Song, Mingyu, Yuji Takahashi, Amanda Burton, Matthew Roesch, Geoffrey Schoenbaum, Yael Niv, and Angela Langdon. 2022. “Minimal Cross-Trial Generalization in Learning the Representation of an Odor-Guided Choice Task”. PLOS Computational Biology 18 (3). PDF: Minimal cross-trial generalization in learning the representation of an odor-guided choice task.

Bennett, Daniel, Yael Niv, and Angela Langdon. 2021. “Value-Free Reinforcement Learning: Policy Optimization As a Minimal Model of Operant Behavior”. Current Opinion in Behavioral Sciences 41: 114–121. PDF: Value-free reinforcement learning: policy optimization as a minimal model of operant behavior.

Langdon, Angela, and Nathaniel Daw. 2020. “Beyond the Average View of Dopamine”. Trends in Cognitive Sciences. doi:10.1016/j.tics.2020.04.006.

Langdon, Angela, Mingyu Song, and Yael Niv. (2019) 2019. “Uncovering the ‘state’: Tracing the Hidden State Representations That Structure Learning and Decision-Making”. Behavioural Processes 167: 103891. doi:10.1016/j.beproc.2019.103891.

Langdon, Angela, Melissa Sharpe, Geoffrey Schoenbaum, and Yael Niv. (2018) 2018. “Model-Based Predictions for Dopamine”. Current Opinion in Neurobiology 49: 1–7. doi:10.1016/j.conb.2017.10.006.

Niv, Yael, and Angela Langdon. 2016. “Reinforcement Learning With Marr”. Current Opinion in Behavioral Sciences 11: 67–73. doi:http://dx.doi.org/10.1016/j.cobeha.2016.04.005.

Niv, Yael, Angela Langdon, and Angela Radulescu. (2015) 2015. “A Free-Choice Premium in the Basal Ganglia”. Trends in Cognitive Sciences 19 (1): 4–5. doi:10.1016/j.tics.2014.09.005.