Publications

Pérez-Cervera, A. , Gutkin, B., J Thomas, P. & Lindner, B. (2023). A universal description of stochastic oscillators. Proceedings of the National Academy of Sciences of the United States of America, 120(29), e2303222120. doi:10.1073/pnas.2303222120

Lazarevich, I. , Prokin, I., Gutkin, B. & Kazantsev, V. (2023). Spikebench: An open benchmark for spike train time-series classification. PLoS computational biology, 19(1), e1010792. doi:10.1371/journal.pcbi.1010792

K Chillale, R., Shamma, S., Ostojic, S. & Boubenec, Y. (2023). Dynamics and maintenance of categorical responses in primary auditory cortex during task engagement. eLife, 12(e85706). doi:10.7554/eLife.85706

Gurnani, H. & Cayco Gajic, A. (2023). Signatures of task learning in neural representations. Signatures of task learning in neural representations, Current Opinion in Neurobiology,, 83, 102759. doi:10.1016/j.conb.2023.102759

Duriez, A., Bergerot, C., J Cone, J., F Roitman, M. & Gutkin, B. (2023). Homeostatic Reinforcement Theory Accounts for Sodium Appetitive State- and Taste-Dependent Dopamine Responding. Nutrients, 15(4), 1015. doi:10.3390/nu15041015

Cimesa, L., Ciric, L. & Ostojic, S. (2023). Geometry of population activity in spiking networks with low-rank structure. PLoS computational biology, 19(8), e1011315. doi:10.1371/journal.pcbi.1011315

Beiran, M., Meirhaeghe, N., Sohn, H., Jazayeri, M. & Ostojic, S. (2023). Parametric control of flexible timing through low-dimensional neural manifolds. Neuron, 111(5), 739-753.e8. doi:10.1016/j.neuron.2022.12.016

Pellegrino, A., Stein, H. & Alex Cayco-Gajic, N. (2024). Dimensionality reduction beyond neural subspaces with slice tensor component analysis. Nature neuroscience, . doi:10.1038/s41593-024-01626-2

Ostojic, S. & Fusi, S. (2024). Computational role of structure in neural activity and connectivity. Trends in cognitive sciences, 28(7), 677-690. doi:10.1016/j.tics.2024.03.003

Lussange, J., Vrizzi, S., Palminteri, S. & Gutkin, B. (2024). Mesoscale effects of trader learning behaviors in financial markets: A multi-agent reinforcement learning study. PloS one, 19(4), e0301141. doi:10.1371/journal.pone.0301141

D Cazé, R., Tran-Van-Minh, A., Gutkin, B. & A Digregorio, D. (2024). Demonstration that sublinear dendrites enable linearly non-separable computations. Scientific reports, 14(1), 18226. doi:10.1038/s41598-024-65866-9