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Rate models are often used to study the behavior of large networks of spiking neurons. Here we propose a procedure to derive rate models that take into account the fluctuations of the input current and firing-rate adaptation, two ubiquitous features in the central nervous system that have been previously overlooked in constructing rate models. The procedure(More)
Neurons generate spikes reliably with millisecond precision if driven by a fluctuating current--is it then possible to predict the spike timing knowing the input? We determined parameters of an adapting threshold model using data recorded in vitro from 24 layer 5 pyramidal neurons from rat somatosensory cortex, stimulated intracellularly by a fluctuating(More)
Integrate-and-Fire-type models are usually criticized because of their simplicity. On the other hand, the Integrate-and-Fire model is the basis of most of the theoretical studies on spiking neuron models. Here, we develop a sequential procedure to quantitatively evaluate an equivalent Integrate-and-Fire-type model based on intracellular recordings of(More)
Glucocorticoids, such as dexamethasone, have been used as in vitro inducers of adipogenesis. However, the roles of the glucocorticoid receptor (GR) in adipogenesis have not been well characterized yet. Here, we show that inhibition of GR activity using the GR antagonist RU486 prevents human mesenchymal stem cell and mouse embryonic fibroblast (MEF)(More)
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 optimal filtering technique combined with a black-box numerical optimization. We found that the aEIF(More)
Data recorded from multiple sources sometimes exhibit non-instanteneous couplings. For simple data sets, cross-correlograms may reveal the coupling dynamics. But when dealing with high-dimensional multivariate data there is no such measure as the cross-correlogram. We propose a simple algorithm based on Kernel Canonical Correlation Analysis (kCCA) that(More)
Pharmacological magnetic resonance imaging (phMRI) is a current direction in biomedical imaging, whose goal is the non-invasive monitoring of pharmacological manipulations on brain processes. We have developed techniques combining phMRI with simultaneous monitoring of electrophysiological activity during local injections of pharmacological agents into(More)
Automated analysis of fluorescence microscopy data relies on robust segmentation and tracking algorithms for sub-cellular structures in order to generate quantitative results. The accuracy of the image processing results is, however, frequently unknown or determined a priori on synthetic benchmark data. We present a particle filter framework based on Markov(More)
A novel integrate-and-fire model neuron is proposed to account for a non-monotonic f-I response function, as experimentally observed. As opposed to classical forms of adaptation, the present integrate and fire model the spike-emission process incorporates a state-dependent inactivation that makes the probability of emitting a spike decreasing as a function(More)
Spike frequency adaptation is an important cellular mechanism by which neocortical neurons accommodate their responses to transient , as well as sustained, stimulations. This can be quantified by the slope reduction in the f-I curves due to adaptation. When the neuron is driven by a noisy, in vivo-like current, adaptation might also affect the sensitivity(More)