Effects of Neural Synchrony on Surface EEG

Musall, Simon; Pföstl, Veronika von; Rauch, Alexander; Logothetis, Nikos K.; Whittingstall, Kevin

doi:10.1093/cercor/bhs389

Cited by 109 publications

(96 citation statements)

References 45 publications

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“…8 and 9), that amplitude and coherence of the LFPs are each separately correlated with the magnitude of the EEG signal. However, while Musall et al (2014) found significant partial correlations for both amplitude and coherence at all six frequency bands of interest (except for the alpha band, for which coherence was not significantly correlated), we found that LFP amplitude (Fig. 8), but not LFP coherence (Fig.…”

Section: Discussioncontrasting

confidence: 61%

“…4). Musall et al (2014) recorded simultaneous EEG and LFP during visual stimulation with three penetrating electrodes, which enabled them to assay the contribution of spatial coherence of the LFP signals to the amplitude of the EEG. They found, as we did (Figs.…”

Section: Discussionmentioning

confidence: 99%

“…The partial correlation between each pair of these three variables controlled for the third variable. Following Musall et al (2014), we analyzed six canonical frequency bands of interest: delta (2-4 Hz), theta (4 -8 Hz), alpha (8 -12), beta (12-24 Hz), low gamma (24 -50 Hz), and high gamma (50 -100 Hz). Values of amplitude and coherence were averaged across frequencies within each bin.…”

Section: Methodsmentioning

confidence: 99%

“…They found that the rate of MUA was negatively correlated with the voltage on the EEG electrode (referenced to a frontal site). In another case, Musall et al (2014) used the same methodology as Whittingstall and Logothetis (2009), but with three penetrating microelectrodes rather than one. This enabled them to test the effect of the coherence of LFPs across pairs of microelectrodes on the magnitude of EEG signals.…”

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Stimulus-dependent spiking relationships with the EEG

Snyder

2015

Journal of Neurophysiology

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Snyder AC, Smith MA. Stimulus-dependent spiking relationships with the EEG. J Neurophysiol 114: 1468 -1482. First published June 24, 2015 doi:10.1152/jn.00427.2015The development and refinement of noninvasive techniques for imaging neural activity is of paramount importance for human neuroscience. Currently, the most accessible and popular technique is electroencephalography (EEG). However, nearly all of what we know about the neural events that underlie EEG signals is based on inference, because of the dearth of studies that have simultaneously paired EEG recordings with direct recordings of single neurons. From the perspective of electrophysiologists there is growing interest in understanding how spiking activity coordinates with large-scale cortical networks. Evidence from recordings at both scales highlights that sensory neurons operate in very distinct states during spontaneous and visually evoked activity, which appear to form extremes in a continuum of coordination in neural networks. We hypothesized that individual neurons have idiosyncratic relationships to large-scale network activity indexed by EEG signals, owing to the neurons' distinct computational roles within the local circuitry. We tested this by recording neuronal populations in visual area V4 of rhesus macaques while we simultaneously recorded EEG. We found substantial heterogeneity in the timing and strength of spike-EEG relationships and that these relationships became more diverse during visual stimulation compared with the spontaneous state. The visual stimulus apparently shifts V4 neurons from a state in which they are relatively uniformly embedded in large-scale network activity to a state in which their distinct roles within the local population are more prominent, suggesting that the specific way in which individual neurons relate to EEG signals may hold clues regarding their computational roles. EEG; local field potential; spiking activity ELECTROENCEPHALOGRAPHY (EEG) has been a boon to human neuroscience. Because EEG is noninvasive, it is one of the few methods that can be used to measure human brain activity in both health and disease. Moreover, EEG has advantages over other neuroimaging methods. The cost is relatively low, compared with approaches such as functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG); there is no ionizing radiation, as with positron emission tomography (PET); the materials are portable (even usable with actively moving subjects; De Sanctis et al. 2012;Makeig et al. 2009), unlike nearly all alternatives; and the temporal resolution is exquisitely fine, unlike functional near-infrared spectroscopy (fNIRS) and fMRI. EEG covers a wide range of neurophysiological applications, from diagnosis of brain stem lesions to basic research on complex cognition.The principal limitation of EEG is spatial resolution. Typically, EEG is useful for implicating activity in parts of the brain on the order of a cubic centimeter (Sejnowski et al. 2014). The computational machinations of the neurons within ...

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Section: Discussioncontrasting

confidence: 61%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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confidence: 99%

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Stimulus-dependent spiking relationships with the EEG

Snyder

2015

Journal of Neurophysiology

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“…Neurofeedback has been used to self-regulate electroencephalography (EEG) amplitudes, which correlate with the degree of intracortical neuronal synchronization 16 . Indeed, neurofeedback-mediated reductions in parieto-occipital EEG amplitudes boosted visual attention 17 or curbed mind-wandering 18 , and neurofeedback-mediated increases in intracortical neuronal synchronization elicited improvements in tasks requiring internal processing, such as mental rotation 19 or musical performance 20 .…”

Section: Coherencementioning

confidence: 99%