Project abstract for group limko

White Matter Abnormalities in Brain Disorders

The objective of this continuing study is to examine structural neuroimaging metrics and neurocognitive assessments within several populations with brain disorders including schizophrenia, fetal alcohol spectrum disorders, pediatric traumatic brain injury, myotonic dystrophy, binge-eating disorder, Parkinson's disease, Alzheimer's disease, mild cognitive impairment, cocaine users, and also drug users who are currently abstinent and enrolled in a drug-treatment program. All of these studies also recruit matched control subjects. The researchers are examining these subjects’ white matter microstructure and fiber connectivity in a variety of ways. The researchers are also studying brain morphometrics using the automated brain segmentation software FreeSurfer, which can be used to generate volumes of neuroanatomical regions, segment white matter and gray matter from surrounding tissues, and compute the thickness of the cerebral cortex across the brain. For one major analysis the researchers combine the FreeSurfer anatomical information with their white-matter metrics to obtain valuable information about the brain’s long-range connectivity patterns. The FreeSurfer anatomical regions are used as seeds and targets. The white matter is prepared using and FMRIB Software Library’s (FSL) Bedpost (Bayesian Estimation of Diffusion Parameters Obtained using Sampling Techniques) program. After this, FSL’s Probtrack program is run using the Freesurfer seeds/targets. All of these programs are very computationally intensive and take many hours per subject. The researchers have also begun to take advantage of TRACULA to provide comprehensive tractography for all of their datasets. They are expanding our processing techniques to better handle accommodate multi-band MR images. Multi-band images are able to processed in a way that better utilizes a parallel computing environment than traditional MR images, but these images ultimately consume more overall CPU time as the images are of higher resolution. 

A bibliography of this group’s publications acknowledging MSI is attached.