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266 Réponse à London et al. spike do so at approximately the same time (because of the precision due to fast depolarization). Because, as they show in their simulations, it only takes a few synchronous spikes to produce a new set of fast voltage excursions, the stochastic spike timing code will continue to propagate. This propagation is much like a synfire chain, except that it is an unreliable chain, since only a small fraction of neurons spike at each stage. However, such unreliable but precise synfire chains were explicitly ruled out by Diesmann and colleagues (Diesmann et al. 1999), who showed that, in a noisy environment, synfire chains either die out or the spikes become very reliable. Consequently, for recurrent networks, which are intrinsically noisy, a spike timing code can exist only if the precisely timed spikes are reliable. Thus, while the proposal of a stochastic spike timing code is an interesting one, we believe that such codes are ruled out by the chaotic dynamics, and thus high noise, that we have shown to exist in rat barrel cortex.
Annexe 267 B Publications Journal Papers 1. Rossant, C. ; Goodman, D.F.M. ; Platkiewicz, J. & Brette, R. Automatic fitting of spiking neuron models to electrophysiological recordings. Frontiers in Neuroinformatics, 2010, 4. 2. Rossant, C. ; Goodman, D.F.M. ; Fontaine, B. ; Platkiewicz, J. ; Magnusson, A. & Brette, R. Fitting neuron models to spike trains. Frontiers in Neuroscience, 2011, 5. 3. Rossant, C. ; Fontaine, B. & Goodman, D.F.M. Playdoh : a lightweight Python library for distributed computing and optimisation. Journal of Computational Science, 2011. 4. Rossant, C., Leijon, S. ; Magnusson, A. & Brette, R. Sensitivity of Noisy Neurons to Coincident Inputs. The Journal of Neuroscience, Society for Neuroscience, 2011, 31, 17193-17206. 5. Rossant, C. ; Fontaine, B. ; Magnusson, A. & Brette, R. A calibration-free electrode compensation method. The Journal of Neurophysiology (in revision), 2012. 6. Rossant, C. & Brette, R. Theory of stochastic coincidence detection in spiking neuron models. Journal of Computational Neuroscience (in preparation), 2012. Posters 1. Rossant, C. & Brette, R. Coincidence detection in active neurons. Cosyne, Salt Lake City (poster), 2010.
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THÈSE DE DOCTORAT DE L’UNIVERSIT
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