Jesse P. Geerts, Samuel J. Gershman, Neil Burgess, Kimberly L. Stachenfeld. (2023). A probabilistic successor representation for context-dependent prediction. Psychological Review, [DOI]
Geerts, J. P., Chersi, F., Stachenfeld, K. L., & Burgess, N. (2020). A general model of hippocampal and dorsal striatal learning and decision making. Proceedings of the National Academy of Sciences, 202007981. [DOI]
Phillips, M. G., Lenzi, S. C., & Geerts, J. P. (2017). Cortical predictive mechanisms of auditory response attenuation to self-generated sounds. Journal of Neuroscience, 37(22). [DOI]
Pinotsis, D. A., Geerts, J. P., Pinto, L., Fitzgerald, T. H. B., Litvak, V., Auksztulewicz, R., & Friston, K. J. (2017). Linking canonical microcircuits and neuronal activity: Dynamic causal modelling of laminar recordings. NeuroImage. [DOI]
Jiang, J., Correa, C. M., Geerts, J., & van Gaal, S. (2018). The relationship between conflict awareness and behavioral and oscillatory signatures of immediate and delayed cognitive control. NeuroImage, 177, 11–19. [DOI]
Conference proceedings
Geerts, J.P., Burgess, N. & Stachenfeld, K.L. Probabilistic Successor Features Allow for Flexible Behaviour. International Conference on Learning Representations, BAICS Workshop Paper[PDF]
Geerts, J.P., Stachenfeld, K.L. & Burgess, N. Probabilistic Successor Representations with Kalman Temporal Differences. Conference on Cognitive Computational Neuroscienc, Berlin, Germany 2019[DOI][PDF]
Talks and posters
Geerts, J.P. Context-dependent prediction with probabilistic successor representations. Poster at RLDM, Providence, 2022
Geerts, J.P. Prediction and uncertainty in the hippocampus. Invited talk at Theoretical and Cognitive Neuroscience lab, UPF Barcelona, 2021
Geerts, J.P. Uncertainty and the hippocampal predictive map. Invited talk at Gershman lab, Harvard University, 2020
Geerts, J.P. Learning distributed Successor Representations using Kalman Filters. Invited talk at Mila NeuroAI reading group, Montreal, CA 2020
Geerts, J.P., Stachenfeld, K.L. & Burgess, N. Probabilistic Successor Features allow for flexible behaviour. Spotlight Presentation at ICLR, 2020
Geerts, J.P., Stachenfeld, K.L. & Burgess, N. Probabilistic Successor Representations allow for flexible behaviour. Poster at Cosyne, Denver, CO 2020
Geerts, J.P. A probabilistic approach to learning Successor Representations. Invited talk at Behrens lab, UCL / University of Oxford
Geerts, J.P., Stachenfeld, K.L. & Burgess, N. Probabilistic Successor Representations with Kalman Temporal Differences. Poster at CCN, Berlin, Germany 2019
Geerts, J.P., Stachenfeld, K.L. & Burgess, N. Value, Prediction and Uncertainty in Hippocampus and Striatum. Bernstein Centre for Computational Neuroscience Retreat, Tutzing, Germany 2019
Geerts, J.P., Chersi, F., Stachenfeld, K.L. & Burgess, N. Hippocampal and striatal localisation and navigation strategies. HBP Neural SLAM Workshop, Paris, France 2019
Geerts, J.P., Chersi, F., Stachenfeld, K.L. & Burgess, N. Spatial reinforcement learning using allocentric and egocentric basis functions. Cosyne Coordinate Transforms Workshop, Lisbon, Portugal 2019
Stachenfeld, K.L., Geerts, J.P., Burgess, N., Behrens, T.E.J., Botvinick, M. & Gershman, S. Representation learning for exploration and generalization in RL. Society for Neuroscience Meeting, San Diego, USA 2018. [Abstract]
Geerts, J.P., Chersi, F., Stachenfeld, K.L. & Burgess, N. Modelling hippocampal and striatal contributions to reward-based navigation. iNav Symposium, Mont Tremblant, CA 2018.[Poster]
Preprints
Dimitriadis, G., Neto, J. P., … Geerts, J. P., … Kampff, A. R. (2018). Why not record from every channel with a CMOS scanning probe? BioRxiv.[DOI]