Publications

Balsdon, T. & Clifford, C. (2017). Detecting and identifying offset gaze. Attention, perception & psychophysics, 79(7), 1993-2006. doi:10.3758/s13414-017-1347-0

Balsdon, T. & Clifford, C. (2017). A bias-minimising measure of the influence of head orientation on perceived gaze direction. Scientific reports, 7, 41685. doi:10.1038/srep41685

Balsdon, T. & Azzopardi, P. (2015). Absolute and relative blindsight. Consciousness and cognition, 32, 79-91. doi:10.1016/j.concog.2014.09.010

Balsdon, T., Summersby, S., Kemp, R. & White, D. (2018). Improving face identification with specialist teams. Cognitive Research: Principles and Implications, 3(1), 25. doi:10.1186/s41235-018-0114-7

Balsdon, T., Schweitzer, R. , Watson, T. & Rolfs, M. (2018). All is not lost: Post-saccadic contributions to the perceptual omission of intra-saccadic streaks. Consciousness and Cognition , 64, 19-31. doi:10.1016/j.concog.2018.05.004

Balsdon, T. & Clifford, C. (2018). How wide is the cone of direct gaze? Royal Society open science 6, 5(8), 180249

Balsdon, T. & Clifford, C. (2018). Task Dependent Effects of Head Orientation on Perceived Gaze Direction. Frontiers in Psychology, 9, 2491. doi:10.3389/fpsyg.2018.02491

Balsdon, T. & Clifford, C. (2018). Visual processing: conscious until proven otherwise. , 5(1). doi:10.1098/rsos.171783

Baroncelli, L. & Lunghi, C. (2020). Neuroplasticity of the visual cortex: In sickness and in health. Experimental Neurology, 335, 113515. doi:10.1016/j.expneurol.2020.113515

Barthelmé, S. & Mamassian, P. (2009). Evaluation of objective uncertainty in the visual system. PLoS Computational Biology, 5(9), e1000504. doi:10.1371/journal.pcbi.1000504

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)

Betina Ip, I. , Emir, U., Lunghi, C., Parker, A. & Bridge, H. (2021). GABAergic inhibition in the human visual cortex relates to eye dominance. Scientific Reports , 11, 17022. doi:10.1038/s41598-021-95685-1

Binda, P. & Lunghi, C. (2017). Short-Term Monocular Deprivation Enhances Physiological Pupillary Oscillations. Neural Plasticity, 2017. doi:10.1155/2017/6724631

Binda, P., Kurzawski, J., Lunghi, C., Biagi, L., Tosetti, M. & Morrone, M. (2018). Response to short-term deprivation of the human adult visual cortex measured with 7T BOLD. eLife, 7. doi:10.7554/eLife.40014

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

Chambon, V., Thero, H., Vidal, M., Vandendriessche, C., Haggard, P. & Palminteri, S. (2020). Choosing and learning: outcome valence differentially affects learning from free versus forced choices. Nature Human Behaviour, .

Chambon, V., Thero, H., Vidal, M., Vandendriessche, H., Haggard, P. & Palminteri, S. (2020). Information about action outcomes differentially affects learning from self-determined versus imposed choices. Nature Human Behaviour , 4, 1067-1079. doi:10.1038/s41562-020-0919-5

Chambon, V., Thero, H., Findling, C. & Koechlin, E. (2018). Believing in one's power: a counterfactual heuristic for goal-directed control. bioRxiv, 498675. doi:10.1101/498675

Chambon, V., Domenech, P., Jacquet, P., Barbalat, G., Bouton, S., Pacherie, E., Koechlin, E. & Farrer, C. (2017). Neural coding of prior expectations in hierarchical intention inference. Scientific reports, 7(1), 1278. doi:10.1038/s41598-017-01414-y

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

Daniele, G. , Lunghi, C., Dardano, A. , Binda, P. , Ceccarini, G., Ferruccio, S. , Giusti, L. , Ciccarone, A. , Bellini, R. , Moretto, C. , Maria Concetta, M. & Del Prato, S. (2021). Bariatric surgery restores visual cortical plasticity in nondiabetic subjects with obesity. International Journal of Obesity , 45, 1821-1829. doi:10.1038/s41366-021-00851-0

Deneux, T., Kempf, A., Daret, A., Ponsot, E. & Bathellier, B. (2016). Temporal asymmetries in auditory coding and perception reflect multi-layered nonlinearities. Nature communications, 7, 12682. doi:10.1038/ncomms12682

Domenech, P., Rheims, S. & Koechlin, E. (2020 ). Neural Mechanisms resolving Exploitation-Exploration dilemmas in the prefrontal cortex. Science, 369(6507), eabb0184. doi:10.1126/science.abb0184

Domenech, P., Redouté, J., Koechlin, E. & Dreher, J. (2018). The Neuro-Computational Architecture of Value-Based Selection in the Human Brain. Cerebral cortex (New York, N.Y. : 1991), 28(2), 585-601. doi:10.1093/cercor/bhw396

Duverne, S. & Koechlin, E. (2017). Rewards and Cognitive Control in the Human Prefrontal Cortex. Cerebral cortex (New York, N.Y. : 1991), 27(10), 5024-5039. doi:10.1093/cercor/bhx210

Erdmann, A. , Joseph Wrisley, D., Allen, B. , Brown, C. , Cohen-Bodenes, S., Elsner, M. , Feng, Y. , D Joseph, B. , Joyeux-Prunel, B. & de Marneffe, M. (2019). Practical, Efficient, and Customizable Active Learning for Named Entity Recognition in the Digital Humanities. In Proceedings of the 2019 Conference of the North, 2223-2234. doi:10.18653/v1/N19-1231

Findling, C., Chopin, N. & Koechlin, E. (2021). Imprecise neural computations as a source of adaptive behaviour in volatile environments. Nature Human Behaviour , 5, 99-112. doi:10.1038/s41562-020-00971-z

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

Fontanesi , L., Palminteri, S. & Lebreton, M. (2019). Decomposing the effects of context valence and feedback information on speed and accuracy during reinforcement learning: A meta-analytical approach using diffusion decision modeling. Cognitive Affective Behavioral Neuroscience, 1-13. doi:10.3758/s13415-019-00723-1