Anticipated synchronization in human EEG data: Unidirectional causality with negative phase lag

Carlos, Francisco-Leandro P.; Ubirakitan, Maciel-Monteiro; Rodrigues, Michele; Aguilar-Domingo, Moisés; Herrera-Gutiérrez, Eva; Gómez-Amor, Jesús; Copelli, Mauro; Carelli, Pedro V.; Matias, Fernanda S.

doi:10.1103/physreve.102.032216

Cited by 13 publications

(8 citation statements)

References 68 publications

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“…This characterizes the anticipated synchronization regime (AS, with mean time delay τ = −39 ms for this example). This counter intuitive regime explains the observed unidirectional influence with negative phase difference verified in LFP monkey data [26,28,29] as well as in human EEG [57]. Moreover, AS could be possibly related to commonly reported short latency in visual systems [58][59][60][61][62][63], olfactory circuits [64], songbirds brain [43] and human perception [65,66].…”

Section: Local Properties At the Receiver Population Modulates Global...mentioning

confidence: 83%

Neuronal heterogeneity modulates phase-synchronization between unidirectionally coupled populations with excitation-inhibition balance

Brito,

Matias

2021

Preprint

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Section: Local Properties At the Receiver Population Modulates Global...mentioning

confidence: 83%

Neuronal heterogeneity modulates phase-synchronization between unidirectionally coupled populations with excitation-inhibition balance

Brito,

Matias

2021

Preprint

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“…Granger causality (GC) is a nonlinear analysis tool that can determine the direction of neuron interaction and can be used to measure effective connectivity [ 18 ]. It has been widely used to analyze EEG signals [ 19 , 20 ] and has been proven to play an important role in providing EEG change information [ 21 , 22 ].…”

Section: Methodsmentioning

confidence: 99%

Effects of Motor Imagery Tasks on Brain Functional Networks Based on EEG Mu/Beta Rhythm

Guo

et al. 2022

Brain Sciences

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Motor imagery (MI) refers to the mental rehearsal of movement in the absence of overt motor action, which can activate or inhibit cortical excitability. EEG mu/beta oscillations recorded over the human motor cortex have been shown to be consistently suppressed during both the imagination and performance of movements, although the specific effect on brain function remains to be confirmed. In this study, Granger causality (GC) was used to construct the brain functional network of subjects during motor imagery and resting state based on EEG in order to explore the effects of motor imagery on brain function. Parameters of the brain functional network were compared and analyzed, including degree, clustering coefficient, characteristic path length and global efficiency of EEG mu/beta rhythm in different states. The results showed that the clustering coefficient and efficiency of EEG mu/beta rhythm decreased significantly during motor imagery (p < 0.05), while degree distribution and characteristic path length increased significantly (p < 0.05), mainly concentrated in the frontal lobe and sensorimotor area. For the resting state after motor imagery, the changes of brain functional characteristics were roughly similar to those of the task state. Therefore, it is concluded that motor imagery plays an important role in activation of cortical excitability.

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“…Thus, while in many cases the statistically -inferred directed FC goes, e.g., from the phase-leading to the phase-lagging neuronal population [183,184], i.e. respects a sequentiality criterion, in other cases the relation can be inverted, reflecting non-linear interactions between populations, as anticipatory synchronisation [185] or heterogeneities in internal synchrony levels [186]. More explicitly, causality could be captured: by the detection of remote effects on distant regions triggered by interventions in local regions (as in "Dynamic Causal Modelling" [178]); or, by showing that consideration of the past activity of a putative causal source region improves the prediction of the future activity of a target region, as in Granger Causality analyses of neural time-series [187][188][189][190].…”

Section: Application To Neurosciencementioning

confidence: 99%

A stylised view on structural and functional connectivity in dynamical processes in networks

Voutsa¹,

Battaglia²,

Bracken³

et al. 2021

Preprint

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The relationship of network structure and dynamics is one of most extensively investigated problems in the theory of complex systems of the last years. Understanding this relationship is of relevance to a range of disciplines -from Neuroscience to Geomorphology. A major strategy of investigating this relationship is the quantitative comparison of a representation of network architecture (structural connectivity) with a (network) representation of the dynamics (functional connectivity). Analysing such SC/FC relationships has over the past years contributed substantially to our understanding of the functional role of network properties, such as modularity, hierarchical organization, hubs and cycles.Here, we show that one can distinguish two classes of functional connectivity -one based on simultaneous activity (co-activity) of nodes the other based on sequential activity of nodes. We delineate these two classes in different categories of dynamical processesexcitations, regular and chaotic oscillators -and provide examples for SC/FC correlations of both classes in each of these models. We expand the theoretical view of the SC/FC relationships, with conceptual instances of the SC and the two classes of FC for various application scenarios in Geomorphology, Freshwater Ecology, Systems Biology, Neuroscience and Social-Ecological Systems.Seeing the organization of a dynamical processes in a network either as governed by coactivity or by sequential activity allows us to bring some order in the myriad of observations relating structure and function of complex networks.

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Anticipated synchronization in human EEG data: Unidirectional causality with negative phase lag

Cited by 13 publications

References 68 publications

Neuronal heterogeneity modulates phase-synchronization between unidirectionally coupled populations with excitation-inhibition balance

Neuronal heterogeneity modulates phase-synchronization between unidirectionally coupled populations with excitation-inhibition balance

Effects of Motor Imagery Tasks on Brain Functional Networks Based on EEG Mu/Beta Rhythm

A stylised view on structural and functional connectivity in dynamical processes in networks

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