Regional Brain Activity Estimation from M/EEG Data

Source Signal Imaging, Inc., San Diego CA

Investigators

Abstract

Ongoing development of multimodal functional neuroimaging has been fueling productive new lines of research, in basic systems neuroscience, clinical neurology and neuropsychiatry. The dominant modality, functional Magnetic Resonance Imaging (fMRI), which is based on the measurement of activity-related hemodynamic changes, has not attained the millisecond resolution required for imaging of fast neuroelectric activity. Magneto- and electro-encephalography (M/EEG) can achieve this temporal resolution, although with uncertain and variable spatial resolution. Our objective is to estimate fast neuroelectric activity in brain regions of interest (ROIs) from M/EEG, using a threshold based on calibrated signal discriminability and spatial resolution characteristics. ROIs may be obtained from structural or functional MRI data. We describe a new method, REGional Activity Estimation (REGAE), that differs substantially from existing methods of M/EEG source analysis. REGAE optimizes and calibrates the theoretical tradeoff between ROI signal discriminability and spatial resolution. These calibration curves permit the user to fine-tune a ROI signal detector for a specified decision criterion. The aims of this work are: (a) to implement REGAE prototype software, (b) to systematically characterize factors that influence REGAE discriminability and resolution, including sensor configuration, signal-to-noise ratio, and ROI location, and (c) to integrate REGAE with existing commercial EMSE Suite software (http://www.sourcesignal.com/sw-desc.htm). PROPOSED COMMERCIAL APPLICATION: The software and methods that we propose are non-invasive, non- radiological and relatively low cost addition to existing EEG, MEG and MRI systems, and provide information that is not currently available from these systems independently. The resulting software will have direct application in clinical and cognitive neuroscience research. If clinical value is demonstrated, systems based on this methodology may find applications in the areas of psychiatry, neurology and psychology.