Publications

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

Ostojic, S., Szapiro, G., Schwartz, E., Barbour, B., Brunel, N. & Hakim, V. (2015). Neuronal morphology generates high-frequency firing resonance. The Journal of Neuroscience, 35(18), 7056-68. doi:10.1523/JNEUROSCI.3924-14.2015

Gutkin, B. & Ermentrout, G. (2006). Neuroscience: Spikes too kinky in the cortex? Nature, 440(7087), 999-1000. doi:10.1038/440999a

Koukouli, F., Rooy, M., Tziotis, D., Sailor, K., O'Neill, H., Levenga, J., Witte, M., Nilges, M., Changeux, J., Hoeffer, C., Stitzel, J., Gutkin, B., Digregorio, D. & Maskos, U. (2017). Nicotine reverses hypofrontality in animal models of addiction and schizophrenia. Nature medicine, 23(3), 347-354. doi:10.1038/nm.4274

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

Angeletos Chrysaitis, N. , Jardri, R., Denève, S. & Seriès, P. (2021). No increased circular inference in adults with high levels of autistic traits or autism. Plos Computational Biology, 17(9), e1009006. doi:10.1371/journal.pcbi.1009006

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

Palminteri, S. & Pessiglione, M. (2016). Opponent brain systems for reward and punishment learning: Causal evidence from drug and lesion studies in humans. Decision Neuroscience: An Integrative Perspective, 291-303. doi:10.1016/B978-0-12-805308-9.00023-3

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

Beiran, M., Meirhaeghe, N., Sohn, H., Jazayeri, M. & Ostojic, S. (2023). Parametric control of flexible timing through low-dimensional neural manifolds. Neuron, 111(5), 739-753.e8. doi:10.1016/j.neuron.2022.12.016

Winkler, M. , Dumont, G., Schöll, E. & Gutkin, B. (2021). Phase response approaches to neural activity models with distributed delay. Bio Cybern. doi:10.1007/s00422-021-00910-9

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

Gutkin, B. & Stiefel, K. (2007). Phase-resetting curves and neuromodulation of action potential dynamics in the cortex. (Vol. 40, pp. 14-15).

Joao, B., Lozano-Soldevilla, D. & Compte, A. (2021). Pinging the brain with visual impulses reveals electrically active, not activity-silent, working memories. PLOS Biology, 20(3), e3001603. doi:10.1371/journal.pbio.3001436

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. (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

Valente, A., Ostojic, S. & Pillow, J. (2022). Probing the Relationship Between Latent Linear Dynamical Systems and Low-Rank Recurrent Neural Network Models. Neural Computation, 1-22. doi:10.1162/neco_a_01522

Gutkin, B., Jost, J. & Tuckwell, H. (2008). Random perturbations of spiking activity in a pair of coupled neurons. Theory in Biosciences, 127(2), 135-139. doi:10.1007/s12064-008-0039-7

C M Gueguen, M., Anlló, H., Bonagura, D., Kong, J., Hafezi, S., Palminteri, S. & B Konova, A. (2023). Recent Opioid Use Impedes Range Adaptation in Reinforcement Learning in Human Addiction. Biological psychiatry, . doi:10.1016/j.biopsych.2023.12.005

Maex, R., Budygin, E., Grinevich, V., Bencherif, M. & Gutkin, B. (2014). Receptor activation and desensitization as mechanisms for a7 regulation of dopamine response to nicotine. Chemical Neuroscience , 15(10), 1032-40. doi:10.1021/cn500126t

Completo Guerreiro, I., Gu, Z., Yakel, J. & Gutkin, B. (2022). Recurring Cholinergic Inputs Induce Local Hippocampal Plasticity through Feedforward Disinhibition. eNeuro. doi:10.1523/ENEURO.0389-21.2022

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

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)

Shao, Y. & Ostojic, S. (2023). Relating local connectivity and global dynamics in recurrent excitatory-inhibitory networks. PLoS computational biology, 19(1), e1010855. doi:10.1371/journal.pcbi.1010855

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

Kim , K., Ladenbauer, J., Babo-Rebelo, M., Buot, A., Kehongre , K., Adam, C., Hasboun, D., Lambrecq , V., Navarro , V., Ostojic, S. & Tallon-Baudry, C. (2019 ). Resting-state neural firing is linked to cardiac cycle duration in the human cingulate and parahippocampal cortices. Journal of Neuroscience , 39(19), 3676-3686. doi:10.1523/JNEUROSCI.2291-18.2019

Dogonasheva, O., Kasatkin, D., Gutkin, B. & Zakharov, D. (2021). Robust universal approach to identify travelling chimeras and synchronized clusters in spiking networks. Chaos, Solitons & Fractals, 153(1), 111541. doi:10.1016/j.chaos.2021.111541

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

Novikov, N. & Gutkin, B. (2016). Robustness of persistent spiking to partial synchronization in a minimal model of synaptically driven self-sustained activity. Physical review. E, 94(5-1), 052313. doi:10.1103/PhysRevE.94.052313