The ability to predict brain activity from words before they occur can be explained by information shared between neighbouring words, without requiring next-word prediction by the brain.
Detecting replay during longer time periods (e.g. resting state or sleep) with temporally delayed linear modeling (TDLM) requires biologically implausible event densities, and purely synthetic simulations substantially overestimate the method's sensitivity.
The phase of cortical activity, measured in the gray matter, is organized at multiple spatial scales, with the largest scales explaining most variance in phase at a given temporal frequency.
