Functional connectivity patterns of human magnetoencephalographic recordings: a 'small-world' network?

By Cornelis J. Stam. Neuroscience Letters, 2004

553 citations recorded by the source corpus.

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In Cognitive Neuroscience

Citations in the corpus

Age- and gender-related differences in the cortical anatomical network (2009, background): “In terms of network efficiency, a small world network is the one with high Eglob and Eloc (i.e., very efficient both in global and local information transfer) (Latora and Marchiori, 2003).”
Functionally linked resting‐state networks reflect the underlying structural connectivity architecture of the human brain (2009, background): “Our study adds to the accumulating evidence that our brain is an integrated network of interconnected regions [Achard and Bullmore, 2007; Hagmann et al., 2008; Liu et al., 2008; Stam, 2004; Van den Heuvel et al., 2008c].”
Neurophysiological architecture of functional magnetic resonance images of human brain. (2005, background): “…from measures of synchronization between multiple (126) magnetoencephalography (MEG) Cerebral Cortex September 2005, V 15 N 9 1339 Downloaded from https://academic.oup.com/cercor/article-abstract/15/9/1332/288667 by guest on 29 July 2018 channels of ‘resting’ human brain dynamics (Stam, 2004).”
Exploring the brain network: a review on resting-state fMRI functional connectivity. (2010, result): “, 2006; Watts and Strogatz 1998), supporting the findings of MEG and EEG studies (Bassett et al., 2006; Micheloyannis et al., 2006a; Stam, 2004).”
A Small World of Neuronal Synchrony (2008, background): “…al. 2007), others on functional analyses of electroencephalographic (EEG) and magnetoencephalographic or fMRI signals, reflecting the activity of large populations of neurons (Stam 2004; Achard et al. 2006; Bassett et al. 2006; Micheloyannis et al. 2006; Achard and Bullmore 2007; Stam et al. 2007).”
A Resilient, Low-Frequency, Small-World Human Brain Functional Network with Highly Connected Association Cortical Hubs (2006, background): “There is evidence also for small-world properties of graphs inferred from functional connectivity matrices measured at a macroscopic (regional) scale in monkey and human neurophysiological data (Stephan et al., 2000; Stam, 2004; Salvador et al., 2005b) and at a mesoscopic (voxel) scale in human func”
Whole-brain anatomical networks: Does the choice of nodes matter? (2010, background): “…et al., 2006 28 Scalp sensors Stam et al., 2007 21 Scalp sensors MEG Bassett et al., 2006 275 Scalp sensors Deuker et al., 2009 204 Scalp sensors Stam, 2004 126 Scalp sensors Anatomical-MRI Bassett et al., 2008 104 Pick Atlas He et al., 2007, 2008 54 Jacob Atlas d-MRI vs. f-MRI Honey et al.,…”
Disrupted small-world networks in schizophrenia. (2008, result): “This issue is supported by many previous studies based on MEG (Stam, 2004), EEG (Micheloyannis et al., 2006b) and fMRI (Eguiluz et al., 2005; Salvador et al., 2005a; Achard et al., 2006).”
GRETNA: a graph theoretical network analysis toolbox for imaging connectomics (2015, background): “9:386. doi: 10.3389/fnhum.2015.00386 Recent studies have suggested that the brain’s structural and functional networks (i.e., connectomics) can be constructed by various imaging technologies (e.g., EEG/MEG; structural, diffusion and functional MRI) and further characterized by graph theory.”
Efficiency of Functional Brain Networks and Intellectual Performance (2009, background): “1a– d), expressed by L L random and 1 for T 0.5 and C Crandom and 1 for T 0.3 (one-sample t test, all p of 0.01, Bonferroni corrected for multiple comparisons of T, df 18), indicating a small-world organization (Sporns et al., 2004; Stam, 2004; Achard et al., 2006; van den Heuvel et al., 2008b).”
Studying the human brain anatomical network via diffusion-weighted MRI and Graph Theory (2008, unknown): “Functional human brain networks derived from functional Magnetic Resonance Imaging (fMRI), Electroencephalogram (EEG) and Magnetoencephalographic (MEG) data also exhibit small-world properties (Stam, 2004; Eguiluz et al., 2005; Salvador et al., 2005; Achard et al., 2006; Bassett et al., 2006).”
Graph Neural Networks in Network Neuroscience (2021, background): “which are derived from structural T1-weighted, diffusionweighted and resting-state functional MRI, respectively [7], [8], [9], [10], [11].”
NeuCube: A spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data (2014, unknown): “Magnetoencephalography (MEG) measures millisecond-long changes in magnetic fields created by the brain’s electrical currents.”
Graph theoretical analysis of magnetoencephalographic functional connectivity in Alzheimer's disease. (2009, unknown): “However, Ĉw was very close to one in both groups, and much lower than reported in other studies, where Ĉw was usually around two (Stam, 2004; Salvador et al., 2005; Achard et al., 2006; Bassett et al., 2006; Stam et al., 2007a).”
Small-world anatomical networks in the human brain revealed by cortical thickness from MRI. (2007, methodology): “The human brain is a large, interacting, complex network with nontrivial topological properties (Sporns et al. 2004; Stam 2004; Eguiluz et al. 2005; Salvador, Suckling, Coleman, et al. 2005; Achard et al. 2006; Stam et al. 2007).”