Prior studies have demonstrated that correlated variability changes with cognitive processes that improve perceptual performance. We tested whether correlated variability covaries with subjects' performance-whether performance improves quickly with attention or slowly with perceptual learning. We found a single, consistent relationship between correlated variability and behavioral performance, regardless of the time frame of correlated variability change. This correlated variability was oriented along the dimensions in population space used by the animal on a trial-by-trial basis to make decisions. That subjects' choices were predicted by specific dimensions that were aligned with the correlated variability axis clarifies long-standing paradoxes about the relationship between shared variability and behavior.

Normalization, which divisively scales neuronal responses to multiple stimuli, is thought to underlie many sensory, motor, and cognitive processes. In every study where it has been investigated, neurons measured in the same brain area under identical conditions exhibit a range of normalization, ranging from suppression by nonpreferred stimuli (strong normalization) to additive responses to combinations of stimuli (no normalization). Normalization has been hypothesized to arise from interactions between neuronal populations, either in the same or different brain areas, but current models of normalization are not mechanistic and focus on trial-averaged responses. To gain insight into the mechanisms underlying normalization, we examined interactions between neurons that exhibit different degrees of normalization. We recorded from multiple neurons in three cortical areas while rhesus monkeys viewed superimposed drifting gratings. We found that neurons showing strong normalization shared less trial-to-trial variability with other neurons in the same cortical area and more variability with neurons in other cortical areas than did units with weak normalization. Furthermore, the cortical organization of normalization was not random: neurons recorded on nearby electrodes tended to exhibit similar amounts of normalization. Together, our results suggest that normalization reflects a neuron's role in its local network and that modulatory factors like normalization share the topographic organization typical of sensory tuning properties.