Publications

Bondanelli, G. & Ostojic, S. (2020). Coding with transient trajectories in recurrent neural networks. PLoS Computational Biology, 16 (2), e1007655. doi:10.1371/journal.pcbi.1007655

Baumard, N., Safra, L., Martins, M. & Chevallier, C. (2024). Cognitive fossils: using cultural artifacts to reconstruct psychological changes throughout history. Trends in cognitive sciences, 28(2), 172-186. doi:10.1016/j.tics.2023.10.001

Chung, V., Grèzes, J. & Pacherie, E. (2023). Collective Emotion: A Framework for Experimental Research. Emotion Review, 16(1), 28-45. doi:10.1177/17540739231214533

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

Findling, C. & Wyart, V. (2021). Computation noise in human learning and decision-making: origin, impact, function. Current Opinion in Behavioral Sciences, 38, 124-132. doi:10.1016/j.cobeha.2021.02.018

Tegnér, J., Compte, A., Auffray, C., An, G., Cedersund, G., Clermont, G., Gutkin, B., Oltvai, Z., Stephan, K., Thomas, R. & Villoslada, P. (2009). Computational disease modeling - Fact or fiction? BMC Systems Biology, 3. doi:10.1186/1752-0509-3-56

Findling, C., Skvortsova , V., Dromnelle, R. , Palminteri, S. & Wyart, V. (2019). Computational noise in reward-guided learning drives behavioral variability in volatile environments. Nature Neuroscience , 22, 2066–2077. doi:10.1101/439885

Ostojic, S. & Fusi, S. (2024). Computational role of structure in neural activity and connectivity. Trends in cognitive sciences, 28(7), 677-690. doi:10.1016/j.tics.2024.03.003

Zamani, A. , Novikov, N. & Gutkin, B. (2020). Concomitance of inverse stochastic resonance and stochastic resonance in a minimal bistable spiking neural circuit. Communications in Nonlinear Science and Numerical Simulation, 82, 105024. doi:10.1016/j.cnsns.2019.105024

Balsdon, T., Wyart, V. & Mamassian, P. (2020). Confidence controls perceptual evidence accumulation. Nature Communications, 11(1), 1753. doi:10.1038/s41467-020-15561-w

Leclercq, S., Szaffarczyk, S., Leptourgos, P., Yger, P., Fakhri, A., Wathelet, M., Bouttier, V., Denève, S. & Jardri, R. (2024). Conspiracy beliefs and perceptual inference in times of political uncertainty. Scientific reports, 14(1), 9001. doi:10.1038/s41598-024-59434-4

Beiran, M. & Ostojic, S. (2019). Contrasting the effects of adaptation and synaptic filtering on the timescales of dynamics in recurrent networks . PLoS Computational Biology, 15(3), e1006893. doi:10.1371/journal.pcbi.1006893

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

Morozova, E., Myroshnychenko, M., Zakharov, D., Di Volo, M., Gutkin, B., Lapish, C. & Kuznetsov, A. (2016). Contribution of synchronized GABAergic neurons to dopaminergic neuron firing and bursting. Journal of neurophysiology, 116(4), 1900-1923. doi:10.1152/jn.00232.2016

Dipoppa, M., Szwed, M. & Gutkin, B. (2016). Controlling Working Memory Operations by Selective Gating: The Roles of Oscillations and Synchrony. Advances in cognitive psychology, 12(4), 209-232. doi:10.5709/acp-0199-x

Martí, D., Brunel, N. & Ostojic, S. (2018). Correlations between synapses in pairs of neurons slow down dynamics in randomly connected neural networks. Physical Review E, 97, 062314. doi:https://doi.org/10.1103/PhysRevE.97.062314

Dipoppa, M. & Gutkin, B. (2013). Correlations in background activity control persistent state stability and allow execution of working memory tasks. Frontiers in Computational Neuroscience, 7, 139. doi:10.3389/fncom.2013.00139

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

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

Van Den Stock, J., Tamietto, M., Sorger, B., Pichon, S., Grèzes, J. & De Gelder, B. (2011). Cortico-subcortical visual, somatosensory, and motor activations for perceiving dynamic whole-body emotional expressions with and without striate cortex (V1). Proceedings of the National Academy of Sciences of the United States of America, 108(39), 16188-93. doi:10.1073/pnas.1107214108

Chevallier, C., Hacquin, A. & Mercier, H. (2021). COVID-19 Vaccine Hesitancy: Shortening the Last Mile. Trends in Cognitive Sciences, 25(5), 331–333. doi:10.1016/j.tics.2021.02.002

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

Oswald, A. & Ostojic, S. (2020). Curating more diverse scientific conferences. Nat Rev Neurosci, 21, 589-590. doi:10.1038/s41583-020-0373-4

Thouzeau, V., Bollée, J. , Cristia, A. & Chevallier, C. (2023). Decades of Trivers-Willard research on humans: What conclusions can be drawn? Evolution and Human Behavior, 44(4). doi:10.1016/j.evolhumbehav.2023.03.005

Remme, M., Lengyel, M. & Gutkin, B. (2010). Democracy-independence trade-off in oscillating dendrites and its implications for grid cells. Neuron, 66(3), 429-437. doi:10.1016/j.neuron.2010.04.027

D Cazé, R., Tran-Van-Minh, A., Gutkin, B. & A Digregorio, D. (2024). Demonstration that sublinear dendrites enable linearly non-separable computations. Scientific reports, 14(1), 18226. doi:10.1038/s41598-024-65866-9

Grèzes, J., Risch, N., Courtet, P. , Olié, E. & Mennella, R. (2023). Depression and approach-avoidance decisions to emotional displays: The role of anhedonia. Behaviour Research and Therapy, 104306. doi:10.1016/j.brat.2023.104306

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

Mus, M., Mercier, H. & Chevallier, C. (2023). Designing an acceptable and fair carbon tax: The role of mental accounting. Plos Climate, 2(10), e0000227. doi:10.1371/journal.pclm.0000227

Pingault, J., Pouga, L., Grèzes, J. & Berthoz, S. (2012). Determination of emotional endophenotypes: a validation of the Affective Neuroscience Personality Scales and further perspectives. Psychological assessment, 24(2), 375-85. doi:10.1037/a0025692