Publications

Schlenker, P., Chemla, E. & Zuberbühler, K. (2016). What Do Monkey Calls Mean? Trends in cognitive sciences, 20(12), 894-904. doi:10.1016/j.tics.2016.10.004

Gutkin, B., Jost, J. & Tuckwell, H. (2008). Transient termination of spiking by noise in coupled neurons. EPL, 81(2). doi:10.1209/0295-5075/81/20005

Remme, M., Lengyel, M. & Gutkin, B. (2015). Trade-off between dendritic democracy and independence in neurons with intrinsic subthreshold membrane potential oscillatio. In Remme et al (eds) (Eds.), Dendritic ComputationSpringer

Schlenker, P., Chemla, E., Cäsar, C., Zuberbühler, K. & Ryder, R. (2017). Titi semantics: Context and meaning in Titi monkey call sequences. Natural Language and Linguistic Theory, 35(1), 271-298. doi:10.1007/s11049-016-9337-9

Gutkin, B. (2015). Theta-neurons. In Springer Verlag (Eds.), Encyclopedia of Comptutational Neuroscience (pp. 1034-1042).

Dezecache, G., Grèzes, J. & Dahl, C. (2017). The nature and distribution of affiliative behaviour during exposure to mild threat. Royal Society open science, 4(8), 170265. doi:10.1098/rsos.170265

Schlenker, P., Coye, C. , Leroux, M. & Chemla, E. (2023). The ABC-D of animal linguistics: are syntax and compositionality for real? Biological reviews of the Cambridge Philosophical Society, 98(4), 1142-1159. doi:10.1111/brv.12944

Maex, R. & Gutkin, B. (2017). Temporal integration and 1/f power scaling in a circuit model of cerebellar interneurons. Journal of neurophysiology, 118(1), 471-485. doi:10.1152/jn.00789.2016

Zakharov, D., Lapish, C., Gutkin, B. & Kuznetsov, A. (2016). Synergy of AMPA and NMDA Receptor Currents in Dopaminergic Neurons: A Modeling Study. Frontiers in computational neuroscience, 10, 48. doi:10.3389/fncom.2016.00048

Jeong, H. & Gutkin, B. (2007). Synchrony of neuronal oscillations controlled by GABAergic reversal potentials. Neural Computation, 19(3), 706-729. doi:10.1162/neco.2007.19.3.706

Lussange, J., Vrizzi, S., Bourgeois-Gironde, S., Palminteri, S. & Gutkin, B. (2022). Stock Price Formation: Precepts from a Multi-Agent Reinforcement Learning Model. Comput Econ. doi:10.1007/s10614-022-10249-3

Zuberbühler, K., Chemla, E. & Schlenker, P. (2021). Stereotyped vocalizations. Encyclopedia of Evolutionary Psychological Science (pp. 7970-7974).Springer. doi:10.1007/978-3-319-16999-6_3330-1

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

Muller, L., Brette, R. & Gutkin, B. (2011). Spike-timing dependent plasticity and feed-forward input oscillations produce precise and invariant spike phase-locking. Frontiers in Computational Neuroscience, 15(5), 45. doi:10.3389/fncom.2011.00045

Hyafil, A., Fontolan, L., Kabdebon, C., Gutkin, B. & Giraud, A. (2015). Speech encoding by coupled cortical theta and gamma oscillations. eLife, 4, 1-45. doi:10.7554/eLife.06213

Dezecache, G., Conty, L. & Grèzes, J. (2013). Social affordances: is the mirror neuron system involved? The Behavioral and brain sciences, 36(4), 417-8. doi:10.1017/S0140525X12001872

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

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

Chalk, M., Masset, P., Denève, S. & Gutkin, B. (2017). Sensory noise predicts divisive reshaping of receptive fields. PLoS computational biology, 13(6), e1005582. doi:10.1371/journal.pcbi.1005582

Schlenker, P., Chemla, E. & Zuberbühler, K. (2017). Semantics and Pragmatics of Monkey Communication. In Mark Aronoff (Eds.), Oxford Research Encyclopedia of LinguisticsNew York: Oxford University Press. doi:10.1093/acrefore/9780199384655.013.220

Soussignan, R., Chadwick, M., Philip, L., Conty, L., Dezecache, G. & Grèzes, J. (2013). Self-relevance appraisal of gaze direction and dynamic facial expressions: Effects on facial electromyographic and autonomic reactions. Emotion, 13(2), 330-337. doi:10.1037/a0029892

Grèzes, J., Philip, L., Chadwick, M., Dezecache, G., Soussignan, R. & Conty, L. (2013). Self-relevance appraisal influences facial reactions to emotional body expressions. PLoS ONE, 8(2). doi:10.1371/journal.pone.0055885

Grèzes, J., Philip, L., Chadwick, M., Dezecache, G., Soussignan, R. & Conty, L. (2013). Self-relevance appraisal influences facial reactions to emotional body expressions. PloS one, 8(2), e55885. doi:10.1371/journal.pone.0055885

Novikov, N. & Gutkin, B. (2020). Role of synaptic nonlinearity in persistent firing rate shifts caused by external periodic forcing. PHYSICAL REVIEW E, 101(5), 052408. doi:10.1103/PhysRevE.101.052408

Novikov, N. & Gutkin, B. (2016). Robustness of persistent spiking to partial synchronization in a minimal model of synaptically driven self-sustained activity. Physical review. E, 94(5-1), 052313. doi:10.1103/PhysRevE.94.052313

Dogonasheva, O., Kasatkin, D., Gutkin, B. & Zakharov, D. (2021). Robust universal approach to identify travelling chimeras and synchronized clusters in spiking networks. Chaos, Solitons & Fractals, 153(1), 111541. doi:10.1016/j.chaos.2021.111541

Steinert-Threlkeld, S., Schlenker, P. & Chemla, E. (2021). Referential and general calls in primate semantics. Linguistics and Philosophy , 44, 1317-1342. doi:10.1007/s10988-021-09322-1

Buchin, A., Chizhov, A., Huberfeld, G., Miles, R. & Gutkin, B. (2016). Reduced Efficacy of the KCC2 Cotransporter Promotes Epileptic Oscillations in a Subiculum Network Model. The Journal of Neuroscience, 36(46), 11619--11633. doi:10.1523/JNEUROSCI.4228-15.2016

Completo Guerreiro, I., Gu, Z., Yakel, J. & Gutkin, B. (2022). Recurring Cholinergic Inputs Induce Local Hippocampal Plasticity through Feedforward Disinhibition. eNeuro. doi:10.1523/ENEURO.0389-21.2022

Maex, R., Budygin, E., Grinevich, V., Bencherif, M. & Gutkin, B. (2014). Receptor activation and desensitization as mechanisms for a7 regulation of dopamine response to nicotine. Chemical Neuroscience , 15(10), 1032-40. doi:10.1021/cn500126t