User:Daniel Mietchen

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Revision as of 20:30, 7 June 2009 by imported>Daniel Mietchen (partial transclusion)
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I am a biophysicist focusing on the application of methods from physics to the study of biological structures and processes from a comparative evolutionary perspective, with a current emphasis on applications of brain morphometry (e.g. gyrification and cortical thickness) to the study of schizophrenia. My activities at CZ are centred around these matters and sustainable science but other topics of interest to me are listed here, and I also contribute to CZ:Eduzendium (e.g. this summer school). Though I prefer to edit here, I still occasionally do so at the Wikipedias, particularly in areas or languages not covered here yet. More information about me can be found via my lab page, PhD thesis, online book collection, blog, feed, tag cloud and band.

Research areas

Developing Article Brain morphometry: The quantitative study of structures in the brain, their differences between individuals, correlations with brain function, and changes of these characteristics over time. [e]


(CC) Image: Robert Dahnke
Surface-based brain morphometry.

Brain morphometry is a subfield of both morphometry and the brain sciences, concerned with the measurement of brain structures and changes thereof during development, aging, learning, disease and evolution. Since autopsy-like dissection is generally impossible on living brains, brain morphometry starts with noninvasive neuroimaging data, typically obtained from magnetic resonance imaging (or MRI for short). These data are born digital, which allows researchers to analyze the brain images further by using advanced mathematical and statistical methods such as shape quantification or multivariate analysis. This allows researchers to quantify anatomical features of the brain in terms of shape, mass, volume (e.g. of the hippocampus, or of the primary versus secondary visual cortex), and to derive more specific information, such as the encephalization quotient, grey matter density and white matter connectivity, gyrification, cortical thickness, or the amount of cerebrospinal fluid. These variables can then be mapped within the brain volume or on the cortical surface, providing a convenient way to assess their pattern and extent over time, across individuals or even between different biological species. The field is rapidly evolving along with neuroimaging techniques — which deliver the underlying data — but also develops in part independently from them, as part of the emerging field of neuroinformatics, which is concerned with developing and adapting algorithms to analyze those data. (Read more...)

Research publications

For full publication list, go here.

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