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Volume 26, Issue 2 (summer 2024)
Advances in Cognitive Sciences 2024, 26(2): 47-62 |
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Ethics code: IR. UT. PSYEDU. REC. 1401. 083
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Piryaei S, Rahnama ye Lashkami P. Electroencephalography-based neural correlates of cognitive flexibility in adults as potential biomarkers. Advances in Cognitive Sciences 2024; 26 (2) :47-62
URL: http://icssjournal.ir/article-1-1543-en.html
URL: http://icssjournal.ir/article-1-1543-en.html
1- Assistant Professor, Department of Psychology, Refah University College, Tehran, Iran
2- PhD Student of Cognitive Neuroscience, Shahid Beheshti University, Tehran, Iran
2- PhD Student of Cognitive Neuroscience, Shahid Beheshti University, Tehran, Iran
Abstract: (527 Views)
Introduction
Cognitive flexibility is a critical executive function that enables individuals to adapt to change and problem-solve in new situations. A key component of cognitive flexibility is the ability to think beyond conventional frameworks, allowing for alternative solutions when initial strategies fail. This capacity for flexible thinking forms the foundation for generating innovative and creative ideas.
Cognitive flexibility is intricately linked to brain function. Previous research has established a strong association between cognitive flexibility, prefrontal cortex activity, as well as, frontotemporal region and fronto-parietal networks, which are involved in higher-order cognitive processes. Various neuroimaging techniques have been developed to assess brain function, with Electroencephalography (EEG) emerging as a particularly promising tool for evaluation and clinical applications. The EEG and Event-Related Potentials (ERPs) allow an investigation of brain large-scale networks with millisecond precision. Therefore, high-density ERPs can capture the brain dynamics of cognitive flexibility. Furthermore, this method is non-invasive, making it particularly suitable for studying mental disorders. The EEG monitors the electrical activity within the brain using small electrodes, measuring voltage fluctuations on the scalp. Studies have demonstrated that EEG waves can serve as a predictor of cognitive performance, specifically highlighting the relevance of theta and alpha frequency bands to cognitive functions.
Cognitive flexibility plays a vital role in our daily lives, making it crucial to understand the factors that affect this ability. In this regard, Several types of biomarkers have been associated with cognitive flexibility. Neurotransmitters such as dopamine and serotonin play critical roles in modulating cognitive functions, with variations in their signaling pathways linked to changes in cognitive flexibility. Electrophysiological measures, such as ERPs and EEG, offer insights into brain activity associated with cognitive processing. EEG is considered a physiological biomarker through signal processing. Additionally, genetic and epigenetic markers provide a deeper understanding of the underlying biological mechanisms influencing cognitive flexibility. This study aims to explore the neural correlates of cognitive flexibility based on electrophysiological biomarkers assessing among employees, thereby enhancing our understanding of how individual differences in brain function impact workplace performance and adaptability.
Methods
This study utilized a correlational research design. The target population included all employees (N=300) at a telephone counseling center in Tehran. From this population, 53 participants (43 female, 10 male) were selected through the purposive sampling method. Participants were required to be over 20 years old and have no history of brain damage or seizures to be included in the study.
The study was approved by the research Ethics Committee of the Faculty of Psychology and Education of Tehran University, Iran, under the ethics code IR.UT.PSYEDU.REC.1401.083. Cognitive flexibility was measured using the Wisconsin Card Sorting Test (WCST). Brain activity was recorded using the MITSAR 32-Channel EEG Amplifier. EEG data were collected from 19 electrodes positioned according to the international 10-20 system, with the average of the channels used as a reference. The sampling rate was set at 250 Hz. To remove electrical noise at 50 Hz, a 40 Hz low-pass filter was applied, and Independent Component Analysis (ICA) was used to eliminate artifacts from the EEG signals. After preprocessing, the power of theta (4-8 Hz) and alpha (8-12 Hz) frequency bands was calculated using the Welch method.
During data collection, participants first completed the WCST. EEG data were then recorded while participants sat in a comfortable chair in a quiet room free from environmental distractions. The scalp was prepared with cleaning gels, and electrogel was applied to ensure proper electrode contact for accurate brain signal recording.
Descriptive statistics, including mean and standard deviation, were calculated. Partial correlation analyses using Bonferroni correction were conducted to examine the relationships between variables. All data analyses were conducted using SPSS-26 software.
Results
Fifty-three people (43 women and 10 men), with an average age of 27.7 years for men and 27.07 years for women, participated in this research. The results revealed significant correlations between the number of categories completed indicator in the WCST, the absolute power of theta in the T5 region (r=-0.471, P=0.0001) and a negative and significant relationship with the absolute power of alpha in the T5 region (r=-0.421, P=0.002). Furthermore, significant correlations were observed between the number of correct response indicator and the absolute theta power in the T5 region (r=-0.423, P=0.002). Partial correlation analysis revealed that, among the electrophysiological biomarkers of brain activity, alpha and theta activity in the left temporal lobe significantly related to cognitive flexibility indicators in adults.
Conclusion
In summary, the obtained findings highlighted significant relationships between brain waves and indicators of cognitive flexibility. This suggests that alpha and theta waves in this specific brain area may serve as valuable biomarkers for assessing cognitive adaptability.
However, this research has certain limitations that should be addressed in future studies. One limitation is the disproportionate number of female participants compared to male participants, which may affect the generalizability of the findings. Additionally, the study’s cross-sectional design limits the ability to draw causal conclusions and assess changes over time. Future research should include a more balanced sample and employ longitudinal approaches to further elucidate biomarkers’ role in cognitive flexibility.
Ethical Considerations
Compliance with ethical guidelines
To comply with the ethical principles of the research, the researchers obtained written consent forms from all employees to participate in the research. The study was also approved by the Research Ethics Committee of the Faculty of Psychology and Education of Tehran University under the Ethics Code: IR.UT.PSYEDU.REC.1401.083.
Authors’ contributions
Salehe Piryaei provided overall guidance for the research implementation and led the revision of the manuscript. Parisa Rahnama ye Lashkami was responsible for data collection, data analysis, and the initial drafting of the manuscript.
Funding
This research was conducted with personal financial resources.
Acknowledgments
The authors express their deepest gratitude to the managing director of the Heyva telephone consultation group, the executive staff, and all the employees who cooperated in implementing the research.
Conflict of interest
The authors of the present article have not reported any conflict of interest from the publication of the article.
Cognitive flexibility is a critical executive function that enables individuals to adapt to change and problem-solve in new situations. A key component of cognitive flexibility is the ability to think beyond conventional frameworks, allowing for alternative solutions when initial strategies fail. This capacity for flexible thinking forms the foundation for generating innovative and creative ideas.
Cognitive flexibility is intricately linked to brain function. Previous research has established a strong association between cognitive flexibility, prefrontal cortex activity, as well as, frontotemporal region and fronto-parietal networks, which are involved in higher-order cognitive processes. Various neuroimaging techniques have been developed to assess brain function, with Electroencephalography (EEG) emerging as a particularly promising tool for evaluation and clinical applications. The EEG and Event-Related Potentials (ERPs) allow an investigation of brain large-scale networks with millisecond precision. Therefore, high-density ERPs can capture the brain dynamics of cognitive flexibility. Furthermore, this method is non-invasive, making it particularly suitable for studying mental disorders. The EEG monitors the electrical activity within the brain using small electrodes, measuring voltage fluctuations on the scalp. Studies have demonstrated that EEG waves can serve as a predictor of cognitive performance, specifically highlighting the relevance of theta and alpha frequency bands to cognitive functions.
Cognitive flexibility plays a vital role in our daily lives, making it crucial to understand the factors that affect this ability. In this regard, Several types of biomarkers have been associated with cognitive flexibility. Neurotransmitters such as dopamine and serotonin play critical roles in modulating cognitive functions, with variations in their signaling pathways linked to changes in cognitive flexibility. Electrophysiological measures, such as ERPs and EEG, offer insights into brain activity associated with cognitive processing. EEG is considered a physiological biomarker through signal processing. Additionally, genetic and epigenetic markers provide a deeper understanding of the underlying biological mechanisms influencing cognitive flexibility. This study aims to explore the neural correlates of cognitive flexibility based on electrophysiological biomarkers assessing among employees, thereby enhancing our understanding of how individual differences in brain function impact workplace performance and adaptability.
Methods
This study utilized a correlational research design. The target population included all employees (N=300) at a telephone counseling center in Tehran. From this population, 53 participants (43 female, 10 male) were selected through the purposive sampling method. Participants were required to be over 20 years old and have no history of brain damage or seizures to be included in the study.
The study was approved by the research Ethics Committee of the Faculty of Psychology and Education of Tehran University, Iran, under the ethics code IR.UT.PSYEDU.REC.1401.083. Cognitive flexibility was measured using the Wisconsin Card Sorting Test (WCST). Brain activity was recorded using the MITSAR 32-Channel EEG Amplifier. EEG data were collected from 19 electrodes positioned according to the international 10-20 system, with the average of the channels used as a reference. The sampling rate was set at 250 Hz. To remove electrical noise at 50 Hz, a 40 Hz low-pass filter was applied, and Independent Component Analysis (ICA) was used to eliminate artifacts from the EEG signals. After preprocessing, the power of theta (4-8 Hz) and alpha (8-12 Hz) frequency bands was calculated using the Welch method.
During data collection, participants first completed the WCST. EEG data were then recorded while participants sat in a comfortable chair in a quiet room free from environmental distractions. The scalp was prepared with cleaning gels, and electrogel was applied to ensure proper electrode contact for accurate brain signal recording.
Descriptive statistics, including mean and standard deviation, were calculated. Partial correlation analyses using Bonferroni correction were conducted to examine the relationships between variables. All data analyses were conducted using SPSS-26 software.
Results
Fifty-three people (43 women and 10 men), with an average age of 27.7 years for men and 27.07 years for women, participated in this research. The results revealed significant correlations between the number of categories completed indicator in the WCST, the absolute power of theta in the T5 region (r=-0.471, P=0.0001) and a negative and significant relationship with the absolute power of alpha in the T5 region (r=-0.421, P=0.002). Furthermore, significant correlations were observed between the number of correct response indicator and the absolute theta power in the T5 region (r=-0.423, P=0.002). Partial correlation analysis revealed that, among the electrophysiological biomarkers of brain activity, alpha and theta activity in the left temporal lobe significantly related to cognitive flexibility indicators in adults.
Conclusion
In summary, the obtained findings highlighted significant relationships between brain waves and indicators of cognitive flexibility. This suggests that alpha and theta waves in this specific brain area may serve as valuable biomarkers for assessing cognitive adaptability.
However, this research has certain limitations that should be addressed in future studies. One limitation is the disproportionate number of female participants compared to male participants, which may affect the generalizability of the findings. Additionally, the study’s cross-sectional design limits the ability to draw causal conclusions and assess changes over time. Future research should include a more balanced sample and employ longitudinal approaches to further elucidate biomarkers’ role in cognitive flexibility.
Ethical Considerations
Compliance with ethical guidelines
To comply with the ethical principles of the research, the researchers obtained written consent forms from all employees to participate in the research. The study was also approved by the Research Ethics Committee of the Faculty of Psychology and Education of Tehran University under the Ethics Code: IR.UT.PSYEDU.REC.1401.083.
Authors’ contributions
Salehe Piryaei provided overall guidance for the research implementation and led the revision of the manuscript. Parisa Rahnama ye Lashkami was responsible for data collection, data analysis, and the initial drafting of the manuscript.
Funding
This research was conducted with personal financial resources.
Acknowledgments
The authors express their deepest gratitude to the managing director of the Heyva telephone consultation group, the executive staff, and all the employees who cooperated in implementing the research.
Conflict of interest
The authors of the present article have not reported any conflict of interest from the publication of the article.
Type of Study: Research |
Received: 2023/05/1 | Accepted: 2024/09/26 | Published: 2024/11/3
Received: 2023/05/1 | Accepted: 2024/09/26 | Published: 2024/11/3
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