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Cao J, Luo J, Zhou J, Jiang Y. Attention switching through text dissimilarity: a cognition research on fragmented reading behavior. Front Hum Neurosci 2024; 18:1402746. [PMID: 38983754 PMCID: PMC11231079 DOI: 10.3389/fnhum.2024.1402746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 06/03/2024] [Indexed: 07/11/2024] Open
Abstract
People tend to obtain information through fragmented reading. However, this behavior itself might lead to distraction and affect cognitive ability. To address it, it is necessary to understand how fragmented reading behavior influences readers' attention switching. In this study, the researchers first collected online news that had 6 theme words and 60 sentences to compose the experimental material, then defined the degree of text dissimilarity, used to measure the degree of attention switching based on the differences in text content, and conducted an EEG experiment based on P200. The results showed that even after reading the fragmented text content with the same overall content, people in subsequent cognitive tasks had more working memory capacity, lower working memory load, and less negative impact on cognitive ability with the text content with lower text dissimilarity. Additionally, attention switching caused by differences in concept or working memory representation of text content might be the key factor affecting cognitive ability in fragmented reading behavior. The findings disclosed the relation between cognitive ability and fragmented reading and attention switching, opening a new perspective on the method of text dissimilarity. This study provides some references on how to reduce the negative impact of fragmented reading on cognitive ability on new media platforms.
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Affiliation(s)
- Jingjing Cao
- School of Management Science and Real Estate, Chongqing University, Chongqing, China
| | - Jingtao Luo
- College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, China
| | - Jia Zhou
- School of Management Science and Real Estate, Chongqing University, Chongqing, China
| | - Yunshan Jiang
- School of Management Science and Real Estate, Chongqing University, Chongqing, China
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2
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Pan L, Wang J, Wu W, Wang Y, Zhu Y, Song Y. Transcutaneous auricular vagus nerve stimulation improves working memory in temporal lobe epilepsy: A randomized double-blind study. CNS Neurosci Ther 2024; 30:e14395. [PMID: 37553557 PMCID: PMC10848055 DOI: 10.1111/cns.14395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 06/08/2023] [Accepted: 07/27/2023] [Indexed: 08/10/2023] Open
Abstract
AIMS This study investigated the impact of transcutaneous auricular vagus nerve stimulation (taVNS) on working memory (WM) in refractory temporal lobe epilepsy (rTLE) and the underlying mechanisms. METHODS In this randomized double-blind study, 28 rTLE patients were subjected to an active or sham taVNS (a/s-taVNS) protocol for 20 weeks (a-taVNS group, n = 19; s-ta VNS group, n = 9). Patients performed visual WM tasks during stimulation and neural oscillations were simultaneously recorded by 19-channel electroencephalography. RESULTS Compared with the baseline state, reaction time was significantly shorter after 20 weeks of taVNS in the a-taVNS group (p = 0.010), whereas no difference was observed in the s-taVNS group (p > 0.05). The power spectral density (PSD) of the theta frequency band in the Fz channel decreased significantly after a-taVNS during WM-encoding (p = 0.020), maintenance (p = 0.038), and retrieval (p = 0.039) phases, but not in the s-taVNS group (all p > 0.05). CONCLUSION Neural oscillations during WM were altered by taVNS and WM performance was improved. Alterations in frontal midline theta oscillations may be a marker for the effect of taVNS on cognitive regulation.
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Affiliation(s)
- Liping Pan
- General Medicine DepartmentTianjin Medical University General HospitalTianjinChina
| | - Jiajing Wang
- Department of Intensive Care Medicine, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeTianjinChina
- Tianjin Medical UniversityTianjinChina
| | - Wenjuan Wu
- Department of NeurologyThe First Affiliated Hospital of Henan University of Science and TechnologyLuoyangChina
| | | | | | - Yijun Song
- Department of Intensive Care Medicine, State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology and Blood Diseases HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeTianjinChina
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3
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Chen C, Liang Y, Xu S, Yi C, Li Y, Chen B, Yang L, Liu Q, Yao D, Li F, Xu P. The dynamic causality brain network reflects whether the working memory is solidified. Cereb Cortex 2024; 34:bhad467. [PMID: 38061696 DOI: 10.1093/cercor/bhad467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 11/13/2023] [Accepted: 11/15/2023] [Indexed: 01/19/2024] Open
Abstract
Working memory, which is foundational to higher cognitive function, is the "sketchpad of volitional control." Successful working memory is the inevitable outcome of the individual's active control and manipulation of thoughts and turning them into internal goals during which the causal brain processes information in real time. However, little is known about the dynamic causality among distributed brain regions behind thought control that underpins successful working memory. In our present study, given that correct responses and incorrect ones did not differ in either contralateral delay activity or alpha suppression, further rooting on the high-temporal-resolution EEG time-varying directed network analysis, we revealed that successful working memory depended on both much stronger top-down connections from the frontal to the temporal lobe and bottom-up linkages from the occipital to the temporal lobe, during the early maintenance period, as well as top-down flows from the frontal lobe to the central areas as the delay behavior approached. Additionally, the correlation between behavioral performance and casual interactions increased over time, especially as memory-guided delayed behavior approached. Notably, when using the network metrics as features, time-resolved multiple linear regression of overall behavioral accuracy was exactly achieved as delayed behavior approached. These results indicate that accurate memory depends on dynamic switching of causal network connections and shifting to more task-related patterns during which the appropriate intervention may help enhance memory.
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Affiliation(s)
- Chunli Chen
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Yi Liang
- Department of Neurology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 610072, China
- Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu 610072, China
| | - Shiyun Xu
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Chanlin Yi
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Yuqin Li
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Baodan Chen
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Lei Yang
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Qiang Liu
- Institute of Brain and Psychological Science, Sichuan Normal University, Chengdu 610000, China
| | - Dezhong Yao
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Fali Li
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
| | - Peng Xu
- MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu 611731, China
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China
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Chen X, Ma R, Zhang W, Zeng GQ, Wu Q, Yimiti A, Xia X, Cui J, Liu Q, Meng X, Bu J, Chen Q, Pan Y, Yu NX, Wang S, Deng ZD, Sack AT, Laughlin MM, Zhang X. Alpha oscillatory activity is causally linked to working memory retention. PLoS Biol 2023; 21:e3001999. [PMID: 36780560 PMCID: PMC9983870 DOI: 10.1371/journal.pbio.3001999] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 03/03/2023] [Accepted: 01/12/2023] [Indexed: 02/15/2023] Open
Abstract
Although previous studies have reported correlations between alpha oscillations and the "retention" subprocess of working memory (WM), causal evidence has been limited in human neuroscience due to the lack of delicate modulation of human brain oscillations. Conventional transcranial alternating current stimulation (tACS) is not suitable for demonstrating the causal evidence for parietal alpha oscillations in WM retention because of its inability to modulate brain oscillations within a short period (i.e., the retention subprocess). Here, we developed an online phase-corrected tACS system capable of precisely correcting for the phase differences between tACS and concurrent endogenous oscillations. This system permits the modulation of brain oscillations at the target stimulation frequency within a short stimulation period and is here applied to empirically demonstrate that parietal alpha oscillations causally relate to WM retention. Our experimental design included both in-phase and anti-phase alpha-tACS applied to participants during the retention subprocess of a modified Sternberg paradigm. Compared to in-phase alpha-tACS, anti-phase alpha-tACS decreased both WM performance and alpha activity. These findings strongly support a causal link between alpha oscillations and WM retention and illustrate the broad application prospects of phase-corrected tACS.
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Affiliation(s)
- Xueli Chen
- Department of Radiology, the First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science & Technology of China, Hefei, China
- Department of Social and Behavioural Sciences, City University of Hong Kong, Hong Kong, People’s Republic of China
| | - Ru Ma
- Department of Radiology, the First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science & Technology of China, Hefei, China
| | - Wei Zhang
- Department of Radiology, the First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science & Technology of China, Hefei, China
| | - Ginger Qinghong Zeng
- Application Technology Center of Physical Therapy to Brain Disorders, Institute of Advanced Technology, University of Science & Technology of China, Hefei, China
| | - Qianying Wu
- Department of Radiology, the First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science & Technology of China, Hefei, China
- Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, California, United States of America
| | - Ajiguli Yimiti
- Department of Radiology, the First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science & Technology of China, Hefei, China
| | - Xinzhao Xia
- Centers for Biomedical Engineering, School of Information Science and Technology, University of Science & Technology of China, Hefei, China
| | - Jiangtian Cui
- Centers for Biomedical Engineering, School of Information Science and Technology, University of Science & Technology of China, Hefei, China
- School of Optometry and Vision Science, Cardiff University, Cardiff, United Kingdom
| | - Qiongwei Liu
- Department of Radiology, the First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science & Technology of China, Hefei, China
| | - Xueer Meng
- Department of Radiology, the First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science & Technology of China, Hefei, China
| | - Junjie Bu
- School of Biomedical Engineering, Anhui Medical University, Hefei, China
| | - Qi Chen
- School of Psychology, South China Normal University, Guangzhou, China
| | - Yu Pan
- Shanghai Key Laboratory of Brain-Machine Intelligence for Information Behavior, School of Business and Management, Shanghai International Studies University, Shanghai, China
| | - Nancy Xiaonan Yu
- Department of Social and Behavioural Sciences, City University of Hong Kong, Hong Kong, People’s Republic of China
| | - Shouyan Wang
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
| | - Zhi-De Deng
- Noninvasive Neuromodulation Unit, Experimental Therapeutics & Pathophysiology Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, USA
| | - Alexander T. Sack
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Myles Mc Laughlin
- Exp ORL, Department of Neuroscience, Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Xiaochu Zhang
- Department of Radiology, the First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science & Technology of China, Hefei, China
- Application Technology Center of Physical Therapy to Brain Disorders, Institute of Advanced Technology, University of Science & Technology of China, Hefei, China
- Department of Psychology, School of Humanities & Social Science, University of Science & Technology of China, Hefei, China
- Institute of Health and Medicine, Hefei Comprehensive National Science Center, Hefei, China
- * E-mail:
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Plaska CR, Ortega J, Gomes BA, Ellmore TM. Interhemispheric Connectivity Supports Load-Dependent Working Memory Maintenance for Complex Visual Stimuli. Brain Connect 2022; 12:892-904. [PMID: 35473394 PMCID: PMC9807256 DOI: 10.1089/brain.2021.0171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
Abstract Introduction: One manipulation used to study the neural basis of working memory (WM) is to vary the information load at encoding, then measure activity and connectivity during maintenance in the delay period. A hallmark finding is increased delay activity and connectivity between frontoparietal brain regions with increased load. Most WM studies, however, employ simple stimuli during encoding and unfilled intervals during the delay. In this study, we asked how delay period activity and connectivity change during low and high load maintenance of complex stimuli. Methods: Twenty-two participants completed a modified Sternberg WM task with two or five naturalistic scenes as stimuli during scalp electroencephalography (EEG). On each trial, the delay was filled with phase-scrambled scenes to provide a visual perceptual control with similar color and spatial frequency as presented during encoding. Functional connectivity during the delay was assessed by the phase-locking value (PLV). Results: Results showed reduced theta/alpha delay activity amplitude during high compared with low WM load across frontal, central, and parietal sources. A network with higher connectivity during low load consisted of increased PLV between (1) left frontal and right posterior temporal sources in the theta/alpha bands, (2) right anterior temporal and left central sources in the alpha and lower beta bands, and (3) left anterior temporal and posterior temporal sources in the theta, alpha, and lower beta bands. Discussion: The findings suggest a role for interhemispheric connectivity during WM maintenance of complex stimuli with load modulation when limited attentional resources are essential for filtering. Impact statement The patterns of brain connectivity subserving working memory (WM) have largely been investigated to date using simple stimuli, including letters, digits, and shapes and during unfilled WM delay intervals. Fewer studies describe functional connectivity changes during the maintenance of more naturalistic stimuli in the presence of distractors. In the present study, we employed a scene-based WM task during electroencephalography in healthy humans and found that during low-load WM maintenance with distractors increased interhemispheric connectivity in frontotemporal networks. These findings suggest a role for increased interhemispheric connectivity during maintenance of complex stimuli when attentional resources are essential for filtering.
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Affiliation(s)
- Chelsea Reichert Plaska
- The Behavioral and Cognitive Neuroscience Program, CUNY Graduate Center, New York, New York, USA.,Department of Psychology, The City College of New York, New York, New York, USA
| | - Jefferson Ortega
- The Behavioral and Cognitive Neuroscience Program, CUNY Graduate Center, New York, New York, USA
| | | | - Timothy M. Ellmore
- The Behavioral and Cognitive Neuroscience Program, CUNY Graduate Center, New York, New York, USA.,Department of Psychology, The City College of New York, New York, New York, USA.,Address correspondence to: Timothy M. Ellmore, Department of Psychology, The City College of New York, North Academic Center, 160 Convent Avenue, New York, NY 10031, USA
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6
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Wang J, Huo S, Wu KC, Mo J, Wong WL, Maurer U. Behavioral and neurophysiological aspects of working memory impairment in children with dyslexia. Sci Rep 2022; 12:12571. [PMID: 35869126 PMCID: PMC9307804 DOI: 10.1038/s41598-022-16729-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 07/14/2022] [Indexed: 11/09/2022] Open
Abstract
AbstractThe present study aimed to identify behavioral and neurophysiological correlates of dyslexia which could potentially predict reading difficulty. One hundred and three Chinese children with and without dyslexia (Grade 2 or 3, 7- to 11-year-old) completed both verbal and visual working memory (n-back) tasks with concurrent EEG recording. Data of 74 children with sufficient usable EEG data are reported here. Overall, the typically developing control group (N = 28) responded significantly faster and more accurately than the group with dyslexia (N = 46), in both types of tasks. Group differences were also found in EEG band power in the retention phase of the tasks. Moreover, forward stepwise logistic regression demonstrated that both behavioral and neurophysiological measures predicted reading difficulty uniquely. Dyslexia was associated with higher frontal midline theta activity and reduced upper-alpha power in the posterior region. This finding is discussed in relation to the neural efficiency hypothesis. Whether these behavioral and neurophysiological patterns can longitudinally predict later reading development among preliterate children requires further investigation.
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Li B, Dong H, Wang Y, Li F, Gao X, Ma H, Gao L. Effects of sleep insufficiency on spatial working memory in low-pressure and hypoxic environments. Medicine (Baltimore) 2022; 101:e30210. [PMID: 36107513 PMCID: PMC9439777 DOI: 10.1097/md.0000000000030210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/31/2022] Open
Abstract
BACKGROUND This study aimed to investigate the effects of sleep insufficiency on spatial working memory in low-pressure and hypoxic environments. METHODS We selected 58 insufficient sleepers and 27 normal sleepers among the college students living in high-altitude areas for a long time to receive a spatial 2-back working memory task, while collecting behavioral and electroencephalograph data. We adopted an independent sample t-test and repeated measures analysis of variance to compare the differences in response time and accuracy, P2 and late positive potential components, and theta band energy values in the spatial working memory task between insufficient and normal sleepers. RESULTS We found no significant differences in response time and accuracy between the insufficient sleep group and the normal sleep group; however, the P2 peak value and the early theta band energy value were higher in the insufficient sleep group than in the normal sleep group. CONCLUSIONS These results suggest that the spatial working memory ability of individuals with sleep insufficiency was weakened under low-pressure and low-oxygen environment.
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Affiliation(s)
- Bingqi Li
- Plateau Brain Science Research Center, Tibet University/South China Normal University, Lhasa, China
| | - Haotian Dong
- Plateau Brain Science Research Center, Tibet University/South China Normal University, Lhasa, China
| | - Yanxiang Wang
- Plateau Brain Science Research Center, Tibet University/South China Normal University, Lhasa, China
| | - Fangming Li
- Plateau Brain Science Research Center, Tibet University/South China Normal University, Lhasa, China
| | - Xiaolei Gao
- Plateau Brain Science Research Center, Tibet University/South China Normal University, Lhasa, China
| | - Hailin Ma
- Plateau Brain Science Research Center, Tibet University/South China Normal University, Lhasa, China
| | - Lei Gao
- Plateau Brain Science Research Center, Tibet University/South China Normal University, Lhasa, China
- *Correspondence: Lei Gao, Plateau Brain Science Research Center, Tibet University, Jiangsu Road No. 36, Chengguan District, Lhasa 850000, China (e-mail: )
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Ye H, Li G, Sheng X, Zhu X. Phase-amplitude coupling between low-frequency scalp EEG and high-frequency intracranial EEG during working memory task. J Neural Eng 2022; 19. [PMID: 35441594 DOI: 10.1088/1741-2552/ac63e9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 04/04/2022] [Indexed: 11/12/2022]
Abstract
Objective. Revealing the relationship between simultaneous scalp electroencephalography (EEG) and intracranial electroencephalography (iEEG) is of great importance for both neuroscientific research and translational applications. However, whether prominent iEEG features in the high-gamma band can be reflected by scalp EEG is largely unknown. To address this, we investigated the phase-amplitude coupling (PAC) phenomenon between the low-frequency band of scalp EEG and the high-gamma band of iEEG.Approach. We analyzed a simultaneous iEEG and scalp EEG dataset acquired under a verbal working memory paradigm from nine epilepsy subjects. The PAC values between pairs of scalp EEG channel and identified iEEG channel were explored. After identifying the frequency combinations and electrode locations that generated the most significant PAC values, we compared the PAC values of different task periods (encoding, maintenance, and retrieval) and memory loads.Main results. We demonstrated that the amplitude of high-gamma activities in the entorhinal cortex, hippocampus, and amygdala was correlated to the delta or theta phase at scalp locations such as Cz and Pz. In particular, the frequency bin that generated the maximum PAC value centered at 3.16-3.84 Hz for the phase and 50-85 Hz for the amplitude. Moreover, our results showed that PAC values for the retrieval period were significantly higher than those of the encoding and maintenance periods, and the PAC was also influenced by the memory load.Significance. This is the first human simultaneous iEEG and scalp EEG study demonstrating that the amplitude of iEEG high-gamma components is associated with the phase of low-frequency components in scalp EEG. These findings enhance our understanding of multiscale neural interactions during working memory, and meanwhile, provide a new perspective to estimate intracranial high-frequency features with non-invasive neural recordings.
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Affiliation(s)
- Huanpeng Ye
- State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Guangye Li
- State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Xinjun Sheng
- State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Xiangyang Zhu
- State Key Laboratory of Mechanical System and Vibration, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, People's Republic of China
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Guan K, Zhang Z, Chai X, Tian Z, Liu T, Niu H. EEG Based Dynamic Functional Connectivity Analysis in Mental Workload Tasks with Different Types of Information. IEEE Trans Neural Syst Rehabil Eng 2022; 30:632-642. [PMID: 35239485 DOI: 10.1109/tnsre.2022.3156546] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
The accurate evaluation of operators' mental workload in human-machine systems plays an important role in ensuring the correct execution of tasks and the safety of operators. However, the performance of cross-task mental workload evaluation based on physiological metrics remains unsatisfactory. To explore the changes in dynamic functional connectivity properties with varying mental workload in different tasks, four mental workload tasks with different types of information were designed and a newly proposed dynamic brain network analysis method based on EEG microstate was applied in this paper. Six microstate topographies labeled as Microstate A-F were obtained to describe the task-state EEG dynamics, which was highly consistent with previous studies. Dynamic brain network analysis revealed that 15 nodes and 68 pairs of connectivity from the Frontal-Parietal region were sensitive to mental workload in all four tasks, indicating that these nodal metrics had potential to effectively evaluate mental workload in the cross-task scenario. The characteristic path length of Microstate D brain network in both Theta and Alpha bands decreased whereas the global efficiency increased significantly when the mental workload became higher, suggesting that the cognitive control network of brain tended to have higher function integration property under high mental workload state. Furthermore, by using a SVM classifier, an averaged classification accuracy of 95.8% for within-task and 80.3% for cross-task mental workload discrimination were achieved. Results implies that it is feasible to evaluate the cross-task mental workload using the dynamic functional connectivity metrics under specific microstate, which provided a new insight for understanding the neural mechanism of mental workload with different types of information.
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Zhang W, Guo L, Liu D. Concurrent interactions between prefrontal cortex and hippocampus during a spatial working memory task. Brain Struct Funct 2022; 227:1735-1755. [DOI: 10.1007/s00429-022-02469-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Accepted: 01/28/2022] [Indexed: 11/02/2022]
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Chikhi S, Matton N, Blanchet S. EEG
power spectral measures of cognitive workload: A meta‐analysis. Psychophysiology 2022; 59:e14009. [DOI: 10.1111/psyp.14009] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 12/13/2021] [Accepted: 01/10/2022] [Indexed: 12/22/2022]
Affiliation(s)
- Samy Chikhi
- Laboratoire Mémoire, Cerveau et Cognition (MC2Lab, URP 7536), Institute of Psychology University of Paris Boulogne‐Billancourt France
| | - Nadine Matton
- CLLE‐LTC University of Toulouse, CNRS (UMR5263) Toulouse France
- ENAC Research Lab École Nationale d’Aviation Civile Toulouse France
| | - Sophie Blanchet
- Laboratoire Mémoire, Cerveau et Cognition (MC2Lab, URP 7536), Institute of Psychology University of Paris Boulogne‐Billancourt France
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Pan L, Wu Y, Bao J, Guo D, Zhang X, Wang J, Deng M, Yu P, Wei G, Zhang L, Qin X, Song Y. Alterations in Neural Networks During Working Memory Encoding Related to Cognitive Impairment in Temporal Lobe Epilepsy. Front Hum Neurosci 2022; 15:770678. [PMID: 35069151 PMCID: PMC8766724 DOI: 10.3389/fnhum.2021.770678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Accepted: 12/13/2021] [Indexed: 11/13/2022] Open
Abstract
Objective: The aim of the current study was to investigate the alterations in the neural networks of patients with temporal lobe epilepsy (TLE) during working memory (WM) encoding. Methods: Patients with TLE (n = 52) and healthy volunteers (n = 35) completed a WM task, during which 34-channel electroencephalogram signals were recorded. The neural networks during WM encoding were calculated in TLE patients with (TLE-WM) and without (TLE-N) WM deficits. Results: Functional connectivity strength decreased, and the theta network was altered in the TLE-WM group, although no significant differences in clinical features were observed between the TLE-N and TLE-WM groups. Conclusions: Not all patients with TLE present with cognitive impairments and alterations in the theta network were identified in TLE patients with functional cognitive deficits. Significance: The theta network may represent a sensitive measure of cognitive impairment and could predict cognitive outcomes among patients with TLE.
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Affiliation(s)
- Liping Pan
- General Medicine Department, Tianjin Medical University General Hospital, Tianjin, China
| | - Yakun Wu
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
- Department of Neurology, Tangshan Gongren Hospital, Tangshan, China
| | - Jie Bao
- Department of Rehabilitation Medicine, Tianjin Medical University General Hospital, Tianjin, China
| | - Dandan Guo
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Xin Zhang
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Jiajing Wang
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Meili Deng
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Peiran Yu
- School of Basic Medical Science, Tianjin Medical University, Tianjin, China
| | - Gaoxu Wei
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Lulin Zhang
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
- Department of Neurology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Xiao Qin
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin, China
| | - Yijun Song
- General Medicine Department, Tianjin Medical University General Hospital, Tianjin, China
- Key Laboratory of Central Nerve Injury Repair and Regeneration, Ministry of Education, Tianjin Neurological Institute, Tianjin, China
- *Correspondence: Yijun Song
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Guan K, Chai X, Zhang Z, Li Q, Niu H. Evaluation of Mental Workload in Working Memory Tasks with Different Information Types Based on EEG. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:5682-5685. [PMID: 34892411 DOI: 10.1109/embc46164.2021.9630575] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
To explore the effectiveness of using Electro- encephalogram (EEG) spectral power and multiscale sample entropy for accessing mental workload in different tasks, working memory tasks with different information types (verbal, object and spatial) and various mental loads were designed based on the N-Back paradigm. Subjective scores, accuracy and response time were used to verify the rationality of the tasks. EEGs from 18 normal adults were acquired when tasks were being performed, an independent component analysis (ICA) based artifact removal method were applied to get clean data. Linear (relative power in Theta and Alpha band, etc.) and nonlinear (multiscale sample entropy) features of EEGs were then extracted. Indices that can effectively reflect mental workload levels were selected by using multivariate analysis of variance statistical approach. Results showed that with the increment of task load, power of frontal Theta, Theta/Alpha ratio and sample entropies at scale more than 10 in parietal regions increased significantly first and decreased slightly then, while the power of central-parietal Alpha decreased significantly first and increased slightly then. Considering the difference between task types, no difference in power of frontal Theta, central-parietal Alpha and sample entropies at scales more than 10 of parietal regions were found between verbal and object tasks, as well as between two spatial tasks. No difference of frontal Theta/Alpha ratio was found in all the four tasks. The results can provide evidence for the mental workload evaluation in tasks with different information types.
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Pan L, Guo D, Wang J, Hao Y, Zhang L, Qin X, Song Y. Alterations in neural oscillations related to working memory deficit in temporal lobe epilepsy. Epilepsy Behav 2021; 121:108063. [PMID: 34052633 DOI: 10.1016/j.yebeh.2021.108063] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 02/21/2021] [Accepted: 05/10/2021] [Indexed: 02/04/2023]
Abstract
OBJECTIVE Working memory (WM) is critical for higher level cognition, but the underlying neural mechanisms are not fully understood. Impaired WM affects routine daily activities and is observed in patients with temporal lobe epilepsy (TLE). This study investigated neural oscillations associated with different WM phases, to determine the specific neural activity linked with the phases of WM impairment. METHODS Patients with TLE (n = 52) and healthy volunteers (n = 35) completed a WM task, during which 34-channel electroencephalogram signals were recorded. Characteristic neural oscillation patterns during each WM phase were compared between the 2 groups. RESULTS Patients with TLE showed decreased theta power during the encoding phase of WM, which was associated with reduced accuracy in the WM task. Altered theta power in the frontal region of the brain during the encoding phase was associated with a longer reaction time. CONCLUSIONS Alterations in theta oscillation are related to WM impairment in patients with TLE and may serve as an early marker for evaluating WM deficits. SIGNIFICANCE This study provides an early marker for evaluating WM deficits in TLE.
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Affiliation(s)
- Liping Pan
- General Medicine Department, Tianjin Medical University General Hospital, Tianjin 300052, China; Tianjin Neurological Institute, Tianjin 300052, China
| | - Dandan Guo
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Jiajing Wang
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin 300052, China; Second Clinical Medical College of Tianjin Medical University, Tianjin 300211, China
| | - Yuhan Hao
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Lulin Zhang
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Xiao Qin
- Department of Neurology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yijun Song
- General Medicine Department, Tianjin Medical University General Hospital, Tianjin 300052, China; Tianjin Neurological Institute, Tianjin 300052, China.
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15
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Xie Y, Li Y, Duan H, Xu X, Zhang W, Fang P. Theta Oscillations and Source Connectivity During Complex Audiovisual Object Encoding in Working Memory. Front Hum Neurosci 2021; 15:614950. [PMID: 33762914 PMCID: PMC7982740 DOI: 10.3389/fnhum.2021.614950] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 01/28/2021] [Indexed: 12/02/2022] Open
Abstract
Working memory is a limited capacity memory system that involves the short-term storage and processing of information. Neuroscientific studies of working memory have mostly focused on the essential roles of neural oscillations during item encoding from single sensory modalities (e.g., visual and auditory). However, the characteristics of neural oscillations during multisensory encoding in working memory are rarely studied. Our study investigated the oscillation characteristics of neural signals in scalp electrodes and mapped functional brain connectivity while participants encoded complex audiovisual objects in a working memory task. Experimental results showed that theta oscillations (4–8 Hz) were prominent and topographically distributed across multiple cortical regions, including prefrontal (e.g., superior frontal gyrus), parietal (e.g., precuneus), temporal (e.g., inferior temporal gyrus), and occipital (e.g., cuneus) cortices. Furthermore, neural connectivity at the theta oscillation frequency was significant in these cortical regions during audiovisual object encoding compared with single modality object encoding. These results suggest that local oscillations and interregional connectivity via theta activity play an important role during audiovisual object encoding and may contribute to the formation of working memory traces from multisensory items.
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Affiliation(s)
- Yuanjun Xie
- School of Education, Xin Yang College, Xinyang, China.,Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Yanyan Li
- School of Education, Xin Yang College, Xinyang, China
| | - Haidan Duan
- School of Education, Xin Yang College, Xinyang, China
| | - Xiliang Xu
- School of Education, Xin Yang College, Xinyang, China
| | - Wenmo Zhang
- Department of Fundamental, Army Logistical University, Chongqing, China.,Department of Social Medicine and Health and Management, College of Military Preventive Medicine, Army Medical University, Chongqing, China
| | - Peng Fang
- Department of Military Medical Psychology, Fourth Military Medical University, Xi'an, China
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16
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Pavlov YG, Kotchoubey B. Oscillatory brain activity and maintenance of verbal and visual working memory: A systematic review. Psychophysiology 2020; 59:e13735. [PMID: 33278030 DOI: 10.1111/psyp.13735] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2020] [Revised: 11/04/2020] [Accepted: 11/10/2020] [Indexed: 12/15/2022]
Abstract
Brain oscillations likely play a significant role in the storage of information in working memory (WM). Despite the wide popularity of the topic, current attempts to summarize the research in the field are narrative reviews. We address this gap by providing a descriptive systematic review, in which we investigated oscillatory correlates of maintenance of verbal and visual information in WM. The systematic approach enabled us to challenge some common views popularized by previous research. The identified literature (100 EEG/MEG studies) highlighted the importance of theta oscillations in verbal WM: frontal midline theta enhanced with load in most verbal studies, while more equivocal results have been obtained in visual studies. Increasing WM load affected alpha activity in most studies, but the direction of the effect was inconsistent: the ratio of studies that found alpha increase versus decrease with increasing load was 80/20% in the verbal WM domain and close to 60/40% in the visual domain. Alpha asymmetry (left < right) was a common finding in both verbal and visual WM studies. Beta and gamma activity studies yielded the least convincing data: a diversity in the spatial and frequency distribution of beta activity prevented us from making a coherent conclusion; gamma rhythm was virtually neglected in verbal WM studies with no systematic support for sustained gamma changes during the delay in EEG studies in general.
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Affiliation(s)
- Yuri G Pavlov
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany.,Department of Psychology, Ural Federal University, Ekaterinburg, Russian Federation
| | - Boris Kotchoubey
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
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17
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Puszta A, Pertich Á, Giricz Z, Nyujtó D, Bodosi B, Eördegh G, Nagy A. Predicting Stimulus Modality and Working Memory Load During Visual- and Audiovisual-Acquired Equivalence Learning. Front Hum Neurosci 2020; 14:569142. [PMID: 33132883 PMCID: PMC7578848 DOI: 10.3389/fnhum.2020.569142] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Accepted: 09/01/2020] [Indexed: 11/13/2022] Open
Abstract
Scholars have extensively studied the electroencephalography (EEG) correlates of associative working memory (WM) load. However, the effect of stimulus modality on EEG patterns within this process is less understood. To fill this research gap, the present study re-analyzed EEG datasets recorded during visual and audiovisual equivalence learning tasks from earlier studies. The number of associations required to be maintained (WM load) in WM was increased using the staircase method during the acquisition phase of the tasks. The support vector machine algorithm was employed to predict WM load and stimulus modality using the power, phase connectivity, and cross-frequency coupling (CFC) values obtained during time segments with different WM loads in the visual and audiovisual tasks. A high accuracy (>90%) in predicting stimulus modality based on power spectral density and from the theta-beta CFC was observed. However, accuracy in predicting WM load was higher (≥75% accuracy) than that in predicting stimulus modality (which was at chance level) using theta and alpha phase connectivity. Under low WM load conditions, this connectivity was highest between the frontal and parieto-occipital channels. The results validated our findings from earlier studies that dissociated stimulus modality based on power-spectra and CFC during equivalence learning. Furthermore, the results emphasized the importance of alpha and theta frontoparietal connectivity in WM load.
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Affiliation(s)
- András Puszta
- Department of Neuropsychology, Helgeland Hospital, Mosjøen, Norway.,Department of Psychology, Faculty of Social Sciences, University of Oslo, Oslo, Norway.,Department of Physiology, University of Szeged, Szeged, Hungary
| | - Ákos Pertich
- Department of Neuropsychology, Helgeland Hospital, Mosjøen, Norway
| | - Zsófia Giricz
- Department of Neuropsychology, Helgeland Hospital, Mosjøen, Norway
| | - Diána Nyujtó
- Department of Neuropsychology, Helgeland Hospital, Mosjøen, Norway
| | - Balázs Bodosi
- Department of Neuropsychology, Helgeland Hospital, Mosjøen, Norway
| | - Gabriella Eördegh
- Faculty of Health Sciences and Social Studies, University of Szeged, Szeged, Hungary
| | - Attila Nagy
- Department of Neuropsychology, Helgeland Hospital, Mosjøen, Norway
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18
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Ren Y, Pan L, Du X, Li X, Hou Y, Bao J, Song Y. Theta oscillation and functional connectivity alterations related to executive control in temporal lobe epilepsy with comorbid depression. Clin Neurophysiol 2020; 131:1599-1609. [DOI: 10.1016/j.clinph.2020.03.038] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Revised: 03/01/2020] [Accepted: 03/27/2020] [Indexed: 12/13/2022]
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19
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Ren Y, Pan L, Du X, Hou Y, Li X, Song Y. Functional brain network mechanism of executive control dysfunction in temporal lobe epilepsy. BMC Neurol 2020; 20:137. [PMID: 32295523 PMCID: PMC7161158 DOI: 10.1186/s12883-020-01711-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Accepted: 03/30/2020] [Indexed: 11/10/2022] Open
Abstract
Background Executive control dysfunction is observed in a sizable number of patients with temporal lobe epilepsy (TLE). Neural oscillations in the theta band are increasingly recognized as having a crucial role in executive control network. The purpose of this study was to investigate the alterations in the theta band in executive control network and explore the functional brain network mechanisms of executive control dysfunction in TLE patients. Methods A total of 20 TLE patients and 20 matched healthy controls (HCs) were recruited in the present study. All participants were trained to perform the executive control task by attention network test while the scalp electroencephalogram (EEG) data were recorded. The resting state signals were collected from the EEG in the subjects with quiet and closed eyes conditions. Functional connectivity among EEGs in the executive control network and resting state network were respectively calculated. Results We found the significant executive control impairment in the TLE group. Compared to the HCs, the TLE group showed significantly weaker functional connectivity among EEGs in the executive control network. Moreover, in the TLE group, we found that the functional connectivity was significantly positively correlated with accuracy and negatively correlated with EC_effect. In addition, the functional connectivity of the executive control network was significantly higher than that of the resting state network in the HCs. In the TLE group, however, there was no significant change in functional connectivity strengths between the executive control network and resting state network. Conclusion Our results indicate that the decreased functional connectivity in theta band may provide a potential mechanism for executive control deficits in TLE patients.
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Affiliation(s)
- Yanping Ren
- Department of Neurology, Tianjin Medical University General Hospital, Key Laboratory of Neurotrauma, Variation and Regeneration, Ministry of Education and 4Tianjin Municipal Government, Tianjin Neurological Institute, Tianjin, 300052, China
| | - Liping Pan
- Department of Neurology, Tianjin Medical University General Hospital, Key Laboratory of Neurotrauma, Variation and Regeneration, Ministry of Education and 4Tianjin Municipal Government, Tianjin Neurological Institute, Tianjin, 300052, China
| | - Xueyun Du
- Department of Neurology, Tianjin Medical University General Hospital, Key Laboratory of Neurotrauma, Variation and Regeneration, Ministry of Education and 4Tianjin Municipal Government, Tianjin Neurological Institute, Tianjin, 300052, China
| | - Yuying Hou
- Department of Neurology, Tianjin Medical University General Hospital, Key Laboratory of Neurotrauma, Variation and Regeneration, Ministry of Education and 4Tianjin Municipal Government, Tianjin Neurological Institute, Tianjin, 300052, China
| | - Xun Li
- Department of Neurology, Tianjin Medical University General Hospital, Key Laboratory of Neurotrauma, Variation and Regeneration, Ministry of Education and 4Tianjin Municipal Government, Tianjin Neurological Institute, Tianjin, 300052, China
| | - Yijun Song
- Department of Neurology, Tianjin Medical University General Hospital, Key Laboratory of Neurotrauma, Variation and Regeneration, Ministry of Education and 4Tianjin Municipal Government, Tianjin Neurological Institute, Tianjin, 300052, China.
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20
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Deep fuzzy model for non-linear effective connectivity estimation in the intuition of consciousness correlates. Biomed Signal Process Control 2020. [DOI: 10.1016/j.bspc.2019.101732] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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21
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Angsuwatanakul T, O’Reilly J, Ounjai K, Kaewkamnerdpong B, Iramina K. Multiscale Entropy as a New Feature for EEG and fNIRS Analysis. ENTROPY (BASEL, SWITZERLAND) 2020; 22:E189. [PMID: 33285964 PMCID: PMC7516618 DOI: 10.3390/e22020189] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Revised: 12/27/2019] [Accepted: 01/06/2020] [Indexed: 11/16/2022]
Abstract
The present study aims to apply multiscale entropy (MSE) to analyse brain activity in terms of brain complexity levels and to use simultaneous electroencephalogram and functional near-infrared spectroscopy (EEG/fNIRS) recordings for brain functional analysis. A memory task was selected to demonstrate the potential of this multimodality approach since memory is a highly complex neurocognitive process, and the mechanisms governing selective retention of memories are not fully understood by other approaches. In this study, 15 healthy participants with normal colour vision participated in the visual memory task, which involved the making the executive decision of remembering or forgetting the visual stimuli based on his/her own will. In a continuous stimulus set, 250 indoor/outdoor scenes were presented at random, between periods of fixation on a black background. The participants were instructed to make a binary choice indicating whether they wished to remember or forget the image; both stimulus and response times were stored for analysis. The participants then performed a scene recognition test to confirm whether or not they remembered the images. The results revealed that the participants intentionally memorising a visual scene demonstrate significantly greater brain complexity levels in the prefrontal and frontal lobe than when purposefully forgetting a scene; p < 0.05 (two-tailed). This suggests that simultaneous EEG and fNIRS can be used for brain functional analysis, and MSE might be the potential indicator for this multimodality approach.
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Affiliation(s)
| | - Jamie O’Reilly
- College of Biomedical Engineering, Rangsit University, Pathum Thani 12000, Thailand
| | - Kajornvut Ounjai
- Biological Engineering Program, Faculty of Engineering, King Mongkut’s University of Technology Thonburi, Bangkok 10140, Thailand; (K.O.); (B.K.)
| | - Boonserm Kaewkamnerdpong
- Biological Engineering Program, Faculty of Engineering, King Mongkut’s University of Technology Thonburi, Bangkok 10140, Thailand; (K.O.); (B.K.)
| | - Keiji Iramina
- Graduate School of Systems Life Sciences, Kyushu University, Fukuoka 819-0395, Japan;
- Faculty of Information Sciences and Electrical Engineering, Kyushu University, Fukuoka 819-0395, Japan
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22
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Luo W, Zhou R. Can Working Memory Task-Related EEG Biomarkers Measure Fluid Intelligence and Predict Academic Achievement in Healthy Children? Front Behav Neurosci 2020; 14:2. [PMID: 32038192 PMCID: PMC6987418 DOI: 10.3389/fnbeh.2020.00002] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Accepted: 01/03/2020] [Indexed: 12/22/2022] Open
Abstract
Background Educational psychology research has linked fluid intelligence (Gf) with working memory (WM), but it is still dubious whether electroencephalography (EEG) markers robustly indicate Gf. This study addresses this issue and notes the relationship between WM task-related EEG markers with Gf and academic performance. Method A sample of 62 healthy children between the ages of 9 and 12 years was selected to perform three tasks: (1) Raven’s Standard Progressive Matrices (RSPM) test to assess Gf; (2) 2-back task to assess central executive system (CES); and (3) delayed match-to-sample task to assess short-term storage. These subjects were divided into high ability (HA) and low ability (LA) groups based on their RSPM scores. Support vector machine and logistic regression were used to train the EEG candidate indicators. A multiple regression was used to predict children’s academic performance using P3 amplitude, P2 latency, and θ-ERS. Results Behavioral results demonstrated that the correct rate of the HA group is higher than that of the LA group. The event-related potential results of the 2-back task showed that the P3 amplitude of the HA group was relatively larger and that the P2 latency was shorter than that observed in the LA group. For the delayed matching to sample task, the θ-ERS of the LA group was higher than that of the HA group. However, the area under the curve of these three indicators for Gf was < 0.75 for each and < 0.85 for the combined indicators. In predicting academic performance, only P3 amplitude showed a significant effect. Conclusion These results challenge previous findings, which reported that P3, P2, or theta power might be used in standard psychometric tests to assess an individual’s intelligence.
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Affiliation(s)
- Wei Luo
- Department of Psychology, Nanjing University, Nanjing, China
| | - Renlai Zhou
- Department of Psychology, Nanjing University, Nanjing, China
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23
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Functional dissociation of anterior cingulate cortex and intraparietal sulcus in visual working memory. Cortex 2019; 121:277-291. [DOI: 10.1016/j.cortex.2019.09.009] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Revised: 07/31/2019] [Accepted: 09/16/2019] [Indexed: 12/21/2022]
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24
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Lin Y, Liu T, Huang Q, Su Y, Chen W, Gao D, Tian X, Huang T, Zhen Z, Han T, Ye H, Wang Y. Electroencephalography and Functional Magnetic Resonance Imaging-Guided Simultaneous Transcranial Direct Current Stimulation and Repetitive Transcranial Magnetic Stimulation in a Patient With Minimally Conscious State. Front Neurosci 2019; 13:746. [PMID: 31417339 PMCID: PMC6685103 DOI: 10.3389/fnins.2019.00746] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Accepted: 07/05/2019] [Indexed: 12/23/2022] Open
Abstract
Objective A minimally conscious state (MCS) is characterized by discernible behavioral evidence of consciousness that cannot be reproduced consistently. This condition is highly challenging to treat. Recent studies have demonstrated the potential therapeutic effect of non-invasive brain stimulation in patients with MCS. In one patient in an MCS, we delivered simultaneous transcranial direct current stimulation (tDCS) and repetitive transcranial magnetic stimulation (rTMS) based on an individual brain network analysis and evaluated the therapeutic effect. Methods The directional transfer function (DTF) was calculated based on electroencephalograph (EEG) analysis. Global brain connectivity was calculated based on functional magnetic resonance imaging (fMRI) analysis. By referring to the EEG and fMRI results, we identified inferior parietal lobes (IPLs) as targets. In the 2-week treatment period, 14 sessions were applied to the identified bilateral parietal regions. Simultaneous 1.5-mA anodal tDCS and 5-Hz rTMS were delivered for 20 min per hemisphere in each session. Clinical evaluation scores were recorded weekly throughout the treatment. A second patient given the routine treatment was evaluated as a control. Results The clinical scores of patient 1 with MCS improved after 2 weeks of stimulation treatment, and the effect lasted for up to 1 month. EEG analysis showed a significant increase (p < 0.001) in the DTF value in the gamma band in a bilateral set of posterior regions, and fMRI showed a trend toward normalized activity in the IPLs. The clinical scores of patient 2 with coma did not improve much after 2 weeks of routine treatment. The EEG analysis showed a significant increase (p = 0.021) in the DTF value in the gamma band in a bilateral set of posterior regions. Conclusion The application of EEG and fMRI to characterize the functional connectivity features of the network in an MCS patient provided a reasonable and accurate stimulation target and verified the changes in functional connectivity resulting from stimulation.
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Affiliation(s)
- Yicong Lin
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Tiaotiao Liu
- School of Biomedical Engineering, Tianjin Medical University, Tianjin, China
| | - Qian Huang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yingying Su
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Weibi Chen
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Daiquan Gao
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xin Tian
- School of Biomedical Engineering, Tianjin Medical University, Tianjin, China
| | - Taicheng Huang
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Zonglei Zhen
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Tao Han
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Hong Ye
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yuping Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,The Beijing Key Laboratory of Neuromodulation, Beijing, China.,Center of Epilepsy, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
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Ghaderi AH, Nazari MA, Darooneh AH. Functional brain segregation changes during demanding mathematical task. Int J Neurosci 2019; 129:904-915. [DOI: 10.1080/00207454.2019.1586688] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Affiliation(s)
- Amir Hossein Ghaderi
- Vision: Science to Applications (VISTA) Program, York University, Toronto, ON, Canada
- Iranian Neuro-Wave Lab, Vilashahr, Isfahan, Iran
- Division of Cognitive Neuroscience, University of Tabriz, Tabriz, Iran
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26
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Comparison of brain effective connectivity in different states of attention and consciousness based on EEG signals. Biomed Signal Process Control 2019. [DOI: 10.1016/j.bspc.2019.02.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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27
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28
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Broomell APR, Bell MA. Inclusion of a Mixed Condition Makes the Day/Night Task More Analogous to the Adult Stroop. Dev Neuropsychol 2017; 42:241-252. [PMID: 28467111 PMCID: PMC6151866 DOI: 10.1080/87565641.2017.1309655] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
In a study with 4-year-old children, we added a mixed condition to the traditional day/night task to examine performance and response times for congruent and incongruent trials within the same condition. There were no differences in percentage correct performance between the incongruent and mixed conditions; however, children performed best on the congruent condition. EEG recordings showed differential patterns of frontal power and coherence suggesting increasing cognitive load from congruent to incongruent to mixed conditions. Our pattern of findings suggest that the mixed condition of the day/night Stroop task is a more appropriate child equivalent to the adult color-word Stroop task.
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Affiliation(s)
| | - Martha Ann Bell
- a Department of Psychology , Virginia Tech , Blacksburg , Virginia
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29
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Dissociated roles of the parietal and frontal cortices in the scope and control of attention during visual working memory. Neuroimage 2017; 149:210-219. [DOI: 10.1016/j.neuroimage.2017.01.061] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2016] [Revised: 01/24/2017] [Accepted: 01/25/2017] [Indexed: 01/06/2023] Open
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30
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Yin Z, Zhang J. Cross-session classification of mental workload levels using EEG and an adaptive deep learning model. Biomed Signal Process Control 2017. [DOI: 10.1016/j.bspc.2016.11.013] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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