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

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

Proust, J. (2021). Penser vite ou penser bien ? Odile Jacob

Beran, M., Brandl, J., Perner, J. & Proust, J. (2012). The Foundations of Metacognition.

Bouvier, A. (2011). Individualism, Collective Agency and The “Micro–Macro Relation”. In Ian Jarvie and Jesus Zamora (Eds.), Handbook of Philosophy of Social Science (pp. 199).Sage Publications

Bouvier, A. (2009). Joint Commitment, Coercion and Freedom in Science : Conceptual Analysis and Case Studies. , 143–61

Bouvier, A. (2018). Intentional, unintentional and sub-intentional aspects of social mechanisms and rationality. The example of commitments in political life. In Gérald Bronner, Francesco Di Iorio (Eds.), The Mystery of Rationality: Mind, Beliefs and the Social Sciences (pp. 17-35). Cham (CH): Springer Nature

Bouvier, A. (2017). Analyse critique de Ch. Plantin, 2016, Dictionnaire de l’argumentation. Une introduction aux études d’argumentation. L’Année sociologique (Vol. 67, pp. 1-5). Lyon: ENS Editions

Bouvier, A. (2017). Analyse critique de F.H. Van Eemeren, B. Garssen, E.C.W.Krabbe, A.F. Snoeck Henkemans, B. Verheij, J.H.M. Wagemans (eds), 2014, Handbook of Argumentation Theory. L’Année sociologique (Vol. 67, pp. 7-11). Dordrecht: Springer Verlag

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

Chiril, P. , Moriceau, V. , Benamara, F. , Mari, A., Origgi, G. & Coulomb-Gully, M. (2020). An Annotated Corpus for Sexism Detection in French Tweets. In LREC 2020, Marseille, EuropeanLanguageResourcesAssociation (ELRA), 1397–1403.

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. & Proust, J. (2002). Simulation and Knowledge of Action.

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

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

Gutkin, B. & Stiefel, K. (2014). Cholinergic Neuromodulation of Phase Response Curves. In Schultheiss et al (eds) (Eds.), Phase Response Cruves in NeuroscienceSpringer

Kim, S., Shahaeian, A. & Proust, J. (2018). Developmental diversity in mindreading and metacognition. In Proust, J. & Fortier, M (Eds.), Metacognitive Diversity (pp. 97-133).OUP

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

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

Origgi, G. (2019). Reputation: What it is and why it Matters. Princeton University Press

Origgi, G. (2019). Reputation in Moral Philosophy and Epistemology. In F. Giardini, R. Wittek (Eds.), he Oxford Handbook of Gossip and Reputation (pp. 69-81).Oxford University Press

Origgi, G. (2020). Trust and Reputation. In Judith Simon (Eds.), The Routledge Handbook of Trust and PhilosophyRoutledge