BrainVoyager QX v2.8
Overview Of Sub-Millimeter MRI Data Analysis
In recent years, interest in anatomical and functional MRI data with very high spatial resolution has increased, especially for data measured with ultra-high field (UHF) MRI scanners. These devices allow to obtain images with sub-millimeter resolution that can be used for "mesoscopic" brain imaging targeting cortical layers and cortical columns. In BrainVoyager QX, a set of tools has been made available that extent standard tools to be applicable for high-resolution data. More importantly, new tools have been developed that allow to perform new analyses that are unique to sub-millimeter data.
One issue with UHF MRI data is that intensity inhomogeneities in T1-weighted data are much stronger than on 3 Tesla scanners. To cope with these issues, a proton-density based estimation technique has been implemented that largely corrects these inhomogeneities.
The creation of volume time course (VTC) data from original functional FMR data sets has been adjusted to properly handle functional data with sub-millimeter resolution. A new approach has also been implemented that creates VTC files without changing the voxel time course data in FMR-STC data. In this approach, the FMR data is transformed in FMR-VTC space, which is essentially the original FMR-STC space with some 90-degree rotations to adjust to the sagittal orientation of VMR space. The advantage of this FMR-VTC space is that it allows to run VTC space analysis tools (e.g. MVPA, grid sampling) without the necessity to resample the original data (even in case of non-iso voxels). The disadvantage of this approach is that the data can not be analyzed at the group level using standard normalized space since no transformation in Talairach space is performed. Other forms of group-level analyses (e.g MVPA accuracies, ROI analyses) can, of course, be applied.
Because of its high spatial resolution, UHF MRI data allows to look inside the intrinsic organization of the cortex. In order to enable sampling functional data at different cortical depth levels, two approaches are availabe. One works with high-resolution - but otherwise regular - cortex meshes that are reconstructed at different relative cortical depth levels. A more advanced but only locally operating approach creates regular two-dimensional grids at different relative cortical depth levels. The latter approach has been successfully used to map the columnar organization in specialized brain areas as well as to separate functional data from different cortical layers.
Copyright © 2014 Rainer Goebel. All rights reserved.