Abstract
A pervasive yet puzzling feature of cortical circuits is that despite their complex wiring, population-wide shared spiking variability is low dimensional. Neuronal variability is often used as a probe to understand how recurrent circuitry supports network dynamics. However, current models cannot internally produce low dimensional shared variability, and rather assume that it is inherited from outside the circuit. We analyze population recordings from the visual pathway where directed attention differentially modulates shared variability within and between areas, which is difficult to explain with externally imposed variability. We show that if the spatial and temporal scales of inhibitory coupling match physiology, network models capture the low dimensional shared variability of our population data. Our theory provides a critical link between measured cortical circuit structure and recorded population activity.
One Sentence Summary Circuit models with spatio-temporal excitatory and inhibitory interactions generate population variability that captures recorded neuronal activity across cognitive states.