The expanding horizons of network neuroscience: From description to prediction and control

Srivastava, Pragya; Fotiadis, Panagiotis; Parkes, Linden; Bassett, Dani S.

doi:10.1016/j.neuroimage.2022.119250

Cited by 19 publications

(14 citation statements)

References 296 publications

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“…Resting-state blood-oxygenation level-dependent (BOLD) functional magnetic resonance imaging (rs-fMRI) is extensively used for mapping resting-state functional connectivity (rs-fcMRI) and for providing brain-health assessments (Srivastava et al, 2022; van den Heuvel and Hulshoff Pol, 2010). This technique has been used in aging, Alzheimer’s disease (Vemuri et al, 2012) and stroke (Ovadia-Caro et al, 2014), among others, and is commonly applied in studying brain development and aging processes (Andrews-Hanna et al, 2007; Geerligs et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Assessment of the macrovascular contribution to resting-state fMRI functional connectivity at 3 Tesla

Zhong,

Tong,

Chen

2023

Preprint

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In resting-state functional magnetic resonance imaging (rs-fMRI) functional connectivity (FC) mapping, temporal correlation are widely assumed to reflect synchronized neural-related activaty. Although a large number of studies have demonstrated the potential vascular effects on FC, little research has been conducted on FC resulting from macrovascular signal fluctuations. Previously, Tong et al. found (Tong et al., 2019b) a robust anti-correlation between the fMRI signals in the internal carotid artery and the internal jugular vein (and the sagittal sinus). The present study extends the previous study to include all detectable major veins and arteries in the brain in a systematic analysis of the macrovascular contribution to the functional connectivity of the whole-GM. This study demonstrates that: 1) The macrovasculature consistently exhibited strong correlational connectivity among itself, with the sign of the correlations varying between arterial and venous connectivity; 2) GM connectivity was found to have a strong macrovascular contribution, stronger from veins than arteries; 3) functional connectivity originating from the macrovasculature displayed disproportionately high spatial variability compared to across all GM voxels; 4) macrovascular contributions to connectivity were still evident well beyond the confines of the macrovascular space. These findings highlight the extensive contribution to rs-fMRI BOLD and FC predominantly by large veins, but also by large arteries. These findings pave the way for future studies aimed at more comprehensively modeling and thereby removing these macrovascular contributions.

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Section: Introductionmentioning

confidence: 99%

Assessment of the macrovascular contribution to resting-state fMRI functional connectivity at 3 Tesla

Zhong,

Tong,

Chen

2023

Preprint

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“…This growing interest has expanded the number of options available in fMRI analysis pipelines. Further, the ongoing development of network science itself is likely to introduce even more options for graph-based fMRI data analysis (Srivastava et al, 2022). This expansion of available options reflects the field’s continuous development, and it does not necessarily imply a compromise in methodological rigor.…”

Section: Discussionmentioning

confidence: 99%

The multiverse of data preprocessing and analysis in graph-based fMRI: A systematic literature review of analytical choices fed into a decision support tool for informed analysis

Kristanto,

Burkhardt,

Thiel

et al. 2024

Preprint

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The large number of different analytical choices researchers use may be partly responsible for the replication challenge in neuroimaging studies. For robustness analysis, knowledge of the full space of options is essential. We conducted a systematic literature review to identify the analytical decisions in functional neuroimaging data preprocessing and analysis in the emerging field of cognitive network neuroscience. We found 61 different steps, with 17 of them having debatable options. Scrubbing, global signal regression, and spatial smoothing are among the controversial steps. There is no standardized order in which different steps are applied, and the options within several steps vary widely across studies. By aggregating the pipelines across studies, we propose three taxonomic levels to categorize analytical choices: 1) inclusion or exclusion of specific steps, 2) distinct sequencing of steps, and 3) parameter tuning within steps. To facilitate access to the data, we developed a decision support app with high educational value called METEOR, which allows researchers to explore the space of choices as reference for well-informed robustness (multiverse) analysis.

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“…The SC's Laplacian eigenmodes may be thought of as the substrate on which functional patterns of the brain are established via a process of network transmission (Atasoy et al, 2016 ; Robinson et al, 2016 ; Abdelnour et al, 2018 ; Preti and Van De Ville, 2019 ; Glomb et al, 2020 ). Another class of models, the linear time-invariant system models based on the SC, have also been widely used to estimate brain controllability and energy required to transition to different states (Gu et al, 2015 , 2017 ; Tang and Bassett, 2018 ; Stiso et al, 2019 ; Srivastava et al, 2022 ).…”

Section: Mathematical Modelsmentioning

confidence: 99%

Structure-function models of temporal, spatial, and spectral characteristics of non-invasive whole brain functional imaging

2022

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We review recent advances in using mathematical models of the relationship between the brain structure and function that capture features of brain dynamics. We argue the need for models that can jointly capture temporal, spatial, and spectral features of brain functional activity. We present recent work on spectral graph theory based models that can accurately capture spectral as well as spatial patterns across multiple frequencies in MEG reconstructions.

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The expanding horizons of network neuroscience: From description to prediction and control

Cited by 19 publications

References 296 publications

Assessment of the macrovascular contribution to resting-state fMRI functional connectivity at 3 Tesla

Assessment of the macrovascular contribution to resting-state fMRI functional connectivity at 3 Tesla

The multiverse of data preprocessing and analysis in graph-based fMRI: A systematic literature review of analytical choices fed into a decision support tool for informed analysis

Structure-function models of temporal, spatial, and spectral characteristics of non-invasive whole brain functional imaging

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