Functional connectivity dynamics: modeling the switching behavior of the resting state.
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TLDR
It is demonstrated that a slight enhancement of the non-linearity of the network nodes is sufficient to broaden the repertoire of possible network behaviors, leading to modes of fluctuations, reminiscent of some of the most frequently observed Resting State Networks.About:
This article is published in NeuroImage.The article was published on 2015-01-15 and is currently open access. It has received 479 citations till now. The article focuses on the topics: Resting state fMRI.read more
Citations
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Dynamic models of large-scale brain activity
TL;DR: Evidence supports the view that collective, nonlinear dynamics are central to adaptive cortical activity and aberrant dynamic processes appear to underlie a number of brain disorders.
Journal ArticleDOI
Conscious Processing and the Global Neuronal Workspace Hypothesis.
George A. Mashour,Pieter R. Roelfsema,Pieter R. Roelfsema,Jean-Pierre Changeux,Jean-Pierre Changeux,Jean-Pierre Changeux,Stanislas Dehaene,Stanislas Dehaene +7 more
TL;DR: The GNW hypothesis proposes that, in the conscious state, a non-linear network ignition associated with recurrent processing amplifies and sustains a neural representation, allowing the corresponding information to be globally accessed by local processors.
Journal ArticleDOI
Linking Structure and Function in Macroscale Brain Networks.
TL;DR: The current state of knowledge linking structure and function in macroscale brain networks is synthesized and it is argued that current models do not include the requisite biological detail to completely predict function.
Journal ArticleDOI
The dynamics of resting fluctuations in the brain: metastability and its dynamical cortical core
TL;DR: It is revealed that the human brain during resting state operates at maximum metastability, i.e. in a state of maximum network switching, which significantly pertain to the important role of computational connectomics in understanding principles of brain function.
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Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature
David Grayson,Damien A. Fair +1 more
TL;DR: Key areas ripe for future research are discussed in order to better characterize normative developmental trajectories, link these trajectories to biologic mechanistic events, as well as component behaviors and better understand the clinical implications and pathophysiological basis of aberrant network development.
References
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An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.
Rahul S. Desikan,Florent Ségonne,Bruce Fischl,Bruce Fischl,Brian T. Quinn,Bradford C. Dickerson,Deborah Blacker,Randy L. Buckner,Randy L. Buckner,Anders M. Dale,R. Paul Maguire,Bradley T. Hyman,Marilyn S. Albert,Ronald J. Killiany +13 more
TL;DR: An automated labeling system for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable and may be useful for both morphometric and functional studies of the cerebral cortex.
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Complex network measures of brain connectivity: uses and interpretations.
Mikail Rubinov,Olaf Sporns +1 more
TL;DR: Construction of brain networks from connectivity data is discussed and the most commonly used network measures of structural and functional connectivity are described, which variously detect functional integration and segregation, quantify centrality of individual brain regions or pathways, and test resilience of networks to insult.
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Dynamic causal modelling.
TL;DR: As with previous analyses of effective connectivity, the focus is on experimentally induced changes in coupling, but unlike previous approaches in neuroimaging, the causal model ascribes responses to designed deterministic inputs, as opposed to treating inputs as unknown and stochastic.
Journal ArticleDOI
Consistent resting-state networks across healthy subjects
Jessica S. Damoiseaux,Serge A.R.B. Rombouts,Frederik Barkhof,Philip Scheltens,Cornelis J. Stam,Stephen M. Smith,Christian F. Beckmann +6 more
TL;DR: Findings show that the baseline activity of the brain is consistent across subjects exhibiting significant temporal dynamics, with percentage BOLD signal change comparable with the signal changes found in task-related experiments.
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