Online detection of low-frequency functional connectivity

Synchronized oscillations in resting state timecourses have been detected in recent fMRI studies. These oscillations are low frequency in nature (< 0.08 Hz), and seem to be a property of symmetric cortices. These fluctuations are important as a potential signal of interest, which could indicate connectivity between functionally related areas of the brain. It has also been shown that the synchronized oscillations decrease in some spontaneous pathological states (such as cocaine injection). Thus, detection of these functional connectivity patterns may help to serve as a gauge of normal brain activity. Currently, functional connectivity detection is applied only in offline post-processing analysis. Online detection methods have been applied to detect task activation in functional MRI. This allows real-time analysis of fMRI results, and could be important in detecting short-term changes in functional states. In this work, we develop an online algorithm to detect low frequency resting state functional connectivity in real time. This will extend connectivity analysis to allow online detection of changes in “resting state” brain networks.