TY - JOUR
T1 - Modeling neural activity with cumulative damage distributions
AU - Leiva, Víctor
AU - Tejo, Mauricio
AU - Guiraud, Pierre
AU - Schmachtenberg, Oliver
AU - Orio, Patricio
AU - Marmolejo-Ramos, Fernando
N1 - Funding Information:
The authors thank the Editor-in-Chief, Prof. Dr. J. Leo van Hemmen, and two anonymous referees for their valuable comments on an earlier version of this manuscript, which resulted in this improved version. The authors thank Rosie Gronthos from Australia for proofreading the first revised version of this manuscript and Patricia Van Roon from Canada for proofreading its second version. The research of V. Leiva was supported by FONDECYT 1120879 grant from the Chilean government; of M. Tejo by FONDECYT 3140613 postdoctorate grant; of P. Guiraud by PIA-Anillo ACT1112 grant from the Chilean government; of P. Orio by FONDECYT 1130862 and PIA-Anillo ACT-1113; and of P. Orio and O. Schmachtenberg by The Centro Interdisciplinario de Neurociencia de Valparaíso, which is a Millennium Institute supported by the Millennium Scientific Initiative of the Ministerio de Economía, Fomento y Turismo of the Chilean government.
Publisher Copyright:
© 2015, Springer-Verlag Berlin Heidelberg.
PY - 2015/10/24
Y1 - 2015/10/24
N2 - 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.
AB - 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.
KW - Birnbaum–Saunders and inverse Gaussian distributions
KW - Integrate-and-fire model
KW - Inter-spike intervals
KW - Maximum likelihood method
KW - Model selection and goodness of fit
UR - http://www.scopus.com/inward/record.url?scp=84942195713&partnerID=8YFLogxK
U2 - 10.1007/s00422-015-0651-9
DO - 10.1007/s00422-015-0651-9
M3 - Article
C2 - 25998210
AN - SCOPUS:84942195713
VL - 109
SP - 421
EP - 433
JO - Biological Cybernetics
JF - Biological Cybernetics
SN - 0340-1200
IS - 4-5
ER -