On the timescale of sensory processing, neuronal networks have relatively fixed anatomical connectivity, while functional interactions between neurons can vary depending on the ongoing activity of the neurons within the network. In a paper published in Nature Communications, a team of researchers, including School of Mathematics Assistant Professor Hannah Choi, hypothesizes that different types of stimuli could lead those networks to display stimulus-dependent functional connectivity patterns. The team analyzed single-cell resolution electrophysiological data from the Allen Institute, with simultaneous recordings of stimulus-evoked activity from neurons across 6 regions of the mouse visual cortex. The work reveals unexpected stimulus-dependence regarding the way groups of neurons interact to process incoming sensory information.