Development of new tools for the study of human brain connectomics

Project Type: Regular FONDECYT #1161427
Position: Head Researcher
Award Year: 2016. Ending Year: 2019.

Description

This project aims to continue with the development and optimization of tools for the study and analysis of the brain connectomics, using data mainly from Diffusion Magnetic Resonance Imaging (dMRI), focused on the study of the Human Connectome.

The study of the Human Connectome has awakened a great interested in the scientific community for some years, and has promoted large initiatives like the Human Connectome Project (http://www.humanconnectomeproject.org/) or the Human Brain Project (https://www.humanbrainproject.eu/).

Its main objective is to know in more detail the structure and operation of the brain and be able to construct a diagram of the brain regions and their connections. In this analysis a large quantity of modalities, and they involve the study of anatomical, functional, and clinical data, among others.

In the case of this project, the studies are based in the study of the connectivity, based mainly on High Angular Resolution Diffusion Imaging (HARDI) images.

The main objective is to provide the community with new tools that allow the construction of connectomes, more representative of the underlying anatomical connectivity.

The developments aim to:

  • Improve the analysis of the reproducibility of short association fascicles of the brain.

  • Continue the development of the optimized brain tracts visualization and manipulation tool.

  • Develop a new fiber clustering algorithm based on the form.

  • Evaluate the feasibility of creating a cortical parcellation starting from brain fibers fascicles.

Undergraduate Theses related to the project

Student Thesis Defense Date
Felipe Silva V. Biomedical Engineering Thesis: “Cortical parcellation method based on a graph representation of brain connections” April 1st, 2019.
Daniela Pinto D. Biomedical Engineering Thesis: “Segmentation of short brain fibers based on their form starting from difussion magnetic resonance imaging.” August 30th, 2018.
Ignacio Espinoza C. Biomedical Engineering Thesis: “Virtual reality software for the exploration of the brain in 3D.” August 29th, 2018.
Claudio Huaiqueo T. Biomedical Engineering Thesis: “Parcellation of the brain cortex starting from fiber fascicles.” April 5th, 2018.
Diego Carrasco V. Electronic Engineering Thesis: “Brain fibers visualization and manipulation software” December 30th, 2016.
Edgardo Cabrera F. Electronic Engineering Thesis: “Brain fibers clustering using distance measure based on the form” August 22nd, 2016.

Postgraduate Theses related to the project

Student Thesis Defense Date
Claudio Román G. Master in Engineering Sciences w/m in Electrical Engineering. “Segmentation of short brain fibers based on hierarchical Clustering based on HARDI database” January 26th, 2017.
Miguel Guevara O. Master in Engineering Sciences w/m in Electrical Engineering.
“Parcellation of the brain cortex based on fiber atlas calculated from tractography”
January 30th, 2016.

Publications

1012, 2018

Parallel optimization for the segmentation of fiber fascicles in massive tractography data sets

A. Vázquez, N. López-López, M. Figueroa, C. Hernández, P. Guevara. Optimización paralela para la segmentación de fascículos de fibras en conjuntos masivos de datos de tractografía (Parallel optimization for the segmentation of fiber fascicles in massive tractography data sets). XXVII Congress of Electronics-Electricity (INGELECTRA 2018), Valdivia, Chile, 2018. First place in postgraduate category.

612, 2018

Virtual Reality Software for 3D Exploration of the Brain

I. Espinoza, P. Guevara. Software de realidad virtual para exploración del cerebro en 3D (Virtual Reality Software for 3D Exploration of the Brain). 2nd National Congress of Electronics Engineering, CONACINEL 2018, Valdivia, Chile, 2018. First place, Paper contest.

112, 2018

Local structural connectivity is associated with social cognition in autism spectrum disorder

M. A. d'Albis, P. Guevara, M. Guevara, C. Laidi, J. Boisgontier, S. Sarrazin, D. Duclap, R. Delorme, F. Bolognani, C. Czech, C. Bouquet, M. Ly-Le Moal, Š. Holiga, A. Amestoy, I. Scheid, A. Gaman, C. Poupon, J.-F. Mangin, J. Houenou. Local structural connectivity is associated with social cognition in autism spectrum disorder. Brain 141:12, p3472-3481, 2018. DOI: https://doi.org/10.1093/brain/awy275

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