Electrophysiological correlates of the brain's intrinsic large-scale functional architecture

By Biyu J. He, Abraham Z. Snyder, John M. Zempel, M. Smyth, Marcus E. Raichle. Proceedings of the National Academy of Sciences of the United States of America, 2008

685 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/f854ae2f8f84110d8941471ac533421d6df5c2d8

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In Cognitive Neuroscience

Citations in the corpus

Role of local network oscillations in resting-state functional connectivity (2011, background): “As BOLD observations have been found to have counterparts in the neural activity, in particular in the slow power fluctuations of the LFP in the gamma frequency range (Leopold et al., 2003; Shmuel and Leopold, 2008; Nir et al., 2008; He et al., 2008; Miller et al., 2009; Schölvinck et al., 2010), we”
Functional connectivity dynamically evolves on multiple time-scales over a static structural connectome: Models and mechanisms (2017, background): “…local increases in the power of neural activity, not only in the gamma-frequency band (Logothetis et al., 2001, Leopold et al., 2003, Nir et al., 2007), but also at lower frequencies (He et al., 2008, Scholvinck et al., 2010, Magri et al., 2012, Tagliazucchi et al., 2012b, Keller et al., 2013).”
Neural basis of global resting-state fMRI activity (2010, background): “In particular, electrophysiological studies in both humans and animals point to slow fluctuations in high-frequency “gamma” local field potential (LFP) power (>30 Hz) as exhibiting spatial coherence over long timescales (4, 42, 43), with some evidence suggesting that this coherence is strongest betw”
A Convergent Functional Architecture of the Insula Emerges Across Imaging Modalities (2012, positive): “, 2008), electrophysiological measures of neuronal activity (He et al., 2008; Keller et al., 2011), and static measures of brain structure (Mars et al.”
Schizophrenia, neuroimaging and connectomics (2012, background): “…such conditions recapitulates well-known task-evoked co-activation patterns (Smith et al., 2009) and is correlated with underlying anatomical connectivity (Honey et al., 2009; Skudlarski et al., 2008; Zalesky and Fornito, 2009) and synchronized oscillations in neuronal activity (He et al., 2008).”
The Nuisance of Nuisance Regression: Spectral Misspecification in a Common Approach to Resting-State fMRI Preprocessing Reintroduces Noise and Obscures Functional Connectivity (2013, background): “The BOLD signal measures metabolic changes that result from neural activity (Magri et al., 2012), and during resting-state fMRI, BOLD fluctuations reflect spontaneous neural activity, which are strongest in the .009 Hz – .08 Hz frequency range (He et al., 2008; Schölvinck et al., 2010).”
Large-Scale Brain Networks in Cognition: Emerging Principles (2010, methodology): “Although the method relies on analysis of low-frequency signals in fMRI data, electrophysiological studies point to a reliable neurophysiological basis for these signals (He et al., 2008; Nir et al., 2008).”
Clinical applications of the functional connectome (2013, positive): “Encouragingly, initial efforts to validate R-fMRI using intracranial approaches such as electrocorticography and corticocortical evoked potentials have demonstrated good correspondence with R-fMRI results (He et al., 2008; Keller et al., 2011).”
Saliency, switching, attention and control: a network model of insula function (2010, positive): “While the method relies on analysis of low-frequency signals in fMRI data, electrophysiological studies point to a neuronal basis for these signals (He et al. 2008; Nir et al. 2008).”
Experimental and theoretical approaches to conscious processing. (2011, background): “…but such strategic control appears to require consciousness (Posner et al., 1975/2004) and is not deployed when the stimuli are masked or unattended and therefore are not consciously detected (Heinemann et al., 2009; Kinoshita et al., 2008; Merikle and Joordens, 1997; Van den Bussche et al., 2008).”
Predicting human resting-state functional connectivity from structural connectivity (2009, methodology): “Studies, which compare fMRI FC against FC in modalities with higher sampling rates (16, 46, 47) remain crucial in determining the potential cognitive and behavioral significance of slow correlated fluctuations in the BOLD signal.”
Periodic changes in fMRI connectivity (2012, neutral): “Recent work has shown the different brain networks have distinct spectral profiles (He et al., 2008, 2010; Niazy et al., 2011).”
Questions and controversies in the study of time-varying functional connectivity in resting fMRI (2020, positive): “…directly comparable to BOLD ﬂuctuations ( < 1 Hz) also contribute substantially to measures of functional connectivity and TVFC (Grooms et al., 2017; He et al., 2008; Hiltunen et al., 2014; Pan, Thompson, Magnuson, Jaeger, & Keilholz, 2013; G. J. Thompson, Pan, Magnuson, Jaeger, & Keilholz,…”
EEG correlates of time-varying BOLD functional connectivity (2013, neutral): “5 Hz)were found to have a spatial structure that alignedwith a sensorimotor network defined by resting-state BOLD correlations (He et al., 2008).”
Scaling Brain Size, Keeping Timing: Evolutionary Preservation of Brain Rhythms (2013, positive): “…reflecting the fact that slow oscillations generate large, synchronous membrane-potential fluctuations in many neurons in brain-wide networks (He et al., 2008), whereas faster oscillations are associated with smaller changes in membrane potential in a limited number of cells, that are…”