High-resolution connectomic fingerprints: Mapping neural identity and behavior

S Mansour L; Y Tian; BTT Yeo; V Cropley; A Zalesky

Journal article

High-resolution connectomic fingerprints: Mapping neural identity and behavior

S Mansour L, Y Tian, BTT Yeo, V Cropley, A Zalesky

Neuroimage | ACADEMIC PRESS INC ELSEVIER SCIENCE | Published : 2021

DOI: 10.1016/j.neuroimage.2020.117695

Abstract

Connectomes are typically mapped at low resolution based on a specific brain parcellation atlas. Here, we investigate high-resolution connectomes independent of any atlas, propose new methodologies to facilitate their mapping and demonstrate their utility in predicting behavior and identifying individuals. Using structural, functional and diffusion-weighted MRI acquired in 1000 healthy adults, we aimed to map the cortical correlates of identity and behavior at ultra-high spatial resolution. Using methods based on sparse matrix representations, we propose a computationally feasible high-resolution connectomic approach that improves neural fingerprinting and behavior prediction. Using this hig..

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University of Melbourne Researchers

Ye Ella Tian Author

Vanessa Cropley Author

Andrew Zalesky Author

Sina Mansour L. Author

Related Projects (1)

NEUROPSYCHIATRIC CONNECTOMICS

Mental illness is the largest single cause of disability in Australia. While mental illness is increasingly recognised as a disorder of the ..

Grants

Awarded by National Institutes of Health

Funding Acknowledgements

Data were provided by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University. The data analysis was supported by SPARTAN High Performance Computing System at the University of Melbourne (Meade et al., 2017), and also supported by use of the Melbourne Research Cloud (MRC) providing Infrastructure-as-a-Service (IaaS) cloud computing to the University of Melbourne researchers through the NeCTAR Research Cloud, a collaborative Australian research platform supported by the NCRIS-funded Australian Research Data Commons (ARDC). S.M.L. is funded by a Melbourne Research Scholarship. B.T.T.Y. is funded by the Singapore National Research Foundation (NRF) Fellowship (Class of 2017) and the National University of Singapore Yong Loo Lin School of Medicine (NUHSRO/2020/124/TMR/LOA). V.C. was supported by a National Health and Medical Research Council (NHMRC) Investigator Grant (1177370). A.Z. is supported by the Australian National Health and Medical Research Council (NHMRC) Senior Research Fellowship B (1136649).