Cargando…
Self-consistent determination of the spike-train power spectrum in a neural network with sparse connectivity
A major source of random variability in cortical networks is the quasi-random arrival of presynaptic action potentials from many other cells. In network studies as well as in the study of the response properties of single cells embedded in a network, synaptic background input is often approximated b...
Autores principales: | Dummer, Benjamin, Wieland, Stefan, Lindner, Benjamin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4166962/ https://www.ncbi.nlm.nih.gov/pubmed/25278869 http://dx.doi.org/10.3389/fncom.2014.00104 |
Ejemplares similares
-
Self-Consistent Scheme for Spike-Train Power Spectra in Heterogeneous Sparse Networks
por: Pena, Rodrigo F. O., et al.
Publicado: (2018) -
Sparse Computation in Adaptive Spiking Neural Networks
por: Zambrano, Davide, et al.
Publicado: (2019) -
Latency correction in sparse neuronal spike trains
por: Kreuz, Thomas, et al.
Publicado: (2022) -
Heterogeneous short-term plasticity enables spectral separation of information in the neural spike train
por: Droste, Felix, et al.
Publicado: (2012) -
Sparse Data Analysis Strategy for Neural Spike Classification
por: Vigneron, Vincent, et al.
Publicado: (2014)