New tools and methods are needed to process and analyze brain activity in fast sampled fMRI data.
With MREG (magnetic resonance encephalography), an ultrafast fMRI sequence, it is possible to record activity of the whole brain with 10 Hz sampling rate and good spatial accuracy. BOLD fMRI resting state activity is clustered into resting state networks, from which the most active is the default mode network (DMN). Numerous mental diseases have been found to be related to DMN dysfunction.
High sampling rates enable to record physiological pulsations of the brain without aliasing, but this technique also produces large data sets. It is now possible to separate cardio-respiratory pulsations from fMRI recordings, and reveal short-term brain activity phenomena, such as activity avalanches in the DMN. We are working on characterization and quantification of short-term activity spreading in the brain.
Large data sets challenge data storage, and thus data compression and data access speed. We have achieved a thousand-fold random access speed-up of large fMRI recordings with the current compression standard, and we are working on introducing new compression techniques to improve analysis speed of MREG recordings.
Our work focuses on developing methods to interpret ultrafast fMRI recordings, in order to reveal details and properties of various mental diseases, and thus improve medical opportunities for individual patients in the future.
Last updated: 21.11.2016