Imaging Brain Function and Structure Using MRI
Office Phone: (608) 263-1685
My research lab focuses on the field of magnetic resonance imaging (MRI)
of the human brain. The general theme of our work is clinical
neuroscience. Our goal is the development and application of new MR
methods to visualize the structure and function of the brain and to
translate these methods to the hospital for clinical diagnosis. One of
the areas upon which we concentrate our research is functional MRI
(fMRI). FMRI allows us to noninvasively visualize both the temporal and
spatial patterns of brain activity in response to different stimuli.
In addition to analyzing brain activation, we are also developing
techniques to explore brain connectivity using diffusion tensor imaging
(DTI). As implemented in MRI, DTI is a noninvasive imaging technique
that can be used to probe the intrinsic diffusion characteristics of
tissue. Brain tissue where diffusion is restricted or anisotropic (white
matter) will appear at a different level of brightness in a DTI image
than tissue with isotropic diffusion (gray matter). As a result, DTI is
extremely useful for providing exquisitely detailed in vivo maps of
major white matter fiber pathways. Techniques for diffusion imaging are
evolving rapidly. Diffusion MRI research has been shown to have
important applications, especially in stroke, the effects of tumors,
degenerative diseases and brain injury.
Effective connectivity describes the integration within and between
functionally specialized areas of the brain. Regions of the brain are
located using fMRI. Integration of these regions is achieved through the
information gained from DTI. We explore the effective connectivity in a
variety of large-scale neurocognitive networks using different modeling
We apply all of these methods to a variety of patient populations
including: epilepsy, coma, brain tumors, schizophrenia, Alzheimer’s
disease and Parkinson’s disease.
- McMillan, K.M., A.R. Laird, S.T. Witt, M.E. Meyerand. 2007. Self-paced working memory: validation of verbal variations of the n-back paradigm. Brain Reseach 1139: 133-142.
- McMillan, K.M., B.P. Rogers, C.G. Koay, A.R. Laird, R.R. Price, M.E. Meyerand. 2007. An objective method for combining multi-parametric MRI datasets to characterize malignant tumors. Medical Physics 34: 1053-1061.
- Johnson S.C., T.W. Schmitz, C.H. Moritz, M.E. Meyerand, H.A. Rowley, A.L. Alexander, K.W. Hansen, C.E. Gleason, C.M. Carlsson, M.L. Ries, S. Asthana, K. Chen, E.M. Reiman, G.E. Alexander. 2006. Activation of Brain Regions Vulnerable to Alzheimer;s Disease: The Effect of Mild Cognitive Impairment. Neurobiology of Aging 27:1604-12.
- Moritz, C.H., J.D. Carew, A.B. McMillan, and M.E. Meyerand. 2005. Independent component analysis applied to self-paced functional MR imaging paradigms. NeuroImage 25: 181-192.
- McMillan, A.B., B.P. Hermann, S.C. Johnson, R.R. Hansen, M. Seidenberg, and M.E. Meyerand. 2004. Voxel-based morphometry of unilateral temporal lobe epilepsy reveals abnormalities in cerebral white matter. NeuroImage 23: 167-174.
- Moritz, C.H. and M.E. Meyerand. 2003. Power spectrum ranked independent component analysis of a periodic fMRI complex motor paradigm. Hum. Brain Mapp. 18: 111-122.
- Witwer, B.P., R. Moftakhar, K. Hasan, P. Deshmukh, K. Arfanakis, V. Haughton, H. Rowley, A. Field, J. Noyes, C. Moritz, M.E. Meyerand, A. Alexander, and B. Badie. 2002. Diffusion tensor imaging of white matter tracts in patients with cerebral neoplasms. J. Neurosurg. 97: 568-575.
- Arfanakis, K., B. Hermann, V. Haughton, J.D. Carew, B.P. Rogers, and M.E. Meyerand. 2002. Diffusion tensor MRI in temporal lobe epilepsy. Magnetic Resonance Imaging 20: 511-519.
- Moritz, C., V. Haughton, D. Cordes, M. Quigley, and M.E. Meyerand. 2000. Whole-brain functional MRI activation from a finger tapping task examined with independent component analysis. AJNR. 21: 1628-1635.