scholarly journals Nonsinusoidal neuronal oscillations: bug or feature?

2018 ◽  
Vol 119 (5) ◽  
pp. 1595-1598 ◽  
Author(s):  
Diego Lozano-Soldevilla
Keyword(s):  
State Of The Art ◽  
Time And Space ◽  
Neuronal Oscillations ◽  
Neuronal Ensembles ◽  
Frequency Coupling ◽  
New Research ◽  
Cross Frequency Coupling

There is compiling evidence suggesting that independent neuronal ensembles are coordinated in time and space through cross-frequency coupling (CFC). However, recent studies have convincingly demonstrated that nonsinusoidal oscillations produce serious biases in state of the art CFC metrics. Although most of studies treat nonsinusoidal waves as a nuisance or just ignore them, fortunately some scientists are starting to exploit their neurophysiological relevance opening new research vistas with critical implications.

Cross-sensory cuing drives cross-frequency neural coupling, dramatically altering performance of a taxing visual-detection task

2012 ◽  
Vol 25 (0) ◽  
pp. 62
Author(s):  
John J. Foxe ◽  
Adam C. Snyder ◽  
Manuel R. Mercier ◽  
John S. Butler ◽  
Sophie Molholm ◽  
...  
Keyword(s):  
Target Detection ◽  
Visual Detection ◽  
Visual Target ◽  
Phase Detection ◽  
Perceptual Sensitivity ◽  
Attention Task ◽  
Neuronal Ensembles ◽  
Frequency Coupling ◽  
Phase Amplitude ◽  
Cross Frequency Coupling

Functional networks are comprised of neuronal ensembles bound through synchronization across multiple intrinsic oscillatory frequencies. Various coupled interactions between brain oscillators have been described (e.g., phase–amplitude coupling), but with little evidence that these interactions actually influence perceptual sensitivity. Here, electroencephalographic recordings were made during a sustained-attention task to demonstrate that cross-frequency coupling, driven by cross-sensory cuing, has significant consequences for perceptual outcomes (i.e., whether participants detect a near-threshold visual target). Our results reveal that phase-detection relationships at higher frequencies are entirely dependent on the phase of lower frequencies, such that higher frequencies alternate between periods when their phase is strongly predictive of visual-target detection and periods when their phase has no influence whatsoever. These data thus bridge the crucial gap between complex oscillatory phenomena and perceptual outcomes. Accounting for cross-frequency coupling between lower (i.e., delta and theta) and higher frequencies (e.g., beta and gamma), we show that visual-target detection fluctuates dramatically as a function of pre-stimulus phase, with performance swings of as much as 80%.

Fluid Intelligence and the Cross-Frequency Coupling of Neuronal Oscillations

2016 ◽  
Vol 19 ◽  
Author(s):  
Adam Chuderski
Keyword(s):  
Fluid Intelligence ◽  
Theoretical Models ◽  
Optimal Level ◽  
Neuronal Oscillations ◽  
Frequency Coupling ◽  
Individual Capacity ◽  
Oscillatory Coupling ◽  
The Individual ◽  
Promising Line ◽  
Cross Frequency Coupling

AbstractSeveral existing theoretical models predict that the individual capacity of working memory and abstract reasoning (fluid intelligence) strongly depends on certain features of neuronal oscillations, especially their cross-frequency coupling. Empirical evidence supporting these predictions is still scarce, but it makes the future studies on oscillatory coupling a promising line of research that can uncover the physiological underpinnings of fluid intelligence. Cross-frequency coupling may serve as the optimal level of description of neurocognitive processes, integrating their genetic, structural, neurochemical, and bioelectrical underlying factors with explanations in terms of cognitive operations driven by neuronal oscillations.

scholarly journals Two generalized algorithms measuring phase–amplitude cross-frequency coupling in neuronal oscillations network

2016 ◽  
Vol 10 (3) ◽  
pp. 235-243 ◽  
Author(s):  
Qun Li ◽  
Chen-guang Zheng ◽  
Ning Cheng ◽  
Yi-yi Wang ◽  
Tao Yin ◽  
...  
Keyword(s):  
Neuronal Oscillations ◽  
Frequency Coupling ◽  
Phase Amplitude ◽  
Cross Frequency Coupling

scholarly journals Advances in the Application of Machine Learning Techniques for Power System Analytics: A Survey

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4776
Author(s):  
Seyed Mahdi Miraftabzadeh ◽  
Michela Longo ◽  
Federica Foiadelli ◽  
Marco Pasetti ◽  
Raul Igual
Keyword(s):  
Machine Learning ◽  
Power Systems ◽  
Smart Grids ◽  
State Of The Art ◽  
Smart Cities ◽  
Power Grids ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
New Research ◽  
Traditional Approaches

The recent advances in computing technologies and the increasing availability of large amounts of data in smart grids and smart cities are generating new research opportunities in the application of Machine Learning (ML) for improving the observability and efficiency of modern power grids. However, as the number and diversity of ML techniques increase, questions arise about their performance and applicability, and on the most suitable ML method depending on the specific application. Trying to answer these questions, this manuscript presents a systematic review of the state-of-the-art studies implementing ML techniques in the context of power systems, with a specific focus on the analysis of power flows, power quality, photovoltaic systems, intelligent transportation, and load forecasting. The survey investigates, for each of the selected topics, the most recent and promising ML techniques proposed by the literature, by highlighting their main characteristics and relevant results. The review revealed that, when compared to traditional approaches, ML algorithms can handle massive quantities of data with high dimensionality, by allowing the identification of hidden characteristics of (even) complex systems. In particular, even though very different techniques can be used for each application, hybrid models generally show better performances when compared to single ML-based models.

scholarly journals Delta-mediated cross-frequency coupling organizes oscillatory activity across the rat cortico-basal ganglia network

2013 ◽  
Vol 7 ◽  
Author(s):  
Jon López-Azcárate ◽  
María Jesús Nicolás ◽  
Ivan Cordon ◽  
Manuel Alegre ◽  
Miguel Valencia ◽  
...  
Keyword(s):  
Basal Ganglia ◽  
Oscillatory Activity ◽  
Frequency Coupling ◽  
Cross Frequency Coupling
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