Publications

Radushev, D. , Dogonasheva, O., Gutkin, B. & Zakharov, D. (2023). Chimera states in a ring of non-locally connected interneurons. In 7th Scientific School Dynamics of Complex Networks and their Applications (DCNA), Kaliningrad, Russian Federation, 229-232. doi:10.1109/DCNA59899.2023.10290318

Pacherie, E. & Castro, V. (2022). Robots and Resentment: Commitments, recognition and social motivation in HRI. Emotional Machines. Perspectives from Affective Computing and Emotional Human-Machine InteractionSpringer Fachmedien Wiesbaden

Zakharov, D., Dogonasheva, O. & Gutkin, B. (2021). Bistability of globally synchronous and chimera states in a ring of phase oscillators coupled by a cosine kernel. In 2021 5th Scientific School Dynamics of Complex Networks and their Applications (DCNA), 211-214. doi:10.1109/DCNA53427.2021.9586968

Dogonasheva, O., Gutkin, B. & Zakharov, D. (2021). Calculation of travelling chimera speeds for dynamical systems with ring topologies. In 5th Scientific School Dynamics of Complex Networks and their Applications (DCNA), 61-64. doi:10.1109/DCNA53427.2021.9586903

Bourgeois-Gironde, S. (2020). Le sourire de ma boulangère : sur le rôle des expressions faciales dans les transactions monétaires. In Claudia Senik (Eds.), Crise de confiance ? (pp. 213-230). Paris: La Découverte, "Recherche"

Bourgeois-Gironde, S., Mari, A., Nicolas, D. & Blunier, D. (2019). Grammatical mood and ambiguity aversion. In Proceedings of 10th International Conference of Experimental Linguistics, Lisbon, Portugal, 33-36. doi:10.36505/ExLing-2019/10/0008/000370

Bourgeois-Gironde, S. (2019). Comment Managua fut vers 1979 le lieu d’un événement linguistique révolutionnaire. In ESKA (Eds.), Problèmes d'Amérique latine (Vol. 112, pp. 101-114). doi:0.3917/pal.112.0101

Bourgeois-Gironde, S. (2017). How regret moves individual and collective choices towards rationality. Handbook of Behavioural Economics and Smart Decision-Making: Rational …

Butterfill , S. & Pacherie, E. (2020). Towards a blueprint for a social animal. In Fiebich, Anika (Eds.), Minimal Cooperation and Shared Agency (pp. 111-125).Springer . doi:10.1007/978-3-030-29783-1

Castro, V. , Clodic, A., Alami, R. & Pacherie, E. (2019). Commitments in Human-Robot Interaction. In AI-HRI 2019 Proceedings. AAAI Fall Symposium Series.

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

Caze, R., Humphries, M. & Gutkin, B. (2013). Dendrites enhance both single neuron and network computation. In Remme et al (eds) (Eds.), Dendritic ComputationSpringer

Deperrois, N. & Gutkin, B. (2018). Nicotinic and Cholinergic Modulation of Reward Prediction Error Computations in the Ventral Tegmental Area: a Minimal Circuit Model. bioRxiv, 423806. doi:10.1101/423806

Dokic, J. & Pacherie, E. (2006). On the Very Idea of a Frame of Reference . (pp. 259-280).

Dumont, G., Maex, R. & Gutkin, B. (2018). Dopaminergic Neurons in the Ventral Tegmental Area and Their Dysregulation in Nicotine Addiction. In Alan Anticevic and John D. Murray (Eds.), Computational Psychiatry: Mathematical Modeling of Mental Illness (pp. 47-84). doi:10.1016/B978-0-12-809825-7.00003-1

Dumont, G. & Gutkin, B. (2018). Macroscopic phase resetting-curves determine oscillatory coherence and signal transfer in inter-coupled neural circuits. arXiv , 1812.03455

Graupner, M. & Gutkin, B. (2012). Dynamical Approaches to understanding cholinergic control of nicotine action pathways in the dopaminergic reward circuits. Computational Neuroscience of Drug Addiction (Springer ed.).Ahmed and Gutkin (eds.)

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

Kuznetsov, A. & Gutkin, B. (2015). Dopaminergic cell Models. The Encyclopedia of Computational Neuroscience (pp. 2958-2965).

Lazarevich, I. , Gutkin, B. & Prokin, I. (2018). Neural activity classification with machine learning models trained on interspike interval series data. arxiv , 1810.03855

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

Lussange, J., Belianin, A., Bourgeois-Gironde, S. & Gutkin, B. (2017). A bright future for financial agent-based models. arXiv preprint arXiv:1801.08222

Martinez-Saito, M. , Konovalov, R. , Piradov, M. , Shestakova, A. , Gutkin, B. & Klucharev, V. (2018). Action in auctions: neural and computational mechanisms of bidding behavior. BioRxiv, 464925. doi:10.1101/464925

Mylopoulos, M. & Pacherie, E. (2020). Self-Control as Hybrid Skill. In A. Mele (Eds.), Surrounding Self-Control (pp. 81-100). Oxford : Oxford University Press. doi:10.1093/oso/9780197500941.003.0005

Novikov, N. & Gutkin, B. (2018). Role of NMDA conductance in average firing rate shifts caused by external periodic forcing. arXiv , 1812.03609

Pacherie, E. (2002). Intention .

Pacherie, E. (2002). Reply to John Campbell on Joint attention and simulation.

Pacherie, E. (2006). Towards a Dynamic Theory of Intentions . (pp. 145-167).

Pacherie, E. (2008). Perception, Emotions and Delusions: Revisiting the Capgras Delusion . (pp. 07-126).

Pacherie, E. (2005). Perceiving Intentions. (pp. 401-414).