Difference of Gaussians

SpikeSift applies a Difference-of-Gaussians (DoG) filter to isolate the frequency band where spikes are most prominent. Because the rest of the pipeline is highly optimized, filtering accounts for nearly one-third of total runtime — making an efficient implementation essential.

Why Gaussians?

Gaussian filters apply a smooth weighting, emphasizing nearby samples while gently suppressing distant ones. This avoids artifacts and sharp transitions introduced by filters with abrupt cutoffs.

Why take the difference of two Gaussians?

Subtracting two Gaussians produces a clean bandpass effect:

• The narrow Gaussian removes high-frequency noise

• The wide Gaussian eliminates slow fluctuations like local field potentials

Why is this more efficient than standard filters?

Each Gaussian is approximated using four recursive moving averages (box filters). This avoids expensive operations like convolutions or FFTs, while still preserving signal fidelity.