Biography: My desire to understand how our brains control our behavior started when I was an undergraduate at Denison University in Granville, Ohio. I soon became interested in learning about how neural systems could be disrupted by disease and degeneration in humans. After college, I turned my attention to the neurobiology of autism, conducting research under the guidance of Martha Herbert and Verne Caviness at the Massachusetts General Hospital (MGH). During this time, I gained experience using a wide range of structural neuroimaging techniques. The possibilities that these sophisticated methods held for studying brain development and cognition in humans fascinated me and I found this work tremendously rewarding.

After several productive years at MGH, I enrolled as a graduate student in the Department of Brain and Cognitive Sciences at MIT. In my doctoral dissertation, under the mentorship of Suzanne Corkin, I studied how healthy aging affects brain anatomy and physiology and how these neural changes impact cognitive control processes. To pursue these questions, I took a multimodal neuroimaging approach, embracing structural MRI, DTI, fMRI, and MEG. I showed that the integrity of white matter pathways declines during the course of healthy aging, and that this decline is associated with diminished performance on tasks that engage prefrontal control networks (Ziegler et al., 2010. Neurobiol. Aging). In parallel, I used MEG to assess age-related changes in prestimulus somatosensory mu rhythms and applied a biophysically based computational model to predict the cellular mechanisms underlying these changes (Ziegler et al., 2010. Neuroimage). Building on these studies, I combined DTI, fMRI, and MEG to address the critical question of whether the degradation of white matter pathways in older adults interferes with the synchronized, oscillatory activity that is often observed when healthy young adults perform attention-demanding tasks (manuscript in review). These results are the first to document age-related changes in the modulation of top-down oscillatory activity in the context of visual search and suggest that these effects may be mediated by the strength of connections between frontal and parietal cortices.

Concurrent with these studies of healthy aging, I developed new multispectral MRI tools to visualize the substantia nigra and basal forebrain—a structure that includes the cholinergic nucleus basalis of Meynert. These structures are specifically affected by Parkinson’s disease pathophysiology, but are not readily detectable on standard T1-weighted images. By creating a weighted average of multiple MRI scans (T1-, T2-, T2-FLAIR-, and proton density-weighted), I was able to obtain a single volume with an optimized contrast-to-noise ratio tailored to the visualization of a particular structure. Application of these tools to MRI data from Parkinson’s patients and matched controls revealed a decrease in volumes of the basal forebrain and substantia nigra related to disease severity (manuscript in review). These tools provide new MRI-based biomarkers that are capable of detecting subcortical brain abnormalities in the early stages of Parkinson’s disease.