Practical Considerations in the Implementation of the French-Holden Algorithm for Sampling of Neuronal Spike Trains

The French-Holden algorithm (1), (2), (3) provides a sampled data time series representation of a neuronal spike train in order to facilitate subsequent analyses by conventional signal processing techniques. Two characteristics of this filtering algorithm make the choice of data record length particularly important: (a) an ideal, sharp cutoff filter is used on the spike train, and (b) the Nyquist sampling frequency is chosen exactly equal to the filter cutoff frequency. In this note, sources of distortion and aliasing errors due to finite data records are discussed and guidelines for the selection of minimum record length are given.