Matthieu Delescluse

Graduate student

Laboratoire de Physiologie Cérébrale
CNRS UMR 8118
UFR biomédicale de l'Université René Descartes (Paris V)
45, rue des Saints Pères
75006 Paris
France
tel: 01 42 86 38 31
fax: 01 42 86 38 30
matthieu.delescluse@polytechnique.org

A lot of work has been carried out to study the properties of individual neurons and their synaptic connections in slices of cerebellar cortex. These studies essentially make use of the patch-clamp technique. More recently, calcium imaging, aimed at understanding calcium dynamics within individual cells, has enjoyed a growing success. Moreover, the circuit organization of the cerbellar cortex has been established for a long time and is known in detail. If one knows (at least some of) the properties of the different cell types, (some of) the properties of their synaptic connections, as well as the way they are spatially organized and connected, one (at least I) would like to know how they work together. Are the activities of individual cells linked at all or are they completely random and independent? Are individual spike trains correlated? And if yes to what extent? In which conditions? And can we relate what we knows about individual cells to the global activity of a group of cells?

Together with Christophe Pouzat, we try to work on the population activity of the principal cells of the cerebellar cortex, namely the Purkinje Cells (PCs), in slices. Our goal is to make the link between the available knowledge about individual cells and synapses and the observed group activity.

Doing that requires a difficult problem to be solved though. First, we have to record the activities of several cells simultaneously. We use multisite electrode provided by the Center for Neural Communication Technology of the University of Michigan that we placed extracellularly along the PC layer. Second, we have to re-build the individual spike trains present in a mixture of action potentials generated by several neurons simultaneously. In the raw data collected by our electrode, the spike trains of all neurons are completely mixed up, so that they are not exploitable at all as such. We have to extract each individual spike train. This is the spike-sorting problem. Once this is (correctly) done, one can analyse the putative correlations between the reconstructed spike trains.

The spike-sorting problem is an old problem but has not received any fully satisfying solution yet. Christophe Pouzat initiated a radically new approach that solves some of the recurrent spike-sorting problems and offers a promising framework for future advances. I try to bring my own contribution to it. We developed SpikeOMatic, a software that performs the complete analysis of multineuron data, from reading the raw data to the end of the spike-sorting. You can discover and use the software on this page.




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