Publications

Google Scholar

Journal articles

  • 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. Prediction and uncertainty in the hippocampus. Invited talk at Theoretical and Cognitive Neuroscience lab, UPF Barcelona, 2012
  • 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]