Education [MSc/MD/PhD neuroscience] Promotion of young researchers Flow cytometry Brain imaging [from cell to system] Proteomik,Genomik, Genetik Research area A: Mechanisms of damage Research Area B: Endogenous brain protection Research area C: Regeneration Research area D: Crosstalk between nervous and immune system Research area E: Developmental disturbances Research area F: Plasticity Disorders of network formation Neuroinflammation Cerebro-vascular diseases (CVD) Research unit for long-term outcome and behavioral analysis Research unit for long-term outcome and behavioral analysis NeuroCure Clinical Research Center


Brain imaging [from cell to system]

Brain imaging, data analysis, and computational modeling

Brain imaging has been a major driving force behind the impressive progress made in the neurosciences over the last decade. Brain imaging now spans from the subcellular to the systems level, and not only allows researchers and clinicians to obtain structural, but increasingly also functional information. Of particular relevance to NeuroCure , brain imaging may hold the key to translational neuroscience: in animal models of disease, it is possible to image ,fingerprints' of pathophysiology and treatment responses, which can be validated and applied to human patients using the same non-invasive brain imaging techniques (e.g. MRI, near-infrared spectroscopy, MEG, and PET). NeuroCure scientists have already developed and applied such methods (functional and molecular optical imaging as well as MRI) to animal models of stroke, MS, and focal epilepsies.

To further develop brain imaging and harvest its full potential, a broad expertise in advanced data-analysis methods and computational modeling will be increasingly important in the future. Here, the members of NeuroCure have been at the forefront of a whole range of emerging techniques. This concerns advanced signal processing tools for the spatio-temporal analysis of brain signals, multivariate analyses of multichannel EEG and MEG recordings, and model-based studies of structural and functional changes in brain connectivity. Expertise in computational modeling is crucial for the development of sophisticated multi-scale models of diseases that bridge the gap between microarchitecture and large-scale brain function. The Bernstein Center for Computational Neuroscience Berlin provides a lively forum to discuss emerging research trends and initiate new joint projects of physicists, mathematicians, biologists, and clinical neuroscientists.

 

Available imaging technologies (selected): Two-photon and conventional confocal microscopy, MRI (several research scanners for human studies, 1.5T / 3T / future 7T; 3T at the stroke unit), 128 channel MRI-compatible EEG, MEG, several small animal MR scanners (2.4T / 7T / future 9.4T); small animal PET, human PET, and PET-multiline CT; several multiline CTs, human and small animal near-infrared brain imagers (including tomography), whole-head 96-channel MEG, 63-channel DC-MEG, 304-channel vector MEG, combined probes for invasive electrocorticography and laser-Doppler flowmetry as well as combined probes for simultaneous non-invasive DC-MEG, DC-EEG, and near-infrared spectroscopy for animal and human studies.

 

Expert knowledge in data analysis and modeling (selected): ICA , PCA, statistical pattern recognition and kernel methods, cortical segmentation, voxel-based morphometry, computational analysis of cortical surface topography, biophysical modeling, probability and information theory, statistics, non-linear dynamics, and systems theory.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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