Computational modeling of brain connectivity and spatiotemporal organization using network and machine learning methods.
Projects can include graph construction, network analysis, connectivity measures, dynamic modeling, and spatiotemporal representations.
Applications include brain network research, connectivity studies, neural dynamics, and computational neuroscience.
Implementation is selected according to the available data, technical constraints, required level of automation, and the existing software or research environment. The solution can be implemented as a standalone component or integrated into a larger system.
The resulting system is intended to provide a clear computational workflow that can be evaluated, maintained, and extended as the project develops. Model choice, data processing, interfaces, and deployment can therefore be adapted to the requirements of the specific project.