scholarly journals Structural and functional connectivity reconstruction with CATO - A Connectivity Analysis TOolbox

2021 ◽  
Author(s):  
Siemon C de Lange ◽  
Martijn P van den Heuvel
Keyword(s):  
Functional Mri ◽  
Resting State ◽  
Diffusion Weighted Imaging ◽  
Brain Connectivity ◽  
Connectivity Analysis ◽  
Imaging Data ◽  
Functional Connectome ◽  
Modular Software ◽  
Diffusion Weighted ◽  
Human Connectome Project

We describe a Connectivity Analysis TOolbox (CATO) for the reconstruction of structural and functional brain connectivity based on diffusion weighted imaging and resting-state functional MRI data. CATO is an integrative and modular software package that enables researchers to run end-to-end reconstructions from MRI data to structural and functional connectome maps, customize their analysis and utilize different software packages during the data preprocessing. The structural and functional connectome maps can be reconstructed with respect to user-defined (sub)cortical atlases providing aligned connectivity matrices for integrative multimodal analyses. We outline the structural and functional processing pipelines in CATO, the implementation in MATLAB and associated stand-alone application, and the calibration of performance with respect to simulated diffusion weighted imaging data and resting-state functional MRI data from the ICT2015 challenge and the Human Connectome Project. CATO is free open-source software and available at www.dutchconnectomelab.nl/CATO.

Individual Uniqueness in the Neonatal Functional Connectome

2021 ◽  
Author(s):  
Qiushi Wang ◽  
Yuehua Xu ◽  
Tengda Zhao ◽  
Zhilei Xu ◽  
Yong He ◽  
...  
Keyword(s):  
Individual Differences ◽  
Individual Identification ◽  
Imaging Data ◽  
Functional Connectome ◽  
Middle Range ◽  
Human Connectome Project ◽  
The Individual ◽  
And Behavior ◽  
Identification Analysis ◽  
The Brain

Abstract The functional connectome is highly distinctive in adults and adolescents, underlying individual differences in cognition and behavior. However, it remains unknown whether the individual uniqueness of the functional connectome is present in neonates, who are far from mature. Here, we utilized the multiband resting-state functional magnetic resonance imaging data of 40 healthy neonates from the Developing Human Connectome Project and a split-half analysis approach to characterize the uniqueness of the functional connectome in the neonatal brain. Through functional connectome-based individual identification analysis, we found that all the neonates were correctly identified, with the most discriminative regions predominantly confined to the higher-order cortices (e.g., prefrontal and parietal regions). The connectivities with the highest contributions to individual uniqueness were primarily located between different functional systems, and the short- (0–30 mm) and middle-range (30–60 mm) connectivities were more distinctive than the long-range (>60 mm) connectivities. Interestingly, we found that functional data with a scanning length longer than 3.5 min were able to capture the individual uniqueness in the functional connectome. Our results highlight that individual uniqueness is present in the functional connectome of neonates and provide insights into the brain mechanisms underlying individual differences in cognition and behavior later in life.

scholarly journals Sex Classification by Resting State Brain Connectivity

2019 ◽  
Vol 30 (2) ◽  
pp. 824-835 ◽  
Author(s):  
Susanne Weis ◽  
Kaustubh R Patil ◽  
Felix Hoffstaedter ◽  
Alessandra Nostro ◽  
B T Thomas Yeo ◽  
...  
Keyword(s):  
Resting State ◽  
Brain Connectivity ◽  
Brain Regions ◽  
Brain Organization ◽  
Functional Brain ◽  
Clear Cut ◽  
Human Connectome Project ◽  
Machine Learning Approach ◽  
Imaging Research ◽  
Functional Brain Organization

Abstract A large amount of brain imaging research has focused on group studies delineating differences between males and females with respect to both cognitive performance as well as structural and functional brain organization. To supplement existing findings, the present study employed a machine learning approach to assess how accurately participants’ sex can be classified based on spatially specific resting state (RS) brain connectivity, using 2 samples from the Human Connectome Project (n1 = 434, n2 = 310) and 1 fully independent sample from the 1000BRAINS study (n = 941). The classifier, which was trained on 1 sample and tested on the other 2, was able to reliably classify sex, both within sample and across independent samples, differing both with respect to imaging parameters and sample characteristics. Brain regions displaying highest sex classification accuracies were mainly located along the cingulate cortex, medial and lateral frontal cortex, temporoparietal regions, insula, and precuneus. These areas were stable across samples and match well with previously described sex differences in functional brain organization. While our data show a clear link between sex and regionally specific brain connectivity, they do not support a clear-cut dimorphism in functional brain organization that is driven by sex alone.

scholarly journals Global tractography of multi-shell diffusion-weighted imaging data using a multi-tissue model

NeuroImage ◽  
2015 ◽  
Vol 123 ◽  
pp. 89-101 ◽  
Author(s):  
Daan Christiaens ◽  
Marco Reisert ◽  
Thijs Dhollander ◽  
Stefan Sunaert ◽  
Paul Suetens ◽  
...  
Keyword(s):  
Diffusion Weighted Imaging ◽  
Imaging Data ◽  
Tissue Model ◽  
Diffusion Weighted

Detecting cognitive impairment in HIV-infected individuals using mutual connectivity analysis of resting state functional MRI

2020 ◽  
Vol 26 (2) ◽  
pp. 188-200
Author(s):  
Anas Z. Abidin ◽  
Adora M. DSouza ◽  
Giovanni Schifitto ◽  
Axel Wismüller
Keyword(s):  
Cognitive Impairment ◽  
Functional Mri ◽  
Resting State ◽  
Connectivity Analysis

scholarly journals Whole-brain connectivity analysis and classification of spinocerebellar ataxia type 7 by functional MRI

2014 ◽  
Vol 1 (1) ◽  
pp. 2 ◽  
Author(s):  
Carlos R Hernandez-Castillo ◽  
Víctor Galvez ◽  
Consuelo Morgado-Valle ◽  
Juan Fernandez-Ruiz
Keyword(s):  
Functional Mri ◽  
Spinocerebellar Ataxia ◽  
Brain Connectivity ◽  
Spinocerebellar Ataxia Type ◽  
Connectivity Analysis ◽  
Whole Brain ◽  
Spinocerebellar Ataxia Type 7

scholarly journals The ABCD and ABCD2 Scores and the Risk of Stroke following a TIA: A Narrative Review

2011 ◽  
Vol 2011 ◽  
pp. 1-12 ◽  
Author(s):  
Archit Bhatt ◽  
Vishal Jani
Keyword(s):  
Atrial Fibrillation ◽  
Diffusion Weighted Imaging ◽  
Prognostic Value ◽  
Risk Scores ◽  
Large Artery ◽  
Imaging Data ◽  
Short Term ◽  
Vascular Events ◽  
Diffusion Weighted ◽  
Abcd2 Score

The California, ABCD, and ABCD2 risk scores (ABCD system) were developed to help stratify short-term stroke risk in patients with TIA (transient ischemic attack). Beyond this scope, the ABCD system has been extensively used to study other prognostic information such as DWI (diffusion-weighted imaging) abnormalities, large artery stenosis, atrial fibrillation and its diagnostic accuracy in TIA patients, which are independent predictors of subsequent stroke in TIA patients. Our comprehensive paper suggested that all scores have and equivalent prognostic value in predicting short-term risk of stroke; however, the ABCD2 score is being predominantly used at most centers. The majority of studies have shown that more than half of the strokes in the first 90 days, occur in the first 7 days. The majority of patients studied were predominantly classified to have a higher ABCD/ABCD2 > 3 scores and were particularly at a higher short-term risk of stroke or TIA and other vascular events. However, patients with low risk ABCD2 score < 4 may have high-risk prognostic indicators, such as diffusion weighted imaging (DWI) abnormalities, large artery atherosclerosis (LAA), and atrial fibrillation (AF). The prognostic value of these scores improved if used in conjunction with clinical information, vascular imaging data, and brain imaging data. Before more data become available, the diagnostic value of these scores, its applicability in triaging patients, and its use in evaluating long-term prognosis are rather secondary; thus, indicating that the primary significance of these scores is for short-term prognostic purposes.

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