Publications

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

Wong, D., Di Liberto, G. & de Cheveigné, A. (2019). Accurate Modeling of Brain Responses to Speech. bioRxiv. doi:10.1101/509307

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

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

Graves, J., Egré, P., Pressnitzer, D. & de Gardelle, V. (2021). An implicit representation of stimulus ambiguity in pupil size. , Vol. 18: In Proceedings of the National Academy of Sciences, e2107997118. doi:10.1073/pnas.2107997118

Pressnitzer, D., Agus, T., Kang, H. , Graves, J. & Andrillon, T. (2021). Apprentissage de motifs sonores. In S. Samson, B. Tillmann, C. Jourdan, V. Brun (Eds.), Audition et Cognition Montpellier: Sauramps Medical

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

Gutkin, B. & Stiefel, K. (2014). Cholinergic Neuromodulation of Phase Response Curves. In Schultheiss et al (eds) (Eds.), Phase Response Cruves in NeuroscienceSpringer

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

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

Ponsot, E., Déjardin, H. & Roncière, E. (2016). Controlling Programme Loudness in Individualized Binaural Rendering of Multi-Channel Audio Contents. , Vol. 140: In Audio Engineering Society .

Romagnoni, A. , Colonnese, M. , Touboul, J. & Gutkin, B. (2018). Development of inhibitory synaptic delay drives maturation of thalamocortical network dynamics. bioRxiv, 296673. doi:10.1101/296673

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

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

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.)

Parikh, R. , Kavalerov, I. , Espy-Wilson, C. & Shamma, S. (2022). Harmonicity Plays a Critical Role in DNN Based Versus in Biologically-Inspired Monaural Speech Segregation Systems. In ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 536-540. doi:10.1109/ICASSP43922.2022.9747314

Berthommier, F. & Lorenzi, C. (2021). Implications of Physiological Mechanisms of Amplitude Modulation Processing for Modeling Complex Sounds Analysis and Separation. (pp. 12). doi:10.1201/9781003064183

Ponsot, E. & Neri, P. (2020). Inter-individual differences in spectrotemporal modulation processing despite similar audiograms : could they be used to assess supra-threshold hearing distortions? In e-Forum Acusticum 2020. doi:10.48465/fa.2020.0808

Mamassian, P. & Vemuri, B. (1993). ISOPHOTES ON A SMOOTH SURFACE RELATED TO SCENE GEOMETRY. , Vol. 2031: In Geometric Methods in Computer Vision II, 124-133. doi:10.1117/12.146619

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

Alemi, A., Machens, C., Denève, S. & Slotine, J. (2018). Learning nonlinear dynamics in efficient, balanced spiking networks using local plasticity rules. In Thirty-Second AAAI Conference on Artificial Intelligence, New Orleans, Louisiana, USA, AAAI Press.

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

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

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

Aucouturier, J., Liuni, M. & Ponsot, E. (2017). Not so scary anymore : Screaming voices embedded in harmonic contexts are more positive and less arousing. In ESCOM.

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

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

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

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