B.S.  Physics	UCSC	1994
Ph.D. Biomedical Physics	UCLA	2002

I am interested in how to best integrate EEG and fMRI data to investigate neuropsychological and neurocognitive questions, ultimately to examine relationships of brain-mind-body connections to illness and health. As my doctoral dissertation at UCLA, I developed a system for acquiring EEG during functional MRI (Simultaneous Imaging for Tomographic Electrophysiology, or SITE) and used it to localize potential generators of the alpha rhythm in normal subjects during rest. I am now expanding this prototype system, and am developing single-trial analysis techniques for integration of these multi-modal data sets in order to truly utilize the high temporal and spatial resolution of SITE. With these techniques, I am examining changes in cognition with aging using memory and novelty paradigms in both young and old subjects, am investigating variability in neural processing during visual perception, and am continuing to study variations in the normal resting state.

Research Project with the LIINC Lab: The overall goal of this project is to develop an integrated single-trial system for neuroimaging that combines high-density electroencephalography (EEG) with simultaneous functional magnetic resonance imaging (fMRI), and to use this system to investigate variability in neural processing. The high-temporal resolution of EEG will enable the detection of signal variability in single-trial events, and this information will be used as the input function for analysis of simultaneously acquired event-related fMRI (efMRI). We hypothesize that using single-trial EEG derived regressors for efMRI (stEEG/fMRI) will yield high spatial and high temporal resolution information about the functional neuroanatomy involved in cognitive processing.  This will enable construction of unique EEG derived fMRI activation maps that are not based on pre-defined labels or observed behavioral responses but rather on task and subject specific electrophysiological source variability. The broad impact of this work will be development of a new non-invasive imaging system (stEEG/fMRI) for the cognitive neurosciences as well as a clinical tool for diagnosis and monitoring of a broad spectrum of neurological diseases.

We are currently building a high density (64 channels) EEG/fMRI integrated system for single-trial analysis, and are characterizing possible differences between the EEG recorded in an MR environment and that recorded in a standard environment. Following this, we will demonstrate the use of stEEG/fMRI in a pilot study of cognitive aging. The aims for this study are:

1. Use single-trial EEG-derived regressors, constructed via supervised machine learning, to construct efMRI activation maps (stEEG/fMRI activation maps) for auditory oddball and Eriksen flanker tasks.

 

2. Use alpha power as a complementary regressor within stEEG/fMRI for capturing additional single-trial variance in the hemodynamic response.

 

3. Demonstrate that stEEG/fMRI activation maps yield new information for discriminating young and old adult populations, as compared to traditional fMRI (event related or block design) and ERP (P3 and ERN) analysis.