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Representational spaces in orbitofrontal and ventromedial prefrontal cortex: task states, values, and beyond
N Moneta, S Grossman, NW Schuck - Trends in Neurosciences, 2024 - cell.com
The orbitofrontal cortex (OFC) and ventromedial-prefrontal cortex (vmPFC) play a key role in
decision-making and encode task states in addition to expected value. We review evidence …
decision-making and encode task states in addition to expected value. We review evidence …
Dissociable Representations of Decision Variables within Subdivisions of the Macaque Orbital and Ventrolateral Frontal Cortex
FM Stoll, PH Rudebeck - Journal of Neuroscience, 2024 - jneurosci.org
The ventral frontal cortex (VFC) in macaques is involved in many affective and cognitive
processes and has a key role in flexibly guiding reward-based decision-making. VFC is …
processes and has a key role in flexibly guiding reward-based decision-making. VFC is …
Advanced reinforcement learning and its connections with brain neuroscience
C Fan, L Yao, J Zhang, Z Zhen, X Wu - Research, 2023 - spj.science.org
In recent years, brain science and neuroscience have greatly propelled the innovation of
computer science. In particular, knowledge from the neurobiology and neuropsychology of …
computer science. In particular, knowledge from the neurobiology and neuropsychology of …
An opponent striatal circuit for distributional reinforcement learning
AS Lowet, Q Zheng, M Meng, S Matias, J Drugowitsch… - Nature, 2025 - nature.com
Abstract Machine learning research has achieved large performance gains on a wide range
of tasks by expanding the learning target from mean rewards to entire probability …
of tasks by expanding the learning target from mean rewards to entire probability …
Distributed representations of temporally accumulated reward prediction errors in the mouse cortex
H Makino, A Suhaimi - Science Advances, 2025 - science.org
Reward prediction errors (RPEs) quantify the difference between expected and actual
rewards, serving to refine future actions. Although reinforcement learning (RL) provides …
rewards, serving to refine future actions. Although reinforcement learning (RL) provides …
Dopamine neurons encode a multidimensional probabilistic map of future reward
Learning to predict rewards is a fundamental driver of adaptive behavior. Midbrain
dopamine neurons (DANs) play a key role in such learning by signaling reward prediction …
dopamine neurons (DANs) play a key role in such learning by signaling reward prediction …
Distributional bellman operators over mean embeddings
LK Wenliang, G Delétang, M Aitchison, M Hutter… - arxiv preprint arxiv …, 2023 - arxiv.org
We propose a novel algorithmic framework for distributional reinforcement learning, based
on learning finite-dimensional mean embeddings of return distributions. We derive several …
on learning finite-dimensional mean embeddings of return distributions. We derive several …
The representational instability in the generalization of fear learning
K Yu, W Vanpaemel, F Tuerlinckx, J Zaman - npj Science of Learning, 2024 - nature.com
Perception and perceptual memory play crucial roles in fear generalization, yet their
dynamic interaction remains understudied. This research (N= 80) explored their relationship …
dynamic interaction remains understudied. This research (N= 80) explored their relationship …
A cognitive map for value-guided choice in ventromedial prefrontal cortex
S Veselic, TH Muller, E Gutierrez, TEJ Behrens… - …, 2023 - pmc.ncbi.nlm.nih.gov
The prefrontal cortex is crucial for economic decision-making and representing the value of
options. However, how such representations facilitate flexible decisions remains unknown …
options. However, how such representations facilitate flexible decisions remains unknown …
NeuroAI for AI Safety
P Mineault, N Zanichelli, JZ Peng, A Arkhipov… - arxiv preprint arxiv …, 2024 - arxiv.org
As AI systems become increasingly powerful, the need for safe AI has become more
pressing. Humans are an attractive model for AI safety: as the only known agents capable of …
pressing. Humans are an attractive model for AI safety: as the only known agents capable of …