Research

Structural MRI

Neurodegenerative and psychiatric disorders are frequently associated with structural changes in the brain. These changes can cause alterations in the imaging properties of brain tissue, as well as result in variations in morphometric properties of the brain such as volume, folding, and surface area. In the past three decades, the classical correlations based on post mortem examination have been confirmed, modified, and extended using in vivo imaging methods, first using CT and now structural MRI. Increasingly, structural analysis has moved from visual description to objective quantification. However, quantification has generally been time consuming and difficult due to the 3D folding patterns of the cortex, and the overall complexity of cerebral anatomy. Consistency between observers requires extensive training and high expertise. Recently, automated quantification of cerebral anatomy has become possible, following from automated labeling, or "segmentation", of the 3D anatomy including subcortical structures, as well as from automated reconstruction and labeling, or "parcellation", of the cortical surface.

With the advent of diffusion tensor imaging (DTI), non-invasive quantification of fiber tracts in the human brain has become possible. Multi-compartment diffusion MRI models permit more extensive characterization of brain gray and white matter than DTI. These techniques can be used to identify diffusion signal associated with cellular changes, such as demyelination or the loss of neurons, axon or dendrites, that occur with aging or disease.

We develop state-of-the art tools for anatomical segmentation and quantitative analysis based on structural MRI data. This includes optimized protocols and procedures for MRI acquisition, distortion correction, segmentation of intra- and extra-cranial anatomical structures, and Quality Control of both raw and processed image data.

Functional MRI/EEG/MEG

Human brain function can be probed non-invasively by measuring the minute currents produced by active neurons using electroencephalography (EEG) and magnetoencephalography (MEG). Neuronal activity also results in localized changes in blood oxygenation and flow, which can be measured using functional magnetic resonance imaging (fMRI). The development of fMRI has enabled imaging of task-related brain activation, with good spatial resolution to within a few hundred microns in normal subjects. Similarly, advances in MEG and high-density EEG have enabled estimation of brain activity with temporal resolution on the order of milliseconds. However, each of these signal modalities is limited either in terms of its temporal or spatial resolution. Hence, high-resolution spatiotemporal imaging of brain activity requires integration of information from multiple signal modalities.

We aim to facilitate combining the spatial resolution of fMRI and the temporal resolution of MEG/EEG concurrently within advanced source localization computational models. Knowledge of the spatio-temporal distribution of human brain activity during cognition would fulfill a basic goal of human neuroscience. Applied to patient groups, integrated fMRI/EEG/MEG computational source modeling will provide the highest level of spatiotemporal resolution possible with non-invasive measures.

Neurovascular Coupling & Physiological Basis for Functional Neuroimaging

One of our major research interests is neurovascular coupling and neuronal correlates of non-invasive fMRI signals. To this end, we combine a suite of technologies including fMRI, optical brain imaging of intrinsic (hemodynamic) signals, voltage-sensitive dyes imaging, calcium-sensitive dyes imaging, 2-photon microscopy and electrophysiological recordings to measure neuronal and vascular activity in animal models.

Recent advances in noninvasive imaging methods, in particular fMRI and MEG, have led to an enormous growth in our ability to measure and visualize the structure and function of the working human brain in vivo in response to a wide variety of sensory and cognitive tasks and manipulation. However, due to the poorly understood nature of the coupling between the imaging signals and the underlying physiological and biophysical mechanisms, the analysis and interpretation of such data has so far been largely correlational and descriptive. We aim to bridge this critical gap in our understanding, by developing and validating an integrative model linking neuronal to vascular activation, and different levels of brain activity. Specifically, we 1) characterize the spatial and temporal aspects of coupling between neuronal electrical activity and hemodynamic/metabolic physiological measures using advanced imaging techniques; and 2) relate imaging signals to the underlying physiological processes at the microscopic and mesoscopic levels through mechanistic models that incorporate detailed structural reconstructions of neuronal and vascular architecture.

Blood-brain Barrier Permeability MRI

Neurovascular dysfunction can occur with aging or disease and may disrupt normal brain function by damaging the blood-brain barrier. As breakdown of the blood-brain barrier may be a contributing factor to or result of many conditions, including dementia, stroke, or multiple sclerosis, measuring blood-brain barrier permeability can improve our understanding of neurological disorders and potentially guide avenues for therapeutic intervention.

We have developed a permeability MRI technique that images the dynamic passage of an injected contrast agent from the blood to brain tissue. This approach is currently being used to localize regions of blood-brain barrier leakage in patients with cognitive impairment and is being expanded to applications in other neurological disorders.