Annals of the New York Academy of Sciences Efficient Coding and the Neural Representation of Value
暂无分享,去创建一个
P. Glimcher | K. Louie | Sci | A. N. Acad
[1] E. Rowland. Theory of Games and Economic Behavior , 1946, Nature.
[2] P. Samuelson,et al. Foundations of Economic Analysis. , 1948 .
[3] F. Attneave. Some informational aspects of visual perception. , 1954, Psychological review.
[4] R J HERRNSTEIN,et al. Relative and absolute strength of response as a function of frequency of reinforcement. , 1961, Journal of the experimental analysis of behavior.
[5] A. Tversky. Elimination by aspects: A theory of choice. , 1972 .
[6] R. Duncan Luce,et al. Individual Choice Behavior: A Theoretical Analysis , 1979 .
[7] S. Lea,et al. Contemporary Animal Learning Theory, Anthony Dickinson. Cambridge University Press, Cambridge (1981), xii, +177 pp. £12.50 hardback, £3.95 paperback , 1981 .
[8] S. Laughlin. A Simple Coding Procedure Enhances a Neuron's Information Capacity , 1981, Zeitschrift fur Naturforschung. Section C, Biosciences.
[9] A G Barto,et al. Toward a modern theory of adaptive networks: expectation and prediction. , 1981, Psychological review.
[10] Christopher P. Puto,et al. Adding Asymmetrically Dominated Alternatives: Violations of Regularity & the Similarity Hypothesis. , 1981 .
[11] I. Ohzawa,et al. Contrast gain control in the cat visual cortex , 1982, Nature.
[12] J. Movshon,et al. The statistical reliability of signals in single neurons in cat and monkey visual cortex , 1983, Vision Research.
[13] C. Enroth-Cugell,et al. Chapter 9 Visual adaptation and retinal gain controls , 1984 .
[14] T. Wiesel,et al. Intrinsic connectivity and receptive field properties in visual cortex , 1985, Vision Research.
[15] 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.
[16] W. Schultz,et al. Responses of monkey dopamine neurons during learning of behavioral reactions. , 1992, Journal of neurophysiology.
[17] D. Heeger. Normalization of cell responses in cat striate cortex , 1992, Visual Neuroscience.
[18] A. Tversky,et al. Choice under Conflict: The Dynamics of Deferred Decision , 1992 .
[19] William R. Softky,et al. The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs , 1993, The Journal of neuroscience : the official journal of the Society for Neuroscience.
[20] I. Ohzawa,et al. Length and width tuning of neurons in the cat's primary visual cortex. , 1994, Journal of neurophysiology.
[21] W. Schultz,et al. Importance of unpredictability for reward responses in primate dopamine neurons. , 1994, Journal of neurophysiology.
[22] Peter Dayan,et al. Bee foraging in uncertain environments using predictive hebbian learning , 1995, Nature.
[23] 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.
[24] R. Wise,et al. Addictive drugs and brain stimulation reward. , 1996, Annual review of neuroscience.
[25] Peter Dayan,et al. A Neural Substrate of Prediction and Reward , 1997, Science.
[26] Michael J. Berry,et al. Adaptation of retinal processing to image contrast and spatial scale , 1997, Nature.
[27] David J. Field,et al. Sparse coding with an overcomplete basis set: A strategy employed by V1? , 1997, Vision Research.
[28] J. Movshon,et al. Linearity and Normalization in Simple Cells of the Macaque Primary Visual Cortex , 1997, The Journal of Neuroscience.
[29] J. Hollerman,et al. Influence of reward expectation on behavior-related neuronal activity in primate striatum. , 1998, Journal of neurophysiology.
[30] J. Hollerman,et al. Dopamine neurons report an error in the temporal prediction of reward during learning , 1998, Nature Neuroscience.
[31] M. Goldberg,et al. The representation of visual salience in monkey parietal cortex , 1998, Nature.
[32] W. Newsome,et al. The Variable Discharge of Cortical Neurons: Implications for Connectivity, Computation, and Information Coding , 1998, The Journal of Neuroscience.
[33] D. Ruderman,et al. Independent component analysis of natural image sequences yields spatio-temporal filters similar to simple cells in primary visual cortex , 1998, Proceedings of the Royal Society of London. Series B: Biological Sciences.
[34] O. Hikosaka,et al. Expectation of reward modulates cognitive signals in the basal ganglia , 1998, Nature Neuroscience.
[35] D. Munoz,et al. Saccadic Probability Influences Motor Preparation Signals and Time to Saccadic Initiation , 1998, The Journal of Neuroscience.
[36] Michael L. Platt,et al. Neural correlates of decision variables in parietal cortex , 1999, Nature.
[37] W. Schultz,et al. Relative reward preference in primate orbitofrontal cortex , 1999, Nature.
[38] K. H. Britten,et al. Spatial Summation in the Receptive Fields of MT Neurons , 1999, The Journal of Neuroscience.
[39] William Bialek,et al. Adaptive Rescaling Maximizes Information Transmission , 2000, Neuron.
[40] M. Lepper,et al. The Construction of Preference: When Choice Is Demotivating: Can One Desire Too Much of a Good Thing? , 2006 .
[41] J L Gallant,et al. Sparse coding and decorrelation in primary visual cortex during natural vision. , 2000, Science.
[42] J. Price,et al. The organization of networks within the orbital and medial prefrontal cortex of rats, monkeys and humans. , 2000, Cerebral cortex.
[43] Adrienne L. Fairhall,et al. Efficiency and ambiguity in an adaptive neural code , 2001, Nature.
[44] Eero P. Simoncelli,et al. Natural signal statistics and sensory gain control , 2001, Nature Neuroscience.
[45] W. Schultz,et al. Dopamine responses comply with basic assumptions of formal learning theory , 2001, Nature.
[46] W. Newsome,et al. Neural basis of a perceptual decision in the parietal cortex (area LIP) of the rhesus monkey. , 2001, Journal of neurophysiology.
[47] T. Başar,et al. A New Approach to Linear Filtering and Prediction Problems , 2001 .
[48] Eero P. Simoncelli,et al. Natural image statistics and neural representation. , 2001, Annual review of neuroscience.
[49] S. Shafir,et al. Context-dependent violations of rational choice in honeybees (Apis mellifera) and gray jays (Perisoreus canadensis) , 2001, Behavioral Ecology and Sociobiology.
[50] K. H. Britten,et al. Contrast dependence of response normalization in area MT of the rhesus macaque. , 2002, Journal of neurophysiology.
[51] J. R. DeShazo,et al. Designing Choice Sets for Stated Preference Methods: The Effects of Complexity on Choice Consistency , 2002 .
[52] J. Movshon,et al. Nature and interaction of signals from the receptive field center and surround in macaque V1 neurons. , 2002, Journal of neurophysiology.
[53] M. Shadlen,et al. Response of Neurons in the Lateral Intraparietal Area during a Combined Visual Discrimination Reaction Time Task , 2002, The Journal of Neuroscience.
[54] J. Gallant,et al. Natural Stimulation of the Nonclassical Receptive Field Increases Information Transmission Efficiency in V1 , 2002, The Journal of Neuroscience.
[55] J. Assad,et al. Dynamic coding of behaviourally relevant stimuli in parietal cortex , 2002, Nature.
[56] J. Movshon,et al. Time Course and Time-Distance Relationships for Surround Suppression in Macaque V1 Neurons , 2003, The Journal of Neuroscience.
[57] Eero P. Simoncelli. Vision and the statistics of the visual environment , 2003, Current Opinion in Neurobiology.
[58] P. Lennie,et al. Local signals from beyond the receptive fields of striate cortical neurons. , 2003, Journal of neurophysiology.
[59] E. Miller,et al. Neuronal activity in primate dorsolateral and orbital prefrontal cortex during performance of a reward preference task , 2003, The European journal of neuroscience.
[60] R. Navarro,et al. Optimal coding through divisive normalization models of V1 neurons. , 2003 .
[61] Wolfram Schultz,et al. Effects of expectations for different reward magnitudes on neuronal activity in primate striatum. , 2003, Journal of neurophysiology.
[62] R. Navarro,et al. Optimal coding through divisive normalization models of V1 neurons , 2003, Network.
[63] M. Shadlen,et al. Representation of Time by Neurons in the Posterior Parietal Cortex of the Macaque , 2003, Neuron.
[64] Okihide Hikosaka,et al. Reward-Dependent Gain and Bias of Visual Responses in Primate Superior Colliculus , 2003, Neuron.
[65] T. A. Hurly,et al. Context–dependent foraging decisions in rufous hummingbirds , 2003, Proceedings of the Royal Society of London. Series B: Biological Sciences.
[66] M. Goldberg,et al. Neuronal Activity in the Lateral Intraparietal Area and Spatial Attention , 2003, Science.
[67] R. Wise. Dopamine, learning and motivation , 2004, Nature Reviews Neuroscience.
[68] P. Glimcher,et al. Activity in Posterior Parietal Cortex Is Correlated with the Relative Subjective Desirability of Action , 2004, Neuron.
[69] W. Newsome,et al. Matching Behavior and the Representation of Value in the Parietal Cortex , 2004, Science.
[70] R. Andersen,et al. Cognitive Control Signals for Neural Prosthetics , 2004, Science.
[71] H. Ozeki,et al. Relationship between Excitation and Inhibition Underlying Size Tuning and Contextual Response Modulation in the Cat Primary Visual Cortex , 2004, The Journal of Neuroscience.
[72] S. Thorpe,et al. The orbitofrontal cortex: Neuronal activity in the behaving monkey , 2004, Experimental Brain Research.
[73] M. Roesch,et al. Neuronal Activity Related to Reward Value and Motivation in Primate Frontal Cortex , 2004, Science.
[74] J. Maunsell. Neuronal representations of cognitive state: reward or attention? , 2004, Trends in Cognitive Sciences.
[75] K. Doya,et al. Representation of Action-Specific Reward Values in the Striatum , 2005, Science.
[76] W. Schultz,et al. Adaptive Coding of Reward Value by Dopamine Neurons , 2005, Science.
[77] James J DiCarlo,et al. Multiple Object Response Normalization in Monkey Inferotemporal Cortex , 2005, The Journal of Neuroscience.
[78] J. Touryan,et al. Contextual modulation of orientation tuning contributes to efficient processing of natural stimuli , 2005, Network.
[79] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[80] P. Glimcher,et al. Midbrain Dopamine Neurons Encode a Quantitative Reward Prediction Error Signal , 2005, Neuron.
[81] C. Padoa-Schioppa,et al. Neurons in the orbitofrontal cortex encode economic value , 2006, Nature.
[82] Katherine I. Nagel,et al. Temporal Processing and Adaptation in the Songbird Auditory Forebrain , 2006, Neuron.
[83] Kenneth D. Miller,et al. Adaptive filtering enhances information transmission in visual cortex , 2006, Nature.
[84] Sang Joon Kim,et al. A Mathematical Theory of Communication , 2006 .
[85] Joseph J. Paton,et al. The primate amygdala represents the positive and negative value of visual stimuli during learning , 2006, Nature.
[86] O. Hikosaka,et al. Comparison of Reward Modulation in the Frontal Eye Field and Caudate of the Macaque , 2006, The Journal of Neuroscience.
[87] M. Carandini,et al. The Statistical Computation Underlying Contrast Gain Control , 2006, The Journal of Neuroscience.
[88] P. Dayan,et al. Space and time in visual context , 2007, Nature Reviews Neuroscience.
[89] A. Kohn. Visual adaptation: physiology, mechanisms, and functional benefits. , 2007, Journal of neurophysiology.
[90] Michael N. Shadlen,et al. Probabilistic reasoning by neurons , 2007, Nature.
[91] A. Fairhall,et al. Shifts in Coding Properties and Maintenance of Information Transmission during Adaptation in Barrel Cortex , 2007, PLoS biology.
[92] P. Glimcher,et al. The neural correlates of subjective value during intertemporal choice , 2007, Nature Neuroscience.
[93] Tai Sing Lee,et al. Contextual Influences in Visual Processing , 2008 .
[94] C. Padoa-Schioppa,et al. The representation of economic value in the orbitofrontal cortex is invariant for changes of menu , 2008, Nature Neuroscience.
[95] P. Glimcher,et al. Value Representations in the Primate Striatum during Matching Behavior , 2008, Neuron.
[96] Joseph J. Paton,et al. Moment-to-Moment Tracking of State Value in the Amygdala , 2008, The Journal of Neuroscience.
[97] M. Kimura,et al. Neuronal encoding of reward value and direction of actions in the primate putamen. , 2009, Journal of neurophysiology.
[98] D. Heeger,et al. The Normalization Model of Attention , 2009, Neuron.
[99] C. Padoa-Schioppa. Range-Adapting Representation of Economic Value in the Orbitofrontal Cortex , 2009, The Journal of Neuroscience.
[100] P. Glimcher,et al. The Neurobiology of Decision: Consensus and Controversy , 2009, Neuron.
[101] H. Seo,et al. Lateral Intraparietal Cortex and Reinforcement Learning during a Mixed-Strategy Game , 2009, Journal of Neuroscience.
[102] W. Schultz,et al. Adaptation of Reward Sensitivity in Orbitofrontal Neurons , 2010, The Journal of Neuroscience.
[103] Antonio Rangel,et al. Neural computations associated with goal-directed choice , 2010, Current Opinion in Neurobiology.
[104] M. Goldberg,et al. Attention, intention, and priority in the parietal lobe. , 2010, Annual review of neuroscience.
[105] James L. McClelland,et al. Integration of Sensory and Reward Information during Perceptual Decision-Making in Lateral Intraparietal Cortex (LIP) of the Macaque Monkey , 2010, PloS one.
[106] P. Glimcher. Foundations of Neuroeconomic Analysis , 2010 .
[107] V. Stuphorn,et al. Supplementary eye field encodes option and action value for saccades with variable reward. , 2010, Journal of neurophysiology.
[108] Kenway Louie,et al. Separating Value from Choice: Delay Discounting Activity in the Lateral Intraparietal Area , 2010, The Journal of Neuroscience.
[109] C. Padoa-Schioppa. Neurobiology of economic choice: a good-based model. , 2011, Annual review of neuroscience.
[110] P. Glimcher,et al. Reward Value-Based Gain Control: Divisive Normalization in Parietal Cortex , 2011, The Journal of Neuroscience.
[111] Paul Cisek,et al. Neural Correlates of Biased Competition in Premotor Cortex , 2011, The Journal of Neuroscience.
[112] P. Glimcher. Understanding dopamine and reinforcement learning: The dopamine reward prediction error hypothesis , 2011, Proceedings of the National Academy of Sciences.
[113] Joseph J Atick,et al. Could information theory provide an ecological theory of sensory processing? , 2011, Network.
[114] M. Carandini,et al. Normalization as a canonical neural computation , 2011, Nature Reviews Neuroscience.
[115] H. B. Barlow,et al. Possible Principles Underlying the Transformations of Sensory Messages , 2012 .