Dopamine Cells Respond to Predicted Events during Classical Conditioning: Evidence for Eligibility Traces in the Reward-Learning Network
暂无分享,去创建一个
W. Pan | R. Schmidt | J. Wickens | B. Hyland
[1] L. S. Kogan. Review of Principles of Behavior. , 1943 .
[2] B. Skinner,et al. Principles of Behavior , 1944 .
[3] E. Fischer. Conditioned Reflexes , 1942, American journal of physical medicine.
[4] R. Roth,et al. Comparison of effects of L-dopa, amphetamine and apomorphine on firing rate of rat dopaminergic neurones. , 1973, Nature: New biology.
[5] A. Grace,et al. Nigral dopamine neurons: intracellular recording and identification with L-dopa injection and histofluorescence. , 1980, Science.
[6] J. D. Miller,et al. Mesencephalic dopaminergic unit activity in the behaviorally conditioned rat. , 1981, Life sciences.
[7] R. Sutton,et al. Simulation of anticipatory responses in classical conditioning by a neuron-like adaptive element , 1982, Behavioural Brain Research.
[8] A. Grace,et al. Intracellular and extracellular electrophysiology of nigral dopaminergic neurons—1. Identification and characterization , 1983, Neuroscience.
[9] G. Paxinos,et al. The Rat Brain in Stereotaxic Coordinates , 1983 .
[10] W. Schultz,et al. The activity of pars compacta neurons of the monkey substantia nigra is depressed by apomorphine , 1984, Neuroscience Letters.
[11] W. Schultz. Responses of midbrain dopamine neurons to behavioral trigger stimuli in the monkey. , 1986, Journal of neurophysiology.
[12] A. Klopf. A neuronal model of classical conditioning , 1988 .
[13] W. Schultz,et al. Dopamine neurons of the monkey midbrain: contingencies of responses to active touch during self-initiated arm movements. , 1990, Journal of neurophysiology.
[14] Richard S. Sutton,et al. Time-Derivative Models of Pavlovian Reinforcement , 1990 .
[15] M. Gabriel,et al. Learning and Computational Neuroscience: Foundations of Adaptive Networks , 1990 .
[16] W. Schultz,et al. Responses of monkey dopamine neurons during learning of behavioral reactions. , 1992, Journal of neurophysiology.
[17] W. Schultz,et al. Responses of monkey dopamine neurons to reward and conditioned stimuli during successive steps of learning a delayed response task , 1993, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[18] Joel L. Davis,et al. A Model of How the Basal Ganglia Generate and Use Neural Signals That Predict Reinforcement , 1994 .
[19] J. Chapin,et al. Behavioral associations of neuronal activity in the ventral tegmental area of the rat , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[20] W. Schultz,et al. Importance of unpredictability for reward responses in primate dopamine neurons. , 1994, Journal of neurophysiology.
[21] Pawel Cichosz,et al. Truncating Temporal Differences: On the Efficient Implementation of TD(lambda) for Reinforcement Learning , 1994, J. Artif. Intell. Res..
[22] A. Barto. Adaptive Critics and the Basal Ganglia , 1995 .
[23] Joel L. Davis,et al. In : Models of Information Processing in the Basal Ganglia , 2008 .
[24] Pawea Cichosz. Truncating Temporal Diierences: on the Eecient Implementation of Td() for Reinforcement Learning , 1995 .
[25] Andrew W. Moore,et al. Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..
[26] P. Dayan,et al. A framework for mesencephalic dopamine systems based on predictive Hebbian learning , 1996, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[27] Richard S. Sutton,et al. Reinforcement Learning with Replacing Eligibility Traces , 2005, Machine Learning.
[28] Peter Dayan,et al. A Neural Substrate of Prediction and Reward , 1997, Science.
[29] Andrew G. Barto,et al. Reinforcement learning , 1998 .
[30] W. Schultz,et al. Learning of sequential movements by neural network model with dopamine-like reinforcement signal , 1998, Experimental Brain Research.
[31] J. Hollerman,et al. Dopamine neurons report an error in the temporal prediction of reward during learning , 1998, Nature Neuroscience.
[32] W. Schultz,et al. A neural network model with dopamine-like reinforcement signal that learns a spatial delayed response task , 1999, Neuroscience.
[33] Rajesh P. N. Rao,et al. Spike-Timing-Dependent Hebbian Plasticity as Temporal Difference Learning , 2001, Neural Computation.
[34] W. Schultz,et al. Dopamine responses comply with basic assumptions of formal learning theory , 2001, Nature.
[35] G. Rebec,et al. Impulse activity of ventral tegmental area neurons during heroin self-administration in rats , 2001, Neuroscience.
[36] R. Suri. Anticipatory responses of dopamine neurons and cortical neurons reproduced by internal model , 2001, Experimental Brain Research.
[37] Roland E. Suri,et al. Temporal Difference Model Reproduces Anticipatory Neural Activity , 2001, Neural Computation.
[38] B. Hyland,et al. Firing modes of midbrain dopamine cells in the freely moving rat , 2002, Neuroscience.
[39] W. Schultz. Getting Formal with Dopamine and Reward , 2002, Neuron.
[40] David S. Touretzky,et al. Timing and Partial Observability in the Dopamine System , 2002, NIPS.
[41] Karl J. Friston,et al. Temporal Difference Models and Reward-Related Learning in the Human Brain , 2003, Neuron.
[42] W. Schultz,et al. Discrete Coding of Reward Probability and Uncertainty by Dopamine Neurons , 2003, Science.
[43] O. Hikosaka,et al. Dopamine Neurons Can Represent Context-Dependent Prediction Error , 2004, Neuron.
[44] Karl J. Friston,et al. Dissociable Roles of Ventral and Dorsal Striatum in Instrumental Conditioning , 2004, Science.
[45] B. Bunney,et al. Dopamine “Autoreceptors”: Pharmacological characterization by microiontophoretic single cell recording studies , 1977, Naunyn-Schmiedeberg's Archives of Pharmacology.
[46] O. Hikosaka,et al. A possible role of midbrain dopamine neurons in short- and long-term adaptation of saccades to position-reward mapping. , 2004, Journal of neurophysiology.
[47] Gerald Tesauro,et al. Practical issues in temporal difference learning , 1992, Machine Learning.
[48] Peter Dayan,et al. Temporal difference models describe higher-order learning in humans , 2004, Nature.
[49] E. Vaadia,et al. Coincident but Distinct Messages of Midbrain Dopamine and Striatal Tonically Active Neurons , 2004, Neuron.
[50] Richard S. Sutton,et al. Learning to predict by the methods of temporal differences , 1988, Machine Learning.