6533b83afe1ef96bd12a7091

RESEARCH PRODUCT

A Measure of Concurrent Neural Firing Activity Based on Mutual Information

Tatjana Loncar-turukaloGorana MijatovicLuca FaesNina MilosavljevicRiccardo StorchiNebojsa Bozanic

subject

Computer scienceModels NeurologicalAction PotentialsBinary numberRetinal ganglionMeasure (mathematics)050105 experimental psychologySynchronizationSurrogate data03 medical and health sciencesBursting0302 clinical medicineComputer Simulation0501 psychology and cognitive sciencesRepresentation (mathematics)Neuronsbusiness.industryGeneral Neuroscience05 social sciencesFiring patternsPattern recognitionMutual informationCorrelationConcurrent activityMutual informationArtificial intelligencebusinessNeural synchrony030217 neurology & neurosurgerySoftwareInformation Systems

description

Multiple methods have been developed in an attempt to quantify stimulus-induced neural coordination and to understand internal coordination of neuronal responses by examining the synchronization phenomena in neural discharge patterns. In this work we propose a novel approach to estimate the degree of concomitant firing between two neural units, based on a modified form of mutual information (MI) applied to a two-state representation of the firing activity. The binary profile of each single unit unfolds its discharge activity in time by decomposition into the state of neural quiescence/low activity and state of moderate firing/bursting. Then, the MI computed between the two binary streams is normalized by their minimum entropy and is taken as positive or negative depending on the prevalence of identical or opposite concomitant states. The resulting measure, denoted as Concurrent Firing Index based on MI (CFIMI), relies on a single input parameter and is otherwise assumption-free and symmetric. Exhaustive validation was carried out through controlled experiments in three simulation scenarios, showing that CFIMI is independent on firing rate and recording duration, and is sensitive to correlated and anti-correlated firing patterns. Its ability to detect non-correlated activity was assessed using ad-hoc surrogate data. Moreover, the evaluation of CFIMI on experimental recordings of spiking activity in retinal ganglion cells brought insights into the changes of neural synchrony over time. The proposed measure offers a novel perspective on the estimation of neural synchrony, providing information on the co-occurrence of firing states in the two analyzed trains over longer temporal scales compared to existing measures.

10.1007/s12021-021-09515-whttps://doi.org/10.1007/s12021-021-09515-w