3D Brain Atlas_Trajectory_1000

The purpose of this application is primarily the education for neurofeedback enthusiasts and all those people who are interested in getting acquainted with this complex matter in a simple way. The purpose of this application is not analyzing human neuropsychological data for which there are specialized softwares today, but rather, one educational tool which uses data and  information outlined further in the text.

About software

Code

Software has been made in C# programming language with Unity technology by Dr. Slobodan Jovanovic

3D brain mesh models:

1.     Colin Skin , Skull and  Vessels   are extracted from MRI images – THE MC CONNELL IMAGING CENTRE, Montreal Neurological Institute, McGill University

Colin 27 Average Brain, Stereotaxic Registration Model, high-resolution version 2008

http://www.bic.mni.mcgill.ca/ServicesAtlases/Colin27Highres

2.    Average Skull extracted from MRI images

THE MC CONNELL IMAGING CENTRE, Montreal Neurological Institute, McGill University

Linear ICBM Average Brain (ICBM152) Stereotaxic Registration Model

http://nist.mni.mcgill.ca/?p=798

3.    Average face mesh model

MNE – MEG and EEG analysis@visualisation

https://github.com/mne-tools/mne-python/tree/master/mne/data/fsaverage

4.    Average Brain mesh model and Brodmann meshes

are obtained indirectly from DSI Studio and ROI (txt data) which are used in that software and obtained by Freesurfer

https://surfer.nmr.mgh.harvard.edu/

Fibers:

This software uses fibers (trk files)obtained by DSI Studio, open-source diffusion MRI analysis tool. I used different algoritm for fibers coloring, because i want to accent difference between directions of fibers.

https://dsi-studio.labsolver.org/Home.

Data used with DSI Studio are originally from the WU-Minn HCP Consortium and distributed under the WU-Minn HCP open access :

HCP-1021

The HCP 1021 template was constructed from a total of 1021 subjects diffusion MRI data from the Human Connectome Project (2017 Q4, 1200-subject release). A multishell diffusion scheme was used, and the b-values were 1000, 2000, 3000 s/mm2. The number of diffusion sampling directions were 90, 90, and 90, respectively. The in-plane resolution was 1.25 mm. The slice thickness was 1.25 mm. The diffusion data were reconstructed in the MNI space using q-space diffeomorphic reconstruction (Yeh et al., Neuroimage, 58(1):91-9, 2011) to obtain the spin distribution function (Yeh et al., IEEE TMI, ;29(9):1626-35, 2010). A diffusion sampling length ratio of 2.5 was used, and the output resolution was 1 mm. The analysis was conducted using DSI Studio (http://dsi-studio.labsolver.org).