References
Arnsten AFT (1998) Catecholamine modulation of prefrontal cortical cognitive function. Trends Cogn Sci 2:436–447
Berridge KC, Robinson TE (1998) What is the role of dopamine in reward: hedonic impact, reward learning, or incentive salience? Brain Res Rev 28:309–369
Braver TS, Cohen JD (1999) Dopamine, cognitive control, and schizophrenia: the gating model. Prog Brain Res 121:327–349
Clarke CR, Geffen GM, Geffen LB (1987) Catecholamines and attention I: animal and clinical studies. Neurosci Biobehav Rev 11:341–352
Cohen JD, Braver TS, Brown JW (2002) Computational perspectives on dopamine function in prefrontal cortex. Curr Opin Neurobiol 12:223–229
Cohen JD, McClure SM, Yu AJ (2007) Should I stay or should I go? How the human brain manages the trade-off between exploitation and exploration. Philos Trans R Soc Lond B Biol Sci 362:933–942
Cools R, Altamirano L, D’Esposito M (2006) Reversal learning in Parkinson’s disease depends on medication status and outcome valence. Neuropsychologia 44:1663–1673
Dagher A, Robbins T (2009) Personality addiction dopamine: Insights from Parkinson’s disease. Neuron 61:502–510
Daw ND, Courville AC, Touretzky DS (2006) Representation and timing in theories of the dopamine system. Neural Comput 18:1637–1677
Denk F, Walton ME, Jennings KA, Sharp T, Rushworth MF, Bannerman DM (2005) Differential involvement of serotonin and dopamine systems in cost–benefit decisions about delay oreffort. Psychopharmacology (Berl) 179:587–596
Durstewitz D, Seamans JK (2008) The dual-state theory of prefrontal cortex dopamine function with relevance to COMT genotypes and schizophrenia. Biol Psychiatry 64:739–749
Durstewitz D, Kelc M, Güntürkün O (1999) A neurocomputational theory of the dopaminergic modulation of working memory functions. J Neurosci 19:2807–2822
Foote L, Morrison JH (1987) Extrathalamic modulation of cortical function. Annu Rev Neurosci 10:67–95
Frank MJ (2005) Dynamic dopamine modulation in the basal ganglia: a neurocomputational account of cognitive deficits in medicated and nonmedicated Parkinsonism. J Cogn Neurosci 17:51–72
Frank MJ (2008) Schizophrenia: a computational reinforcement learning perspective. Schizophr Bull 34:1008–1011
Frank MJ, Seeberger L, O'Reilly RC (2004) By carrot or by stick: cognitive reinforcement learning in Parkinsonism. Science 306:1940–1943
Glimcher PW (2011) Understanding dopamine and reinforcement learning: the dopamine reward prediction error hypothesis. Proc Natl Acad Sci 108:15647–15654
Grace AA (1991) Phasic versus tonic dopamine release and the modulation of dopamine system responsivity: a hypothesis of the etiology of schizophrenia. Neuroscience 41:1–24
Hollerman JR, Schultz W (1998) Dopamine neurons report an error in the temporal prediction of reward during learning. Nat Neurosci 1:304–309
Horvitz JC, Stewart T, Jacobs B (1997) Burst activity of ventral tegmental dopamine neurons is elicited by sensory stimuli in the awake cat. Brain Res 759:251–258
Houk JC, Adams JL, Barto AG (1995) A model of how the basal ganglia generate and use neural signals that predict reinforcement. In: Houk JC, Davis JL, Beiser DG (eds) Models of information processing in the basal ganglia. MIT Press, Cambridge, MA, pp 249–270
Kakade S, Dayan P (2002) Dopamine: generalization and bonuses. Neural Netw 15:549–559
Lapish CC, Kroener S, Durstewitz D, Lavin A, Seamans JK (2007) The ability of the mesocortical dopamine system to operate in distinct temporal modes. Psychopharmacology (Berl) 191:609–625
Levitt JB, Lewis DA, Yoshioka T, Lund JS (1993) Topography of pyramidal neuron intrinsic connections in macaque monkey prefrontal cortex (areas 9 and 46). J Comp Neurol 338:360–376
Mazzoni P, Hristova A, Krakauer JW (2007) Why don’t we move faster? Parkinson’s disease, movement vigor, and implicit motivation. J Neurosci 27:7105–7116
Montague PR, Dayan P, Sejnowski TJ (1996) A framework for mesencephalic dopamine systems based on predictive Hebbian learning. J Neurosci 16(5):1936–1947
Morris G, Nevet A, Arkadir D, Vaadia E, Bergman H (2006) Midbrain dopamine neurons encode decisions for future action. Nature Neuroscience 9:1057–1063
Moustafa AA, Cohen MX, Sherman SJ, Frank MJ (2008a) A role for dopamine in temporal decision making and reward maximization in Parkinsonism. J Neurosci 28:12294–12304
Moustafa AA, Sherman SJ, Frank MJ (2008b) A dopaminergic basis for working memory, learning, and attentional shifting in Parkinson’s disease. Neuropsychologia 46:3144–3156
Moyer JT, Wolf JA, Finkel LH (2007) Effects of dopaminergic modulation on the integrative properties of the ventral striatal medium spiny neuron. J Neurophysiol 98:3731–3748
Niv Y, Rivlin-Etzion M (2007) Parkinson’s disease: fighting the will? J Neurosci 27:11777–11779
Niv Y, Daw ND, Joel D, Dayan P (2007) Tonic dopamine: opportunity costs and the controlof response vigor. Psychopharmacology (Berl) 191:507–520
O'Reilly RC, Frank MJ (2006) Making working memory work: a computational model of learning in the prefrontal cortex and basal ganglia. Neural Comput 18:283–328
Roesch MR, Calu DJ, Schoenbaum G (2007) Dopamine neurons encode the better options in rats deciding between differently delayed or sized rewards. Nature Neuroscience 10:1615:1624
Salamone JD, Wisniecki A, Carlson BB, Correa M (2001) Nucleus accumbens dopamine depletions make animals highly sensitive to high fixed ratio requirements but do not impair primary food reinforcement. Neuroscience 5:863–870
Sawaguchi T, Goldman-Rakic PS (1991) D1 dopamine receptors in prefrontal cortex: involvement in working memory. Science 251:947–950
Schultz W (2007) Multiple dopamine functions at different time courses. Annu Rev Neurosci 30:259–288
Schultz W, Dayan P, Montague PR (1997) A neural substrate of prediction and reward. Science 275:1593–1599
Servan-Schreiber D, Printz H, Cohen JD (1990) A network model of catecholamine effects: gain, signal-to-noise ratio, and behavior. Science 249:892–895
Sokolowski JD, Salamone JD (1998) The role of accumbens dopamine in lever pressing and response allocation: effects of 6-OHDA injected into core and dorsomedial shell. Pharmacol Biochem Behav 59:557–566
Suri RE, Schultz W (1998) Learning of sequential movements by neural network model with dopamine-like reinforcement signal. Exp Brain Res 121:350–354
Sutton RS, Barto AG (1998) Reinforcement learning: an introduction. MIT Press, Cambridge, MA
Trantham-Davidson H, Neely LC, Lavin A, Seamans JK (2004) Mechanisms underlying differential D1 versus D2 dopamine receptor regulation of inhibition in prefrontal cortex. J Neurosci 24:10652–10659
Waltz JA, Frank MJ, Robinson BM, Gold JM (2007) Selective reinforcement learning deficits in schizophrenia support predictions from computational models of striatal-corticaldysfunction. Biol Psychiatry 62:756–764
Wiecki TV, Frank MJ (2010) Neurocomputational models of motor and cognitive deficits in Parkinson’s disease. Prog Brain Res 183:275–297
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Gershman, S. (2013). Computation with Dopaminergic Modulation. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_631-3
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