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

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

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

Varzi, A. & Casati, R. (2021). Ballot Ontology. In Sara Bernstein & Tyron Goldschmidt (Eds.), Non-Being: New Essay on the Metaphysics of Non-Existence (pp. 139–164). Oxford: Oxford University Press.

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

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

Koechlin, E. (2020). Executive Control and Decision-Making: a neural theory of prefrontal function. The Cognitive Neurosciences VI (pp. 451).

Varzi, A. & Casati, R. (2020). Ballot Ontology. In Sara Bernstein & Tyron Goldschmidt (Eds.), Non-Being: New Essay on the Metaphysics of Non-ExistenceOxford University Press

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

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

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

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

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).

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

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

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.)

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

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

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

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.

Vacher, J. , Davila, A., Kohn, A. & Coen-Cagli, R. (2020). Texture Interpolation for Probing Visual Perception. Advances in Neural Information Processing Systems (Spotlight – top 5%)

Mamassian, P. & Coen-Cagli, R. (2018). An Ideal Observer Model to Probe Human Visual Segmentation of Natural Images. arXiv

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

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