Preprocessing module

The preprocessing module includes preprocessing steps to apply before spike sorting. Preprocessors are lazy, meaning that no computation is performed until it is required (usually at the spike sorting step). This enables one to build preprocessing chains to be applied in sequence to a RecordingExtractor object. This is possible because each preprocessing step returns a new RecordingExtractor that can be input to the next step in the chain.

In this code example, we build a preprocessing chain with 2 steps:

  1. bandpass filter

  2. common median reference (CMR)

import spikeinterface.preprocessing import bandpass_filter, common_reference

# recording is a RecordingEctractor object
recording_f = bandpass_filter(recording, freq_min=300, freq_max=6000)
recording_cmr = common_reference(recording_f, operator="median")

After preprocessing, we can optionally save the processed recording with the efficient SI save() function:

recording_saved ="preprocessed", n_jobs=8, total_memory="2G")

In this case, the save() function will process in parallel our original recording with the bandpass filter and CMR and save it to a binary file in the “preprocessed” folder. The recording_saved is yet another RecordignExtractor which maps directly to the newly created binary file, for very quick access.