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In the intact brain neurons are constantly exposed to intense synaptic activity. This heavy barrage of excitatory and inhibitory inputs was recreated in vitro by injecting a noisy current, generated as an Ornstein-Uhlenbeck process, into the soma of rat neocortical pyramidal cells. The response to such in vivo-like currents was studied systematically by(More)
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)
Neural dynamic processes correlated over several time scales are found in vivo, in stimulus-evoked as well as spontaneous activity, and are thought to affect the way sensory stimulation is processed. Despite their potential computational consequences, a systematic description of the presence of multiple time scales in single cortical neurons is lacking. In(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)
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 activity of neurons under temporally structured current injection. It is, however, difficult to compare the(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)
The relationship of the blood oxygen-level-dependent (BOLD) signal to its underlying neuronal activity is still poorly understood. Combined physiology and functional MRI experiments suggested that local field potential (LFP) is a better predictor of the BOLD signal than multiunit activity (MUA). To further explore this relationship, we simultaneously(More)