Fluid Intelligence and the Cross-Frequency Coupling of Neuronal Oscillations

2016 ◽  
Vol 19 ◽  
Author(s):  
Adam Chuderski

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.

2018 ◽  
Vol 119 (5) ◽  
pp. 1595-1598 ◽  
Author(s):  
Diego Lozano-Soldevilla

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.


2016 ◽  
Vol 10 (3) ◽  
pp. 235-243 ◽  
Author(s):  
Qun Li ◽  
Chen-guang Zheng ◽  
Ning Cheng ◽  
Yi-yi Wang ◽  
Tao Yin ◽  
...  

2019 ◽  
Author(s):  
Alexander Maye ◽  
Peng Wang ◽  
Jonathan Daume ◽  
Xiaolin Hu ◽  
Andreas K. Engel

AbstractLearning and memorizing sequences of events is an important function of the human brain and the basis for forming expectations and making predictions. Learning is facilitated by repeating a sequence several times, causing rhythmic appearance of the individual sequence elements. This observation invites to consider the resulting multitude of rhythms as a spectral ‘fingerprint’ which characterizes the respective sequence. Here we explore the implications of this perspective by developing a neurobiologically plausible computational model which captures this ‘fingerprint’ by attuning an ensemble of neural oscillators. In our model, this attuning process is based on a number of oscillatory phenomena that have been observed in electrophysiological recordings of brain activity like synchronization, phase locking and reset as well as cross-frequency coupling. We compare the learning properties of the model with behavioral results from a study in human participants and observe good agreement of the errors for different levels of complexity of the sequence to be memorized. Finally, we suggest an extension of the model for processing sequences that extend over several sensory modalities.


Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4842
Author(s):  
Waldemar Kamiński

Nowadays, hydrostatic levelling is a widely used method for the vertical displacements’ determinations of objects such as bridges, viaducts, wharfs, tunnels, high buildings, historical buildings, special engineering objects (e.g., synchrotron), sports and entertainment halls. The measurements’ sensors implemented in the hydrostatic levelling systems (HLSs) consist of the reference sensor (RS) and sensors located on the controlled points (CPs). The reference sensor is the one that is placed at the point that (in theoretical assumptions) is not a subject to vertical displacements and the displacements of controlled points are determined according to its height. The hydrostatic levelling rule comes from the Bernoulli’s law. While using the Bernoulli’s principle in hydrostatic levelling, the following components have to be taken into account: atmospheric pressure, force of gravity, density of liquid used in sensors places at CPs. The parameters mentioned above are determined with some mean errors that influence on the accuracy assessment of vertical displacements. In the subject’s literature, there are some works describing the individual accuracy analyses of the components mentioned above. In this paper, the author proposes the concept of comprehensive determination of mean error of vertical displacement (of each CPs), calculated from the mean errors’ values of components dedicated for specific HLS. The formulas of covariances’ matrix were derived and they enable to make the accuracy assessment of the calculations’ results. The author also presented the subject of modelling of vertical displacements’ gained values. The dependences, enabling to conduct the statistic tests of received model’s parameters, were implemented. The conducted tests make it possible to verify the correctness of used theoretical models of the examined object treated as the rigid body. The practical analyses were conducted for two simulated variants of sensors’ connections in HLS. Variant no. I is the sensors’ serial connection. Variant no. II relies on the connection of each CPs with the reference sensor. The calculations’ results show that more detailed value estimations of the vertical displacements can be obtained using variant no. II.


Author(s):  
Jon López-Azcárate ◽  
María Jesús Nicolás ◽  
Ivan Cordon ◽  
Manuel Alegre ◽  
Miguel Valencia ◽  
...  

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