git clone https://github.com/isebenius/MIND.git 

import sys
sys.path.insert(1, '/path/to/MIND/code/')
from MIND import compute_MIND

## Specify path to surfer directory. This is the path to the Freesurfer folder containing all standard output directories (e.g. surf, mri, label)
path_to_surf_dir = '/path/to/surfer/dir' 

## Specify features to include in MIND calculation. The following abbreviations specifies the ?h.thickness, ?h.curv, ?h.volume, ?h.sulc, and ?h.area Freesurfer surface features.
features = ['CT','MC','Vol','SD','SA'] 

## Select which parcellation to use. This has been tested on Desikan Killiany (DK), HCP-Glasser, DK-308 and DK-318 parcellations.
parcellation = 'aparc' 

## Returns a dataframe of regions X regions containing the final MIND network.
MIND = compute_MIND(path_to_surf_dir, features, parcellation) 

features = ['CT', 'path/to/?h.feature']

def get_vertex_df(surf_dir, features, parcellation):

    '''
    INPUT SPECIFICATIONS:
    • surf_dir (str) : This is a string the location containing all relevant directories output by FreeSurfer (i.e. label, mri, surf).

    • features (list):
        This function accepts the "features" argument as a list containing items in the following forms:
            str: 

                • One of ['CT','Vol','SA','MC','SD']. In this form, the function will automatically assume that the requested features are found in the surf_dir/surf directory and correspond to the following files:
                    CT: ?h.thickness
                    Vol: ?h.volume
                    SA: ?h.area
                    MC: ?h.curv
                    SD: ?h.sulc 

                • You may also pass a string in the form 'thickness', 'volume', 'sulc', etc, which refer directly to default files already found in the surf_dir/surf directory for both rh and lh.
                For example, the function will interpret the entry 'thickness' to refer to the files surf_dir/surf/lh.thickness and surf_dir/surf/rh.thickness

                • Finally, you may pass a string in the form of a FULL path as follows: with a question mark '?' indicating the position specifying the hemisphere such as "full/path/to/?h.feature".
                Using this formulation will cause the command to look for files that exactly match both "full/path/to/lh.feature" and "full/path/to/rh.feature". If the left and right version of the files aren't exactly the same otherwise, this won't work.


            tuple: (path/to/lh_surface_feature, path/to/rh_surface_feature)
                • If you would rather pass other features directly into the function, you must specify the locations (using paths) of both the left and right versions of each desired feature as a tuple.
                **The files must be readable by nibabel's read_morph_data function, i.e. in FreeSurfer's surface format!***
                So for example, if you have used the provided register_and_vol2surf function to generate surface maps of fractional anisotropy in a separate folder, you could pass them as an element in the list like:
                (path/to/lh.FA.mgh, path/to/rh.FA.mgh)

        A valid list of feature values combining these different input types would therefore be: ['CT','SD',(path/to/lh_feature1, path/to/rh_feature1), (path/to/lh_feature2, path/to/rh_feature2)] 
    
    • parcellation (str): This is a string the location containing parcellation scheme to be used. The files 'lh.' + parcellation + '.annot' and 'rh.' + parcellation + '.annot' must exist inside the surf_dir/label directory.
    '''

function register_and_vol2surf(mov, subject_id, out_dir, b0 = None, feature_name = 'vol-feature', contrast = 't2', sampling_units = 'frac', sampling_range = (0.2,0.8,0.1), sampling_method = 'average', cleanup=True):
  '''
  This commands registers a volumetric image to T1 then projects to the white surface.
  
  	mov: the volume to be registered.
	subject_id: The subject id, found in SUBJECTS_DIR.
	out_dir: path to output files.
	b0: if registering DWI images, this is the image to use for registration (using the B0 or S0 is recommended).
	feature_name: the name of the feature you would like to project (e.g., FA etc.). This is just so the output files are named nicely.
	contrast: either 't1' or 't2' based on the contrast of the registration image:
	sampling units: either 'frac' or 'mm'
	sampling method: 'point’ or ‘max’ or ‘average,’ tells the command how to sample.
	sampling range: a float or a tuple of the form: (a float, a float, a float)) – Sampling range - a point or a tuple of (min, max, step).
	cleanup: boolean, whether to delete all intermediate files or not.
  '''
 
function calculate_surface_t1t2_ratio(t2_loc, subject_id, out_dir, t1_loc = None, feature_name = 'T2', contrast = 't2', sampling_units = 'frac', sampling_range = (0.2,0.8,0.1), sampling_method = 'average', cleanup=True):

  '''
  This commands registers T2 to T1, divides T1 by the registered T2, then projects to the white surface.
  We recommend using the T2.mgz file in the mri/ folder output from freesurfer.
  
  	mov: the volume to be registered.
	subject_id: The subject id, found in SUBJECTS_DIR.
	out_dir: path to output files.
	t1_loc: the location.
	feature_name: the name of the feature you would like to project (e.g., FA etc.). This is just so the output files are named nicely.
	contrast: either 't1' or 't2' based on the contrast of the registration image:
	sampling units: either 'frac' or 'mm'
	sampling method: 'point’ or ‘max’ or ‘average,’ tells the command how to sample.
	sampling range: a float or a tuple of the form: (a float, a float, a float)) – Sampling range - a point or a tuple of (min, max, step).
	cleanup: boolean, whether to delete all intermediate files or not.
   '''