It is not all about phase: Amplitude dynamics in corticomuscular interactions

Bayraktaroğlu, Zübeyir; Carlowitz-Ghori, Katherina von; Curio, Gabriel; Nikulin, Vadim V.

doi:10.1016/j.neuroimage.2012.08.069

Cited by 27 publications

(24 citation statements)

References 50 publications

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“…These findings add to an increasing body of literature suggesting that neuronal interactions result in both in phase and amplitude coupling (Bayraktaroglu et al, 2013;Chawla et al, 1999Chawla et al, , 2000Daffertshofer and van Wijk, 2011;Mehrkanoon et al, 2014). On the other hand, amplitude and phase coupling are considered to have different causes and putative functions (Engel et al, 2013), and to operate at different time scales .…”

Section: Discussionsupporting

confidence: 57%

Intrinsic Coupling Modes in Source-Reconstructed Electroencephalography

et al. 2014

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Intrinsic coupling of neuronal assemblies constitutes a key feature of ongoing brain activity, yielding the rich spatiotemporal patterns observed in neuroimaging data and putatively supporting cognitive processes. Intrinsic coupling has been investigated in electrophysiological recordings using two types of functional connectivity measures: amplitude and phase coupling. These two coupling modes differ in their likely causes and functions, and have been proposed to provide complementary insights into intrinsic neuronal interactions. Here, we investigate the relationship between amplitude and phase coupling in source-reconstructed electroencephalography (EEG). Volume conduction is a key obstacle for connectivity analysis in EEG-we therefore also test the envelope correlation of orthogonalized signals and the phase lag index. Functional connectivity between six seed source regions (bilateral visual, sensorimotor, and auditory cortices) and all other cortical voxels was computed. For all four measures, coupling between homologous sensory areas in both hemispheres was significantly higher than with other voxels at the same physical distance. The frequency of significant coupling differed between sensory areas: 10 Hz for visual, 30 Hz for auditory, and 40 Hz for sensorimotor cortices. By contrasting envelope correlations and phase locking values, we observed two distinct clusters of voxels showing a different relationship between amplitude and phase coupling. Large clusters contiguous to the seed regions showed an identity (1:1) relationship between amplitude and phase coupling, whereas a cluster located around the contralateral homologous regions showed higher phase than amplitude coupling. These results show a relationship between intrinsic coupling modes that is distinct from the effect of volume conduction.

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Section: Discussionsupporting

confidence: 57%

Intrinsic Coupling Modes in Source-Reconstructed Electroencephalography

et al. 2014

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“…The n:m coherence is a generalized coherence measure incorporating both phase and amplitude relationship (Yang et al, 2015, 2016a). A recent study found that EEG oscillations, originating from the primary sensorimotor areas, can transmit not only the phase but also amplitude dynamics through the spinal motoneurons down to the periphery (Bayraktaroglu et al, 2013). Thus, the n:m coherence is more suitable to assess the corticomuscular coupling than other cross-frequency coupling measures purely assessing phase or amplitude relationships (Young and Eggermont, 2009).…”

Section: Discussionmentioning

confidence: 99%

Nonlinear Coupling between Cortical Oscillations and Muscle Activity during Isotonic Wrist Flexion

Yang

Solis‐Escalante

Ruit

et al. 2016

Front. Comput. Neurosci.

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Coupling between cortical oscillations and muscle activity facilitates neuronal communication during motor control. The linear part of this coupling, known as corticomuscular coherence, has received substantial attention, even though neuronal communication underlying motor control has been demonstrated to be highly nonlinear. A full assessment of corticomuscular coupling, including the nonlinear part, is essential to understand the neuronal communication within the sensorimotor system. In this study, we applied the recently developed n:m coherence method to assess nonlinear corticomuscular coupling during isotonic wrist flexion. The n:m coherence is a generalized metric for quantifying nonlinear cross-frequency coupling as well as linear iso-frequency coupling. By using independent component analysis (ICA) and equivalent current dipole source localization, we identify four sensorimotor related brain areas based on the locations of the dipoles, i.e., the contralateral primary sensorimotor areas, supplementary motor area (SMA), prefrontal area (PFA) and posterior parietal cortex (PPC). For all these areas, linear coupling between electroencephalogram (EEG) and electromyogram (EMG) is present with peaks in the beta band (15–35 Hz), while nonlinear coupling is detected with both integer (1:2, 1:3, 1:4) and non-integer (2:3) harmonics. Significant differences between brain areas is shown in linear coupling with stronger coherence for the primary sensorimotor areas and motor association cortices (SMA, PFA) compared to the sensory association area (PPC); but not for the nonlinear coupling. Moreover, the detected nonlinear coupling is similar to previously reported nonlinear coupling of cortical activity to somatosensory stimuli. We suggest that the descending motor pathways mainly contribute to linear corticomuscular coupling, while nonlinear coupling likely originates from sensory feedback.

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“…The alpha frequency band is located slightly posterior to the beta (Pfurtscheller and Lopes da Silva, 1999; Ritter et al, 2009) and shows prominent reaction to somatosensory events (Babiloni et al, 2008; van Ede et al, 2014). On the other hand, the amplitude of the beta frequency band EEG is attenuated, but the phase synchronization is maintained between the beta frequency band EEG and the spinal motoneuronal pool activities during tonic motor contraction tasks (Conway et al, 1995; Leocani et al, 1997; Bayraktaroglu et al, 2013). Furthermore, in the post-movement period, the amplitude of the beta-band consistently returns to and exceeds pre-movement levels via synchronization (Pfurtscheller et al, 1996a; Bauer et al, 2006; Jurkiewicz et al, 2006; Parkes et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Resting-State Fluctuations of EEG Sensorimotor Rhythm Reflect BOLD Activities in the Pericentral Areas: A Simultaneous EEG-fMRI Study

Tsuchimoto

Shibusawa

Mizuguchi

et al. 2017

Front. Hum. Neurosci.

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Blockade of the scalp electroencephalographic (EEG) sensorimotor rhythm (SMR) is a well-known phenomenon following attempted or executed motor functions. Such a frequency-specific power attenuation of the SMR occurs in the alpha and beta frequency bands and is spatially registered at primary somatosensory and motor cortices. Here, we hypothesized that resting-state fluctuations of the SMR in the alpha and beta frequency bands also covary with resting-state sensorimotor cortical activity, without involving task-related neural dynamics. The present study employed functional magnetic resonance imaging (fMRI) to investigate the neural regions whose activities were correlated with the simultaneously recorded SMR power fluctuations. The SMR power fluctuations were convolved with a canonical hemodynamic response function and correlated with blood-oxygen-level dependent (BOLD) signals obtained from the entire brain. Our findings show that the alpha and beta power components of the SMR correlate with activities of the pericentral area. Furthermore, brain regions with correlations between BOLD signals and the alpha-band SMR fluctuations were located posterior to those with correlations between BOLD signals and the beta-band SMR. These results are consistent with those of event-related studies of SMR modulation induced by sensory input or motor output. Our findings may help to understand the role of the sensorimotor cortex activity in contributing to the amplitude modulation of SMR during the resting state. This knowledge may be applied to the diagnosis of pathological conditions in the pericentral areas or the refinement of brain–computer interfaces using SMR in the future.

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It is not all about phase: Amplitude dynamics in corticomuscular interactions

Cited by 27 publications

References 50 publications

Intrinsic Coupling Modes in Source-Reconstructed Electroencephalography

Intrinsic Coupling Modes in Source-Reconstructed Electroencephalography

Nonlinear Coupling between Cortical Oscillations and Muscle Activity during Isotonic Wrist Flexion

Resting-State Fluctuations of EEG Sensorimotor Rhythm Reflect BOLD Activities in the Pericentral Areas: A Simultaneous EEG-fMRI Study

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