Publications

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

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. & 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). 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

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

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).

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

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

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

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

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

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

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

de Vignemont, F. & Sackur, J. (2018). La conscience. In Collins, Thérèse, Tallon-Baudry, Catherine, Andler, Daniel (Eds.), La cognitionGallimard

de Vignemont, F. (2018). Schéma corporel et image corporelle. In De Boeck/Solal (Eds.), Manuel de psychomotricité

de Vignemont, F. (2018). Was Descartes right after all? An affective background for bodily awareness. . In Tsakiris, Manos de Preester, Helena (Eds.), The Interoceptive Basis of the Mind: from homeostasis to awareness Oxford: Oxford University Press

de Vignemont, F. (2018). Varieties of bodily feelings. In Kriegel, Uriah (Eds.), The Oxford handbook of consciousness Oxford: Oxford University Press

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

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

Erdmann, A. , Joseph Wrisley, D., Allen, B. , Brown, C. , Cohen-Bodenes, S., Elsner, M. , Feng, Y. , D Joseph, B. , Joyeux-Prunel, B. & de Marneffe, M. (2019). Practical, Efficient, and Customizable Active Learning for Named Entity Recognition in the Digital Humanities. In Proceedings of the 2019 Conference of the North, 2223-2234. doi:10.18653/v1/N19-1231

Alsmith, A. & Longo, M. (2019). Using VR technologies to investigate the flexibility of human self-conception. In E. Fischer and M. Curtis (Eds.), Methodological Advances in Experimental Philosophy (pp. 153-174). London: Bloomsbury

van der Veer, A. , Alsmith, A., Longo, M. , Wong, H. , Diers, D. , Bues, M. , Giron, A. & Mohler, B. (2019). The influence of the viewpoint in a self-avatar on body part and self-localization. In ACM Symposium on Applied Perception 2019, 1-11. doi:10.1145/3343036.3343124

de Vignemont, F. (2019). Against phenomenal parsimony: a plea for bodily feelings. In Goldman, Alvin McLaughlin, McLaughlin (Eds.), Metaphysics and cognitive science Oxford: Oxford University Press

de Vignemont, F. (2019). The phenomenology of bodily ownership. In Guillot, Marie Garcia-Carpintero, Manuel (Eds.), The sense of mineness Oxford: Oxford University Press

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

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%)