Most genes’ expression variability is currently discarded as superfluous noise, because genes are not conceptualized as hubs within a largely interconnected and statistically co-dependent network. For this reason, important aspects of pluripotent cellular evolution are overlooked and not all genetic interactions included. We have recently developed new methods that afford the tracking of high dimensional spaces of the human and mouse transcriptomes, to better understand cells’ evolution and neuronal states as genes dynamically change states and cells reach their fate.