Large-scale neural recordings contain high-dimensional structure that cannot be easily captured by existing data visualization methods. We therefore developed an embedding algorithm called Rastermap, which captures highly nonlinear relationships between neurons, and provides useful visualizations by assigning each neuron to a location in the embedding space. Compared to standard algorithms such as t-SNE and UMAP, Rastermap finds finer and higher dimensional patterns of neural variability, as measured by quantitative benchmarks. We applied Rastermap to a variety of datasets, including spontaneous neural activity, neural activity during a virtual reality task, widefield neural imaging data during a 2AFC task, artificial neural activity from an agent playing atari games, and neural responses to visual textures. We found within these datasets unique subpopulations of neurons encoding abstract properties of the environment.

By continuously producing electrical signals, neurones are amongst the most energy-demanding cells in the organism. Resting ionic levels are restored via metabolic pumps that receive the necessary energy from oxygen supplied by blood vessels. Intense spontaneous neural activity is omnipresent in the developing CNS. It occurs during short, well-defined periods that coincide precisely with the timing of angiogenesis. Such coincidence cannot be random; there must be a universal mechanism triggering spontaneous activity concurrently with blood vessels invading neural territories for the first time. However, surprisingly little is known about the role of neural activity per se in guiding angiogenesis. Part of the reason is that it is challenging to study developing neurovascular networks in tri-dimensional space in the brain. We investigate these questions in the neonatal mouse retina, where blood vessels are much easier to visualise because they initially grow in a plane, while waves of spontaneous neural activity (spreading via cholinergic starburst amacrine cells) sweep across the retinal ganglion cell layer, in close juxtaposition with the growing vasculature. Blood vessels reach the periphery by postnatal day (P) 7-8, shortly before the cholinergic waves disappear (at P10). We discovered transient clusters of auto-fluorescent cells that form an annulus around the optic disc, gradually expanding to the periphery, which they reach at the same time as the growing blood vessels. Remarkably, these cells appear locked to the frontline of the growing vasculature. Moreover, by recording waves with a large-scale multielectrode array that enables us to visualise them at pan-retinal level, we found that their initiation points are not random; they follow a developmental centre-to-periphery pattern similar to the clusters and blood vessels. The density of growing blood vessels is higher in cluster areas than in-between clusters at matching eccentricity. The cluster cells appear to be phagocytosed by microglia. Blocking Pannexin1 (PANX1) hemichannels activity with probenecid completely blocks the spontaneous waves and results in the disappearance of the fluorescent cell clusters. We suggest that these transient cells are specialised, hyperactive neurones that form spontaneous activity hotspots, thereby triggering retinal waves through the release of ATP via PANX1 hemichannels. These activity hotspots attract new blood vessels to enhance local oxygen supply. Signalling through PANX1 attracts microglia that establish contact with these cells, eventually eliminating them once blood vessels have reached their vicinity. The auto-fluorescence that characterises the cell clusters may develop only once the process of microglial phagocytosis is initiated.