Publications

Zeldenrust, F., De Knecht, S., Wadman, W., Denève, S. & Gutkin, B. (2017). Estimating the Information Extracted by a Single Spiking Neuron from a Continuous Input Time Series. Frontiers in computational neuroscience, 11, 49. doi:10.3389/fncom.2017.00049

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

Andrillon, T., Kouider, S., Agus, T. & Pressnitzer, D. (2015). Perceptual learning of acoustic noise generates memory-evoked potentials. Current biology : CB, 25(21), 2823-2829. doi:10.1016/j.cub.2015.09.027

Joly, O., Pallier, C., Ramus, F., Pressnitzer, D., Vanduffel, W. & Orban, G. (2012). Processing of vocalizations in humans and monkeys: a comparative fMRI study. NeuroImage, 62(3), 1376-89. doi:10.1016/j.neuroimage.2012.05.070

Joly, O., Ramus, F., Pressnitzer, D., Vanduffel, W. & Orban, G. (2012). Interhemispheric differences in auditory processing revealed by fMRI in awake rhesus monkeys. Cerebral cortex (New York, N.Y. : 1991), 22(4), 838-53. doi:10.1093/cercor/bhr150

Alemi, A., Machens, C., Denève, S. & Slotine, J. (2018). Learning nonlinear dynamics in efficient, balanced spiking networks using local plasticity rules. In Thirty-Second AAAI Conference on Artificial Intelligence, New Orleans, Louisiana, USA, AAAI Press.

Koechlin, E. (2020). Executive Control and Decision-Making: a neural theory of prefrontal function. The Cognitive Neurosciences VI (pp. 451).