Brains constantly change in response to internal and external cues. While most of these changes simply reflect normal development and learning, others could lead to brain diseases or detrimental aging processes. Helping people with the latter kind of changes is one of the central motivators of neurology and psychiatry research. However, many aspects of brain structure and function – as well as their interactions, from the molecular to the cognitive and sociological levels – are still not sufficiently understood to provide a clear biological framework on which clinicians can base their diagnoses and therapeutic decisions. As a consequence, many neuropsychiatric disorders continue to lack promising therapies, and quite a few are still hard to diagnose.
Our group focuses on the quantification of macroscopic structures in the brain and on the classification of the changes they undergo, especially in the early phases of neuropsychiatric disorders like schizophrenia or Alzheimer’s disease. Any findings can be considered to be a contribution to a coherent theoretical framework for brain changes across time and levels of biological organization.
|methods for structural brain imaging:
The development of algorithms and tools for processing of voxel- and surface based imaging data encompasses segmentation, surface reconstruction, correction of topology artifacts and conformal mapping. more…
|development and evolution
We use structural MRI data to investigate age-related (i.e., ontogenetic) changes of brain morphology and also their phylogenetic variation between species. more…
| schizophrenia research
Voxel- and surface based imaging data provide insight into abnormal brain development for certain diseases. The study of morphological differences between healthy subjects and schizophrenic patients might help to clarify the mechanism and progression of the underlying alterations in brain development. more…
|gyrification and cortical measures
To study inter-individual differences in brain structure, we intend to develop, improve, or use pre-existing local and global brain measures. Some such measures have recently emerged in the field of magnetic resonance brain imaging, including sulcal depth, cortical thickness, and local gyrification indices. more…
|surface shape analysis
The reconstructed cortical surfaces and its shape properties are analyzed with methods of spherical harmonic decomposition and multiscale approaches like spherical wavelets. more…
|classification of brain structure
Structural brain imaging data can be used to predict the group membership (such as gender or disease) of unknown individuals. Several multivariate analysis and machine learning techniques give a solution for this classification problem. Our emphasis is the application of kernel methods and support vector classification. more…