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Saha P, Sarkar D. Characterization and Classification of ADHD Subtypes: An Approach Based on the Nodal Distribution of Eigenvector Centrality and Classification Tree Model. Child Psychiatry Hum Dev 2024; 55:622-634. [PMID: 36100839 DOI: 10.1007/s10578-022-01432-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/29/2022] [Indexed: 11/30/2022]
Abstract
In recent times, the complex network theory is increasingly applied to characterize, classify, and diagnose a broad spectrum of neuropathological conditions, including attention deficit hyperactivity disorder (ADHD), Alzheimer's disease, bipolar disorder, and many others. Nevertheless, the diagnosis and associated subtype identification majorly rely on the baseline correlation matrix obtained from the functional MRI scan. Thus, the existing protocols are either full of personalized bias or computationally expensive as network complexity-based simple but deterministic protocols are yet to be developed and formalized. This article proposes a deterministic method to identify and differentiate the common ADHD subtypes, which is based on a single complexity measure, namely the eigenvector centrality. The node-wise centrality differences were explored using a classification tree model (p < 0.05) to diagnose the subtypes. Identification of marker nodes from default mode, visual, frontoparietal, limbic, and cerebellar networks strongly vouch for the involvement of multiple brain regions in ADHD neuropathology.
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Affiliation(s)
- Papri Saha
- Department of Computer Science, Derozio Memorial College, Kolkata, 700136, India.
| | - Debasish Sarkar
- Department of Chemical Engineering, University of Calcutta, Kolkata, 700009, India
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2
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Tang C, Guo G, Fang S, Yao C, Zhu B, Kong L, Pan X, Li X, He W, Wu Z, Fang M. Abnormal brain activity in lumbar disc herniation patients with chronic pain is associated with their clinical symptoms. Front Neurosci 2023; 17:1206604. [PMID: 37575297 PMCID: PMC10416647 DOI: 10.3389/fnins.2023.1206604] [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: 04/16/2023] [Accepted: 07/13/2023] [Indexed: 08/15/2023] Open
Abstract
Introduction Lumbar disc herniation, a chronic degenerative disease, is one of the major contributors to chronic low back pain and disability. Although many studies have been conducted in the past on brain function in chronic low back pain, most of these studies did not classify chronic low back pain (cLBP) patients according to their etiology. The lack of etiologic classification may lead to inconsistencies between findings, and the correlation between differences in brain activation and clinical symptoms in patients with cLBP was less studied in the past. Methods In this study, 36 lumbar disc herniation patients with chronic low back pain (LDHCP) and 36 healthy controls (HCs) were included to study brain activity abnormalities in LDHCP. Visual analogue scale (VAS), oswestry disability index (ODI), self-rating anxiety scale (SAS), self-rating depression scale (SDS) were used to assess clinical symptoms. Results The results showed that LDHCP patients exhibited abnormally increased and diminished activation of brain regions compared to HCs. Correlation analysis showed that the amplitude of low frequency fluctuations (ALFF) in the left middle frontal gyrus is negatively correlated with SAS and VAS, while the right superior temporal gyrus is positively correlated with SAS and VAS, the dorsolateral left superior frontal gyrus and the right middle frontal gyrus are negatively correlated with VAS and SAS, respectively. Conclusion LDHCP patients have brain regions with abnormally increased and abnormally decreased activation compared to healthy controls. Furthermore, some of the abnormally activated brain regions were correlated with clinical pain or emotional symptoms.
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Affiliation(s)
- Cheng Tang
- Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Guangxin Guo
- School of Acupuncture-Moxibustion and Tuina, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Sitong Fang
- Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Chongjie Yao
- School of Acupuncture-Moxibustion and Tuina, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Bowen Zhu
- Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Lingjun Kong
- Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xuanjin Pan
- School of Acupuncture-Moxibustion and Tuina, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xinrong Li
- School of Acupuncture-Moxibustion and Tuina, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Weibin He
- Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Zhiwei Wu
- Research Institute of Tuina, Shanghai Academy of Traditional Chinese Medicine, Shanghai, China
- Yueyang Hospital of Integrated Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Min Fang
- Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, China
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3
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Tanglay O, Dadario NB, Chong EHN, Tang SJ, Young IM, Sughrue ME. Graph Theory Measures and Their Application to Neurosurgical Eloquence. Cancers (Basel) 2023; 15:556. [PMID: 36672504 PMCID: PMC9857081 DOI: 10.3390/cancers15020556] [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: 11/29/2022] [Revised: 01/04/2023] [Accepted: 01/14/2023] [Indexed: 01/18/2023] Open
Abstract
Improving patient safety and preserving eloquent brain are crucial in neurosurgery. Since there is significant clinical variability in post-operative lesions suffered by patients who undergo surgery in the same areas deemed compensable, there is an unknown degree of inter-individual variability in brain 'eloquence'. Advances in connectomic mapping efforts through diffusion tractography allow for utilization of non-invasive imaging and statistical modeling to graphically represent the brain. Extending the definition of brain eloquence to graph theory measures of hubness and centrality may help to improve our understanding of individual variability in brain eloquence and lesion responses. While functional deficits cannot be immediately determined intra-operatively, there has been potential shown by emerging technologies in mapping of hub nodes as an add-on to existing surgical navigation modalities to improve individual surgical outcomes. This review aims to outline and review current research surrounding novel graph theoretical concepts of hubness, centrality, and eloquence and specifically its relevance to brain mapping for pre-operative planning and intra-operative navigation in neurosurgery.
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Affiliation(s)
- Onur Tanglay
- UNSW School of Clinical Medicine, Faulty of Medicine and Health, University of New South Wales, Sydney, NSW 2052, Australia
- Omniscient Neurotechnology, Level 10/580 George Street, Sydney, NSW 2000, Australia
| | - Nicholas B. Dadario
- Robert Wood Johnson Medical School, Rutgers University, 125 Paterson St, New Brunswick, NJ 08901, USA
| | - Elizabeth H. N. Chong
- Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Dr, Singapore 117597, Singapore
| | - Si Jie Tang
- School of Medicine, University of California Davis, Sacramento, CA 95817, USA
| | - Isabella M. Young
- Omniscient Neurotechnology, Level 10/580 George Street, Sydney, NSW 2000, Australia
| | - Michael E. Sughrue
- Omniscient Neurotechnology, Level 10/580 George Street, Sydney, NSW 2000, Australia
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4
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Wang M, Zhao G, Jiang Y, Lu T, Wang Y, Zhu Y, Zhang Z, Xie C, Wang Z, Ren Q. Disconnection of Network Hubs Underlying the Executive Function Deficit in Patients with Ischemic Leukoaraiosis. J Alzheimers Dis 2023; 94:1577-1586. [PMID: 37458032 DOI: 10.3233/jad-230048] [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] [Indexed: 07/18/2023]
Abstract
BACKGROUND Cognitive impairment is the most common clinical manifestation of ischemic leukoaraiosis (ILA), but the underlying neurobiological pathways have not been well elucidated. Recently, it was thought that ILA is a "disconnection syndrome". Disorganized brain connectome were considered the key neuropathology underlying cognitive deficits in ILA patients. OBJECTIVE We aimed to detect the disruption of network hubs in ILA patients using a new analytical method called voxel-based eigenvector centrality (EC) mapping. METHODS Subjects with moderate to severe white matters hyperintensities (Fazekas score ≥3) and healthy controls (HCs) (Fazekas score = 0) were included in the study. The resting-state functional magnetic resonance imaging and the EC mapping approach were performed to explore the alteration of whole-brain network connectivity in ILA patients. RESULTS Relative to the HCs, the ILA patients exhibited poorer cognitive performance in episodic memory, information processing speed, and executive function (all ps < 0.0125). Additionally, compared with HCs, the ILA patients had lower functional connectivity (i.e., EC values) in the medial parts of default-mode network (i.e., bilateral posterior cingulate gyrus and ventral medial prefrontal cortex [vMPFC]). Intriguingly, the functional connectivity strength at the right vMPFC was positively correlated with executive function deficit in the ILA patients. CONCLUSION The findings suggested disorganization of the hierarchy of the default-mode regions within the whole-brain network in patients with ILA and advanced our understanding of the neurobiological mechanism underlying executive function deficit in ILA.
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Affiliation(s)
- Mengxue Wang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Guofeng Zhao
- Center of Interventional Radiology and Vascular Surgery, Department of Radiology, Zhongda Hospital, Medical School, Southeast University, Nanjing, China
- Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education Institutions, Suzhou, China
| | - Ying Jiang
- Department of Neurology, The 962nd Hospital of the PLA Joint Logistic Support Force, Harbin, China
| | - Tong Lu
- Department of Radiology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Yanjuan Wang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Yixin Zhu
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Zhengsheng Zhang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Chunming Xie
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Zan Wang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Qingguo Ren
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
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5
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The overlapping modular organization of human brain functional networks across the adult lifespan. Neuroimage 2022; 253:119125. [PMID: 35331872 DOI: 10.1016/j.neuroimage.2022.119125] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 03/02/2022] [Accepted: 03/19/2022] [Indexed: 01/06/2023] Open
Abstract
Previous studies have demonstrated that the brain functional modular organization, which is a fundamental feature of the human brain, would change along the adult lifespan. However, these studies assumed that each brain region belonged to a single functional module, although there has been convergent evidence supporting the existence of overlap among functional modules in the human brain. To reveal how age affects the overlapping functional modular organization, this study applied an overlapping module detection algorithm that requires no prior knowledge to the resting-state fMRI data of a healthy cohort (N = 570) aged from 18 to 88 years old. A series of measures were derived to delineate the characteristics of the overlapping modular structure and the set of overlapping nodes (brain regions participating in two or more modules) identified from each participant. Age-related regression analyses on these measures found linearly decreasing trends in the overlapping modularity and the modular similarity. The number of overlapping nodes was found increasing with age, but the increment was not even over the brain. In addition, across the adult lifespan and within each age group, the nodal overlapping probability consistently had positive correlations with both functional gradient and flexibility. Further, by correlation and mediation analyses, we showed that the influence of age on memory-related cognitive performance might be explained by the change in the overlapping functional modular organization. Together, our results revealed age-related decreased segregation from the brain functional overlapping modular organization perspective, which could provide new insight into the adult lifespan changes in brain function and the influence of such changes on cognitive performance.
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A hands-on tutorial on network and topological neuroscience. Brain Struct Funct 2022; 227:741-762. [PMID: 35142909 PMCID: PMC8930803 DOI: 10.1007/s00429-021-02435-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 11/23/2021] [Indexed: 02/08/2023]
Abstract
The brain is an extraordinarily complex system that facilitates the optimal integration of information from different regions to execute its functions. With the recent advances in technology, researchers can now collect enormous amounts of data from the brain using neuroimaging at different scales and from numerous modalities. With that comes the need for sophisticated tools for analysis. The field of network neuroscience has been trying to tackle these challenges, and graph theory has been one of its essential branches through the investigation of brain networks. Recently, topological data analysis has gained more attention as an alternative framework by providing a set of metrics that go beyond pairwise connections and offer improved robustness against noise. In this hands-on tutorial, our goal is to provide the computational tools to explore neuroimaging data using these frameworks and to facilitate their accessibility, data visualisation, and comprehension for newcomers to the field. We will start by giving a concise (and by no means complete) overview of the field to introduce the two frameworks and then explain how to compute both well-established and newer metrics on resting-state functional magnetic resonance imaging. We use an open-source language (Python) and provide an accompanying publicly available Jupyter Notebook that uses the 1000 Functional Connectomes Project dataset. Moreover, we would like to highlight one part of our notebook dedicated to the realistic visualisation of high order interactions in brain networks. This pipeline provides three-dimensional (3-D) plots of pairwise and higher-order interactions projected in a brain atlas, a new feature tailor-made for network neuroscience.
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7
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Wang H, Labus JS, Griffin F, Gupta A, Bhatt RR, Sauk JS, Turkiewicz J, Bernstein CN, Kornelsen J, Mayer EA. Functional brain rewiring and altered cortical stability in ulcerative colitis. Mol Psychiatry 2022; 27:1792-1804. [PMID: 35046525 PMCID: PMC9095465 DOI: 10.1038/s41380-021-01421-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 12/04/2021] [Accepted: 12/08/2021] [Indexed: 12/12/2022]
Abstract
Despite recent advances, there is still a major need to better understand the interactions between brain function and chronic gut inflammation and its clinical implications. Alterations in executive function have previously been identified in several chronic inflammatory conditions, including inflammatory bowel diseases. Inflammation-associated brain alterations can be captured by connectome analysis. Here, we used the resting-state fMRI data from 222 participants comprising three groups (ulcerative colitis (UC), irritable bowel syndrome (IBS), and healthy controls (HC), N = 74 each) to investigate the alterations in functional brain wiring and cortical stability in UC compared to the two control groups and identify possible correlations of these alterations with clinical parameters. Globally, UC participants showed increased functional connectivity and decreased modularity compared to IBS and HC groups. Regionally, UC showed decreased eigenvector centrality in the executive control network (UC < IBS < HC) and increased eigenvector centrality in the visual network (UC > IBS > HC). UC also showed increased connectivity in dorsal attention, somatomotor network, and visual networks, and these enhanced subnetwork connectivities were able to distinguish UC participants from HCs and IBS with high accuracy. Dynamic functional connectome analysis revealed that UC showed enhanced cortical stability in the medial prefrontal cortex (mPFC), which correlated with severe depression and anxiety-related measures. None of the observed brain changes were correlated with disease duration. Together, these findings are consistent with compromised functioning of networks involved in executive function and sensory integration in UC.
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Affiliation(s)
- Hao Wang
- grid.19006.3e0000 0000 9632 6718G. Oppenheimer Center for Neurobiology of Stress & Resilience, UCLA Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-7378 USA ,grid.54549.390000 0004 0369 4060Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, 611731 P. R. China
| | - Jennifer S. Labus
- grid.19006.3e0000 0000 9632 6718G. Oppenheimer Center for Neurobiology of Stress & Resilience, UCLA Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-7378 USA
| | - Fiona Griffin
- grid.19006.3e0000 0000 9632 6718G. Oppenheimer Center for Neurobiology of Stress & Resilience, UCLA Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-7378 USA
| | - Arpana Gupta
- grid.19006.3e0000 0000 9632 6718G. Oppenheimer Center for Neurobiology of Stress & Resilience, UCLA Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-7378 USA
| | - Ravi R. Bhatt
- grid.42505.360000 0001 2156 6853Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School Medicine at USC, University of Southern California, 4676 Admiralty Way, Marina Del Rey, CA 90292 USA
| | - Jenny S. Sauk
- grid.19006.3e0000 0000 9632 6718G. Oppenheimer Center for Neurobiology of Stress & Resilience, UCLA Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-7378 USA
| | - Joanna Turkiewicz
- grid.266093.80000 0001 0668 7243University of California, Irvine School of Medicine, Irvine, CA 92697 USA
| | - Charles N. Bernstein
- grid.21613.370000 0004 1936 9609University of Manitoba IBD Clinical and Research Centre, Department of Internal Medicine, Rady Faculty of Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, Canada
| | - Jennifer Kornelsen
- grid.21613.370000 0004 1936 9609University of Manitoba IBD Clinical and Research Centre, Department of Internal Medicine, Rady Faculty of Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, Canada
| | - Emeran A. Mayer
- grid.19006.3e0000 0000 9632 6718G. Oppenheimer Center for Neurobiology of Stress & Resilience, UCLA Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-7378 USA
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8
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Zhang S, Li H, Xu Q, Wang C, Li X, Sun J, Wang Y, Sun T, Wang Q, Zhang C, Wang J, Jia X, Sun X. Regional homogeneity alterations in multi-frequency bands in tension-type headache: a resting-state fMRI study. J Headache Pain 2021; 22:129. [PMID: 34711175 PMCID: PMC8555254 DOI: 10.1186/s10194-021-01341-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 10/11/2021] [Indexed: 01/03/2023] Open
Abstract
OBJECTIVES In this study, we aimed to investigate the spontaneous neural activity in the conventional frequency band (0.01-0.08 Hz) and two sub-frequency bands (slow-4: 0.027-0.073 Hz, and slow-5: 0.01-0.027 Hz) in tension-type headache (TTH) patients with regional homogeneity (ReHo) analyses. METHODS Thirty-eight TTH patients and thirty-eight healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (RS-fMRI) scanning to investigate abnormal spontaneous neural activity using ReHo analysis in conventional frequency band (0.01-0.08 Hz) and two sub-frequency bands (slow-4: 0.027-0.073 Hz and slow-5: 0.01-0.027 Hz). RESULTS In comparison with the HC group, patients with TTH exhibited ReHo increases in the right medial superior frontal gyrus in the conventional frequency band (0.01-0.08 Hz). The between group differences in the slow-5 band (0.01-0.027 Hz) highly resembled the differences in the conventional frequency band (0.01-0.08 Hz); even the voxels with increased ReHo were spatially more extensive, including the right medial superior frontal gyrus and the middle frontal gyrus. In contrast, no region showed significant between-group differences in the slow-4 band (0.027-0.073 Hz). The correlation analyses showed no correlation between the ReHo values in TTH patients and VAS scores, course of disease and number of seizures per month in conventional band (0.01-0.08 Hz), slow-4 band (0.027-0.073 Hz), as well as in slow-5 band (0.01-0.027 Hz). CONCLUSIONS The results showed that the superior frontal gyrus and middle frontal gyrus were involved in the integration and processing of pain signals. In addition, the abnormal spontaneous neural activity in TTH patients was frequency-specific. Namely, slow-5 band (0.01-0.027 Hz) might contain additional useful information in comparison to slow-4 band (0.027-0.073 Hz). This preliminary exploration might provide an objective imaging basis for the understanding of the pathophysiological mechanism of TTH.
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Affiliation(s)
- Shuxian Zhang
- Affiliated Hospital of Weifang Medical University, Weifang, Shandong Province, China
| | - Huayun Li
- College of Teacher Education, Zhejiang Normal University, Jinhua, China
- Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua, China
| | - Qinyan Xu
- Affiliated Hospital of Weifang Medical University, Weifang, Shandong Province, China
| | - Chao Wang
- Affiliated Hospital of Weifang Medical University, Weifang, Shandong Province, China
| | - Xue Li
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Jiawei Sun
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Yaqi Wang
- Weifang Hospital of Traditional Chinese Medicine, Weifang, Shandong Province, China
| | - Tong Sun
- Weifang Hospital of Traditional Chinese Medicine, Weifang, Shandong Province, China
| | - Qianqian Wang
- College of Teacher Education, Zhejiang Normal University, Jinhua, China
| | - Chengcheng Zhang
- Department of Medical Imaging, Weifang Medical University, Weifang, Shandong Province, China
| | - Jili Wang
- Department of Medical Imaging, Weifang Medical University, Weifang, Shandong Province, China
| | - Xize Jia
- Centre for Cognition and Brain disorders, the Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.
| | - Xihe Sun
- Affiliated Hospital of Weifang Medical University, Weifang, Shandong Province, China.
- Department of Medical Imaging, Weifang Medical University, Weifang, Shandong Province, China.
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9
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Ingala S, Tomassen J, Collij LE, Prent N, van 't Ent D, Ten Kate M, Konijnenberg E, Yaqub M, Scheltens P, de Geus EJC, Teunissen CE, Tijms B, Wink AM, Barkhof F, van Berckel BNM, Visser PJ, den Braber A. Amyloid-driven disruption of default mode network connectivity in cognitively healthy individuals. Brain Commun 2021; 3:fcab201. [PMID: 34617016 PMCID: PMC8490784 DOI: 10.1093/braincomms/fcab201] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 04/06/2021] [Accepted: 05/03/2021] [Indexed: 12/03/2022] Open
Abstract
Cortical accumulation of amyloid beta is one of the first events of Alzheimer’s disease pathophysiology, and has been suggested to follow a consistent spatiotemporal ordering, starting in the posterior cingulate cortex, precuneus and medio-orbitofrontal cortex. These regions overlap with those of the default mode network, a brain network also involved in memory functions. Aberrant default mode network functional connectivity and higher network sparsity have been reported in prodromal and clinical Alzheimer’s disease. We investigated the association between amyloid burden and default mode network connectivity in the preclinical stage of Alzheimer’s disease and its association with longitudinal memory decline. We included 173 participants, in which amyloid burden was assessed both in CSF by the amyloid beta 42/40 ratio, capturing the soluble part of amyloid pathology, and in dynamic PET scans calculating the non-displaceable binding potential in early-stage regions. The default mode network was identified with resting-state functional MRI. Then, we calculated functional connectivity in the default mode network, derived from independent component analysis, and eigenvector centrality, a graph measure recursively defining important nodes on the base of their connection with other important nodes. Memory was tested at baseline, 2- and 4-year follow-up. We demonstrated that higher amyloid burden as measured by both CSF amyloid beta 42/40 ratio and non-displaceable binding potential in the posterior cingulate cortex was associated with lower functional connectivity in the default mode network. The association between amyloid burden (CSF and non-displaceable binding potential in the posterior cingulate cortex) and aberrant default mode network connectivity was confirmed at the voxel level with both functional connectivity and eigenvector centrality measures, and it was driven by voxel clusters localized in the precuneus, cingulate, angular and left middle temporal gyri. Moreover, we demonstrated that functional connectivity in the default mode network predicts longitudinal memory decline synergistically with regional amyloid burden, as measured by non-displaceable binding potential in the posterior cingulate cortex. Taken together, these results suggest that early amyloid beta deposition is associated with aberrant default mode network connectivity in cognitively healthy individuals and that default mode network connectivity markers can be used to identify subjects at risk of memory decline.
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Affiliation(s)
- Silvia Ingala
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Jori Tomassen
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Naomi Prent
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands.,Faculty of Behavioral and Movement Sciences, Section Clinical Neuropsychology, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands.,Vesalius, Centre for Neuropsychiatry, GGZ Altrecht, 3447 GM Woerden, The Netherlands
| | - Dennis van 't Ent
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Neuroscience Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Mara Ten Kate
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands.,Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Elles Konijnenberg
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Maqsood Yaqub
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Neuroscience Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- Department of Clinical Chemistry, Neurochemistry Laboratory, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, 1081 HV Amsterdam, The Netherlands
| | - Betty Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Alle Meije Wink
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands.,Institute of Neurology and Healthcare Engineering, University College London, WC1E 6BT London, UK
| | - Bart N M van Berckel
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands
| | - Anouk den Braber
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Location VUmc, 1081 HZ Amsterdam, The Netherlands.,Department of Biological Psychology, Vrije Universiteit Amsterdam, Neuroscience Amsterdam, 1081 HV Amsterdam, The Netherlands
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Ogawa A. Time-varying measures of cerebral network centrality correlate with visual saliency during movie watching. Brain Behav 2021; 11:e2334. [PMID: 34435748 PMCID: PMC8442596 DOI: 10.1002/brb3.2334] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 07/05/2021] [Accepted: 08/07/2021] [Indexed: 12/12/2022] Open
Abstract
The extensive development of graph-theoretic analysis for functional connectivity has revealed the multifaceted characteristics of brain networks. Network centralities identify the principal functional regions, individual differences, and hub structure in brain networks. Neuroimaging studies using movie-watching have investigated brain function under naturalistic stimuli. Visual saliency is one of the promising measures for revealing cognition and emotions driven by naturalistic stimuli. This study investigated whether the visual saliency in movies was associated with network centrality. The study examined eigenvector centrality (EC), which is a measure of a region's influence in the brain network, and the participation coefficient (PC), which reflects the hub structure in the brain, was used for comparison. Static and time-varying EC and PC were analyzed by a parcel-based technique. While EC was correlated with brain activity in parcels in the visual and auditory areas during movie-watching, it was only correlated with parcels in the visual areas in the retinotopy task. In addition, high PC was consistently observed in parcels in the putative hub both during the tasks and the resting-state condition. Time-varying EC in the parietal parcels and time-varying PC in the primary sensory parcels significantly correlated with visual saliency in the movies. These results suggest that time-varying centralities in brain networks are distinctively associated with perceptual processing and subsequent higher processing of visual saliency.
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Affiliation(s)
- Akitoshi Ogawa
- Faculty of Medicine, Juntendo University, Bunkyo-ku, Tokyo, Japan.,Brain Science Institute, Tamagawa University, Machida, Tokyo, Japan
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Huiskamp M, Eijlers AJC, Broeders TAA, Pasteuning J, Dekker I, Uitdehaag BMJ, Barkhof F, Wink AM, Geurts JJG, Hulst HE, Schoonheim MM. Longitudinal Network Changes and Conversion to Cognitive Impairment in Multiple Sclerosis. Neurology 2021; 97:e794-e802. [PMID: 34099528 PMCID: PMC8397585 DOI: 10.1212/wnl.0000000000012341] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 05/17/2021] [Indexed: 11/16/2022] Open
Abstract
OBJECTIVE To characterize functional network changes related to conversion to cognitive impairment in a large sample of patients with multiple sclerosis (MS) over a period of 5 years. METHODS Two hundred twenty-seven patients with MS and 59 healthy controls of the Amsterdam MS cohort underwent neuropsychological testing and resting-state fMRI at 2 time points (time interval 4.9 ± 0.9 years). At both baseline and follow-up, patients were categorized as cognitively preserved (CP; n = 123), mildly impaired (MCI; z < -1.5 on ≥2 cognitive tests, n = 32), or impaired (CI; z < -2 on ≥2 tests, n = 72), and longitudinal conversion between groups was determined. Network function was quantified with eigenvector centrality, a measure of regional network importance, which was computed for individual resting-state networks at both time points. RESULTS Over time, 18.9% of patients converted to a worse phenotype; 22 of 123 patients who were CP (17.9%) converted from CP to MCI, 10 of 123 from CP to CI (8.1%), and 12 of 32 patients with MCI converted to CI (37.5%). At baseline, default-mode network (DMN) centrality was higher in CI individuals compared to controls (p = 0.05). Longitudinally, ventral attention network (VAN) importance increased in CP, driven by stable CP and CP-to-MCI converters (p < 0.05). CONCLUSIONS Of all patients, 19% worsened in their cognitive status over 5 years. Conversion from intact cognition to impairment is related to an initial disturbed functioning of the VAN, then shifting toward DMN dysfunction in CI. Because the VAN normally relays information to the DMN, these results could indicate that in MS normal processes crucial for maintaining overall network stability are progressively disrupted as patients clinically progress.
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Affiliation(s)
- Marijn Huiskamp
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK.
| | - Anand J C Eijlers
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Tommy A A Broeders
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Jasmin Pasteuning
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Iris Dekker
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Bernard M J Uitdehaag
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Frederik Barkhof
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Alle-Meije Wink
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Jeroen J G Geurts
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Hanneke E Hulst
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
| | - Menno M Schoonheim
- From the Department of Anatomy and Neurosciences (M.H., A.J.C.E., T.A.A.B., J.P., J.J.G.G., H.E.H., M.M.S.), Department of Neurology (I.D., B.M.J.U.), and Department of Radiology and Nuclear Medicine (I.D., F.B., A.-M.W.), MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands; and UCL Institutes of Neurology and Healthcare Engineering (F.B.), London, UK
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Dhamala E, Jamison KW, Sabuncu MR, Kuceyeski A. Sex classification using long-range temporal dependence of resting-state functional MRI time series. Hum Brain Mapp 2020; 41:3567-3579. [PMID: 32627300 PMCID: PMC7416025 DOI: 10.1002/hbm.25030] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 04/27/2020] [Indexed: 12/13/2022] Open
Abstract
A thorough understanding of sex differences that exist in the brains of healthy individuals is crucial for the study of neurological illnesses that exhibit phenotypic differences between males and females. Here we evaluate sex differences in regional temporal dependence of resting-state brain activity in 195 adult male-female pairs strictly matched for total grey matter volume from the Human Connectome Project. We find that males have more persistent temporal dependence in regions within temporal, parietal, and occipital cortices. Machine learning algorithms trained on regional temporal dependence measures achieve sex classification accuracies up to 81%. Regions with the strongest feature importance in the sex classification task included cerebellum, amygdala, and frontal and occipital cortices. Secondarily, we show that even after strict matching of total gray matter volume, significant volumetric sex differences persist; males have larger absolute cerebella, hippocampi, parahippocampi, thalami, caudates, and amygdalae while females have larger absolute cingulates, precunei, and frontal and parietal cortices. Sex classification based on regional volume achieves accuracies up to 85%, highlighting the importance of strict volume-matching when studying brain-based sex differences. Differential patterns in regional temporal dependence between the sexes identifies a potential neurobiological substrate or environmental effect underlying sex differences in functional brain activation patterns.
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Affiliation(s)
- Elvisha Dhamala
- Department of RadiologyWeill Cornell MedicineNew YorkNew YorkUSA
- Brain and Mind Research InstituteWeill Cornell MedicineNew YorkNew YorkUSA
| | - Keith W. Jamison
- Department of RadiologyWeill Cornell MedicineNew YorkNew YorkUSA
| | - Mert R. Sabuncu
- School of Electrical and Computer EngineeringCornell UniversityIthacaNew YorkUSA
- Meinig School of Biomedical EngineeringCornell UniversityIthacaNew YorkUSA
| | - Amy Kuceyeski
- Department of RadiologyWeill Cornell MedicineNew YorkNew YorkUSA
- Brain and Mind Research InstituteWeill Cornell MedicineNew YorkNew YorkUSA
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