Publications de Renaud Jolivet

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As large-scale, detailed network modeling projects are flourishing in the field of computational neuroscience, it is more and more important to design single neuron models that not only capture qualitative features of real neurons but are quantitatively ac ...

This work investigates the capacity of Integrate-and-Fire-type (I&F-type) models to quantitatively predict spike trains of real neurons in various laboratory and in vivo-like settings. A step-by-step methodology is developed to build an equivalent effectiv ...

Several methods and algorithms have recently been proposed that allow for the systematic evaluation of simple neuron models from intracellular or extracellular recordings. Models built in this way generate good quantitative predictions of the future activi ...

An adaptive Exponential Integrate-and-Fire (aEIF) model was used to predict the activity of layer-V-pyramidal neurons of rat neocortex under random current injection. A new protocol has been developed to extract the parameters of the aEIF model using an op ...

Renaud Jolivet

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The quantitative single-neuron modeling competition

Effective minimal threshold models of neuronal activity

A benchmark test for a quantitative assessment of simple neuron models

Predicting neuronal activity with simple models of the threshold type: Adaptive Exponential Integrate-and-Fire model with two compartments

Special issue on quantitative neuron modeling