Publications

Jardri, R. & Denève, S. (2017). [Jumping-to-conclusions in schizophrenia is mediated by circular inference]. Medecine sciences : M/S, 33(11), 933-935. doi:10.1051/medsci/20173311006

Caze, R., Humphries, M., Gutkin, B. & Schultz, S. (2013). A difficult classification for neurons without dendrites. In Neural Engineering (NER), 2013 6th International IEEE/EMBS Conference on, San Diego, CA, USA, IEEE, 215-218. doi:10.1109/NER.2013.6695910

Stefanini, F. , A. Kheirbek, M. , Kushnir, L., C. Jimenez, J. , H. Jennings, J. , D. Stuber, G. , Hen, R. & Fusi, S. (2018). A distributed neural code in the dentate gyrus and in CA1. . doi:10.1101/292953

Leptourgos, P., Bouttier, V., Jardri, R. & Denève, S. (2021). A functional theory of bistable perception based on dynamical circular inference. Plos Computational Biology, 16(12), e1008480. doi:10.1371/journal.pcbi.1008480

Mastrogiuseppe, F. & Ostojic, S. (2019). A geometrical description of global dynamics in trained feedback networks. Neural Computation, 31(6), 1139-1182. doi:10.1162/neco_a_01187

Barbosa, J., Stein, H., Zorowitz, S. , Niv, Y. , Summerfield, C., Soto-Faraco, S. & Hyafil, A. (2022). A practical guide for studying human behavior in the lab. Behavior Research Methods. doi:10.3758/s13428-022-01793-9

Oster, A. & Gutkin, B. (2011). A reduced model of DA neuronal dynamics that displays quiescence, tonic firing and bursting. Journal of Physiology Paris, 105, 53-58. doi:10.1016/j.jphysparis.2011.07.012

Keramati, M. & Gutkin, B. (2011). A Reinforcement Learning Theory for Homeostatic Regulation. NIPS, .

Mcdonnell, M., Iannella, N., To, M., Tuckwell, H., Jost, J., Gutkin, B. & Ward, L. (2015). A review of methods for identifying stochastic resonance in simulations of single neuron models. Network: Computation in Neural Systems, 26(2), 35-71. doi:10.3109/0954898X.2014.990064

Barbosa, J., Babushkin, V. , Temudo, A. , Sreenivasan, K. & Compte, A. (2021). Across-Area Synchronization Supports Feature Integration in a Biophysical Network Model of Working Memory. Front. Neural Circuits. doi:10.3389/fncir.2021.716965

Jedlicka, P., Deller, T., Gutkin, B. & Backus, K. (2011). Activity-dependent intracellular chloride accumulation and diffusion controls GABA(A) receptor-mediated synaptic transmission. Hippocampus, 21(8), 885-98. doi:10.1002/hipo.20804

Ghambaryan, A., Gutkin, B., Klucharev, V. & Koechlin, E. (2021). Additively Combining Utilities and Beliefs: Research Gaps and Algorithmic Developments. Frontiers in Neuroscience, . doi:10.3389/fnins.2021.704728

Fontolan, L., Krupa, M., Hyafil, A. & Gutkin, B. (2013). Analytical insights on theta-gamma coupled neural oscillators. Journal of Mathematical Neuroscience, 3(1), 1-20. doi:10.1186/2190-8567-3-16

V Kuchibhotla, K. , Hindmarsh Sten, T., C. Papadoyannis, E. , Elnozahy, S. , Fogelson, K. , Chillale, R. , Boubenec, Y., C. Holland, P. , Ostojic, S. & C. Froemke, R. (2020). Author Correction: Dissociating task acquisition from expression during learning reveals latent knowledge. Nat Commun, 11(3176). doi:10.1038/s41467-020-17023-9

Chambon, V., Thero, H., Findling, C. & Koechlin, E. (2018). Believing in one's power: a counterfactual heuristic for goal-directed control. bioRxiv, 498675. doi:10.1101/498675

Leptourgos, P., Denève, S. & Jardri, R. (2017). Can circular inference relate the neuropathological and behavioral aspects of schizophrenia? Current opinion in neurobiology, 46, 154-161. doi:10.1016/j.conb.2017.08.012

Jardri, R., Leptourgos, P., Bouttier, V. & Denève, S. (2020). Circular Inference and Hallucinations. Biological Psychiatry, 87(9), S41-S42. doi:10.1016/j.biopsych.2020.02.131

Leptourgos, P., Notredame, C., Jardri, R., Denève, S. & Eck, M. (2020). Circular inference in bistable perception. Journal of Vision, 20(12), 521195. doi:10.1167/jov.20.4.12

Bouttier, V., Duttagupta, S. , Denève, S. & Jardri, R. (2022). Circular inference predicts nonuniform overactivation and dysconnectivity in brain-wide connectomes. Schizophrenia Research, 245, 59-67. doi:10.1016/j.schres.2020.12.045

Tolu, S., Eddine, R., Marti, F., David, V., Graupner, M., Pons, S., Baudonnat, M., Husson, M., Besson, M., Reperant, C., Zemdegs, J., Pagès, C., Hay, Y., Lambolez, B., Caboche, J., Gutkin, B., Gardier, A., Changeux, J., Faure, P. & Maskos, U. (2013). Co-activation of VTA da and GABA neurons mediates nicotine reinforcement. Molecular Psychiatry, 18(3), 382-393. doi:10.1038/mp.2012.83

Bondanelli, G. & Ostojic, S. (2020). Coding with transient trajectories in recurrent neural networks. PLoS Computational Biology, 16 (2), e1007655. doi:10.1371/journal.pcbi.1007655

Koren, V. & Denève, S. (2017). Computational Account of Spontaneous Activity as a Signature of Predictive Coding. PLoS computational biology, 13(1), e1005355. doi:10.1371/journal.pcbi.1005355

Koechlin, E. (2021). Computational models of adaptive behavior and prefrontal cortex. Neuropsychopharmacology, 47, 58–71. doi:10.1038/s41386-021-01123-1

Gutkin, B. & Ahmed, S. (2012). Computational Neuroscience of Drug Addiction.

Beiran, M. & Ostojic, S. (2019). Contrasting the effects of adaptation and synaptic filtering on the timescales of dynamics in recurrent networks . PLoS Computational Biology, 15(3), e1006893. doi:10.1371/journal.pcbi.1006893

Tran-Van-Minh, A., Caze, R., Abrahamsson, T., Cathala, L., Gutkin, B. & Digregorio, D. (2015). Contribution of sublinear and supralinear dendritic integration to neuronal computations. Frontiers in cellular neuroscience, 9, 67. doi:10.3389/fncel.2015.00067

Dipoppa, M. & Gutkin, B. (2013). Correlations in background activity control persistent state stability and allow execution of working memory tasks. Frontiers in Computational Neuroscience, 7, 139. doi:10.3389/fncom.2013.00139

Wu, J., Gao, M., Shen, J., Shi, W., Oster, A. & Gutkin, B. (2013). Cortical control of VTA function and influence on nicotine reward. Biochemical Pharmacology, 86(8), 1173-1180. doi:10.1016/j.bcp.2013.07.013

Oswald, A. & Ostojic, S. (2020). Curating more diverse scientific conferences. Nat Rev Neurosci, 21, 589-590. doi:10.1038/s41583-020-0373-4

Dubreuil, A., Valente, A., Mastrogiuseppe, F. & Ostojic, S. (2019). Disentangling the roles of dimensionality and cell classes in neural computation. In NeurIPS Workshop.