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Fotiadis P, Parkes L, Davis KA, Satterthwaite TD, Shinohara RT, Bassett DS. Structure-function coupling in macroscale human brain networks. Nat Rev Neurosci 2024:10.1038/s41583-024-00846-6. [PMID: 39103609 DOI: 10.1038/s41583-024-00846-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/03/2024] [Indexed: 08/07/2024]
Abstract
Precisely how the anatomical structure of the brain gives rise to a repertoire of complex functions remains incompletely understood. A promising manifestation of this mapping from structure to function is the dependency of the functional activity of a brain region on the underlying white matter architecture. Here, we review the literature examining the macroscale coupling between structural and functional connectivity, and we establish how this structure-function coupling (SFC) can provide more information about the underlying workings of the brain than either feature alone. We begin by defining SFC and describing the computational methods used to quantify it. We then review empirical studies that examine the heterogeneous expression of SFC across different brain regions, among individuals, in the context of the cognitive task being performed, and over time, as well as its role in fostering flexible cognition. Last, we investigate how the coupling between structure and function is affected in neurological and psychiatric conditions, and we report how aberrant SFC is associated with disease duration and disease-specific cognitive impairment. By elucidating how the dynamic relationship between the structure and function of the brain is altered in the presence of neurological and psychiatric conditions, we aim to not only further our understanding of their aetiology but also establish SFC as a new and sensitive marker of disease symptomatology and cognitive performance. Overall, this Review collates the current knowledge regarding the regional interdependency between the macroscale structure and function of the human brain in both neurotypical and neuroatypical individuals.
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Affiliation(s)
- Panagiotis Fotiadis
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Anaesthesiology, University of Michigan, Ann Arbor, MI, USA.
| | - Linden Parkes
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Kathryn A Davis
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Theodore D Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing & Analytics, University of Pennsylvania, Philadelphia, PA, USA
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing & Analytics, University of Pennsylvania, Philadelphia, PA, USA
| | - Dani S Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, PA, USA.
- Santa Fe Institute, Santa Fe, NM, USA.
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Ke M, Wang F, Liu G. Altered effective connectivity of the default mode network in juvenile myoclonic epilepsy. Cogn Neurodyn 2024; 18:1549-1561. [PMID: 39104702 PMCID: PMC11297871 DOI: 10.1007/s11571-023-09994-4] [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: 03/23/2023] [Revised: 06/29/2023] [Accepted: 07/17/2023] [Indexed: 08/07/2024] Open
Abstract
Juvenile myoclonic epilepsy (JME) is associated with brain dysconnectivity in the default mode network (DMN). Most previous studies of patients with JME have assessed static functional connectivity in terms of the temporal correlation of signal intensity among different brain regions. However, more recent studies have shown that the directionality of brain information flow has a more significant regional impact on patients' brains than previously assumed in the present study. Here, we introduced an empirical approach incorporating independent component analysis (ICA) and spectral dynamic causal modeling (spDCM) analysis to study the variation in effective connectivity in DMN in JME patients. We began by collecting resting-state functional magnetic resonance imaging (rs-fMRI) data from 37 patients and 37 matched controls. Then, we selected 8 key nodes within the DMN using ICA; finally, the key nodes were analyzed for effective connectivity using spDCM to explore the information flow and detect patient abnormalities. This study found that compared with normal subjects, patients with JME showed significant changes in the effective connectivity among the precuneus, hippocampus, and lingual gyrus (p < 0.05 with false discovery rate (FDR) correction) with most of the effective connections being strengthened. In addition, previous studies have found that the self-connection of normal subjects' nodes showed strong inhibition, but the self-connection inhibition of the anterior cingulate cortex and lingual gyrus of the patient was decreased in this experiment (p < 0.05 with FDR correction); as the activity in these areas decreased, the nodes connected to them all appeared abnormal. We believe that the changes in the effective connectivity of nodes within the DMN are accompanied by changes in information transmission that lead to changes in brain function and impaired cognitive and executive function in patients with JME. Overall, our findings extended the dysconnectivity hypothesis in JME from static to dynamic causal and demonstrated that aberrant effective connectivity may underlie abnormal brain function in JME patients at early phase of illness, contributing to the understanding of the pathogenesis of JME. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-023-09994-4.
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Affiliation(s)
- Ming Ke
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050 China
| | - Feng Wang
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050 China
| | - Guangyao Liu
- Department of Nuclear Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, 730030 China
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Sun YW, Lyu XY, Lei XY, Huang MM, Wang ZM, Gao B. Association study of brain structure-function coupling and glymphatic system function in patients with mild cognitive impairment due to Alzheimer's disease. Front Neurosci 2024; 18:1417986. [PMID: 39139498 PMCID: PMC11320604 DOI: 10.3389/fnins.2024.1417986] [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: 04/15/2024] [Accepted: 07/17/2024] [Indexed: 08/15/2024] Open
Abstract
Background Mild cognitive impairment (MCI) is a critical transitional phase from healthy cognitive aging to dementia, offering a unique opportunity for early intervention. However, few studies focus on the correlation of brain structure and functional activity in patients with MCI due to Alzheimer's disease (AD). Elucidating the complex interactions between structural-functional (SC-FC) brain connectivity and glymphatic system function is crucial for understanding this condition. Method The aims of this study were to explore the relationship among SC-FC coupling values, glymphatic system function and cognitive function. 23 MCI patients and 18 healthy controls (HC) underwent diffusion tensor imaging (DTI) and resting-state functional MRI (fMRI). DTI analysis along the perivascular space (DTI-ALPS) index and SC-FC coupling values were calculated using DTI and fMRI. Correlation analysis was conducted to assess the relationship between Mini-Mental State Examination (MMSE) scores, DTI-ALPS index, and coupling values. Receiver operating characteristic (ROC) curves was conducted on the SC-FC coupling between the whole brain and subnetworks. The correlation of coupling values with MMSE scores was also analyzed. Result MCI patients (67.74 ± 6.99 years of age) exhibited significantly lower coupling in the whole-brain network and subnetworks, such as the somatomotor network (SMN) and ventral attention network (VAN), than HCs (63.44 ± 6.92 years of age). Whole-brain network coupling was positively correlated with dorsal attention network (DAN), SMN, and visual network (VN) coupling. MMSE scores were significantly positively correlated with whole-brain coupling and SMN coupling. In MCI, whole-brain network demonstrated the highest performance, followed by the SMN and VAN, with the VN, DAN, limbic network (LN), frontoparietal network (FPN), and default mode network (DMN). Compared to HCs, lower DTI-ALPS index was observed in individuals with MCI. Additionally, the left DTI-ALPS index showed a significant positive correlation with MMSE scores and coupling values in the whole-brain network and SMN. Conclusion These findings reveal the critical role of SC-FC coupling values and the ALPS index in cognitive function of MCI. The positive correlations observed in the left DTI-ALPS and whole-brain and SMN coupling values provide a new insight for investigating the asymmetrical nature of cognitive impairments.
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Affiliation(s)
- Yong-Wen Sun
- Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Xin-Yue Lyu
- Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Xiao-Yang Lei
- Department of Neurology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Ming-Ming Huang
- Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
| | - Zhen-Min Wang
- Key Laboratory of Brain Imaging, Guizhou Medical University, Guiyang, China
| | - Bo Gao
- Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China
- Key Laboratory of Brain Imaging, Guizhou Medical University, Guiyang, China
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Wang Y, Zhu D, Zhao L, Wang X, Zhang Z, Hu B, Wu D, Zheng W. Profiling cortical morphometric similarity in perinatal brains: Insights from development, sex difference, and inter-individual variation. Neuroimage 2024; 295:120660. [PMID: 38815676 DOI: 10.1016/j.neuroimage.2024.120660] [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: 02/23/2024] [Revised: 05/17/2024] [Accepted: 05/28/2024] [Indexed: 06/01/2024] Open
Abstract
The topological organization of the macroscopic cortical networks important for the development of complex brain functions. However, how the cortical morphometric organization develops during the third trimester and whether it demonstrates sexual and individual differences at this particular stage remain unclear. Here, we constructed the morphometric similarity network (MSN) based on morphological and microstructural features derived from multimodal MRI of two independent cohorts (cross-sectional and longitudinal) scanned at 30-44 postmenstrual weeks (PMW). Sex difference and inter-individual variations of the MSN were also examined on these cohorts. The cross-sectional analysis revealed that both network integration and segregation changed in a nonlinear biphasic trajectory, which was supported by the results obtained from longitudinal analysis. The community structure showed remarkable consistency between bilateral hemispheres and maintained stability across PMWs. Connectivity within the primary cortex strengthened faster than that within high-order communities. Compared to females, male neonates showed a significant reduction in the participation coefficient within prefrontal and parietal cortices, while their overall network organization and community architecture remained comparable. Furthermore, by using the morphometric similarity as features, we achieved over 65 % accuracy in identifying an individual at term-equivalent age from images acquired after birth, and vice versa. These findings provide comprehensive insights into the development of morphometric similarity throughout the perinatal cortex, enhancing our understanding of the establishment of neuroanatomical organization during early life.
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Affiliation(s)
- Ying Wang
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Dalin Zhu
- Department of Medical Imaging Center, Gansu Provincial Maternity and Child-Care Hospital, Lanzhou, China
| | - Leilei Zhao
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Xiaomin Wang
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Zhe Zhang
- Institute of Brain Science, Hangzhou Normal University, Hangzhou, China; School of Physics, Hangzhou Normal University, Hangzhou, China
| | - Bin Hu
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China; School of Medical Technology, Beijing Institute of Technology, Beijing, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
| | - Weihao Zheng
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China.
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Stam CJ. Hub overload and failure as a final common pathway in neurological brain network disorders. Netw Neurosci 2024; 8:1-23. [PMID: 38562292 PMCID: PMC10861166 DOI: 10.1162/netn_a_00339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 09/26/2023] [Indexed: 04/04/2024] Open
Abstract
Understanding the concept of network hubs and their role in brain disease is now rapidly becoming important for clinical neurology. Hub nodes in brain networks are areas highly connected to the rest of the brain, which handle a large part of all the network traffic. They also show high levels of neural activity and metabolism, which makes them vulnerable to many different types of pathology. The present review examines recent evidence for the prevalence and nature of hub involvement in a variety of neurological disorders, emphasizing common themes across different types of pathology. In focal epilepsy, pathological hubs may play a role in spreading of seizure activity, and removal of such hub nodes is associated with improved outcome. In stroke, damage to hubs is associated with impaired cognitive recovery. Breakdown of optimal brain network organization in multiple sclerosis is accompanied by cognitive dysfunction. In Alzheimer's disease, hyperactive hub nodes are directly associated with amyloid-beta and tau pathology. Early and reliable detection of hub pathology and disturbed connectivity in Alzheimer's disease with imaging and neurophysiological techniques opens up opportunities to detect patients with a network hyperexcitability profile, who could benefit from treatment with anti-epileptic drugs.
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Affiliation(s)
- Cornelis Jan Stam
- Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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Rainer LJ, Kuchukhidze G, Trinka E, Braun M, Kronbichler M, Langthaler P, Zimmermann G, Kronbichler L, Said-Yürekli S, Kirschner M, Zamarian L, Schmid E, Jokeit H, Höfler J. Recognition and perception of emotions in juvenile myoclonic epilepsy. Epilepsia 2023; 64:3319-3330. [PMID: 37795683 DOI: 10.1111/epi.17783] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 09/26/2023] [Accepted: 09/28/2023] [Indexed: 10/06/2023]
Abstract
OBJECTIVE Perception and recognition of emotions are fundamental prerequisites of human life. Patients with juvenile myoclonic epilepsy (JME) may have emotional and behavioral impairments that might influence socially desirable interactions. We aimed to investigate perception and recognition of emotions in patients with JME by means of neuropsychological tests and functional magnetic resonance imaging (fMRI). METHODS Sixty-five patients with JME (median age = 27 years, interquartile range [IQR] = 23-34) were prospectively recruited at the Department of Neurology, Christian Doppler University Hospital, Paracelsus Medical University, Salzburg, Austria. Patients were compared to 68 healthy controls (median age = 24 years, IQR = 21-31), matched for sex, age, and education. All study participants underwent the Networks of Emotion Processing test battery (NEmo), an fMRI paradigm of "dynamic fearful faces," a structured interview for psychiatric and personality disorders, and comprehensive neuropsychological testing. RESULTS JME patients versus healthy controls demonstrated significant deficits in emotion recognition in facial and verbal tasks of all emotions, especially fear. fMRI revealed decreased amygdala activation in JME patients as compared to healthy controls. Patients were at a higher risk of experiencing psychiatric disorders as compared to healthy controls. Cognitive evaluation revealed impaired attentional and executive functioning, namely psychomotor speed, tonic alertness, divided attention, mental flexibility, and inhibition of automated reactions. Duration of epilepsy correlated negatively with parallel prosodic and facial emotion recognition in NEmo. Deficits in emotion recognition were not associated with psychiatric comorbidities, impaired attention and executive functions, types of seizures, and treatment. SIGNIFICANCE This prospective study demonstrated that as compared to healthy subjects, patients with JME had significant deficits in recognition and perception of emotions as shown by neuropsychological tests and fMRI. The results of this study may have importance for psychological/psychotherapeutic interventions in the management of patients with JME.
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Affiliation(s)
- Lucas Johannes Rainer
- Department of Neurology, Christian Doppler University Hospital, Paracelsus Medical University, Center for Cognitive Neuroscience Salzburg, member of the European Reference Network EpiCARE, Salzburg, Austria
- Neuroscience Institute, Christian Doppler University Hospital, Center for Cognitive Neuroscience, Salzburg, Austria
- Department of Child and Adolescent Psychiatry, Christian Doppler University Hospital, Paracelsus Medical University, Salzburg, Austria
| | - Giorgi Kuchukhidze
- Department of Neurology, Christian Doppler University Hospital, Paracelsus Medical University, Center for Cognitive Neuroscience Salzburg, member of the European Reference Network EpiCARE, Salzburg, Austria
- Neuroscience Institute, Christian Doppler University Hospital, Center for Cognitive Neuroscience, Salzburg, Austria
| | - Eugen Trinka
- Department of Neurology, Christian Doppler University Hospital, Paracelsus Medical University, Center for Cognitive Neuroscience Salzburg, member of the European Reference Network EpiCARE, Salzburg, Austria
- Neuroscience Institute, Christian Doppler University Hospital, Center for Cognitive Neuroscience, Salzburg, Austria
- Department of Public Health, Health Services Research and Health Technology Assessment, University for Health Sciences, Medical Informatics, and Technology, Hall in Tirol, Austria
- Karl-Landsteiner Institute for Neurorehabilitation and Space Neurology, Salzburg, Austria
| | - Mario Braun
- Center for Cognitive Neuroscience/Department of Psychology, Faculty of Natural Sciences, Paris Lodron University, Salzburg, Austria
| | - Martin Kronbichler
- Neuroscience Institute, Christian Doppler University Hospital, Center for Cognitive Neuroscience, Salzburg, Austria
- Center for Cognitive Neuroscience/Department of Psychology, Faculty of Natural Sciences, Paris Lodron University, Salzburg, Austria
| | - Patrick Langthaler
- Department of Neurology, Christian Doppler University Hospital, Paracelsus Medical University, Center for Cognitive Neuroscience Salzburg, member of the European Reference Network EpiCARE, Salzburg, Austria
- Department of Mathematics, Faculty of Natural Sciences, Paris Lodron University, Salzburg, Austria
| | - Georg Zimmermann
- Team Biostatistics and Big Medical Data, Lab for Intelligent Data Analytics Salzburg, Paracelsus Medical University, Salzburg, Austria
- Research and Innovation Management, Paracelsus Medical University, Salzburg, Austria
| | - Lisa Kronbichler
- Neuroscience Institute, Christian Doppler University Hospital, Center for Cognitive Neuroscience, Salzburg, Austria
- Department of Child and Adolescent Psychiatry, Christian Doppler University Hospital, Paracelsus Medical University, Salzburg, Austria
| | - Sarah Said-Yürekli
- Department of Neurology, Christian Doppler University Hospital, Paracelsus Medical University, Center for Cognitive Neuroscience Salzburg, member of the European Reference Network EpiCARE, Salzburg, Austria
- Center for Cognitive Neuroscience/Department of Psychology, Faculty of Natural Sciences, Paris Lodron University, Salzburg, Austria
| | - Margarita Kirschner
- Department of Neurology, Christian Doppler University Hospital, Paracelsus Medical University, Center for Cognitive Neuroscience Salzburg, member of the European Reference Network EpiCARE, Salzburg, Austria
| | - Laura Zamarian
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Elisabeth Schmid
- Department of Child and Adolescent Psychiatry, Christian Doppler University Hospital, Paracelsus Medical University, Salzburg, Austria
| | | | - Julia Höfler
- Department of Neurology, Christian Doppler University Hospital, Paracelsus Medical University, Center for Cognitive Neuroscience Salzburg, member of the European Reference Network EpiCARE, Salzburg, Austria
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Lin Q, Li W, Li Y, Liu P, Zhang Y, Gong Q, Zhou D, An D. Aberrant structural rich club organization in temporal lobe epilepsy with focal to bilateral tonic-clonic seizures. Neuroimage Clin 2023; 40:103536. [PMID: 37944396 PMCID: PMC10663961 DOI: 10.1016/j.nicl.2023.103536] [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: 05/30/2023] [Revised: 09/19/2023] [Accepted: 10/31/2023] [Indexed: 11/12/2023]
Abstract
OBJECTIVE The purpose of this study was to assess the differences of topological characteristic and rich club organization between temporal lobe epilepsy (TLE) patients with focal seizure (FS) only and those with focal to bilateral tonic-clonic seizures (FBTCS). METHODS We recruited 130 unilateral TLE patients, of which 57 patients with FS only and 73 patients with both FS and FBTCS, and 68 age- and gender-matched healthy controls (HC). Whole-brain networks were constructed based on diffusion weighted imaging data. Graph theory was applied to quantify the topological network metrics and rich club organization. Network-based statistic (NBS) analysis was administered to investigate the difference in edge-wise connectivity strength. The non-parametric permutation test was applied to evaluate the differences between groups. Benjamini-Hochberg FDR at the alpha of 5% was carried out for multiple comparations. RESULTS In comparison with HC, both the FS and FBTCS group displayed a significant reduction in whole-brain connectivity strength and global efficiency. The FBTCS group showed lower connectivity strength both in the rich club and feeder connections compared to HC. The FS group had lower connectivity strength in the feeder and local connections compared to HC. NBS analysis revealed a wider range of decreased connectivity strength in the FBTCS group, involving 90% of the rich club regions, mainly affecting temporal-subcortical, frontal-parietal, and frontal-temporal lobe, the majority decreasing connections were between temporal lobe and stratum. While the decreased connectivity strength in the FS group were relatively local, involving 50% of rich club regions, mainly concentrated on the temporal-subcortical lobe. CONCLUSIONS Network integration was reduced in TLE. TLE with FBTCS selectively disrupted the rich club regions, while TLE with FS only were more likely to affect the non-rich club regions, emphasizing the contribution of rich club organization to seizure generalization.
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Affiliation(s)
- Qiuxing Lin
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wei Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yuming Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Peiwen Liu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yingying Zhang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Dongmei An
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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Sheng Y, Yang S, Rao J, Zhang Q, Li J, Wang D, Zheng W. Age of Bilingual Onset Shapes the Dynamics of Functional Connectivity and Laterality in the Resting-State. Brain Sci 2023; 13:1231. [PMID: 37759832 PMCID: PMC10526135 DOI: 10.3390/brainsci13091231] [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: 06/27/2023] [Revised: 08/11/2023] [Accepted: 08/21/2023] [Indexed: 09/29/2023] Open
Abstract
Bilingualism is known to enhance cognitive function and flexibility of the brain. However, it is not clear how bilingual experience affects the time-varying functional network and whether these changes depend on the age of bilingual onset. This study intended to investigate the bilingual-related dynamic functional connectivity (dFC) based on the resting-state functional magnetic resonance images, including 23 early bilinguals (EBs), 30 late bilinguals (LBs), and 31 English monolinguals. The analysis identified two dFC states, and LBs showed more transitions between these states than monolinguals. Moreover, more frequent left-right switches were found in functional laterality in prefrontal, lateral temporal, lateral occipital, and inferior parietal cortices in EBs compared with LB and monolingual cohorts, and the laterality changes in the anterior superior temporal cortex were negatively correlated with L2 proficiency. These findings highlight how the age of L2 acquisition affects cortico-cortical dFC pattern and provide insight into the neural mechanisms of bilingualism.
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Affiliation(s)
- Yucen Sheng
- School of Foreign Languages, Lanzhou Jiaotong University, Lanzhou 730070, China
| | - Songyu Yang
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
| | - Juan Rao
- School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
| | - Qin Zhang
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
| | - Jialong Li
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
| | - Dianjian Wang
- School of Foreign Languages, Lanzhou Jiaotong University, Lanzhou 730070, China
| | - Weihao Zheng
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
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9
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Dong Q, Li J, Ju Y, Xiao C, Li K, Shi B, Zheng W, Zhang Y. Altered Relationship between Functional Connectivity and Fiber-Bundle Structure in High-Functioning Male Adults with Autism Spectrum Disorder. Brain Sci 2023; 13:1098. [PMID: 37509029 PMCID: PMC10377258 DOI: 10.3390/brainsci13071098] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 07/04/2023] [Accepted: 07/18/2023] [Indexed: 07/30/2023] Open
Abstract
Autism spectrum disorder (ASD) is a pervasive neurodevelopmental disorder characterized by abnormalities in structure and function of the brain. However, how ASD affects the relationship between fiber-bundle microstructures and functional connectivity (FC) remains unclear. Here, we analyzed structural and functional images of 26 high-functioning adult males with ASD, alongside 26 age-, gender-, and full-scale IQ-matched typically developing controls (TDCs) from the BNI dataset in the ABIDE database. We utilized fixel-based analysis to extract microstructural information from fiber tracts, which was then used to predict FC using a multilinear model. Our results revealed that the structure-function relationships in both ASD and TDC cohorts were strongly aligned in the primary cortex but decoupled in the high-order cortex, and the ASD patients exhibited reduced structure-function relationships throughout the cortex compared to the TDCs. Furthermore, we observed that the disrupted relationships in ASD were primarily driven by alterations in FC rather than fiber-bundle microstructures. The structure-function relationships in the left superior parietal cortex, right precentral and inferior temporal cortices, and bilateral insula could predict individual differences in clinical symptoms of ASD patients. These findings underscore the significance of altered relationships between fiber-bundle microstructures and FC in the etiology of ASD.
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Affiliation(s)
- Qiangli Dong
- Department of Psychiatry, Lanzhou University Second Hospital, Lanzhou 730000, China
| | - Jialong Li
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
| | - Yumeng Ju
- Department of Psychiatry & National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Chuman Xiao
- Department of Psychiatry & National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Kangning Li
- Department of Psychiatry & National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Bin Shi
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
| | - Weihao Zheng
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
| | - Yan Zhang
- Department of Psychiatry & National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China
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Wu D, Wang X, Lin S, Xu G, Tian J, Ma X. Predicting insomnia severity using structure-function coupling in female chronic insomnia patients. Behav Brain Res 2023; 441:114283. [PMID: 36621579 DOI: 10.1016/j.bbr.2023.114283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 12/13/2022] [Accepted: 01/02/2023] [Indexed: 01/07/2023]
Abstract
Functional connectivity between brain regions is constrained by the underlying structural pathways. However, how this structure-function coupling is disrupted in female patients with insomnia disorder is unclear. This study examines if the whole-brain pattern of structure-function coupling could be used to predict unseen female patients' insomnia severity index. Resting-state functional MRI and diffusion-weighted imaging were performed in 82 female participants with chronic insomnia. Structure-function coupling was computed using the Spearman rank correlations between structural and functional connectivity profiles. Using relevance vector regression approach and 10-fold cross-validation, we predicted the individuals' insomnia severity index using the pattern of whole-brain structure-function coupling. Finally, we extracted the contribution of each regional coupling to the prediction model. The pattern of structure-function coupling could be used to significantly predict unseen individuals' insomnia severity index scores (r = 0.29, permutation P < 0.001; mean absolute error (MAE) = 4.59, permutation P < 0.001). Moreover, the brain regions with high functional hierarchy, including regions in the default mode network, mainly displayed negative contribution weights, while the regions with lower functional hierarchy, including occipital regions and the precentral gyrus, mainly displayed positive contribution weights. This is the first study to demonstrate an association between structure-function coupling and the insomnia severity index in females with insomnia disorder. Importantly, our data suggest that insomnia severity is associated with a reduction in structure-function coupling in higher-order brain regions and an increase in structure-function coupling in lower-order brain regions.
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Affiliation(s)
- Dongyan Wu
- Department of Neurology, China-Japan Friendship Hospital, Beijing, PR China
| | - Xinzhi Wang
- Department of Radiology, Guangdong Second Provincial General Hospital, Guangzhou, PR China
| | - Shiqi Lin
- Department of Radiology, Guangdong Second Provincial General Hospital, Guangzhou, PR China
| | - Guang Xu
- Department of Neurology, Guangdong Second Provincial General Hospital, Guangzhou, PR China
| | - Junzhang Tian
- Department of Radiology, Guangdong Second Provincial General Hospital, Guangzhou, PR China
| | - Xiaofen Ma
- Department of Radiology, Guangdong Second Provincial General Hospital, Guangzhou, PR China.
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Liu X, Qiu S, Wang X, Chen H, Tang Y, Qin Y. Aberrant dynamic Functional-Structural connectivity coupling of Large-scale brain networks in poststroke motor dysfunction. Neuroimage Clin 2023; 37:103332. [PMID: 36708666 PMCID: PMC10037213 DOI: 10.1016/j.nicl.2023.103332] [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: 10/05/2022] [Revised: 01/11/2023] [Accepted: 01/19/2023] [Indexed: 01/24/2023]
Abstract
BACKGROUND AND PURPOSE Stroke may lead to widespread functional and structural reorganization in the brain. Several studies have reported a potential correlation between functional network changes and structural network changes after stroke. However, it is unclear how functional-structural relationships change dynamically over the course of one resting-state fMRI scan in patients following a stroke; furthermore, we know little about their relationships with the severity of motor dysfunction. Therefore, this study aimed to investigate dynamic functional and structural connectivity (FC-SC) coupling and its relationship with motor function in subcortical stroke from the perspective of network dynamics. METHODS Resting-state functional magnetic resonance imaging and diffusion tensor imaging were obtained from 39 S patients (19 severe and 20 moderate) and 22 healthy controls (HCs). Brain structural networks were constructed by tracking fiber tracts in diffusion tensor imaging, and structural network topology metrics were calculated using a graph-theoretic approach. Independent component analysis, the sliding window method, and k-means clustering were used to calculate dynamic functional connectivity and to estimate different dynamic connectivity states. The temporal patterns and intergroup differences of FC-SC coupling were analyzed within each state. We also calculated dynamic FC-SC coupling and its relationship with functional network efficiency. In addition, the correlation between FC-SC coupling and the Fugl-Meyer assessment scale was analyzed. RESULTS For SC, stroke patients showed lower global efficiency than HCs (all P < 0.05), and severely affected patients had a higher characteristic path length (P = 0.003). For FC and FC-SC coupling, stroke patients predominantly showed lower local efficiency and reduced FC-SC coupling than HCs in state 2 (all P < 0.05). Furthermore, severely affected patients also showed lower local efficiency (P = 0.031) and reduced FC-SC coupling (P = 0.043) in state 3, which was markedly linked to the severity of motor dysfunction after stroke. In addition, FC-SC coupling was correlated with functional network efficiency in state 2 in moderately affected patients (r = 0.631, P = 0.004) but not significantly in severely affected patients. CONCLUSIONS Stroke patients show abnormal dynamic FC-SC coupling characteristics, especially in individuals with severe injuries. These findings may contribute to a better understanding of the anatomical functional interactions underlying motor deficits in stroke patients and provide useful information for personalized rehabilitation strategies.
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Affiliation(s)
- Xiaoying Liu
- Department of Rehabilitation Medicine, The 900th Hospital of People's Liberation Army (Fuzhou General Hospital of Nanjing Military Region), Fuzhou, 350025, China
| | - Shuting Qiu
- Department of Rehabilitation Medicine, The 900th Hospital of People's Liberation Army (Fuzhou General Hospital of Nanjing Military Region), Fuzhou, 350025, China
| | - Xiaoyang Wang
- Department of the Fujian Key Laboratory of Functional Imaging, Department of Radiology, The 900th Hospital of People's Liberation Army (Fuzhou General Hospital of Nanjing Military Region), Fuzhou 350025, China
| | - Hui Chen
- Department of Rehabilitation Medicine, The 900th Hospital of People's Liberation Army (Fuzhou General Hospital of Nanjing Military Region), Fuzhou, 350025, China
| | - Yuting Tang
- Department of Rehabilitation Medicine, The 900th Hospital of People's Liberation Army (Fuzhou General Hospital of Nanjing Military Region), Fuzhou, 350025, China
| | - Yin Qin
- Department of Rehabilitation Medicine, The 900th Hospital of People's Liberation Army (Fuzhou General Hospital of Nanjing Military Region), Fuzhou, 350025, China; Department of Rehabilitation Medicine, Fuzhou General Hospital (Dongfang Hospital), Xiamen University, Fuzhou 350025, China.
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Chen Z, Fan B, Pang L, Wei M, Lv C, Zheng J. Longitudinal alterations of cortical structural-functional coupling in temporal lobe epilepsy. J Neuroimaging 2023; 33:156-166. [PMID: 36085558 DOI: 10.1111/jon.13046] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 08/16/2022] [Accepted: 08/25/2022] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND AND PURPOSE To investigate the longitudinal alterations of cortical structural-functional coupling (SF coupling) in patients with temporal lobe epilepsy (TLE) over a 2-year follow-up, thereby exploring the neuropathophysiological mechanisms of TLE. METHODS Twenty-eight TLE patients and 42 age- and gender-matched healthy controls (HCs) were recruited. We used resting-state functional MRI and diffusion-weighted imaging to estimate and compare SF coupling at the multiscale network level (whole-brain, modular, and regional levels). Then, we analyzed the relationships between the spatial patterns of SF coupling, the principal functional connectivity (FC) gradient, and the functional participation coefficient (PC). Finally, we related regional SF coupling changes between baseline and follow-up to the expression of regional TLE-specific genes. RESULTS Compared with HCs, TLE patients showed higher baseline SF couplings within the whole-brain, limbic, and default-mode modules. SF couplings within visual and dorsal attention modules were increased at follow-up compared to baseline. In all three groups, the spatial patterns of SF coupling aligned with the principal FC gradient and the functional PC. The longitudinal change in regional SF coupling in TLE patients was significantly positively correlated with the expression of the CUX2 gene. CONCLUSIONS Aberrant SF coupling was revealed in TLE and related to macroscale cortical hierarchies, functional segregation, and TLE-specific gene expression; these data help increase our understanding of the neuropathophysiological mechanisms underlying TLE.
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Affiliation(s)
- Zexiang Chen
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Binglin Fan
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Linlin Pang
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Minda Wei
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Caitiao Lv
- Department of Neurology, 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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