We then investigated two #LossyCompression strategies: bit truncation and WavPack Hybrid mode. Lossy compression can dramatically boost compression performance, but we must first assess how it affects downstream analysis (i.e., spike sorting).

(5/n)

Using simulated data with known ground truth spike times, we used #Kilosort 2.5 to evaluate spike sorting performance. WavPack Hybrid does not affect spike sorting accuracy, even at maximum compression levels (~14% file size).

(6/n)

We repeated spike sorting on experimental data, this time counting the number of units passing or failing quality control (QC). Again, we observed minimal changes in the results when using WavPack Hybrid.

(7/n)

Waveform shapes are also important for downstream analysis, e.g., cell-type classification. On simulated data, we found that WavPack Hybrid nicely preserves three commonly used waveform features.

(8/n)

WavPack Hybrid is promising, but we observed subtle differences in spike trains before and after compression. We need better methods for comparing spike sorting results to make sure we’re not losing any critical info. Until then, we’ll be using lossless compression.

(9/n)

Do you want to apply compression right away? All compression options can be readily deployed with a few lines using
@spikeinterface
, so you can easily try them out of your own data! This will also make it easy to benchmark new compression methods as they become available.

(10/n)

At @AllenInstitute
for Neural Dynamics we value fairness and reproducibility in science. All figures of the manuscript can be reproduced with
@codeocean:

https://codeocean.com/capsule/3822095/tree/v1

(11/n)

Finally, kudos to all co-authors!
Olivier Winter, David Bryant, David Feng, @svoboda314 and Josh Siegle, and thanks to
@alleninstitute for sponsoring this work!

(12/n)

@buccino_alessio 👍 I always wondered if ephys and (human) audio signals are similar for some deep reason or just coincidence. I guess they are both roughly 1/f with about 20 kHz bandwidth