Other_analysis_methods

Tutorial

This brief tutorial specifically covers Neuropixels Phase3A data in Matlab, and in some cases specifically for files recorded with SpikeGLX and/or processed with Kilosort. But it will hopefully be useful also as a guide for other situations.

The code here is also contained in the exampleScript.m file of the spikes repository. You will also need the npy-matlab repository to load kilosort/phy files.

Loading kilosort/phy data easily

Kilosort output files can be loaded directly:

spikeTimes = readNPY('spike_times.npy');

But more convenient will be to load many of the relevant files quickly with one command:

myKsDir = 'C:\...\data\myKilosortOutputDirectory';
sp = loadKSdir(myKsDir)

sp.st are spike times in seconds, and sp.clu are cluster identities.

Spikes from clusters labeled "noise" have already been omitted.

Analyzing Drift

Because the Neuropixels probes sample densely of a long continuous span, movement of the brain relative to the electrode can be well detected and quantified. Methods to correct for it are under development.

To observe whether there was drift in your recording, a useful type of plot is the “driftmap”. Make sure to zoom in on the y-axis to look carefully. A drift of 20µm can move a neuron off your site, but the probe is 4mm long.

[spikeTimes, spikeAmps, spikeDepths, spikeSites] = ksDriftmap(myKsDir);
figure; plotDriftmap(spikeTimes, spikeAmps, spikeDepths);

Quantification of spiking amplitudes

Basic LFP characterization

Computing some useful properties of the spikes and templates

Loading synchronization data

Looking at PSTHs aligned to some event

Loading raw waveforms (or spike-triggered LFP, e.g.)