Removing Horizontal Noise from Recordings
Version 4 Miniscopes with version numbers under v4.40 (these include v4.34 and v4.30) may show some small horizontal row noise in their neural imaging recordings. If this is the case, we have outlined 2 solutions below for removing this noise. One is a post-processing spatial filter approach using a Python Jupyter Notebook and the other is a hardware modification. We generally recommend using the offline post-processing approach as it seems to work very well and doesn't require any tricking modification to your hardware.
This noise shows up due to less than adequate noise rejection of one of the on-board voltage regulaters on the V4 Rigid-Flex PCB. The electrowetting lens driver ends up injecting noise at around 5KHz back into the 3.3V voltage regulator which then directly affects the reference voltage pin of the CMOS image sensor. This causes some pixel rows in the recorded data to be slightly dimmer or brighter than they should be.
Miniscopes with version v4.40 and later will include the denoising hardware modification natively on their Rigid-Flex PCB so no additional denoising solution should be needed.
We have written a simple Miniscope Denoising Jupyter Notebook to walk users through the process of denoising their already recorded Miniscope videos. This notebook explains what it is doing and why it is doing it as well as provides visualizations of each step in the process.
This notebook also can change which codec and compression is used to re-save Miniscope data.
