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Zhong H, Wang J, Li H, Tian J, Fang J, Xu Y, Jiao W, Li G. Reorganization of Brain Functional Network during Task Switching before and after Mental Fatigue. SENSORS (BASEL, SWITZERLAND) 2022; 22:8036. [PMID: 36298387 PMCID: PMC9611295 DOI: 10.3390/s22208036] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Revised: 10/18/2022] [Accepted: 10/19/2022] [Indexed: 06/16/2023]
Abstract
Mental fatigue is a widely studied topic on account of its serious negative effects. But how the neural mechanism of task switching before and after mental fatigue remains a question. To this end, this study aims to use brain functional network features to explore the answer to this question. Specifically, task-state EEG signals were recorded from 20 participants. The tasks include a 400-s 2-back-task (2-BT), followed by a 6480-s of mental arithmetic task (MAT), and then a 400-s 2-BT. Network features and functional connections were extracted and analyzed based on the selected task switching states, referred to from Pre_2-BT to Pre_MAT before mental fatigue and from Post_MAT to Post_2-BT after mental fatigue. The results showed that mental fatigue has been successfully induced by long-term MAT based on the significant changes in network characteristics and the high classification accuracy of 98% obtained with Support Vector Machines (SVM) between Pre_2-BT and Post_2-BT. when the task switched from Pre_2-BT to Pre_MAT, delta and beta rhythms exhibited significant changes among all network features and the selected functional connections showed an enhanced trend. As for the task switched from Post_MAT to Post_2-BT, the network features and selected functional connectivity of beta rhythm were opposite to the trend of task switching before mental fatigue. Our findings provide new insights to understand the neural mechanism of the brain in the process of task switching and indicate that the network features and functional connections of beta rhythm can be used as neural markers for task switching before and after mental fatigue.
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Affiliation(s)
- Hongyang Zhong
- Key Laboratory of Urban Rail Transit Intelligent Operation and Maintenance Technology & Equipment of Zhejiang Provincial, Zhejiang Normal University, Jinhua 321004, China
- College of Mathematics and Computer Science, Zhejiang Normal University, Jinhua 321004, China
| | - Jie Wang
- Key Laboratory of Urban Rail Transit Intelligent Operation and Maintenance Technology & Equipment of Zhejiang Provincial, Zhejiang Normal University, Jinhua 321004, China
- College of Mathematics and Computer Science, Zhejiang Normal University, Jinhua 321004, China
| | - Huayun Li
- College of Teacher Education, Zhejiang Normal University, Jinhua 321004, China
- Key Laboratory of Intelligent Education Technology and Application, Zhejiang Normal University, Jinhua 321004, China
| | - Jinghong Tian
- Key Laboratory of Urban Rail Transit Intelligent Operation and Maintenance Technology & Equipment of Zhejiang Provincial, Zhejiang Normal University, Jinhua 321004, China
- College of Engineering, Zhejiang Normal University, Jinhua 321004, China
| | - Jiaqi Fang
- Key Laboratory of Urban Rail Transit Intelligent Operation and Maintenance Technology & Equipment of Zhejiang Provincial, Zhejiang Normal University, Jinhua 321004, China
- College of Engineering, Zhejiang Normal University, Jinhua 321004, China
| | - Yanting Xu
- Key Laboratory of Urban Rail Transit Intelligent Operation and Maintenance Technology & Equipment of Zhejiang Provincial, Zhejiang Normal University, Jinhua 321004, China
- College of Engineering, Zhejiang Normal University, Jinhua 321004, China
| | - Weidong Jiao
- Key Laboratory of Urban Rail Transit Intelligent Operation and Maintenance Technology & Equipment of Zhejiang Provincial, Zhejiang Normal University, Jinhua 321004, China
- College of Engineering, Zhejiang Normal University, Jinhua 321004, China
| | - Gang Li
- Key Laboratory of Urban Rail Transit Intelligent Operation and Maintenance Technology & Equipment of Zhejiang Provincial, Zhejiang Normal University, Jinhua 321004, China
- College of Mathematical Medicine, Zhejiang Normal University, Jinhua 321004, China
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Conklin BD. Spectral characteristics of visual working memory in the monkey frontoparietal network. PSYCHOLOGY OF LEARNING AND MOTIVATION 2022. [DOI: 10.1016/bs.plm.2022.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Ruiz NC, Egido J, Galindo-Villardón P, Del-Río P. Advantages of Using HJ-Biplot Analysis in Executive Functions Studies. PSICOLOGIA: TEORIA E PESQUISA 2018. [DOI: 10.1590/0102.3772e3426] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Abstract Executive functions (EFs) are considered a multiple system of processing, associated with different components, such as inhibition, working memory, planning, among others. The study of EFs requires the assessment of all its components, having in mind the socio-demographic and cognitive characteristics of the target population. Nowadays, analysis of variance is used to achieve this goal; nevertheless, HJ-Biplot analysis overcome its limitations by allowing simultaneous examination of multiple data, such as those generated in EFs studies. This study evaluates possible differences in the EFs of 80 8-year-old Colombian children by their sex, socio-economic status and type of school they attend, to exemplify the advantages of using HJ-Biplot analysis in neuropsychological studies.
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Thompson GJ. Neural and metabolic basis of dynamic resting state fMRI. Neuroimage 2017; 180:448-462. [PMID: 28899744 DOI: 10.1016/j.neuroimage.2017.09.010] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2017] [Revised: 08/30/2017] [Accepted: 09/06/2017] [Indexed: 02/07/2023] Open
Abstract
Resting state fMRI (rsfMRI) as a technique showed much initial promise for use in psychiatric and neurological diseases where diagnosis and treatment were difficult. To realize this promise, many groups have moved towards examining "dynamic rsfMRI," which relies on the assumption that rsfMRI measurements on short time scales remain relevant to the underlying neural and metabolic activity. Many dynamic rsfMRI studies have demonstrated differences between clinical or behavioral groups beyond what static rsfMRI measured, suggesting a neurometabolic basis. Correlative studies combining dynamic rsfMRI and other physiological measurements have supported this. However, they also indicate multiple mechanisms and, if using correlation alone, it is difficult to separate cause and effect. Hypothesis-driven studies are needed, a few of which have begun to illuminate the underlying neurometabolic mechanisms that shape observed differences in dynamic rsfMRI. While the number of potential noise sources, potential actual neurometabolic sources, and methodological considerations can seem overwhelming, dynamic rsfMRI provides a rich opportunity in systems neuroscience. Even an incrementally better understanding of the neurometabolic basis of dynamic rsfMRI would expand rsfMRI's research and clinical utility, and the studies described herein take the first steps on that path forward.
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Affiliation(s)
- Garth J Thompson
- iHuman Institute, ShanghaiTech University, Shanghai 201210, China.
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Kim HY, Seo K, Jeon HJ, Lee U, Lee H. Application of Functional Near-Infrared Spectroscopy to the Study of Brain Function in Humans and Animal Models. Mol Cells 2017; 40:523-532. [PMID: 28835022 PMCID: PMC5582298 DOI: 10.14348/molcells.2017.0153] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2017] [Accepted: 08/03/2017] [Indexed: 01/26/2023] Open
Abstract
Functional near-infrared spectroscopy (fNIRS) is a noninvasive optical imaging technique that indirectly assesses neuronal activity by measuring changes in oxygenated and deoxygenated hemoglobin in tissues using near-infrared light. fNIRS has been used not only to investigate cortical activity in healthy human subjects and animals but also to reveal abnormalities in brain function in patients suffering from neurological and psychiatric disorders and in animals that exhibit disease conditions. Because of its safety, quietness, resistance to motion artifacts, and portability, fNIRS has become a tool to complement conventional imaging techniques in measuring hemodynamic responses while a subject performs diverse cognitive and behavioral tasks in test settings that are more ecologically relevant and involve social interaction. In this review, we introduce the basic principles of fNIRS and discuss the application of this technique in human and animal studies.
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Affiliation(s)
- Hak Yeong Kim
- Department of Brain and Cognitive Sciences, DGIST, Daegu 42988,
Korea
| | - Kain Seo
- Department of Brain and Cognitive Sciences, DGIST, Daegu 42988,
Korea
| | - Hong Jin Jeon
- Department of Psychiatry, Depression Center, Samsung Medical Center, Sungkyunkwan University, School of Medicine, Seoul 06351,
Korea
| | - Unjoo Lee
- Department of Electronic Engineering, Hallym University, Kangwon 24252,
Korea
| | - Hyosang Lee
- Department of Brain and Cognitive Sciences, DGIST, Daegu 42988,
Korea
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