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Herbert C, Northoff G. Editorial: Analyzing and computing humans - the role of language, culture, brain and health. Front Hum Neurosci 2024; 18:1439729. [PMID: 39015823 PMCID: PMC11250248 DOI: 10.3389/fnhum.2024.1439729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2024] [Accepted: 06/06/2024] [Indexed: 07/18/2024] Open
Affiliation(s)
- Cornelia Herbert
- Applied Emotion and Motivation Psychology, Institute of Psychology and Education, Faculty of Engineering, Computer Science and Psychology, Ulm University, Ulm, Germany
| | - Georg Northoff
- Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
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Thanaraju A, Marzuki AA, Chan JK, Wong KY, Phon-Amnuaisuk P, Vafa S, Chew J, Chia YC, Jenkins M. Structural and functional brain correlates of socioeconomic status across the life span: A systematic review. Neurosci Biobehav Rev 2024; 162:105716. [PMID: 38729281 DOI: 10.1016/j.neubiorev.2024.105716] [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: 01/28/2024] [Revised: 04/08/2024] [Accepted: 05/06/2024] [Indexed: 05/12/2024]
Abstract
It is well-established that higher socioeconomic status (SES) is associated with improved brain health. However, the effects of SES across different life stages on brain structure and function is still equivocal. In this systematic review, we aimed to synthesise findings from life course neuroimaging studies that investigated the structural and functional brain correlates of SES across the life span. The results indicated that higher SES across different life stages were independently and cumulatively related to neural outcomes typically reflective of greater brain health (e.g., increased cortical thickness, grey matter volume, fractional anisotropy, and network segregation) in adult individuals. The results also demonstrated that the corticolimbic system was most commonly impacted by socioeconomic disadvantages across the life span. This review highlights the importance of taking into account SES across the life span when studying its effects on brain health. It also provides directions for future research including the need for longitudinal and multimodal research that can inform effective policy interventions tailored to specific life stages.
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Affiliation(s)
- Arjun Thanaraju
- Department of Biological Sciences, School of Medical and Life Sciences, Sunway University, Malaysia.
| | - Aleya A Marzuki
- Department for Psychiatry and Psychotherapy, Medical School and University Hospital, Eberhard Karls University of Tübingen, Germany
| | - Jee Kei Chan
- Department of Psychology, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Malaysia
| | - Kean Yung Wong
- Sensory Neuroscience and Nutrition Lab, University of Otago, New Zealand
| | - Paveen Phon-Amnuaisuk
- Department of Psychology, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Malaysia
| | - Samira Vafa
- Department of Psychology, School of Medical and Life Sciences, Sunway University, Malaysia
| | - Jactty Chew
- Department of Biological Sciences, School of Medical and Life Sciences, Sunway University, Malaysia
| | - Yook Chin Chia
- Department of Medical Sciences, School of Medical and Life Sciences, Sunway University, Malaysia
| | - Michael Jenkins
- Department of Psychology, School of Medical and Life Sciences, Sunway University, Malaysia
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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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Herbert C. Analyzing and computing humans by means of the brain using Brain-Computer Interfaces - understanding the user - previous evidence, self-relevance and the user's self-concept as potential superordinate human factors of relevance. Front Hum Neurosci 2024; 17:1286895. [PMID: 38435127 PMCID: PMC10904616 DOI: 10.3389/fnhum.2023.1286895] [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: 08/31/2023] [Accepted: 12/11/2023] [Indexed: 03/05/2024] Open
Abstract
Brain-computer interfaces (BCIs) are well-known instances of how technology can convert a user's brain activity taken from non-invasive electroencephalography (EEG) into computer commands for the purpose of computer-assisted communication and interaction. However, not all users are attaining the accuracy required to use a BCI consistently, despite advancements in technology. Accordingly, previous research suggests that human factors could be responsible for the variance in BCI performance among users. Therefore, the user's internal mental states and traits including motivation, affect or cognition, personality traits, or the user's satisfaction, beliefs or trust in the technology have been investigated. Going a step further, this manuscript aims to discuss which human factors could be potential superordinate factors that influence BCI performance, implicitly, explicitly as well as inter- and intraindividually. Based on the results of previous studies that used comparable protocols to examine the motivational, affective, cognitive state or personality traits of healthy and vulnerable EEG-BCI users within and across well-investigated BCIs (P300-BCIs or SMR-BCIs, respectively), it is proposed that the self-relevance of tasks and stimuli and the user's self-concept provide a huge potential for BCI applications. As potential key human factors self-relevance and the user's self-concept (self-referential knowledge and beliefs about one's self) guide information processing and modulate the user's motivation, attention, or feelings of ownership, agency, and autonomy. Changes in the self-relevance of tasks and stimuli as well as self-referential processing related to one's self (self-concept) trigger changes in neurophysiological activity in specific brain networks relevant to BCI. Accordingly, concrete examples will be provided to discuss how past and future research could incorporate self-relevance and the user's self-concept in the BCI setting - including paradigms, user instructions, and training sessions.
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Affiliation(s)
- Cornelia Herbert
- Department of Applied Emotion and Motivation Psychology, Institute of Psychology and Education, Ulm University, Ulm, Germany
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Prasad R, Tarai S, Bit A. Hybrid computational model depicts the contribution of non-significant lobes of human brain during the perception of emotional stimuli. Comput Methods Biomech Biomed Engin 2024:1-27. [PMID: 38328832 DOI: 10.1080/10255842.2024.2311876] [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: 12/19/2022] [Accepted: 11/03/2023] [Indexed: 02/09/2024]
Abstract
Emotions are synchronizing responses of human brain while executing cognitive tasks. Earlier studies had revealed strong correlation between specific lobes of the brain to different types of emotional valence. In the current study, a comprehensive three-dimensional mapping of human brain for executing emotion specific tasks had been formulated. A hybrid computational machine learning model customized from Custom Weight Allocation Model (CWAM) and defined as Custom Rank Allocation Model (CRAM). This regression-based hybrid computational model computes the allocated tasks to different lobes of the brain during their respective executive stage. Event Related Potentials (ERP) were obtained with significant effect at P1, P2, P3, N170, N2, and N4. These ERPs were configured at Pz, Cz, F3, and T8 regions of the brain with maximal responses; while regions like Cz, C4 and F4 were also found to make effective contributions to elevate the responses of the brain, and thus these regions were configured as augmented source regions of the brain. In another circumstance of frequent -deviant - equal (FDE) presentation of the emotional stimuli, it was observed that the brain channels C3, C4, P3, P4, O1, O2, and Oz were contributing their emotional quotient to the overall response of the brain regions; whereas, the interaction effect was found presentable at O2, Oz, P3, P4, T8 and C3 regions of brain. The proposed computational model had identified the potential neural pathways during the execution of emotional task.
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Affiliation(s)
| | | | - Arindam Bit
- Department of Biomedical Engineering, NIT Raipur
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Zhou X, Liao PC, Xu Q. Reinvestigation of the Psychological Mechanisms of Construction Experience on Hazard Recognition Performance. HUMAN FACTORS 2024; 66:221-233. [PMID: 35225014 DOI: 10.1177/00187208211066666] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
OBJECTIVE The study aimed to reinvestigate psychological mechanisms of the influence of construction workers' experience on hazard recognition performance, with signal detection theory (SDT) and electroencephalogram (EEG) readings. BACKGROUND Existing evidence regarding the effect of experience on hazard recognition performance in the construction industry remains inconsistent. Behavior-wise, identification of dominant hazard recognition factors (sensitivity or response bias, or both) would help determine appropriate training strategies to improve hazard recognition. In terms of neuro-responses, induced gamma-band activity was expected to reflect the cognitive functions mediating the psychological effects of experience. METHOD Seventy-seven construction workers participated in a predesigned hazard recognition task, in which participants judged whether a hazard was present from a series of construction scenario pictures. We computed and compared the sensitivity and response bias of SDT and time-frequency representations of recorded EEG signals of the two experience-level groups. RESULTS Novice workers had higher hazard recognition rates. Behavior-wise, novices were more sensitive than more experienced workers. Compared with experienced workers, novices showed stronger gamma-band difference power (hazardous minus safe) in the left frontal and right posterior parietal areas during the hazard recognition process. CONCLUSION Novices performed better at hazard recognition, indicating their sensitivity to the hazards without a clear difference in response bias. Based on the EEG data, novices' sensitivity may be attributed to more efficient working memory and attentional control. APPLICATION There is a need for continuous refreshment of hazard recognition skills for experienced workers for safety interventions.
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Affiliation(s)
- Xiaoshan Zhou
- Department of Construction Management, Tsinghua University, Beijing, China
| | - Pin-Chao Liao
- Department of Construction Management, Tsinghua University, Beijing, China
| | - Qingwen Xu
- Department of Construction Management, Tsinghua University, Beijing, China
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de Souza DLS, Costa HMGES, Neta FI, Morais PLADG, Guerra LMDM, Guzen FP, de Oliveira LC, Cavalcanti JRLDP, de Albuquerque CC, de Vasconcelos CL. Brain Neuroplasticity after Treatment with Antiseizure: A Review. CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE : THE OFFICIAL SCIENTIFIC JOURNAL OF THE KOREAN COLLEGE OF NEUROPSYCHOPHARMACOLOGY 2023; 21:665-675. [PMID: 37859439 PMCID: PMC10591163 DOI: 10.9758/cpn.23.1058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 04/15/2023] [Accepted: 04/17/2023] [Indexed: 10/21/2023]
Abstract
Epilepsy is a disease characterized by the periodic occurrence of seizures. Seizures can be controlled by antiseizure medications, which can improve the lives of individuals with epilepsy when given proper treatment. Therefore, this study aimed to review the scientific literature on brain neuroplasticity after treatment with antiseizure drugs in different regions of the brain. According to the findings, that several antiseizure, such as lamotrigine, diazepam, levetiracetam, and valproic acid, in addition to controlling seizures, can also act on neuroplasticity in different brain regions. The study of this topic becomes important, as it will help to understand the neuroplastic mechanisms of these drugs, in addition to helping to improve the effectiveness of these drugs in controlling the disease.
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Affiliation(s)
- Débora Lopes Silva de Souza
- Faculty of Health Sciences, Department of Biomedical Sciences, Universidade do Estado do Rio Grande do Norte, Mossoró, Brazil
| | | | - Francisca Idalina Neta
- Faculty of Health Sciences, Department of Biomedical Sciences, Universidade do Estado do Rio Grande do Norte, Mossoró, Brazil
| | | | - Luís Marcos de Medeiros Guerra
- Faculty of Health Sciences, Department of Biomedical Sciences, Universidade do Estado do Rio Grande do Norte, Mossoró, Brazil
| | - Fausto Pierdoná Guzen
- Faculty of Health Sciences, Department of Biomedical Sciences, Universidade do Estado do Rio Grande do Norte, Mossoró, Brazil
| | | | | | - Cynthia Cavalcanti de Albuquerque
- Faculty of Exact and Natural Sciences, Department of Biological Sciences, Universidade do Estado do Rio Grande do Norte, Mossoró, Brazil
| | - Claudio Lopes de Vasconcelos
- Faculty of Exact and Natural Sciences, Department of Chemistry, Universidade do Estado do Rio Grande do Norte, Mossoró, Brazil
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Zhao M, Hao Z, Li M, Xi H, Hu S, Wen J, Gao Y, Antwi CO, Jia X, Yu Y, Ren J. Functional changes of default mode network and structural alterations of gray matter in patients with irritable bowel syndrome: a meta-analysis of whole-brain studies. Front Neurosci 2023; 17:1236069. [PMID: 37942144 PMCID: PMC10627928 DOI: 10.3389/fnins.2023.1236069] [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: 06/07/2023] [Accepted: 10/09/2023] [Indexed: 11/10/2023] Open
Abstract
Background Irritable bowel syndrome (IBS) is a brain-gut disorder with high global prevalence, resulting from abnormalities in brain connectivity of the default mode network and aberrant changes in gray matter (GM). However, the findings of previous studies about IBS were divergent. Therefore, we conducted a meta-analysis to identify common functional and structural alterations in IBS patients. Methods Altogether, we identified 12 studies involving 194 IBS patients and 230 healthy controls (HCs) from six databases using whole-brain resting state functional connectivity (rs-FC) and voxel-based morphometry. Anisotropic effect-size signed differential mapping (AES-SDM) was used to identify abnormal functional and structural changes as well as the overlap brain regions between dysconnectivity and GM alterations. Results Findings indicated that, compared with HCs, IBS patients showed abnormal rs-FC in left inferior parietal gyrus, left lingual gyrus, right angular gyrus, right precuneus, right amygdala, right median cingulate cortex, and left hippocampus. Altered GM was detected in the fusiform gyrus, left triangular inferior frontal gyrus (IFG), right superior marginal gyrus, left anterior cingulate gyrus, left rectus, left orbital IFG, right triangular IFG, right putamen, left superior parietal gyrus and right precuneus. Besides, multimodal meta-analysis identified left middle frontal gyrus, left orbital IFG, and right putamen as the overlapped regions. Conclusion Our results confirm that IBS patients have abnormal alterations in rs-FC and GM, and reveal brain regions with both functional and structural alterations. These results may contribute to understanding the underlying pathophysiology of IBS. Systematic review registration https://www.crd.york.ac.uk/prospero, identifier CRD42022351342.
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Affiliation(s)
- Mengqi Zhao
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent, Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, China
| | - Zeqi Hao
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent, Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, China
| | - Mengting Li
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent, Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, China
| | - Hongyu Xi
- School of Western Languages, Heilongjiang University, Harbin, China
| | - Su Hu
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent, Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, China
| | - Jianjie Wen
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent, Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, China
| | - Yanyan Gao
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent, Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, China
| | - Collins Opoku Antwi
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent, Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, China
| | - Xize Jia
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent, Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, China
| | - Yang Yu
- Department of Psychiatry, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Jun Ren
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent, Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, China
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Mitsopoulos K, Fiska V, Tagaras K, Papias A, Antoniou P, Nizamis K, Kasimis K, Sarra PD, Mylopoulou D, Savvidis T, Praftsiotis A, Arvanitidis A, Lyssas G, Chasapis K, Moraitopoulos A, Astaras A, Bamidis PD, Athanasiou A. NeuroSuitUp: System Architecture and Validation of a Motor Rehabilitation Wearable Robotics and Serious Game Platform. SENSORS (BASEL, SWITZERLAND) 2023; 23:3281. [PMID: 36991992 PMCID: PMC10053382 DOI: 10.3390/s23063281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 03/04/2023] [Accepted: 03/14/2023] [Indexed: 06/19/2023]
Abstract
BACKGROUND This article presents the system architecture and validation of the NeuroSuitUp body-machine interface (BMI). The platform consists of wearable robotics jacket and gloves in combination with a serious game application for self-paced neurorehabilitation in spinal cord injury and chronic stroke. METHODS The wearable robotics implement a sensor layer, to approximate kinematic chain segment orientation, and an actuation layer. Sensors consist of commercial magnetic, angular rate and gravity (MARG), surface electromyography (sEMG), and flex sensors, while actuation is achieved through electrical muscle stimulation (EMS) and pneumatic actuators. On-board electronics connect to a Robot Operating System environment-based parser/controller and to a Unity-based live avatar representation game. BMI subsystems validation was performed using exercises through a Stereoscopic camera Computer Vision approach for the jacket and through multiple grip activities for the glove. Ten healthy subjects participated in system validation trials, performing three arm and three hand exercises (each 10 motor task trials) and completing user experience questionnaires. RESULTS Acceptable correlation was observed in 23/30 arm exercises performed with the jacket. No significant differences in glove sensor data during actuation state were observed. No difficulty to use, discomfort, or negative robotics perception were reported. CONCLUSIONS Subsequent design improvements will implement additional absolute orientation sensors, MARG/EMG based biofeedback to the game, improved immersion through Augmented Reality and improvements towards system robustness.
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Affiliation(s)
- Konstantinos Mitsopoulos
- Medical Physics & Digital Innovation Laboratory, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Vasiliki Fiska
- Medical Physics & Digital Innovation Laboratory, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Konstantinos Tagaras
- Medical Physics & Digital Innovation Laboratory, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Athanasios Papias
- Medical Physics & Digital Innovation Laboratory, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Panagiotis Antoniou
- Medical Physics & Digital Innovation Laboratory, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Konstantinos Nizamis
- Department of Design, Production and Management, University of Twente, 7522 NB Enschede, The Netherlands
| | - Konstantinos Kasimis
- Department of Physiotherapy, International Hellenic University, 57400 Thessaloniki, Greece
| | - Paschalina-Danai Sarra
- Medical Physics & Digital Innovation Laboratory, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Diamanto Mylopoulou
- Medical Physics & Digital Innovation Laboratory, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Theodore Savvidis
- Medical Physics & Digital Innovation Laboratory, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Apostolos Praftsiotis
- Medical Physics & Digital Innovation Laboratory, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Athanasios Arvanitidis
- Medical Physics & Digital Innovation Laboratory, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - George Lyssas
- Medical Physics & Digital Innovation Laboratory, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Konstantinos Chasapis
- Medical Physics & Digital Innovation Laboratory, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Alexandros Moraitopoulos
- Medical Physics & Digital Innovation Laboratory, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Alexander Astaras
- Department of Computer Science, American College of Thessaloniki, 55535 Thessaloniki, Greece
| | - Panagiotis D. Bamidis
- Medical Physics & Digital Innovation Laboratory, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - Alkinoos Athanasiou
- Medical Physics & Digital Innovation Laboratory, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
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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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Shi Y, Zeng W. The integrative functional connectivity analysis between seafarer’s brain networks using functional magnetic resonance imaging data of different states. Front Neurosci 2022; 16:1008652. [DOI: 10.3389/fnins.2022.1008652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 09/30/2022] [Indexed: 11/13/2022] Open
Abstract
The particularity of seafarers’ occupation makes their brain functional activities vulnerable to the influence of working environments, which leads to abnormal functional connectivities (FCs) between brain networks. To further investigate the influences of maritime environments on the seafarers’ functional brain networks, the functional magnetic resonance imaging (fMRI) datasets of 33 seafarers before and after sailing were used to study FCs among the functional brain networks in this paper. On the basis of making full use of the intrinsic prior information from fMRI data, six resting-state brain functional networks of seafarers before and after sailing were obtained by using group independent component analysis with intrinsic reference, and then the differences between the static and dynamic FCs among these six brain networks of seafarers before and after sailing were, respectively, analyzed from both group and individual levels. Subsequently, the potential dynamic functional connectivity states of seafarers before and after sailing were extracted by using the affine propagation clustering algorithm and the probabilities of state transition between them were obtained simultaneously. The results show that the dynamic FCs among large-scale brain networks have significant difference seafarers before and after sailing both at the group level and individual level, while the static FCs between them varies only at the individual level. This suggests that the maritime environments can indeed affect the brain functional activity of seafarers in real time, and the degree of influence is different for different subjects, which is of a great significance to explore the neural changes of seafarer’s brain functional network.
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Rus-Oswald OG, Benner J, Reinhardt J, Bürki C, Christiner M, Hofmann E, Schneider P, Stippich C, Kressig RW, Blatow M. Musicianship-Related Structural and Functional Cortical Features Are Preserved in Elderly Musicians. Front Aging Neurosci 2022; 14:807971. [PMID: 35401149 PMCID: PMC8990841 DOI: 10.3389/fnagi.2022.807971] [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: 11/02/2021] [Accepted: 01/25/2022] [Indexed: 11/13/2022] Open
Abstract
Background Professional musicians are a model population for exploring basic auditory function, sensorimotor and multisensory integration, and training-induced neuroplasticity. The brain of musicians exhibits distinct structural and functional cortical features; however, little is known about how these features evolve during aging. This multiparametric study aimed to examine the functional and structural neural correlates of lifelong musical practice in elderly professional musicians. Methods Sixteen young musicians, 16 elderly musicians (age >70), and 15 elderly non-musicians participated in the study. We assessed gray matter metrics at the whole-brain and region of interest (ROI) levels using high-resolution magnetic resonance imaging (MRI) with the Freesurfer automatic segmentation and reconstruction pipeline. We used BrainVoyager semiautomated segmentation to explore individual auditory cortex morphotypes. Furthermore, we evaluated functional blood oxygenation level-dependent (BOLD) activations in auditory and non-auditory regions by functional MRI (fMRI) with an attentive tone-listening task. Finally, we performed discriminant function analyses based on structural and functional ROIs. Results A general reduction of gray matter metrics distinguished the elderly from the young subjects at the whole-brain level, corresponding to widespread natural brain atrophy. Age- and musicianship-dependent structural correlations revealed group-specific differences in several clusters including superior, middle, and inferior frontal as well as perirolandic areas. In addition, the elderly musicians exhibited increased gyrification of auditory cortex like the young musicians. During fMRI, the elderly non-musicians activated predominantly auditory regions, whereas the elderly musicians co-activated a much broader network of auditory association areas, primary and secondary motor areas, and prefrontal and parietal regions like, albeit weaker, the young musicians. Also, group-specific age- and musicianship-dependent functional correlations were observed in the frontal and parietal regions. Moreover, discriminant function analysis could separate groups with high accuracy based on a set of specific structural and functional, mainly temporal and occipital, ROIs. Conclusion In conclusion, despite naturally occurring senescence, the elderly musicians maintained musicianship-specific structural and functional cortical features. The identified structural and functional brain regions, discriminating elderly musicians from non-musicians, might be of relevance for the aging musicians’ brain. To what extent lifelong musical activity may have a neuroprotective impact needs to be addressed further in larger longitudinal studies.
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Affiliation(s)
- Oana G. Rus-Oswald
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
- University Department of Geriatric Medicine FELIX PLATTER, Basel, Switzerland
- *Correspondence: Oana G. Rus-Oswald,
| | - Jan Benner
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
- Jan Benner,
| | - Julia Reinhardt
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
- Division of Diagnostic and Interventional Neuroradiology, Department of Radiology, University Hospital Basel, University of Basel, Basel, Switzerland
- Department of Cardiology and Cardiovascular Research Institute Basel, University Hospital Basel, University of Basel, Basel, Switzerland
- Department of Orthopedic Surgery and Traumatology, University Hospital of Basel, University of Basel, Basel, Switzerland
| | - Céline Bürki
- University Department of Geriatric Medicine FELIX PLATTER, Basel, Switzerland
| | - Markus Christiner
- Centre for Systematic Musicology, University of Graz, Graz, Austria
- Vitols Jazeps Latvian Academy of Music, Riga, Latvia
| | - Elke Hofmann
- Academy of Music, University of Applied Sciences and Arts Northwestern Switzerland (FHNW), Basel, Switzerland
| | - Peter Schneider
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
- Centre for Systematic Musicology, University of Graz, Graz, Austria
- Vitols Jazeps Latvian Academy of Music, Riga, Latvia
| | - Christoph Stippich
- Department of Neuroradiology and Radiology, Kliniken Schmieder, Allensbach, Germany
| | - Reto W. Kressig
- University Department of Geriatric Medicine FELIX PLATTER, Basel, Switzerland
| | - Maria Blatow
- Section of Neuroradiology, Department of Radiology and Nuclear Medicine, Neurocenter, Cantonal Hospital Lucerne, University of Lucerne, Lucerne, Switzerland
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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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15
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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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16
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Wang Y, Wei H, Du S, Yan H, Li X, Wu Y, Zhu J, Wang Y, Cai Z, Wang N. Functional Covariance Connectivity of Gray and White Matter in Olfactory-Related Brain Regions in Parkinson’s Disease. Front Neurosci 2022; 16:853061. [PMID: 35310108 PMCID: PMC8930839 DOI: 10.3389/fnins.2022.853061] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 02/14/2022] [Indexed: 01/13/2023] Open
Abstract
Before the onset of motor symptoms, Parkinson’s disease (PD) involves dysfunction of the anterior olfactory nucleus and olfactory bulb, causing olfactory disturbance, commonly resulting in hyposmia in the early stages of PD. Accumulating evidence has shown that blood oxygen level dependent (BOLD) signals in white matter are altered by olfactory disorders and related stimuli, and the signal changes in brain white matter pathways show a certain degree of specificity, which can reflect changes of early olfactory dysfunction in Parkinson’s disease. In this study, we apply the functional covariance connectivity (FCC) method to decode FCC of gray and white matter in olfactory-related brain regions in Parkinson’s disease. Our results show that the dorsolateral prefrontal, anterior entorhinal cortex and fronto-orbital cortices in the gray matter have abnormal connectivity with the posterior corona radiata and superior corona radiata in white matter in patients with Parkinson’s hyposmia. The functional covariance connection strength (FCS) of the right dorsolateral prefrontal cortex and white matter, and the covariance connection strength of the left superior corona radiata and gray matter function have potential diagnostic value. These results demonstrate that alterations in FCC of gray and white matter in olfactory-related brain regions can reflect the change of olfactory function in the early stages of Parkinson’s disease, indicating that it could be a potential neuroimaging marker for early diagnosis.
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Affiliation(s)
- Yiqing Wang
- Department of Neurology, The Affiliated Suzhou Science and Technology Town Hospital of Nanjing Medical University, Suzhou, China
- Department of Neurology, Gusu School, Nanjing Medical University, Suzhou, China
| | - Hongyu Wei
- Department of Neurology, The Affiliated Suzhou Science and Technology Town Hospital of Nanjing Medical University, Suzhou, China
| | - Shouyun Du
- Department of Neurology, Guanyun People’s Hospital, Lianyungang, China
| | - Hongjie Yan
- Department of Neurology, Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, China
| | - Xiaojing Li
- Department of Neurology, The Affiliated Suzhou Science and Technology Town Hospital of Nanjing Medical University, Suzhou, China
| | - Yijie Wu
- Department of Neurology, The Affiliated Suzhou Science and Technology Town Hospital of Nanjing Medical University, Suzhou, China
| | - Jianbing Zhu
- Department of Radiology, The Affiliated Suzhou Science and Technology Town Hospital of Nanjing Medical University, Suzhou, China
| | - Yi Wang
- Department of Radiology, The Affiliated Suzhou Science and Technology Town Hospital of Nanjing Medical University, Suzhou, China
| | - Zenglin Cai
- Department of Neurology, The Affiliated Suzhou Science and Technology Town Hospital of Nanjing Medical University, Suzhou, China
- Department of Neurology, 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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Yu Q, Cai Z, Li C, Xiong Y, Yang Y, He S, Tang H, Zhang B, Du S, Yan H, Chang C, Wang N. A Novel Spectrum Contrast Mapping Method for Functional Magnetic Resonance Imaging Data Analysis. Front Hum Neurosci 2021; 15:739668. [PMID: 34566609 PMCID: PMC8455948 DOI: 10.3389/fnhum.2021.739668] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2021] [Accepted: 08/18/2021] [Indexed: 12/18/2022] Open
Abstract
Many studies reported that spontaneous fluctuation of the blood oxygen level-dependent signal exists in multiple frequency components and changes over time. By assuming a reliable energy contrast between low- and high-frequency bands for each voxel, we developed a novel spectrum contrast mapping (SCM) method to decode brain activity at the voxel-wise level and further validated it in designed experiments. SCM consists of the following steps: first, the time course of each given voxel is subjected to fast Fourier transformation; the corresponding spectrum is divided into low- and high-frequency bands by given reference frequency points; then, the spectral energy ratio of the low- to high-frequency bands is calculated for each given voxel. Finally, the activity decoding map is formed by the aforementioned energy contrast values of each voxel. Our experimental results demonstrate that the SCM (1) was able to characterize the energy contrast of task-related brain regions; (2) could decode brain activity at rest, as validated by the eyes-closed and eyes-open resting-state experiments; (3) was verified with test-retest validation, indicating excellent reliability with most coefficients > 0.9 across the test sessions; and (4) could locate the aberrant energy contrast regions which might reveal the brain pathology of brain diseases, such as Parkinson’s disease. In summary, we demonstrated that the reliable energy contrast feature was a useful biomarker in characterizing brain states, and the corresponding SCM showed excellent brain activity-decoding performance at the individual and group levels, implying its potentially broad application in neuroscience, neuroimaging, and brain diseases.
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Affiliation(s)
- Qin Yu
- Artificial Intelligence and Neuro-Informatics Engineering (ARINE) Laboratory, School of Computer Engineering, Jiangsu Ocean University, Lianyungang, China
| | - Zenglin Cai
- Department of Neurology, The Affiliated Suzhou Science and Technology Town Hospital of Nanjing Medical University, Suzhou, China
| | - Cunhua Li
- Artificial Intelligence and Neuro-Informatics Engineering (ARINE) Laboratory, School of Computer Engineering, Jiangsu Ocean University, Lianyungang, China
| | - Yulong Xiong
- Artificial Intelligence and Neuro-Informatics Engineering (ARINE) Laboratory, School of Computer Engineering, Jiangsu Ocean University, Lianyungang, China
| | - Yang Yang
- Center for Brain Science and Learning Difficulties, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Shuang He
- Artificial Intelligence and Neuro-Informatics Engineering (ARINE) Laboratory, School of Computer Engineering, Jiangsu Ocean University, Lianyungang, China
| | - Haitong Tang
- Artificial Intelligence and Neuro-Informatics Engineering (ARINE) Laboratory, School of Computer Engineering, Jiangsu Ocean University, Lianyungang, China
| | - Bo Zhang
- Department of Radiology, Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, China
| | - Shouyun Du
- Department of Neurology, Guanyun People's Hospital, Guanyun, China
| | - Hongjie Yan
- Department of Neurology, Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, China
| | - Chunqi Chang
- Health Science Center, School of Biomedical Engineering, Shenzhen University, Shenzhen, China.,Pengcheng Laboratory, Shenzhen, China
| | - Nizhuan Wang
- Artificial Intelligence and Neuro-Informatics Engineering (ARINE) Laboratory, School of Computer Engineering, Jiangsu Ocean University, Lianyungang, China
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Koch K, Rodriguez-Manrique D, Rus-Oswald OG, Gürsel DA, Berberich G, Kunz M, Zimmer C. Homogeneous grey matter patterns in patients with obsessive-compulsive disorder. NEUROIMAGE-CLINICAL 2021; 31:102727. [PMID: 34146774 PMCID: PMC8220095 DOI: 10.1016/j.nicl.2021.102727] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 05/19/2021] [Accepted: 06/09/2021] [Indexed: 11/16/2022]
Abstract
BACKGROUND Changes in grey matter volume have frequently been reported in patients with obsessive-compulsive disorder (OCD). Most studies performed whole brain or region-of-interest based analyses whereas grey matter volume based on structural covariance networks has barely been investigated up to now. Therefore, the present study investigated grey matter volume within structural covariance networks in a sample of 228 participants (n = 117 OCD patients, n = 111 healthy controls). METHODS First, an independent component analysis (ICA) was performed on all subjects' preprocessed T1 images to derive covariance-dependent morphometric networks. Then, grey matter volume from each of the ICA-derived morphometric networks was extracted and compared between the groups. In addition, we performed logistic regressions and receiver operating characteristic (ROC) analyses to investigate whether network-related grey matter volume could serve as a characteristic that allows to differentiate patients from healthy volunteers. Moreover, we assessed grey matter pattern organization by correlating grey matter volume in all networks across all participants. Finally, we explored a potential association between grey matter volume or whole-brain grey matter pattern organization and clinical characteristics in terms of symptom severity and duration of illness. RESULTS There were only subtle group differences in network-related grey matter volume. Network-related grey matter volume had moreover a very poor discrimination performance. We found, however, significant group differences with regard to grey matter pattern organization. When correlating grey matter volume in all networks across all participants, patients showed a significantly higher homogeneity across all networks and a significantly lower heterogeneity, as assessed by the coefficient of variation across all networks as well as in several single networks. There was no association with clinical characteristics. CONCLUSION The findings of the present study suggest that the pathological mechanisms of OCD reduce interindividual grey matter variability. We assume that common characteristics associated with the disorder may lead to a more uniform, disorder-specific morphometry.
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Affiliation(s)
- Kathrin Koch
- Department of Neuroradiology & TUM-Neuroimaging Center (TUM-NIC), Klinikum rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675 Munich, Germany; Graduate School of Systemic Neurosciences GSN, Ludwig-Maximilians-Universität, Biocenter, Groβhaderner Strasse 2, 82152 Munich, Germany.
| | - Daniela Rodriguez-Manrique
- Department of Neuroradiology & TUM-Neuroimaging Center (TUM-NIC), Klinikum rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675 Munich, Germany; Graduate School of Systemic Neurosciences GSN, Ludwig-Maximilians-Universität, Biocenter, Groβhaderner Strasse 2, 82152 Munich, Germany
| | | | - Deniz A Gürsel
- Department of Neuroradiology & TUM-Neuroimaging Center (TUM-NIC), Klinikum rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675 Munich, Germany
| | - Götz Berberich
- Windach Institute and Hospital of Neurobehavioural Research and Therapy (WINTR), Schützenstr. 100, 86949 Windach, Germany
| | - Miriam Kunz
- Department of Medical Psychology, University of Augsburg, 86156 Augsburg, Germany
| | - Claus Zimmer
- Department of Neuroradiology & TUM-Neuroimaging Center (TUM-NIC), Klinikum rechts der Isar, Technische Universität München, Ismaninger Straße 22, 81675 Munich, Germany
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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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