Spatially uniform temporally flickering white noise is a powerful stimulus for early stages of the visual system, evoking spikes at specific times in the white noise sequence with high reliability and precision. Consequently, if the same white noise stimulus is presented repeatedly and the responses are aligned to the stimulus and displayed as a raster plot, the neural response literally resembles a barcode. Different neurons exhibit different barcodes in response to the same stimulus, reflecting their distinct spatiotemporal integration filters and intrinsic nonlinearities. There are a few examples in the literature, however, of the identical barcode showing up in different neurons even in different animals or different species. This inspired the idea that neurons might be classified according to their barcode patterns in response to some standard white noise stimulus.

However, it is not known whether neurons in visual cortical areas or in the superior colliculus will also be driven by spatially uniform white noise, or whether their responses will be barcode-like. Even in the dLGN, where barcodes have been observed before, it remains unknown whether dGN responses will be barcode-like in awake animals. Finally we have no idea how many such barcode classes there might be, how discrete or continuous the categories, or what fraction of neurons belong to an identifiable barcode class.

To answer all these questions, we asked the Allen Instute OpenScope project to present many repeats of a white noise stimulus to awake mice while recording throughout the brain with Neuropixels electrodes, targeting as many visually responsive cortical and subcortical brain areas as possible. In addition to spatially uniform white noise, the experiment also presented spatially static sinusoidal gratings whose contrast was modulated by the identical temporal white noise sequence.

The dataset is openly available here
An introductory Jupyter Noteook tour is available here
Code for our data analysis will eventually be released here