Subdivision of Broca's region based on individual-level functional connectivity.

Broca's region is composed of two adjacent cytoarchitectonic areas, 44 and 45, which have distinct connectivity to superior temporal and inferior parietal regions in both macaque monkeys and humans. The current study aimed to make use of prior knowledge of sulcal anatomy and resting-state functional connectivity, together with a novel visualization technique, to manually parcellate areas 44 and 45 in individual brains in vivo. One hundred and one resting-state functional magnetic resonance imaging datasets from the Human Connectome Project were used. Left-hemisphere surface-based correlation matrices were computed and visualized in brainGL. By observation of differences in the connectivity patterns of neighbouring nodes, areas 44 and 45 were manually parcellated in individual brains, and then compared at the group-level. Additionally, the manual labelling approach was compared with parcellation results based on several data-driven clustering techniques. Areas 44 and 45 could be clearly distinguished from each other in all individuals, and the manual segmentation method showed high test-retest reliability. Group-level probability maps of areas 44 and 45 showed spatial consistency across individuals, and corresponded well to cytoarchitectonic probability maps. Group-level connectivity maps were consistent with previous studies showing distinct connectivity patterns of areas 44 and 45. Data-driven parcellation techniques produced clusters with varying degrees of spatial overlap with the manual labels, indicating the need for further investigation and validation of machine learning cortical segmentation approaches. The current study provides a reliable method for individual-level cortical parcellation that could be applied to regions distinguishable by even the most subtle differences in patterns of functional connectivity.

Connexel visualization: a software implementation of glyphs and edge-bundling for dense connectivity data using brainGL.

The visualization of brain connectivity becomes progressively more challenging as analytic and computational advances begin to facilitate connexel-wise analyses, which include all connections between pairs of voxels. Drawing full connectivity graphs can result in depictions that, rather than illustrating connectivity patterns in more detail, obfuscate patterns owing to the data density. In an effort to expand the possibilities for visualization, we describe two approaches for presenting connexels: edge-bundling, which clarifies structure by grouping geometrically similar connections; and, connectivity glyphs, which depict a condensed connectivity map at each point on the cortical surface. These approaches can be applied in the native brain space, facilitating interpretation of the relation of connexels to brain anatomy. The tools have been implemented as part of brainGL, an extensive open-source software for the interactive exploration of structural and functional brain data.

Three-dimensional mean-shift edge bundling for the visualization of functional connectivity in the brain.

Functional connectivity, a flourishing new area of research in human neuroscience, carries a substantial challenge for visualization: while the end points of connectivity are known, the precise path between them is not. Although a large body of work already exists on the visualization of anatomical connectivity, the functional counterpart lacks similar development. To optimize the clarity of whole-brain and complex connectivity patterns in three-dimensional brain space, we develop mean-shift edge bundling, which reveals the multitude of connections as derived from correlations in the brain activity of cortical regions.

Visualizing the human connectome.

Innovations in data visualization punctuate the landmark advances in human connectome research since its beginnings. From tensor glyphs for diffusion-weighted imaging, to advanced rendering of anatomical tracts, to more recent graph-based representations of functional connectivity data, many of the ways we have come to understand the human connectome are through the intuitive insight these visualizations enable. Nonetheless, several unresolved problems persist. For example, probabilistic tractography lacks the visual appeal of its deterministic equivalent, multimodal representations require extreme levels of data reduction, and rendering the full connectome within an anatomical space makes the contents cluttered and unreadable. In part, these challenges require compromises between several tensions that determine connectome visualization practice, such as prioritizing anatomic or connectomic information, aesthetic appeal or information content, and thoroughness or readability. To illustrate the ongoing negotiation between these priorities, we provide an overview of various visualization methods that have evolved for anatomical and functional connectivity data. We then describe interactive visualization tools currently available for use in research, and we conclude with concerns and developments in the presentation of connectivity results.

A software tool for interactive exploration of intrinsic functional connectivity opens new perspectives for brain surgery.

BACKGROUND: Functional connectivity analysis of resting-state functional magnetic resonance imaging data (fcrs-fMRI) has been shown to be a robust non-invasive method for localization of functional networks (without using specific tasks) and to be promising for presurgical planning. However, in order to transfer the approach to everyday clinical practice, fcrs-fMRI needs to be further validated and made easily accessible to neurosurgeons. This paper addresses the latter by presenting a software tool designed for neurosurgeons for analyzing and visualizing fcrs-fMRI data. METHODS: A prototypical interactive visualization tool was developed to enable neurosurgeons to explore functional connectivity data and evaluate its usability. The implementation builds upon LIPSIA, an established software package for the assessment of functional neuroimaging data, and integrates the selection of a region-of-interest with the computation and visualization of functionally connected areas. The tool was used to explore data from a healthy participant and eight brain lesion patients. The usability of the software was evaluated with four neurosurgeons previously unacquainted with the methodology, who were asked to identify prominent, large-scale cortical networks. FINDINGS: With this novel tool, previously published findings, such as tumor displacement of the sensorimotor cortex and other disturbances of functional networks, were reproduced. The neurosurgeons were able to consistently obtain results similar to the results of an expert, with the exception of the language network. Immediate feedback helped to pinpoint functional networks quickly and intuitively, with even inexperienced users requiring less than 3 min per network. CONCLUSIONS: Although fcrs-fMRI is a nascent method still undergoing evaluation with respect to established standards, the interactive software is nonetheless a promising tool for non-invasive exploration of individual functional connectivity networks in neurosurgical practice, both for well-known networks and for those less typically addressed.

Resting developments: a review of fMRI post-processing methodologies for spontaneous brain activity.

Analytic tools for addressing spontaneous brain activity, as acquired with fMRI during the "resting-state," have grown dramatically over the past decade. Along with each new technique, novel hypotheses about the functional organization of the brain are also available to researchers. We review six prominent categories of resting-state fMRI data analysis: seed-based functional connectivity, independent component analysis, clustering, pattern classification, graph theory, and two "local" methods. In surveying these methods, we address their underlying assumptions, methodologies, and novel applications.

Sarcoidosis after adjustable silicone gastric banding - a report of two cases in Germany.

We report 2 patients who developed sarcoidosis after the implantation of adjustable silicone gastric banding (GB) in Germany. Before implantation, no pulmonary diseases were evident in the medical history of either patient. The 1st patient suffered sarcoidosis 12 months after GB. He has been treated at a hospital specialising in pulmonary diseases. Because of the treatment with corticoids, the patient has regained weight after the initial weight reduction. The 2nd patient developed signs of pulmonary infection on the 7th postoperative day (after GB). Pulmonary sarcoidosis was diagnosed 4 months later after consultation with a pulmonologist.

Map warping for the annotation of metro maps.

Schematic transportation maps usually contain little or no detail describing the environment of stations or their embedding in the surrounding area. The annotation of a distorted city map alleviates this deficiency and further improves the usability of schematic transportation maps by merging two different navigational spaces.

Complex logarithmic views for small details in large contexts.

Commonly known detail in context techniques for the two-dimensional Euclidean space enlarge details and shrink their context using mapping functions that introduce geometrical compression. This makes it difficult or even impossible to recognize shapes for large differences in magnification factors. In this paper we propose to use the complex logarithm and the complex root functions to show very small details even in very large contexts. These mappings are conformal, which means they only locally rotate and scale, thus keeping shapes intact and recognizable. They allow showing details that are orders of magnitude smaller than their surroundings in combination with their context in one seamless visualization. We address the utilization of this universal technique for the interaction with complex two-dimensional data considering the exploration of large graphs and other examples.

Thoracoscopic thymectomy in the treatment concept for myasthenia gravis.

Myasthenia gravis (MG) is a chronic autoimmune disease that usually responds positively to treatment with thymectomy. Standard surgical procedures have been shown to result in a beneficial outcome. This Chapter includes discussions regarding what are controversial, and opinions as to what constitutes the optimal access to be used for thymectomy. In a prospective study conducted between 8/97 and 12/03, 137 patients with MG underwent thoracoscopic thymectomy, for which a left-sided approach was generally applied. An analysis of the intraoperative and postoperative course was performed, as well as of the impact of the surgical procedure on further development of the disease. The results obtained were compared with those published in the literature, with particular reference to results obtained with open surgery. The patients in this study were 96 females and 41 males, with a mean age of 35.8 (range: 9-83) years. The mean preoperative duration of the disease was 22.9 (range: 1-140) months. In 8 (5.8%) patients, the procedure was converted to an anterolateral thoracotomy or sternotomy. The postoperative morbidity rate was 5.8%, one (0.7) patient died and the mean follow up was 24.7 (range: 1-57) months. Complete remission was noted in 19.4%, and improvements reflected either in a reduction in the medication required or a decrease in symptom severity, in a total of 76.8%. Complete thoracoscopic thymectomy is a technically feasible operation, equally as effective as conventional open surgery. Remissions or symptomatic improvements were observed in more than 70% of the patients. The low morbidity rate, coupled with excellent cosmetic results, have led to increasing acceptance of the operation both by patients and Neurologists. Therefore, thoracoscopic thymectomy represents a new, alternative method for use in patients with MG.