Measuring the Spatial Scale of Brain Representations

Abstract

Understanding how the brain encodes information is one of the core questions in cognitive neuroscience. This question has been tackled by measuring finegrained fMRI activity patterns across voxels, termed brain representations. These measured representations likely capture gross variations in activity across functional sub-regions, which are reflected in patterns of low spatial frequency. However, it is unclear whether patterns that are not driven by functional/anatomical structure (and are therefore expected to contain higher spatial frequencies) also contribute to these representations. Such rugged patterns have the potential to reflect more intricate stimulus-related information. Here we present a novel method for separating the highfrom the low-frequency patterns, and evaluating whether these patterns contain reliable information. By relying on cross-subject temporal synchronization of brain activity and within-subject consistency of activity patterns, our method provides evidence that, at least in sensory brain regions, highfrequency patterns hold reliable information. Using the same method we also demonstrate that many of these activity patterns are unique to each individual. These results demonstrate the potential of our novel method to shed new light on the types of information conveyed by brain representation.