We recently proposed that short-latency, sensory-evoked dopamine release is critical for learning action-outcome causality [1]. If an action causes an unexpected outcome associated with a phasic visual event, there will be a phasic burst of dopamine in the striatum. Subsequent reinforcement of the striatal response to the cortical representation of the action then makes the selection of the action (and its outcome) more likely; i.e. there is "repetition biasing" of action selection. This, in turn, facilitates associative learning of the action-outcome pairing elsewhere in the brain. Here, we present a model of cortico-striatal plasticity in medium spiny neurons (MSNs) that could form the basis for a quantitative account of action-outcome le...
Dopamine-dependent long-term plasticity is believed to be a cellular mechanism underlying reinforcem...
Abstract Organisms are able to learn from reward and punishment to cope with unknown situations, in ...
Abstract. Extending previous work, we introduce a spiking actor-critic network model of learning fro...
Operant learning requires that reinforcement signals interact with action representations at a suita...
The basal ganglia (BG), and more specifically the striatum, have long been proposed to play an essen...
Action discovery is the cognitive process of learning new actions to achieve desirable outcomes in t...
Abstract The reinforcement learning hypothesis of dopa-mine function predicts that dopamine acts as ...
Operant learning requires that reinforcement signals interact with action representations at a suita...
The basal ganglia are a dynamic neural network of telencephalic subcortical nuclei, involved in adap...
The basal ganglia (BG), and more specifically the striatum, have long been proposed to play an essen...
The striatum is the major input nucleus of basal ganglia, an ensemble of interconnected sub-cortical...
The basal ganglia network is thought to be involved in adaptation oforganism's behavior when facing ...
Learning from experience requires knowing whether a past action resulted in a desired outcome. The p...
International audienceDescribing cognition as cooperating learning mechanisms [1] is a fruitful way ...
In this work, we introduce a spiking actor-critic network model of learning from both reward and pun...
Dopamine-dependent long-term plasticity is believed to be a cellular mechanism underlying reinforcem...
Abstract Organisms are able to learn from reward and punishment to cope with unknown situations, in ...
Abstract. Extending previous work, we introduce a spiking actor-critic network model of learning fro...
Operant learning requires that reinforcement signals interact with action representations at a suita...
The basal ganglia (BG), and more specifically the striatum, have long been proposed to play an essen...
Action discovery is the cognitive process of learning new actions to achieve desirable outcomes in t...
Abstract The reinforcement learning hypothesis of dopa-mine function predicts that dopamine acts as ...
Operant learning requires that reinforcement signals interact with action representations at a suita...
The basal ganglia are a dynamic neural network of telencephalic subcortical nuclei, involved in adap...
The basal ganglia (BG), and more specifically the striatum, have long been proposed to play an essen...
The striatum is the major input nucleus of basal ganglia, an ensemble of interconnected sub-cortical...
The basal ganglia network is thought to be involved in adaptation oforganism's behavior when facing ...
Learning from experience requires knowing whether a past action resulted in a desired outcome. The p...
International audienceDescribing cognition as cooperating learning mechanisms [1] is a fruitful way ...
In this work, we introduce a spiking actor-critic network model of learning from both reward and pun...
Dopamine-dependent long-term plasticity is believed to be a cellular mechanism underlying reinforcem...
Abstract Organisms are able to learn from reward and punishment to cope with unknown situations, in ...
Abstract. Extending previous work, we introduce a spiking actor-critic network model of learning fro...