MEG-SIM: a web portal for testing MEG analysis methods using realistic simulated and empirical data

MEG and EEG measure electrophysiological activity in the brain with exquisite temporal resolution. Because of this unique strength relative to noninvasive hemodynamic-based measures (fMRI, PET), the complementary nature of hemodynamic and electrophysiological techniques is becoming more widely recognized (e.g., Human Connectome Project). However, the available analysis methods for solving the inverse problem for MEG and EEG have not been compared and standardized to the extent that they have for fMRI/PET. A number of factors, including the non-uniqueness of the solution to the inverse problem for MEG/EEG, have led to multiple analysis techniques which have not been tested on consistent datasets, making direct comparisons of techniques challenging (or impossible). Since each of the methods is known to have their own set of strengths and weaknesses, it would be beneficial to quantify them. Toward this end, we are announcing the establishment of a website containing an extensive series of realistic simulated data for testing purposes ( http://cobre.mrn.org/megsim/ ). Here, we present: 1) a brief overview of the basic types of inverse procedures; 2) the rationale and description of the testbed created; and 3) cases emphasizing functional connectivity (e.g., oscillatory activity) suitable for a wide assortment of analyses including independent component analysis (ICA), Granger Causality/Directed transfer function, and single-trial analysis.

Different strategies for auditory word recognition in healthy versus normal aging

To explore the effects of commonly encountered pathology on auditory recognition strategies in elderly participants, magnetoencephalographic (MEG) brain activation patterns and performance were examined in 30 elderly [18 controls and 12 elderly with mild cognitive impairment (MCI) or probable Alzheimer's disease (AD)]. It was predicted that participants with known pathology would reveal different networks of brain activation, compared to healthy elderly, which should correlate with poorer performance. Participants heard a list of words representing common objects, twice. After 20 minutes a list of new and old words was presented and participants judged whether each word was heard earlier. MEG responses were analyzed using a semiautomated source modeling procedure. A cluster analysis using all subjects' MEG sources revealed three dominant patterns of activity which correlated with IQ and task performance. The highest performing group revealed activity in premotor, anterior temporal, and superior parietal lobes with little contribution from prefrontal cortex. Performance and brain activation patterns were also compared for individuals with or without abnormalities such as white matter hyperintensities and/or volume reduction evidenced on their MRIs. Memory performance and activation patterns for individuals with white matter hyperintensities resembled the group of MCI/AD patients. These results emphasize the following: (1) general pathology correlates with cognitive decline and (2) full characterization of the health of elderly participants is important in studies of normal aging since random samples from the elderly population are apt to include individuals with subclinical pathology that can affect cognitive performance.