Publications

Engelen, T., Solca, M. & Tallon-Baudry, C. (2023). Interoceptive rhythms in the brain. Nature neuroscience, 26, 1670–1684. doi:10.1038/s41593-023-01425-1

Petzschner, F., Critchley, H. & Tallon-Baudry, C. (2022). Interoception. Scholarpedia, . doi:10.4249/scholarpedia.55569

Cimesa, L., Ciric, L. & Ostojic, S. (2023). Geometry of population activity in spiking networks with low-rank structure. PLoS computational biology, 19(8), e1011315. doi:10.1371/journal.pcbi.1011315

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

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

Tallon-Baudry, C. (2023). Interoception: Probing internal state is inherent to perception and cognition. Neuron, . doi:10.1016/j.neuron.2023.04.019

Engelen, T., Buot, A., Grèzes, J. & Tallon-Baudry, C. (2023). Whose emotion is it? Perspective matters to understand brain-body interactions in emotions. NeuroImage, 268, 119867. doi:10.1016/j.neuroimage.2023.119867

Tallon-Baudry, C. (2022). The topological space of subjective experience. Trends in Cognitive Sciences. doi:10.1016/j.tics.2022.09.002

Barbosa, J., Babushkin, V. , Temudo, A. , Sreenivasan, K. & Compte, A. (2021). Across-Area Synchronization Supports Feature Integration in a Biophysical Network Model of Working Memory. Front. Neural Circuits. doi:10.3389/fncir.2021.716965

Stein, H., Barbosa, J. & Compte, A. (2021). Towards biologically constrained attractor models of schizophrenia. Current Opinion in Neurobiology, 70, 171-181. doi:10.1016/j.conb.2021.10.013

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

Barbosa, J., Stein, H., Zorowitz, S. , Niv, Y. , Summerfield, C., Soto-Faraco, S. & Hyafil, A. (2022). A practical guide for studying human behavior in the lab. Behavior Research Methods. doi:10.3758/s13428-022-01793-9

Jazayeri, M. & Ostojic, S. (2021). Interpreting neural computations by examining intrinsic and embedding dimensionality of neural activity. Current Opinion in Neurobiology, 70, 113-120. doi:10.1016/j.conb.2021.08.002

Dubreuil, A., Valente, A., Beiran, M., Mastrogiuseppe, F. & Ostojic, S. (2022). The role of population structure in computations through neural dynamics. Nature Neuroscience, 25, 783–794. doi:10.1038/s41593-022-01088-4

Mello, M. , Dupont, L. , Engelen, T., Acciarino, A. , W. de Borst, A. & de Gelder, B. (2022). The influence of body expression, group affiliation and threat proximity on interactions in virtual reality. Current Research in Behavioral Sciences, 3, 100075. doi:10.1016/j.crbeha.2022.100075

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

Cleeremans, A. & Tallon-Baudry, C. (2022). Consciousness matters: phenomenal experience has functional value. Neuroscience of Consciousness., 2022(1), niac007. doi:10.1093/nc/niac007

Azzalini, D., Rebollo, I. & Tallon-Baudry, C. (2019). Visceral Signals Shape Brain Dynamics and Cognition. Trends in Cognitive Sciences , 23(6), 488-509. doi:10.1016/j.tics.2019.03.007

Babo-Rebelo, M., Buot, A. & Tallon-Baudry, C. (2019). Neural responses to heartbeats distinguish self from other during imagination. NeuroImage, 191, 10-20. doi:10.1016/j.neuroimage.2019.02.012

Babo-Rebelo, M., Richter, C. & Tallon-Baudry, C. (2016). Neural Responses to Heartbeats in the Default Network Encode the Self in Spontaneous Thoughts. The Journal of Neuroscience, 36(30), 7829-7840. doi:10.1523/JNEUROSCI.0262-16.2016

Babo-Rebelo, M., Wolpert, N., Adam, C., Hasboun, D. & Tallon-Baudry, C. (2016). Is the cardiac monitoring function related to the self in both the default network and right anterior insula? Philosophical Transactions B, 371(1708), 20160004. doi:10.1098/rstb.2016.0004

Bagur, S. , Averseng, M., Elgueda, D., David, S., Fritz, J., Yin, P., Shamma, S., Boubenec, Y. & Ostojic, S. (2018). Go/No-Go task engagement enhances population representation of target stimuli in primary auditory cortex. Nature Communications, 9, 2529 . doi:10.1038/s41467-018-04839-9

Beiran, M., Dubreuil, A., Valente, A., Mastrogiuseppe, F. & Ostojic, S. (2021). Shaping dynamics with multiple populations in low-rank recurrent networks. Neural Computation, 33(6), 1572-1615. doi:10.1162/neco_a_01381 Article history

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

Bimbard, C., Ledoux, E. & Ostojic, S. (2016). Instability to a heterogeneous oscillatory state in randomly connected recurrent networks with delayed interactions. Physical review. E, 94(6-1), 062207. doi:10.1103/PhysRevE.94.062207

Blot, A., De Solages, C., Ostojic, S., Szapiro, G., Hakim, V. & Léna, C. (2016). Time-invariant feed-forward inhibition of Purkinje cells in the cerebellar cortex in vivo. The Journal of physiology, 594(10), 2729-49. doi:10.1113/JP271518

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

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

Buot, A., Azzalini, D., Chaumon, M. & Tallon-Baudry, C. (2021). Does stroke volume influence heartbeat evoked responses? Biological Psychology. doi:10.1016/j.biopsycho.2021.108165

Campana, F. & Tallon-Baudry, C. (2013). Anchoring visual subjective experience in a neural model: the coarse vividness hypothesis. Neuropsychologia, 51(6). doi:10.1016/j.neuropsychologia.2013.02.021