The Linear and Nonlinear Indices of Electroencephalography Change in the Stroop Color and Word Test
Introduction: This study evaluated the brain activity based on the linear and nonlinear features of surface electroencephalography (EEG) in the Stroop Color and Word Test (SCWT) and the effect of learning in the test response and related EEG features. Materials and Methods: A total of 21 women and...
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| Format: | Article |
| Language: | English |
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Tehran University of Medical Sciences
2022-04-01
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| Series: | Journal of Modern Rehabilitation |
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| Online Access: | https://jmr.tums.ac.ir/index.php/jmr/article/view/384 |
| _version_ | 1818239559003013120 |
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| author | Vahid Sobhani Zahra Rezvani Gholam Hossein Meftahi Fahimeh Ghahvehchi-Hosseini Boshra Hatef |
| author_facet | Vahid Sobhani Zahra Rezvani Gholam Hossein Meftahi Fahimeh Ghahvehchi-Hosseini Boshra Hatef |
| author_sort | Vahid Sobhani |
| collection | DOAJ |
| description |
Introduction: This study evaluated the brain activity based on the linear and nonlinear features of surface electroencephalography (EEG) in the Stroop Color and Word Test (SCWT) and the effect of learning in the test response and related EEG features.
Materials and Methods: A total of 21 women and 19 men with physical and mental health participated in this study. Four stages of this SCWT, consistently in the first and second stages and inconsistently in the third and fourth stages, were taken twice by the participants with a 10-min interval. Besides, EEG recording was simultaneously taken for 1 minute at each stage.
Results: The number of correct responses in the inconsistent stages was lower than that in the consistent stages, while the delay of correct responses was more in the consistent stages. EEG features showed that the relative power band of alpha 1 (8-10 Hz) frequency reduced during the test compared to the resting state. In contrast, the gamma 2 (40-50 Hz) frequency band showed a significant increase. There was no significant difference between various stages of the test and between two repetitions in the test indices and EEG features.
Conclusion: Compared to the resting state, the relative power of alpha 1 and gamma 2 frequency bands changed during SCWT without considering the stage of the test.
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| first_indexed | 2024-12-12T12:59:28Z |
| format | Article |
| id | doaj.art-b2fa8c5fb0f94c49bda33add29753827 |
| institution | Directory Open Access Journal |
| issn | 2538-385X 2538-3868 |
| language | English |
| last_indexed | 2024-12-12T12:59:28Z |
| publishDate | 2022-04-01 |
| publisher | Tehran University of Medical Sciences |
| record_format | Article |
| series | Journal of Modern Rehabilitation |
| spelling | doaj.art-b2fa8c5fb0f94c49bda33add297538272022-12-22T00:23:48ZengTehran University of Medical SciencesJournal of Modern Rehabilitation2538-385X2538-38682022-04-0116210.18502/jmr.v16i2.9300The Linear and Nonlinear Indices of Electroencephalography Change in the Stroop Color and Word TestVahid Sobhani0Zahra Rezvani1Gholam Hossein Meftahi2Fahimeh Ghahvehchi-Hosseini3Boshra Hatef4Exercise Physiology Research Center, Life Style Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.Department of Cognitive and Brain Sciences, Shahid Beheshti University GC, Tehran, Iran.Neuroscience Research Center, Baqiyatallah University of Medical Science, Tehran, Iran.Behavioral Sciences Research Center, Life Style Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.Neuroscience Research Center, Baqiyatallah University of Medical Science, Tehran, Iran. Introduction: This study evaluated the brain activity based on the linear and nonlinear features of surface electroencephalography (EEG) in the Stroop Color and Word Test (SCWT) and the effect of learning in the test response and related EEG features. Materials and Methods: A total of 21 women and 19 men with physical and mental health participated in this study. Four stages of this SCWT, consistently in the first and second stages and inconsistently in the third and fourth stages, were taken twice by the participants with a 10-min interval. Besides, EEG recording was simultaneously taken for 1 minute at each stage. Results: The number of correct responses in the inconsistent stages was lower than that in the consistent stages, while the delay of correct responses was more in the consistent stages. EEG features showed that the relative power band of alpha 1 (8-10 Hz) frequency reduced during the test compared to the resting state. In contrast, the gamma 2 (40-50 Hz) frequency band showed a significant increase. There was no significant difference between various stages of the test and between two repetitions in the test indices and EEG features. Conclusion: Compared to the resting state, the relative power of alpha 1 and gamma 2 frequency bands changed during SCWT without considering the stage of the test. https://jmr.tums.ac.ir/index.php/jmr/article/view/384Stroop color and word testElectroencephalograpy (EEG)NonlinearArtificial neural network model |
| spellingShingle | Vahid Sobhani Zahra Rezvani Gholam Hossein Meftahi Fahimeh Ghahvehchi-Hosseini Boshra Hatef The Linear and Nonlinear Indices of Electroencephalography Change in the Stroop Color and Word Test Journal of Modern Rehabilitation Stroop color and word test Electroencephalograpy (EEG) Nonlinear Artificial neural network model |
| title | The Linear and Nonlinear Indices of Electroencephalography Change in the Stroop Color and Word Test |
| title_full | The Linear and Nonlinear Indices of Electroencephalography Change in the Stroop Color and Word Test |
| title_fullStr | The Linear and Nonlinear Indices of Electroencephalography Change in the Stroop Color and Word Test |
| title_full_unstemmed | The Linear and Nonlinear Indices of Electroencephalography Change in the Stroop Color and Word Test |
| title_short | The Linear and Nonlinear Indices of Electroencephalography Change in the Stroop Color and Word Test |
| title_sort | linear and nonlinear indices of electroencephalography change in the stroop color and word test |
| topic | Stroop color and word test Electroencephalograpy (EEG) Nonlinear Artificial neural network model |
| url | https://jmr.tums.ac.ir/index.php/jmr/article/view/384 |
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