|
Description: |
Traditionally neuroscience, like most biological sciences, has focused on gathering experimental data. While these huge data collection efforts are usually embedded in the context of some theory on the function of the system, such theories are often not formalized into a mathematical model. Because of the huge complexity of nervous systems, which spans 8 different levels of spatial complexity and temporal scales from microseconds to decades, it will be impossible to arrive at a full understanding of neural processing without mathematical modeling and theory. In addition we also need to make all the collected data available through electronic databases to facilitate these modeling efforts. I will present a general overview of the science of neuroinformatics and use several examples from my own modeling of cerebellar circuitry and neurons to demonstrate these issues.
Area(s):
|
