Regionconnect: Rapidly extracting standardized brain connectivity information in voxel-wise neuroimaging studies

Qi, Xiaoxiao; Arfanakis, Konstantinos

doi:10.1016/j.neuroimage.2020.117462

Cited by 30 publications

(28 citation statements)

References 72 publications

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“…Existing evidence also suggests altered functional connectivity between PCC and amygdala associated with obesity. 69 Pathological changes affecting those regions might therefore result in impaired processing and regulation of emotions related to food intake control. 70,71 One of the possible assumptions could be that increased food intake results from insufficient emotional control.…”

Section: Discussionmentioning

confidence: 99%

A systematic review of diffusion tensor imaging studies in obesity

2021

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Obesity is a major global health problem leading to serious complications. It has been consistently associated with alterations in brain structure. Diffusion tensor imaging is used to examine brain white matter microstructure by assessing the dynamics of water diffusion in white matter tracts. Fractional anisotropy and mean diffusivity are two parameters measuring the directionality and rate of diffusion, respectively.Changes in these indices associated with obesity have been previously reported in numerous fiber tracts. This systematic review investigates microstructural white matter alterations in obesity using diffusion tensor imaging. A computerized search was performed in PubMed, Web of Science, and Livivo databases. Based on the inclusion/exclusion criteria, 31 cross-sectional studies comparing individuals with obesity and lean controls were identified. The studies included mixed-gender samples of children, young, middle-aged, and older adults. The majority of included studies reported decreased fractional anisotropy and increased mean diffusivity associated with elevated body mass index, suggesting white matter abnormalities. Nevertheless, a pattern of alterations is inconsistent across studies. This could be explained by several potential biases assessed by the National Institute of Health quality assessment tool. Furthermore, a direct assessment of body fat is recommended for a more accurate characterization of the brain-body relationship.

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Section: Discussionmentioning

confidence: 99%

A systematic review of diffusion tensor imaging studies in obesity

2021

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“…Most frequently reported WM tracts were used to generate ROIs in an IIT space using the mean FA template. The "regionconnect" algorithm was used to integrate information across selected WM ROI voxels and generate probable pairs of GM regions connected through that ROI 48 . The analysis was performed in FSLeyes (FMRIB, University of Oxford, UK) using ICBM-DTI-81 white-matter labels and JHU white-matter tractography atlases.…”

Section: Methodsmentioning

confidence: 99%

A systematic review of diffusion tensor imaging studies in obesity

Okudzhava

Heldmann

Münte

2021

Preprint

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“…The structural connectome data were obtained from the IIT Human Brain Atlas (V.5.0) (xhttps://www.nitrc.org/projects/iit/) and generated using artefact-free MRI data from 72 subjects (Qi and Arfanakis, 2021).…”

Section: Structural Connectomementioning

confidence: 99%

Network diffusion model predicts neurodegeneration in limb-onset amyotrophic lateral sclerosis

Bhattarai

Chen

Chua

et al. 2021

Preprint

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The trans-neural propagation of phosphorylated 43-kDa transactive response DNA-binding protein (pTDP-43) contributes to neurodegeneration in Amyotrophic Lateral Sclerosis (ALS). We investigated whether Network Diffusion Model (NDM), a biophysical model of spread of pathology via the brain connectome, could capture the severity and progression of neurodegeneration (atrophy) in ALS. We measured degeneration in limb-onset ALS patients (n=14 at baseline, 12 at 6-months, and 9 at 12 months) and controls (n=12 at baseline) using FreeSurfer analysis on the structural T1-weighted Magnetic Resonance Imaging (MRI) data. The NDM was simulated on the canonical structural connectome from the IIT Human Brain Atlas. To determine whether NDM could predict the atrophy pattern in ALS, the accumulation of pathology modelled by NDM was correlated against atrophy measured using MRI. The cross-sectional analyses revealed that the network diffusion seeded from the inferior frontal gyrus (pars triangularis and pars orbitalis) significantly predicts the atrophy pattern in ALS compared to controls. Whereas, atrophy over time with-in the ALS group was best predicted by seeding the network diffusion process from the inferior temporal gyrus at 6-month and caudal middle frontal gyrus at 12-month. Our findings suggest the involvement of extra-motor regions in seeding the spread of pathology in ALS. Importantly, NDM was able to recapitulate the dynamics of pathological progression in ALS. Understanding the spatial shifts in the seeds of degeneration over time can potentially inform further research in the design of disease modifying therapeutic interventions in ALS.

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Regionconnect: Rapidly extracting standardized brain connectivity information in voxel-wise neuroimaging studies

Cited by 30 publications

References 72 publications

A systematic review of diffusion tensor imaging studies in obesity

A systematic review of diffusion tensor imaging studies in obesity

A systematic review of diffusion tensor imaging studies in obesity

Network diffusion model predicts neurodegeneration in limb-onset amyotrophic lateral sclerosis

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