Published journal articles

Context is key for learning motor skills [PDF]
Collins and McDougle (2021)

How working memory and reinforcement learning are intertwined: a cognitive, neural, and computational perspective [PsyArXiv]
Yoo and Collins (2021)
PsyArXiv preprint

Executive Function Assigns Value to Novel Goal-Congruent Outcomes [pdf]
McDougle, Ballard, Baribault, Bishop, and Collins (2021)
Cerebral Cortex

What do reinforcement learning models measure? Interpreting model parameters in cognition and neuroscience [pdf]
Eckstein, Wilbrecht, and Collins (2021)
Current Opinion in Behavioral Sciences

Learning Rates Are Not All the Same: The Interpretation of Computational Model Parameters Depends on the Context [bioRxiv]
Eckstein, Master, Xia, Dahl, Wilbrecht, and Collins (2021)
bioRxiv Preprint

Proof-of-Mechanism Study of the PDE10 Inhibitor RG7203 in Patients with Schizophrenia and Negative Symptoms [pdf]
Umbricht D, Abt M, Tamburri P, Chatham C, Holiga Š, Frank MJ, Collins AGE, Walling DP, Mofsen R, Gruener D, Gertsik L, Sevigny J, Keswani S & Dukart J (2021)
Biological Psychiatry Global Open Science

Beyond simple dichotomies in reinforcement learning. [pdf]
Collins and Cockburn (2020)
Nature Reviews Neuroscience

Modeling the influence of working memory, reinforcement, and action uncertainty on reaction time and choice during instrumental learning [pdf]
McDougle and Collins (2020)
Psychonomic Bulletin & Review

Understanding the Unique Advantage of Adolescents in Stochastic, Volatile Environments: Combining Reinforcement Learning and Bayesian Inference [bioRxiv]
Eckstein, Master, Dahl, Wilbrecht, and Collins (2020)
bioRxiv Preprint

The Role of Executive Function in Shaping Reinforcement Learning [pdf] [psyArXiv]
Rmus, McDougle, and Collins (2020)
Current Opinion in Behavioral Sciences

Temporal and state abstractions for efficient learning, transfer and composition in humans [pdf] [SI]
Xia and Collins (2020)
Psychological Review (in press)

Learning under uncertainty changes during adolescence [pdf]
Xia, Master, Eckstein, Wilbrecht, and Collins (2020)
CogSci 2020 Submission

What is a Choice in Reinforcement Learning? [pdf]
Rmus and Collins (2020)
CogSci 2020 Submission

Computational Evidence for Hierarchically-Structured Reinforcement Learning in Humans [bioRxiv]
Eckstein and Collins (2020)

Disentangling the systems contributing to changes in learning during adolescence [pdf]
Master, Eckstein, Gotlieb, Dahl, Wilbrecht, and Collins (2020)
Developmental Cognitive Neuroscience

Ten simple rules for the computational modeling of behavioral data [pdf] [example code]
Wilson and Collins (2019)

Reinforcement learning: bringing together computation and cognition [pdf]
Collins (2019)
Current Opinion in Behavioral Sciences

Event segmentation reveals working memory forgetting rate [pdf] [bioRxiv]
Jafarpour, Buffalo, Knight, and Collins (2019)
bioRxiv Preprint

Chapter 5: Learning Structures Through Reinforcement [pdf]
Collins, AGE (2018)
Goal-Directed Decision Making

Sequential control underlies robust ramping dynamics in the rostrolateral prefrontal cortex [pdf]
Desrochers, Collins, and Badre (2018)
Journal of Neuroscience

The tortoise and the hare: interactions between reinforcement learning and working memory [pdf] [summary]
Collins, AGE (2018)
Journal of Cognitive Neuroscience

Within and across-trial dynamics of human EEG reveal cooperative interplay between reinforcement learning and working memory [pdf]
Collins, AGE and Frank, MJ (2018)

Interactions Among Working Memory, Reinforcement Learning, and Effort in Value-Based Choice: A New Paradigm and Selective Deficits in Schizophrenia [pdf]
Collins, AGE, Albrecht, MA, Waltz, JA, Gold, JM and Frank, MJ (2017)
Biological Psychiatry

Prefrontal Cortex in Control: Broadening the Scope to Identify Mechanisms [pdf]
Alexander, WH, Brown, JW, Collins, AGE, Hayden, BY, and Vassena, E (2017)
Journal of Cognitive Neuroscience

Working memory load strengthens reward prediction errors [pdf] [SI]
Collins, AGE, Ciullo, B, Frank, MJ, and Badre, D. (2017)
Journal of Neuroscience

The cost of structure learning [pdf]
Collins, AGE (2017)
Journal of Cognitive Neuroscience

Stimulus discriminability may bias value-based probabilistic learning [pdf]
Schutte, I, Slagter, HA, Collins, AGE, Frank, MJ, and Kenemans, JL (2017)
PLoS One

Role of Prefrontal Cortex in Learning and Generalizing Hierarchical Rules in 8-Month-Old Infants [pdf]
Werchan, DM, Collins, AGE, Frank, MJ, and Amso, D (2016)
The Journal of Neuroscience

Probabilistic Reinforcement Learning in Patients with Schizophrenia: Relationships to Anhedonia and Avolition [pdf]
Dowd, EC, Frank, MJ, Collins, AGE, Gold, JM, and Barch, DM (2016)
Biological Psychiatry

Neural signature of hierarchically structured expectations predicts clustering and transfer of rule sets in reinforcement learning [pdf]
Collins, AGE, Frank, MJ (2016)

Motor demands constrain cognitive rule structures [pdf]
Collins, AGE, and Frank, MJ (2016)
Plos Computational Biology

Surprise! dopamine signals mix action, value and error [pdf]
Collins, AGE, and Frank, MJ (2015)
Nature Neuroscience

8-Month-Old infants spontaneously learn and generalize hierarchical rules [pdf]
Werchan, DM, Collins, AGE, Frank, MJ, and Amso, D (2015)
Psychological Science

Working memory contributions to reinforcement learning impairments in schizophrenia [pdf]
Collins, AGE, Brown, J, Gold, J, Waltz, J, and Frank, MJ (2014)
Journal of Neuroscience

A reinforcement learning mechanism responsible for the valuation of free choice [pdf]
Cockburn, J, Collins, AGE, and Frank, MJ (2014)

Opponent Actor Learning (OpAL): modeling interactive effect of striatal dopamine on reinforcement learning and choice incentive [pdf]
Collins, AGE and Frank, MJ. (2014)
Psychological Review

Foundations of human reasoning in the prefrontal cortex [pdf]
Donoso, M, Collins, AGE, Koechlin, E. (2014)

Human EEG uncovers latent generalizable rule structure during learning [pdf]
Collins, AGE, Cavanagh, JF, and Frank, MJ (2014)
Journal of Neuroscience

Cognitive control over learning: creating, clustering and generalizing task-set structure [pdf]
Collins, AGE and Frank, MJ. (2013)
Psychological Review

How much of reinforcement learning is working memory, not reinforcement learning? A behavioral, computational and neurogenetic analysis [pdf]
Collins, AGE and Frank, MJ. (2012)
European Journal of Neuroscience

Negative symptoms and the failure to represent the expected reward value of actions: behavioral and computational modeling evidence [pdf]
Gold, JM; Waltz, JA; Matveeva, TM; Kasanova, Z; Strauss, G; Herbener, E; Collins, AGE; Frank, MJ (2012)
Arch Gen Psychiatry

Reasoning, learning, and creativity: frontal lobe function and human decision-making [pdf]
Collins A, Koechlin E (2012)
PLoS Biology

A computational theory of prefrontal executive control
Collins, A. and Koechlin, E. (2009)
Frontiers in Systems Neuroscience

Computational models and code

This is a link to the neural network model simulated in Collins & Frank, 2013, Psychological Review. It is a model of task-set structure learning in hierarchical corticostriatal circuits. It runs on the emergent neural simulator (Aisa et al., 2008). Details about emergent and previous neural networks on which this network builds can be found on Michael Frank's basal ganglia projects webpage, here.

This network includes a two-stage cascaded basal ganglia loop circuit enabling hierarchical control of action selection and learning by generating task-set structure, generalizable to novel situations. The model selects among four different motor actions, and at the higher level, three possible task-sets, and simultaneously learns to create (or re-use) abstract task-sets while also learning the particular response mappings given the selected task-set, using pure reinforcement learning.

This matlab script can be used for more detailed analysis of model output showing transfer, and here is an example mat file. Similarly, for more detailed analysis of a case in which there is incentive to clustering task-sets around context during initial learning, please use this matlab script.

The computations of this model were linked to those of a higher level "C-TS" (context task-set) model based on a non-parametric Bayesian approach to clustering task-sets using a Chinese Restaurant Process. Here is a single zip file including simulations from the C-TS model in matlab.