Reward prediction error neurons implement an efficient code for reward

HH Schütt, D Kim, WJ Ma - Nature Neuroscience, 2024 - nature.com
We use efficient coding principles borrowed from sensory neuroscience to derive the optimal
neural population to encode a reward distribution. We show that the responses of …

[PDF][PDF] Reward prediction error neurons implement an efficient code for reward

D Kim, HH Schütt, WJ Ma - scholar.archive.org
We apply efficient coding principles to derive the optimal population of neurons to encode
rewards from a distribution. Similar to this optimal population, dopaminergic reward …

Reward Prediction Error Neurons Implement an Efficient Code for Reward

D Kim, HH Schuett, WJ Ma - Proceedings of the Annual Meeting of …, 2022 - escholarship.org
Dopaminergic reward prediction error neurons in the midbrain are the most prominent type
of neurons encoding rewards. To explain the coding properties of these neurons, we apply …

Reward prediction error neurons implement an efficient code for reward

HH Schütt, D Kim, WJ Ma - 2022 - europepmc.org
We use efficient coding principles borrowed from sensory neuroscience to derive the optimal
population of neurons to encode rewards from a probability distribution. We find that the …

Reward prediction error neurons implement an efficient code for reward

HH Schütt, D Kim, WJ Ma - Nature neuroscience - pubmed.ncbi.nlm.nih.gov
We use efficient coding principles borrowed from sensory neuroscience to derive the optimal
neural population to encode a reward distribution. We show that the responses of …

Reward prediction error neurons implement an efficient code for reward

HH Schütt, D Kim, WJ Ma - bioRxiv, 2022 - biorxiv.org
We use efficient coding principles borrowed from sensory neuroscience to derive the optimal
population of neurons to encode rewards from a probability distribution. We find that the …

Reward prediction error neurons implement an efficient code for reward

D Kim, HH Schütt, WJ Ma - bioRxiv, 2022 - biorxiv.org
We apply efficient coding principles to derive the optimal population of neurons to encode
rewards from a distribution. Similar to this optimal population, dopaminergic reward …