Neuroanatomical prerequisites for language functions in the maturing brain

The 2 major language-relevant cortical regions in the human brain, Broca's area and Wernicke's area, are connected via the fibers of the arcuate fasciculus/superior longitudinal fasciculus (AF/SLF). Here, we compared this pathway in adults and children and its relation to language processing during development. Comparison of fiber properties demonstrated lower anisotropy in children's AF/SLF, arguing for an immature status of this particular pathway with conceivably a lower degree of myelination. Combined diffusion tensor imaging (DTI) data and functional magnetic resonance imaging (fMRI) data indicated that in adults the termination of the AF/SLF fiber projection is compatible with functional activation in Broca's area, that is pars opercularis. In children, activation in Broca's area extended from the pars opercularis into the pars triangularis revealing an alternative connection to the temporal lobe (Wernicke's area) via the ventrally projecting extreme capsule fiber system. fMRI and DTI data converge to indicate that adults make use of a more confined language network than children based on ongoing maturation of the structural network. Our data suggest relations between language development and brain maturation and, moreover, indicate the brain's plasticity to adjust its function to available structural prerequisites

Parametric spherical deconvolution: Inferring anatomical connectivity using diffusion MR imaging

3

The concurrence of cortical surface area expansion and white matter myelination in human brain development

The human brain undergoes dramatic structural changes during childhood that co-occur with behavioral development. These age-related changes are documented for the brain’s gray matter and white matter. However, their interrelation is largely unknown. In this study, we investigated age-related effects in cortical thickness (CT) and in cortical surface area (SA) as parts of the gray matter volume as well as age effects in T1 relaxation times in the white matter. Data from N = 170 children between the ages of 3 and 7 years contributed to the sample. We found a high spatial overlap of age-related correlations between SA and T1 relaxation times of the corresponding white matter connections, but no such relation between SA and CT. These results indicate that during childhood the developmental expansion of the cortical surface goes hand-in-hand with age-related increase of white matter fiber connections terminating in the cortical surface

A comparison of methods for the registration of tractographic fibre images

Diffusion tensor imaging (DTI) and tractography have opened up new avenues in neuroscience. As most applications require precise spatial localization of the fibre images, image registration is an important area of research. Registration is usually performed prior to tractography. However more reliable images could be produced if a viable registration can be performed post tractography. This study shows two available techniques for direct registration of fibre images and explores novel adaptations of these. The methods register volume images derived from the fibres, and reapply the transformation from these registrations to the fibre images. The first method is a local affine registration and the second is a global affine registration. The local affine method produced superior results

Beyond fractional anisotropy: Extraction of bundle-specific structural metrics from crossing fiber models

Diffusion MRI (dMRI) measurements are used for inferring the microstructural properties of white matter and to reconstruct fiber pathways. Very often voxels contain complex fiber configurations comprising multiple bundles, rendering the simple diffusion tensor model unsuitable. Multi-compartment models deliver a convenient parameterization of the underlying complex fiber architecture, but pose challenges for fitting and model selection. Spherical deconvolution, in contrast, very economically produces a fiber orientation density function (fODF) without any explicit model assumptions. Since, however, the fODF is represented by spherical harmonics, a direct interpretation of the model parameters is impossible. Based on the fact that the fODF can often be interpreted as superposition of multiple peaks, each associated to one relatively coherent fiber population (bundle), we offer a solution that seeks to combine the advantages of both approaches: first the fiber configuration is modeled as fODF represented by spherical harmonics and then each of the peaks is parameterized separately in order to characterize the underlying bundle. In this work, the fODF peaks are approximated by Bingham distributions, capturing first and second-order statistics of the fiber orientations, from which we derive metrics for the parametric quantification of fiber bundles. We propose meaningful relationships between these measures and the underlying microstructural properties. We focus on metrics derived directly from properties of the Bingham distribution, such as peak length, peak direction, peak spread, integral over the peak, as well as a metric derived from the comparison of the largest peaks, which probes the complexity of the underlying microstructure. We compare these metrics to the conventionally used fractional anisotropy (FA) and show how they may help to increase the specificity of the characterization of microstructural properties. While metric relying on the first moments of the Bingham distributions provide relatively robust results, second-order metrics representing the peak spread are only meaningful, if the SNR is very high and no fiber crossings are present in the voxel

Axon diameter measurements using diffusion MRI are infeasible

The feasibility of non-invasive axonal diameter quantification with diffusion MRI is a strongly debated topic due to the neuroscientific potential of such information and its relevance for the axonal signal transmission speed. It has been shown that under ideal conditions, the minimal diameter producing detectable signal decay is bigger than most human axons in the brain, even using the strongest currently available MRI systems. We show that resolving the simplest situations including multiple diameters is unfeasible even with diameters much bigger than the diameter limit. Additionally, the recently proposed effective diameter resulting from fitting a single value over a distribution is almost exclusively influenced by the biggest axons. We show how impractical this metric is for comparing different distributions. Overall, axon diameters currently cannot be quantified by diffusion MRI in any relevant way