What do reinforcement learning models measure? Interpreting model parameters in cognition and neuroscience

MK Eckstein, L Wilbrecht, AGE Collins - Current opinion in behavioral …, 2021‏ - Elsevier
Highlights•'Reinforcement learning'(RL) refers to different concepts in machine learning,
psychology, and neuroscience.•In psychology and neuroscience, RL models have provided …

The interpretation of computational model parameters depends on the context

MK Eckstein, SL Master, L **a, RE Dahl, L Wilbrecht… - Elife, 2022‏ - elifesciences.org
Reinforcement Learning (RL) models have revolutionized the cognitive and brain sciences,
promising to explain behavior from simple conditioning to complex problem solving, to shed …

Reinforcement learning and Bayesian inference provide complementary models for the unique advantage of adolescents in stochastic reversal

MK Eckstein, SL Master, RE Dahl, L Wilbrecht… - Developmental …, 2022‏ - Elsevier
During adolescence, youth venture out, explore the wider world, and are challenged to learn
how to navigate novel and uncertain environments. We investigated how performance …

Are adolescents more optimal decision‐makers in novel environments? Examining the benefits of heightened exploration in a patch foraging paradigm

A Lloyd, R McKay, CL Sebastian… - Developmental …, 2021‏ - Wiley Online Library
Adolescence is a period of heightened exploration relative to adulthood and childhood. This
predisposition has been linked with negative behaviours related to risk‐taking, including …

Local and global reward learning in the lateral frontal cortex show differential development during human adolescence

MK Wittmann, M Scheuplein, SG Gibbons… - PLoS …, 2023‏ - journals.plos.org
Reward-guided choice is fundamental for adaptive behaviour and depends on several
component processes supported by prefrontal cortex. Here, across three studies, we show …

Stochastic decisions support optimal foraging of volatile environments, and are disrupted by anxiety

A Lloyd, R McKay, N Furl - Cognitive, Affective, & Behavioral Neuroscience, 2025‏ - Springer
Adolescence is a developmental period of relative volatility, where the individual
experiences significant changes to their physical and social environment. The ability to …

Prepubertal ovariectomy alters dorsomedial striatum indirect pathway neuron excitability and explore/exploit balance in female mice

K Delevich, CD Hall, L Wilbrecht - bioRxiv, 2021‏ - biorxiv.org
Decision-making circuits are modulated across life stages (eg juvenile, adolescent, or adult)—
as well as on the shorter timescale of reproductive cycles in females—to meet changing …

Understanding the unique advantage of adolescents in stochastic, volatile environments: Combining reinforcement learning and Bayesian inference

MK Eckstein, SL Master, RE Dahl, L Wilbrecht… - 2020‏ - pure.mpg.de
During adolescence, youth venture out, explore the wider world, and are challenged to learn
how to navigate novel and uncertain environments. We investigated whether adolescents …

[PDF][PDF] Childhood internalising problems

I Costantini, I Costantini - children‏ - research-information.bris.ac.uk
The intergenerational transmission of poor mental health from parent to child is not
surprising given the multiple plausible pathways through which transmission could occur. In …

Three systems interact in one-shot reinforcement learning

AR Zou, AGE Collins - Proceedings of the Annual Meeting of the …, 2022‏ - escholarship.org
Human adaptive decision-making recruits multiple cognitive processes for learning stimulus-
action (SA) associations. These proceses include reinforcement learning (RL), which …