Literature DB >> 24666162

Prestimulus interhemispheric coupling of brain rhythms predicts cognitive-motor performance in healthy humans.

Fabrizio Vecchio1, Giordano Lacidogna, Francesca Miraglia, Placido Bramanti, Florinda Ferreri, Paolo Maria Rossini.   

Abstract

Physiological and neuroimaging studies suggest that human actions are characterized by time-varying engagement of functional distributed networks within the brain. In this study, we investigated whether specific prestimulus interhemispheric connectivity, as a measure of synchronized network between the two hemispheres, could lead to a better performance (as revealed by RT) in a simple visuomotor task. Eighteen healthy adults underwent EEG recording during a visual go/no-go task. In the go/no-go task, a central fixation stimulus was followed by a green (50% of probability) or red visual stimulus. Participants had to press the mouse button after the green stimuli (go trials). Interhemispheric coupling was evaluated by the spectral coherence among all the electrodes covering one hemisphere and matched with those on the other. The frequency bands of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), beta 2 (20-30 Hz), and gamma (30-40 Hz). The task-related results showed that interhemispheric connectivity decreased in delta and increased in alpha band. Furthermore, we observed positive delta and negative alpha correlations with the RT; namely, the faster the RT, the lower delta and the higher alpha connection between the two hemispheres. These results suggested that the best performance is anticipated by the better functional coupling of cortical circuits involved during the processing of the sensorimotor information, occurring between the two hemispheres pending cognitive go/no-go task.

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Year:  2014        PMID: 24666162     DOI: 10.1162/jocn_a_00615

Source DB:  PubMed          Journal:  J Cogn Neurosci        ISSN: 0898-929X            Impact factor:   3.225


  7 in total

1.  Role of Interhemispheric Cortical Interactions in Poststroke Motor Function.

Authors:  Jacqueline A Palmer; Lewis A Wheaton; Whitney A Gray; Mary Alice Saltão da Silva; Steven L Wolf; Michael R Borich
Journal:  Neurorehabil Neural Repair       Date:  2019-07-22       Impact factor: 3.919

2.  Performance prediction in a visuo-motor task: the contribution of EEG analysis.

Authors:  Fabrizio Vecchio; Francesca Alù; Alessandro Orticoni; Francesca Miraglia; Elda Judica; Maria Cotelli; Paolo Maria Rossini
Journal:  Cogn Neurodyn       Date:  2021-09-11       Impact factor: 5.082

3.  Evaluating interhemispheric cortical responses to transcranial magnetic stimulation in chronic stroke: A TMS-EEG investigation.

Authors:  Michael R Borich; Lewis A Wheaton; Sonia M Brodie; Bimal Lakhani; Lara A Boyd
Journal:  Neurosci Lett       Date:  2016-03-03       Impact factor: 3.046

4.  Probing the Functional and Structural Connectivity Underlying EEG Traveling Waves.

Authors:  Yun Qin; Nan Zhang; Yan Chen; Yue Tan; Zhenglin Yang; Yi Shi; Cheng Luo; Tiejun Liu; Dezhong Yao
Journal:  Brain Topogr       Date:  2021-07-21       Impact factor: 3.020

5.  Opportunities for concurrent transcranial magnetic stimulation and electroencephalography to characterize cortical activity in stroke.

Authors:  Sumire Sato; Til Ole Bergmann; Michael R Borich
Journal:  Front Hum Neurosci       Date:  2015-05-05       Impact factor: 3.169

6.  Unimanual sensorimotor learning-A simultaneous EEG-fMRI aging study.

Authors:  Sabrina Chettouf; Paul Triebkorn; Andreas Daffertshofer; Petra Ritter
Journal:  Hum Brain Mapp       Date:  2022-02-08       Impact factor: 5.038

7.  Ready for change: Oscillatory mechanisms of proactive motor control.

Authors:  Matthias Liebrand; Jascha Kristek; Elinor Tzvi; Ulrike M Krämer
Journal:  PLoS One       Date:  2018-05-16       Impact factor: 3.240

  7 in total

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