Individualized single-subject networks from T1 mri features such as cortical thickness, gray matter density, subcortical morphometric features, gyrification and curvature.
Applicable for whenever network-level features are useful, among which common use cases are
- biomarker development and
- brain-behaviour relationships (e.g. for the diagnosis and prognosis of many brain disorders such as Alzheimer's, Parkinson's, Schizophrenia and the like).
- aging (changes in network properties over age and their relations to other variables)
pip install -U graynet