 |
|
||||||||||
Education
Spotlight
Computational models of brain connectivity, coupled with machine learning algorithms, make it possible to infer neuronal disease mechanisms from
non-invasive functional magnetic resonance imaging (fMRI) data in humans.
This illustration shows how dynamic systems models can be used for reducing
complex (high-dimensional) brain activity data to a simple (low-dimensional)
and mechanistically interpretable representation (Brodersen et al., PLoS
Comput. Biol. 2011). Please also see the summary on ETH Life.
Current Semester - SS 2013
| 252-0526-00 | Lecture | Statistical Learning Theory | Details |
| 263-0008-00 | Lecture | Computational Intelligence Lab | Details |
| 252-0055-00 | Lecture | Informationstheorie | Details |
|
252-5101-00 |
Lecture | Numerical Simulation of Dynamic Systems |
Details |
Student Projects
If you are interested in doing a project (such as a semster or master thesis) in our group, please have a look at our list of open and completed projects (you need your ETH login). Do not hesitate to contact Dr. Ludwig Busse (our thesis coordinator) or Prof. Joachim Buhmann if you have questions.
Wichtiger Hinweis:
Diese Website wird in älteren Versionen von Netscape ohne
graphische Elemente dargestellt. Die Funktionalität der
Website ist aber trotzdem gewährleistet. Wenn Sie diese
Website regelmässig benutzen, empfehlen wir Ihnen, auf
Ihrem Computer einen aktuellen Browser zu installieren. Weitere
Informationen finden Sie auf
folgender
Seite.
Important Note:
The content in this site is accessible to any browser or
Internet device, however, some graphics will display correctly
only in the newer versions of Netscape. To get the most out of
our site we suggest you upgrade to a newer browser.
More
information
