NeuroGraph Preprocessing Functionalities

class Age_Dataset(root, dataset_name, dataset, transform=None, pre_transform=None, pre_filter=None)

Bases: InMemoryDataset

process()

Processes the dataset to the self.processed_dir folder.

property processed_file_names

The name of the files in the self.processed_dir folder that must be present in order to skip processing.

class Brain_Connectome_Rest(root, name, n_rois, threshold, path_to_data, n_jobs, transform=None, pre_transform=None, pre_filter=None)

Bases: InMemoryDataset

construct_adj_postive_perc(corr)

construct adjacency matrix from the given correlation matrix and threshold

extract_from_3d_no(volume, fmri)

Extract time-series data from a 3d atlas with non-overlapping ROIs.

Inputs:

path_to_atlas = ‘/path/to/atlas.nii.gz’ path_to_fMRI = ‘/path/to/fmri.nii.gz’

Output:

returns extracted time series # volumes x # ROIs

get_data_obj(iid, behavioral_data, path_to_data, volume)

process()

Processes the dataset to the self.processed_dir folder.

property processed_file_names

The name of the files in the self.processed_dir folder that must be present in order to skip processing.

class Brain_Connectome_Rest_Download(root, name, n_rois, threshold, path_to_data, n_jobs, s3, transform=None, pre_transform=None, pre_filter=None)

Bases: InMemoryDataset

construct_Adj_postive_perc(corr)

extract_from_3d_no(volume, fmri)

Extract time-series data from a 3d atlas with non-overlapping ROIs.

Inputs:

path_to_atlas = ‘/path/to/atlas.nii.gz’ path_to_fMRI = ‘/path/to/fmri.nii.gz’

Output:

returns extracted time series # volumes x # ROIs

get_data_obj(iid, behavioral_data, BUCKET_NAME, volume)

process()

Processes the dataset to the self.processed_dir folder.

property processed_file_names

The name of the files in the self.processed_dir folder that must be present in order to skip processing.

class Brain_Connectome_Task(root, dataset_name, n_rois, threshold, path_to_data, n_jobs, transform=None, pre_transform=None, pre_filter=None)

Bases: InMemoryDataset

construct_adj_postive_perc(corr)

construct adjacency matrix from the given correlation matrix and threshold

extract_from_3d_no(volume, fmri)

Extract time-series data from a 3d atlas with non-overlapping ROIs.

Inputs:

path_to_atlas = ‘/path/to/atlas.nii.gz’ path_to_fMRI = ‘/path/to/fmri.nii.gz’

Output:

returns extracted time series # volumes x # ROIs

get_data_obj_task(iid, target_path, volume)

process()

Processes the dataset to the self.processed_dir folder.

property processed_file_names

The name of the files in the self.processed_dir folder that must be present in order to skip processing.

class Brain_Connectome_Task_Download(root, dataset_name, n_rois, threshold, path_to_data, n_jobs, s3, transform=None, pre_transform=None, pre_filter=None)

Bases: InMemoryDataset

construct_Adj_postive_perc(corr)

extract_from_3d_no(volume, fmri)

Extract time-series data from a 3d atlas with non-overlapping ROIs.

Inputs:

path_to_atlas = ‘/path/to/atlas.nii.gz’ path_to_fMRI = ‘/path/to/fmri.nii.gz’

Output:

returns extracted time series # volumes x # ROIs

get_data_obj_task(iid, BUCKET_NAME, volume)

process()

Processes the dataset to the self.processed_dir folder.

property processed_file_names

The name of the files in the self.processed_dir folder that must be present in order to skip processing.

class Dyn_Down_Prep(root, name, s3, n_rois=100, threshold=10, window_size=50, stride=3, dynamic_length=150)

Bases: object

construct_Adj_postive_perc(corr)

construct_dataset()

extract_from_3d_no(fmri)

Extract time-series data from a 3d atlas with non-overlapping ROIs.

Inputs:

path_to_atlas = ‘/path/to/atlas.nii.gz’ path_to_fMRI = ‘/path/to/fmri.nii.gz’

Output:

returns extracted time series # volumes x # ROIs

get_dynamic_data_object(iid)

process_dynamic_fc(timeseries, y, sampling_init=None, self_loop=True)

Dyn_Prep(fmri, regs, n_rois=100, window_size=50, stride=3, dynamic_length=None)

Preprocess fMRI data using NeuroGraph preprocessing pipeline and construct dynamic functional connectome matrices

Args:

fmri (numpy array): fmri image regs (numpy array): regressor array rois (int): {100, 200, 300, 400, 500, 600, 700, 800, 900, 1000}, optional, Number of regions of interest. Default=100. window_size (int) : the length of the window, default = 50 stride (int): default: 3 dynamic_length (int) : length of the timeseries to be considered for dynamic graphs. For memory and compution efficiency, we set dynamic length = 50, default = None, if None, consider the whole timeseries object

class FI_Dataset(root, dataset_name, dataset, transform=None, pre_transform=None, pre_filter=None)

Bases: InMemoryDataset

process()

Processes the dataset to the self.processed_dir folder.

property processed_file_names

The name of the files in the self.processed_dir folder that must be present in order to skip processing.

class Gender_Dataset(root, dataset_name, dataset, transform=None, pre_transform=None, pre_filter=None)

Bases: InMemoryDataset

process()

Processes the dataset to the self.processed_dir folder.

property processed_file_names

The name of the files in the self.processed_dir folder that must be present in order to skip processing.

class WM_Dataset(root, dataset_name, dataset, transform=None, pre_transform=None, pre_filter=None)

Bases: InMemoryDataset

process()

Processes the dataset to the self.processed_dir folder.

property processed_file_names

The name of the files in the self.processed_dir folder that must be present in order to skip processing.