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Shi Y, Li Y. The effective connectivity analysis of fMRI based on asymmetric detection of transfer brain entropy. Cereb Cortex 2024; 34:bhae070. [PMID: 38466114 DOI: 10.1093/cercor/bhae070] [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: 11/19/2023] [Revised: 02/05/2024] [Accepted: 02/06/2024] [Indexed: 03/12/2024] Open
Abstract
It is important to explore causal relationships in functional magnetic resonance imaging study. However, the traditional effective connectivity analysis method is easy to produce false causality, and the detection accuracy needs to be improved. In this paper, we introduce a novel functional magnetic resonance imaging effective connectivity method based on the asymmetry detection of transfer entropy, which quantifies the disparity in predictive information between forward and backward time, subsequently normalizing this disparity to establish a more precise criterion for detecting causal relationships while concurrently reducing computational complexity. Then, we evaluate the effectiveness of this method on the simulated data with different level of nonlinearity, and the results demonstrated that the proposed method outperforms others methods on the detection of both linear and nonlinear causal relationships, including Granger Causality, Partial Granger Causality, Kernel Granger Causality, Copula Granger Causality, and traditional transfer entropy. Furthermore, we applied it to study the effective connectivity of brain functional activities in seafarers. The results showed that there are significantly different causal relationships between different brain regions in seafarers compared with non-seafarers, such as Temporal lobe related to sound and auditory information processing, Hippocampus related to spatial navigation, Precuneus related to emotion processing as well as Supp_Motor_Area associated with motor control and coordination, which reflects the occupational specificity of brain function of seafarers.
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Affiliation(s)
- Yuhu Shi
- College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China
| | - Yidan Li
- College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China
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Wang B, Chen Y, Chen K, Lu H, Zhang Z. From local properties to brain-wide organization: A review of intraregional temporal features in functional magnetic resonance imaging data. Hum Brain Mapp 2023; 44:3926-3938. [PMID: 37086446 DOI: 10.1002/hbm.26302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 03/15/2023] [Accepted: 03/21/2023] [Indexed: 04/24/2023] Open
Abstract
Based on the fluctuations ensembled over neighbouring neurons, blood oxygen level-dependent (BOLD) signal is a mesoscale measurement of brain signals. Intraregional temporal features (IRTFs) of BOLD signal, extracted from regional neural activities, are utilized to investigate how the brain functions in local brain areas. This literature highlights four types of IRTFs and their representative calculations including variability in the temporal domain, variability in the frequency domain, entropy, and intrinsic neural timescales, which are tightly related to cognitions. In the brain-wide spatial organization, these brain features generally organized into two spatial hierarchies, reflecting structural constraints of regional dynamics and hierarchical functional processing workflow in brain. Meanwhile, the spatial organization gives rise to the link between neuronal properties and cognitive performance. Disrupted or unbalanced spatial conditions of IRTFs emerge with suboptimal cognitive states, which improved our understanding of the aging process and/or neuropathology of brain disease. This review concludes that IRTFs are important properties of the brain functional system and IRTFs should be considered in a brain-wide manner.
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Affiliation(s)
- Bolong Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- BABRI Centre, Beijing Normal University, Beijing, China
| | - Yaojing Chen
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- BABRI Centre, Beijing Normal University, Beijing, China
| | - Kewei Chen
- Banner Alzheimer's Institute, Phoenix, Arizona, USA
| | - Hui Lu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- BABRI Centre, Beijing Normal University, Beijing, China
| | - Zhanjun Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- BABRI Centre, Beijing Normal University, Beijing, China
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Wu H, Peng D, Yan H, Yang Y, Xu M, Zeng W, Chang C, Wang N. Occupation-modulated language networks and its lateralization: A resting-state fMRI study of seafarers. Front Hum Neurosci 2023; 17:1095413. [PMID: 36992794 PMCID: PMC10040660 DOI: 10.3389/fnhum.2023.1095413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 02/27/2023] [Indexed: 03/14/2023] Open
Abstract
IntroductionStudies have revealed that the language network of Broca’s area and Wernicke’s area is modulated by factors such as disease, gender, aging, and handedness. However, how occupational factors modulate the language network remains unclear.MethodsIn this study, taking professional seafarers as an example, we explored the resting-state functional connectivity (RSFC) of the language network with seeds (the original and flipped Broca’s area and Wernicke’s area).ResultsThe results showed seafarers had weakened RSFC of Broca’s area with the left superior/middle frontal gyrus and left precentral gyrus, and enhanced RSFC of Wernicke’s area with the cingulate and precuneus. Further, seafarers had a less right-lateralized RSFC with Broca’s area in the left inferior frontal gyrus, while the controls showed a left-lateralized RSFC pattern in Broca’s area and a right-lateralized one in Wernicke’s area. Moreover, seafarers displayed stronger RSFC with the left seeds of Broca’s area and Wernicke’s area.DiscussionThese findings suggest that years of working experience significantly modulates the RSFC of language networks and their lateralization, providing rich insights into language networks and occupational neuroplasticity.
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Affiliation(s)
- Huijun Wu
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
| | - Deyuan Peng
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
| | - Hongjie Yan
- Department of Neurology, Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, China
- Hongjie Yan,
| | - Yang Yang
- CAS Key Laboratory of Behavioral Science, Center for Brain Science and Learning Difficulties, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Min Xu
- Center for Brain Disorders and Cognitive Science, Shenzhen University, Shenzhen, China
| | - Weiming Zeng
- Lab of Digital Image and Intelligent Computation, Shanghai Maritime University, Shanghai, China
| | - Chunqi Chang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
- Peng Cheng Laboratory, Shenzhen, China
- Chunqi Chang,
| | - Nizhuan Wang
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
- *Correspondence: Nizhuan Wang,
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Du S, Wang Y, Li G, Wei H, Yan H, Li X, Wu Y, Zhu J, Wang Y, Cai Z, Wang N. Olfactory functional covariance connectivity in Parkinson's disease: Evidence from a Chinese population. Front Aging Neurosci 2023; 14:1071520. [PMID: 36688163 PMCID: PMC9846552 DOI: 10.3389/fnagi.2022.1071520] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Accepted: 12/12/2022] [Indexed: 01/05/2023] Open
Abstract
Introduction Central anosmia is a potential marker of the prodrome and progression of Parkinson's disease (PD). Resting-state functional magnetic resonance imaging studies have shown that olfactory dysfunction is related to abnormal changes in central olfactory-related structures in patients with early PD. Methods This study, which was conducted at Guanyun People's Hospital, analyzed the resting-state functional magnetic resonance data using the functional covariance connection strength method to decode the functional connectivity between the white-gray matter in a Chinese population comprising 14 patients with PD and 13 controls. Results The following correlations were observed in patients with PD: specific gray matter areas related to smell (i.e., the brainstem, right cerebellum, right temporal fusiform cortex, bilateral superior temporal gyrus, right Insula, left frontal pole and right superior parietal lobule) had abnormal connections with white matter fiber bundles (i.e., the left posterior thalamic radiation, bilateral posterior corona radiata, bilateral superior corona radiata and right superior longitudinal fasciculus); the connection between the brainstem [region of interest (ROI) 1] and right cerebellum (ROI2) showed a strong correlation. Right posterior corona radiation (ROI11) showed a strong correlation with part 2 of the Unified Parkinson's Disease Rating Scale, and right superior longitudinal fasciculus (ROI14) showed a strong correlation with parts 1, 2, and 3 of the Unified Parkinson's Disease Rating Scale and Hoehn and Yahr Scale. Discussion The characteristics of olfactory-related brain networks can be potentially used as neuroimaging biomarkers for characterizing PD states. In the future, dynamic testing of olfactory function may help improve the accuracy and specificity of olfactory dysfunction in the diagnosis of neurodegenerative diseases.
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Affiliation(s)
- Shouyun Du
- Department of Neurology, Guanyun County People's Hospital, Lianyungang, China
| | - Yiqing Wang
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing University Medical School, Suzhou, China,Department of Neurology, Suzhou Science & Technology Town Hospital, Gusu School, Nanjing Medical University, Suzhou, China
| | - Guodong Li
- Department of Neurology, Guanyun County People's Hospital, Lianyungang, China
| | - Hongyu Wei
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing University Medical School, Suzhou, China
| | - Hongjie Yan
- Department of Neurology, Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, China
| | - Xiaojing Li
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing University Medical School, Suzhou, China
| | - Yijie Wu
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing University Medical School, Suzhou, China
| | - Jianbing Zhu
- Department of Radiology, The Affiliated Suzhou Hospital of Nanjing University Medical School, Suzhou, China
| | - Yi Wang
- Department of Radiology, The Affiliated Suzhou Hospital of Nanjing University Medical School, Suzhou, China
| | - Zenglin Cai
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing University Medical School, Suzhou, China,Department of Neurology, Suzhou Science & Technology Town Hospital, Gusu School, Nanjing Medical University, Suzhou, China,*Correspondence: Zenglin Cai, ✉
| | - Nizhuan Wang
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China,Nizhuan Wang, ✉
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An J, Gao W, Liu R, Liu Z. Empirical Study on the Relationship Between Vacation Schedule and Seafarers' Fatigue in Chinese Seafarer Population. Front Psychol 2022; 13:838811. [PMID: 35386897 PMCID: PMC8977519 DOI: 10.3389/fpsyg.2022.838811] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Accepted: 02/23/2022] [Indexed: 12/05/2022] Open
Abstract
Background Fatigue is an important factor for the safety of ships. In order to alleviate fatigue of the seafarers, the STCW Convention (International Convention on Standards of Training, Certification, and Watchkeeping for Seafarers) has made many regulations on the working time of seafarers. At present, if a crew member takes only one day off at home before returning to work on the ship, the working time on the ship must be re-calculated again. If the time spent at home is not sufficient to allow the crew to recover, the regulations of only stipulating the working time, not stipulating the home vacation time, cannot guarantee the crew's fatigue been well controlled. The aim of present study is to explore the relationship between vacation schedule and fatigue of the seafarers. Methods In present study, a simplified stress scale developed by the Ministry of Labor of Japan has been used as a measurement tool. The method of stratified sampling was adopted. Data collection mainly came from domestic ocean-going seafarers (n = 165). Analysis was conducted using the Cross (chi-square) analysis and hierarchical multiple regression analysis methods. Results We found that there was no difference between crew members of different positions in terms of average vacation time and on-board service time (p > 0.05). The length of last vacation time and this service time for seafarers of different positions showed obvious differences (p < 0.01). The rank has a significant effect on the length of the last vacation (χ2 = 101.560, p = 0.000 < 0.01) and the length of this service time (χ2 = 75.624, p = 0.000 < 0.01). Also, the results showed that there was a significant negative correlation between the duration of vacation and overall fatigue (t = -7.160, p = 0.000 < 0.01), while there was a significant positive correlation between the length of service time on board and overall fatigue (t = 3.474, p = 0.001 < 0.01). Conclusion The results indicated that a reasonable vacation schedule was crucial for the relief of the seafarers' fatigue, and also played a positive role in the state of working on the ship again.
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Affiliation(s)
- Ji An
- Merchant Marine College, Shanghai Maritime University, Shanghai, China
| | - Wenting Gao
- Merchant Marine College, Shanghai Maritime University, Shanghai, China
| | - Runze Liu
- Maritime College, Beibu Gulf University, Guangxi, China
| | - Ziqi Liu
- Merchant Marine College, Shanghai Maritime University, Shanghai, China
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Yan H, Wu H, Chen Y, Yang Y, Xu M, Zeng W, Zhang J, Chang C, Wang N. Dynamical Complexity Fingerprints of Occupation-Dependent Brain Functional Networks in Professional Seafarers. Front Neurosci 2022; 16:830808. [PMID: 35368265 PMCID: PMC8973415 DOI: 10.3389/fnins.2022.830808] [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: 12/07/2021] [Accepted: 01/24/2022] [Indexed: 12/24/2022] Open
Abstract
The complexity derived from resting-state functional magnetic resonance imaging (rs-fMRI) data has been applied for exploring cognitive states and occupational neuroplasticity. However, there is little information about the influence of occupational factors on dynamic complexity and topological properties of the connectivity networks. In this paper, we proposed a novel dynamical brain complexity analysis (DBCA) framework to explore the changes in dynamical complexity of brain activity at the voxel level and complexity topology for professional seafarers caused by long-term working experience. The proposed DBCA is made up of dynamical brain entropy mapping analysis and complex network analysis based on brain entropy sequences, which generate the dynamical complexity of local brain areas and the topological complexity across brain areas, respectively. First, the transient complexity of voxel-wise brain map was calculated; compared with non-seafarers, seafarers showed decreased dynamic entropy values in the cerebellum and increased values in the left fusiform gyrus (BA20). Further, the complex network analysis based on brain entropy sequences revealed small-worldness in terms of topological complexity in both seafarers and non-seafarers, indicating that it is an inherent attribute of human the brain. In addition, seafarers showed a higher average path length and lower average clustering coefficient than non-seafarers, suggesting that the information processing ability is reduced in seafarers. Moreover, the reduction in efficiency of seafarers suggests that they have a less efficient processing network. To sum up, the proposed DBCA is effective for exploring the dynamic complexity changes in voxel-wise activity and region-wise connectivity, showing that occupational experience can reshape seafarers’ dynamic brain complexity fingerprints.
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Affiliation(s)
- Hongjie Yan
- Department of Neurology, Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, China
| | - Huijun Wu
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
| | - Yanyan Chen
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
| | - Yang Yang
- Key Laboratory of Behavioral Science, Center for Brain Science and Learning Difficulties, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Min Xu
- Center for Brain Disorders and Cognitive Science, Shenzhen University, Shenzhen, China
| | - Weiming Zeng
- Lab of Digital Image and Intelligent Computation, Shanghai Maritime University, Shanghai, China
| | - Jian Zhang
- School of Pharmacy, Health Science Center, Shenzhen University, Shenzhen, China
| | - Chunqi Chang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
- Peng Cheng Laboratory, Shenzhen, China
- *Correspondence: Nizhuan Wang,
| | - Nizhuan Wang
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
- *Correspondence: Nizhuan Wang,
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Kadota K, Onoda K, Abe S, Hamada C, Mitaki S, Oguro H, Nagai A, Kitagaki H, Yamaguchi S. Multiscale Entropy of Resting-State Functional Magnetic Resonance Imaging Differentiates Progressive Supranuclear Palsy and Multiple System Atrophy. Life (Basel) 2021; 11:life11121411. [PMID: 34947943 PMCID: PMC8707613 DOI: 10.3390/life11121411] [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] [Received: 11/15/2021] [Revised: 12/13/2021] [Accepted: 12/14/2021] [Indexed: 11/16/2022] Open
Abstract
Distinguishing progressive supranuclear palsy (PSP) from multiple system atrophy (MSA) in the early clinical stages is challenging; few sensitive and specific biomarkers are available for their differential diagnosis. Resting-state functional magnetic resonance imaging (rs-fMRI) is used to study the fluctuations in blood oxygen level-dependent (BOLD) signals at rest, which provides evidence for aberrant brain functional networks in neurodegenerative diseases. We aimed to examine whether rs-fMRI data could differentiate between PSP and MSA via a multiscale entropy (MSE) analysis of BOLD signals, which estimates the complexity of temporal fluctuations in brain activity. We recruited 14 and 18 patients with PSP and MSA, respectively, who underwent neuropsychological tests and rs-fMRI. PSP patients demonstrated greater cognitive function impairments, particularly in the frontal executive function. The bilateral prefrontal cortex revealed lower entropy BOLD signal values in multiple time scales for PSP, compared to the values observed in MSA patients; however, the functional connectivity of the representative brain networks was comparable between the diseases. The reduced complexity of BOLD signals in the prefrontal cortex was associated with frontal dysfunction. Thus, an MSE analysis of rs-fMRI could differentiate between PSP and MSA, and the reduced complexity of BOLD signals could be associated with cognitive impairment.
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Affiliation(s)
- Katsuhiko Kadota
- Department of Neurology, Faculty of Medicine, Shimane University, Izumo 693-8501, Japan; (S.A.); (C.H.); (S.M.); (H.O.); (A.N.); (S.Y.)
- Correspondence: ; Tel.: +81-3-3813-3111
| | - Keiichi Onoda
- Department of Psychology, Otemon Gakuin University, Osaka 567-8502, Japan;
| | - Satoshi Abe
- Department of Neurology, Faculty of Medicine, Shimane University, Izumo 693-8501, Japan; (S.A.); (C.H.); (S.M.); (H.O.); (A.N.); (S.Y.)
| | - Chizuko Hamada
- Department of Neurology, Faculty of Medicine, Shimane University, Izumo 693-8501, Japan; (S.A.); (C.H.); (S.M.); (H.O.); (A.N.); (S.Y.)
| | - Shingo Mitaki
- Department of Neurology, Faculty of Medicine, Shimane University, Izumo 693-8501, Japan; (S.A.); (C.H.); (S.M.); (H.O.); (A.N.); (S.Y.)
| | - Hiroaki Oguro
- Department of Neurology, Faculty of Medicine, Shimane University, Izumo 693-8501, Japan; (S.A.); (C.H.); (S.M.); (H.O.); (A.N.); (S.Y.)
| | - Atsushi Nagai
- Department of Neurology, Faculty of Medicine, Shimane University, Izumo 693-8501, Japan; (S.A.); (C.H.); (S.M.); (H.O.); (A.N.); (S.Y.)
| | - Hajime Kitagaki
- Department of Radiology, Faculty of Medicine, Shimane University, Izumo 693-8501, Japan;
| | - Shuhei Yamaguchi
- Department of Neurology, Faculty of Medicine, Shimane University, Izumo 693-8501, Japan; (S.A.); (C.H.); (S.M.); (H.O.); (A.N.); (S.Y.)
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Xin X, Long S, Sun M, Gao X. The Application of Complexity Analysis in Brain Blood-Oxygen Signal. Brain Sci 2021; 11:brainsci11111415. [PMID: 34827414 PMCID: PMC8615802 DOI: 10.3390/brainsci11111415] [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: 09/16/2021] [Revised: 10/22/2021] [Accepted: 10/25/2021] [Indexed: 11/17/2022] Open
Abstract
One of the daunting features of the brain is its physiology complexity, which arises from the interaction of numerous neuronal circuits that operate over a wide range of temporal and spatial scales, enabling the brain to adapt to the constantly changing environment and to perform various cognitive functions. As a reflection of the complexity of brain physiology, the complexity of brain blood-oxygen signal has been frequently studied in recent years. This paper reviews previous literature regarding the following three aspects: (1) whether the complexity of the brain blood-oxygen signal can serve as a reliable biomarker for distinguishing different patient populations; (2) which is the best algorithm for complexity measure? And (3) how to select the optimal parameters for complexity measures. We then discuss future directions for blood-oxygen signal complexity analysis, including improving complexity measurement based on the characteristics of both spatial patterns of brain blood-oxygen signal and latency of complexity itself. In conclusion, the current review helps to better understand complexity analysis in brain blood-oxygen signal analysis and provide useful information for future studies.
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The Study of Sailors’ Brain Activity Difference Before and After Sailing Using Activated Functional Connectivity Pattern. Neural Process Lett 2021. [DOI: 10.1007/s11063-021-10545-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Shi Y, Zeng W, Wang N. The Brain Alteration of Seafarer Revealed by Activated Functional Connectivity Mode in fMRI Data Analysis. Front Hum Neurosci 2021; 15:656638. [PMID: 33967722 PMCID: PMC8100688 DOI: 10.3389/fnhum.2021.656638] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Accepted: 03/09/2021] [Indexed: 11/27/2022] Open
Abstract
As a special occupational group, the working and living environments faced by seafarers are greatly different from those of land. It is easy to affect the psychological and physiological activities of seafarers, which inevitably lead to changes in the brain functional activities of seafarers. Therefore, it is of great significance to study the neural activity rules of seafarers' brain. In view of this, this paper studied the seafarers' brain alteration at the activated voxel level based on functional magnetic resonance imaging technology by comparing the differences in functional connectivities (FCs) between seafarers and non-seafarers. Firstly, the activated voxels of each group were obtained by independence component analysis, and then the distribution of these voxels in the brain and the common activated voxels between the two groups were statistically analyzed. Next, the FCs between the common activated voxels of the two groups were calculated and obtained the FCs that had significant differences between them through two-sample T-test. Finally, all FCs and FCs with significant differences (DFCs) between the common activated voxels were used as the features for the support vector machine to classify seafarers and non-seafarers. The results showed that DFCs between the activated voxels had better recognition ability for seafarers, especially for Precuneus_L and Precuneus_R, which may play an important role in the classification prediction of seafarers and non-seafarers, so that provided a new perspective for studying the specificity of neurological activities of seafarers.
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Affiliation(s)
- Yuhu Shi
- College of Information Engineering, Shanghai Maritime University, Shanghai, China
| | - Weiming Zeng
- College of Information Engineering, Shanghai Maritime University, Shanghai, China
| | - Nizhuan Wang
- Artificial Intelligence and Neuro-Informatics Engineering (ARINE) Laboratory, School of Computer Engineering, Jiangsu Ocean University, Lianyungang, China
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Bu L, Xu N, Wang Y, Liu H. Decreased low-frequency brain effective connectivity in seafarers during voyages: a functional near-infrared spectroscopy study. Physiol Meas 2020; 41:095003. [PMID: 32759489 DOI: 10.1088/1361-6579/abad13] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
OBJECTIVE During voyages, seafarers experience psychological problems that act to decrease operational safety. Psychological problems in seafarers can lead to changes in functional brain networks. This study investigated the low-frequency brain effective connectivity (EC) in seafarers during voyages by using the coupling strength (CS) of functional near-infrared spectroscopy (fNIRS) imaging. APPROACH This study recruited 15 seafarers (seafarer group) working on a container ship and 15 healthy age-matched controls (control group). The EC was assessed using dynamic Bayesian inference (DBI) of the oxygenated hemoglobin concentration (delta HbO2) as measured through a 14-channel fNIRS system. These channels covered the left and right prefrontal cortices (LPFC/RPFC), left and right motor cortices (LMC/RMC), and left and right occipital lobes (LOL/ROL). MAIN RESULTS The EC levels of LPFC to RMC (F = 4.239, p = 0.049), LPFC to ROL (F = 5.385, p = 0.028), LOL to RPFC (F = 11.128, p = 0.002), ROL to RPFC (F = 10.714, p = 0.003) and LMC to ROL (F= 6.136, p = 0.02) were significantly lower in the seafarer group than in the control group. Correlation analysis revealed that the patient health questionnaire-9 (PHQ-9) scores were positively correlated with the systolic blood pressure (SBP) values, delta HbO2 values and EC levels, respectively. Meanwhile, the correlation analysis revealed that the SBP values significantly positively correlated with the CS values. SIGNIFICANCE Decreased EC levels may be a marker of psychological subhealth in seafarers. The approach combines fNIRS and PHQ-9 scores, providing a quantitative method for the assessment of mental health problems and further help with better rehabilitation designs in seafarers during voyages.
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Affiliation(s)
- Lingguo Bu
- Department of Physical Medicine and Rehabilitation, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, People's Republic of China. School of Mechanical and Aerospace Engineering, Nanyang Technological University, 639798, Singapore
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Wu H, Yan H, Yang Y, Xu M, Shi Y, Zeng W, Li J, Zhang J, Chang C, Wang N. Occupational Neuroplasticity in the Human Brain: A Critical Review and Meta-Analysis of Neuroimaging Studies. Front Hum Neurosci 2020; 14:215. [PMID: 32760257 PMCID: PMC7373999 DOI: 10.3389/fnhum.2020.00215] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2020] [Accepted: 05/13/2020] [Indexed: 12/14/2022] Open
Abstract
Many studies have revealed the structural or functional brain changes induced by occupational factors. However, it remains largely unknown how occupation-related connectivity shapes the brain. In this paper, we denote occupational neuroplasticity as the neuroplasticity that takes place to satisfy the occupational requirements by extensively professional training and to accommodate the long-term, professional work of daily life, and a critical review of occupational neuroplasticity related to the changes in brain structure and functional networks has been primarily presented. Furthermore, meta-analysis revealed a neurophysiological mechanism of occupational neuroplasticity caused by professional experience. This meta-analysis of functional neuroimaging studies showed that experts displayed stronger activation in the left precentral gyrus [Brodmann area (BA)6], left middle frontal gyrus (BA6), and right inferior frontal gyrus (BA9) than novices, while meta-analysis of structural studies suggested that experts had a greater gray matter volume in the bilateral superior temporal gyrus (BA22) and right putamen than novices. Together, these findings not only expand the current understanding of the common neurophysiological basis of occupational neuroplasticity across different occupations and highlight some possible targets for neural modulation of occupational neuroplasticity but also provide a new perspective for occupational science research.
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Affiliation(s)
- Huijun Wu
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
| | - Hongjie Yan
- Department of Neurology, Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, China
| | - Yang Yang
- Center for Brain Science and Learning Difficulties, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Min Xu
- Center for Brain Disorders and Cognitive Science, Shenzhen University, Shenzhen, China
| | - Yuhu Shi
- Lab of Digital Image and Intelligent Computation, Shanghai Maritime University, Shanghai, China
| | - Weiming Zeng
- Lab of Digital Image and Intelligent Computation, Shanghai Maritime University, Shanghai, China
| | - Jiewei Li
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Pokfulam, Hong Kong
| | - Jian Zhang
- School of Pharmacy, Health Science Center, Shenzhen University, Shenzhen, China
| | - Chunqi Chang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China.,Pengcheng Laboratory, Shenzhen, China
| | - Nizhuan Wang
- Artificial Intelligence & Neuro-Informatics Engineering (ARINE) Laboratory, School of Computer Engineering, Jiangsu Ocean University, Lianyungang, China
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13
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Zheng H, Onoda K, Nagai A, Yamaguchi S. Reduced Dynamic Complexity of BOLD Signals Differentiates Mild Cognitive Impairment From Normal Aging. Front Aging Neurosci 2020; 12:90. [PMID: 32322197 PMCID: PMC7156890 DOI: 10.3389/fnagi.2020.00090] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Accepted: 03/17/2020] [Indexed: 12/11/2022] Open
Abstract
Mild cognitive impairment (MCI) is characterized as a transitional phase between cognitive decline associated with normal aging and Alzheimer’s disease (AD). Resting-state functional magnetic resonance imaging (fMRI) measuring blood oxygenation level-dependent (BOLD) signals provides complementary information considered essential for understanding disease progression. Previous studies suggested that multi-scale entropy (MSE) analysis quantifying the complexity of BOLD signals is a novel and promising method for investigating neurodegeneration associated with cognitive decline in different stages of MCI. Therefore, the current study used MSE to explore the changes in the complexity of resting-state brain BOLD signals in patients with early MCI (EMCI) and late MCI (LMCI). We recruited 345 participants’ data from the Alzheimer’s Disease Neuroimaging Initiative database, including 176 normal control (NC) subjects, 87 patients with EMCI and 82 patients with LMCI. We observed a significant reduction of brain signal complexity toward regularity in the left fusiform gyrus region in the EMCI group and in the rostral anterior cingulate cortex in the LMCI group. Our results extend prior work by revealing that significant reductions of brain BOLD signal complexity can be detected in different stages of MCI independent of age, sex and regional atrophy. Notably, the reduction of BOLD signal complexity in the rostral anterior cingulate cortex was significantly associated with greater risk of progression to AD. The present study thus identified MSE as a potential imaging biomarker for the early diagnosis of pre-clinical Alzheimer’s disease and provides further insights into the neuropathology of cognitive decline in prodromal AD.
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Affiliation(s)
- Haixia Zheng
- Laureate Institute for Brain Research, Tulsa, OK, United States
| | - Keiichi Onoda
- Department of Neurology, Faculty of Medicine, Shimane University, Izumo, Japan
| | - Atsushi Nagai
- Department of Neurology, Faculty of Medicine, Shimane University, Izumo, Japan
| | - Shuhei Yamaguchi
- Department of Neurology, Faculty of Medicine, Shimane University, Izumo, Japan
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14
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Liang L, Hu R, Luo X, Feng B, Long W, Song R. Reduced Complexity in Stroke with Motor Deficits: A Resting-State fMRI Study. Neuroscience 2020; 434:35-43. [PMID: 32194224 DOI: 10.1016/j.neuroscience.2020.03.020] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Revised: 03/09/2020] [Accepted: 03/10/2020] [Indexed: 01/02/2023]
Abstract
Recently, alterations of complexity due to brain disorders have been demonstrated using brain entropy (BEN), while the changes of brain complexity in stroke, a common cerebrovascular disease, remain unclear. In this research, resting-state functional magnetic resonance imaging (fMRI) was performed to explore the alterations of brain complexity using BEN in twenty stroke patients with motor deficits and nineteen matched healthy controls. The sample entropy (SampEn) was applied to build the BEN mapping for each participant. Compared with healthy controls, stroke patients exhibited lower BEN values in the contralesional precentral gyrus (preCG), bilateral dorsolateral frontal gyrus (SFGdor) and bilateral supplementary motor area (SMA). Moreover, significantly positive correlations between BEN values and Fugl-Meyer Assessment scores were detected in the ipsilesional SFGdor and ipsilesional SMA. Mutual information independence was observed between BEN and regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF), respectively, in the stroke patients. Our findings implied that brain complexity had been impacted after stroke, and also suggested that BEN could be a complementary tool for evaluating the motor impairment after stroke.
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Affiliation(s)
- Liuke Liang
- Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510006, China
| | - Rongliang Hu
- Department of Rehabilitation Medicine, Jiangmen Central Hospital, Jiangmen, Guangdong, China
| | - Xuemao Luo
- Department of Radiology, Jiangmen Central Hospital, Jiangmen, Guangdong, China
| | - Bao Feng
- Department of Radiology, Jiangmen Central Hospital, Jiangmen, Guangdong, China
| | - Wansheng Long
- Department of Radiology, Jiangmen Central Hospital, Jiangmen, Guangdong, China
| | - Rong Song
- Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510006, China; Shenzhen Research Institute of Sun Yat-sen University, Shenzhen, Guangdong, China.
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15
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Wang Y, Wang X, Ye L, Yang Q, Cui Q, He Z, Li L, Yang X, Zou Q, Yang P, Liu D, Chen H. Spatial complexity of brain signal is altered in patients with generalized anxiety disorder. J Affect Disord 2019; 246:387-393. [PMID: 30597300 DOI: 10.1016/j.jad.2018.12.107] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Revised: 12/19/2018] [Accepted: 12/24/2018] [Indexed: 12/11/2022]
Abstract
BACKGROUND Is it healthy to be chaotic? Recent studies have argued that mental disorders are associated with more orderly neural activities, corresponding to a less flexible functional system. These conclusions were derived from altered temporal complexity. However, the relationship between spatial complexity and health is unknown, although spatial configuration is of importance for normal brain function. METHODS Based on resting-state functional magnetic resonance imaging data, we used Sample entropy (SampEn) to evaluate the altered spatial complexity in patients with generalized anxiety disorder (GAD; n = 47) compared to healthy controls (HCs; n = 38) and the relationship between spatial complexity and anxiety level. RESULTS Converging results showed increased spatial complexity in patients with GAD, indicating more chaotic spatial configuration. Interestingly, inverted-U relationship was revealed between spatial complexity and anxiety level, suggesting complex relationship between health and the chaos of human brain. LIMITATIONS Anxiety-related alteration of spatial complexity should be verified at voxel level in a larger sample and compared with results of other indices to clarify the mechanism of spatial chaotic of anxiety. CONCLUSIONS Altered spatial complexity in the brain of GAD patients mirrors inverted-U relationship between anxiety and behavioral performance, which may reflect an important characteristic of anxiety. These results indicate that SampEn is a good reflection of human health or trait mental characteristic.
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Affiliation(s)
- Yifeng Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, 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, China
| | - Xinqi Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, 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, China
| | - Liangkai Ye
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, 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, China
| | - Qi Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, 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, China
| | - Qian Cui
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, China; School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu, China
| | - Zongling He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, 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, China
| | - Liyuan Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, 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, China
| | - Xuezhi Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, 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, China
| | - Qijun Zou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, 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, China
| | - Pu Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, 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, China
| | - Dongfeng Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, 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, China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, 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, China.
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16
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Wang N, Wu H, Xu M, Yang Y, Chang C, Zeng W, Yan H. Occupational functional plasticity revealed by brain entropy: A resting-state fMRI study of seafarers. Hum Brain Mapp 2018; 39:2997-3004. [PMID: 29676512 DOI: 10.1002/hbm.24055] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2017] [Revised: 02/12/2018] [Accepted: 03/12/2018] [Indexed: 11/09/2022] Open
Abstract
Recently, functional magnetic resonance imaging (fMRI) has been increasingly used to assess brain function. Brain entropy is an effective model for evaluating the alteration of brain complexity. Specifically, the sample entropy (SampEn) provides a feasible solution for revealing the brain's complexity. Occupation is one key factor affecting the brain's activity, but the neuropsychological mechanisms are still unclear. Thus, in this article, based on fMRI and a brain entropy model, we explored the functional complexity changes engendered by occupation factors, taking the seafarer as an example. The whole-brain entropy values of two groups (i.e., the seafarers and the nonseafarers) were first calculated by SampEn and followed by a two-sample t test with AlphaSim correction (p < .05). We found that the entropy of the orbital-frontal gyrus (OFG) and superior temporal gyrus (STG) in the seafarers was significantly higher than that of the nonseafarers. In addition, the entropy of the cerebellum in the seafarers was lower than that of the nonseafarers. We conclude that (1) the lower entropy in the cerebellum implies that the seafarers' cerebellum activity had strong regularity and consistency, suggesting that the seafarer's cerebellum was possibly more specialized by the long-term career training; (2) the higher entropy in the OFG and STG possibly demonstrated that the seafarers had a relatively decreased capability for emotion control and auditory information processing. The above results imply that the seafarer occupation indeed impacted the brain's complexity, and also provided new neuropsychological evidence of functional plasticity related to one's career.
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Affiliation(s)
- Nizhuan Wang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518060, China.,Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen University, Shenzhen, 518060, China
| | - Huijun Wu
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518060, China.,Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen University, Shenzhen, 518060, China
| | - Min Xu
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518060, China.,Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen University, Shenzhen, 518060, China.,Center for Neuroimaging, Shenzhen Institute of Neuroscience, Shenzhen, 518057, China
| | - Yang Yang
- Center for Neuroimaging, Shenzhen Institute of Neuroscience, Shenzhen, 518057, China
| | - Chunqi Chang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, 518060, China.,Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen University, Shenzhen, 518060, China.,Center for Neuroimaging, Shenzhen Institute of Neuroscience, Shenzhen, 518057, China
| | - Weiming Zeng
- Digital Image and Intelligent computation Laboratory, College of Information Engineering, Shanghai Maritime University, Shanghai, 201306, China
| | - Hongjie Yan
- Department of Neurology, Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, 222002, China
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