ZETA benchmarking neuropixels data

Pre-processed matlab data files containing clustered spiking data of cells
recorded across various visually-responsive regions with Neuropixels. The
data can be accessed using the files provided at
https://github.com/JorritMontijn/ZETA_analysis_repository.
Neurophysiological studies depend on a reliable quantification of whether
and when a neuron responds to stimulation. Current methods to determine
responsiveness require arbitrary parameter choices, such as binning size.
These choices can change the results, which invites bad statistical
practice and reduces the replicability. Moreover, many methods only detect
mean-rate modulated cells. New recording techniques that yield
increasingly large numbers of cells would benefit from a test for
cell-inclusion that requires no manual curation. Here, we present the
parameter-free ZETA-test, which outperforms t-tests and ANOVAs by
including more cells at a similar false-positive rate. We show that our
procedure works across brain regions and recording techniques, including
calcium imaging and Neuropixels data. Furthermore, in illustration of the
method, we show in mouse visual cortex that 1) visuomotor-mismatch and
spatial location are encoded by different neuronal subpopulations; and 2)
optogenetic stimulation of VIP cells leads to early inhibition and
subsequent disinhibition.