Project Description

Modeling and understanding neurodegeneration from an engineering perspective is key to better understand the processes that undertake the human brain in diseases such as Alzheimer's disease, even at very early stages. For this purpose, robust and reliable characterization of structural and functional connectivity of the human brain at individual subjects (as opposed to group average representations) is critical. This project will use state of the art frameworks for processing brain data and modeling brain connections as well as for uncovering brain fingerprints that characterize individuals at different stages of neurodegeneration.

Data used in this project will be multi-modal, exploiting the best characteristics of different neuroimaging acquisition techniques such as diffusion weighted imaging, functional magnetic resonance imaging, magnetoencephalography and near-infrared spectroscopy. The datasets that will be assessed include: The Human Connectome Project (Aging cohort) , Alzheimer's Disease Neuroimaging Initiative and a cohort recruited in Spain by our collaborator in this project, Dr. Maestu, leading expert in neurodegeneration of the human brain.

Modeling of neurodegenerative effects in brain will use several techniques derived from network science and graph theory. Frameworks developed during this project will be posted as code toolboxes and will be freely available for the research community. 

Start Date

09/01/2021

Postdoc Qualifications

Ph.D in Biomedical Engineering or in Physics or similar. Expert in neuroimage data processing (software such as MRtrix, FSL, FreeSurfer, AFNI). Knowledge on data dimensionality techniques such us Principal Components Analysis and Independent Component Analysis. Expert on Linux bash scripting. Knowledge on using computing clusters and parallelization. Knowledge on Network Science and Graph Theory. High skills on Matlab programming.  

Co-Advisors

Joaquín Goñi
Assistant Professor
Head of the CONNplexity Lab
https://engineering.purdue.edu/ConnplexityLab
School of Industrial Engineering

Yunjie Tong
Assistant Professor
Head of the Tong Lab
https://engineering.purdue.edu/TongLab
Weldon School of Biomedical Engineering.

References

Rogier B Mars, Richard E Passingham, and Saad Jbabdi. Connectivity fingerprints: from areal descriptions to abstract spaces.Trends in cognitive sciences, 22(11):1026–1037, 2018.

The quest for identifiability in human functional connectomes (2018) Amico E, Goñi J. Nature Scientific Reports 8.1: 8254.

Uncovering differential identifiability in network properties of human brain functional connectomes. Meenusree Rajapandian, Enrico Amico, Kausar Abbas, Mario Ventresca and Joaquín Goñi

Kuhl, E. (2019). Connectomics of neurodegeneration. Nature neuroscience, 22(8), 1200-1202.

Brier, M. R., Thomas, J. B., & Ances, B. M. (2014). Network dysfunction in Alzheimer's disease: refining the disconnection hypothesis. Brain connectivity, 4(5), 299-311.