Spatial-temporal analysis of non-stationary fMEG data.

Magnetoencephalography (MEG) is a technique used to non-invasively record neuromagnetic fields generated by the human brain. Our new SARA (SQUID Array for Reproductive Assessment) is a unique MEG device designed specifically for the study of the fetal neurophysiology. During the acquistion of fetal magnetoencephalography (fMEG), many other interfering bio-magnetic signals are collected as well. Examples include the movement of fetus or muscle contraction of the mother. As a result, the recorded signals may show unexpected patterns, other than the target signal of interest. These interventions makes it difficult for a physician to assess the exact fetal condition, including its response to various stimuli. We propose using intervention analysis and spatial-temporal autoregressive moving average (STARMA) modeling to address the problem. STARMA is a statistical method that examines the relationship between the current observations as a linear combination of past observations, as well as observations at neighboring sites. Through intervention analysis, the change in pattern due to interfering signals can be well accounted for. When these interferences are removed, the end product is a template time series, or a typical signal from the target of interest thus providing a more reliable means to monitor the actual signals generated by the fetal brain and other organs of interest.