Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review

NeuroImage, Journal Year: 2022, Volume and Issue: 249, P. 118870 - 118870

Published: Jan. 1, 2022

Diffusion magnetic resonance imaging (dMRI) tractography is an advanced technique that enables in vivo reconstruction of the brain's white matter connections at macro scale. It provides important tool for quantitative mapping structural connectivity using measures or tissue microstructure. Over last two decades, study brain dMRI has played a prominent role neuroimaging research landscape. In this paper, we provide high-level overview how used to enable analysis health and disease. We focus on types analyses tractography, including: 1) tract-specific refers typically hypothesis-driven studies particular anatomical fiber tracts, 2) connectome-based more data-driven generally entire brain. first review methodology involved three main processing steps are common across most approaches including methods correction, segmentation quantification. For each step, aim describe methodological choices, their popularity, potential pros cons. then have matter, focusing applications neurodevelopment, aging, neurological disorders, mental neurosurgery. conclude that, while there been considerable advancements technologies breadth applications, nevertheless remains no consensus about "best" researchers should remain cautious when interpreting results clinical applications.

Language: Английский

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Global waves synchronize the brain’s functional systems with fluctuating arousal

Science Advances, Journal Year: 2021, Volume and Issue: 7(30)

Published: July 21, 2021

Traveling waves spatiotemporally organize brain-wide activity in synchrony with ongoing arousal fluctuations.

Language: Английский

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Brain network communication: concepts, models and applications

Nature reviews. Neuroscience, Journal Year: 2023, Volume and Issue: 24(9), P. 557 - 574

Published: July 12, 2023

Language: Английский

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Structural-functional brain network coupling predicts human cognitive ability

NeuroImage, Journal Year: 2024, Volume and Issue: 290, P. 120563 - 120563

Published: March 16, 2024

Individual differences in general cognitive ability (GCA) have a biological basis within the structure and function of human brain. Network neuroscience investigations revealed neural correlates GCA structural as well functional brain networks. However, whether relationship between networks, structural-functional network coupling (SC-FC coupling), is related to individual remains an open question. We used data from 1030 adults Human Connectome Project, derived connectivity diffusion weighted imaging, resting-state fMRI, assessed latent g-factor 12 tasks. Two similarity measures six communication were model possible interactions arising SC-FC was estimated degree which these align with actual connectivity, providing insights into different strategies. At whole-brain level, higher associated coupling, but only when considering path transitivity strategy. Taking region-specific variations strategy account differentiating positive negative associations GCA, allows for prediction scores cross-validated framework (correlation predicted observed scores: r = .25, p < .001). The same also predicts completely independent sample (N 567, .19, Our results propose neurobiological correlate suggest strategies efficient information processing predictive ability.

Language: Английский

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The architecture of the human default mode network explored through cytoarchitecture, wiring and signal flow

Nature Neuroscience, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 28, 2025

Abstract The default mode network (DMN) is implicated in many aspects of complex thought and behavior. Here, we leverage postmortem histology vivo neuroimaging to characterize the anatomy DMN better understand its role information processing cortical communication. Our results show that cytoarchitecturally heterogenous, containing cytoarchitectural types are variably specialized for unimodal, heteromodal memory-related processing. Studying diffusion-based structural connectivity combination with cytoarchitecture, found contains regions receptive input from sensory cortex a core relatively insulated environmental input. Finally, analysis signal flow effective models showed unique amongst networks balancing output across levels hierarchies. Together, our study establishes an anatomical foundation which accounts broad plays human brain function cognition can be developed.

Language: Английский

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Network communication models improve the behavioral and functional predictive utility of the human structural connectome

Network Neuroscience, Journal Year: 2020, Volume and Issue: 4(4), P. 980 - 1006

Published: Jan. 1, 2020

The connectome provides the structural substrate facilitating communication between brain regions. We aimed to establish whether accounting for polysynaptic in connectomes would improve prediction of interindividual variation behavior as well increase structure-function coupling strength. Connectomes were mapped 889 healthy adults participating Human Connectome Project. To account signaling, transformed into matrices each 15 different network models. Communication (a) used perform predictions five data-driven behavioral dimensions and (b) correlated resting-state functional connectivity (FC). While FC was most accurate predictor behavior, models, particular communicability navigation, improved performance connectomes. also strengthened coupling, with navigation shortest paths models leading 35–65% increases association strength FC. combined results a single ranking that insight which may more faithfully recapitulate underlying neural signaling patterns. Comparing across multiple mapping pipelines suggested modeling is particularly beneficial sparse high-resolution conclude can augment predictive utility human connectome.

Language: Английский

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Signal diffusion along connectome gradients and inter-hub routing differentially contribute to dynamic human brain function

NeuroImage, Journal Year: 2020, Volume and Issue: 224, P. 117429 - 117429

Published: Oct. 7, 2020

Human cognition is dynamic, alternating over time between externally-focused states and more abstract, often self-generated, patterns of thought. Although cognitive neuroscience has documented how networks anchor particular modes brain function, mechanisms that describe transitions distinct functional remain poorly understood. Here, we examined time-varying changes in function emerge within the constraints imposed by macroscale structural network organization. Studying a large cohort healthy adults (n = 326), capitalized on manifold learning techniques identify low dimensional representations connectome organization decomposed neurophysiological activity into their transition using Hidden Markov Models. Structural predicted dynamic anchored sensorimotor systems those transmodal states. Connectome topology analyses revealed involving traversed short intermediary distances adhered strongly to communication diffusion. Conversely, involved spatially distributed hubs increasingly engaged long-range routing. These findings establish structure cortex optimized allow neural freedom vary processing, so provides key insight give rise flexibility human cognition.

Language: Английский

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The structural connectome constrains fast brain dynamics

eLife, Journal Year: 2021, Volume and Issue: 10

Published: July 9, 2021

Brain activity during rest displays complex, rapidly evolving patterns in space and time. Structural connections comprising the human connectome are hypothesized to impose constraints on dynamics of this activity. Here, we use magnetoencephalography (MEG) quantify extent which fast neural brain constrained by structural inferred from diffusion MRI tractography. We characterize spatio-temporal unfolding whole-brain at millisecond scale source-reconstructed MEG data, estimating probability that any two regions will significantly deviate baseline consecutive time epochs. find relates to, likely affects, rapid spreading neuronal avalanches, evidenced a significant association between these transition probabilities connectivity strengths (r = 0.37, p<0.0001). This finding opens new avenues study relationship structure dynamics.

Language: Английский

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Signal propagation via cortical hierarchies

Network Neuroscience, Journal Year: 2020, Volume and Issue: 4(4), P. 1072 - 1090

Published: Jan. 1, 2020

The wiring of the brain is organized around a putative unimodal-transmodal hierarchy. Here we investigate how this intrinsic hierarchical organization shapes transmission information among regions. positioning individual regions was quantified by applying diffusion map embedding to resting-state functional MRI networks. Structural networks were reconstructed from spectrum imaging and topological shortest paths all computed. Sequences nodes encountered along path then labeled their position, tracing out motifs. We find that cortical hierarchy guides communication in network. Specifically, are more likely forward signals closer cover range unimodal transmodal regions, potentially enriching or diversifying en route. also evidence systematic detours, particularly attention networks, where rerouted. Altogether, present work highlights signal exchange imparts behaviorally relevant patterns

Language: Английский

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Network communication models narrow the gap between the modular organization of structural and functional brain networks

NeuroImage, Journal Year: 2022, Volume and Issue: 257, P. 119323 - 119323

Published: May 20, 2022

Structural and functional brain networks are modular. Canonical systems, such as the default mode network, well-known modules of human have been implicated in a large number cognitive, behavioral clinical processes. However, delineated structural inferred from tractography generally do not recapitulate canonical systems. Neuroimaging evidence suggests that connectivity between regions same systems is always underpinned by anatomical connections. As such, direct alone would be insufficient to characterize modular organization brain. Here, we demonstrate augmenting with models indirect (polysynaptic) communication unveils network architecture more closely resembles brain's established We find diffusion polysynaptic connectivity, particularly communicability, narrow gap 20-60%, whereas routing based on single efficient paths improve mesoscopic structure-function correspondence. This emerge constraints imposed local structure facilitates diffusive neural communication. Our work establishes importance modeling understand basis

Language: Английский

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