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ZETA benchmarking neuropixels data

Citation

Montijn, Jorrit (2020), ZETA benchmarking neuropixels data, Dryad, Dataset, https://doi.org/10.5061/dryad.6djh9w108

Abstract

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.

Methods

Data were recorded using SpikeGLX and pre-processed with Kilosort2. More information can be found here: https://www.biorxiv.org/content/10.1101/2020.09.24.311118v1.

Usage Notes

Each data file contains a separate recording. The data structure is as follows:

sAP – main structure containing the following fields:

 

sAP.sMetaNI – National Instruments and SpikeGLX metadata

sAP.vecChannelDepth – Depth in microns per channel

sAP.vecBregmaCoords – Coordinates of Bregma

sAP.cellStim – Stimulus data (see below)

sAP.sCluster – Single cluster data (see below)

 

sAP.cellStim – cell array, with each cell corresponding to a separate stimulus presentation block. Each block i contains two variables:

 

cellStim{i}.sParamsSGL – SpikeGLX metadata

cellStim{i}.structEP – Stimulus data. The most important variables are:

structEP.strFile – Source file identifier; “RunDriftingGratings” or “RunNaturalMovie”

structEP.vecStimOnTime – Timestamps for stimulus onsets

structEP.vecStimOffTime – Timestamps for stimulus offsets

structEP.Orientation – Stimulus orientation (if drifting grating)

 

In case of a natural movie, the movie loops every 20 seconds and is presented at 60Hz.

 

sAP.sCluster – structure array, with each structure corresponding to a single cluster. Each structure j contains several variables, of which the following are most important:

 

.Area – Brain area in which this cluster was found

.SpikeTimes – Spikes synchronized to structEP timestamps

.Contamination Spike contamination to determine whether to include this cluster in further analyses

.KilosortGood – Boolean indicating whether Kilosort determined this cluster to be of sufficient quality

 

Default inclusion criteria were: (KilosortGood == 1) OR (Contamination < 0.1).