Head: Dr. Viktor Jirsa Information processing in the human brain relies on the synchronization, as well as the recruitment and disengagement of far distant neural areas. Such high-dimensional neural dynamics results in lower-dimensional behavioral processes including cognition, perception, and motor actions. We wish to understand the fundamental principles of the emergence of cognition from neural network dynamics. Our research is guided by ideas from nonlinear dynamics and self-organization theories, and informed by non-invasive brain imaging (EEG, MEG and fMRI).
We use experiments, mathematical analysis, and computer simulations to understand things with lots of pieces that interact strongly with each other.
- Fluid flow across cell membranes and tissues.
- Electrical currents through single ion channel proteins in the cell membrane.
- Motions in proteins.
- Nonlinear analysis of experimental and clinical data from the heart and lung.
- Reverse engineering the one celled algae Chlamydomonas.
- How genes control other genes based on mRNA measurements from cDNA microarrays.
- Genetic networks in heart disease.
- Spread of electronic and biological infections.
- Artificial neural networks for therapeutic drug discovery.
- Educational materials on fractals and chaos for scientists who want to use these ideas in their work and for students who never liked math.
