Publications

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

Rooy, M., Koukouli, F., Maskos, U. & Gutkin, B. (2018). Nicotinic modulation of hierarchal inhibitory control over prefrontal cortex resting state dynamics: modeling of genetic modification and schizophreniarelated pathology. bioRxiv, 301051. doi:10.1101/301051

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

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

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

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

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

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.)

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

Remme, M., Lengyel, M. & Gutkin, B. (2014). Phase Response Methods in Dendritic Dynamics. In Schultheiss et al (eds) (Eds.), Phase Response Cruves in NeuroscienceSpringer

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

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

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

Nicolas, D. (2018). The logic of mass expressions. In E. N. Zalta (Eds.), Stanford Encyclopedia of Philosophy Stanford: The Metaphysics Research Lab Center for the Study of Language and Information Stanford University

Mari, A. (2018). The French Future : evidentiality and information increase. Evidence for Evidentiality (pp. 199-226). Dordrecht: Benjamins

Mari, A. (2018). The French Future : evidentiality and information increase. Evidence for Evidentiality (pp. 199-226). Dordrecht: Benjamins

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

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

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

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

Zakharov, D., Dogonasheva, O. & Gutkin, B. (2020). Role of Pyramidal Cell M-current in Weak Pyramidal/Interneuronal Gamma Cluster Formation. In 2020 4th Scientific School on Dynamics of Complex Networks and their Application in Intellectual Robotics (DCNAIR), Innopolis, Russia, IEEE. doi:10.1109/DCNAIR50402.2020.9216942

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.

Nicolas, D. (2002). La distinction entre noms massifs et noms comptables. Leuven: Editions Peeters

Nicolas, D. (2002). La catégorisation des noms communs : massifs et comptables. Catégorisation et Langage (pp. 29-51).

Nicolas, D. (2002). Do mass nouns constitute a semantically uniform class? Kansas Working Papers in Linguistics, 26, 113-121. doi:10.17161/KWPL.1808.591

Nicolas, D. & Lefeuvre, F. (2003). La phrase averbale existentielle et la distinction aspectuelle télique / atélique. Revue de Sémantique et Pragmatique, 14, 157-168

Justo, D., Dutant, J., Hardy-Vallée, B., Nicolas, D. & Sylvand, B. (2003). Delegation, subdivision, and modularity: How rich is Conceptual Structure? Behavioral and Brain Sciences, 26(6), 683-684. doi:10.1017/S0140525X03390156

Nicolas, D. (2004). The semantics of nouns derived from gradable adjectives. In Proceedings of Sinn und Bedeutung 8, 197-207.

Nicolas, D. (2004). Is there anything characteristic about the meaning of a count noun? Revue de la Lexicologie, 18-19, 125-138

Stojanovic, I., De Brabanter, P., Nicolas, D. & Villanueva, N. (2005). Deferential Utterances. In Casati, R. and Origgi, G. (Eds.), In Referring to Objects, Interdisciplines.org., 4-19.