Publications

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

Kriegel, U. (2017). Introduction. In Uriak Kriegel (Eds.), Routledge Handbook of Franz Brentano and the Brentano School (pp. 1-11). London and New York: Routledge

Kriegel, U. (2017). Brentano's Concept of Mind: Underlying Nature, Reference-Fixing, and the Mark of the Mental. In Sandra Lapointe & Christopher Pincock (Eds.), Innovations in the History of Analytical PhilosophyPalgrave-Macmillan

Kriegel, U. (2017). Dignity and the Phenomenology of Recognition-Respect. In J. J. Drummond & S. Rinofner-Kreidl (Eds.), Emotional Experience: Ethical and Social SignificanceRowman & Littlefield

Kriegel, U. (2017). Metaphysics and Conceptual Analysis: Experimental Philosophy's Place Under the Sun. (pp. 7–46).

Kriegel, U. (2017). Brentano's Philosophical Program. (pp. 21–32 ).

Kriegel, U. (2017). Brentano on Judgment. (pp. 103–109).

Kriegel, U. (2017). Brentano's Classification of Mental Phenomena. (pp. 97–102).

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.)

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

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.

Ting, C. , Palminteri, S., Engelmann, J. & Lebreton, M. (2019). Decreased confidence in loss-avoidance contexts is a primary meta-cognitive bias of human reinforcement learning. bioRxiv. doi:10.1101/593368

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

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

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

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

Lebreton, M. & Palminteri, S. (2016). When are inter-individual brain-behavior correlations informative? bioRxiv. doi:10.1101/036772

Tallon-Baudry, C. (2013). Catherine Tallon-Baudry. Current Biology, 23(14), R588-R590. doi:10.1016/j.cub.2013.06.010