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Characterization of reliability of spike timing in spinal interneurons during oscillating inputs

Related publications (34)

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Goodness-of-fit tests for neural population models: the multivariate time-rescaling theorem

Joao Emanuel Felipe Gerhard

Statistical models of neural activity are at the core of the field of modern computational neuroscience. The activity of single neurons has been modeled to successfully explain dependencies of neural dynamics to its own spiking history, to external stimuli ...

2010

Complexity and performance in simple neuron models

Wulfram Gerstner, Richard Naud, Skander Mensi

The ability of simple mathematical models to predict the activity of single neurons is important for computational neuroscience. In neurons, stimulated by a time-dependent current or conductance, we want to predict precisely the timing of spikes and the su ...

2010

The coordinated, collective spiking activity of neuronal populations encodes and processes information. One approach towards understanding such population based computation is to fit statistical models to simultaneously recorded spike trains and use these ...

2010

Although it is widely believed that reinforcement learning is a suitable tool for describing behavioral learning, the mechanisms by which it can be implemented in networks of spiking neurons are not fully understood. Here, we show that different learning r ...

Massachusetts Institute of Technology Press2009

The complexity of processes occurring in the brain is an intriguing issue not just for scientists and medical doctors, but the humanity in general. The cortex ability to perceive and analyze an enormous amount of information in an instance of time, the par ...

EPFL2008

Dynamic I-V curves are reliable predictors of naturalistic pyramidal-neuron voltage traces

Wulfram Gerstner, Carl Petersen, Laurent Badel, Sandrine Lefort, Romain Brette

Neuronal response properties are typically probed by intracellular measurements of current-voltage (I-V) relationships during application of current or voltage steps. Here we demonstrate the measurement of a novel I-V curve measured while the neuron exhibi ...

American Physiological Society2008

Simple Neuron Models and Adaptation

Skander Mensi

Predicting activity of single neuron is an important part of the computational neuroscience and a great challenge. Several mathematical models exist, from the simple (one compartment and few parameters, like the SRM or the IF-type models), to the more comp ...

2008

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For simulations of large spiking neuron networks, an accurate, simple and versatile single-neuron modeling framework is required. Here we explore the versatility of a simple two-equation model: the adaptive exponential integrate-and-fire neuron. We show th ...

Springer Verlag2008

Minimal nonlinear dynamic neuron models of the generic bifurcation type may provide the middle way between the detailed models favored by experimentalists and the simplified threshold and rate model of computational neuroscientists. This thesis investigate ...

EPFL2006

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Non-invasive brain-computer interfaces are traditionally based on mu rhythms, beta rhythms, slow cortical potentials or P300 event-related potentials. However, there is mounting evidence that neural oscillations up to 200 Hz play important roles in process ...

2006