scholarly journals Cross Frequency Coupling during the resting state with and without visual input

2012 ◽  
Vol 12 (9) ◽  
pp. 131-131
Author(s):  
R. Sokoliuk ◽  
R. VanRullen
Keyword(s):  
Resting State ◽  
Visual Input ◽  
Frequency Coupling ◽  
Cross Frequency Coupling

scholarly journals Altered cross-frequency coupling in resting-state MEG after mild traumatic brain injury

2016 ◽  
Vol 102 ◽  
pp. 1-11 ◽  
Author(s):  
Marios Antonakakis ◽  
Stavros I. Dimitriadis ◽  
Michalis Zervakis ◽  
Sifis Micheloyannis ◽  
Roozbeh Rezaie ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Mild Traumatic Brain Injury ◽  
Resting State ◽  
Frequency Coupling ◽  
Cross Frequency Coupling

scholarly journals Dissociating harmonic and non-harmonic phase-amplitude coupling in the human brain

2020 ◽  
Author(s):  
Janet Giehl ◽  
Nima Noury ◽  
Markus Siegel
Keyword(s):  
Human Brain ◽  
Resting State ◽  
Higher Harmonics ◽  
Spectral Leakage ◽  
Harmonic Phase ◽  
Harmonic Signals ◽  
Cast Doubt ◽  
Frequency Coupling ◽  
Phase Amplitude ◽  
Cross Frequency Coupling

AbstractPhase-amplitude coupling (PAC) has been hypothesized to coordinate cross-frequency interactions of neuronal activity in the brain. However, little is known about the distribution of PAC across the human brain and the frequencies involved. Furthermore, it remains unclear to what extend PAC may reflect spurious cross-frequency coupling induced by physiological artifacts or rhythmic non-sinusoidal signals with higher harmonics. Here, we combined MEG, source-reconstruction and different measures of cross-frequency coupling to systematically characterize PAC across the resting human brain. We show that cross-frequency measures of phase-amplitude, phase-phase, and amplitude-amplitude coupling are all sensitive to signals with higher harmonics. In conjunction, these measures allow to distinguish harmonic and non-harmonic PAC. Based on these insights, we found no evidence for non-harmonic PAC in resting-state MEG. Instead, we found cortically and spectrally wide-spread PAC driven by harmonic signals. Furthermore, we show how physiological artifacts and spectral leakage cause spurious PAC across wide frequency ranges. Our result clarify how different measures of cross-frequency interactions can be combined to characterize PAC and cast doubt on the presence of prominent non-harmonic phase-amplitude coupling in human resting-state MEG.

scholarly journals The absence of resting-state high-gamma cross-frequency coupling in patients with tinnitus

2017 ◽  
Vol 356 ◽  
pp. 63-73 ◽  
Author(s):  
Min-Hee Ahn ◽  
Sung Kwang Hong ◽  
Byoung-Kyong Min
Keyword(s):  
Resting State ◽  
High Gamma ◽  
Frequency Coupling ◽  
Cross Frequency Coupling

scholarly journals Aberrant resting-state functional brain networks in dyslexia: Symbolic mutual information analysis of neuromagnetic signals

2018 ◽  
Author(s):  
Stavros I. Dimitriadis ◽  
Panagiotis G. Simos ◽  
Jack M. Fletcher ◽  
Andrew C. Papanicolaou
Keyword(s):  
Reading Achievement ◽  
Resting State ◽  
Cost Efficiency ◽  
Reading Difficulties ◽  
Global Network ◽  
List Type ◽  
Global Cost ◽  
Symbolic Sequences ◽  
Frequency Coupling ◽  
Cross Frequency Coupling

AbstractNeuroimaging studies have identified a variety of structural and functional connectivity abnormalities in students experiencing reading difficulties. The present study adopted a novel approach to assess the dynamics of resting-state neuromagnetic recordings in the form of symbolic sequences (i.e., repeated patterns of neuromagnetic fluctuations within and/or between sensors).Participants were 25 students experiencing severe reading difficulties (RD) and 27 age-matched non-impaired readers (NI) aged 7-14 years. Sensor-level data were first represented as symbolic sequences in eight conventional frequency bands. Next, dominant types of sensor-to-sensor interactions in the form of intra and cross-frequency coupling were computed and subjected to graph modeling to assess group differences in global network characteristics.As a group RD students displayed predominantly within-frequency interactions between neighboring sensors which may reflect reduced overall global network efficiency and cost-efficiency of information transfer. In contrast, sensor networks among NI students featured a higher proportion of cross-frequency interactions. Brain-reading achievement associations highlighted the role of left hemisphere temporo-parietal functional networks, at rest, for reading acquisition and ability.HighlightsSymbolic dynamics of MEG time series revealed aberrant Cross Frequency Coupling in RD studentsGlobal efficiency and strength of Cross Frequency Coupling could reliably identify RD students from age-matched controlsGlobal Cost Efficiency, coupling strength, and the relative preponderance of cross-frequency interactions strongly correlated with reading achievement across groups.

scholarly journals Genuine cross-frequency coupling networks in human resting-state electrophysiological recordings

PLoS Biology ◽  
2020 ◽  
Vol 18 (5) ◽  
pp. e3000685 ◽  
Author(s):  
Felix Siebenhühner ◽  
Sheng H. Wang ◽  
Gabriele Arnulfo ◽  
Anna Lampinen ◽  
Lino Nobili ◽  
...  
Keyword(s):  
Resting State ◽  
Electrophysiological Recordings ◽  
Frequency Coupling ◽  
Cross Frequency Coupling

scholarly journals Genuine cross-frequency coupling networks in human resting-state electrophysiological recordings

2019 ◽  
Author(s):  
Felix Siebenhühner ◽  
Sheng H Wang ◽  
Gabriele Arnulfo ◽  
Anna Lampinen ◽  
Lino Nobili ◽  
...  
Keyword(s):  
Neuronal Activity ◽  
Resting State ◽  
Large Scale ◽  
Phase Synchronization ◽  
Functional Organization ◽  
Brain Regions ◽  
Neuronal Processing ◽  
Frequency Coupling ◽  
Cross Frequency Coupling ◽  
Frequency Phase

AbstractPhase synchronization of neuronal oscillations in specific frequency bands coordinates anatomically distributed neuronal processing and communication. Typically, oscillations and synchronization take place concurrently in many distinct frequencies, which serve separate computational roles in cognitive functions. While within-frequency phase synchronization has been studied extensively, less is known about the mechanisms that govern neuronal processing distributed across frequencies and brain regions. Such integration of processing between frequencies could be achieved via cross-frequency coupling (CFC), either by phase-amplitude coupling (PAC) or by n:m-cross-frequency phase synchrony (CFS). So far, studies have mostly focused on local CFC in individual brain regions, whereas the presence and functional organization of CFC between brain areas have remained largely unknown. We posit that inter-areal CFC may be essential for large-scale coordination of neuronal activity and investigate here whether genuine CFC networks are present in human resting-state brain activity.To assess the functional organization of CFC networks, we identified brain-wide CFC networks at meso-scale resolution from stereo-electroencephalography (SEEG) and at macro-scale resolution from source-reconstructed magnetoencephalography (MEG) data. We developed a novel graph-theoretical method to distinguish genuine CFC from spurious CFC that may arise from non-sinusoidal signals ubiquitous in neuronal activity. We show that genuine inter-areal CFC is present in human resting-state activity in both MEG and SEEG data. Both CFS and PAC networks coupled theta and alpha oscillations with higher frequencies in large-scale networks connecting anterior and posterior brain regions. CFS and PAC networks had distinct spectral patterns and opposing distribution of low- and high frequency network hubs, implying that they constitute distinct CFC mechanisms. The strength of CFS networks was also predictive of cognitive performance in a separate neuropsychological assessment. In conclusion, these results provide evidence for inter-areal CFS and PAC being two distinct mechanisms for coupling oscillations across frequencies in large-scale brain networks.

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