Title: “Wire Loop Motion Sensor Optimization for Artifact Reduction in EEG-fMRI Recordings”
Laura Lewis, PhD – BME (Advisor, Chair)
David Boas, PhD – BME
Sam Ling, PhD – Psychological & Brain Sciences
The simultaneous use of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) has allowed for the improved characterization of neurological phenomena, combining the high spatial resolution of fMRI with the high temporal resolution of EEG. However, the artifacts observed in EEG during this combined recording method have posed a challenging problem. The high magnetic field creates these artifacts via Faraday's law of induction whenever the field shifts during imaging or when the subject moves in the scanner. In an attempt to reduce these artifacts, techniques involving external referential devices to record only the artifacts have been deployed. One such method, known as wire loop motion sensors, has been successful in regressing out noise, though there is still further to be explored with regard to their effectiveness at varying frequencies as well as whether increasing the number of loops and regressing based on proximity to sensors would yield further improvements. This thesis shows that utilizing an expanded geometrical arrangement of sensors enables improved artifact reduction, effective at 4, 7.5, 10, and 15Hz, without significantly impacting overall power. This work thus provides an approach to improve signal quality in simultaneous EEG-fMRI studies.