Publications

Cayco Gajic, A. & Zylberberg, A. (2021). Good decisions require more than information. Nature Neuroscience, 2', 903-904. doi:10.1038/s41593-021-00883-9

Canavier, C., Evans, R., Oster, A., Pissadaki, E., Drion, G., Kuznetsov, A. & Gutkin, B. (2016). Implications of cellular models of dopamine neurons for disease. Journal of neurophysiology, 116(6), 2815-2830. doi:10.1152/jn.00530.2016

Calmels, C., Pichon, S. & Grèzes, J. (2014). Can we simulate an action that we temporarily cannot perform? Neurophysiologie Clinique/Clinical Neurophysiology, 44(5), 433-445. doi:10.1016/j.neucli.2014.08.004

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

Buchin, A., Rieubland, S., Häusser, M., Gutkin, B. & Roth, A. (2016). Inverse Stochastic Resonance in Cerebellar Purkinje Cells. PLoS computational biology, 12(8), e1005000. doi:10.1371/journal.pcbi.1005000

Buchin, A., Chizhov, A., Huberfeld, G., Miles, R. & Gutkin, B. (2016). Reduced Efficacy of the KCC2 Cotransporter Promotes Epileptic Oscillations in a Subiculum Network Model. The Journal of Neuroscience, 36(46), 11619--11633. doi:10.1523/JNEUROSCI.4228-15.2016

Brumberg, J. & Gutkin, B. (2007). Cortical pyramidal cells as non-linear oscillators: Experiment and spike-generation theory. Brain Research, 1171(1), 122-137. doi:10.1016/j.brainres.2007.07.028

Brendel, W. , Bourdoukan, R., Vertechi, P. , Machens, C. & Denève, S. (2020). Learning to represent signals spike by spike. PLOS Computational Biology, 16(3), e1007692. doi:10.1371/journal.pcbi.1007692

Bouchacourt, F., Palminteri, S., Koechlin, E. & Ostojic, S. (2020). Temporal Chunking as a Mechanism for Unsupervised Learning of Task-Sets. eLife, 9, e50469. doi:10.7554/eLife.50469

Bobashev, G., Costenbader, E. & Gutkin, B. (2007). Comprehensive mathematical modeling in drug addiction sciences. Drug and Alcohol Dependence, 89(1), 102-106. doi:10.1016/j.drugalcdep.2006.12.029

Beaurenaut, M., Dezecache, G. & Grèzes, J. (2021). Action co-representation under threat: A Social Simon study. Cognition, 215, 104829. doi:10.1016/j.cognition.2021.104829

Beaurenaut, M., Tokarski , E., Dezecache, G. & Grèzes, J. (2020). The ‘Threat of Scream’ paradigm: a tool for studying sustained physiological and subjective anxiety. Scientific Reports, 10(1), 1-11. doi:10.1038/s41598-020-68889-0

Bavard, S., Rustichini, A. & Palminteri, S. (2021). Two sides of the same coin: Beneficial and detrimental consequences of range adaptation in human reinforcement learning. Science Advances, 7(14). doi:10.1126/sciadv.abe0340

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)

Azzalini, D., Buot, A., Palminteri, S. & Tallon-Baudry, C. (2021). Responses to Heartbeats in Ventromedial Prefrontal Cortex Contribute to Subjective Preference-Based Decisions. Journal of Neuroscience, 41(23), 5102-5114. doi:10.1523/JNEUROSCI.1932-20.2021

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.

Baumard, N., Safra, L., Martins, M. & Chevallier, C. (2023). Cognitive fossils: using cultural artifacts to reconstruct psychological changes throughout history. Trends in Cognitive Sciences, . doi:10.1016/j.tics.2023.10.001

Radushev, D. , Dogonasheva, O., Gutkin, B. & Zakharov, D. (2023). Chimera states in a ring of non-locally connected interneurons. In 7th Scientific School Dynamics of Complex Networks and their Applications (DCNA), Kaliningrad, Russian Federation, 229-232. doi:10.1109/DCNA59899.2023.10290318

Gurnani, H. & Cayco Gajic, A. (2023). Signatures of task learning in neural representations. Signatures of task learning in neural representations, Current Opinion in Neurobiology,, 83, 102759. doi:10.1016/j.conb.2023.102759

Derome, M., Kozuharova, P., O Diaconescu, A., Denève, S., Jardri, R. & Allen, P. (2023). Functional connectivity and glutamate levels of the medial prefrontal cortex in schizotypy are related to sensory amplification in a probabilistic reasoning task. NeuroImage, 278, 120280. doi:10.1016/j.neuroimage.2023.120280

Palminteri, S. (2023). Choice-confirmation bias and gradual perseveration in human reinforcement learning. Behavioral neuroscience, 137(1), 78-88. doi:10.1037/bne0000541

Bavard, S. & Palminteri, S. (2023). The functional form of value normalization in human reinforcement learning. eLife, 12, e83891. doi:10.7554/eLife.83891

Vandendriessche, H. & Palminteri, S. (2023). Neurocognitive biases from the lab to real life. Communications biology, 6(1), 158. doi:10.1038/s42003-023-04544-4

Palminteri, S. & Cecchi, R. (2023). Objective models of subjective feelings. Neuroscience and biobehavioral reviews, 151, 105233. doi:10.1016/j.neubiorev.2023.105233

Metzler, H., Vilarem, E., Petschen, A. & Grèzes, J. (2023). Power pose effects on approach and avoidance decisions in response to social threat. PloS one, 18(8), e0286904. doi:10.1371/journal.pone.0286904

Dogonasheva, O., Kasatkin, D., Gutkin, B. & Zakharov, D. (2022). Multistability and evolution of chimera states in a network of type II Morris-Lecar neurons with asymmetrical nonlocal inhibitory connections. Chaos (Woodbury, N.Y.), 32(10), 101101. doi:10.1063/5.0117845

Pérez-Cervera, A. , Gutkin, B., J Thomas, P. & Lindner, B. (2023). A universal description of stochastic oscillators. Proceedings of the National Academy of Sciences of the United States of America, 120(29), e2303222120. doi:10.1073/pnas.2303222120

Gurnani, H. & Cayco Gajic, A. (2023). Signatures of task learning in neural representations. Current opinion in neurobiology, 83, 102759. doi:10.1016/j.conb.2023.102759

Lunven, M., Hernandez Dominguez, K., Youssov, K., Hamet Bagnou, J., Fliss, R. , Vandendriessche, H., Bapst, B. , Morgado, G., Remy, P., Schubert, R. , Reilmann, R., Busse, M., Craufurd, D., Massart, R., Rosser, A. & Bachoud-Levi, A. (2023). A new approach to digitized cognitive monitoring: validity of the SelfCog in Huntington's disease. Brain communications, 5(2), fcad043. doi:10.1093/braincomms/fcad043

Anlló, H., Bavard, S., Benmarrakchi, F., Bonagura, D., Cerrotti, F., Cicue, M., Gueguen, M., Guzmán, E., Kadieva, D., Kobayashi, M., Lukumon, G., Sartorio, M., Yang, J., Zinchenko, O., Bahrami, B., Silva, J., Hertz, U., Konova, A., Li, J., O'Madagain, C., Navajas, J., Reyes, G., Sarabi-Jamab, A., Shestakova, A. , Sukumaran, B., Watanabe, K. & Palminteri, S. (2023). Outcome context-dependence is not WEIRD: Comparing reinforcement- and description-based economic preferences worldwide. Research square, . doi:10.21203/rs.3.rs-2621222/v1