[HTML][HTML] Quantitative map** of the brain's structural connectivity using diffusion MRI tractography: A review

F Zhang, A Daducci, Y He, S Schiavi, C Seguin… - Neuroimage, 2022 - Elsevier
Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging
technique that enables in vivo reconstruction of the brain's white matter connections at …

Common misconceptions, hidden biases and modern challenges of dMRI tractography

F Rheault, P Poulin, AV Caron, E St-Onge… - Journal of neural …, 2020 - iopscience.iop.org
The human brain is a complex and organized network, where the connection between
regions is not achieved with single axons crisscrossing each other but rather millions of …

Hi-GCN: A hierarchical graph convolution network for graph embedding learning of brain network and brain disorders prediction

H Jiang, P Cao, MY Xu, J Yang, O Zaiane - Computers in Biology and …, 2020 - Elsevier
Purpose Recently, brain connectivity networks have been used for the classification of
neurological disorder, such as Autism Spectrum Disorders (ASD) or Alzheimer's disease …

Large-scale DCMs for resting-state fMRI

A Razi, ML Seghier, Y Zhou, P McColgan… - Network …, 2017 - direct.mit.edu
This paper considers the identification of large directed graphs for resting-state brain
networks based on biophysical models of distributed neuronal activity, that is, effective …

[HTML][HTML] The effect of network thresholding and weighting on structural brain networks in the UK Biobank

CR Buchanan, ME Bastin, SJ Ritchie, DC Liewald… - NeuroImage, 2020 - Elsevier
Whole-brain structural networks can be constructed using diffusion MRI and probabilistic
tractography. However, measurement noise and the probabilistic nature of the tracking …

[HTML][HTML] Surface-based single-subject morphological brain networks: effects of morphological index, brain parcellation and similarity measure, sample size-varying …

Y Li, N Wang, H Wang, Y Lv, Q Zou, J Wang - NeuroImage, 2021 - Elsevier
Morphological brain networks, in particular those at the individual level, have become an
important approach for studying the human brain connectome; however, relevant …

TE-HI-GCN: An ensemble of transfer hierarchical graph convolutional networks for disorder diagnosis

L Li, H Jiang, G Wen, P Cao, M Xu, X Liu, J Yang… - Neuroinformatics, 2022 - Springer
Accurate diagnosis of psychiatric disorders plays a critical role in improving the quality of life
for patients and potentially supports the development of new treatments. Graph …

Signed graph representation learning for functional-to-structural brain network map**

H Tang, L Guo, X Fu, Y Wang, S Mackin, O Ajilore… - Medical image …, 2023 - Elsevier
MRI-derived brain networks have been widely used to understand functional and structural
interactions among brain regions, and factors that affect them, such as brain development …

[HTML][HTML] Multidimensional associations between cognition and connectome organization in temporal lobe epilepsy

R Rodríguez-Cruces, BC Bernhardt, L Concha - NeuroImage, 2020 - Elsevier
Objective Temporal lobe epilepsy (TLE) is known to affect large-scale structural networks
and cognitive function in multiple domains. The study of complex relations between …

[HTML][HTML] Data-driven subty** of executive function–related behavioral problems in children

J Bathelt, J Holmes, DE Astle, S Gathercole… - Journal of the American …, 2018 - Elsevier
Objective Executive functions (EF) are cognitive skills that are important for regulating
behavior and for achieving goals. Executive function deficits are common in children who …