Stochastic transitions between in-phase and anti-phase synchronization in coupled map-based neural oscillators

Bashkirtseva, Irina; Ryashko, Lev; Pisarchik, Alexander N.

doi:10.1016/j.cnsns.2020.105611

Cited by 19 publications

(6 citation statements)

References 46 publications

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“…But, later it was proved wrong [3] and a stable anti-phase oscillations in electrically coupled relaxation oscillators were reported [15]. The stochastic transitions between in-phase and anti-phase synchronisations in neural oscillators are still of great interest even after these many years [16,17]. Researchers have proposed different modifications in inhibitory and excitatory connections to induce anti-and in-phase oscillations [8,18].…”

Section: Introductionmentioning

confidence: 99%

In-phase and anti-phase bursting dynamics and synchronisation scenario in neural network by varying coupling phase

Remi

Subha

2023

J Biol Phys

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Section: Introductionmentioning

confidence: 99%

In-phase and anti-phase bursting dynamics and synchronisation scenario in neural network by varying coupling phase

Remi

Subha

2023

J Biol Phys

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“…From the previous investigation, it is clear that the in-phase is more stable than the anti-phase leading to the identification of important invariant system features (Haken et al, 1985). With respect to the reconfirmation based on cluster methods, the present experiment was designed to find a relevant in-phase bimanual synchrony variable by using another fundamental technique (intensively defined as a prototype modeling for contexttual constraints invetigation (i.e., symmetry, handedness, and topological attractor; Pikovsky et al, 2003;Shea et al, 2016;Treffner & Turvey, 1996;)), and the collected data were calculated to compare different characteristics between one joint performance and several different joint performances (Bashkirtseva et al, 2021). In particular, although the wrist point is properly used compared to other possible bimanual pendulum areas, such as the elbow or shoulder, whether this value was representative of the overall characteristics of a system had to be assessed (Bossel, 2002).…”

Section: Methodsmentioning

confidence: 99%

Dynamic Coordination Phase and Joint Profiles: Cluster and Fixed-point Shift Techniques

Park¹

2021

Int J Appl Sports Sci

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This study aims to represent a more preferential bilateral movement template by introducing empirical measures of cluster (Experiment 1) and fixed-point shift (Experiment 2) during the bimanual coordination. We showed how the phase dynamics can be calculated using the cluster method (analysis 1). Relatively stable patterns defined by the cluster process were employed for the fixed-point shift calculation to compare three joint oscillations (wrist, elbow, and shoulder; Analysis 2). The analysis revealed that (i) anti-phase coordination was less stable underlying the cluster phase and amplitude analysis; a significance that was mainly driven by higher radial variability. (ii) The three joint couplings and noise oscillations showed that they were wider for the distal (wrist) than the proximal (shoulder) areas. (iii) Repetition with one joint (i.e., wrist) may be significantly associated with trial effects; thus, using data of pick only one joint (wrist) but collecting data from different (three) joints seems more reliable to be a typical dependent variable for the trial effect. Observations and suggestions derived from this aspect represent how the bilateral movement calculation methods can be applied to measure the type of coordination stability eliminating of the learning effect stemming from numerous trials.

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“…Spike-timing-dependent plasticity (STDP) is necessary for the hippocampus to function properly and depends on the frequency and timing of spike synchronization. Synchronized activity of cells innervated by the dopamine system loses its essential properties and gives rise to PD symptoms ( Touboul et al, 2020 ; Bashkirtseva et al, 2021 ). The PD symptoms in such a model are generated as a result of stochastic resonance, which leads to an increase in periodic oscillations.…”

Section: Hypothetical Mechanisms Explaining Positive Effects Of Trans...mentioning

confidence: 99%

Transcranial Current Stimulation as a Tool of Neuromodulation of Cognitive Functions in Parkinson’s Disease

Brak

Filimonova²,

Zakhariya³

et al. 2022

Front. Neurosci.

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Decrease in cognitive function is one of the most common causes of poor life quality and early disability in patients with Parkinson’s disease (PD). Existing methods of treatment are aimed at both correction of motor and non-motor symptoms. Methods of adjuvant therapy (or complementary therapy) for maintaining cognitive functions in patients with PD are of interest. A promising subject of research in this regard is the method of transcranial electric current stimulation (tES). Here we reviewed the current understanding of the pathogenesis of cognitive impairment in PD and of the effects of transcranial direct current stimulation and transcranial alternating current stimulation on the cognitive function of patients with PD-MCI (Parkinson’s Disease–Mild Cognitive Impairment).

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Stochastic transitions between in-phase and anti-phase synchronization in coupled map-based neural oscillators

Cited by 19 publications

References 46 publications

In-phase and anti-phase bursting dynamics and synchronisation scenario in neural network by varying coupling phase

In-phase and anti-phase bursting dynamics and synchronisation scenario in neural network by varying coupling phase

Dynamic Coordination Phase and Joint Profiles: Cluster and Fixed-point Shift Techniques

Transcranial Current Stimulation as a Tool of Neuromodulation of Cognitive Functions in Parkinson’s Disease

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