Publications

Hertz, U., Palminteri, S., Brunetti, S., Olesen, C., Frith, C. & Bahrami, B. (2017). Neural computations underpinning the strategic management of influence in advice giving. Nature communications, 8(1), 2191. doi:10.1038/s41467-017-02314-5

Palminteri, S., Lefebvre, G., Kilford, E. & Blakemore, S. (2017). Confirmation bias in human reinforcement learning: Evidence from counterfactual feedback processing. PLoS computational biology, 13(8), e1005684. doi:10.1371/journal.pcbi.1005684

Salvador, A., Worbe, Y., Delorme, C., Coricelli, G., Gaillard, R., Robbins, T., Hartmann, A. & Palminteri, S. (2017). Specific effect of a dopamine partial agonist on counterfactual learning: evidence from Gilles de la Tourette syndrome. Scientific reports, 7(1), 6292. doi:10.1038/s41598-017-06547-8

Gutierrez, G. & Denève, S. (2018). Population adaptation in efficient balanced networks. eLife, 8, e46926. doi:10.7554/eLife.46926

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

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.

Palminteri, S. & Chevallier, C. (2018). Can We Infer Inter-Individual Differences in Risk-Taking From Behavioral Tasks? Frontiers in psychology, 9, 2307. doi:10.3389/fpsyg.2018.02307

Lefebvre, G., Nioche, A., Bourgeois-Gironde, S. & Palminteri, S. (2018). Contrasting temporal difference and opportunity cost reinforcement learning in an empirical money-emergence paradigm. PNAS, 115(49), E11446-E11454. doi:10.1073/pnas.1813197115

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

Volk, D., Dubinin, I., Gutkin, B., Myasnikova, A. & Nikulin, V. (2018). Cross-Frequency Synchrony Analysis. Frontiers in Neuroinformatics , 12, 72. doi:10.3389/fninf.2018.00072

Novikov, N. & Gutkin, B. (2018). and Gamma Oscillations in Working Memory Functions. Psychology. Journal of Higher School of Economics, 15(1), 174-182

Buchin, A., Kerr, C., Huberfeld, G., Miles, R. & Gutkin, B. (2018). Adaptation and Inhibition Control Pathological Synchronization in a Model of Focal Epileptic Seizure. eNeuro, 5(5), 0019-18. doi:10.1523/ENEURO.0019-18.2018

Di Volo, M., Morozova, E., Lapish, C., Kuznetsov, A. & Gutkin, B. (2018). Dynamical ventral tegmental area circuit mechanisms of alcohol‐dependent dopamine release. European Journal of Neuroscience, Special issue article. doi:10.1111/ejn.14147

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

Zakharov, D., Krupa, M., Gutkin, B. & Kuznetsov, A. (2018). High-frequency forced oscillations in neuronlike elements. Physical Review E , 97(6). doi:10.1103/PhysRevE.97.062211

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

Lussange, J., Belianin, A., Bourgeois-Gironde, S. & Gutkin, B. (2018). A bright future for financial agent-based models. arxiv, nc

Stefanini, F. , A. Kheirbek, M. , Kushnir, L., C. Jimenez, J. , H. Jennings, J. , D. Stuber, G. , Hen, R. & Fusi, S. (2018). A distributed neural code in the dentate gyrus and in CA1. . doi:10.1101/292953

Kushnir, L. & Fusi, S. (2018). Neural Classifiers with Limited Connectivity and Recurrent Readouts. Journal of Neuroscience, 38 (46), 9900-9924. doi:10.1523/JNEUROSCI.3506-17.2018

Tallon-Baudry, C., Florence, C., Hyeong-Dong, P. & Babo-Rebelo, M. (2018). The neural monitoring of visceral inputs, rather than attention, accounts for first-person perspective in conscious vision. Cortex, . doi:10.1016/j.cortex.2017.05.019

Correa, C. , Noorman, S. , Jiang, J. , Palminteri, S., Cohen, M. , Lebreton, M. & van Gaal, S. (2018). How the level of reward awareness changes the computational and electrophysiological signatures of reinforcement learning. Journal of Neuroscience , 0457-18. doi:10.1523/JNEUROSCI.0457-18.2018

Bavard, S., Lebreton, M., Khamassi, M., Coricelli, G. & Palminteri, S. (2018). Reference-point centering and range-adaptation enhance human reinforcement learning at the cost of irrational preferences. Nature Communications, 9(4503)

Rebollo, I., Devauchelle, A., D., Béranger, B. & Tallon-Baudry, C. (2018). Stomach-brain synchrony reveals a novel, delayed-connectivity resting-state network in humans. eLife, 7, e33321. doi:10.7554/eLife.33321

Giavazzi, M., Daland, R., Palminteri, S., Peperkamp, S., Brugières, P., Jacquemot, C., Schramm, C., Cleret de Langavant, L. & Bachoud-Levi, A. (2018 ). The role of the striatum in linguistic selection: Evidence from Huntington’s disease and computational modeling. Cortex, 109, 189-204. doi:10.1016/j.cortex.2018.08.031

Simeone, O. , Rajendran, B. , Gruning, A. , Eleftheriou, E. , Davies, M. , Denève, S. & Huang, G. (2019). Learning Algorithms and Signal Processing for Brain-Inspired Computing. IEEE Signal Processing Magazine, 36(6), 12-15. doi:10.1109/MSP.2019.2935557

Safra, L., Chevallier, C. & Palminteri, S. (2019). Depressive symptoms are associated with blunted reward learning in social contexts. PLOS Computational Biology, 15(7), e1007224. doi:10.1371/journal.pcbi.1007224