Dynamic large-scale network synchronization from perception to action

Hirvonen, J.; Monto, Simo; Wang, Sheng H.; Palva, Satu

doi:10.1162/netn_a_00039

Cited by 27 publications

(28 citation statements)

References 75 publications

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“…Furthermore, in these data, the individual capacity limitations of VWM were predicted by concurrent largescale high-alpha-(10-14 Hz,) and beta-(14-30 Hz) band phase synchronization. Similar observations of concurrent synchronization in many frequency bands, has been obtained in an attentional blink study [203] and during perception-action cycle in the somatosensory modality [204] suggesting that more complex tasks involve synchronization in multiple spectrally distributed networks.…”

Section: B Oscillatory Activitiessupporting

confidence: 75%

Electrophysiological Brain Connectivity: Theory and Implementation

Astolfi

Valdés‐Sosa

et al. 2019

IEEE Trans. Biomed. Eng.

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183

144

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We review the theory and algorithms of electrophysiological brain connectivity analysis. This tutorial is aimed at providing an introduction to brain functional connectivity from electrophysiological signals, including electroencephalography, magnetoencephalography, electrocorticography, and stereoelectroencephalography. Various connectivity estimators are discussed, and algorithms introduced. Important issues for estimating and mapping brain functional connectivity with electrophysiology are discussed.Index Terms-Brain functional connectivity, electrophysiological connectivity, effective connectivity, EEG, MEG, intracranial EEG, electrophysiological connectome.

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Section: B Oscillatory Activitiessupporting

confidence: 75%

Electrophysiological Brain Connectivity: Theory and Implementation

Astolfi

Valdés‐Sosa

et al. 2019

IEEE Trans. Biomed. Eng.

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183

144

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“…The motor cortex is also phase-synchronized with other brain regions in a task dependent manner. For example, concurrent synchronization in delta and gamma bands connects sensorimotor, frontal, and parietal brain areas during conscious somatosensory perception and action [71]. For speech perception, theta-band synchronization between auditory and speech-motor regions was observed while participants listened to syllables [72].…”

Section: Sensorimotor Coordination By Brain Rhythmicitymentioning

confidence: 99%

Roles of Brain Criticality and Multiscale Oscillations in Temporal Predictions for Sensorimotor Processing

Palva

2018

Trends in Neurosciences

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115

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Sensorimotor predictions are essential for adaptive behavior. In natural environments, events that demand sensorimotor predictions unfold across many timescales, and corresponding temporal predictions (either explicit or implicit) should therefore emerge in brain dynamics. Neuronal oscillations are scalespecific processes found in several frequency bands. They underlie periodicity in sensorimotor processing and can represent temporal predictions via their phase dynamics. These processes build upon endogenous neural rhythmicity and adapt in response to exogenous timing demands. While much of the research on periodicity in neural processing has focused on subsecond oscillations, these fast-scale rhythms are in fact paralleled by critical-like, scale-free dynamics and fluctuations of brain activity at various timescales, ranging from seconds to hundreds of seconds. In this review, we put forth a framework positing that critical brain dynamics are essential for the role of neuronal oscillations in timing and that cross-frequency coupling flexibly organizes neuronal processing across multiple frequencies. Critical-like Multiscale Brain Oscillations for Processing a Critical-like Multiscale Environment? Perception and action in natural environments necessitate interplay among representations of past events, the current state, as well as predictions of both future events and the consequences of our own actions across a continuum of vastly different timescales. Notably, natural visual [1] and auditory [2] scenes are characteristically scale-free and arrhythmic signals with power-law scaling behavior (Box 1 and Figure 1A-C). Such lack of scaling or periodicities is perhaps not too surprising, considering that many aspects of our environment are ongoing processes involving nonlinear interactions among many agents, or are products of such processes, and thereby encompass complex or 'critical' spatiotemporal dynamics [3]. Critical dynamics appear in systems poised at a transition between two phases, and such systems are characterized by stochastic fractal-like architectures, power-law correlations, and rapid intermittent state transitions [3,4]. However, in many real-world settings scale-free environmental contexts are accompanied by distinct scale-specific phenomena (i.e., periodic or quasiperiodic signals; Box 1). Such scale-specific components arise both from artificial sources and from biological systems, for instance through phenomena with rhythmic components, such as gait and production of speech and music (Figure 1C-E). What are the neural processes that facilitate effective perception, cognition, and action in environments that consist of both scale-free and scale-specific temporal structures? The range of behaviorally relevant environmental temporal scales is well paralleled by the spectrum of Highlights Neuronal oscillations in ongoing brain activity adapt to behaviorally relevant sensorimotor rhythmicities by phase prediction and entrainment. Neuronal oscillations also endogenously impose rhythmicity on perceptual...

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“…Then, vertex fidelity was estimated for each source vertex by the correlation between the forward-inverse-modeled data and ground-truth data. This correlation was quantified with the absolute-valued real part of the complex PLV (cPLV) between Z V,orig and Z V,mod , which was defined [38,39,108] as follows:…”

Section: Meg Source Reconstruction: Inverse Transform and Collapsingmentioning

confidence: 99%

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

et al. 2020

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Phase 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 interareal CFC may be essential for large-scale coordination of neuronal activity and investigate here whether genuine CFC networks are present in human resting-state (RS) brain activity. To assess the functional organization of CFC networks, we identified brain-wide CFC networks at mesoscale resolution from stereoelectroencephalography (SEEG) and at macroscale resolution from source-reconstructed magnetoencephalography (MEG) data. We developed a novel, to our knowledge, graphtheoretical method to distinguish genuine CFC from spurious CFC that may arise from nonsinusoidal signals ubiquitous in neuronal activity. We show that genuine interareal CFC is present in human RS activity in both SEEG and MEG 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,

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Dynamic large-scale network synchronization from perception to action

Cited by 27 publications

References 75 publications

Electrophysiological Brain Connectivity: Theory and Implementation

Electrophysiological Brain Connectivity: Theory and Implementation

Roles of Brain Criticality and Multiscale Oscillations in Temporal Predictions for Sensorimotor Processing

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

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