title: An efficient method for the Fourier transform of a neuronal spike train.
abstract: A spike train may be represented by a superposition of Dirac delta-functions. One of the simplest ways of converting such a comb function into a continuous function is to use a Fourier transform. In general there are two possibilities, both of which have their disadvantages: the direct transform which is extremely time-consuming, and the fast Fourier transform of the low pass filtered comb function; the latter method, although quicker, often requires a greater storage capacity than is readily available. In the present paper, therefore, a third possibility is suggested. Essentially, it is a direct Fourier transform which takes advantage of certain properties of a spike train. The corresponding algorithm works much faster than a common Fourier transform.
mesh_terms: D000818:Animals; D005071:Evoked Potentials; D005583:Fourier Analysis; D006801:Humans; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology; D009435:Synaptic Transmission