Publications

Zhang, D., Gao, M., Xu, D., Shi, W., Gutkin, B., Steffensen, S., Lukas, R. & Wu, J. (2012). Impact of prefrontal cortex in nicotine-induced excitation of ventral tegmental area dopamine neurons in anesthetized rats. Journal of Neuroscience, 32(36), 12366-12375. doi:10.1523/JNEUROSCI.5411-11.2012

Zeldenrust, F., De Knecht, S., Wadman, W., Denève, S. & Gutkin, B. (2017). Estimating the Information Extracted by a Single Spiking Neuron from a Continuous Input Time Series. Frontiers in computational neuroscience, 11, 49. doi:10.3389/fncom.2017.00049

Zeldenrust, F., Gutkin, B. & Denève, S. (2021). Efficient and robust coding in heterogeneous recurrent networks. Plos Computational Biology, 17(4), e1008673. doi:10.1371/journal.pcbi.1008673

Zahle , J., Kaldis , B., Bouvier, A., Roth, P., Montuschi , E., Bohman, J., Turner, S., Wylie, A. & Zamora-Bonilla, J. (2014). Special Issue: Selected Papers From the ENPOSS Meeting, Venice 3-4 September 2013. Philosophy of the Social Sciences, 44(1 )

Zahle , J., Bouvier, A., Kaldis , B., Uebel, T. & Zamora-Bonilla, J. (2013). Special Issue: Papers From the Inaugural Meeting of ENPOSS (European Network for the Philosophy of the Social Sciences), University of Copenhagen, September 21-23, 2012. Philosophy of the Social Sciences, 43(3 )

Wu, J., Gao, M., Shen, J., Shi, W., Oster, A. & Gutkin, B. (2013). Cortical control of VTA function and influence on nicotine reward. Biochemical Pharmacology, 86(8), 1173-1180. doi:10.1016/j.bcp.2013.07.013

Udden, J. , Martins, M. , Zuidema, W. & Tecumseh Fitch, W. (2019). Hierarchical Structure in Sequence Processing: How to Measure It and Determine Its Neural Implementation. Topics in Cognitive Science . doi:10.1111/tops.12442

Tran-Van-Minh, A., Caze, R., Abrahamsson, T., Cathala, L., Gutkin, B. & Digregorio, D. (2015). Contribution of sublinear and supralinear dendritic integration to neuronal computations. Frontiers in cellular neuroscience, 9, 67. doi:10.3389/fncel.2015.00067

Tolu, S., Eddine, R., Marti, F., David, V., Graupner, M., Pons, S., Baudonnat, M., Husson, M., Besson, M., Reperant, C., Zemdegs, J., Pagès, C., Hay, Y., Lambolez, B., Caboche, J., Gutkin, B., Gardier, A., Changeux, J., Faure, P. & Maskos, U. (2013). Co-activation of VTA da and GABA neurons mediates nicotine reinforcement. Molecular Psychiatry, 18(3), 382-393. doi:10.1038/mp.2012.83

Ting, C. , Palminteri, S., Engelmann, J. & Lebreton, M. (2020). Robust valence-induced biases on motor response and confidence in human reinforcement learning. Cognitive, Affective, & Behavioral Neuroscience, . doi:10.3758/s13415-020-00826-0

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

Skvortsova , V., Palminteri, S., Buot, A., Karachi, C., Welter, M., Grabli, D. & Pessiglione, M. (2020). A Causal Role for the Pedunculopontine Nucleus in Human Instrumental Learning. Current Biology, 31(5). doi:10.1016/j.cub.2020.11.042

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

Sidarus, N., Palminteri, S. & Chambon, V. (2019). Cost-benefit trade-offs in decision-making and learning. PLOS Computational Biology, 15(9), e1007326. doi:10.1371/journal.pcbi.1007326

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

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

Safra, L., Palminteri, S. & Chevallier, C. (2019). Social information impairs reward learning in depressive subjects: behavioral and computational characterization. Plos Computational Biology, 15(7), e1007224. doi:10.1101/378281

Recanatesi, S., Farrell, M., Lajoie, G., Denève, S., Rigotti, M. & Shea-Brown, E. (2021). Predictive learning as a network mechanism for extracting low-dimensional latent space representations. Nature Communications, 12(1417). doi:10.1038/s41467-021-21696-1

Proust, J. (2019). From Comparative Studies to Interdisciplinary Research on Metacognition. Animal Behavior and Cognition, 6(4), 309-328. doi:10.26451/abc.06.04.10.2019

Proust, J. & Fortier, M. (2018). Metacognitive Diversity - An Interdisciplinary approaches. Oxford: Oxford University Press

Proust, J. (2016). The Evolution of Primate Communication and Metacommunication. Mind and Language, 31 (2), 177–203

Proust, J. (2015). Time and Action: Impulsivity, Habit, Strategy. Review of Philosophy and Psychology, 6(4 ), 717–743. doi:10.1007/s13164-014-0224-1

Proust, J. (2014). Epistemic Action, Extended Knowledge, and Metacognition . Philosophical Issues, 24(1), 364–392

Proust, J. (2014). Précis of The Philosophy of Metacognition. Philosophy and Phenomenological Research, 89(3), 703–709. doi:10.1111/phpr.12152

Proust, J. (2013). The Philosophy of Metacognition: Mental Agency and Self-Awareness.

Proust, J. (2010). Metacognition. Philosophy Compass, 5 (11), 989–998

Proust, J. (2009). On Indicative Conditionals and Rationality in the Wason Task. PSYCHE: An Interdisciplinary Journal of Research On Consciousness, 15(1), 132-136

Proust, J. (2008). Précis de La Nature de la Volonté Et Disputatio . Philosophiques, 0–00

Proust, J. (2008). XIII-Epistemic Agency and Metacognition: An Externalist View. Proceedings of the Aristotelian Society , 108(1pt3), 241–268

Proust, J. (2006). Why Evolution has to Matter to Cognitive Psychology and to Philosophy of Mind . Biological Theory, 1(4), 349-351