Phase-lag synchronization analysis in complex systems with directed inter-relations

Martins, Viviane S. G.; Rodrigues, Abner Cardoso; Cerdeira, Hilda A.; Machado, Birajara Soares

doi:10.1140/epjst/e2016-02618-7

Cited by 11 publications

(7 citation statements)

References 35 publications

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“…Thus, LPS represents the connectivity of two signals after excluding the instantaneous zero-lag component (i.e., a lot of artifact elements). This is necessary as both scalp and tomography (estimated intracranial) EEG signals can be biased by non-physiological, artifactual components (including volume conduction; Martins et al, 2016 ). The electrocortical sources’ density and connectivity were analyzed using a statistical nonparametric mapping method and a non-parametric permutation/randomization procedure (Holmes et al, 1996 ; Nichols and Holmes, 2002 ).…”

Section: Case Descriptionmentioning

confidence: 99%

A Case of Psychogenic Myoclonus Responding to a Novel Transcranial Magnetic Stimulation Approach: Rationale, Feasibility, and Possible Neurophysiological Basis

Naro

Pignolo

Billeri

et al. 2020

Front. Hum. Neurosci.

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Repetitive transcranial magnetic stimulation (rTMS) can relieve motor symptoms related to psychogenic movement disorders (PMDs), but the subtending neurophysiological basis is unclear. We report on a 50-year-old woman with a diagnosis of psychogenic myoclonus in the right lower limb, who was treated with a daily session (in the late morning/early afternoon) of 1 Hz rTMS over the left premotor cortex (PMC), five times a week for 6 weeks. Clinical data and EEG at rest were collected before and immediately and 2-month after the rTMS protocol completion. The patient reported a significant reduction of involuntary movement frequency and intensity and the related disability burden up to the follow-up. In parallel, any abnormality in terms of source current density within and connectivity between the frontal and parietal areas was reset. The short follow-up period, the lack of extensive neurophysiological measures, and the lack of control treatment represent the main limitation of the study. However, lowfrequency rTMS over PMC seems a safe and promising approach for the management of psychogenic myoclonus owing to the combination of cortical neuromodulation and non-specific mechanisms suggesting cognitive-behavioral effects.

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Section: Case Descriptionmentioning

confidence: 99%

A Case of Psychogenic Myoclonus Responding to a Novel Transcranial Magnetic Stimulation Approach: Rationale, Feasibility, and Possible Neurophysiological Basis

Naro

Pignolo

Billeri

et al. 2020

Front. Hum. Neurosci.

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“…The articles can be grouped into four categories, namely 1. Synchronization and control in time delayed and other networks [23][24][25][26][27][28][29] [36][37][38][39][40][41].…”

mentioning

confidence: 99%

“…The effect of network-level synchronization with Izhikevich neuron under external periodic signals is reported in [25]. Phase lag synchronization with Izhikevich neuron is also investigated in [26]. The results are useful to study synchronization in complex networks where the nodes are composed by another complex system.…”

mentioning

confidence: 99%

Synchronization and control in time-delayed complex networks and spatio-temporal patterns

Banerjee

Kurths

Schöll

2016

Eur. Phys. J. Spec. Top.

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Abstract. This special topics issue is a collection of contributions on the recent developments of control and synchronization in time delayed systems and space time chaos. The various articles report interesting results on time delayed complex networks; fractional order delayed models; dynamics of spatio-temporal patterns; stochastic models etc. Experimental analysis on synchronization, dynamics and control of chaos are also well investigated using Field Programmable Gate Array (FPGA), circuit realizations and chemical reactions.Complexity and networks, originated in different contexts have been received much attention as interdisciplinary subjects. Of late, they are found to be jointly associated to characterize the so-called complex networked model in different areas that range from natural phenomena on technological aspects to socio-economic systems. It has been reported well that complex networks (CN) widely exist in the real world, including food webs, communication networks, social networks, power grids, cellular and metabolic networks, world wide web, disease transmission networks,neural networks, electrical power grids, scientific citation web, living organisms, etc. [1,2].Complex networks are involved in a number of different fields that include physics, chemistry, computer science, sociology, economics, finance, biology, epidemiology, etc. However in all of these CN's a very common feature is the presence of a large number of objects (e.g. individuals, computers, cells, molecules, etc.), which interact in a way that quantifies strong irregularities. A network can be essentially represented by a graph, an abstract mathematical structure consists of a set of generically called nodes (vertices) connected by links (edges) representing some binary relationship. In case of World Wide Web, the websites are the nodes and the hyperlinks between a

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“…Erro de previsão η em função de β. A predição foi calculada considerando a dependência causal x → y. Adaptado deMartins, V.S.G. et al (2016).a predição de y dado x é:ŷ (t + 1) = 1 |U ε (x(t))| # τ /x(τ )∈Uε(x(t)) y(τ + 1) , (A.3)onde U ε (x(t)) = {x(τ ) : x(t) − x(τ ) < } é a vizinhança de x(t) com raio ε e |U ε (x(t))| # é o número de elementos nesta vizinhança.…”

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“…PLV para o sistema Rössler-Lorenz usando parâmetro de acoplamento β = 0. A curva azul é o PLV ij (d) para dois sinais i e j, enquanto que a linha tracejada em vermelho corresponde ao PLV com o sinal permutado de j. Adaptado deMartins, V.S.G. et al (2016).…”

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Caracterização e modelagem da atividade eletrofisiológica em pacientes com epilepsia

Neto¹,

Cardoso²

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Complex networks applyed to brain activity signals show the presence abnormal of connectivity patterns in patients suffering with diseases and others psychiatric disorders. From this, some authors began to question the influence of these structures in the cause of these problems and how it leads to the development of these abnormal patterns. From a theoretical point of view, several studies show how the topology of a network can change a process that maintains it, for example how a network influences the propagation of a system failure, synchronization or difussion processes. In this sense, the objective of this study is to characterize the functional networks of patients during episodes of seizures, making a parallel between the structure of these networks and the dynamic processes involved in the epilepsy, in particular the synchronization. For this, real data were analyzed and the inferred networks in a first step. And then, artificial simulations using the parameters obtained from the analysis were employed to show the impact of these networks in dynamic processes. The results indicate structures that can enhance the synchronization and the influence of the coupling mode on these systems.

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Phase-lag synchronization analysis in complex systems with directed inter-relations

Cited by 11 publications

References 35 publications

A Case of Psychogenic Myoclonus Responding to a Novel Transcranial Magnetic Stimulation Approach: Rationale, Feasibility, and Possible Neurophysiological Basis

A Case of Psychogenic Myoclonus Responding to a Novel Transcranial Magnetic Stimulation Approach: Rationale, Feasibility, and Possible Neurophysiological Basis

Synchronization and control in time-delayed complex networks and spatio-temporal patterns

Caracterização e modelagem da atividade eletrofisiológica em pacientes com epilepsia

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