Literature DB >> 30070505

Rhythmic activities of the brain: Quantifying the high complexity of beta and gamma oscillations during visuomotor tasks.

Roman Baravalle1, Osvaldo A Rosso2, Fernando Montani1.   

Abstract

Electroencephalography (EEG) signals depict the electrical activity that takes place at the surface of the brain and provide an important tool for understanding a variety of cognitive processes. The EEG is the product of synchronized activity of the brain, and variations in EEG oscillations patterns reflect the underlying changes in neuronal synchrony. Our aim is to characterize the complexity of the EEG rhythmic oscillations bands when the subjects perform a visuomotor or imagined cognitive tasks (imagined movement), providing a causal mapping of the dynamical rhythmic activities of the brain as a measure of attentional investment. We estimate the intrinsic correlational structure of the signals within the causality entropy-complexity plane H×C, where the enhanced complexity in the gamma 1, gamma 2, and beta 1 bands allows us to distinguish motor-visual memory tasks from control conditions. We identify the dynamics of the gamma 1, gamma 2, and beta 1 rhythmic oscillations within the zone of a chaotic dissipative behavior, whereas in contrast the beta 2 band shows a much higher level of entropy and a significant low level of complexity that correspond to a non-invertible cubic map. Our findings enhance the importance of the gamma band during attention in perceptual feature binding during the visuomotor/imagery tasks.

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Year:  2018        PMID: 30070505     DOI: 10.1063/1.5025187

Source DB:  PubMed          Journal:  Chaos        ISSN: 1054-1500            Impact factor:   3.642


  3 in total

1.  Introducing chaotic codes for the modulation of code modulated visual evoked potentials (c-VEP) in normal adults for visual fatigue reduction.

Authors:  Zahra Shirzhiyan; Ahmadreza Keihani; Morteza Farahi; Elham Shamsi; Mina GolMohammadi; Amin Mahnam; Mohsen Reza Haidari; Amir Homayoun Jafari
Journal:  PLoS One       Date:  2019-03-06       Impact factor: 3.240

2.  Causal Shannon-Fisher Characterization of Motor/Imagery Movements in EEG.

Authors:  Román Baravalle; Osvaldo A Rosso; Fernando Montani
Journal:  Entropy (Basel)       Date:  2018-09-02       Impact factor: 2.524

3.  Permutation Entropy and Statistical Complexity in Mild Cognitive Impairment and Alzheimer's Disease: An Analysis Based on Frequency Bands.

Authors:  Ignacio Echegoyen; David López-Sanz; Johann H Martínez; Fernando Maestú; Javier M Buldú
Journal:  Entropy (Basel)       Date:  2020-01-18       Impact factor: 2.524

  3 in total

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