Publications

Bouvier, A. (2002). An Epistemological Plea for Methodological Individualism and Rational Choice Theory in Cognitive Rhetoric. Philosophy of the Social Sciences, 32(1 ), 51–70

Bouvier, A. (2002). Dans quelle mesure la théorie sociale de James Coleman est-elle trop parcimonieuse?

Bouvier, A. (1995). Les Paralogismes d'Un Point de Vue Sociologique. Hermes, 16 , 45

Bouvier, A. (2018). La Théorie de L’Argumentation Comme Épistémologie Sociale Naturalisée. Philosophia Scientiæ, 22(1), 17–35. doi:10.4000/philosophiascientiae.1461

Bouvier, A. (2018). Selected Papers from the 6th ENPOSS Meeting, Cracow, 20-22 September, 2017.

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

Caze, R., Humphries, M. & Gutkin, B. (2013). Modulation of computational capacity of neurons due to dendritic synaptic interactions. PLoS Comput. Biol., 9(2)

Caze, R., Humphries, M. & Gutkin, B. (2012). Spiking and saturating dendrites differentially expand single neuron computation capacity. , Vol. 13: In Twenty First Annual Computational Neuroscience Meeting: CNS*2012, Decatur, GA, USA.

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

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

Chambon, V., Domenech, P., Jacquet, P., Barbalat, G., Bouton, S., Pacherie, E., Koechlin, E. & Farrer, C. (2017). Neural coding of prior expectations in hierarchical intention inference. Scientific reports, 7(1), 1278. doi:10.1038/s41598-017-01414-y

Chiril, P. , Moriceau, V. , Benamara, F. , Origgi, G., Coulomb-Gully, M. & Mari, A. (2020). He said “who’s gonna take care of your children when you are at ACL?”: Reported Sexist Acts are Not Sexist. In 58th Annual Meeting of the Association for Computational Linguistics 2020, France, 4055-4066. doi:10.18653/v1/2020.acl-main.373

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.

Dipoppa, M. & Gutkin, B. (2013). Flexible frequency control of cortical oscillations enables computations required for working memory. Proceedings of the National Academy of Sciences of the United States of America, 110(31), 12828-12833. doi:10.1073/pnas.1303270110

Dipoppa, M. & Gutkin, B. (2013). Correlations in background activity control persistent state stability and allow execution of working memory tasks. Frontiers in Computational Neuroscience, 7, 139. doi:10.3389/fncom.2013.00139

Dipoppa, M., Krupa, M., Torcini, A. & Gutkin, B. (2012). Marginally Stable States and Quasi-periodic minor attractors in excitable pulse-coupled networks. SIADS , 63(1), 62-97

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

Domenech, P., Rheims, S. & Koechlin, E. (2020 ). Neural Mechanisms resolving Exploitation-Exploration dilemmas in the prefrontal cortex. Science, 369(6507), eabb0184. doi:10.1126/science.abb0184

Domenech, P., Redouté, J., Koechlin, E. & Dreher, J. (2018). The Neuro-Computational Architecture of Value-Based Selection in the Human Brain. Cerebral cortex (New York, N.Y. : 1991), 28(2), 585-601. doi:10.1093/cercor/bhw396

Duverne, S. & Koechlin, E. (2017). Rewards and Cognitive Control in the Human Prefrontal Cortex. Cerebral cortex (New York, N.Y. : 1991), 27(10), 5024-5039. doi:10.1093/cercor/bhx210

Eskenazi, T., Montalan, B., Jacquot, A., Proust, J., Grèzes, J. & Conty, L. (2016). Social influence on metacognitive evaluations: The power of nonverbal cues. Quarterly journal of experimental psychology (2006), 69(11), 2233-47. doi:10.1080/17470218.2015.1115111

Feest, U. , Bouvier, A., Henderson, D. , Kaldis , B., Montuschi , E., Risjord, M. , Roth, P., Zahle , J. & Zamora-Bonilla, J. (2019). Special Issue (Part II) In Joint Session of the European Network for the Philosophy of the Social Sciences (ENPOSS) and the Roundtable on Philosophy of the Social Sciences, Hannover.

Feest, U. , Bouvier, A., Henderson, D. , Kaldis , B., Montuschi , E., Risjord, M. , Roth, P., Zahle , J. & Zamora-Bonilla, J. (2019). Special Issue (Part I) , Vol. 49: In Joint Session of the European Network for the Philosophy of the Social Sciences (ENPOSS) and the Roundtable on Philosophy of the Social Sciences , Hannover.

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

Fontolan, L., Krupa, M., Hyafil, A. & Gutkin, B. (2013). Analytical insights on theta-gamma coupled neural oscillators. Journal of Mathematical Neuroscience, 3(1), 1-20. doi:10.1186/2190-8567-3-16

Graupner, M., Maex, R. & Gutkin, B. (2013). Endogenous Cholinergic Inputs and Local Circuit Mechanisms Govern the Phasic Mesolimbic Dopamine Response to Nicotine. PLoS Computational Biology, 9(8). doi:10.1371/journal.pcbi.1003183

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.)