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Chang B, Mei J, Ni C, Chen P, Jiang Y, Niu C. Oscillation-specific nodal differences in Parkinson's disease patients with anxiety. J Parkinsons Dis 2024:JPD240055. [PMID: 38701162 DOI: 10.3233/jpd-240055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
Background Parkinson's disease (PD) is a common neurodegenerative disorder that is predominantly known for its motor symptoms but is also accompanied by non-motor symptoms, including anxiety. Objective The underlying neurobiological substrates and brain network changes associated with comorbid anxiety in PD require further exploration. Methods An analysis of oscillation-specific nodal properties in patients with and without anxiety was conducted using resting-state functional magnetic resonance imaging (rs-fMRI) and graph theory. We used a band-pass filtering approach to differentiate oscillatory frequency bands for subsequent functional connectivity (FC) and graph analyses. Results The study included 68 non-anxiety PD (naPD) patients, 62 anxiety PD (aPD) patients, and 64 healthy controls (NC). Analyses of nodal betweenness centrality (BC), degree centrality (DC), and efficiency were conducted across multiple frequency bands. The findings indicated no significant differences in BC among naPD, aPD, and NC within the 0.01-0.08 Hz frequency range. However, we observed a specific reduction in BC at narrower frequency ranges in aPD patients, as well as differing patterns of change in DC and efficiency, which are believed to reflect the neurophysiological bases of anxiety symptoms in PD. Conclusions Differential oscillation-specific nodal characteristics have been identified in PD patients with anxiety, suggesting potential dysregulations in brain network dynamics. These findings emphasize the complexity of brain network alterations in anxiety-associated PD and identify oscillatory frequencies as potential biomarkers. The study highlights the importance of considering oscillatory frequency bands in the analysis of brain network changes.
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Affiliation(s)
- Bowen Chang
- Department of Neurosurgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui Province, P. R. China
- Anhui Province Key Laboratory of Brain Function and Brain Disease, Hefei, Anhui Province, P. R. China
| | - Jiaming Mei
- Department of Neurosurgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui Province, P. R. China
- Anhui Province Key Laboratory of Brain Function and Brain Disease, Hefei, Anhui Province, P. R. China
| | - Chen Ni
- Department of Neurosurgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui Province, P. R. China
- Anhui Province Key Laboratory of Brain Function and Brain Disease, Hefei, Anhui Province, P. R. China
| | - Peng Chen
- Department of Neurosurgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui Province, P. R. China
- Anhui Province Key Laboratory of Brain Function and Brain Disease, Hefei, Anhui Province, P. R. China
| | - Yuge Jiang
- Key Laboratory of Xin'an Medicine, Ministry of Education, Anhui Province Key Laboratory of R& D of Chinese Medicine, Anhui University of Chinese Medicine, Hefei, Anhui Province, P. R. China
| | - Chaoshi Niu
- Department of Neurosurgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui Province, P. R. China
- Anhui Province Key Laboratory of Brain Function and Brain Disease, Hefei, Anhui Province, P. R. China
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Ai H, Yang C, Lu M, Ren J, Li Z, Zhang Y. Abnormal white matter structural network topological property in patients with temporal lobe epilepsy. CNS Neurosci Ther 2024; 30:e14414. [PMID: 37622409 PMCID: PMC10805448 DOI: 10.1111/cns.14414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 08/02/2023] [Accepted: 08/04/2023] [Indexed: 08/26/2023] Open
Abstract
BACKGROUND Diffusion tensor imaging (DTI) studies have demonstrated white matter (WM) abnormalities in patients with temporal lobe epilepsy (TLE). However, alterations in the topological properties of the WM structural network in patients with TLE remain unclear. Graph theoretical analysis provides a new perspective for evaluating the connectivity of WM structural networks. METHODS DTI was used to map the structural networks of 18 patients with TLE (10 males and 8 females) and 29 (17 males and 12 females) age- and gender-matched normal controls (NC). Graph theory was used to analyze the whole-brain networks and their topological properties between the two groups. Finally, partial correlation analyses were performed on the weighted network properties and clinical characteristics, namely, duration of epilepsy, verbal intelligence quotient (IQ), and performance IQ. RESULTS Patients with TLE exhibited reduced global efficiency and increased characteristic path length. A total of 31 regions with nodal efficiency alterations were detected in the fractional anisotropy_ weighted network of the patients. Communication hubs, such as the middle temporal gyrus, right inferior temporal gyrus, left calcarine, and right superior parietal gyrus, were also differently distributed in the patients compared with the NC. Several node regions showed close relationships with duration of epilepsy, verbal IQ, and performance IQ. CONCLUSIONS Our results demonstrate the disruption of the WM structural network in TLE patients. This study may contribute to the further understanding of the pathological mechanism of TLE.
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Affiliation(s)
- Haiming Ai
- Faculty of Science and TechnologyBeijing Open UniversityBeijingChina
| | - Chunlan Yang
- College of Life Science and BioengineeringBeijing University of TechnologyBeijingChina
| | - Min Lu
- College of Life Science and BioengineeringBeijing University of TechnologyBeijingChina
| | - Jiechuan Ren
- Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Zhimei Li
- Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Yining Zhang
- Department of EquipmentBaoding first Central HospitalBaodingChina
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Pitetzis D, Frantzidis C, Psoma E, Ketseridou SN, Deretzi G, Kalogera-Fountzila A, Bamidis PD, Spilioti M. The Pre-Interictal Network State in Idiopathic Generalized Epilepsies. Brain Sci 2023; 13:1671. [PMID: 38137119 PMCID: PMC10741409 DOI: 10.3390/brainsci13121671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 11/24/2023] [Accepted: 11/30/2023] [Indexed: 12/24/2023] Open
Abstract
Generalized spike wave discharges (GSWDs) are the typical electroencephalographic findings of Idiopathic Generalized Epilepsies (IGEs). These discharges are either interictal or ictal and recent evidence suggests differences in their pathogenesis. The aim of this study is to investigate, through functional connectivity analysis, the pre-interictal network state in IGEs, which precedes the formation of the interictal GSWDs. A high-density electroencephalogram (HD-EEG) was recorded in twenty-one patients with IGEs, and cortical connectivity was analyzed based on lagged coherence and individual anatomy. Graph theory analysis was used to estimate network features, assessed using the characteristic path length and clustering coefficient. The functional connectivity analysis identified two distinct networks during the pre-interictal state. These networks exhibited reversed connectivity attributes, reflecting synchronized activity at 3-4 Hz (delta2), and desynchronized activity at 8-10.5 Hz (alpha1). The delta2 network exhibited a statistically significant (p < 0.001) decrease in characteristic path length and an increase in the mean clustering coefficient. In contrast, the alpha1 network showed opposite trends in these features. The nodes influencing this state were primarily localized in the default mode network (DMN), dorsal attention network (DAN), visual network (VIS), and thalami. In conclusion, the coupling of two networks defined the pre-interictal state in IGEs. This state might be considered as a favorable condition for the generation of interictal GSWDs.
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Affiliation(s)
- Dimitrios Pitetzis
- Department of Neurology, Papageorgiou General Hospital, 56403 Thessaloniki, Greece;
- Lab of Medical Physics and Digital Innovation, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (C.F.); (S.N.K.); (P.D.B.)
| | - Christos Frantzidis
- Lab of Medical Physics and Digital Innovation, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (C.F.); (S.N.K.); (P.D.B.)
- School of Computer Science, University of Lincoln, Lincoln LN6 7TS, UK
| | - Elizabeth Psoma
- Department of Radiology, AHEPA General Hospital, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece; (E.P.); (A.K.-F.)
| | - Smaranda Nafsika Ketseridou
- Lab of Medical Physics and Digital Innovation, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (C.F.); (S.N.K.); (P.D.B.)
| | - Georgia Deretzi
- Department of Neurology, Papageorgiou General Hospital, 56403 Thessaloniki, Greece;
| | - Anna Kalogera-Fountzila
- Department of Radiology, AHEPA General Hospital, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece; (E.P.); (A.K.-F.)
| | - Panagiotis D. Bamidis
- Lab of Medical Physics and Digital Innovation, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece; (C.F.); (S.N.K.); (P.D.B.)
| | - Martha Spilioti
- 1st Department of Neurology, AHEPA General Hospital, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece;
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Qi L, Wang GL, Tian ZH, Guan S, Yang SY, Yang YL, Liu LQ, Lin YZ. Prefrontal cortical hemodynamics and functional network organization during Tai Chi standing meditation: an fNIRS study. Front Hum Neurosci 2023; 17:1294312. [PMID: 37954940 PMCID: PMC10634523 DOI: 10.3389/fnhum.2023.1294312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 10/11/2023] [Indexed: 11/14/2023] Open
Abstract
Introduction Tai Chi standing meditation (Zhan Zhuang, also called pile standing) is characterized by meditation, deep breathing, and mental focus based on theories of traditional Chinese medicine. The purpose of the present study was to explore prefrontal cortical hemodynamics and the functional network organization associated with Tai Chi standing meditation by using functional near-infrared spectroscopy (fNIRS). Methods Twenty-four channel fNIRS signals were recorded from 24 male Tai Chi Quan practitioners (54.71 ± 8.04 years) while standing at rest and standing during Tai Chi meditation. The general linear model and the SPM method were used to analyze the fNIRS signals. Pearson correlation was calculated to determine the functional connectivity between the prefrontal cortical sub-regions. The small world properties of the FC networks were then further analyzed based on graph theory. Results During Tai Chi standing meditation, significantly higher concentrations of oxygenated hemoglobin were observed in bilateral dorsolateral prefrontal cortex (DLPFC), ventrolateral prefrontal cortex (VLPFC), frontal eye field (FEF), and pre-motor cortex (PMC) compared with the values measured during standing rest (p < 0.05). Simultaneously, significant decreases in deoxygenated hemoglobin concentration were observed in left VLPFC, right PMC and DLPFC during Tai Chi standing meditation than during standing rest (p < 0.05). Functional connectivity between the left and right PFC was also significantly stronger during the Tai Chi standing meditation (p < 0.05). The functional brain networks exhibited small-world architecture, and more network hubs located in DLPFC and VLPFC were identified during Tai Chi standing meditation than during standing rest. Discussion These findings suggest that Tai Chi standing meditation introduces significant changes in the cortical blood flow and the brain functional network organization.
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Affiliation(s)
- Liping Qi
- Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China
| | - Guo-Liang Wang
- Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China
| | - Zhi-Hao Tian
- Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China
| | - Shuo Guan
- Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China
| | - Shu-Ye Yang
- School of Physical Education and Health, Dalian University of Technology, Dalian, China
| | - Yu-Long Yang
- School of Physical Education and Health, Dalian University of Technology, Dalian, China
| | - Li-Qing Liu
- School of Physical Education and Health, Dalian University of Technology, Dalian, China
| | - Yong-Zhong Lin
- The Second Affiliated Hospital of Dalian Medical University, Dalian, China
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刘 欢, 饶 阳, 孙 传, 王 洋, 齐 顺, 李 想, 田 萌, 禹 汛, 穆 允. [Changes of brain network in patients with insomnia following radiotherapy for cervical cancer and their correlation with IT-TMS treatment efficacy: a graph-theory analysis]. Nan Fang Yi Ke Da Xue Xue Bao 2023; 43:1629-1635. [PMID: 37814879 PMCID: PMC10563105 DOI: 10.12122/j.issn.1673-4254.2023.09.22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Indexed: 10/11/2023]
Abstract
OBJECTIVE To analyze the changes of brain small-world and node function network properties in patients with insomnia following radiotherapy for cervical cancer based on graph theory analysis and explore the correlation between functional networks and the clinical efficacy of individual-target transcranial magnetic stimulation (IT-TMS) for treatment of insomnia. METHODS The resting state functional magnetic resonance imaging (rs-fMRI) data were collected from 30 patients with insomnia following radiotherapy for cervical cancer and 30 matched healthy individuals. All the patients received accelerated intelligent neuromodulation TMS therapy. Using graph theory analysis and GRETNA software, the functional connectivity matrices were constructed and the attribute features were extracted. The scores on the Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), Self-Rating Anxiety Scale (SAS), and Self-Rating Depression Scale (SDS) of the participants were collected before and after IT-TMS, and the correlation between improvement in insomnia and the functional network was investigated. RESULTS The two groups matched for age, gender, and education level (P>0.05) showed significant differences in PSQI, ISI, SAS and SDS scores (P<0.05). Both groups showed attributes of the small-world network. Compared with the healthy individuals, the patients showed significantly decreased σ, EI, Cp and Lp (P<0.05) and increased Eg (P<0.05) at baseline, which, along with insomnia symptoms, were all improved after IT-TMS treatment. The patients showed reduced functional connections of the node network at follow-up compared with the baseline, and the low functional connectivity between the right insula and left superior frontal gyrus was correlated with the improvement of ISI scores. CONCLUSION The patients with insomnia following radiotherapy for cervical cancer have impaired information integration ability of the brain network, IT-TMS can significantly improve insomnia symptoms by reducing the hyperconnectivity between the default mode network and the salience network.
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Affiliation(s)
- 欢 刘
- 西安交通大学数学与统计学院,陕西 西安 710049School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049, China
| | - 阳 饶
- 陕西脑控脑科学研发中心,陕西 西安 710075Shaanxi Brain Modulation and Scientific Research Center, Xi'an 710075, China
| | - 传铸 孙
- 陕西脑控脑科学研发中心,陕西 西安 710075Shaanxi Brain Modulation and Scientific Research Center, Xi'an 710075, China
| | - 洋涛 王
- 陕西脑控脑科学研发中心,陕西 西安 710075Shaanxi Brain Modulation and Scientific Research Center, Xi'an 710075, China
| | - 顺 齐
- 陕西脑控脑科学研发中心,陕西 西安 710075Shaanxi Brain Modulation and Scientific Research Center, Xi'an 710075, China
- 西安交通大学类脑智能研究中心,陕西 西安 710049Research Center for Brain-Inspired Intelligence, Xi'an Jiaotong University, Xi'an 710049, China
| | - 想 李
- 西安交通大学生命科学与技术学院//健康与康复科学研究所//生物医学信息工程教育部重点实验室,陕西 西安 710049School of Life Science and Technology//Institute of Health and Rehabilitation Science//The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Xi'an Jiaotong University, Xi'an 710049, China
| | - 萌 田
- 陕西省中医医院米氏内科,陕西 西安 710003Mi Shi Internal Medicine, Shaanxi Academy of Traditional Chinese Medicine, Xi'an 710003, China
| | - 汛 禹
- 陕西脑控脑科学研发中心,陕西 西安 710075Shaanxi Brain Modulation and Scientific Research Center, Xi'an 710075, China
| | - 允凤 穆
- 陕西省肿瘤医院妇瘤病院,陕西 西安 710065Department of Gynecological Oncology, Shaanxi Provincial Cancer Hospital, Xi'an 710065, China
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Germany E, Teixeira I, Danthine V, Santalucia R, Cakiroglu I, Torres A, Verleysen M, Delbeke J, Nonclercq A, Tahry RE. Functional brain connectivity indexes derived from low-density EEG of pre-implanted patients as VNS outcome predictors. J Neural Eng 2023; 20:046039. [PMID: 37595607 DOI: 10.1088/1741-2552/acf1cd] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 08/18/2023] [Indexed: 08/20/2023]
Abstract
Objective. In 1/3 of patients, anti-seizure medications may be insufficient, and resective surgery may be offered whenever the seizure onset is localized and situated in a non-eloquent brain region. When surgery is not feasible or fails, vagus nerve stimulation (VNS) therapy can be used as an add-on treatment to reduce seizure frequency and/or severity. However, screening tools or methods for predicting patient response to VNS and avoiding unnecessary implantation are unavailable, and confident biomarkers of clinical efficacy are unclear.Approach. To predict the response of patients to VNS, functional brain connectivity measures in combination with graph measures have been primarily used with respect to imaging techniques such as functional magnetic resonance imaging, but connectivity graph-based analysis based on electrophysiological signals such as electroencephalogram, have been barely explored. Although the study of the influence of VNS on functional connectivity is not new, this work is distinguished by using preimplantation low-density EEG data to analyze discriminative measures between responders and non-responder patients using functional connectivity and graph theory metrics.Main results. By calculating five functional brain connectivity indexes per frequency band upon partial directed coherence and direct transform function connectivity matrices in a population of 37 refractory epilepsy patients, we found significant differences (p< 0.05) between the global efficiency, average clustering coefficient, and modularity of responders and non-responders using the Mann-Whitney U test with Benjamini-Hochberg correction procedure and use of a false discovery rate of 5%.Significance. Our results indicate that these measures may potentially be used as biomarkers to predict responsiveness to VNS therapy.
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Affiliation(s)
- Enrique Germany
- IoNS, Universite Catholique de Louvain, Brussels, Belgium
- WELBIO Department, WEL Research Institute, Wavre, Belgium
| | - Igor Teixeira
- IoNS, Universite Catholique de Louvain, Brussels, Belgium
| | | | | | - Inci Cakiroglu
- IoNS, Universite Catholique de Louvain, Brussels, Belgium
| | - Andres Torres
- IoNS, Universite Catholique de Louvain, Brussels, Belgium
| | | | - Jean Delbeke
- IoNS, Universite Catholique de Louvain, Brussels, Belgium
| | - Antoine Nonclercq
- Bio-Electro-and Mechanical Systems (BEAMS), Université Libre de Bruxelles, Brussels, Belgium
| | - Riëm El Tahry
- IoNS, Universite Catholique de Louvain, Brussels, Belgium
- WELBIO Department, WEL Research Institute, Wavre, Belgium
- Cliniques Universitaires Saint-Luc, Brussels, Belgium
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Ding H, Wang Z, Tang Y, Wang T, Qi M, Dou W, Qian L, Gao Y, Zhong Q, Yang X, Tian H, Zhang L, Zhu Y. Topological properties of individual gray matter morphological networks in identifying the preclinical stages of Alzheimer's disease: a preliminary study. Quant Imaging Med Surg 2023; 13:5258-5270. [PMID: 37581056 PMCID: PMC10423385 DOI: 10.21037/qims-22-1373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 06/08/2023] [Indexed: 08/16/2023]
Abstract
Background Subjective cognitive decline (SCD) and mild cognitive impairment (MCI) are preclinical stages of Alzheimer's disease (AD). Individual biomarkers are essential for evaluating altered neurological outcomes at both SCD and MCI stages for early diagnosis and intervention of AD. In this study, we aimed to investigate the relationships between topological properties of the individual brain morphological network and clinical cognitive performances among healthy controls (HCs) and patients with SCD or MCI. Methods The topological measurements of individual morphological networks were analyzed using graph theory, and inter-group differences of standard graph topology were correlated and regressed to scores of clinical cognitive functions. Results Compared with HCs, the topology of the individual morphological networks in SCD and MCI patients was significantly altered. At the global level, altered topology was characterized by lower global efficiency, shorter characteristics path length, and normalized characteristics path length [all P<0.05, false discovery rate (FDR) corrected]. In addition, at the regional level, SCD and MCI patients exhibited abnormal degree centrality in the caudate nucleus and nodal efficiency in the caudate nucleus, right insula, lenticular nucleus, and putamen (all P<0.05, FDR corrected). Conclusions The topological features of individual gray matter morphological networks may serve as biomarkers to improve disease prognosis and intervention in the early stages of AD, namely SCD and MCI. Moreover, these findings may further elucidate the relationships between brain morphological alterations and cognitive dysfunctions in SCD and MCI.
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Affiliation(s)
- Hongyuan Ding
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Zhihao Wang
- School of Biological Science & Medical Engineering, Southeast University, Nanjing, China
| | - Yin Tang
- Department of Medical Imaging, Jingjiang People’s Hospital, Jingjiang, China
| | - Tong Wang
- Rehabilitation Medicine Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Ming Qi
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | | | - Long Qian
- MR Research, GE Healthcare, Beijing, China
| | - Yaxin Gao
- Department of Rehabilitation, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
- Gusu School, Nanjing Medical University, Suzhou, China
| | - Qian Zhong
- Department of Rehabilitation, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China
| | - Xi Yang
- School of Rehabilitation Medicine, Nanjing Medical University, Nanjing, China
| | - Huifang Tian
- School of Rehabilitation Medicine, Nanjing Medical University, Nanjing, China
| | - Ling Zhang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yi Zhu
- Rehabilitation Medicine Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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Al-Ezzi A, Kamel N, Al-Shargabi AA, Al-Shargie F, Al-Shargabi A, Yahya N, Al-Hiyali MI. Corrigendum: Machine learning for the detection of social anxiety disorder using effective connectivity and graph theory measures. Front Psychiatry 2023; 14:1257713. [PMID: 37555003 PMCID: PMC10406441 DOI: 10.3389/fpsyt.2023.1257713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 07/13/2023] [Indexed: 08/10/2023] Open
Abstract
[This corrects the article DOI: 10.3389/fpsyt.2023.1155812.].
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Affiliation(s)
- Abdulhakim Al-Ezzi
- Centre for Intelligent Signal & Imaging Research (CISIR), Electrical and Electronic Engineering Department, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Perak, Malaysia
| | - Nidal Kamel
- College of Engineering and Computer Science, VinUniversity, Hanoi, Vietnam
| | - Amal A. Al-Shargabi
- Department of Information Technology, College of Computer, Qassim University, Buraydah, Saudi Arabia
| | - Fares Al-Shargie
- Faculty of Engineering, Abu Dhabi University, Abu Dhabi, United Arab Emirates
| | - Alaa Al-Shargabi
- Department of Information Technology, Universiti Teknlogi Malaysia, Skudai, Malaysia
| | - Norashikin Yahya
- Centre for Intelligent Signal & Imaging Research (CISIR), Electrical and Electronic Engineering Department, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Perak, Malaysia
| | - Mohammed Isam Al-Hiyali
- Centre for Intelligent Signal & Imaging Research (CISIR), Electrical and Electronic Engineering Department, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Perak, Malaysia
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9
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Zhang S, Zhao F, Yang X, Tan Q, Li S, Shao H, Su X, Gong Q, Yue Q. Multiparametric mapping of white matter reorganizations in patients with frontal glioma-related epilepsy. CNS Neurosci Ther 2023. [PMID: 37381706 DOI: 10.1111/cns.14322] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Revised: 05/25/2023] [Accepted: 06/10/2023] [Indexed: 06/30/2023] Open
Abstract
AIMS Epilepsy is a common symptom in diffuse lower-grade glioma (DLGG). The specific role of white matter (WM) alteration in patients with glioma-related epilepsy (GRE) is largely unknown. This study aims to investigate the reorganization of WM tracts and changes in structural networks related to GRE. METHODS Diffusion-weighted images were collected from 70 patients with left frontal DLGG (GRE = 33, non-GRE = 37) and 41 healthy controls (HC). Tractometry with TractSeg was applied to segment tracts and quantify fractional anisotropy (FA) along each tract. Structural network was constructed using constrained spherical deconvolution and probabilistic tractography. FA and network properties were compared among three groups. RESULTS Compared with HC, both GRE and non-GRE showed decreased FA in contralateral inferior fronto-occipital fasciculus, superior longitudinal fasciculus II and arcuate fasciculus, increased nodal efficiency in contralateral nodes of frontal-parietal and limbic networks, whereas decreased degree centrality and betweenness centrality in nodes of dorsal temporal lobe and rostral middle frontal gyrus (rMFG). Additionally, when compared GRE with non-GRE, increased FA in contralateral corticospinal tract (CST) and lower betweenness centrality in paracentral lobule (PCL) in GRE (all p < 0.05 after Bonferroni correction). CONCLUSION This study indicates that patients with left frontal DLGG exhibit complex WM reorganization, and the altered regions mainly concentrated in the language, frontal-parietal and limbic networks. Moreover, the preserved integrity in contralateral CST and server decreased nodal betweenness in PCL may be potential neuroimaging markers underlying the occurrence of presurgical seizures of GRE.
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Affiliation(s)
- Simin Zhang
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Fei Zhao
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Xibiao Yang
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Huaxi Glioma Center, West China Hospital of Sichuan University, Chengdu, China
| | - Qiaoyue Tan
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China
- Division of Radiation Physics, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital of Sichuan University, Chengdu, China
| | - Shuang Li
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Huaxi Glioma Center, West China Hospital of Sichuan University, Chengdu, China
| | - Hanbin Shao
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Huaxi Glioma Center, West China Hospital of Sichuan University, Chengdu, China
| | - Xiaorui Su
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Huaxi Glioma Center, West China Hospital of Sichuan University, Chengdu, China
| | - Qiyong Gong
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China
- Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China
| | - Qiang Yue
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
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10
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Wang H, Wen H, Li J, Chen Q, Li S, Wang Z. Disrupted topological organization of white matter structural networks in high myopia patients revealed by diffusion kurtosis imaging and tractography. Front Neurosci 2023; 17:1158928. [PMID: 37425009 PMCID: PMC10324656 DOI: 10.3389/fnins.2023.1158928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Accepted: 06/06/2023] [Indexed: 07/11/2023] Open
Abstract
Introduction High myopia (HM) is a public health issue that can lead to severe visual impairment. Previous studies have exhibited widespread white matter (WM) integrity damage in HM patients. However, how these WM damages are topologically related, and the network-level structural disruptions underlying HM has not been fully defined. We aimed to assess the alterations of brain WM structural networks in HM patients using diffusion kurtosis imaging (DKI) and tractography in the present study. Methods Individual whole-brain and ROI-level WM networks were constructed using DKI tractography in 30 HM patients and 33 healthy controls. Graph theory analysis was then applied to explore the altered global and regional network topological properties. Pearson correlations between regional properties and disease duration in the HM group were also assessed. Results For global topology, although both groups showed a small-world network organization, HM patients exhibited significant decreased local efficiency and clustering coefficient compared with controls. For regional topology, HM patients and controls showed highly similar hub distributions, except for three additional hub regions in HM patients including left insula, anterior cingulate and paracingulate gyri (ACG), and median cingulate and paracingulate gyri (DCG). In addition, HM patients showed significantly altered nodal betweenness centrality (BC) mainly in the bilateral inferior occipital gyrus (IOG), left superior occipital gyrus (SOG), caudate nucleus, rolandic operculum and right putamen, pallidum, and gyrus rectus compared with controls. Intriguingly, the nodal BC of left IOG was negatively correlated with disease duration in HM patients. Discussion Our findings suggest that HM exhibited alterations in WM structural networks as indicated by decreased local specialization. This study may advance the current understanding of the pathophysiological mechanisms underlying HM.
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Affiliation(s)
- Huihui Wang
- Department of Radiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Hongwei Wen
- Key Laboratory of Cognition and Personality (Ministry of Education), Faculty of Psychology, Southwest University, Chongqing, China
| | - Jing Li
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Qian Chen
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Shanshan Li
- Department of Ophthalmology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Zhenchang Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
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11
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Al-Ezzi A, Kamel N, Al-Shargabi AA, Al-Shargie F, Al-Shargabi A, Yahya N, Al-Hiyali MI. Machine learning for the detection of social anxiety disorder using effective connectivity and graph theory measures. Front Psychiatry 2023; 14:1155812. [PMID: 37255678 PMCID: PMC10226190 DOI: 10.3389/fpsyt.2023.1155812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 04/17/2023] [Indexed: 06/01/2023] Open
Abstract
Introduction The early diagnosis and classification of social anxiety disorder (SAD) are crucial clinical support tasks for medical practitioners in designing patient treatment programs to better supervise the progression and development of SAD. This paper proposes an effective method to classify the severity of SAD into different grading (severe, moderate, mild, and control) by using the patterns of brain information flow with their corresponding graphical networks. Methods We quantified the directed information flow using partial directed coherence (PDC) and the topological networks by graph theory measures at four frequency bands (delta, theta, alpha, and beta). The PDC assesses the causal interactions between neuronal units of the brain network. Besides, the graph theory of the complex network identifies the topological structure of the network. Resting-state electroencephalogram (EEG) data were recorded for 66 patients with different severities of SAD (22 severe, 22 moderate, and 22 mild) and 22 demographically matched healthy controls (HC). Results PDC results have found significant differences between SAD groups and HCs in theta and alpha frequency bands (p < 0.05). Severe and moderate SAD groups have shown greater enhanced information flow than mild and HC groups in all frequency bands. Furthermore, the PDC and graph theory features have been used to discriminate three classes of SAD from HCs using several machine learning classifiers. In comparison to the features obtained by PDC, graph theory network features combined with PDC have achieved maximum classification performance with accuracy (92.78%), sensitivity (95.25%), and specificity (94.12%) using Support Vector Machine (SVM). Discussion Based on the results, it can be concluded that the combination of graph theory features and PDC values may be considered an effective tool for SAD identification. Our outcomes may provide new insights into developing biomarkers for SAD diagnosis based on topological brain networks and machine learning algorithms.
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Affiliation(s)
- Abdulhakim Al-Ezzi
- Centre for Intelligent Signal & Imaging Research (CISIR), Electrical and Electronic Engineering Department, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Perak, Malaysia
| | - Nidal Kamel
- College of Engineering and Computer Science, VinUniversity, Hanoi, Vietnam
| | - Amal A. Al-Shargabi
- Department of Information Technology, College of Computer, Qassim University, Buraydah, Saudi Arabia
| | - Fares Al-Shargie
- Faculty of Engineering, Abu Dhabi University, Abu Dhabi, United Arab Emirates
| | - Alaa Al-Shargabi
- Department of Information Technology, Universiti Teknlogi Malaysia, Skudai, Malaysia
| | - Norashikin Yahya
- Centre for Intelligent Signal & Imaging Research (CISIR), Electrical and Electronic Engineering Department, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Perak, Malaysia
| | - Mohammed Isam Al-Hiyali
- Centre for Intelligent Signal & Imaging Research (CISIR), Electrical and Electronic Engineering Department, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Perak, Malaysia
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12
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Lan Z, Zhu LL, Wu YK, Yang JJ, Li JT, Zeng YW, Li K, Kong QM, Su YA, Si T. Aberrant modular segregation of brain networks in female patients with bulimia nervosa. Int J Eat Disord 2023. [PMID: 36951235 DOI: 10.1002/eat.23939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 03/12/2023] [Accepted: 03/13/2023] [Indexed: 03/24/2023]
Abstract
OBJECTIVE Bulimia nervosa (BN) is an eating disorder associated with the dysfunction of intrinsic brain networks. However, whether the network disruptions in BN patients manifest as dysconnectivity or imbalances of network modular segregation remains unclear. METHOD We collected data from 41 women with BN and 41 matched healthy control (HC) women. We performed graph theory analysis based on resting-state functional magnetic resonance imaging (RS-fMRI) data; then, we computed the participation coefficient (PC) among brain modules to characterize the modular segregation for the BN and HC groups. The number of intra- and inter-modular connections was calculated to explain the PC changes. Additionally, we examined the potential associations of the measures mentioned above with clinical variables within the BN group. RESULTS Compared with the HC group, the BN group showed significantly decreased PC in the fronto-parietal network (FPN), cingulo-opercular network (CON), and cerebellum (Cere). Additionally, the number of intra-modular connections of the default mode network (DMN) and the number of the inter-modular connections between the DMN and CON, FPN and Cere, and CON and Cere in the BN group were lower than those in the HC group. The nodal level analysis showed that the BN group had a decreased PC of the anterior prefrontal cortex (aPFC), dorsal frontal cortex (dFC), inferior parietal lobule (IPL), thalamus, and angular gyrus. Further, these metrics were significantly correlated with clinical variables in the BN group. DISCUSSION These findings may provide novel insights to capture atypical topologies associated with pathophysiology mechanisms and clinical symptoms underlying BN.
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Affiliation(s)
- Zhihui Lan
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Lin-Lin Zhu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yan-Kun Wu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Jing-Jing Yang
- School of Mental Health, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Ji-Tao Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Ya-Wei Zeng
- Department of Radiology, PLA Strategic support Force Characteristic Medical Center, Beijing, China
| | - Ke Li
- Department of Radiology, PLA Strategic support Force Characteristic Medical Center, Beijing, China
| | - Qing-Mei Kong
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Yun-Ai Su
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Tianmei Si
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
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Li Z, Hou X, Lu Y, Zhao H, Wang M, Xu B, Shi Q, Gui Q, Wu G, Shen M, Zhu W, Xu Q, Dong X, Cheng Q, Zhang J, Feng H. Study of brain network alternations in non-lesional epilepsy patients by BOLD-fMRI. Front Neurosci 2023; 16:1031163. [PMID: 36741055 PMCID: PMC9889547 DOI: 10.3389/fnins.2022.1031163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 12/30/2022] [Indexed: 01/20/2023] Open
Abstract
Objective To investigate the changes of brain network in epilepsy patients without intracranial lesions under resting conditions. Methods Twenty-six non-lesional epileptic patients and 42 normal controls were enrolled for BOLD-fMRI examination. The differences in brain network topological characteristics and functional network connectivity between the epilepsy group and the healthy controls were compared using graph theory analysis and independent component analysis. Results The area under the curve for local efficiency was significantly lower in the epilepsy patients compared with healthy controls, while there were no differences in global indicators. Patients with epilepsy had higher functional connectivity in 4 connected components than healthy controls (orbital superior frontal gyrus and medial superior frontal gyrus, medial superior frontal gyrus and angular gyrus, superior parietal gyrus and paracentral lobule, lingual gyrus, and thalamus). In addition, functional connectivity was enhanced in the default mode network, frontoparietal network, dorsal attention network, sensorimotor network, and auditory network in the epilepsy group. Conclusion The topological characteristics and functional connectivity of brain networks are changed in in non-lesional epilepsy patients. Abnormal functional connectivity may suggest reduced brain efficiency in epilepsy patients and also may be a compensatory response to brain function early at earlier stages of the disease.
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Affiliation(s)
- Zhisen Li
- Department of Radiology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Xiaoxia Hou
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Yanli Lu
- Department of Radiology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Huimin Zhao
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Meixia Wang
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Bo Xu
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Qianru Shi
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Qian Gui
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Guanhui Wu
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Mingqiang Shen
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Wei Zhu
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Qinrong Xu
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Xiaofeng Dong
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Qingzhang Cheng
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Jibin Zhang
- Department of Radiology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Hongxuan Feng
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China,*Correspondence: Hongxuan Feng,
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14
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Guo Y, Liu S, Yan F, Yin N, Ni J, Li C, Pan X, Ma R, Wu J, Li S, Li X. Associations between disrupted functional brain network topology and cognitive impairment in patients with rectal cancer during chemotherapy. Front Oncol 2022; 12:927771. [PMID: 36505777 PMCID: PMC9731768 DOI: 10.3389/fonc.2022.927771] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 11/10/2022] [Indexed: 11/25/2022] Open
Abstract
Introduction Cognitive impairment has been identified in patients with non-central nervous system cancer received chemotherapy. Chemotherapy-induced changes in the brain are considered as the possible causes of the cognitive deficits of patients. This study aimed to explore chemotherapy-related functional brain changes and cognitive impairment in rectal cancer (RC) patients who had just finished chemotherapy treatment. Methods In this study, RC patients after chemotherapy (on the day patients received the last dose of chemotherapy) (n=30) and matched healthy controls (HCs) (n=30) underwent cognitive assessments, structural magnetic resonance imaging (MRI) and resting-state functional MRI. The functional brain networks were constructed by thresholding the partial correlation matrices of 90 brain regions in the Anatomical Automatic Labeling template and the topologic properties were evaluated by graph theory analysis. Moreover, correlations between altered topological measures and scores of cognitive scales were explored in the patient group. Results Compared with HCs, RC patients had lower scores of cognitive scales. The functional brain network had preserved small-world topological features but with a tendency towards higher path length in the whole network. In addition, patients had decreased nodal global efficiency (Eglo(i)) in the left superior frontal gyrus (dorsolateral), superior frontal gyrus (orbital part), inferior frontal gyrus (opercular part), inferior frontal gyrus (triangular part) and right inferior frontal gyrus (triangular part). Moreover, values of Eglo(i) in the superior and inferior frontal gyrus were positively associated with cognitive function in the patient group. Conclusion These results suggested that cognitive impairment was associated with disruptions of the topological organization in functional brain networks of RC patients who had just finished chemotherapy, which provided new insights into the pathophysiology underlying acute effects of chemotherapy on cognitive function.
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Affiliation(s)
- Yesong Guo
- Department of Radiotherapy, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Siwen Liu
- Research Center for Clinical Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Fei Yan
- Department of Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Na Yin
- Department of Radiology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Jie Ni
- Department of Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Chenchen Li
- Department of Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Xuan Pan
- Department of Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Rong Ma
- Research Center for Clinical Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Jianzhong Wu
- Research Center for Clinical Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Shengwei Li
- Department of Anorectal, Yangzhou Traditional Chinese Medicine Hospital Affiliated to Nanjing University of Chinese Medicine, Yangzhou, China,*Correspondence: Xiaoyou Li, ; Shengwei Li,
| | - Xiaoyou Li
- Department of Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China,*Correspondence: Xiaoyou Li, ; Shengwei Li,
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Mohammadian F, Zare Sadeghi A, Noroozian M, Malekian V, Abbasi Sisara M, Hashemi H, Mobarak Salari H, Valizadeh G, Samadi F, Sodaei F, Saligheh Rad H. Quantitative Assessment of Resting-State Functional Connectivity MRI to Differentiate Amnestic Mild Cognitive Impairment, Late-Onset Alzheimer's Disease From Normal Subjects. J Magn Reson Imaging 2022; 57:1702-1712. [PMID: 36226735 DOI: 10.1002/jmri.28469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 09/25/2022] [Accepted: 09/27/2022] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Alzheimer disease (AD) is a neurological disorder with brain network dysfunction. Investigation of the brain network functional connectivity (FC) alterations using resting-state functional MRI (rs-fMRI) can provide valuable information about the brain network pattern in early AD diagnosis. PURPOSE To quantitatively assess FC patterns of resting-state brain networks and graph theory metrics (GTMs) to identify potential features for differentiation of amnestic mild cognitive impairment (aMCI) and late-onset AD from normal. STUDY TYPE Prospective. SUBJECTS A total of 14 normal, 16 aMCI, and 13 late-onset AD. FIELD STRENGTH/SEQUENCE A 3.0 T; rs-fMRI: single-shot 2D-EPI and T1-weighted structure: MPRAGE. ASSESSMENT By applying bivariate correlation coefficient and Fisher transformation on the time series of predefined ROIs' pairs, correlation coefficient matrixes and ROI-to-ROI connectivity (RRC) were extracted. By thresholding the RRC matrix (with a threshold of 0.15), a graph adjacency matrix was created to compute GTMs. STATISTICAL TESTS Region of interest (ROI)-based analysis: parametric multivariable statistical analysis (PMSA) with a false discovery rate using (FDR)-corrected P < 0.05 cluster-level threshold together with posthoc uncorrected P < 0.05 connection-level threshold. Graph-theory analysis (GTA): P-FDR-corrected < 0.05. One-way ANOVA and Chi-square tests were used to compare clinical characteristics. RESULTS PMSA differentiated AD from normal, with a significant decrease in FC of default mode, salience, dorsal attention, frontoparietal, language, visual, and cerebellar networks. Furthermore, significant increase in overall FC of visual and language networks was observed in aMCI compared to normal. GTA revealed a significant decrease in global-efficiency (28.05 < 45), local-efficiency (22.98 < 24.05), and betweenness-centrality (14.60 < 17.39) for AD against normal. Moreover, a significant increase in local-efficiency (33.46 > 24.05) and clustering-coefficient (25 > 20.18) were found in aMCI compared to normal. DATA CONCLUSION This study demonstrated resting-state FC potential as an indicator to differentiate AD, aMCI, and normal. GTA revealed brain integration and breakdown by providing concise and comprehensible statistics. EVIDENCE LEVEL 1 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Fatemeh Mohammadian
- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran.,Quantitative Medical Imaging/Spectroscopy Group, Tehran University of Medical Science, Tehran, Iran
| | - Arash Zare Sadeghi
- Medical Physics Department, Iran University of Medical Sciences, Tehran, Iran
| | - Maryam Noroozian
- Department of Psychiatry, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Vahid Malekian
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Majid Abbasi Sisara
- Electrical Engineering Department, Sharif University of Technology, Tehran, Iran
| | - Hasan Hashemi
- Department of Radiology, Advanced Diagnostic and Interventional Radiology Research Center, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Hanieh Mobarak Salari
- Quantitative Medical Imaging/Spectroscopy Group, Tehran University of Medical Science, Tehran, Iran
| | - Gelareh Valizadeh
- Quantitative Medical Imaging/Spectroscopy Group, Tehran University of Medical Science, Tehran, Iran
| | - Fardin Samadi
- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran
| | - Forough Sodaei
- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran.,Quantitative Medical Imaging/Spectroscopy Group, Tehran University of Medical Science, Tehran, Iran
| | - Hamidreza Saligheh Rad
- Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran.,Quantitative Medical Imaging/Spectroscopy Group, Tehran University of Medical Science, Tehran, Iran
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Zhang T, Yuan P, Cui Y, Yuan W, Jiang D. Convergent and Divergent Structural Connectivity of Brain White Matter Network Between Patients With Erectile Dysfunction and Premature Ejaculation: A Graph Theory Analysis Study. Front Neurol 2022; 13:804207. [PMID: 35273555 PMCID: PMC8902049 DOI: 10.3389/fneur.2022.804207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 01/20/2022] [Indexed: 11/13/2022] Open
Abstract
Background Sexual dysfunction, namely, erectile dysfunction (ED) and premature ejaculation (PE), has been found to be associated with abnormal structural connectivity in the brain. Previous studies have mainly focused on a single disorder, however, convergent and divergent structural connectivity patterns of the brain network between ED and PE remain poorly understood. Methods T1-weighted structural data and diffusion tensor imaging data of 28 patients with psychological ED, 28 patients with lifelong PE (LPE), and 28 healthy controls (HCs) were obtained to map the white matter (WM) brain networks. Then, the graph-theoretical method was applied to investigate the differences of network properties (small-world measures) of the WM network between patients with ED and LPE. Furthermore, nodal segregative and integrative parameters (nodal clustering coefficient and characteristic path length) were also explored between these patients. Results Small-world architecture of the brain networks were identified for both psychological ED and LPE groups. However, patients with ED exhibited increased average characteristic path length of the brain network when compared with patients with LPE and HCs. No significant difference was found in the average characteristic path length between patients with LPE and HCs. Moreover, increased nodal characteristic path length was found in the right middle frontal gyrus (orbital part) of patients with ED and LPE when compared with HCs. In addition, patients with ED had increased nodal characteristic path length in the right middle frontal gyrus (orbital part) when compared with patients with LPE. Conclusion Together, our results demonstrated that decreased integration of the right middle frontal gyrus (orbital part) might be a convergent neuropathological basis for both psychological ED and LPE. In addition, patients with ED also exhibited decreased integration in the whole WM brain network, which was not found in patients with LPE. Therefore, altered integration of the whole brain network might be the divergent structural connectivity patterns for psychological ED and LPE.
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Affiliation(s)
- Tielong Zhang
- Department of Urology, The Affiliated Jianhu Hospital of Nantong University, Jianhu People's Hospital, Yancheng, China
| | - Peng Yuan
- Department of Intervention, The Affiliated Jianhu Hospital of Nantong University, Jianhu People's Hospital, Yancheng, China
| | - Yonghua Cui
- Department of Neurosurgery, The Affiliated Jianhu Hospital of Nantong University, Jianhu People's Hospital, Yancheng, China
| | - Weibiao Yuan
- Department of Radiology, The Affiliated Jianhu Hospital of Nantong University, Jianhu People's Hospital, Yancheng, China
| | - Daye Jiang
- Department of Urology, The Affiliated Jianhu Hospital of Nantong University, Jianhu People's Hospital, Yancheng, China
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Wang Y, Hu X, Li Y. Investigating cognitive flexibility deficit in schizophrenia using task-based whole-brain functional connectivity. Front Psychiatry 2022; 13:1069036. [PMID: 36479558 PMCID: PMC9719952 DOI: 10.3389/fpsyt.2022.1069036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 11/07/2022] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Cognitive flexibility is a core cognitive control function supported by the brain networks of the whole-brain. Schizophrenic patients show deficits in cognitive flexibility in conditions such as task-switching. A large number of neuroimaging studies have revealed abnormalities in local brain activations associated with deficits in cognitive flexibility in schizophrenia, but the relationship between impaired cognitive flexibility and the whole-brain functional connectivity (FC) pattern is unclear. METHOD We investigated the task-based functional connectivity of the whole-brain in patients with schizophrenia and healthy controls during task-switching. Multivariate pattern analysis (MVPA) was utilized to investigate whether the FC pattern can be used as a feature to discriminate schizophrenia patients from healthy controls. Graph theory analysis was further used to quantify the degrees of integration and segregation in the whole-brain networks to interpret the different reconfiguration patterns of brain networks in schizophrenia patients and healthy controls. RESULTS The results showed that the FC pattern classified schizophrenia patients and healthy controls with significant accuracy. Moreover, the altered whole-brain functional connectivity pattern was driven by a lower degree of network integration and segregation in schizophrenia, indicating that both global and local information transfers at the entire-network level were less efficient in schizophrenia patients than in healthy controls during task-switching processing. CONCLUSION These results investigated the group differences in FC profiles during task-switching and not only elucidated that FC patterns are changed in schizophrenic patients, suggesting that task-based FC could be used as a potential neuromarker to discriminate schizophrenia patients from healthy controls in cognitive flexibility but also provide increased insight into the brain network organization that may contribute to impaired cognitive flexibility.
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Affiliation(s)
- Yanqing Wang
- Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Xueping Hu
- School of Linguistic Science and Art, Jiangsu Normal University, Xuzhou, China.,Key Laboratory of Language and Cognitive Neuroscience of Jiangsu Province, Collaborative Innovation Center for Language Ability, Xuzhou, China
| | - Yilu Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
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Ni K, Liu Y, Zhu X, Tan H, Zeng Y, Guo Q, Xiao L, Yu B. Changed Cerebral White Matter Structural Network Topological Characters and Its Correlation with Cognitive Behavioral Abnormalities in Narcolepsy Type 1. Nat Sci Sleep 2022; 14:165-173. [PMID: 35140538 PMCID: PMC8818963 DOI: 10.2147/nss.s336967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 01/19/2022] [Indexed: 11/23/2022] Open
Abstract
OBJECTIVE In the current study we investigated topological abnormalities of the cerebral white matter networks in narcolepsy type 1 (NT1) patients and its relationship with their cognitive abnormalities using diffusion tensor imaging (DTI) technology. METHODS DTI and the Beijing version of the Montreal Cognitive Assessment (MoCA-BJ) were applied to 30 NT1 patients and 30 age-matched healthy controls. DTI studies were also carried using the 3T MRI system. Next, DTI data was used to establish a cerebral white matter network for all subjects and graph theory was applied to analyze the topological characteristics of the white matter structural network. Topographical parameters (such as local efficiency (Eloc), global efficiency (Eglob) and small-world (σ)) between NT1 patients and controls were then compared. The correlation between MoCA-BJ scores and topological parameters was also analyzed. RESULTS MoCA-BJ scores in NT1 patients were lower than those in the healthy controls. Compared with healthy controls, the global efficiency of the white matter network and attributes of the small world network were significantly reduced in NT1 patients. Finally, the global efficiency of the white matter structural network was related to the MoCA-BJ score of NT1 patients. CONCLUSION The abnormal topological characteristics of the white matter structural network in NT1 patients may be associated with their cognitive impairment.
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Affiliation(s)
- Kunlin Ni
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, 110004, People's Republic of China
| | - Yishu Liu
- Department of Pulmonary and Critical Care Medicine, Shengjing Hospital of China Medical University, Shenyang, 110004, People's Republic of China
| | - Xiaoyu Zhu
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, 110004, People's Republic of China
| | - Huiwen Tan
- Department of Pulmonary and Critical Care Medicine, Shengjing Hospital of China Medical University, Shenyang, 110004, People's Republic of China
| | - Yin Zeng
- Department of Pulmonary and Critical Care Medicine, Shengjing Hospital of China Medical University, Shenyang, 110004, People's Republic of China
| | - Qiyong Guo
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, 110004, People's Republic of China
| | - Li Xiao
- Department of Pulmonary and Critical Care Medicine, Shengjing Hospital of China Medical University, Shenyang, 110004, People's Republic of China.,Sleep Medicine Center, Shengjing Hospital of China Medical University, Shenyang, 110004, People's Republic of China
| | - Bing Yu
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, 110004, People's Republic of China
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19
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Zhou Y, Liu Z, Sun Y, Zhang H, Ruan J. Altered EEG Brain Networks in Patients with Acute Peripheral Herpes Zoster. J Pain Res 2021; 14:3429-3436. [PMID: 34754236 PMCID: PMC8570286 DOI: 10.2147/jpr.s329068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 10/22/2021] [Indexed: 11/25/2022] Open
Abstract
OBJECTIVE To investigate whether the brain networks changed in patients with acute peripheral herpes zoster (HZ). METHODS We reviewed the EEG database in Jianyang People's Hospital. Patients with acute HZ (n=71) were enrolled from January 2016 to December 2020. Each included subject underwent a ten-minute and 16-channel EEG examination. Five epochs of 10-second EEG data in resting-state were collected from each HZ patient. Five 10-second resting-state EEG epochs from sex- and age-matched healthy controls (HC, n=71) who reported no history of neurological or psychiatric disorders and visited the hospital for routine physical examinations were collected. Brain network and graph theory analysis based on phase locking value parameter and functional ICA were performed using a self-writing Matlab code and the LORETA KEY tool. RESULTS Compared with the HC group, the HZ patients showed significant altered brain networks. The graph theory analysis revealed that the clustering coefficient and local efficiency of full band in HZ patients were lower than those in HC group (P<0.05). In beta band, the global efficiency and local efficiency of HZ patients group decreased, compared with healthy group (P<0.05). The functional ICA showed that three components showed significant differences between the two groups. In component 2, HZ patients showed excess superior frontal gyrus (BA10) neuro oscillation in delta band and less medial frontal gyrus (BA 11) neuro oscillation in beta and gamma bands than that in HCs. And for component 3, the alpha band of the HZ patients presented increased neuro activities in superior frontal gyrus (BA 11) and decreased neuro activities in occipital lobe (BA 18). In component 4, the inferior frontal gyrus (BA 47) showed excess activity in the left hemisphere and reduced activity in the right hemisphere in delta band, compared with HC group. CONCLUSION Altered brain networks exist in resting-state EEG data of patients with acute HZ. The changes of EEG brain networks in HZ patients are characterized by decreased global efficiency and local efficiency in beta band. Moreover, the spontaneous oscillation of some brain regions involving pain management and the connectivity of default mode network changed in HZ patients. Our study provided novel understanding of HZ from an electrophysiological view, and led to converging evidence for treatment of HZ with neural regulation in future.
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Affiliation(s)
- Yan Zhou
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, People’s Republic of China
- Department of Neurology, Jianyang People’s Hospital, Jianyang, 641400, People’s Republic of China
- Laboratory of Neurological Diseases and Brain Function, Luzhou, 646000, People’s Republic of China
| | - Zhenqin Liu
- Department of Dermatology, Jianyang People’s Hospital, Jianyang, 641400, People’s Republic of China
| | - Yuanmei Sun
- Department of Dermatology, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, 400010, People’s Republic of China
| | - Hao Zhang
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, People’s Republic of China
- Laboratory of Neurological Diseases and Brain Function, Luzhou, 646000, People’s Republic of China
| | - Jianghai Ruan
- Department of Neurology, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, People’s Republic of China
- Laboratory of Neurological Diseases and Brain Function, Luzhou, 646000, People’s Republic of China
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20
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Cao Y, Zhan Y, Du M, Zhao G, Liu Z, Zhou F, He L. Disruption of human brain connectivity networks in patients with cervical spondylotic myelopathy. Quant Imaging Med Surg 2021; 11:3418-3430. [PMID: 34341720 DOI: 10.21037/qims-20-874] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Accepted: 03/08/2021] [Indexed: 02/05/2023]
Abstract
Background Brain functional plasticity and reorganization in patients with cervical spondylotic myelopathy (CSM) is increasingly being explored and validated. However, specific topological alterations in functional networks and their role in CSM brain functional reorganization remain unclear. This study investigates the topological architecture of intrinsic brain functional networks in CSM patients using graph theory. Methods Functional MRI was conducted on 67 CSM patients and 60 healthy controls (HCs). The topological organization of the whole-brain functional network was then calculated using theoretical graph analysis. The difference in categorical variables between groups was compared using a chi-squared test, while that between continuous variables was evaluated using a two-sample t-test. Nonparametric permutation tests were used to compare network measures between the two groups. Results Small-world architecture in functional brain networks were identified in both CSM patients and HCs. Compared with HCs, CSM patients showed a decreased area under the curve (AUC) of the characteristic path length (FDR q=0.040), clustering coefficient (FDR q=0.037), and normalized characteristic path length (FDR q=0.038) of the network. In contrast, there was an increased AUC of normalized clustering coefficient (FDR q=0.014), small-worldness (FDR q=0.009), and global network efficiency (FDR q=0.027) of the network. In local brain regions, nodal topological properties revealed group differences which were predominantly in the default-mode network (DMN), left postcentral gyrus, bilateral putamen, lingual gyrus, and posterior cingulate gyrus. Conclusions This study reported altered functional topological organization in CSM patients. Decreased nodal centralities in the visual cortex and sensory-motor regions may indicate sensory-motor dysfunction and blurred vision. Furthermore, increased nodal centralities in the cerebellum may be compensatory for sensory-motor dysfunction in CSM, while the increased DMN may indicate increased psychological processing in CSM patients.
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Affiliation(s)
- Yuan Cao
- Department of Radiology, the First Affiliated Hospital of Nanchang University, Nanchang, China.,Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, China.,Huaxi MR Research Center, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Yaru Zhan
- Department of Radiology, the First Affiliated Hospital of Nanchang University, Nanchang, China.,Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, China
| | - Miao Du
- College of Electrical Engineering of Sichuan University, Chengdu, China
| | - Guoshu Zhao
- Department of Radiology, the First Affiliated Hospital of Nanchang University, Nanchang, China.,Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, China
| | - Zhili Liu
- Department of Orthopedic Surgery, the First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Fuqing Zhou
- Department of Radiology, the First Affiliated Hospital of Nanchang University, Nanchang, China.,Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, China
| | - Laichang He
- Department of Radiology, the First Affiliated Hospital of Nanchang University, Nanchang, China.,Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang, China
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21
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Qi J, Li BZ, Zhang Y, Pan B, Gao YH, Zhan H, Liu Y, Shao YC, Weng XC, Zhang X. Disrupted Small-world Networks are Associated with Decreased Vigilant Attention after Total Sleep Deprivation. Neuroscience 2021; 471:51-60. [PMID: 34293415 DOI: 10.1016/j.neuroscience.2021.07.010] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 07/02/2021] [Accepted: 07/12/2021] [Indexed: 02/06/2023]
Abstract
Sleep deprivation critically affects vigilant attention. Previous neuroimaging studies have revealed altered inter-regional functional connectivity after sleep deprivation, which may disrupt topological properties of brain functional networks. However, little is known about alterations in the topology of intrinsic connectivity and its involvement in attention performance after sleep deprivation. In the current study, we investigated the topological properties of brain networks derived from resting-state functional magnetic resonance imaging of 26 healthy men in rested wakefulness (RW) state and after 36 h of total sleep deprivation (TSD). In the predefined sparsity threshold range, both global and nodal network properties were evaluated based on graph theory analysis. Vigilant attention was assessed using the psychomotor vigilance test (PVT) before and after TSD. Furthermore, Pearson's correlation analyses were conducted to explore the association between altered network properties and changed PVT performance after TSD. At the global level, the brain functional networks in the TSD state showed a significantly lower small-world coefficient than RW, with decreased global efficiency. At the nodal level, the altered regions were selectively distributed in frontoparietal networks, sensorimotor networks, temporal regions, and salience networks. More specifically, the altered clustering coefficient in the posterior superior temporal sulcus (pSTS) and insula, and altered local efficiency in pSTS were further associated with PVT performance after TSD. Our results suggest that the topological properties of brain functional networks are disrupted, and aberrant topology of temporal networks and salience networks may act as neural signatures underlying the vigilant attention impairments after TSD.
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Affiliation(s)
- Jing Qi
- School of Medicine, Nankai University, Tianjin 300071, China; Department of Neurology, The Second Medical Center, Sleep Medicine Research Center, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing 100853, China
| | - Bo-Zhi Li
- Department of Neurology, The Second Medical Center, Sleep Medicine Research Center, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing 100853, China
| | - Ying Zhang
- The Eighth Medical Center of the General Hospital of People's Liberation Army, Beijing 100091, China
| | - Bei Pan
- Airforce Medical Center, PLA, Beijing 100142, China
| | - Yu-Hong Gao
- National Clinical Research Centre for Geriatric Diseases, Second Medical Center, Chinese PLA General Hospital, Beijing 100853, China
| | - Hao Zhan
- Airforce Medical Center, PLA, Beijing 100142, China
| | - Yong Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yong-Cong Shao
- School of Psychology, Beijing Sport University, Beijing 100084, China; School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
| | - Xie-Chuan Weng
- Beijing Institute of Basic Medical Sciences, Beijing 100850, China.
| | - Xi Zhang
- Department of Neurology, The Second Medical Center, Sleep Medicine Research Center, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing 100853, China; School of Medicine, Nankai University, Tianjin 300071, China.
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22
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Ma ZZ, Lu YC, Wu JJ, Li SS, Ding W, Xu JG. Alteration of spatial patterns at the network-level in facial synkinesis: an independent component and connectome analysis. Ann Transl Med 2021; 9:240. [PMID: 33708867 PMCID: PMC7940883 DOI: 10.21037/atm-20-4865] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Background The treatment of post-facial palsy synkinesis (PFPS) remains inadequate. Previous studies have confirmed that brain plasticity is involved in the process of functional restoration. Isolated activation has been well studied, however, the brain works as an integrity of several isolated regions. This study aimed to assess the alteration of the brain network topology with overall and local characteristics of information dissemination. Understanding the neural mechanisms of PFPS could help to improve therapy options and prognosis. Methods Patients with facial synkinesis and healthy controls (HCs) were estimated using functional magnetic resonance imaging (fMRI) of resting-state. Subsequently, an independent component analysis (ICA) was used to extract four subnets from the whole brain. Then we used the measurements of graph theory and calculated in the whole-brain network and each sub-network. Results We found no significant difference between the patient group and the HCs on the whole-brain scale. Then we identified four subnetworks from the resting-state data. In the sub-network property analysis, patients' locally distributed properties in the sensorimotor network (SMN) and ventral default mode network (vDMN) were reduced. It revealed that γ (10,000 permutations, P=0.048) and S (10,000 permutations, P=0.022) within the SMN progressively decreased in patients with PFPS. For the analysis of vDMN, significant differences were found in γ (10,000 permutations, P=0.019), Elocal (10,000 permutations, P=0.008), and β (10,000 permutations, P=0.011) between the groups. Conclusions Our results demonstrated a reduction in local network processing efficiency in patients with PFPS. Therefore, we speculate that decreased characteristics in the intra-vDMN and intra-SMN, rather than the whole-brain network, may serve distinct symptoms such as facial nerve damage or more synkinetic movements. This finding of the alteration of network properties is a small step forward to help uncover the underlying mechanism.
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Affiliation(s)
- Zhen-Zhen Ma
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Ye-Chen Lu
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jia-Jia Wu
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Si-Si Li
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Wei Ding
- Department of Plastic and Reconstructive Surgery, Shanghai Ninth People Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Jian-Guang Xu
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Department of Hand Surgery, Huashan Hospital, Fudan University, Shanghai, China
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23
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Zhu X, Ni K, Tan H, Liu Y, Zeng Y, Yu B, Guo Q, Xiao L. Abnormal Brain Network Topology During Non-rapid Eye Movement Sleep and Its Correlation With Cognitive Behavioral Abnormalities in Narcolepsy Type 1. Front Neurol 2021; 11:617827. [PMID: 33505350 PMCID: PMC7829333 DOI: 10.3389/fneur.2020.617827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 12/04/2020] [Indexed: 11/13/2022] Open
Abstract
Objective: Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) were applied to investigate the abnormalities in the topological characteristics of functional brain networks during non-rapid eye movement(NREM)sleep. And we investigated its relationship with cognitive abnormalities in patients with narcolepsy type 1 (NT1) disorder in the current study. Methods: The Beijing version of the Montreal Cognitive Assessment (MoCA-BJ) and EEG-fMRI were applied in 25 patients with NT1 and 25 age-matched healthy controls. All subjects participated in a nocturnal video polysomnography(PSG)study, and total sleep time (TST), percentage of TST (%TST) for each sleep stage and arousal index were calculated. The Epworth Sleepiness Score (ESS) was used to measure the degree of daytime sleepiness. The EEG-fMRI study was performed simultaneously using a 3T MRI system and a 32-channel MRI-compatible EEG system during sleep. Visual scoring of EEG data was used for sleep staging. Cognitive function was assessed for all subjects using the MoCA-BJ. The fMRI data were applied to establish a whole-brain functional connectivity network for all subjects, and the topological characteristics of the whole-brain functional network were analyzed using a graph-theoretic approach. The topological parameters were compared between groups. Lastly, the correlation between topological parameters and the assessment scale using Montreal Cognition was analyzed. Results: The MoCA-BJ scores were lower in patients with NT1 than in normal controls. Whole-brain global efficiency during stage N2 sleep in patients with NT1 displayed significantly lower small-world properties than in normal controls. Whole-brain functional network global efficiency in patients with NT1 was significantly correlated with MoCA-BJ scores. Conclusion: The global efficiency of the functional brain network during stage N2 sleep in patients with NT1 and the correspondingly reduced small-world attributes were associated with cognitive impairment.
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Affiliation(s)
- Xiaoyu Zhu
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Kunlin Ni
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Huiwen Tan
- Department of Pulmonary and Critical Care Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yishu Liu
- Department of Pulmonary and Critical Care Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yin Zeng
- Department of Pulmonary and Critical Care Medicine, Shengjing Hospital of China Medical University, Shenyang, China
| | - Bing Yu
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Qiyong Guo
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Li Xiao
- Department of Pulmonary and Critical Care Medicine, Shengjing Hospital of China Medical University, Shenyang, China.,Sleep Medicine Center, Shengjing Hospital of China Medical University, Shenyang, China
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24
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Kuang C, Zha Y, Liu C, Chen J. Altered Topological Properties of Brain Structural Covariance Networks in Patients With Cervical Spondylotic Myelopathy. Front Hum Neurosci 2020; 14:364. [PMID: 33100992 PMCID: PMC7500316 DOI: 10.3389/fnhum.2020.00364] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Accepted: 08/10/2020] [Indexed: 01/24/2023] Open
Abstract
Background Brain structural alterations play an important role in patients with cervical spondylotic myelopathy (CSM). However, while there have been studies on regional brain structural alterations, only few studies have focused on the topological organization of the brain structural covariance network. This work aimed to describe the structural covariance network architecture alterations that are possibly linked to cortex reorganization in patients with CSM. Methods High-resolution anatomical images of 31 CSM patients and 31 healthy controls (HCs) were included in the study. The images were acquired using a sagittal three-dimensional T1-weighted BRAVO sequence. Firstly, the gray matter volume of 90 brain regions of automated anatomical labeling atlas were computed using a VBM toolbox based on the DARTEL algorithm. Then, the brain structural covariance network was constructed by thresholding the gray matter volume correlation matrices. Subsequently, the network measures and nodal property were calculated based on graph theory. Finally, the differences in the network metrics and nodal property between groups were compared using a non-parametric test. Results Patients with CSM showed larger global efficiency and smaller local efficiency, clustering coefficient, characteristic path length, and sigma values than HCs. Patients with CSM had greater betweenness in the left superior parietal gyrus (SPG.L) and the left supplementary motor area (SMA.L) than HCs. Besides, patients with CSM had smaller betweenness in right middle occipital gyrus. The brain structural covariance networks of CSM patients exhibited equal resilience to random failure as those of HCs. However, the maximum relative size of giant connected components was approximately 10% larger in HCs than in CSM patients, upon removal of 44 nodes in targeted attack. Conclusion These observed alternations in global network measures in CSM patients reflect that the brain structural covariance network in CSM exhibits the less optimal small-world model compared to that in HCs. Increased betweenness in SPG.L and SMA.L seems to be related to cortex reorganization to recover multiple sensory functions after spinal cord injury in CSM patients. The network resilience of patients with CSM exhibiting a relative mild vulnerability, compared to HCs, is probably attributable to the balance and interplay between cortex reorganization and ongoing degeneration.
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Affiliation(s)
- Cuili Kuang
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Yunfei Zha
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Changsheng Liu
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Jun Chen
- Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China
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25
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Sulthana MT, Alagarsamy V, Chitra K. Design, Synthesis, Pharmacological Evaluation, In silico Modeling, Prediction of Toxicity and Metabolism Studies of Novel 1-(substituted)-2-methyl- 3-(4-oxo-2-phenyl quinazolin-3(4H)-yl)isothioureas. Med Chem 2020; 17:352-368. [PMID: 32807063 DOI: 10.2174/1573406416666200817153033] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2020] [Revised: 05/24/2020] [Accepted: 05/25/2020] [Indexed: 11/22/2022]
Abstract
BACKGROUND Although exhaustive efforts to prevent and treat tuberculosis (TB) have been made, the problem still continues due to multi-drug-resistant (MDR) and extensively drugresistant TB (XDR-TB). It clearly highlights the urgent need to develop novel "druggable" molecules for the co-infection treatment and strains of MDR-TB and XDR-TB. OBJECTIVE In this approach, a hybrid molecule was created by merging two or more pharmacophores. The active site of targets may be addressed by each of the pharmacophores and proffers the opportunity for selectivity. In addition, it also reduces undesirable side effects and drug-resistance. METHODS In this study, a novel quinazolinone analog was designed and synthesized by substituting thiourea nucleus and phenyl ring at N-3 and C-2 position of quinazoline ring, respectively. All title compounds were tested for antitubercular activity by in vitro M. tuberculosis and anti-human immunodeficiency virus (HIV) activity by MT-4 cell assay method. The agar dilution method was used to test the antibacterial potency of entire prepared derivatives against various strains of grampositive and gram-negative microorganisms. RESULTS The title compounds, 1-(substituted)-2-methyl-3-(4-oxo-2-phenyl quinazolin-3(4H)-yl) isothioureas (QTS1 - QTS15) were synthesized by the reaction between key intermediate 3-amino- 2-phenylquinazolin-4(3H)-one with various alkyl/aryl isothiocyanates followed by methylation with dimethyl sulphate. Among the series, compound 1-(3-chlorophenyl)-2-methyl-3-(4-oxo-2-phenyl quinazolin- 3(4H)-yl) isothioureas (QTS14) showed the highest potency against B. subtilis, K. pneumonia and S. aureus at 1.6 μg/mL. The compound QTS14 exhibited the most potent antitubercular activity at the MIC of 0.78 μg/mL and anti-HIV activity at 0.97 μg/mL against HIV1 and HIV2. CONCLUSION The results obtained from this study confirm that the synthesized and biologically evaluated quinazolines showed promising antimicrobial, antitubercular and anti-HIV activities. The new scaffolds proffer a plausible lead for further development and optimization of novel antitubercular and anti-HIV drugs.
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Affiliation(s)
| | - Veerachamy Alagarsamy
- Medicinal Chemistry Research Laboratory, MNR College of Pharmacy, Sangareddy - 502 294, Gr. Hyderabad, India
| | - Krishnan Chitra
- Faculty of Pharmacy, Sri Ramachandra Institute of Higher Education and Research (Deemed to be University), Porur, Chennai, 600 116, India
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26
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Li X, Wang L, Qin B, Zhang Y, Zhou Z, Qin Y, Bao G, Huang J, Cai J. A Sleeping rs-fMRI Study of Preschool Children with Autism Spectrum Disorders. Curr Med Imaging 2020; 16:921-927. [PMID: 32386497 DOI: 10.2174/1573405616666200510003144] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2020] [Revised: 04/02/2020] [Accepted: 04/24/2020] [Indexed: 11/22/2022]
Abstract
OBJECTIVES The brain functional network of autism spectrum disorders (ASDs) in the earlier stages of life has been almost unknown due to difficulties in obtaining a resting-state functional magnetic resonance imaging (rs-fMRI). This study aimed to perform rs-MRI under a sedated sleep state and reveal possible alterations in the brain functional network. METHODS Rs-fMRI was performed in a group of preschool children (aged 2-6 years, 53 with ASD, 63 as controls) under a sedated sleeping state. Based on graph theoretical analysis, global and local topological metrics were calculated to investigate alterations in brain functional networks. Besides, correlation analyses were conducted between the abnormal attribute values and the Childhood Autism Rating Scale (CARS) scores. RESULTS The graph theoretical analysis showed that the nodal degree of the right medial frontal gyrus and the nodal efficiency of the right lingual gyrus in the ASD group were higher than those in the control group (P<0.05). There was a statistically significant positive correlation (R=0.318, P<0.05) between the right midfrontal gyrus nodal degree values and CARS scores in the ASD patients. CONCLUSION Alterations of some nodal attributes in the brain network occurred in preschool autistic children which could serve as potential imaging biomarkers for evaluating ASD in earlier stages.
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Affiliation(s)
- Xiaomeng Li
- Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing 400014, China
| | - Longlun Wang
- Department of Radiology, Children's Hospital of Chongqing Medical University, Chongqing 400014, China
| | - Bin Qin
- Department of Radiology, Children's Hospital of Chongqing Medical University, Chongqing 400014, China
| | - Yun Zhang
- Department of Radiology, Children's Hospital of Chongqing Medical University, Chongqing 400014, China
| | - Zhiming Zhou
- Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing 400014, China
| | - Yong Qin
- Department of Radiology, Children's Hospital of Chongqing Medical University, Chongqing 400014, China
| | - Guangcheng Bao
- Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing 400014, China
| | - Jie Huang
- Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing 400014, China
| | - Jinhua Cai
- Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing 400014, China
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Subramanian S, Rajamanickam K, Prakash JS, Ramachandran M. Study on structural atrophy changes and functional connectivity measures in Alzheimer's disease. J Med Imaging (Bellingham) 2020; 7:016002. [PMID: 32118092 DOI: 10.1117/1.jmi.7.1.016002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Accepted: 02/03/2020] [Indexed: 11/14/2022] Open
Abstract
Alzheimer's disease (AD) is characterized by the progressive accumulation of neurofibrillary tangles associated with amyloid plaques. We used 80 resting-state functional magnetic resonance imaging and 80 T 1 images acquired using MP-RAGE (magnetization-prepared rapid acquisition gradient echo) from Alzheimer's Disease Neuroimaging Initiative data to detect atrophy changes and functional connectivity patterns of the default mode networks (DMNs). The study subjects were classified into four groups (each with n = 20 ) based on their Mini-Mental State Examination (MMSE) score as follows: cognitively normal (CN), early mild cognitive impairment, late mild cognitive impairment, and AD. The resting-state functional connectivity of the DMN was examined between the groups using the CONN functional connectivity toolbox. Loss of gray matter in AD was observed. Atrophy measured by the volume of selected subcortical regions, using the Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library's Integrated Registration and Segmentation Tool (FIRST), revealed significant volume loss in AD when compared to CN ( p < 0.05 ). DMNs were selected to assess functional connectivity. The negative connectivity of DMN increased in AD group compared to controls. Graph theory parameters, such as global and local efficiency, betweenness centrality, average path length, and cluster coefficient, were computed. Relatively higher correlation between MMSE and functional metrics ( r = 0.364 , p = 0.001 ) was observed as compared to atrophy measures ( r = 0.303 , p = 0.006 ). In addition, the receiver operating characteristic analysis showed large area under the curve ( A Z ) for functional parameters ( A Z > 0.9 ), compared to morphometric changes ( A Z < 0.8 ). In summary, it is observed that the functional connectivity measures may serve a better predictor in comparison to structural atrophy changes. We postulate that functional connectivity measures have the potential to evolve as a marker for the early detection of AD.
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Affiliation(s)
- Saraswathi Subramanian
- Chettinad Academy of Research and Education, Faculty of Allied Health Sciences, Kelambakkam, Chennai, Tamil Nadu, India
| | - Karunanithi Rajamanickam
- Chettinad Academy of Research and Education, Faculty of Allied Health Sciences, Kelambakkam, Chennai, Tamil Nadu, India
| | - Joy Sebastian Prakash
- Chettinad Academy of Research and Education, Faculty of Allied Health Sciences, Kelambakkam, Chennai, Tamil Nadu, India
| | - Murugesan Ramachandran
- Chettinad Academy of Research and Education, Faculty of Allied Health Sciences, Kelambakkam, Chennai, Tamil Nadu, India
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Chen HJ, Wang YF, Wen J, Xu Q, Lu GM, Zhang LJ. Functional-structural relationship in large-scale brain networks of patients with end stage renal disease after kidney transplantation: A longitudinal study. Hum Brain Mapp 2020; 41:328-341. [PMID: 31571368 PMCID: PMC7268055 DOI: 10.1002/hbm.24804] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Revised: 09/03/2019] [Accepted: 09/09/2019] [Indexed: 12/14/2022] Open
Abstract
It is unclear how the brain network changed after kidney transplantation (KT). We explored the patterns of large‐scale complex network after KT in end‐stage renal disease (ESRD) patients with resting‐state functional MRI (rs‐fMRI) and diffusion tensor imaging (DTI). Twenty‐one ESRD patients (14 men; mean age, 31.5 ± 9.9 years) scheduled for KT and 17 age‐ and gender‐matched healthy controls (HC) (8 men; mean age, 28.9 ± 7.2 years) were enrolled in this study. Each participant underwent rs‐fMRI and DTI scans in three time points (pre‐KT, 1 and 6 months after KT [for ESRD]). Graph theory analysis was used to characterize the topological properties by using functional and structural network connectivities intergroup correlation analysis was performed between functional/structural MR indexes and clinical markers. Compared with HC, pre‐KT ESRD patients showed an altered topological organization in both functional and structural networks. Compared with pre‐KT, increased node degree and node efficiency were observed for both functional and structural networks at 1 month after KT (all p < .05), which were further increased at 6 months after KT (p < .05). Both functional and structural networks did not recover completely at 6 months after KT (all p < .05). The patients showed an increased functional–structural connectivity coupling at 1 month after KT compared with HC (p = .041). A trend of progressive recovery of functional and structural connectivity networks was observed in ERSD patients after KT, which did not recover to the normal levels even in 6 months after KT. The study results underlie cognitive function recovery in ESRD patients following KT in the neuropathophysiological perspective.
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Affiliation(s)
- Hui J Chen
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China.,Department of Radiology, Affiliated Hainan Hospital of Hainan Medical College, Hainan General Hospital, Haikou, Hainan, P.R. China
| | - Yun F Wang
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Jiqiu Wen
- National Clinical Research Center of Kidney Disease, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Qiang Xu
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Guang M Lu
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
| | - Long J Zhang
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China
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29
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Chen Y, Huang X, Wu M, Li K, Hu X, Jiang P, Chen L, He N, Dai J, Wang S, He M, Guo L, Sweeney JA, Gong Q. Disrupted brain functional networks in drug-naïve children with attention deficit hyperactivity disorder assessed using graph theory analysis. Hum Brain Mapp 2019; 40:4877-4887. [PMID: 31361385 DOI: 10.1002/hbm.24743] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Revised: 07/10/2019] [Accepted: 07/15/2019] [Indexed: 02/05/2023] Open
Abstract
Neuroimaging studies have revealed functional brain network abnormalities in attention deficit hyperactivity disorder (ADHD), but the results have been inconsistent, potentially related to confounding medication effects. Furthermore, specific topological alterations in functional networks and their role in behavioral inhibition dysfunction remain to be established. Resting-state functional magnetic resonance imaging was performed on 51 drug-naïve children with ADHD and 55 age-matched healthy controls. Brain functional networks were constructed by thresholding the partial correlation matrices of 90 brain regions, and graph theory was used to analyze network topological properties. The Stroop test was used to assess cognitive inhibitory abilities. Nonparametric permutation tests were used to compare the topological architectures in the two groups. Compared with healthy subjects, brain networks in ADHD patients demonstrated altered topological characteristics, including lower global (FDR q = 0.01) and local efficiency (p = 0.032, uncorrected) and a longer path length (FDR q = 0.01). Lower nodal efficiencies were found in the left inferior frontal gyrus and anterior cingulate cortex in the ADHD group (FDR both q < 0.05). Altered global and nodal topological efficiencies were associated with the severity of inhibitory cognitive control deficits and hyperactivity symptoms in ADHD (p <0 .05). Alterations in network topologies in drug-naïve ADHD patients indicate weaker small-worldization with decreased segregation and integration of functional brain networks. Deficits in the cingulo-fronto-parietal attention network were associated with inhibitory control deficits.
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Affiliation(s)
- Ying Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, China
| | - Xiaoqi Huang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Min Wu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Kaiming Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Xinyu Hu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Ping Jiang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Lizhou Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Ning He
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, China
| | - Jing Dai
- Department of Psychoradiology, Chengdu Mental Health Center, Chengdu, China
| | - Song Wang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Manxi He
- Department of Psychoradiology, Chengdu Mental Health Center, Chengdu, China
| | - Lanting Guo
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, China
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, Ohio
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.,Psychoradiology Research Unit of Chinese Academy of Medical Sciences (2018RU011), West China Hospital of Sichuan University, Chengdu, Sichuan, China
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Abstract
Cigarette smoking is associated with abnormalities in the widespread inter-regional functional connectivity of the brain. However, few studies focused on the abnormalities in the topological organization of brain functional networks in young smokers. In the current study, resting-state functional magnetic resonance images were acquired from 30 young male smokers and 32 age-, gender-, and education-matched healthy male nonsmokers. A functional network was constructed by calculating the Pearson correlation coefficients among 246 subregions in the human Brainnetome Atlas. The topological parameters were compared between smokers and nonsmokers. The results showed that the functional network of both young smokers and nonsmokers had small-world topology. Compared to nonsmokers, young smokers exhibited a decreased clustering coefficient (Cp) and local network efficiency (Elocal). Cp and Elocal were negatively correlated with the duration of cigarette use. In addition, increased nodal efficiency (Enodal) was mainly located in the prefrontal cortex (PFC), cingulate gyrus, insula, and caudate. Decreased connectivities among the PFC, cingulate gyrus, insula, basal ganglia (of specific node), and thalamus were also observed. In sum, we revealed the abnormal topological organization of brain functional networks in young smokers, which may improve our understanding of the neural mechanism of young smokers from a brain functional network topological organization perspective.
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Affiliation(s)
- Ying Tan
- Health Management Center, Xiangya Hospital, Central South University, Changsha, China
| | - Jing Chen
- Center of Stomatology, Xiangya Hospital, Central South University, Changsha, China
| | - Weiwei Liao
- Health Management Center, Xiangya Hospital, Central South University, Changsha, China
| | - Zhaoxin Qian
- Department of Emergency, Xiangya Hospital, Central South University, Changsha, China
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Park BS, Lee YJ, Park JH, Kim IH, Park SH, Lee HJ, Park KM. Alterations of brain network hubs in reflex syncope: Evidence from a graph theoretical analysis based on DTI. Brain Behav 2018; 8:e01006. [PMID: 29791077 PMCID: PMC5991578 DOI: 10.1002/brb3.1006] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Revised: 04/16/2018] [Accepted: 04/23/2018] [Indexed: 12/19/2022] Open
Abstract
OBJECTIVE We evaluated global topology and organization of regional hubs in the brain networks and microstructural abnormalities in the white matter of patients with reflex syncope. METHODS Twenty patients with reflex syncope and thirty healthy subjects were recruited, and they underwent diffusion tensor imaging (DTI) scans. Graph theory was applied to obtain network measures based on extracted DTI data, using DSI Studio. We then investigated differences in the network measures between the patients with reflex syncope and the healthy subjects. We also analyzed microstructural abnormalities of white matter using tract-based spatial statistics analysis (TBSS). RESULTS Measures of global topology were not different between patients with reflex syncope and healthy subjects. However, in reflex syncope patients, the strength measures of the right angular, left inferior frontal, left middle orbitofrontal, left superior medial frontal, and left middle temporal gyrus were lower than in healthy subjects. The betweenness centrality measures of the left middle orbitofrontal, left fusiform, and left lingual gyrus in patients were lower than those in healthy subjects. The PageRank centrality measures of the right angular, left middle orbitofrontal, and left superior medial frontal gyrus in patients were lower than those in healthy subjects. Regarding the analysis of the white matter microstructure, there were no differences in the fractional anisotropy and mean diffusivity values between the two groups. CONCLUSIONS We have identified a reorganization of network hubs in the brain network of patients with reflex syncope. These alterations in brain network may play a role in the pathophysiologic mechanism underlying reflex syncope.
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Affiliation(s)
- Bong Soo Park
- Department of Internal medicine, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea
| | - Yoo Jin Lee
- Department of Internal medicine, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea
| | - Jin-Han Park
- Department of Internal medicine, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea
| | - Il Hwan Kim
- Department of Internal medicine, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea
| | - Si Hyung Park
- Department of Internal medicine, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea
| | - Ho-Joon Lee
- Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea
| | - Kang Min Park
- Department of Neurology, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea
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32
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Guo T, Guan X, Zeng Q, Xuan M, Gu Q, Huang P, Xu X, Zhang M. Alterations of Brain Structural Network in Parkinson's Disease With and Without Rapid Eye Movement Sleep Behavior Disorder. Front Neurol 2018; 9:334. [PMID: 29867741 PMCID: PMC5958180 DOI: 10.3389/fneur.2018.00334] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2017] [Accepted: 04/26/2018] [Indexed: 11/29/2022] Open
Abstract
Background and objective Rapid eye movement sleep behavior disorder (RBD) has a strong association with alpha synucleinpathies such as Parkinson’s disease (PD) and PD patients with RBD tend to have a poorer prognosis. However, we still know little about the pathogenesis of RBD in PD. Therefore, we aim to detect the alterations of structural correlation network (SCN) in PD patients with and without RBD. Materials and methods A total of 191 PD patients, including 51 patients with possible RBD (pRBD) and 140 patients with non-possible RBD, and 76 normal controls were included in the present study. Structural brain networks were constructed by thresholding gray matter volume correlation matrices of 116 regions and analyzed using graph theoretical approaches. Results There was no difference in global properties among the three groups. Significant enhanced regional nodal measures in limbic system, frontal-temporal regions, and occipital regions and decreased nodal measures in cerebellum were found in PD patients with pRBD (PD-pRBD) compared with PD patients without pRBD. Besides, nodes in frontal lobe, temporal lobe, and limbic system were served as hubs in both two PD groups, and PD-pRBD exhibited additionally recruited hubs in limbic regions. Conclusion Based on the SCN analysis, we found PD-pRBD exhibited a reorganization of nodal properties as well as the remapping of the hub distribution in whole brain especially in limbic system, which may shed light to the pathophysiology of PD with RBD.
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Affiliation(s)
- Tao Guo
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaojun Guan
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Qiaoling Zeng
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Min Xuan
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Quanquan Gu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
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Park KM, Lee BI, Shin KJ, Ha SY, Park J, Kim TH, Mun CW, Kim SE. Progressive topological disorganization of brain network in focal epilepsy. Acta Neurol Scand 2018; 137:425-431. [PMID: 29344935 DOI: 10.1111/ane.12899] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/22/2017] [Indexed: 12/21/2022]
Abstract
OBJECTIVE Increasing evidence has suggested that epilepsy is a network disease. Graph theory is a mathematical tool that allows for the analysis and quantification of the brain network. We aimed to evaluate the influences of duration of epilepsy on the topological organization of brain network in focal epilepsy patients with normal MRI using the graph theoretical analysis based on diffusion tenor imaging. METHODS We prospectively enrolled 66 patients with focal epilepsy (18/66 patients were newly diagnosed) and 84 healthy subjects. All of the patients with epilepsy had normal MRI on visual inspection. All of the subjects underwent diffusion tensor imaging that was analyzed using graph theory to obtain network measures. RESULTS The measures of characteristic path length and small-worldness in the patients with focal epilepsy were significantly decreased, even after multiple corrections (P < .01). Moreover, the measures including mean clustering coefficient and global efficiency in the patients with epilepsy had strong tendency to decrease compared to those in healthy subjects (P = .0153 and P = .0138, respectively). When comparing the measures among the patients with newly diagnosed/chronic epilepsy and healthy subjects using ANOVA, the characteristic path length (P = .006), small-worldness (P = .032), and global efficiency (P = .004) were significantly different. In addition, the duration of epilepsy was negatively correlated with global efficiency (r = -.249, P = .0454). CONCLUSIONS We newly found a progressive topological disorganization of the brain network in focal epilepsy. In addition, we demonstrated disrupted topological organization in focal epilepsy, shifting toward a more random state.
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Affiliation(s)
- K. M. Park
- Department of Neurology; Haeundae Paik Hospital; Inje University College of Medicine; Busan Korea
| | - B. I. Lee
- Department of Neurology; Haeundae Paik Hospital; Inje University College of Medicine; Busan Korea
| | - K. J. Shin
- Department of Neurology; Haeundae Paik Hospital; Inje University College of Medicine; Busan Korea
| | - S. Y. Ha
- Department of Neurology; Haeundae Paik Hospital; Inje University College of Medicine; Busan Korea
| | - J. Park
- Department of Neurology; Haeundae Paik Hospital; Inje University College of Medicine; Busan Korea
| | - T. H. Kim
- Department of Health Science and Technology; Inje University; Gimhae Korea
| | - C. W. Mun
- Department of Health Science and Technology; Inje University; Gimhae Korea
- School of Biomedical Engineering/u-HARC; Inje University; Gimhae Korea
| | - S. E. Kim
- Department of Neurology; Haeundae Paik Hospital; Inje University College of Medicine; Busan Korea
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Oxtoby NP, Garbarino S, Firth NC, Warren JD, Schott JM, Alexander DC. Data-Driven Sequence of Changes to Anatomical Brain Connectivity in Sporadic Alzheimer's Disease. Front Neurol 2017; 8:580. [PMID: 29163343 PMCID: PMC5681907 DOI: 10.3389/fneur.2017.00580] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2017] [Accepted: 10/17/2017] [Indexed: 01/21/2023] Open
Abstract
Model-based investigations of transneuronal spreading mechanisms in neurodegenerative diseases relate the pattern of pathology severity to the brain's connectivity matrix, which reveals information about how pathology propagates through the connectivity network. Such network models typically use networks based on functional or structural connectivity in young and healthy individuals, and only end-stage patterns of pathology, thereby ignoring/excluding the effects of normal aging and disease progression. Here, we examine the sequence of changes in the elderly brain's anatomical connectivity over the course of a neurodegenerative disease. We do this in a data-driven manner that is not dependent upon clinical disease stage, by using event-based disease progression modeling. Using data from the Alzheimer's Disease Neuroimaging Initiative dataset, we sequence the progressive decline of anatomical connectivity, as quantified by graph-theory metrics, in the Alzheimer's disease brain. Ours is the first single model to contribute to understanding all three of the nature, the location, and the sequence of changes to anatomical connectivity in the human brain due to Alzheimer's disease. Our experimental results reveal new insights into Alzheimer's disease: that degeneration of anatomical connectivity in the brain may be a viable, even early, biomarker and should be considered when studying such neurodegenerative diseases.
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Affiliation(s)
- Neil P. Oxtoby
- Progression of Neurodegenerative Disease Group (POND), Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom
| | - Sara Garbarino
- Progression of Neurodegenerative Disease Group (POND), Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom
| | - Nicholas C. Firth
- Progression of Neurodegenerative Disease Group (POND), Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, United Kingdom
| | - Jason D. Warren
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, United Kingdom
| | - Jonathan M. Schott
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, University College London, London, United Kingdom
| | - Daniel C. Alexander
- Progression of Neurodegenerative Disease Group (POND), Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom
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Jiang W, Li J, Chen X, Ye W, Zheng J. Disrupted Structural and Functional Networks and Their Correlation with Alertness in Right Temporal Lobe Epilepsy: A Graph Theory Study. Front Neurol 2017; 8:179. [PMID: 28515708 PMCID: PMC5413548 DOI: 10.3389/fneur.2017.00179] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2017] [Accepted: 04/18/2017] [Indexed: 11/13/2022] Open
Abstract
Previous studies have shown that temporal lobe epilepsy (TLE) involves abnormal structural or functional connectivity in specific brain areas. However, limited comprehensive studies have been conducted on TLE associated changes in the topological organization of structural and functional networks. Additionally, epilepsy is associated with impairment in alertness, a fundamental component of attention. In this study, structural networks were constructed using diffusion tensor imaging tractography, and functional networks were obtained from resting-state functional MRI temporal series correlations in 20 right temporal lobe epilepsy (rTLE) patients and 19 healthy controls. Global network properties were computed by graph theoretical analysis, and correlations were assessed between global network properties and alertness. The results from these analyses showed that rTLE patients exhibit abnormal small-world attributes in structural and functional networks. Structural networks shifted toward more regular attributes, but functional networks trended toward more random attributes. After controlling for the influence of the disease duration, negative correlations were found between alertness, small-worldness, and the cluster coefficient. However, alertness did not correlate with either the characteristic path length or global efficiency in rTLE patients. Our findings show that disruptions of the topological construction of brain structural and functional networks as well as small-world property bias are associated with deficits in alertness in rTLE patients. These data suggest that reorganization of brain networks develops as a mechanism to compensate for altered structural and functional brain function during disease progression.
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Affiliation(s)
- Wenyu Jiang
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Jianping Li
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Xuemei Chen
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Wei Ye
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Jinou Zheng
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
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Abstract
The temporal dynamics of complex networks such as the Internet are characterized by a power scaling between the temporal mean and dispersion of signals at each network node. Here we tested the hypothesis that the temporal dynamics of the brain networks are characterized by a similar power law. This realization could be useful to assess the effects of randomness and external modulators on the brain network dynamics. Simulated data using a well-stablished random diffusion model allowed us to predict that the temporal dispersion of the amplitude of low frequency fluctuations (ALFF) and that of the local functional connectivity density (lFCD) scale with their temporal means. We tested this hypothesis in open-access resting-state functional magnetic resonance imaging datasets from 66 healthy subjects. A robust power law emerged from the temporal dynamics of ALFF and lFCD metrics, which was insensitive to the methods used for the computation of the metrics. The scaling exponents (ALFF: 0.8 ± 0.1; lFCD: 1.1 ± 0.1; mean ± SD) decreased with age and varied significantly across brain regions; multimodal cortical areas exhibited lower scaling exponents, consistent with a stronger influence of external inputs, than limbic and subcortical regions, which exhibited higher scaling exponents, consistent with a stronger influence of internal randomness. Findings are consistent with the notion that external inputs govern neuronal communication in the brain and that their relative influence differs between brain regions. Further studies will assess the potential of this metric as biomarker to characterize neuropathology.
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Affiliation(s)
- Dardo G Tomasi
- National Institute on Alcohol Abuse and Alcoholism Bethesda, MD, USA
| | | | - Nora D Volkow
- National Institute on Alcohol Abuse and AlcoholismBethesda, MD, USA; National Institute on Drug AbuseBethesda, MD, USA
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37
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Liu X, Zhou F, Li X, Qian W, Cui J, Zhou IY, Luk KD, Wu EX, Hu Y. Organization of the intrinsic functional network in the cervical spinal cord: A resting state functional MRI study. Neuroscience 2016; 336:30-8. [PMID: 27590264 DOI: 10.1016/j.neuroscience.2016.08.042] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2016] [Revised: 08/22/2016] [Accepted: 08/24/2016] [Indexed: 12/29/2022]
Abstract
Resting state functional magnetic resonance imaging (rsfMRI) has been extensively applied to investigate the organization of functional networks in the brain. As an essential part of the central nervous system (CNS), the spinal cord has not been well explored about its intrinsic functional network. In this study, we aim to thoroughly investigate the characteristics of the intrinsic functional network in the spinal cord using rsfMRI. Functional connectivity and graph theory analysis were employed to evaluate the organization of the functional network, including its topology and network communication properties. Furthermore, the reproducibility of rsfMRI analysis on the spinal cord was also examined by intra-class correlation (ICC). Comprehensive evaluation of the intrinsic functional organization presented a non-uniform distribution of topological characteristics of the functional network, in which the upper levels (C2 and C3 vertebral levels) of the cervical spinal cord showed high levels of connectivity. The present results revealed the significance of the upper cervical cord in the intrinsic functional network of the human cervical spinal cord. In addition, this study demonstrated the efficiency of the cervical spinal cord functional network and the reproducibility of rsfMRI analysis on the spinal cord was also confirmed. As knowledge expansion of intrinsic functional network from the brain to the spinal cord, this study shed light on the organization of the spinal cord functional network in both normal development and clinical disorders.
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Huang CH, Wu MY, Chang PMH, Huang CY, Ng KL. In silico identification of potential targets and drugs for non-small cell lung cancer. IET Syst Biol 2014; 8:56-66. [PMID: 25014226 PMCID: PMC8687210 DOI: 10.1049/iet-syb.2013.0035] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2013] [Revised: 12/03/2013] [Accepted: 12/23/2013] [Indexed: 12/28/2022] Open
Abstract
Lung cancer is one of the leading causes of death in both the USA and Taiwan, and it is thought that the cause of cancer could be because of the gain of function of an oncoprotein or the loss of function of a tumour suppressor protein. Consequently, these proteins are potential targets for drugs. In this study, differentially expressed genes are identified, via an expression dataset generated from lung adenocarcinoma tumour and adjacent non-tumour tissues. This study has integrated many complementary resources, that is, microarray, protein-protein interaction and protein complex. After constructing the lung cancer protein-protein interaction network (PPIN), the authors performed graph theory analysis of PPIN. Highly dense modules are identified, which are potential cancer-associated protein complexes. Up- and down-regulated communities were used as queries to perform functional enrichment analysis. Enriched biological processes and pathways are determined. These sets of up- and down-regulated genes were submitted to the Connectivity Map web resource to identify potential drugs. The authors' findings suggested that eight drugs from DrugBank and three drugs from NCBI can potentially reverse certain up- and down-regulated genes' expression. In conclusion, this study provides a systematic strategy to discover potential drugs and target genes for lung cancer.
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Affiliation(s)
- Chien-Hung Huang
- Department of Computer Science and Information Engineering, National Formosa University, 64, Wen-Hwa Road, Hu-wei 632, Yun-Lin, Taiwan
| | - Min-You Wu
- Department of Computer Science and Information Engineering, National Formosa University, 64, Wen-Hwa Road, Hu-wei 632, Yun-Lin, Taiwan
| | - Peter Mu-Hsin Chang
- Division of Hematology and Oncology, Department of Medicine, Taipei Veterans General Hospital, Faculty of Medicine, National Yang Ming University, Taipei 112, Taiwan
| | - Chi-Ying Huang
- Institute of Biopharmaceutical Sciences, National Yang-Ming University, 155, Sec. 2, Linong Street, Taipei 112, Taiwan
| | - Ka-Lok Ng
- School of Pharmacy, China Medical University, Taichung 40402, Taiwan.
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