A Best Detecting Synchrony Method in Audio STROOP EEG Based on Wavelet Coherence

Previous studies ignored the distinction between short, medium, and long term by decomposing macroeconomic variables and human development index at different time scales. We re-visit the causal association between biomass energy (BIO), economic growth (GDP), trade openness (TRO), industrialization (IND), foreign direct investment (FDI), and human development (HDI) in China on a quarterly scale by scale basis for the period 1990 to 2019 using the tools of wavelet, i.e., wavelet correlation, wavelet coherence and scale by scale Granger causality test. The main findings uncover that IND, TRO, GDP, and BIO positively drive the HDI at low and medium frequencies, while FDI negatively impacts HDI during the sample period. Additionally, there is a bidirectional relationship between GDP and HDI at different time and frequency domains. Specifically, we discover that the positive co-movement is more robust in the aftermath of the global financial crisis, particularly for HDI, BIO, GDP, and TRO at medium frequencies throughout the period under research. Our empirical insights have significant implications for achieving human development sustainability in China.

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Exploring the co-movements between stock market returns and COVID‑19 pandemic: evidence from wavelet coherence analysis

Applied Economics Letters ◽

10.1080/13504851.2021.1937034 ◽

2021 ◽

pp. 1-9

Author(s):

Ştefan Cristian Gherghina ◽

Liliana Nicoleta Simionescu

Keyword(s):

Stock Market ◽

Wavelet Coherence ◽

Coherence Analysis ◽

Market Returns ◽

Stock Market Returns ◽

Wavelet Coherence Analysis

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Construction and analysis of cortical–muscular functional network based on EEG-EMG coherence using wavelet coherence

Neurocomputing ◽

10.1016/j.neucom.2021.01.102 ◽

2021 ◽

Vol 438 ◽

pp. 248-258

Author(s):

Xugang Xi ◽

Ziyang Sun ◽

Xian Hua ◽

Changmin Yuan ◽

Yun-Bo Zhao ◽

...

Keyword(s):

Functional Network ◽

Wavelet Coherence

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Thalamocortical Connectivity in Experimentally-Induced Migraine Attacks: A Pilot Study

Brain Sciences ◽

10.3390/brainsci11020165 ◽

2021 ◽

Vol 11 (2) ◽

pp. 165

Author(s):

Daniele Martinelli ◽

Gloria Castellazzi ◽

Roberto De Icco ◽

Ana Bacila ◽

Marta Allena ◽

...

Keyword(s):

Disease Model ◽

Episodic Migraine ◽

Wavelet Coherence ◽

Test Time ◽

Prodromal Phase ◽

Brain Changes ◽

The Right ◽

Wavelet Coherence Analysis ◽

Thalamic Function ◽

Experimentally Induced

In this study we used nitroglycerin (NTG)-induced migraine attacks as a translational human disease model. Static and dynamic functional connectivity (FC) analyses were applied to study the associated functional brain changes. A spontaneous migraine-like attack was induced in five episodic migraine (EM) patients using a NTG challenge. Four task-free functional magnetic resonance imaging (fMRI) scans were acquired over the study: baseline, prodromal, full-blown, and recovery. Seed-based correlation analysis (SCA) was applied to fMRI data to assess static FC changes between the thalamus and the rest of the brain. Wavelet coherence analysis (WCA) was applied to test time-varying phase-coherence changes between the thalamus and salience networks (SNs). SCA results showed significantly FC changes between the right thalamus and areas involved in the pain circuits (insula, pons, cerebellum) during the prodromal phase, reaching its maximal alteration during the full-blown phase. WCA showed instead a loss of synchronisation between thalami and SN, mainly occurring during the prodrome and full-blown phases. These findings further support the idea that a temporal change in thalamic function occurs over the experimentally induced phases of NTG-induced headache in migraine patients. Correlation of FC changes with true clinical phases in spontaneous migraine would validate the utility of this model.

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Rhythmic Features of Movement Synchrony for Bonding Individuals in Dyadic Interaction

Journal of Nonverbal Behavior ◽

10.1007/s10919-019-00315-0 ◽

2019 ◽

Vol 44 (1) ◽

pp. 173-193 ◽

Cited By ~ 4

Author(s):

Ken Fujiwara ◽

Masanori Kimura ◽

Ikuo Daibo

Keyword(s):

Hierarchical Linear Modeling ◽

Dyadic Interaction ◽

Wavelet Coherence ◽

Linear Modeling ◽

Theoretical Contribution ◽

Bonding Effect ◽

Slow Tempo ◽

Movement Synchrony ◽

The Impact

Abstract This study examined ways in which rhythmic features of movement contribute to bonding between individuals. Though previous studies have described synchrony as a form of social glue, this research extends those findings to consider the impact of fast versus slow tempo on movement synchrony. This two-part experiment examined dyadic interactions as they occurred between same-sex strangers (Study 1) and friends (Study 2). Participants were video-recorded as they engaged in 5- or 6-min chats, and synchrony was evaluated using wavelet transform via calculations of cross-wavelet coherence. Study 1 employed regression commonality analysis and hierarchical linear modeling and found that among various frequency bands, rapport between individuals was positively associated with synchrony under 0.025 Hz (i.e., slower than once every 40 s) and 0.5–1.5 Hz (i.e., once every 0.67–2 s). On the contrary, Study 2 determined that synchrony of 0.5–1.5 Hz was not impactful among friend dyads and only predictive of the motivation to cultivate a friendly relationship during interactions with strangers. These results indicate the existence of a distinctive rhythm for bonding individuals, and the role of pre-existing friendship as a moderator of the bonding effect of synchrony. However, the role of relative phase (i.e., timing of movement; same versus opposite timing) remains unclear, as the ratio of in- and anti-phase patterning had no significant influence on perceived rapport and motivation to develop relationships. On the basis of the research results, a theoretical contribution is proposed to the study of interpersonal coordination.

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