Abstracts

The ballistocardiogram (BKG) is a significant source of artifact in scalp EEG recorded in the static magnetic field characteristic of human MRI scanners. Multiple methods (averaging, ICA, adaptive filtering) have been successfully employed by others to reduce the BKG. A new method of identifying BKG is used to biologically characterize the BKG across multiple electrodes and subjects. Simultaneous EEG and fMRI recordings were made from twelve subjects. Greater than than ten hours of EEG containing BKG. EEG-fMRI was recorded in a 3 Tesla Siemens Allegra MR scanner using a Neuroscan (El Paso, TX) Synamps/2 amplifier and Maglink cap and cabling system with Scan 4.5 software. Standard 10/20 electrode positions were collected at a 20 kHz sampling rate and the gradient artifact greatly reduced with Scan 4.5 with decimation of the EEG signal to 500 Hz. 10-20 electrodes were referenced to a common electrode halfway between CZ and CPZ). Two additional processing steps were developed to reduce the BKG (Vincent, et al, Soc Neuroscience Abstracts 2005). First, a custom template based beat detector program, which identifies EKG patterns that represent single heart beats, was used to provide accurate triggering. Second, a moving general linear model was used to generate models of the BKG. The extracted BKG signal was characterized by standard averaging and forward FFT techniques. The BKG waveforms recovered by the GLM technique consistently included components outlasting the mean inter-beat interval in all (12/12) subjects and all 10-20 electrodes. Thus, as the waveforms due to successive beats inconsistently overlap, simple averaging cannot adequately characterize and reduce the BKG artifact. The BKG is large at 3 T. The positive to negative peak variation in the BKG is always more than 100 microvolts, and the largest components are most frequently several hundred microvolts in size in the O1-Ref electrode. The frequency content of the BKG is complicated. In addition to the frequency of the heart rate itself, bimodal peaks at 3-5 Hz and 8-10 Hz are present in the BKG, which contaminate frequency ranges needed to recover standard EEG. When the power spectral density of each electrode is averaged across subjects, the frequency bin with peak power varies over the scalp. BKG recorded at 3 Tesla represents a significant electrical signal that must be successfully removed to obtain EEG that represents brain activity. In addition to removing the BKG, biological characterization of the BKG across multiple subjects allows determination of the nature and variability of this signal. BKG itself is spatially variable in size and frequency content across the scalp. These observations constrain theoretical accounts of BKG origin, which presently remain incomplete. (Supported by K12NS01690 for John Zempel and NS06833 (laboratory of Marcus Raichle).)