Spike Train Probability Models for Stimulus-Driven Leaky Integrate-and-Fire Neurons
نویسندگان
چکیده
منابع مشابه
Spike Train Probability Models for Stimulus-Driven Leaky Integrate-and-Fire Neurons
Mathematical models of neurons are widely used to improve understanding of neuronal spiking behavior. These models can produce artificial spike trains that resemble actual spike train data in important ways, but they are not very easy to apply to the analysis of spike train data. Instead, statistical methods based on point process models of spike trains provide a wide range of data-analytical t...
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The response of model neurons driven by a periodic current converges onto mode-locked attractors. Reliability, de%ned as the noise stability of the attractor, was studied as a function of the drive frequency and noise strength. For weak noise, the neuron remained on one attractor and reliability was high. For intermediate noise strength, transitions between attractors occurred. For strong noise...
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We study noise-induced resonance effects in the leaky integrate-and-fire neuron model with absolute refractory period, driven by a Gaussian white noise. It is demonstrated that a finite noise level may either maximize or minimize the regularity of the spike train. We also partition the parameter space into regimes where either or both of these effects occur. It is shown that the coherence minim...
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An analytical description of the response properties of simple but realistic neuron models in the presence of noise is still lacking. We determine completely up to the second order the firing statistics of a single and a pair of leaky integrate-and-fire neurons receiving some common slowly filtered white noise. In particular, the auto- and cross-correlation functions of the output spike trains ...
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Reconstructing stimuli from the spike trains of neurons is an important approach for understanding the neural code. One of the difficulties associated with this task is that signals which are varying continuously in time are encoded into sequences of discrete events or spikes. An important problem is to determine how much information about the continuously varying stimulus can be extracted from...
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ژورنال
عنوان ژورنال: Neural Computation
سال: 2008
ISSN: 0899-7667,1530-888X
DOI: 10.1162/neco.2008.06-07-540