Cross nearest-spike interval based method to measure synchrony dynamics.
A new synchrony index for neural activity is defined in this paper. The method is able to measure synchrony dynamics in low firing rate scenarios. It is based on the computation of the time intervals between nearest spikes of two given spike trains. Generalized additive models are proposed for the synchrony profiles obtained by this method. Two hypothesis tests are proposed to assess for differences in the level of synchronization in a real data example. Bootstrap methods are used to calibrate the distribution of the tests. Also, the expected synchrony due to chance is computed analytically and by simulation to assess for actual synchronization.
Department of Mathematics, Facultad de Informatica, Campus de Elvina s/n, 15071, Universidade da Coruna, A Coruna, Spain. agonzalezmo@udc.es.
Aldana M Gonzalez
AM
Montoro
Ricardo
R
Cao
Christel
C
Faes
Geert
G
Molenberghs
Nelson
N
Espinosa
Javier
J
Cudeiro
Jorge
J
Marino
D000200:Action Potentials / Q000502:physiology*; D000465:Algorithms; D001921:Brain / Q000502:physiology*; D003198:Computer Simulation; D004594:Electrophysiology / Q000379:methods; D006801:Humans; D008959:Models, Neurological; D009474:Neurons / Q000378:metabolism / Q000502:physiology*; D009991:Oscillometry; D016012:Poisson Distribution; D011336:Probability; D009435:Synaptic Transmission; D013997:Time Factors