Publications

Wyart, V. (2018). Leveraging decision consistency to decompose suboptimality in terms of its ultimate predictability. Behavioral and Brain Sciences, 41, e248. doi:10.1017/S0140525X18001504

Courty, A., Maria, A., Lalanne, C., Ringuenet, D., Vindreau, C., Chevallier, C., Pouga, L., Pinabel, F., Philippe, A., Adrien, J., Barry, C. & Berthoz, S. (2013). Levels of autistic traits in anorexia nervosa: a comparative psychometric study. BMC psychiatry, 13, 222. doi:10.1186/1471-244X-13-222

Grèzes, J. (2011). Les émotions, modes d’action et de communication. Med Sci (Paris), 27(8-9), 683-684. doi:10.1051/medsci/2011278001

Brendel, W. , Bourdoukan, R., Vertechi, P. , Machens, C. & Denève, S. (2020). Learning to represent signals spike by spike. PLOS Computational Biology, 16(3), e1007692. doi:10.1371/journal.pcbi.1007692

Lussange, J., Belianin, A., Bourgeois-Gironde, S. & Gutkin, B. (2021). Learning and Cognition in Financial Markets: A Paradigm Shift for Agent-Based Models. Advances in Intelligent Systems and Computing (Vol. 1252, pp. 241-255). doi:10.1007/978-3-030-55190-2_19

Simeone, O. , Rajendran, B. , Gruning, A. , Eleftheriou, E. , Davies, M. , Denève, S. & Huang, G. (2019). Learning Algorithms and Signal Processing for Brain-Inspired Computing. IEEE Signal Processing Magazine, 36(6), 12-15. doi:10.1109/MSP.2019.2935557

Babo-Rebelo, M., Wolpert, N., Adam, C., Hasboun, D. & Tallon-Baudry, C. (2016). Is the cardiac monitoring function related to the self in both the default network and right anterior insula? Philosophical Transactions B, 371(1708), 20160004. doi:10.1098/rstb.2016.0004

Sidarus, N., Vuorre, M., Metcalfe, J. & Haggard, P. (2017). Investigating the Prospective Sense of Agency: Effects of Processing Fluency, Stimulus Ambiguity, and Response Conflict. Frontiers in psychology, 8, 545. doi:10.3389/fpsyg.2017.00545

Buchin, A., Rieubland, S., Häusser, M., Gutkin, B. & Roth, A. (2016). Inverse Stochastic Resonance in Cerebellar Purkinje Cells. PLoS computational biology, 12(8), e1005000. doi:10.1371/journal.pcbi.1005000

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

Krupa, M., Gielen, S. & Gutkin, B. (2014). Intrinsic and synaptic mechanisms for clustered cortical gamma. J Comput. Neurosci , 37(2), 357-76

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

Jazayeri, M. & Ostojic, S. (2021). Interpreting neural computations by examining intrinsic and embedding dimensionality of neural activity. Current Opinion in Neurobiology, 70, 113-120. doi:10.1016/j.conb.2021.08.002

Engelen, T., Solca, M. & Tallon-Baudry, C. (2023). Interoceptive rhythms in the brain. Nature neuroscience, 26, 1670–1684. doi:10.1038/s41593-023-01425-1

Tallon-Baudry, C. (2023). Interoception: Probing internal state is inherent to perception and cognition. Neuron, . doi:10.1016/j.neuron.2023.04.019

Petzschner, F., Critchley, H. & Tallon-Baudry, C. (2022). Interoception. Scholarpedia, . doi:10.4249/scholarpedia.55569

Najar, A., Sigaud, O. & Chetouani , M. (2020). Interactively shaping robot behaviour with unlabeled human instructions. Auton Agent Multi-Agent Syst, 34(35). doi:10.1007/s10458-020-09459-6

Weiss, A., Chambon, V., Drugowitsch, J. & Wyart, V. (2021). Interacting with volatile environments stabilizes hidden-state inference and its brain signatures. Nature Communications, 12, 2228. doi:10.1038/s41467-021-22396-6

Sidarus, N., Vuorre, M. & Haggard, P. (2017). Integrating prospective and retrospective cues to the sense of agency: a multi-study investigation. Neuroscience of Consciousness, 2017(1). doi:10.1093/nc/nix012

Van Den Stock, J., Peretz, I., Grèzes, J. & De Gelder, B. (2009). Instrumental music influences recognition of emotional body language. Brain topography, 21(3-4), 216-20. doi:10.1007/s10548-009-0099-0

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

Tuckwell, H., Jost, J. & Gutkin, B. (2009). Inhibition and modulation of rhythmic neuronal spiking by noise. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 80(3). doi:10.1103/PhysRevE.80.031907

Yesilaltay , S., Hacquin, A., Chevallier, C. & Mercier, H. (2021). Information delivered by a chatbot has a positive impact on COVID-19 vaccines attitudes and intentions. Journal of Experimental Psychology: Applied. doi:10.1037/xap0000400

Chambon, V., Thero, H., Vidal, M., Vandendriessche, H., Haggard, P. & Palminteri, S. (2020). Information about action outcomes differentially affects learning from self-determined versus imposed choices. Nature Human Behaviour , 4, 1067-1079. doi:10.1038/s41562-020-0919-5

Engelen, T., Zhan, M. & de Gelder, B. (2019). Influence of continuous flash suppression mask frequency on stimulus visibility. Neuropsychologia, 128, 65-72. doi:10.1016/j.neuropsychologia.2018.05.012

Ladenbauer, J., McKenzie , S., English , D., Hagens , O. & Ostojic, S. (2019). Inferring and validating mechanistic models of neural microcircuits based on spike-train data. Nature Communications, 10(4933). doi:10.1038/s41467-019-12572-0

Pouga, L., Berthoz, S., De Gelder, B. & Grèzes, J. (2010). Individual differences in socioaffective skills influence the neural bases of fear processing: the case of alexithymia. Human brain mapping, 31(10), 1469-81. doi:10.1002/hbm.20953

Balsdon, T., Summersby, S., Kemp, R. & White, D. (2018). Improving face identification with specialist teams. Cognitive Research: Principles and Implications, 3(1), 25. doi:10.1186/s41235-018-0114-7

Findling, C., Chopin, N. & Koechlin, E. (2021). Imprecise neural computations as a source of adaptive behaviour in volatile environments. Nature Human Behaviour , 5, 99-112. doi:10.1038/s41562-020-00971-z

Canavier, C., Evans, R., Oster, A., Pissadaki, E., Drion, G., Kuznetsov, A. & Gutkin, B. (2016). Implications of cellular models of dopamine neurons for disease. Journal of neurophysiology, 116(6), 2815-2830. doi:10.1152/jn.00530.2016