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 credible account of how the brain keeps track of past sensory events that may be relevant to predicting future reward. Empirically, these shortcomings of previous theories are particularly evident in their account of experiments in which animals were exposed to variation in the timing of events. The original theories mispredicted the results of such experiments due to their use of a representational device called a tapped delay line. Here we propose that a richer understanding of history representation and a better account of these experiments ca...
An open problem in the field of computational neuroscience is how to link synaptic plasticity to sys...
Answering how animal brains measure the passage of time, and, make decisions about the timing of rew...
An open problem in the field of computational neuroscience is how to link synaptic plasticity to sys...
According to a series of influential models, dopamine (DA) neurons sig-nal reward prediction error u...
Temporal-difference learning (TD) models explain most responses of primate dopamine neurons in appet...
A cornerstone of current theorizing about dopamine’s computational role is the idea that the phasic ...
This article focuses on recent modeling studies of dopamine neuron activity and their influence on b...
Does dopamine code for uncertainty (Fiorillo, Tobler & Schultz, 2003; 2005) or is the sustained ...
A striking recent finding is that monkeys behave maladaptively in a class of tasks in which they kno...
Substantial evidence suggests that the phasic activities of dopaminergic neurons in the primate midb...
Anticipatory neural activity preceding behaviorally important events has been reported in cortex, st...
Neural activity in dopaminergic areas such as the ventral tegmental area is influenced by timing pro...
Animals use the neurotransmitter dopamine to encode the relationship between their responses and rew...
Midbrain dopamine neurons signal reward prediction error (RPE), or actual minus expected reward. The...
SummaryReward prediction error (RPE) signals are central to current models of reward-learning. Tempo...
An open problem in the field of computational neuroscience is how to link synaptic plasticity to sys...
Answering how animal brains measure the passage of time, and, make decisions about the timing of rew...
An open problem in the field of computational neuroscience is how to link synaptic plasticity to sys...
According to a series of influential models, dopamine (DA) neurons sig-nal reward prediction error u...
Temporal-difference learning (TD) models explain most responses of primate dopamine neurons in appet...
A cornerstone of current theorizing about dopamine’s computational role is the idea that the phasic ...
This article focuses on recent modeling studies of dopamine neuron activity and their influence on b...
Does dopamine code for uncertainty (Fiorillo, Tobler & Schultz, 2003; 2005) or is the sustained ...
A striking recent finding is that monkeys behave maladaptively in a class of tasks in which they kno...
Substantial evidence suggests that the phasic activities of dopaminergic neurons in the primate midb...
Anticipatory neural activity preceding behaviorally important events has been reported in cortex, st...
Neural activity in dopaminergic areas such as the ventral tegmental area is influenced by timing pro...
Animals use the neurotransmitter dopamine to encode the relationship between their responses and rew...
Midbrain dopamine neurons signal reward prediction error (RPE), or actual minus expected reward. The...
SummaryReward prediction error (RPE) signals are central to current models of reward-learning. Tempo...
An open problem in the field of computational neuroscience is how to link synaptic plasticity to sys...
Answering how animal brains measure the passage of time, and, make decisions about the timing of rew...
An open problem in the field of computational neuroscience is how to link synaptic plasticity to sys...