Investigating Neural Correlations – an Approach to Measure Concurrent Firing Activity

Research in neuroscience studies has typically focus on correlation-based metrics between multiple simultaneously recorded spike trains, when addressing the common question on how particular neurons (or neuronal populations) communicate. In this work, we propose a novel approach to quantify the level of concurrent firing activity between two spike trains based on the coarse decomposition of their firing activities. The overall activity of each neuron is fragmented into three functional states (bursting, moderate firing and non-firing) and the degree of simultaneous activations is measured as a fraction of overlap of the working modes (bursting and moderate firing) between two spike trains. The proposed measure does not consider periods when both neurons are in quiescence. The method is assumption free, requiring only one input parameter estimated for each neuron based on its specific firing properties. The measure is evaluated and compared with the well recognized indexes of spike train correlation in controlled experiments with synthetic Poisson spike trains.