Translating large-scale brain imaging technologies into deployable mobile technologies

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Brain wave technologies such as electroencephalography (EEG) provide an online record of different brain functions. While this low-cost, portable technique has been tremendously useful in recording brain signals for single time point diagnostics at the scalp-level it is difficult to monitor the whole brain because using EEG alone to compute brain activity can be inaccurate. This makes it difficult to distinguish signals from different areas of the brain. At present, analysis and targeting of specific regions of the brain can be accomplished only using expensive, access-limited neuroimaging devices such as functional MRI (fMRI) and magnetoencephalography (MEG) combined with anatomical MRI scans. Even though, EEG and MEG signals originate from the same neurophysiological processes, there are important differences. Magnetic fields are less distorted than electric fields by the skull and scalp, which results in a better spatial resolution of the MEG, allowing signals to be localized with more accuracy. The high cost and lack of portability of fMRI and MEG limits their use in point-of-care settings where portability or frequent imaging can benefit outcomes. Our research will develop software that uses the high spatial information from MEG, MRI and fMRI combined with EEG to find methods to extract EEG signals that have better spatial accuracy. These new techniques will enable EEG to be used to monitor the whole brain, which will open up new diagnostic avenues. These rapid imaging technologies have the advantage of reaching more people while providing individualized care. The ability for rapid imaging technologies to provide a reliable monitor of brain function change would provide considerable insight to guiding on-going treatment and rehabilitation of brain injury and related neurological conditions. For example, portable whole brain imaging can help athletes in high-risk-to-concussion sports by providing a means to do baseline testing before injury as well as provide assessments during recovery back to baseline after injury. The development of a novel monitoring device fulfills a growing need for “online” brain monitoring and will advance biomedical engineering and signal processing techniques by taking advantage of potential market segments that are not yet serviced.