Network neuroscience

Nature Neuroscience, Journal Year: 2017, Volume and Issue: 20(3), P. 353 - 364

Published: Feb. 23, 2017

Language: Английский

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Networks beyond pairwise interactions: Structure and dynamics

Physics Reports, Journal Year: 2020, Volume and Issue: 874, P. 1 - 92

Published: June 13, 2020

The complexity of many biological, social and technological systems stems from the richness interactions among their units. Over past decades, a great variety complex has been successfully described as networks whose interacting pairs nodes are connected by links. Yet, in face-to-face human communication, chemical reactions ecological systems, can occur groups three or more cannot be simply just terms simple dyads. Until recently, little attention devoted to higher-order architecture real systems. However, mounting body evidence is showing that taking structure these into account greatly enhance our modeling capacities help us understand predict emerging dynamical behaviors. Here, we present complete overview field beyond pairwise interactions. We first discuss methods represent give unified presentation different frameworks used describe highlighting links between existing concepts representations. review measures designed characterize models proposed literature generate synthetic structures, such random growing simplicial complexes, bipartite graphs hypergraphs. introduce rapidly research on topology. focus novel emergent phenomena characterizing landmark processes, diffusion, spreading, synchronization games, when extended elucidate relations topology properties, conclude with summary empirical applications, providing an outlook current conceptual frontiers.

Language: Английский

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Controllability of structural brain networks

Nature Communications, Journal Year: 2015, Volume and Issue: 6(1)

Published: Oct. 1, 2015

Abstract Cognitive function is driven by dynamic interactions between large-scale neural circuits or networks, enabling behaviour. However, fundamental principles constraining these network processes have remained elusive. Here we use tools from control and theories to offer a mechanistic explanation for how the brain moves cognitive states drawn organization of white matter microstructure. Our results suggest that densely connected areas, particularly in default mode system, facilitate movement many easily reachable states. Weakly systems, difficult-to-reach Areas located on boundary communities, attentional integration segregation diverse systems. structural differences dictate their distinct roles controlling trajectories function.

Language: Английский

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Communication dynamics in complex brain networks

Nature reviews. Neuroscience, Journal Year: 2017, Volume and Issue: 19(1), P. 17 - 33

Published: Dec. 14, 2017

Language: Английский

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Dynamic reconfiguration of frontal brain networks during executive cognition in humans

Proceedings of the National Academy of Sciences, Journal Year: 2015, Volume and Issue: 112(37), P. 11678 - 11683

Published: Aug. 31, 2015

Significance Cognitive flexibility is hypothesized to require dynamic integration between brain areas. However, the time-dependent nature and distributed complexity of this remains poorly understood. Using recent advances in network science, we examine functional areas during a quintessential task that requires executive function. By linking regions (nodes) by their interactions (time-dependent edges), uncover nontrivial modular structure: groups cluster together into densely interconnected structures whose change execution. Individuals with greater reconfiguration frontal cortices show enhanced memory performance, score higher on neuropsychological tests challenging cognitive flexibility, suggesting forms fundamental neurophysiological mechanism for

Language: Английский

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Emotion and the prefrontal cortex: An integrative review.

Psychological Bulletin, Journal Year: 2017, Volume and Issue: 143(10), P. 1033 - 1081

Published: June 15, 2017

The prefrontal cortex (PFC) plays a critical role in the generation and regulation of emotion. However, we lack an integrative framework for understanding how different emotion-related functions are organized across entire expanse PFC, as prior reviews have generally focused on specific emotional processes (e.g., decision making) or anatomical regions orbitofrontal cortex). Additionally, psychological theories neuroscientific investigations proceeded largely independently because common framework. Here, provide comprehensive review functional neuroimaging, electrophysiological, lesion, structural connectivity studies 8 subregions spanning PFC. We introduce appraisal-by-content model, which provides new integrating diverse range empirical findings. Within this framework, appraisal serves unifying principle PFC's emotion, while relative content-specialization differentiating each subregion. A synthesis data from affective, social, cognitive neuroscience suggests that PFC preferentially involved assigning value to types inputs: exteroceptive sensations, episodic memories imagined future events, viscero-sensory signals, viscero-motor actions, others' mental states intentions), self-related information, ongoing emotions. discuss implications emotion regulation, value-based making, salience, refining theoretical models This unified generates hypotheses about mechanisms underlying adaptive maladaptive functioning. (PsycINFO Database Record

Language: Английский

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Application of Graph Theory for Identifying Connectivity Patterns in Human Brain Networks: A Systematic Review

Frontiers in Neuroscience, Journal Year: 2019, Volume and Issue: 13

Published: June 6, 2019

Background: Analysis of the human connectome using functional magnetic resonance imaging (fMRI) started in mid-1990s and attracted increasing attention attempts to discover neural underpinnings cognition neurological disorders. In general, brain connectivity patterns from fMRI data are classified as statistical dependencies (functional connectivity) or causal interactions (effective among various units. Computational methods, especially graph theory-based have recently played a significant role understanding architecture. Objectives: Thanks emergence theoretical analysis, main purpose current paper is systematically review how properties can emerge through distinct neuronal units cognitive applications fMRI. Moreover, this article provides an overview existing effective methods used construct network, along with their advantages pitfalls. Methods: systematic review, databases Science Direct, Scopus, arXiv, Google Scholar, IEEE Xplore, PsycINFO, PubMed, SpringerLink employed for exploring evolution computational 1990 present, focusing on theory. The Cochrane Collaboration's tool was assess risk bias individual studies. Results: Our results show that theory its implications neuroscience researchers since 2009 (as Human Connectome Project launched), because prominent capability characterizing behavior complex systems. Although approach be generally applied either during rest task performance, date, most articles focused resting-state connectivity. Conclusions: This insight into utilize measures make neurobiological inferences regarding mechanisms underlying well different

Language: Английский

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Topographic organization of the human subcortex unveiled with functional connectivity gradients

Nature Neuroscience, Journal Year: 2020, Volume and Issue: 23(11), P. 1421 - 1432

Published: Sept. 28, 2020

Language: Английский

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Activity flow over resting-state networks shapes cognitive task activations

Nature Neuroscience, Journal Year: 2016, Volume and Issue: 19(12), P. 1718 - 1726

Published: Oct. 10, 2016

Language: Английский

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Task-induced brain state manipulation improves prediction of individual traits

Nature Communications, Journal Year: 2018, Volume and Issue: 9(1)

Published: July 12, 2018

Abstract Recent work has begun to relate individual differences in brain functional organization human behaviors and cognition, but the best state reveal such relationships remains an open question. In two large, independent data sets, we here show that cognitive tasks amplify trait-relevant patterns of connectivity, predictive models built from task fMRI outperform resting-state data. Further, certain consistently yield better predictions fluid intelligence than others, generates best-performing varies by sex. By considering task-induced sex, model explains over 20% variance scores, as compared <6% explained rest-based models. This suggests identifying inducing right a given group can brain-behavior relationships, motivating paradigm shift rest- task-based connectivity analyses.

Language: Английский

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