Generate animation of trk streamlines

Create plots of diffusion metrics (i.e. FA, MD, RD, AD) for each of the segmented tracts from AFQ, known as Tract Profiles. Obtains streamline positions from segmented tracts and plots the metrics of interest along "nodes" of the tract, allowing for comparison of individual subject tracts. Requires the dt6 output from dtiinit and a white matter classification output from AFQ or WMA

This Brainlife App analyses MEG (and EEG) data at the sensor-level using MNE-BIDS-Pipeline (https://mne.tools/mne-bids-pipeline).

HD-BET is an automated brain extraction method for MRI using neural networks.

Create mid-axial, sagittal, and coronal slice png of tissue type masks. If you include a T1, the pngs will display an outline of the different masks on the T1. Else, the pngs will be of binary masks of the different tissue types: gray matter, white matter, CSF, and gray matter white matter interface.

Brain Extraction via FSL's BET command

Open Diffusion Data Derivatives (O3D). Reproducible Neuroimaging via open cloud services: Data upcycling to advance discovery in brain science

Convert ctf files into fif format

This app will map volumated measure files (i.e. qmri) to the cortical surface following Fukutomi et al (2018; 10.1016/j.neuroimage.2018.02.017) using Connectome Workbench.

registering t1w images with ANTs

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This app will compute average surfaces and cortexmap data for group anaylsis

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Generate structural connectomes using MRTrix3 and SIFT2

Brainlife.io app for Noah Benson's neuropythy library, retinotopy from T1 anatomy

This app will generate ROIs from a parcellation, subcortical structures found in the Freesurfer aseg, cortical structures found in the Freesurfer parcellations, and population receptive field visual area segmentations. The ROIs will be resliced into diffusion space in of this, merging ROIs is allowed.

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testing volume and surface fMRI pipelines with fmaps

This is copy of the mergeTCK BL app (https://doi.org/10.25663/brainlife.app.219) modified to take two tractograms as input. This is a temporary workaround for the lack of functionality for multi-input datatypes in brainilfe Pipelines.

A Reproducible Workflow for Structural and Functional Connectome Ensemble Learning

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Track the anterior limb of the internal capsule with streamline tractography using MRTRIX3

fMRIPrep is a functional magnetic resonance imaging (fMRI) data preprocessing pipeline that is designed to provide an easily accessible, state-of-the-art interface that is robust to variations in scan acquisition protocols and that requires minimal user input, while providing easily interpretable and comprehensive error and output reporting.