Title: Prediction of Personality using Diffusion MRI Local Connectome Fingerprints
Project lead: Fang-Cheng Yeh
Registered Brainhack Global 2020 Event: The Pittsburgh Brainhack: DeBurghing 2020, Pittsburgh, PA,
Project Description: Local connectome fingerprints (LCF) are voxel-based metrics derived from diffusion MRI to provide a subject-specific quantification of brain connections. The task of this project is to predict personality using LCF.
Good first issues:
Data to use: https://pitt.box.com/v/HCP1062-NEOFAC
There are a total of 1062 subjects included in this data set. Each LCF of a subject has a total of 128894 brain fingerprint features. Each feature has an associated location (mni_location) and fiber orientation (fiber_direction) to allow plotting the spatial distribution of the feature. Please note that each voxel may have more than one feature (because there could be multiple fiber populations within the same voxel).
dimension: the image dimension of the original MRI data fiber_direction: the axonal fiber direction for each feature mni_location: the spatial location for each feature names: HCP serial number for each subject subjects: The LCFs of 1062 subjects (features) NEOFAC: subjects answers to 60 questions (variable to be predicted). The NEO-FFI variable can be 0.3: strongly disagree, 0.4 disagree, 0.5 neutral, 0.6: agree, 0.7: strongly agree.
Link to project repository/sources: http://dsi-studio.labsolver.org/download-images/local-connectome-fingerprints-of-hcp-1062-subjects-for-neofac-prediction
Goals for Brainhack Global 2020 The goal is to test whether fixed behaviors could be predicted from LCF.
Skills: Data regression using statistics or machine learning methods.
Tools/Software/Methods to Use: Python, Matlab, or R Any data analysis packages.
Communication channels: Twitter account: @FangChengYeh
Now the real list (please indicate all of the labels you’d like to add to your project):
Type of project: #coding_methods, #data_management, #method_development
Project development status: #releases_existing
Topic of the projet: #connectome, #deep_learning, #diffusion, #machine_learning, #MR_methodologies, #neural_decoding, #statistical_modelling,
Tools used in the project: #DSIStudio
Tools skill level required to enter the project (more than one possible): #comfortable, #expert, #familiar
Programming language used in the project: #Matlab, #Python, #R
Modalities involved in the project (if any): #behavioral, #DWI, #MRI
Git skills required to enter the project (more than one possible): #0_no_git_skills
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