Publications

Casati, R. (2021). Im Moment des Schattens. Liddy Scheffknecht – Points in Time,De Gruyter,. doi:10.1515/9783110769562-005

Casati, R. (2021). Shadows in the Moment. Liddy Scheffknecht – Points in Time (pp. 161-164).De Gruyter. doi:10.1515/9783110769562-010

Arcangeli, M. & Dokic, J. (2020). A plea for the Sublime in science. In S. French & M. Ivanova (Eds.), The Aesthetics of Science: Beauty, Imagination and Understanding (Routledge ed., pp. 104-124). doi:10.4324/9780429030284-6

Casati, R. (2020). Technical report on Chapter 0 (Numero Zero) of Cognition in the Wind – Taqwim navigation, May 10-16, 2018.

Casati, R. & Tonello, F. (2018). Voto elettronico e partecipazione democratica. Web e società democratica (pp. 3-15). Turin: Accademia University Press

Casati, R. (2018). Shadows, objects and the lexicon: On some lexicalized and non-lexicalized concepts of shadow and light. In C. Mac Cumhaill, Thomas Crowther (Eds.), Perceptual Ephemera Oxford: OUP. doi:10.1080/13875868.2017.1377204

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

de Vignemont, F. (2018). The first-person in pain. In Bain, D., Brady, M., Corns, J. (Eds.), Philosophy of Pain: Unpleasantness, Emotion, and DevianceRoutledge

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

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

Fernandez-Velasco, P. & Casati, R. (2020). Disorientation and GIS-Informed Wilderness Search and Rescue. The Philosophy of GIS Switzerland: Springer Nature. doi:10.1007/978-3-030-16829-2_11

Fernandez-Velasco, P. & Casati, R. (2021). Making and Breaking Our Shared World: A Phenomenological Analysis of Disorientation as a Way ofUnderstanding Collective Emotions in Distributed Cognition. In Falcato A., Graça da Silva S. (Eds.), The Politics of Emotional Shockwaves (pp. 203-219).Palgrave Macmillan, Cham. doi:10.1007/978-3-030-56021-8_10

Fortier, M. & Kim, S. (2017). From the impossible to the improbable: A probabilistic account of magical beliefs and practices across development and cultures. In C. Zedelius, B. Müller & J. Schooler (Eds.), The science of lay theories: How beliefs shape our cognition, behavior, and health (pp. 265-315). New York: Springer

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

Le Coënt, A., Fribourg, L., Vacher, J. & Wisniewski, R. (2020). Probabilistic reachability and control synthesis for stochastic switched systems using the tamed Euler method. Nonlinear Analysis: Hybrid Systems, 36, 100860Elsevier. doi:10.1016/j.nahs.2020.100860

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

Mamassian, P., Landy, M., Maloney, L., Rao, R., Olshausen, B. & Lewicki, M. (2002). Bayesian modelling of visual perception. In R. Rao, B. Olshausen & M. Lewicki (Eds.), Probabilistic Models of the Brain: Perception and Neural Function (pp. 13-36). Cambridge, MA: MIT Press

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

Neri, P. (2018). Classification images as descriptive statistics. "Journal of Mathematical Psychology", "82"("1), "26–37"

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

Pasquinelli, E., Farina, M. , Bedel, A. & Casati, R. (2020). Defining and educating critical thinking Report produced within the framework of Work Package 1 EEC Project -Critical Education (ANR-18-CE28-0018)

Pasquinelli, E., Farina, M. , Bedel, A. & Casati, R. (2020). Définir et éduquer l'esprit critique.

Recanatesi, S., Farrell, M., Lajoie, G., Denève, S., Rigotti, M. & Shea-Brown, E. (2018). Signatures and mechanisms of low-dimensional neural predictive manifolds. bioRxiv. doi:10.1101/471987

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

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