Naturalistic reinforcement learning

T Wise, K Emery, A Radulescu - Trends in Cognitive Sciences, 2024 - cell.com
Humans possess a remarkable ability to make decisions within real-world environments that
are expansive, complex, and multidimensional. Human cognitive computational …

Environmental statistics and experience shape risk-taking across adolescence

S Ciranka, R Hertwig - Trends in cognitive sciences, 2023 - cell.com
Adolescents are often portrayed as reckless risk-takers because of their immature brains.
Recent research has cast doubt on this portrayal, identifying the environment as a moderator …

Metacognitive computations for information search: Confidence in control.

L Schulz, SM Fleming, P Dayan - Psychological Review, 2023 - psycnet.apa.org
The metacognitive sense of confidence can play a critical role in regulating decision making.
In particular, a lack of confidence can justify the explicit, potentially costly, instrumental …

Anxiety as a disorder of uncertainty: Implications for understanding maladaptive anxiety, anxious avoidance, and exposure therapy

VM Brown, R Price, AY Dombrovski - Cognitive, Affective, & Behavioral …, 2023 - Springer
In cognitive-behavioral conceptualizations of anxiety, exaggerated threat expectancies
underlie maladaptive anxiety. This view has led to successful treatments, notably exposure …

Humans perseverate on punishment avoidance goals in multigoal reinforcement learning

PB Sharp, EM Russek, QJM Huys, RJ Dolan, E Eldar - Elife, 2022 - elifesciences.org
Managing multiple goals is essential to adaptation, yet we are only beginning to understand
computations by which we navigate the resource demands entailed in so doing. Here, we …

[HTML][HTML] Decision-Making, Pro-variance Biases and Mood-Related Traits

W Lin, RJ Dolan - Computational Psychiatry, 2024 - pmc.ncbi.nlm.nih.gov
In value-based decision-making there is wide behavioural variability in how individuals
respond to uncertainty. Maladaptive responses to uncertainty have been linked to a …

Political reinforcement learners

L Schulz, R Bhui - Trends in Cognitive Sciences, 2024 - cell.com
Politics can seem home to the most calculating and yet least rational elements of humanity.
How might we systematically characterize this spectrum of political cognition? Here, we …

Two steps to risk sensitivity

C Gagne, P Dayan - Advances in Neural Information …, 2021 - proceedings.neurips.cc
Distributional reinforcement learning (RL)–in which agents learn about all the possible long-
term consequences of their actions, and not just the expected value–is of great recent …

[HTML][HTML] An opponent striatal circuit for distributional reinforcement learning

AS Lowet, Q Zheng, M Meng, S Matias, J Drugowitsch… - bioRxiv, 2024 - ncbi.nlm.nih.gov
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 …

Modelling rumination as a state-inference process

RL Bedder, S Pisupati, Y Niv - … of the Annual Meeting of the …, 2023 - escholarship.org
Rumination is a kind of repetitive negative thinking that involves prolonged sampling of
negative episodes from one's past, typically prompted by a present negative experience. We …