Metadata-Version: 2.1
Name: graynet
Version: 0.4.8
Summary: Individualized single-subject networks from T1 mri features such as cortical thickness and gray matter density. 
Home-page: https://github.com/raamana/graynet
Author: Pradeep Reddy Raamana
Author-email: raamana@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 2.7
Requires-Dist: numpy
Requires-Dist: pyradigm
Requires-Dist: nibabel
Requires-Dist: networkx
Requires-Dist: medpy

Individualized single-subject networks from T1-weighted magnetic resonance imaging (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.
 - 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).

Docs: https://raamana.github.io/graynet/

