in schizophrenia: disentangling fMRI markers of core pathology vs other aspects of impaired performance. Neuropsychopharmacology 41, 2411–2420 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  130. Moghaddam, B. & Krystal, J.H. Capturing the angel in “angel dust”: twenty years of translational neuroscience studies of NMDA receptor antagonists in animals and humans. Schizophr. Bull. 38, 942–949 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  131. Javitt, D.C., Zukin, S.R., Heresco-Levy, U. & Umbricht, D. Has an angel shown the way? Etiological and therapeutic implications of the PCP/NMDA model of schizophrenia. Schizophr. Bull. 38, 958–966 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  132. Wang, M. et al. NMDA receptors subserve persistent neuronal firing during working memory in dorsolateral prefrontal cortex. Neuron 77, 736–749 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  133. Skoblenick, K.J., Womelsdorf, T. & Everling, S. Ketamine alters outcome-related local field potentials in monkey prefrontal cortex. Cereb. Cortex 26, 2743–2752 (2016).

    Article  PubMed  Google Scholar 

  134. Ma, L., Skoblenick, K., Seamans, J.K. & Everling, S. Ketamine-induced changes in the signal and noise of rule representation in working memory by lateral prefrontal neurons. J. Neurosci. 35, 11612–11622 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. Skoblenick, K. & Everling, S. NMDA antagonist ketamine reduces task selectivity in macaque dorsolateral prefrontal neurons and impairs performance of randomly interleaved prosaccades and antisaccades. J. Neurosci. 32, 12018–12027 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  136. Evans, S. et al. Performance on a probabilistic inference task in healthy subjects receiving ketamine compared with patients with schizophrenia. J. Psychopharmacol. 26, 1211–1217 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  137. Jones, J.A., Sponheim, S.R. & MacDonald, A.W. III. The dot pattern expectancy task: reliability and replication of deficits in schizophrenia. Psychol. Assess. 22, 131–141 (2010).

    Article  PubMed  Google Scholar 

  138. MacDonald, A.W. III. Building a clinically relevant cognitive task: case study of the AX paradigm. Schizophr. Bull. 34, 619–628 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  139. Barch, D.M., Carter, C.S., MacDonald, A.W. III, Braver, T.S. & Cohen, J.D. Context-processing deficits in schizophrenia: diagnostic specificity, 4-week course, and relationships to clinical symptoms. J. Abnorm. Psychol. 112, 132–143 (2003).

    Article  PubMed  Google Scholar 

  140. Blackman, R.K., Macdonald, A.W. III & Chafee, M.V. Effects of ketamine on context-processing performance in monkeys: a new animal model of cognitive deficits in schizophrenia. Neuropsychopharmacology 38, 2090–2100 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. Dias, E.C. et al. Changing plans: neural correlates of executive control in monkey and human frontal cortex. Exp. Brain Res. 174, 279–291 (2006).

    Article  PubMed  Google Scholar 

  142. Karayiorgou, M., Simon, T.J. & Gogos, J.A. 22q11.2 microdeletions: linking DNA structural variation to brain dysfunction and schizophrenia. Nat. Rev. Neurosci. 11, 402–416 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  143. Stark, K.L. et al. Altered brain microRNA biogenesis contributes to phenotypic deficits in a 22q11-deletion mouse model. Nat. Genet. 40, 751–760 (2008).

    Article  CAS  PubMed  Google Scholar 

  144. Sigurdsson, T., Stark, K.L., Karayiorgou, M., Gogos, J.A. & Gordon, J.A. Impaired hippocampal-prefrontal synchrony in a genetic mouse model of schizophrenia. Nature 464, 763–767 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  145. Fénelon, K. et al. Deficiency of Dgcr8, a gene disrupted by the 22q11.2 microdeletion, results in altered short-term plasticity in the prefrontal cortex. Proc. Natl. Acad. Sci. USA 108, 4447–4452 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This work was funded in part by the intramural research program of the National Institute of Mental Health and NIH grants ZIA MH002928-01 (B.B.A.) and 1R01MH107491 (M.V.C.).

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Averbeck, B., Chafee, M. Using model systems to understand errant plasticity mechanisms in psychiatric disorders. Nat Neurosci 19, 1418–1425 (2016). https://doi.org/10.1038/nn.4413

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