Publications

Bagur, S. , Averseng, M., Elgueda, D., David, S., Fritz, J., Yin, P., Shamma, S., Boubenec, Y. & Ostojic, S. (2018). Go/No-Go task engagement enhances population representation of target stimuli in primary auditory cortex. Nature Communications, 9, 2529 . doi:10.1038/s41467-018-04839-9

Bimbard, C., Ledoux, E. & Ostojic, S. (2016). Instability to a heterogeneous oscillatory state in randomly connected recurrent networks with delayed interactions. Physical review. E, 94(6-1), 062207. doi:10.1103/PhysRevE.94.062207

Blot, A., De Solages, C., Ostojic, S., Szapiro, G., Hakim, V. & Léna, C. (2016). Time-invariant feed-forward inhibition of Purkinje cells in the cerebellar cortex in vivo. The Journal of physiology, 594(10), 2729-49. doi:10.1113/JP271518

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

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

Correa, C. , Noorman, S. , Jiang, J. , Palminteri, S., Cohen, M. , Lebreton, M. & van Gaal, S. (2018). How the level of reward awareness changes the computational and electrophysiological signatures of reinforcement learning. Journal of Neuroscience , 0457-18. doi:10.1523/JNEUROSCI.0457-18.2018

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

Garcia, B., Cerrotti, F. & Palminteri, S. (2021). The description-experience gap: a challenge for the neuroeconomics of decision-making under uncertainty. Existence and prevalence of economic behaviours among non-human primates (The Royal Society ed., Vol. 376).Elsa Addessi, Thomas Boraud and Sacha Bourgeois-Gironde. doi:10.1098/rstb.2019.0665

Giavazzi, M., Daland, R., Palminteri, S., Peperkamp, S., Brugières, P., Jacquemot, C., Schramm, C., Cleret de Langavant, L. & Bachoud-Levi, A. (2018 ). The role of the striatum in linguistic selection: Evidence from Huntington’s disease and computational modeling. Cortex, 109, 189-204. doi:10.1016/j.cortex.2018.08.031

Graupner, M., Wallisch, P. & Ostojic, S. (2016). Natural Firing Patterns Imply Low Sensitivity of Synaptic Plasticity to Spike Timing Compared with Firing Rate. The Journal of Neuroscience, 36(44), 11238-11258. doi:10.1523/JNEUROSCI.0104-16.2016

Hertz, U., Palminteri, S., Brunetti, S., Olesen, C., Frith, C. & Bahrami, B. (2017). Neural computations underpinning the strategic management of influence in advice giving. Nature communications, 8(1), 2191. doi:10.1038/s41467-017-02314-5

Ioannou, C., Zein, M., Wyart, V., Scheid, I., Amsellem, F., Delorme, R., Chevallier, C. & Grèzes, J. (2017). Shared mechanism for emotion processing in adolescents with and without autism. Scientific reports, 7, 42696. doi:10.1038/srep42696

Jacquet, P., Wyart, V., Desantis, A., Hsu , Y. , Granjon, L. , Sergent, C. & Waszak, F. (2018). Human susceptibility to social influence and its neural correlates are related to perceived vulnerability to extrinsic morbidity risks. Scientific Reports, 8, 13347. doi:10.1038/s41598-018-31619-8

Lebreton, M. & Palminteri, S. (2016). When are inter-individual brain-behavior correlations informative? bioRxiv. doi:10.1101/036772

Lefebvre, G., Lebreton, M., Meyniel, F., Bourgeois-Gironde, S. & Palminteri, S. (2017). Behavioural and neural characterization of optimistic reinforcement learning. Nature Human Behaviour , 1(4), 0067

Lussange, J., Lazarevich, I. , Bourgeois-Gironde, S., Palminteri, S. & Gutkin, B. (2020). Modelling Stock Markets by Multi-agent Reinforcement Learning. Computational Economics, ., 1-35. doi:10.1007/s10614-020-10038-w

Maravall, M., Ostojic, S., Pressnitzer, D. & Chait, M. (2018). More than the Sum of its Parts: Perception and Neuronal Underpinnings of Sequence Processing. Neuroscience, in press. doi:10.1016/j.neuroscience.2018.07.043

Martí, D., Brunel, N. & Ostojic, S. (2018). Correlations between synapses in pairs of neurons slow down dynamics in randomly connected neural networks. Physical Review E, 97, 062314. doi:https://doi.org/10.1103/PhysRevE.97.062314

Mastrogiuseppe, F. & Ostojic, S. (2017). Intrinsically-generated fluctuating activity in excitatory-inhibitory networks. PLoS computational biology, 13(4), e1005498. doi:10.1371/journal.pcbi.1005498

Mastrogiuseppe, F. & Ostojic, S. (2018). Linking connectivity, dynamics and computations in recurrent neural networks. Neuron, 99(3), 609-623. doi:DOI:https://doi.org/10.1016/j.neuron.2018.07.003

Najar, A., Bonnet, E., Bahador, B. & Palminteri, S. (2020). The actions of others act as a pseudo-reward to drive imitation in the context of social reinforcement learning. PLoS Biology, 18 (12), e3001028. doi:10.1371/journal.pbio.3001028

Ostojic, S., Szapiro, G., Schwartz, E., Barbour, B., Brunel, N. & Hakim, V. (2015). Neuronal morphology generates high-frequency firing resonance. The Journal of Neuroscience, 35(18), 7056-68. doi:10.1523/JNEUROSCI.3924-14.2015

Ostojic, S. (2014). Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons. Nature Neuroscience, 17(4), 594-600. doi:10.1038/nn.3658

Ostojic, S. & Fusi, S. (2013). Synaptic encoding of temporal contiguity. Frontiers in computational neuroscience, 7, 32. doi:10.3389/fncom.2013.00032

Ostojic, S. (2011). Interspike interval distributions of spiking neurons driven by fluctuating inputs. Journal of neurophysiology, 106(1), 361-73. doi:10.1152/jn.00830.2010

Ostojic, S. & Brunel, N. (2011). From spiking neuron models to linear-nonlinear models. PLoS Computational Biology, 7(1), e1001056. doi:10.1371/journal.pcbi.1001056

Ostojic, S., Brunel, N. & Hakim, V. (2009). How connectivity, background activity, and synaptic properties shape the cross-correlation between spike trains. The Journal of Neuroscience, 29(33), 10234-53. doi:10.1523/JNEUROSCI.1275-09.2009

Ostojic, S., Brunel, N. & Hakim, V. (2009). Synchronization properties of networks of electrically coupled neurons in the presence of noise and heterogeneities. Journal of computational neuroscience, 26(3), 369-92. doi:10.1007/s10827-008-0117-3

Ostojic, S., Vlugt, T. & Nienhuis, B. (2007). Universal anisotropy in force networks under shear. Physical Review E, 75(3 Pt 1), 030301. doi:10.1103/PhysRevE.75.030301

Ostojic, S. & Panja, D. (2006). Elasticity from the force network ensemble in granular media. Physical Review Letters, 97(20), 208001. doi:10.1103/PhysRevLett.97.208001