Publications

de Vignemont, F. (2020). What Phenomenal Contrast for Bodily Ownership? Journal of the American Philosophical Association, 6(1), 117-137. doi:10.1017/apa.2019.34

Sidarus, N., Palminteri, S. & Chambon, V. (2018). Trading off the cost of conflict against expected rewards. Plos Computational Biology, 42809. doi:10.1371/journal.pcbi.1007326

de Vignemont, F., Wong, H. , Serino, A. & Farnè, A. (2023). The world at our fingertips: a multidisciplinary investigation of Peripersonal space. . doi:10.1093/oso/9780198851738.001.0001

Cardinali , L., Zanini , A., Yanofsky , R., Roy, A., de Vignemont, F., Culham , J. & Farnè, A. (2021). The toolish hand illusion: embodiment of a tool based on similarity with the hand. Scientific Reports, 11(1), 2024. doi:10.1038/s41598-021-81706-6

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

Dominijanni, G. , Shokur, S. , Salvietti, G. , Palmerini, E. , Rossi, S. , de Vignemont, F., d’Avella, A. , Makin, T., Prattichizzo, D. & Micera , S. (2021). The neural resource allocation problem when enhancing human bodies with extra robotic limbs. Nature Machine Intelligence, 3, 850-860. doi:10.1038/s42256-021-00398-9

van der Veer, A. , Alsmith, A., Longo, M. , Wong, H. , Diers, D. , Bues, M. , Giron, A. & Mohler, B. (2019). The influence of the viewpoint in a self-avatar on body part and self-localization. In ACM Symposium on Applied Perception 2019, 1-11. doi:10.1145/3343036.3343124

Palminteri, S., Wyart, V. & Koechlin, E. (2017). The Importance of Falsification in Computational Cognitive Modeling. Trends in Cognitive Sciences, 21(6), 425-433. doi:10.1016/j.tics.2017.03.011

Denève, S., Alemi, A. & Bourdoukan, R. (2017). The Brain as an Efficient and Robust Adaptive Learner. Neuron, 94(5), 969-977. doi:10.1016/j.neuron.2017.05.016

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

Makin, T. & de Vignemont, F. (2020). Soft Embodiment for Engineering Artificial. Trends in Cognitive, 4(12), 965-968. doi:10.1016/j.tics.2020.09.008

Longo, M., Rajapakse , S., Alsmith, A. & Ferre , F. (2020). Shared contributions of the head and torso to spatial reference frames across spatial judgments. Cognition, .

van der Veer, A. , Longo, M. , Alsmith, A., Wong, H. & Mohler, B. (2019). Self and body part localization in virtual reality: Comparing a headset and a large-screen immersive display. Frontiers in Robotics and AI, 6, 33. doi:10.3389/frobt.2019.00033

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

Romagnoni, A. , Colonnese, M. , Touboul, J. & Gutkin, B. (2020). Progressive alignment of inhibitory and excitatory delay may drive a rapid developmental switch in cortical network dynamics. J. of Neurophysiology, 123(5), 1583-1599. doi:10.1152/jn.00402.2019

Rouault, M., Drugowitsch, J. & Koechlin, E. (2019). Prefrontal mechanisms combining rewards and beliefs in human decision-making. Nature Communications, 10, 301. doi:10.1038/s41467-018-08121-w

Koechlin, E. (2018). Prefrontal function and cognitive control: from action to language. Current Opinion in Behavioral Sciences, 21, 106-111. doi:10.1016/j.cobeha.2018.03.008

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

Gutierrez, G. & Denève, S. (2018). Population adaptation in efficient balanced networks. eLife, 8, e46926. doi:10.7554/eLife.46926

de Vignemont, F., Serino, A., Wong, H. & Farnè, A. (2021). Peripersonal space: a special way of representing space.

de Vignemont, F. (2021). Peripersonal perception in action. Synthese, 198, 4027–4044. doi:10.1007/s11229-018-01962-4

de Vignemont, F. (2018). Peripersonal perception in action. Synthese, 1-18. doi:10.1007/s11229-018-01962-4

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

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

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

Kushnir, L. & Fusi, S. (2018). Neural Classifiers with Limited Connectivity and Recurrent Readouts. Journal of Neuroscience, 38 (46), 9900-9924. doi:10.1523/JNEUROSCI.3506-17.2018

Mansouri, F., Koechlin, E., Rosa, M. & Buckley, M. (2017). Managing competing goals - a key role for the frontopolar cortex. Nature reviews. Neuroscience, 18(11), 645-657. doi:10.1038/nrn.2017.111

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

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

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