16 research outputs found
OpenLB User Guide: Associated with Release 1.6 of the Code
OpenLB is an object-oriented implementation of LBM. It is the first
implementation of a generic platform for LBM programming, which is shared with
the open source community (GPLv2). Since the first release in 2007, the code
has been continuously improved and extended which is documented by thirteen
releases as well as the corresponding release notes which are available on the
OpenLB website (https://www.openlb.net). The OpenLB code is written in C++ and
is used by application programmers as well as developers, with the ability to
implement custom models OpenLB supports complex data structures that allow
simulations in complex geometries and parallel execution using MPI, OpenMP and
CUDA on high-performance computers. The source code uses the concepts of
interfaces and templates, so that efficient, direct and intuitive
implementations of the LBM become possible. The efficiency and scalability has
been checked and proved by code reviews. This user manual and a source code
documentation by DoxyGen are available on the OpenLB project website
The genetic architecture of the human cerebral cortex
The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder
Weiterentwicklung des Digitalen Prototyps zum Digitalen Fingerabdruck
Durch die stark zunehmende Digitalisierung wird das Produkt immer stärker mit der Produktion und dem In-Service-Bereich gekoppelt. Dies unterstützt die Automatisierung vieler Herstellprozesse und ermöglicht eine lückenlose Rückverfolgung eines jeden Bauteils bis hin zum Material. Im Forschungsprojekt Digitaler Fingerabdruck des Forschungscampus ARENA2036 wird in Zusammenarbeit von verschiedenen Instituten und Firmen diese Kopplung an einem Demonstrator ausgeführt und die erforderlichen Schnittstellen und Datenflüsse generiert
Metabolic and structural connectivity within the default mode network relates to working memory performance in young healthy adults
Studies of functional connectivity suggest that the default mode network (DMN) might be
relevant for cognitive functions. Here, we examined metabolic and structural connectivity between
major DMN nodes, the posterior cingulate (PCC) and medial prefrontal cortex (MPFC), in relation
to normal working memory (WM).
DMN was captured using independent component analysis of [18F]fluorodeoxyglucose
positron emission tomography (FDG-PET) data from 35 young healthy adults (27.1±5.1 years).
Metabolic connectivity, a correlation between FDG uptake in PCC and MPFC, was examined in
groups of subjects with (relative to median) low (n=18) and high (n=17) performance on digit span
backward test as an index of verbal WM. In addition, fiber tractography based on PCC and MPFC
nodes as way points was performed in a subset of subjects.
FDG uptake in the DMN nodes did not differ between high and low performers. However,
significantly (p=0.01) lower metabolic connectivity was found in the group of low performers.
Furthermore, as compared to high performers, low performers showed lower density of the left
superior cingulate bundle.
Verbal WM performance is related to metabolic and structural connectivity within the DMN in
young healthy adults. Metabolic connectivity as quantified with FDG-PET might be a sensitive
marker of the normal variability in some cognitive functions
Improving the clinical potential of ultra-high field fMRI using a model-free analysis method based on response consistency
OBJECTIVE To develop an analysis method that is sensitive to non-model-conform responses often encountered in ultra-high field presurgical planning fMRI. Using the consistency of time courses over a number of experiment repetitions, it should exclude low quality runs and generate activation maps that reflect the reliability of responses. MATERIALS AND METHODS 7 T fMRI data were acquired from six healthy volunteers: three performing purely motor tasks and three a visuomotor task. These were analysed with the proposed approach (UNBIASED) and the GLM. RESULTS UNBIASED results were generally less affected by false positive results than the GLM. Runs that were identified as being of low quality were confirmed to contain little or no activation. In two cases, regions were identified as activated in UNBIASED but not GLM results. Signal changes in these areas were time-locked to the task, but were delayed or transient. CONCLUSION UNBIASED is shown to be a reliable means of identifying consistent task-related signal changes regardless of response timing. In presurgical planning, UNBIASED could be used to rapidly generate reliable maps of the consistency with which eloquent brain regions are activated without recourse to task timing and despite modified hemodynamics