Miura, KeijiUchida, Naoshige2017-04-132008Miura, Keiji and Naoshige Uchida. 2008. A Rate-Independent Measure of Irregularity for Event Series and It's Application to Neural Spiking Activity. Proceedings of the 47th IEEE Conference on Decision and Control, Cancun, Mexico, December 9-11, 2008.http://nrs.harvard.edu/urn-3:HUL.InstRepos:32116889Although higher-order statistics of neuronal firing have been characterized in neuroscience, many analyses ignore the nonstationarity of the background firing rate. We discuss how to measure the irregularity of interspike intervals in a rate-independent manner. Under the framework of semiparametric statistical models, we develop an estimator of firing irregularity which remains after the effects of rate modulations are removed. We found that firing irregularity is robust and reproducible in neurons in olfactory cortex irrespective of the rate modulation during the task period. As the level of irregularity varies among neurons, we classified neurons in olfactory cortex by using the proposed measure as a feature.en-USmaximum likelihood estimationneural netsevent series irregularityhigher-order statisticsneural spiking activityneuronal firingolfactory cortexrate modulationsrate-independent measurebrain modelinghigher order statisticsin vivomathematical modelnervous systemneuronsneuroscienceolfactoryparameter estimationrobustnessConference Paper2013-07-09Keiji Miura, Naoshige Uchida10.1109/CDC.2008.4739083