Methods for characterizing interspike intervals and identifying bursts in neuronal activity.

Neurons produce complex patterns of electrical spikes, which are often clustered in bursts. The patterns of spikes and bursts can change substantially when neurons are exposed to toxins and chemical agents. For that reason, characterization of these patterns is important for the development of neuron-based biosensors for environmental threat exposure. Here, we develop a quantitative approach to describe the distribution of interspike intervals, based on plotting histograms of the logarithm of the interspike interval. This approach provides a method for automatically classifying spikes into bursts, which does not depend on assumptions about the burst parameters. Furthermore, the approach provides a sensitive technique for detecting changes in spike and burst patterns induced by pharmacological exposure. Hence, it is suitable for use both as a research tool and for deployment in a neuron-based biosensor.