Modeling neural activity with cumulative damage distributions

Neurons transmit information as action potentials or spikes. Due to the inherent randomness of the inter-spike intervals (ISIs), probabilistic models are often used for their description. Cumulative damage (CD) distributions are a family of probabilistic models that has been widely considered for de...

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Bibliographic Details
Published in:Biological cybernetics 2015-10, Vol.109 (4-5), p.421-433
Main Authors: Leiva, Víctor, Tejo, Mauricio, Guiraud, Pierre, Schmachtenberg, Oliver, Orio, Patricio, Marmolejo-Ramos, Fernando
Format: Article
Language:English
Subjects:
Action Potentials - physiology
Animals
Bioinformatics
Biological
Biomedical and Life Sciences
Biomedicine
Birnbaum-Saunders and inverse Gaussian distributions
Complex Systems
Computer Appl. in Life Sciences
Computer Simulation
Cumulative damage
Cybernetics
Female
Humans
Integrate-and-fire model
Inter-spike intervals
Inverse
Male
Mathematical models
Maximum likelihood method
Model selection and goodness of fit
Models, Neurological
Neurobiology
Neurons
Neurons - physiology
Neurosciences
Normal Distribution
Original Paper
Probabilistic methods
Probability theory
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Summary:Neurons transmit information as action potentials or spikes. Due to the inherent randomness of the inter-spike intervals (ISIs), probabilistic models are often used for their description. Cumulative damage (CD) distributions are a family of probabilistic models that has been widely considered for describing time-related cumulative processes. This family allows us to consider certain deterministic principles for modeling ISIs from a probabilistic viewpoint and to link its parameters to values with biological interpretation. The CD family includes the Birnbaum–Saunders and inverse Gaussian distributions, which possess distinctive properties and theoretical arguments useful for ISI description. We expand the use of CD distributions to the modeling of neural spiking behavior, mainly by testing the suitability of the Birnbaum–Saunders distribution, which has not been studied in the setting of neural activity. We validate this expansion with original experimental and simulated electrophysiological data.
ISSN:0340-1200
1432-0770
1432-0770
DOI:10.1007/s00422-015-0651-9