THE COGNITIVE NEUROSCIENCE OF MOTIVATION AND LEARNING (2009)
Nathaniel D. Daw, Daphna Shohamy, Mate Lengyel, Catherine Myers, Yael Niv, Shannon Tubridy, ...
Recent advances in the cognitive neuroscience of motivation and learning have demonstrated a critical role for midbrain dopamine and its targets in reward prediction. Converging evidence suggests...
Bernard W. Balleine, Nathaniel D. Daw, Bernard Balleine
Among the key findings in the behavioral psychology and systems neuroscience of decision-making is that the same behavior – for instance, a rat’s lever press – can arise from multiple...
A Dual Role for Prediction Error in Associative Learning (2009)
Friston, Karl J., Daw, Nathaniel D., McIntosh, Anthony R., Stephan, Klaas E.
Confronted with a rich sensory environment, the brain must learn statistical regularities across sensory domains to construct causal models of the world. Here, we used functional magnetic resonance...
et de recherche opérationnelle (2008)
Nathaniel D. Daw, Aaron C. Courville
Although theorists have interpreted classical conditioning as a laboratory model of Bayesian belief updating, a recent reanalysis showed that the key features that theoretical models capture about...
Département d’Informatique et (2008)
Nathaniel D. Daw, Aaron C. Courville
The rat as particle filter
Nathaniel D. Daw, Aaron C. Courville, David S. Tourtezky
Although the responses of dopamine neurons in the primate midbrain are well characterized as carrying a temporal difference (TD) error signal for reward prediction, existing theories do not offer a...
Aaron C. Courville, Nathaniel D. Daw, David S. Touretzky
The recent flowering of Bayesian approaches invites the re-examination of classic issues in behavior, even in areas as venerable as Pavlovian conditioning. A statistical account can offer a new,...
The rat as particle filter (2008)
Nathaniel D. Daw, Aaron C. Courville
The core tenet of Bayesian modeling is that subjects represent beliefs as distributions over possible hypotheses. Such models have fruitfully been applied to the study of learning in the context of...
Nathaniel D. Daw, David S. Touretzky
This article addresses the relationship between long-term reward predictions and slow-timescale neural activity in temporal difference (TD) models of the dopamine system. Such models attempt to...
Nathaniel D. Daw, David S. Touretzky
Operant behavior suggests attentional gating of
Semi-rational Models of Conditioning: The Case of Trial Order (2007)
Nathaniel D. Daw, Aaron C. Courville, Peter Dayan
Bayesian treatments of animal conditioning start from a generative model that specifies precisely a set of assumptions about the structure of the learning task. Optimal rules for learning are direct...
Semi-rational Models of Conditioning: The Case of Trial Order (2007)
Nathaniel D. Daw, Aaron C. Courville, Peter Dayan
Bayesian treatments of animal conditioning start from a generative model that specifies precisely a set of assumptions about the structure of the learning task. Optimal rules for learning are direct...
Yael Niv, Nathaniel D. Daw, Daphna Joel, Peter Dayan, Y. Niv, N. D. Daw, ...
Rationale Dopamine neurotransmission has long been known to exert a powerful influence over the vigor, strength, or rate of responding. However, there exists no clear understanding of the...
Nathaniel D. Daw, Yael Niv, Peter Dayan
The basal ganglia are widely believed to be involved in the learned selection of actions. Building on this idea, reinforcement learning (RL) theories of optimal control have had some success in...
Similarity and discrimination in classical conditioning: A latent variable account (2004)
Aaron C. Courville, Nathaniel D. Daw, David S. Touretzky
We propose a probabilistic, generative account of configural learning phenomena in classical conditioning. Configural learning experiments probe how animals discriminate and generalize between...
Similarity and discrimination in classical conditioning: A latent variable account (2004)
Aaron C. Courville, Nathaniel D. Daw, David S. Touretzky
We propose a probabilistic, generative account of configural learning phenomena in classical conditioning. Configural learning experiments probe how animals discriminate and generalize between...
Reinforcement learning models of the dopamine system and their behavioral implications / (2003)
"August 2003."
A computational substrate for incentive (2003)
Samuel M. Mcclure, Nathaniel D. Daw, P. Read Montague
salience
Timing and partial observability in the dopamine system (2003)
Nathaniel D. Daw, Aaron C. Courville, David S. Touretzky
According to a series of influential models, dopamine (DA) neurons signal reward prediction error using a temporal-difference (TD) algorithm. We address a problem not convincingly solved in these...
Timing and partial observability in the dopamine system (2003)
Nathaniel D. Daw, Aaron C. Courville, David S. Touretzky
According to a series of influential models, dopamine (DA) neurons signal reward prediction error using a temporal-difference (TD) algorithm. We address a problem not convincingly solved in these...
Nathaniel D. Daw, L. Mcclelland, Andrew W. Moore, William E. Skaggs
learning models of the dopamine system
Nathaniel D. Daw, L. Mcclelland, Andrew W. Moore, William E. Skaggs
learning models of the dopamine system
Combining configural and TD learning on a robot (2002)
David S. Touretzky, Nathaniel D. Daw
We combine configural and temporal difference learning in a classical conditioning model. The model is able to solve the negative patterning problem, discriminate sequences of stimuli, and exhibit...
Dopamine And Inference, Nathaniel D. Daw
Temporal-di#erence learning (TD) models explain most responses of primate dopamine neurons in appetitive conditioning. But because existing models are based in the simple formal setting of Markov...
Dopamine And Inference, Nathaniel D. Daw, Aaron C. Courville, David S. Touretzky
Temporal-di#erence learning (TD) models explain most responses of primate dopamine neurons in appetitive conditioning. But because existing models are based in the simple formal setting of Markov...
Striatal Activity Underlies Novelty-Based Choice in Humans
Wittmann, Bianca C., Daw, Nathaniel D., Seymour, Ben, Dolan, Raymond J.
The desire to seek new and unfamiliar experiences is a fundamental behavioral tendency in humans and other species. In economic decision making, novelty seeking is often rational, insofar as...
A Dual Role for Prediction Error in Associative Learning
Friston, Karl J., Daw, Nathaniel D., McIntosh, Anthony R., Stephan, Klaas E.
Confronted with a rich sensory environment, the brain must learn statistical regularities across sensory domains to construct causal models of the world. Here, we used functional magnetic resonance...