Marcel Weiss

Microstructural Parcellation of the Human Cerebral Cortex – From Brodmann's Post-Mortem Map to in vivo Mapping with High-Field Magnetic Resonance Imaging

The year 2009 marked the 100th anniversary of the publication of the famous brain map of Korbinian Brodmann. Although a “classic” guide to microanatomical parcellation of the cerebral cortex, it is – from todays state-of-the-art neuroimaging perspective – problematic to use Brodmanns map as a structural guide to functional units in the cortex. In this article we discuss some of the reasons, especially the problematic compatibility of the “post-mortem world” of microstructural brain maps with the “in vivo world” of neuroimaging. We conclude with some prospects for the future of in vivo structural brain mapping: a new approach which has the enormous potential to make direct correlations between microstructure and function in living human brains: “in vivo Brodmann mapping” with high-field magnetic resonance imaging.

Anatomically motivated modeling of cortical laminae.

Improvements in the spatial resolution of structural and functional MRI are beginning to enable analysis of intracortical structures such as heavily myelinated layers in 3D, a prerequisite for in-vivo parcellation of individual human brains. This parcellation can only be performed precisely if the profiles used in cortical analysis are anatomically meaningful. Profiles are often constructed as traverses that are perpendicular to computed laminae. In this case they are fully determined by these laminae. The aim of this study is to evaluate models for cortical laminae used so far and to establish a new model. Methods to model the laminae used so far include constructing laminae that keep a constant distance to the cortical boundaries, so-called equidistant laminae. Another way is to compute equipotentials between the cortical boundary surfaces with the Laplace equation. The Laplace profiles resulting from the gradients to the equipotentials were often-used because of their nice mathematical properties. However, the equipotentials these Laplacian profiles are constructed from and the equidistant laminae do not follow the anatomical layers observed using high resolution MRI of cadaver brain. To remedy this problem, we introduce a novel equi-volume model that derives from work by Bok (1929). He argued that cortical segments preserve their volume, while layer thickness changes to compensate cortical folding. We incorporate this preservation of volume in our new equi-volume model to generate a three-dimensional well-adapted undistorted coordinate system of the cortex. When defined by this well-adapted coordinate system, cortical depth is anatomically meaningful. We compare isocontours from these cortical depth values to locations of myelinated bands on high-resolution ex-vivo and in-vivo three-dimensional MR images. A similar comparison was performed with equipotentials computed with the Laplace equation and with equidistant isocontours. A quantitative evaluation of the equi-volume model using measured image intensities confirms that it provides a much better fit to observed cortical layering.

A computational framework for ultra-high resolution cortical segmentation at 7 Tesla

This paper presents a computational framework for whole brain segmentation of 7Tesla magnetic resonance images able to handle ultra-high resolution data. The approach combines multi-object topology-preserving deformable models with shape and intensity atlases to encode prior anatomical knowledge in a computationally efficient algorithm. Experimental validation on simulated and real brain images shows accuracy and robustness of the method and demonstrates the benefits of an increased processing resolution.

Diffusion tensor imaging segments the human amygdala in vivo

The amygdala plays an important role in emotion, learning, and memory. It would be highly advantageous to understand more precisely its internal structure and connectivity for individual human subjects in vivo. Earlier cytoarchitectural research in post-mortem human and animal brains has revealed multiple subdivisions and connectivity patterns, probably related to different functions. With standard magnetic resonance imaging (MRI) techniques, however, the amygdala appears as an undifferentiated area of grey matter. Using high-quality diffusion tensor imaging (DTI) at 3 Tesla, we show diffusion anisotropy in this grey matter area. Such data allowed us to subdivide the amygdala for the first time in vivo. In 15 living subjects, we applied a spectral clustering algorithm to the principal diffusion direction in each amygdala voxel and found a consistent subdivision of the amygdala into a medial and a lateral region. The topography of these regions is in good agreement with the fibre architecture visible in myelin-stained sections through the amygdala of a human post-mortem brain. From these in vivo results we derived a probabilistic map of amygdalar fibre orientations. This segmentation technique has important implications for functional studies in the processing of emotions, cognitive function, and psychiatric disorders and in studying morphometry and volumetry of amygdala subdivisions.

Optimizing T1-weighted imaging of cortical myelin content at 3.0 T

With increases in the sensitivity and resolution of anatomical MRI for the brain, methods for mapping the organization of the cerebral cortex by imaging its myelin content have emerged. This identifies major sensory and motor regions and could be used in studies of cortical organization, particularly if patterns of myelination can be visualized over the cortical surface robustly in individual subjects. The imaging problem is difficult, however, because of the relative thinness of the cerebral cortex and the low intracortical tissue contrast. In this paper, we optimize the contrast of T(1)-weighted MRI to help better visualize patterns of myelination. We measure a small but statistically significant difference in T(1) of 171 ± 40 ms between cortical regions with low and high myelin contents in the human cortex at 3T, and then perform simulations to choose parameters for an inversion-recovery pulse sequence that utilizes this T(1) difference to increase contrast within the cortex. We show that lengthening the delay between signal acquisition and the next inversion pulse in the sequence increases intracortical contrast more effectively than does image averaging. Using the optimized sequence, we show that major myelinated regions that are relatively thick, such as the primary motor and auditory regions, can be visualized well in individuals at 3T using whole-cortex 3D images made at 1mm isotropic resolution, while thinner regions, such as the primary visual cortex, can be visualized using targeted 3D images made at 0.5mm isotropic resolution. Our findings demonstrate that patterns of myelination can be better visualized in individual subjects when the imaging is optimized to highlight intracortical contrast and can help to pave the way for the creation of matched maps of microanatomy and function in the cortex of living individual humans.

High-resolution MRI and diffusion-weighted imaging of the human habenula at 7 tesla

To investigate the feasibility of discriminating the habenula in human brain using high‐resolution structural MRI and diffusion‐weighted imaging at 7 Tesla (T).

A gradual increase of iron toward the medial‐inferior tip of the subthalamic nucleus

The subthalamic nucleus (STN) is an important node of the cortico‐basal ganglia network and the main target of deep brain stimulation (DBS) in Parkinsons disease. Histological studies have revealed an inhomogeneous iron distribution within the STN, which has been related to putative subdivisions within this nucleus. Here, we investigate the iron distribution in more detail using quantitative susceptibility mapping (QSM), a novel magnetic resonance imaging (MRI) contrast mechanism. QSM allows for detailed assessment of iron content in both in vivo and postmortem tissue. Twelve human participants and 7 postmortem brain samples containing the STN were scanned using ultra‐high field 7 Tesla (T) MRI. Iron concentrations were found to be higher in the medial‐inferior tip of the STN. Using quantitative methods we show that the increase of iron concentration towards the medial‐inferior tip is of a gradual rather than a discrete nature. Hum Brain Mapp 35:4440–4449, 2014.

Mapping of the internal structure of human habenula with ex vivo MRI at 7T

The habenula is a small but important nucleus located next to the third ventricle in front of the pineal body. It helps to control the human reward system and is considered to play a key role in emotion, showing increased activation in major depressive disorders. Its dysfunction may underlie several neurological and psychiatric disorders. It is now possible to visualize the habenula and its anatomical subdivisions—medial habenula (MHB) and lateral habenula (LHB)—using MR techniques. The aim of this study was to further differentiate substructures within human lateral habenula (LHB) using ex vivo ultra-high field MR structural imaging, distinguishing between a medial part (m-LHB) and a lateral part (l-LHB). High resolution T1w images with 0.3-mm isotropic resolution and T2*w images with 60-micrometer isotropic resolution were acquired on a 7T MR scanner and quantitative maps of T1 and T2* were calculated. Cluster analysis of image intensity was performed using the Fuzzy and Noise Tolerant Adaptive Segmentation Method (FANTASM) tool. Ultra-high resolution structural MRI of ex vivo brain tissue at 7T provided sufficient SNR and contrast to discriminate the medial and lateral habenular nuclei. Heterogeneity was observed in the lateral habenula (LHB) nuclei, with clear distinctions between lateral and medial parts (m-LHB, l-LHB) and with the neighboring medial habenula (MHB). Clustering analysis based on the T1 and T2* maps strongly showed 4–6 clusters as subcomponents of lateral and medial habenula.

A geometric morphometric relationship predicts stone flake shape and size variability

The archaeological record represents a window onto the complex relationship between stone artefact variance and hominin behaviour. Differences in the shapes and sizes of stone flakes—the most abundant remains of past behaviours for much of human evolutionary history—may be underpinned by variation in a range of different environmental and behavioural factors. Controlled flake production experiments have drawn inferences between flake platform preparation behaviours, which have thus far been approximated by linear measurements, and different aspects of overall stone flake variability (Dibble and Rezek J Archaeol Sci 36:1945–1954, 2009; Lin et al. Am Antiq 724–745, 2013; Magnani et al. J Archaeol Sci 46:37–49, 2014; Rezek et al. J Archaeol Sci 38:1346–1359, 2011). However, when the results are applied to archaeological assemblages, there remains a substantial amount of unexplained variability. It is unclear whether this disparity between explanatory models and archaeological data is a result of measurement error on certain key variables, whether traditional analyses are somehow a general limiting factor, or whether there are additional flake shape and size drivers that remain unaccounted for. To try and circumvent these issues, here, we describe a shape analysis approach to assessing stone flake variability including a newly developed three-dimensional geometric morphometric method (‘3DGM’). We use 3DGM to demonstrate that a relationship between platform and flake body governs flake shape and size variability. Contingently, we show that by using this 3DGM approach, we can use flake platform attributes to both (1) make fairly accurate stone flake size predictions and (2) make relatively detailed predictions of stone flake shape. Whether conscious or instinctive, an understanding of this geometric relationship would have been critical to past knappers effectively controlling the production of desired stone flakes. However, despite being able to holistically and accurately incorporate three-dimensional flake variance into our analyses, the behavioural drivers of this variance remain elusive.