spiketime

Spiketime refers to the exact moment a neuron emits an action potential. In electrophysiological recordings, spike times are captured as precise time stamps relative to a reference clock or stimulus, and the collection of times for a neuron constitutes its spike train.

In data analysis, spikes are often represented as raster plots or as sequences of event times. Across many trials, spikes are aggregated into peri-stimulus time histograms to estimate how firing rate changes over time. Spike sorting is the process of assigning recorded spikes to putative individual neurons when multiple neurons are recorded on the same channel. Other common analyses include cross-correlations between spike trains, inter-spike interval distributions, and kernel-based estimates of instantaneous firing rate.

The question of coding—whether information is carried by exact spike timing or by average firing rate—has drove substantial research. Temporal coding theories propose that precise spike times can convey information beyond mean rates, while rate coding emphasizes averaged activity over time. Spike-time dependent plasticity (STDP) describes how the relative timing of presynaptic and postsynaptic spikes can strengthen or weaken synapses, linking spiking dynamics to learning.

Applications of spiketime analysis span neuroscience research and applied fields. They underpin brain–machine interfaces, neural prosthetics, and computational models of neural networks. Challenges include noisy data, misclassification in spike sorting, limited temporal resolution, and maintaining consistent spike timing across recording sessions.