Computational workflows for processing and analyzing electroencephalography and magnetoencephalography data.
Work can include preprocessing, artifact correction, spectral analysis, connectivity, event-related analysis, classification, and machine learning.
These methods can support neuroscience experiments, cognitive research, brain-state analysis, and neural decoding studies.
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.