User profiles for Angela J. Langdon
Angela J. LangdonNational Institute of Mental Health Verified email at nih.gov Cited by 561 |
Dopaminergic prediction errors in the ventral tegmental area reflect a multithreaded predictive model
Dopamine neuron activity is tied to the prediction error in temporal difference reinforcement
learning models. These models make significant simplifying assumptions, particularly with …
learning models. These models make significant simplifying assumptions, particularly with …
Model-based predictions for dopamine
… Author links open overlay panel Angela J Langdon 1 , Melissa J Sharpe 1 2 3 , Geoffrey …
https://doi.org/10.1016/j.conb.2017.10.006 … http://dx.doi.org/10.1016/j.conb.2017.10.006 …
https://doi.org/10.1016/j.conb.2017.10.006 … http://dx.doi.org/10.1016/j.conb.2017.10.006 …
[PDF][PDF] Temporal specificity of reward prediction errors signaled by putative dopamine neurons in rat VTA depends on ventral striatum
Dopamine neurons signal reward prediction errors. This requires accurate reward predictions.
It has been suggested that the ventral striatum provides these predictions. Here we tested …
It has been suggested that the ventral striatum provides these predictions. Here we tested …
Value-free reinforcement learning: policy optimization as a minimal model of operant behavior
… Author links open overlay panel Daniel Bennett 1 2 , Yael Niv 1 3 , Angela J Langdon 1 …
https://doi.org/10.1016/j.cobeha.2021.04.020… Klaus, J. Alves da Silva, RM Costa …
https://doi.org/10.1016/j.cobeha.2021.04.020… Klaus, J. Alves da Silva, RM Costa …
Multi-frequency phase locking in human somatosensory cortex
Cortical population responses to sensory input arise from the interaction between external
stimuli and the intrinsic dynamics of the densely interconnected neuronal population. …
stimuli and the intrinsic dynamics of the densely interconnected neuronal population. …
Relative insensitivity to time-out punishments induced by win-paired cues in a rat gambling task
Rationale Pairing rewarding outcomes with audiovisual cues in simulated gambling games
increases risky choice in both humans and rats. However, the cognitive mechanism through …
increases risky choice in both humans and rats. However, the cognitive mechanism through …
[HTML][HTML] The utility of a latent-cause framework for understanding addiction phenomena
Computational models of addiction often rely on a model-free reinforcement learning (RL)
formulation, owing to the close associations between model-free RL, habitual behavior and …
formulation, owing to the close associations between model-free RL, habitual behavior and …
Uncovering the 'state': Tracing the hidden state representations that structure learning and decision-making
We review the abstract concept of a ‘state’ – an internal representation posited by
reinforcement learning theories to be used by an agent, whether animal, human or artificial, to …
reinforcement learning theories to be used by an agent, whether animal, human or artificial, to …
[HTML][HTML] Minimal cross-trial generalization in learning the representation of an odor-guided choice task
There is no single way to represent a task. Indeed, despite experiencing the same task
events and contingencies, different subjects may form distinct task representations. As …
events and contingencies, different subjects may form distinct task representations. As …
Beyond the average view of dopamine
AJ Langdon, ND Daw - Trends in cognitive sciences, 2020 - cell.com
Dopamine (DA) responses are synonymous with the ‘reward prediction error' of reinforcement
learning (RL), and are thought to update neural estimates of expected value. A recent …
learning (RL), and are thought to update neural estimates of expected value. A recent …