Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2023Detection of quadratic phase coupling by cross-bicoherence and spectral Granger causality in bifrequencies interactionscitations

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Lintas, Alessandra
1 / 1 shared
Asai, Yoshiyuki
1 / 1 shared
Abe, Takeshi
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2023

Co-Authors (by relevance)

  • Lintas, Alessandra
  • Asai, Yoshiyuki
  • Abe, Takeshi
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document

Detection of quadratic phase coupling by cross-bicoherence and spectral Granger causality in bifrequencies interactions

  • Lintas, Alessandra
  • Asai, Yoshiyuki
  • Abe, Takeshi
  • Villa, Alessandro E. P.
Abstract

<jats:title>Abstract</jats:title><jats:p>Quadratic Phase Coupling (QPC) is a crucial statistical tool for assessing nonlinear synchronization within multivariate time series data, particularly within signal processing and neuroscience. This study delves into the accuracy of QPC detection by employing numerical estimates through cross-bicoherence and bivariate Granger causality within a simple yet noisy instantaneous multiplier model. The investigation extends to evaluating the influence of incidental statistically significant bifrequency interactions, introducing key metrics such as the ratio of bispectral quadratic phase coupling and the ratio of bivariate Granger causality quadratic phase coupling, with values close to 1 indicating high level of accuracy in QPC detection. The model is tested using 334 electroencephalographic recordings, encompassing diverse carrier frequencies to explore an extensive array of scenarios. The coupling strength between interacting channels emerges as a pivotal factor introducing nonlinearities that affect the signal-to-noise ratio in the output channel. The bispectral approach outperformed bivariate Granger causality, particularly at weak coupling strengths and with noise biases. Especially noteworthy is cross-bicoherence’s effectiveness in detecting QPC in cases of very weak couplings, making it a reliable method for unveiling subtle nonlinear interactions in noisy signals, a common scenario in brain activity recordings.</jats:p>

Topics
  • impedance spectroscopy
  • phase
  • strength