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Spencer APC, Goodfellow M, Chakkarapani E, Brooks JCW. Resting-state functional connectivity in children cooled for neonatal encephalopathy. Brain Commun 2024; 6:fcae154. [PMID: 38741661 PMCID: PMC11089421 DOI: 10.1093/braincomms/fcae154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 03/21/2024] [Accepted: 04/28/2024] [Indexed: 05/16/2024] Open
Abstract
Therapeutic hypothermia improves outcomes following neonatal hypoxic-ischaemic encephalopathy, reducing cases of death and severe disability such as cerebral palsy compared with normothermia management. However, when cooled children reach early school-age, they have cognitive and motor impairments which are associated with underlying alterations to brain structure and white matter connectivity. It is unknown whether these differences in structural connectivity are associated with differences in functional connectivity between cooled children and healthy controls. Resting-state functional MRI has been used to characterize static and dynamic functional connectivity in children, both with typical development and those with neurodevelopmental disorders. Previous studies of resting-state brain networks in children with hypoxic-ischaemic encephalopathy have focussed on the neonatal period. In this study, we used resting-state fMRI to investigate static and dynamic functional connectivity in children aged 6-8 years who were cooled for neonatal hypoxic-ischaemic without cerebral palsy [n = 22, median age (interquartile range) 7.08 (6.85-7.52) years] and healthy controls matched for age, sex and socioeconomic status [n = 20, median age (interquartile range) 6.75 (6.48-7.25) years]. Using group independent component analysis, we identified 31 intrinsic functional connectivity networks consistent with those previously reported in children and adults. We found no case-control differences in the spatial maps of these intrinsic connectivity networks. We constructed subject-specific static functional connectivity networks by measuring pairwise Pearson correlations between component time courses and found no case-control differences in functional connectivity after false discovery rate correction. To study the time-varying organization of resting-state networks, we used sliding window correlations and deep clustering to investigate dynamic functional connectivity characteristics. We found k = 4 repetitively occurring functional connectivity states, which exhibited no case-control differences in dwell time, fractional occupancy or state functional connectivity matrices. In this small cohort, the spatiotemporal characteristics of resting-state brain networks in cooled children without severe disability were too subtle to be differentiated from healthy controls at early school-age, despite underlying differences in brain structure and white matter connectivity, possibly reflecting a level of recovery of healthy resting-state brain function. To our knowledge, this is the first study to investigate resting-state functional connectivity in children with hypoxic-ischaemic encephalopathy beyond the neonatal period and the first to investigate dynamic functional connectivity in any children with hypoxic-ischaemic encephalopathy.
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Affiliation(s)
- Arthur P C Spencer
- Clinical Research and Imaging Centre, University of Bristol, Bristol BS2 8DX, UK
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 1TH, UK
- Department of Radiology, Lausanne University Hospital, 1011 Lausanne, Switzerland
| | - Marc Goodfellow
- Living Systems Institute, University of Exeter, Exeter EX4 4QD, UK
- Department of Mathematics and Statistics, University of Exeter, Exeter EX4 4QF, UK
| | - Ela Chakkarapani
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 1TH, UK
- Neonatal Intensive Care Unit, St Michaels Hospital, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol BS2 8EG, UK
| | - Jonathan C W Brooks
- Clinical Research and Imaging Centre, University of Bristol, Bristol BS2 8DX, UK
- University of East Anglia Wellcome Wolfson Brain Imaging Centre (UWWBIC), University of East Anglia, Norwich NR4 7TJ, UK
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Wang H, Zhu Z, Bi H, Jiang Z, Cao Y, Wang S, Zou L. Changes in Community Structure of Brain Dynamic Functional Connectivity States in Mild Cognitive Impairment. Neuroscience 2024; 544:1-11. [PMID: 38423166 DOI: 10.1016/j.neuroscience.2024.02.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 01/22/2024] [Accepted: 02/24/2024] [Indexed: 03/02/2024]
Abstract
Recent researches have noted many changes of short-term dynamic modalities in mild cognitive impairment (MCI) patients' brain functional networks. In this study, the dynamic functional brain networks of 82 MCI patients and 85 individuals in the normal control (NC) group were constructed using the sliding window method and Pearson correlation. The window size was determined using single-scale time-dependent (SSTD) method. Subsequently, k-means was applied to cluster all window samples, identifying three dynamic functional connectivity (DFC) states. Collective sparse symmetric non-negative matrix factorization (cssNMF) was then used to perform community detection on these states and quantify differences in brain regions. Finally, metrics such as within-community connectivity strength, community strength, and node diversity were calculated for further analysis. The results indicated high similarity between the two groups in state 2, with no significant differences in optimal community quantity and functional segregation (p < 0.05). However, for state 1 and state 3, the optimal community quantity was smaller in MCI patients compared to the NC group. In state 1, MCI patients had lower within-community connectivity strength and overall strength than the NC group, whereas state 3 showed results opposite to state 1. Brain regions with statistical difference included MFG.L, ORBinf.R, STG.R, IFGtriang.L, CUN.L, CUN.R, LING.R, SOG.L, and PCUN.R. This study on DFC states explores changes in the brain functional networks of patients with MCI from the perspective of alterations in the community structures of DFC states. The findings could provide new insights into the pathological changes in the brains of MCI patients.
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Affiliation(s)
- Hongwei Wang
- School of Computer Science and Artificial Intelligence, Aliyun School of Big Data, School of Software, Changzhou University, Changzhou, Jiangsu 213164, China
| | - Zhihao Zhu
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou, Jiangsu 213164, China
| | - Hui Bi
- School of Computer Science and Artificial Intelligence, Aliyun School of Big Data, School of Software, Changzhou University, Changzhou, Jiangsu 213164, China
| | - Zhongyi Jiang
- School of Computer Science and Artificial Intelligence, Aliyun School of Big Data, School of Software, Changzhou University, Changzhou, Jiangsu 213164, China
| | - Yin Cao
- The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou, Jiangsu 213164, China
| | - Suhong Wang
- Clinical Psychology, The Third Affiliated Hospital of Soochow University, Juqian Road No. 185, Changzhou, Jiangsu 213164, China
| | - Ling Zou
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou, Jiangsu 213164, China; The Key Laboratory of Brain Machine Collaborative Intelligence Foundation of Zhejiang Province, Hangzhou, Zhejiang 310018, China.
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Li D, Hou D, Zhang Y, Zhao Y, Cui X, Niu Y, Xiang J, Wang B. Aberrant Functional Connectivity in Core-Periphery Structure Based on WSBM in ADHD. J Atten Disord 2024; 28:415-430. [PMID: 38102929 DOI: 10.1177/10870547231214985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2023]
Abstract
OBJECTIVE Brain network studies have revealed that the community structure of ADHD is altered. However, these studies have only focused on modular community structure, ignoring the core-periphery community structure. METHOD This paper employed the weighted stochastic block model to divide the functional connectivity (FC) into 10 communities. And we adopted core score to define the core-periphery structure of FC. Finally, connectivity strength (CS) and disruption index (DI) were used to evaluate the changes of core-periphery structure in ADHD. RESULTS The core community of visual network showed reduced CS and a positive value of DI, while the CS of periphery community was enhanced. In addition, the interaction between core communities (involving the sensorimotor and visual network) and periphery community of attention network showed increased CS and a negative valve of DI. CONCLUSION Anomalies in core-periphery community structure provide a new perspective for understanding the community structure of ADHD.
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Affiliation(s)
- Dandan Li
- Taiyuan University of Technology, Shanxi, China
| | - Dianni Hou
- Taiyuan University of Technology, Shanxi, China
| | | | - Yao Zhao
- Taiyuan University of Technology, Shanxi, China
| | | | - Yan Niu
- Taiyuan University of Technology, Shanxi, China
| | - Jie Xiang
- Taiyuan University of Technology, Shanxi, China
| | - Bin Wang
- Taiyuan University of Technology, Shanxi, China
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Xiang J, Sun Y, Wu X, Guo Y, Xue J, Niu Y, Cui X. Abnormal Spatial and Temporal Overlap of Time-Varying Brain Functional Networks in Patients with Schizophrenia. Brain Sci 2023; 14:40. [PMID: 38248255 PMCID: PMC10813230 DOI: 10.3390/brainsci14010040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 12/25/2023] [Accepted: 12/27/2023] [Indexed: 01/23/2024] Open
Abstract
Schizophrenia (SZ) is a complex psychiatric disorder with unclear etiology and pathological features. Neuroscientists are increasingly proposing that schizophrenia is an abnormality in the dynamic organization of brain networks. Previous studies have found that the dynamic brain networks of people with SZ are abnormal in both space and time. However, little is known about the interactions and overlaps between hubs of the brain underlying spatiotemporal dynamics. In this study, we aimed to investigate different patterns of spatial and temporal overlap of hubs between SZ patients and healthy individuals. Specifically, we obtained resting-state functional magnetic resonance imaging data from the public dataset for 43 SZ patients and 49 healthy individuals. We derived a representation of time-varying functional connectivity using the Jackknife Correlation (JC) method. We employed the Betweenness Centrality (BC) method to identify the hubs of the brain's functional connectivity network. We then applied measures of temporal overlap, spatial overlap, and hierarchical clustering to investigate differences in the organization of brain hubs between SZ patients and healthy controls. Our findings suggest significant differences between SZ patients and healthy controls at the whole-brain and subnetwork levels. Furthermore, spatial overlap and hierarchical clustering analysis showed that quasi-periodic patterns were disrupted in SZ patients. Analyses of temporal overlap revealed abnormal pairwise engagement preferences in the hubs of SZ patients. These results provide new insights into the dynamic characteristics of the network organization of the SZ brain.
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Affiliation(s)
- Jie Xiang
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China; (J.X.); (Y.S.); (X.W.); (J.X.); (Y.N.)
| | - Yumeng Sun
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China; (J.X.); (Y.S.); (X.W.); (J.X.); (Y.N.)
| | - Xubin Wu
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China; (J.X.); (Y.S.); (X.W.); (J.X.); (Y.N.)
| | - Yuxiang Guo
- School of Software, Taiyuan University of Technology, Taiyuan 030024, China;
| | - Jiayue Xue
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China; (J.X.); (Y.S.); (X.W.); (J.X.); (Y.N.)
| | - Yan Niu
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China; (J.X.); (Y.S.); (X.W.); (J.X.); (Y.N.)
| | - Xiaohong Cui
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China; (J.X.); (Y.S.); (X.W.); (J.X.); (Y.N.)
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Guo Y, Xu X, Li T, Chen H, Wang X, Huang W, Liu T, Kong Q, Chen F. Dynamic functional connectivity changes associated with decreased memory performance in betel quid dependence. Addict Biol 2023; 28:e13329. [PMID: 37753571 DOI: 10.1111/adb.13329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 07/17/2023] [Accepted: 08/15/2023] [Indexed: 09/28/2023]
Abstract
The temporal variability of the dynamic functional connectivity (dFC) has been suggested as a useful metric for studying abnormal cognitive function. This study aimed to explore the associations between the temporal properties of dFC and memory performance in betel quid dependence (BQD). Sixty-four BQD individuals and 47 gender- and age-matched healthy controls (HCs) underwent functional magnetic resonance imaging and a series of neuropsychological assessments. The dFC was constructed by calculating the Pearson correlation coefficients within a sliding window and was clustered into three functional connectivity states using k-means clustering. The dFC temporal properties derived from the cluster results were compared between the BQD and HC groups. The results showed that States 1 and 3 featured more frequent and weak connectivity, and State 2 featured less frequent and strong connectivity. There were significant differences for mean dwell time (MDT) in State 3 (p = 0.022) and fraction of time in State 2 (p = 0.018) between the BQD and HC groups. Pearson correlation analyses showed that the MDT in State 1 was negatively correlated with long delay free recall and short delay free recall, and the MDT in State 3 was positively correlated with false positive of long delay recall. Our findings provide strong evidence that MDT match the memory performance and suggest new insights into the pathophysiological mechanism of memory disorders in BQD individuals.
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Affiliation(s)
- Yihao Guo
- Department of Radiology, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), Haikou, Hainan, China
| | - Xiaoling Xu
- Department of Radiology, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), Haikou, Hainan, China
| | - Tiansheng Li
- Department of Radiology, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), Haikou, Hainan, China
| | - Huijuan Chen
- Department of Radiology, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), Haikou, Hainan, China
| | - Xiaoyi Wang
- Department of Radiology, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), Haikou, Hainan, China
| | - Weiyuan Huang
- Department of Radiology, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), Haikou, Hainan, China
| | - Tao Liu
- Department of Geriatric Center, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), Haikou, Hainan, China
| | - Qingle Kong
- MR Collaboration, Siemens Healthineers Ltd., Beijing, China
| | - Feng Chen
- Department of Radiology, Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), Haikou, Hainan, China
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Misra R, Gandhi TK. Functional Connectivity Dynamics show Resting-State Instability and Rightward Parietal Dysfunction in ADHD. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38083173 DOI: 10.1109/embc40787.2023.10340842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Attention Deficit/Hyperactivity Disorder (ADHD) is one of the most common neurodevelopmental disorders in children and is characterised by inattention, impulsiveness and hyperactivity. While several studies have analysed the static functional connectivity in the resting-state functional MRI (rs-fMRI) of ADHD patients, detailed investigations are required to characterize the connectivity dynamics in the brain. In an attempt to establish a link between attention instability and the dynamic properties of Functional Connectivity (FC), we investigated the differences in temporal variability of FC between 40 children with ADHD and 40 Typically Developing (TD) children. Using a sliding-window method to segment the rs-fMRI scans in time, we employed seed-to-voxel correlation analysis for each window to obtain time-evolving seed connectivity maps for seeds placed in the posterior cingulate cortex (PCC) and the medial prefrontal cortex (mPFC). For each subject, the standard deviation of the voxel connectivity time series was used as a measure of the temporal variability of FC. Results showed that ADHD patients exhibited significantly higher variability in dFC than TD children in the cingulo-temporal, cingulo-parietal, fronto-temporal, and fronto-parietal networks ( pFW E < 0.05). Atypical temporal variability was observed in the left and right temporal gyri, the anterior cingulate cortex, and lateral regions of the right parietal cortex. The observations are consistent with visual attention issues, executive control deficit, and rightward parietal dysfunction reported in ADHD, respectively. These results help in understanding the disorder with a fresh perspective linking behavioural inattention with instability in FC in the brain.
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