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Soltani Kouhbanani S, Arabi SM, Zarenezhad S. Does the Frontal Brain Electrical Activity Mediate the Effect of Home Executive Function Environment and Screen Time on Children's Executive Function? J Genet Psychol 2023; 184:430-445. [PMID: 37335540 DOI: 10.1080/00221325.2023.2223653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Accepted: 06/06/2023] [Indexed: 06/21/2023]
Abstract
Executive functions play an important role in various developmental aspects of children; however, environmental factors influencing individual differences in children's executive function and their neural substructures, particularly in middle childhood, are rarely investigated. Therefore, the current study aimed to investigate the relationship between the home executive function environment (HEFE) and screen time with the executive function of children aged 8-12 years by employing the mediating variables of alpha, beta, and theta waves. The parents of 133 normal children completed Barkley Deficits in Executive Functioning, HEFE, and Screen Time Scales. Alpha, beta, and theta brain waves were also measured. Data were examined using correlational and path analysis. The results suggested a positive and significant relationship between home executive functions and the executive functions of children. Furthermore, the results indicated an inverse and significant relationship between screen time and executive function. The results also proved the mediating role of alpha, beta, and theta brain waves in the relationship between screen time and the children's executive function. Environmental factors (such as home environment and screen time) affect the function of brain waves and, thus, the daily executive function of children.
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Affiliation(s)
- Sakineh Soltani Kouhbanani
- Department of Educational Sciences, Educational Sciences and Psychology Faculty, Ferdowsi University of Mashhad, Mashhad, Iran
| | - Seyedeh Manizheh Arabi
- Department of Motor Behavior, Faculty of Sports Sciences, Bu-Ali Sina University, Hamedan, Iran
| | - Somayeh Zarenezhad
- Department of Educational Sciences, Educational Sciences and Psychology Faculty, Ferdowsi University of Mashhad, Mashhad, Iran
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Thiele JA, Richter A, Hilger K. Multimodal Brain Signal Complexity Predicts Human Intelligence. eNeuro 2023; 10:ENEURO.0345-22.2022. [PMID: 36657966 PMCID: PMC9910576 DOI: 10.1523/eneuro.0345-22.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 12/01/2022] [Accepted: 12/13/2022] [Indexed: 01/20/2023] Open
Abstract
Spontaneous brain activity builds the foundation for human cognitive processing during external demands. Neuroimaging studies based on functional magnetic resonance imaging (fMRI) identified specific characteristics of spontaneous (intrinsic) brain dynamics to be associated with individual differences in general cognitive ability, i.e., intelligence. However, fMRI research is inherently limited by low temporal resolution, thus, preventing conclusions about neural fluctuations within the range of milliseconds. Here, we used resting-state electroencephalographical (EEG) recordings from 144 healthy adults to test whether individual differences in intelligence (Raven's Advanced Progressive Matrices scores) can be predicted from the complexity of temporally highly resolved intrinsic brain signals. We compared different operationalizations of brain signal complexity (multiscale entropy, Shannon entropy, Fuzzy entropy, and specific characteristics of microstates) regarding their relation to intelligence. The results indicate that associations between brain signal complexity measures and intelligence are of small effect sizes (r ∼ 0.20) and vary across different spatial and temporal scales. Specifically, higher intelligence scores were associated with lower complexity in local aspects of neural processing, and less activity in task-negative brain regions belonging to the default-mode network. Finally, we combined multiple measures of brain signal complexity to show that individual intelligence scores can be significantly predicted with a multimodal model within the sample (10-fold cross-validation) as well as in an independent sample (external replication, N = 57). In sum, our results highlight the temporal and spatial dependency of associations between intelligence and intrinsic brain dynamics, proposing multimodal approaches as promising means for future neuroscientific research on complex human traits.
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Affiliation(s)
- Jonas A Thiele
- Department of Psychology I, University of Würzburg, Würzburg 97070, Germany
| | - Aylin Richter
- Department of Biology, University of Würzburg, Würzburg 97074, Germany
| | - Kirsten Hilger
- Department of Psychology I, University of Würzburg, Würzburg 97070, Germany
- Department of Psychology, Frankfurt University, Frankfurt am Main 60629, Germany
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Meng X, Sun C, Du B, Liu L, Zhang Y, Dong Q, Georgiou GK, Nan Y. The development of brain rhythms at rest and its impact on vocabulary acquisition. Dev Sci 2021; 25:e13157. [PMID: 34258830 DOI: 10.1111/desc.13157] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 06/28/2021] [Accepted: 07/01/2021] [Indexed: 11/27/2022]
Abstract
A long-standing question in developmental science is how the neurodevelopment of the brain influences cognitive functions. Here, we examined the developmental change of resting EEG power and its links to vocabulary acquisition in school-age children. We further explored what mechanisms may mediate the relation between brain rhythm maturation and vocabulary knowledge. Eyes-opened resting-state EEG data were recorded from 53 typically-developing Chinese children every 2 years between the ages of 7 and 11. Our results showed first that delta, theta, and gamma power decreased over time, whereas alpha and beta power increased over time. Second, after controlling for general cognitive abilities, age, home literacy environment, and phonological skills, theta decreases explained 6.9% and 14.4% of unique variance in expressive vocabulary at ages 9 and 11, respectively. We also found that beta increase from age 7 to 9 significantly predicted receptive vocabulary at age 11. Finally, theta decrease predicted expressive vocabulary through the effects of phoneme deletion at age 9 and tone discrimination at age 11. These results substantiate the important role of brain oscillations at rest, especially theta rhythm, in language development. The developmental change of brain rhythms could serve as sensitive biomarkers for vocabulary development in school-age children, which would be of great value in identifying children at risk of language impairment.
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Affiliation(s)
- Xiangyun Meng
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Chen Sun
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Boqi Du
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Li Liu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yuxuan Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - George K Georgiou
- Department of Educational Psychology, University of Alberta, Edmonton, Alberta, Canada
| | - Yun Nan
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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Anderson AJ, Perone S. Developmental change in the resting state electroencephalogram: Insights into cognition and the brain. Brain Cogn 2018; 126:40-52. [DOI: 10.1016/j.bandc.2018.08.001] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2018] [Revised: 07/29/2018] [Accepted: 08/01/2018] [Indexed: 01/14/2023]
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Soffer‐Dudek N, Todder D, Shelef L, Deutsch I, Gordon S. A neural correlate for common trait dissociation: Decreased EEG connectivity is related to dissociative absorption. J Pers 2018; 87:295-309. [DOI: 10.1111/jopy.12391] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2017] [Revised: 02/05/2018] [Accepted: 03/26/2018] [Indexed: 12/21/2022]
Affiliation(s)
| | - Doron Todder
- Mental Health Center, Ministry of HealthBeer‐Sheva Israel
- Zlotowski Center for NeuroscienceBen‐Gurion University of the Negev
| | - Leah Shelef
- Israel Defense Force Medical CorpsTel Hashomer Ramat‐Gan Israel
| | - Inbal Deutsch
- Israel Defense Force Medical CorpsTel Hashomer Ramat‐Gan Israel
| | - Shirley Gordon
- Department of PsychologyBen‐Gurion University of the Negev
- Israel Defense Force Medical CorpsTel Hashomer Ramat‐Gan Israel
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Gordon S, Todder D, Deutsch I, Garbi D, Getter N, Meiran N. Are resting state spectral power measures related to executive functions in healthy young adults? Neuropsychologia 2018; 108:61-72. [DOI: 10.1016/j.neuropsychologia.2017.10.031] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2017] [Revised: 10/19/2017] [Accepted: 10/27/2017] [Indexed: 10/18/2022]
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Fleck JI, Kuti J, Mercurio J, Mullen S, Austin K, Pereira O. The Impact of Age and Cognitive Reserve on Resting-State Brain Connectivity. Front Aging Neurosci 2017; 9:392. [PMID: 29249962 PMCID: PMC5716980 DOI: 10.3389/fnagi.2017.00392] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2017] [Accepted: 11/13/2017] [Indexed: 12/20/2022] Open
Abstract
Cognitive reserve (CR) is a protective mechanism that supports sustained cognitive function following damage to the physical brain associated with age, injury, or disease. The goal of the research was to identify relationships between age, CR, and brain connectivity. A sample of 90 cognitively normal adults, ages 45–64 years, had their resting-state brain activity recorded with electroencephalography (EEG) and completed a series of memory and executive function assessments. CR was estimated using years of education and verbal IQ scores. Participants were divided into younger and older age groups and low- and high-CR groups. We observed greater left- than right-hemisphere coherence in younger participants, and greater right- than left-hemisphere coherence in older participants. In addition, greater coherence was observed under eyes-closed than eyes-open recording conditions for both low-CR and high-CR participants, with a more substantial difference between recording conditions in individuals high in CR regardless of age. Finally, younger participants low in CR exhibited greater mean coherence than younger participants high in CR, whereas the opposite pattern was observed in older participants, with greater coherence in older participants high in CR. Together, these findings suggest the possibility of a shift in the relationship between CR and brain connectivity during aging.
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Affiliation(s)
- Jessica I Fleck
- School of Social and Behavioral Sciences, Stockton University, Galloway Township, NJ, United States
| | - Julia Kuti
- School of Social and Behavioral Sciences, Stockton University, Galloway Township, NJ, United States
| | - Jeffrey Mercurio
- Department of Cell Biology and Molecular Biology, National Institute of Child Health and Human Development, Bethesda, MD, United States
| | - Spencer Mullen
- School of Social and Behavioral Sciences, Stockton University, Galloway Township, NJ, United States
| | - Katherine Austin
- School of Graduate Studies, Stockton University, Galloway Township, NJ, United States
| | - Olivia Pereira
- Department of Biomedical Research, Nemours Hospital for Children, Wilmington, DE, United States
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Fleck JI, Kuti J, Brown J, Mahon JR, Gayda-Chelder C. Frontal-posterior coherence and cognitive function in older adults. Int J Psychophysiol 2016; 110:217-230. [DOI: 10.1016/j.ijpsycho.2016.07.501] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2015] [Revised: 07/13/2016] [Accepted: 07/18/2016] [Indexed: 11/26/2022]
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