Autocorrelation of the fMRI signal dynamically changes during different brain states

The autocorrelation (AC) of fMRI signal is affected by brain function and state. We used fMRI data acquired during working memory, mathematical computation, visual attention, and rest, and showed that the AC signal of gray matter dynamically changes across different task blocks. The dynamic AC (dAC) can be used to estimate brain-state changes with high accuracy. Classifier accuracy is correlated with the task performance; Subjects with better task performance have better accuracy in the dAC-based brain state classification. This study shows that the AC of the fMRI signal over time dynamically changes by the cognitive processes.