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Okui N. A Discrete Mathematics Approach for Understanding Risk Factors in Overactive Bladder Treatment. Cureus 2024; 16:e53245. [PMID: 38425586 PMCID: PMC10904023 DOI: 10.7759/cureus.53245] [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] [Accepted: 01/26/2024] [Indexed: 03/02/2024] Open
Abstract
Introduction Discrete mathematics, a branch of mathematics that includes graph theory, combinatorics, and logic, focuses on discrete mathematical structures. Its application in the medical field, particularly in analyzing patterns in patient data and optimizing treatment methods, is invaluable. This study, focusing on post-void residual (PVR) urine following overactive bladder (OAB) treatment, utilized discrete mathematics techniques to analyze PVR and its associated risk factors. Methods A retrospective study was conducted on 128 OAB patients who received intradetrusor onabotulinum toxin A injections between 2020 and 2022. Network graphs based on graph theory were used to analyze correlations between clinical variables, and clustering analysis was performed with PVR as the primary variable. Results The network graph analysis revealed that frailty, daytime frequency, and nocturia episodes were closely related to PVR. Clustering analysis with PVR as the primary variable divided the patients into three groups, suggesting that the group with particularly high frailty (Cluster 1) is at high risk for PVR. Moreover, significant differences in clinical indicators such as age, voiding efficiency, Overactive Bladder Symptom Score, and International Consultation on Incontinence Questionnaire-Short Form were observed in the remaining two clusters (Cluster 0 and 2). Conclusion This study demonstrates the effectiveness of discrete mathematics methods in identifying risk factors for PVR after OAB treatment and in distinguishing clinical subgroups based on patient characteristics. This approach could contribute to the formulation of individualized treatment strategies and the improvement of patient care quality. Further development and clinical application of this methodology are expected in future research.
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Affiliation(s)
- Nobuo Okui
- Urology, Yokosuka Urogynecology and Urology Clinic, Kanagawa, JPN
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Kotlarz P, Lankinen K, Hakonen M, Turpin T, Polimeni JR, Ahveninen J. Multilayer Network Analysis across Cortical Depths in Resting-State 7T fMRI. bioRxiv 2023:2023.12.23.573208. [PMID: 38187540 PMCID: PMC10769454 DOI: 10.1101/2023.12.23.573208] [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] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
In graph theory, "multilayer networks" represent systems involving several interconnected topological levels. A neuroscience example is the hierarchy of connections between different cortical depths or "lamina". This hierarchy is becoming non-invasively accessible in humans using ultra-high-resolution functional MRI (fMRI). Here, we applied multilayer graph theory to examine functional connectivity across different cortical depths in humans, using 7T fMRI (1-mm3 voxels; 30 participants). Blood oxygenation level dependent (BOLD) signals were derived from five depths between the white matter and pial surface. We then compared networks where the inter-regional connections were limited to a single cortical depth only ("layer-by-layer matrices") to those considering all possible connections between regions and cortical depths ("multilayer matrix"). We utilized global and local graph theory features that quantitatively characterize network attributes such as network composition, nodal centrality, path-based measures, and hub segregation. Detecting functional differences between cortical depths was improved using multilayer connectomics compared to the layer-by-layer versions. Superficial aspects of the cortex dominated information transfer and deeper aspects clustering. These differences were largest in frontotemporal and limbic brain regions. fMRI functional connectivity across different cortical depths may contain neurophysiologically relevant information. Multilayer connectomics could provide a methodological framework for studies on how information flows across this hierarchy.
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Affiliation(s)
- Parker Kotlarz
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Kaisu Lankinen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Maria Hakonen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | | | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jyrki Ahveninen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
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Paban V, Mheich A, Spieser L, Sacher M. A multidimensional model of memory complaints in older individuals and the associated hub regions. Front Aging Neurosci 2023; 15:1324309. [PMID: 38187362 PMCID: PMC10771290 DOI: 10.3389/fnagi.2023.1324309] [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: 10/19/2023] [Accepted: 11/27/2023] [Indexed: 01/09/2024] Open
Abstract
Memory complaints are highly prevalent among middle-aged and older adults, and they are frequently reported in individuals experiencing subjective cognitive decline (SCD). SCD has received increasing attention due to its implications for the early detection of dementia. This study aims to advance our comprehension of individuals with SCD by elucidating potential cognitive/psychologic-contributing factors and characterizing cerebral hubs within the brain network. To identify these potential contributing factors, a structural equation modeling approach was employed to investigate the relationships between various factors, such as metacognitive beliefs, personality, anxiety, depression, self-esteem, and resilience, and memory complaints. Our findings revealed that self-esteem and conscientiousness significantly influenced memory complaints. At the cerebral level, analysis of delta and theta electroencephalographic frequency bands recorded during rest was conducted to identify hub regions using a local centrality metric known as betweenness centrality. Notably, our study demonstrated that certain brain regions undergo changes in their hub roles in response to the pathology of SCD. Specifically, the inferior temporal gyrus and the left orbitofrontal area transition into hubs, while the dorsolateral prefrontal cortex and the middle temporal gyrus lose their hub function in the presence of SCD. This rewiring of the neural network may be interpreted as a compensatory response employed by the brain in response to SCD, wherein functional connectivity is maintained or restored by reallocating resources to other regions.
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Affiliation(s)
- Véronique Paban
- Aix-Marseille Université, CNRS, LNC (Laboratoire de Neurosciences Cognitives–UMR 7291), Marseille, France
| | - A. Mheich
- CHUV-Centre Hospitalier Universitaire Vaudois, Service des Troubles du Spectre de l’Autisme et Apparentés, Lausanne University Hospital, Lausanne, Switzerland
| | - L. Spieser
- Aix-Marseille Université, CNRS, LNC (Laboratoire de Neurosciences Cognitives–UMR 7291), Marseille, France
| | - M. Sacher
- University of Toulouse Jean-Jaurès, CNRS, LCLLE (Laboratoire Cognition, Langues, Langage, Ergonomie–UMR 5263), Toulouse, France
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Lu M, Guo Z, Gao Z. Effect of intracranial electrical stimulation on dynamic functional connectivity in medically refractory epilepsy. Front Hum Neurosci 2023; 17:1295326. [PMID: 38178992 PMCID: PMC10765510 DOI: 10.3389/fnhum.2023.1295326] [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: 09/16/2023] [Accepted: 11/21/2023] [Indexed: 01/06/2024] Open
Abstract
Objective The objective of this study was to explore the distributed network effects of intracranial electrical stimulation in patients with medically refractory epilepsy using dynamic functional connectivity (dFC) and graph indicators. Methods The time-varying connectivity patterns of dFC (state-based metrics) as well as topological properties of static functional connectivity (sFC) and dFC (graph indicators) were assessed before and after the intracranial electrical stimulation. The sliding window method and k-means clustering were used for the analysis of dFC states, which were characterized by connectivity strength, occupancy rate, dwell time, and transition. Graph indicators for sFC and dFC were obtained using group statistical tests. Results DFCs were clustered into two connectivity configurations: a strongly connected state (state 1) and a sparsely connected state (state 2). After electrical stimulation, the dwell time and occupancy rate of state 1 decreased, while that of state 2 increased. Connectivity strengths of both state 1 and state 2 decreased. For graph indicators, the clustering coefficient, k-core, global efficiency, and local efficiency of patients showed a significant decrease, but the brain networks of patients exhibited higher modularity after electrical stimulation. Especially, for state 1, there was a significant decrease in functional connectivity strength after stimulation within and between the frontal lobe and temporary lobe, both of which are associated with the seizure onset. Conclusion Our findings demonstrated that intracranial electrical stimulation significantly changed the time-varying connectivity patterns and graph indicators of the brain in patients with medically refractory epilepsy. Specifically, the electrical stimulation decreased functional connectivity strength in both local-level and global-level networks. This might provide a mechanism of understanding for the distributed network effects of intracranial electrical stimulation and extend the knowledge of the pathophysiological network of medically refractory epilepsy.
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Affiliation(s)
- Meili Lu
- School of Information Technology Engineering, Tianjin University of Technology and Education, Tianjin, China
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55
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Ding Y, Guo K, Li J, Shan Q, Guo Y, Chen M, Wu Y, Wang X. Alterations in brain network functional connectivity and topological properties in DRE patients. Front Neurol 2023; 14:1238421. [PMID: 38116109 PMCID: PMC10729765 DOI: 10.3389/fneur.2023.1238421] [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: 06/11/2023] [Accepted: 10/20/2023] [Indexed: 12/21/2023] Open
Abstract
Objective The study aimed to find the difference in functional network topology on interictal electroencephalographic (EEG) between patients with drug-resistant epilepsy (DRE) and healthy people. Methods We retrospectively analyzed the medical records as well as EEG data of ten patients with DRE and recruited five sex-age-matched healthy controls (HC group). Each participant remained awake while undergoing video-electroencephalography (vEEG) monitoring. After excluding data that contained abnormal discharges, we screened EEG segments that were free of artifacts and put them together into 20-min segments. The screened data was bandpass filtered to different frequency bands (delta, theta, alpha, beta, and gamma). The weighted phase lag index (wPLI) and the network properties were calculated to evaluate changes in the topology of the functional network. Finally, the results were statistically analyzed, and the false discovery rate (FDR) was used to correct for differences after multiple comparisons. Results In the full frequency band (0.5-45 Hz), the functional connectivity in the DRE group during the interictal period was significantly lower than that in the HC group (p < 0.05). Compared to the HC group, in the full frequency band, the DRE group exhibited significantly decreased clustering coefficient (CC), node degree (D), and global efficiency (GE), while the characteristic path length (CPL) significantly increased (p < 0.05). In the sub-frequency bands, the functional connectivity of the DRE group was significantly lower than that of the HC group in the delta band but higher in the alpha, beta, and gamma bands (p < 0.05). The statistical results of network properties revealed that in the delta band, the DRE group had significantly decreased values for D, CC, and GE, but in the alpha, beta, and gamma bands, these values were significantly increased (p < 0.05). Additionally, the CPL of the DRE group significantly increased in the delta and theta bands but significantly decreased in the alpha, beta, and gamma bands (p < 0.05). Conclusion The topology structure of the functional network in DRE patients was significantly changed compared with healthy people, which was reflected in different frequency bands. It provided a theoretical basis for understanding the pathological network alterations of DRE.
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Affiliation(s)
- Yongqiang Ding
- Department of Neurosurgery, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Kunlin Guo
- Henan Key Laboratory of Brain Science and Brain–Computer Interface Technology, School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, China
| | - Jialiang Li
- Department of Neurosurgery, The First People Hospital of Shangqiu, Shangqiu, China
| | - Qiao Shan
- Department of Neurosurgery, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yongkun Guo
- Department of Neurosurgery, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Mingming Chen
- Henan Key Laboratory of Brain Science and Brain–Computer Interface Technology, School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, China
| | - Yuehui Wu
- Department of Neurosurgery, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xinjun Wang
- Department of Neurosurgery, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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Haubrich J, Nader K. Network-level changes in the brain underlie fear memory strength. eLife 2023; 12:RP88172. [PMID: 38047914 PMCID: PMC10695559 DOI: 10.7554/elife.88172] [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] [Indexed: 12/05/2023] Open
Abstract
The strength of a fear memory significantly influences whether it drives adaptive or maladaptive behavior in the future. Yet, how mild and strong fear memories differ in underlying biology is not well understood. We hypothesized that this distinction may not be exclusively the result of changes within specific brain regions, but rather the outcome of collective changes in connectivity across multiple regions within the neural network. To test this, rats were fear conditioned in protocols of varying intensities to generate mild or strong memories. Neuronal activation driven by recall was measured using c-fos immunohistochemistry in 12 brain regions implicated in fear learning and memory. The interregional coordinated brain activity was computed and graph-based functional networks were generated to compare how mild and strong fear memories differ at the systems level. Our results show that mild fear recall is supported by a well-connected brain network with small-world properties in which the amygdala is well-positioned to be modulated by other regions. In contrast, this connectivity is disrupted in strong fear memories and the amygdala is isolated from other regions. These findings indicate that the neural systems underlying mild and strong fear memories differ, with implications for understanding and treating disorders of fear dysregulation.
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Affiliation(s)
- Josue Haubrich
- Department of Psychology, McGill UniversityMontréalCanada
- Department of Neurophysiology, Ruhr-University BochumBochumGermany
| | - Karim Nader
- Department of Psychology, McGill UniversityMontréalCanada
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Wang H, Zhan X, Xu J, Yu M, Guo Z, Zhou G, Ren J, Zhang R, Liu W. Disrupted topologic efficiency of brain functional connectome in de novo Parkinson's disease with depression. Eur J Neurosci 2023; 58:4371-4383. [PMID: 37857484 DOI: 10.1111/ejn.16176] [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: 08/13/2023] [Revised: 09/23/2023] [Accepted: 10/05/2023] [Indexed: 10/21/2023]
Abstract
Growing evidence supports that depression in Parkinson's disease (PD) depends on disruptions in specific neural networks rather than regional dysfunction. According to the resting-state functional magnetic resonance imaging data, the study attempted to decipher the alterations in the topological properties of brain networks in de novo depression in PD (DPD). The study also explored the neural network basis for depressive symptoms in PD. We recruited 20 DPD, 37 non-depressed PD and 41 healthy controls (HC). The Graph theory and network-based statistical methods helped analyse the topological properties of brain functional networks and anomalous subnetworks across these groups. The relationship between altered properties and depression severity was also investigated. DPD revealed significantly reduced nodal efficiency in the left superior temporal gyrus. Additionally, DPD decreased five hubs, primarily located in the temporal-occipital cortex, and increased seven hubs, mainly distributed in the limbic cortico-basal ganglia circuit. The betweenness centrality of the left Medio Ventral Occipital Cortex was positively associated with depressive scores in DPD. In contrast to HC, DPD had a multi-connected subnetwork with significantly lower connectivity, primarily distributed in the visual, somatomotor, dorsal attention and default networks. Regional topological disruptions in the temporal-occipital region are critical in the DPD neurological mechanism. It might suggest a potential network biomarker among newly diagnosed DPD patients.
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Affiliation(s)
- Hui Wang
- Department of Neurology, Lianyungang Hospital of Traditional Chinese Medicine, Lianyungang Affiliated Hospital of Nanjing University of Chinese Medicine, Lianyungang, China
| | - Xiaoyan Zhan
- Department of Clinical Laboratory, Jiangsu Province Hospital of Traditional Chinese Medicine, Nanjing, China
| | - Jianxia Xu
- Department of Neurology, Dushu Lake Hospital Affiliated to Soochow University, Suzhou, China
| | - Miao Yu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Zhiying Guo
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Gaiyan Zhou
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Jingru Ren
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Ronggui Zhang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Weiguo Liu
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
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58
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Eussen MJ, Jansen JF, Voncken TP, Debeij-Van Hall MH, Hendriksen JG, Vermeulen RJ, Klinkenberg S, Backes WH, Drenthen GS. Exploring the core network of the structural covariance network in childhood absence epilepsy. Heliyon 2023; 9:e22657. [PMID: 38107302 PMCID: PMC10724663 DOI: 10.1016/j.heliyon.2023.e22657] [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: 02/09/2023] [Revised: 10/04/2023] [Accepted: 11/16/2023] [Indexed: 12/19/2023] Open
Abstract
Childhood absence epilepsy (CAE) is a generalized pediatric epilepsy, which is generally considered to be a benign condition since most children become seizure-free before reaching adulthood. However, cognitive deficits and changes of brain morphological have been previously reported in CAE. These morphological changes, even if they might be very subtle, are not independent due to the underlying network structure and can be captured by the structural covariance network (SCN). In this study, SCNs were used to quantify the structural brain network for children with CAE as well as controls. Seventeen children with CAE (6-12y) and fifteen controls (6-12y) were included. To estimate the SCN, T1-weighted images were acquired and parcellated into 68 cortical regions. Graph measures characterizing the core network architecture, i.e. the assortativity and rich-club coefficient, were calculated for all individuals. Multivariable linear regression models, including age and sex as covariates, were used to assess differences between children with CAE and controls. Additionally, potential relations between the core network and cognitive performance was investigated. A lower assortativity (i.e. less efficiently organized core network organization) was found for children with CAE compared to controls. Moreover, better cognitive performance was found to relate to stronger assortative mixing pattern (i.e. more efficient core network structure). Rich-club coefficients did not differ between groups, nor relate to cognitions. The core network organization of the SCN in children with CAE tend to be less efficient organized compared to controls, and relates to cognitive performance, and therefore this study provides novel insights into the SCN organization in relation to CAE and cognition.
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Affiliation(s)
- Merel J.A. Eussen
- Department of Biomedical Technology, Eindhoven University of Technology, Eindhoven, the Netherlands
- Department of Radiology & Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Jacobus F.A. Jansen
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
- Department of Radiology & Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Twan P.C. Voncken
- Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
- Epilepsy Center Kempenhaeghe, Heeze, the Netherlands
| | | | - Jos G.M. Hendriksen
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
- Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
- Epilepsy Center Kempenhaeghe, Heeze, the Netherlands
| | - R. Jeroen Vermeulen
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
- Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Sylvia Klinkenberg
- Department of Neurology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Walter H. Backes
- Department of Radiology & Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Gerhard S. Drenthen
- Department of Radiology & Nuclear Medicine, Maastricht University Medical Center, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, the Netherlands
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Kulke M, Olson DM, Huang J, Kramer DM, Vermaas JV. Long-Range Electron Transport Rates Depend on Wire Dimensions in Cytochrome Nanowires. Small 2023; 19:e2304013. [PMID: 37653599 DOI: 10.1002/smll.202304013] [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] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 08/18/2023] [Indexed: 09/02/2023]
Abstract
The ability to redirect electron transport to new reactions in living systems opens possibilities to store energy, generate new products, or probe physiological processes. Recent work by Huang et al. showed that 3D crystals of small tetraheme cytochromes (STC) can transport electrons over nanoscopic to mesoscopic distances by an electron hopping mechanism, making them promising materials for nanowires. However, fluctuations at room temperature may distort the nanostructure, hindering efficient electron transport. Classical molecular dynamics simulations of these fluctuations at the nano- and mesoscopic scales allowed us to develop a graph network representation to estimate maximum electron flow that can be driven through STC wires. In longer nanowires, transient structural fluctuations at protein-protein interfaces tended to obstruct efficient electron transfer, but these blockages are ameliorated in thicker crystals where alternative electron transfer pathways become more efficient. The model implies that more flexible proteinprotein interfaces limit the required minimum diameter to carry currents commensurate with conventional electronics.
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Affiliation(s)
- Martin Kulke
- MSU-DOE Plant Research Laboratory and Department of Biochemistry and Molecular Biology, Michigan State University, 612 Wilson Rd, East Lansing, MI, 48824, United States of America
| | - Dayna M Olson
- MSU-DOE Plant Research Laboratory and Department of Biochemistry and Molecular Biology, Michigan State University, 612 Wilson Rd, East Lansing, MI, 48824, United States of America
| | - Jingcheng Huang
- MSU-DOE Plant Research Laboratory and Department of Biochemistry and Molecular Biology, Michigan State University, 612 Wilson Rd, East Lansing, MI, 48824, United States of America
| | - David M Kramer
- MSU-DOE Plant Research Laboratory and Department of Biochemistry and Molecular Biology, Michigan State University, 612 Wilson Rd, East Lansing, MI, 48824, United States of America
| | - Josh V Vermaas
- MSU-DOE Plant Research Laboratory and Department of Biochemistry and Molecular Biology, Michigan State University, 612 Wilson Rd, East Lansing, MI, 48824, United States of America
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Maas DA, Douw L. Multiscale network neuroscience in neuro-oncology: How tumors, brain networks, and behavior connect across scales. Neurooncol Pract 2023; 10:506-517. [PMID: 38026586 PMCID: PMC10666814 DOI: 10.1093/nop/npad044] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2023] Open
Abstract
Network neuroscience refers to the investigation of brain networks across different spatial and temporal scales, and has become a leading framework to understand the biology and functioning of the brain. In neuro-oncology, the study of brain networks has revealed many insights into the structure and function of cells, circuits, and the entire brain, and their association with both functional status (e.g., cognition) and survival. This review connects network findings from different scales of investigation, with the combined aim of informing neuro-oncological healthcare professionals on this exciting new field and also delineating the promising avenues for future translational and clinical research that may allow for application of network methods in neuro-oncological care.
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Affiliation(s)
- Dorien A Maas
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Linda Douw
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam, The Netherlands
- Cancer Center Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Amsterdam, The Netherlands
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Wang L, Liang X, Wang J, Zhang Y, Fan Z, Sun T, Yu X, Wu D, Wang H. Cerebral dominance representation of directed connectivity within and between left-right hemispheres and frontal-posterior lobes in mild cognitive impairment. Cereb Cortex 2023; 33:11279-11286. [PMID: 37804252 DOI: 10.1093/cercor/bhad365] [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: 07/04/2023] [Revised: 09/11/2023] [Accepted: 09/12/2023] [Indexed: 10/09/2023] Open
Abstract
Electroencephalography can assess connectivity between brain hemispheres, potentially influencing cognitive functions. Much of the existing electroencephalography research primarily focuses on undirected connectivity, leaving uncertainties about directed connectivity alterations between left-right brain hemispheres or frontal-posterior lobes in mild cognitive impairment. We analyzed resting-state electroencephalography data from 34 mild cognitive impairment individuals and 23 normal controls using directed transfer function and graph theory for directed network analysis. Concerning the dominance within left-right hemispheres or frontal-posterior lobes, the mild cognitive impairment group exhibited decreased connectivity within the frontal compared with posterior brain regions in the delta and theta bands. Regarding the dominance between the brain hemispheres or lobes, the mild cognitive impairment group showed reduced connectivity from the posterior to the frontal regions versus the reverse direction in the same bands. Among all participants, the intra-lobe frontal-posterior dominance correlated positively with executive function in the delta and alpha bands. Inter-lobe dominance between frontal and posterior regions also positively correlated with executive function, attention, and language in the delta band. Additionally, interhemispheric dominance between the left and right hemispheres positively correlated with attention in delta and theta bands. These findings suggest altered cerebral dominance in mild cognitive impairment, potentially serving as electrophysiological markers for neurocognitive disorders.
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Affiliation(s)
- Luchun Wang
- Beijing Dementia Key Lab, Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing 100191, China
- NHC Key Laboratory of Mental Health, National Clinical Research Center for Mental Disorders, Peking University, Sixth Hospital, Beijing 100191, China
| | - Xixi Liang
- School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
| | - Jing Wang
- Beijing Dementia Key Lab, Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing 100191, China
- NHC Key Laboratory of Mental Health, National Clinical Research Center for Mental Disorders, Peking University, Sixth Hospital, Beijing 100191, China
| | - Ying Zhang
- Beijing Dementia Key Lab, Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing 100191, China
- NHC Key Laboratory of Mental Health, National Clinical Research Center for Mental Disorders, Peking University, Sixth Hospital, Beijing 100191, China
| | - Zili Fan
- Beijing Dementia Key Lab, Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing 100191, China
- NHC Key Laboratory of Mental Health, National Clinical Research Center for Mental Disorders, Peking University, Sixth Hospital, Beijing 100191, China
- Beijing Anding Hospital, Capital Medical University, Beijing 100044, China
| | - Tingting Sun
- Beijing Dementia Key Lab, Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing 100191, China
- NHC Key Laboratory of Mental Health, National Clinical Research Center for Mental Disorders, Peking University, Sixth Hospital, Beijing 100191, China
- Department of Psychiatry, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510080, China
| | - Xin Yu
- Beijing Dementia Key Lab, Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing 100191, China
- NHC Key Laboratory of Mental Health, National Clinical Research Center for Mental Disorders, Peking University, Sixth Hospital, Beijing 100191, China
| | - Dan Wu
- School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China
| | - Huali Wang
- Beijing Dementia Key Lab, Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing 100191, China
- NHC Key Laboratory of Mental Health, National Clinical Research Center for Mental Disorders, Peking University, Sixth Hospital, Beijing 100191, China
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Xu Q, Yang J, Cheng F, Ning Z, Xi C, Sun Z. Changes in Multiparametric Magnetic Resonance Imaging and Plasma Amyloid-Beta Protein in Subjective Cognitive Decline. Brain Sci 2023; 13:1624. [PMID: 38137072 PMCID: PMC10742209 DOI: 10.3390/brainsci13121624] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 11/16/2023] [Accepted: 11/21/2023] [Indexed: 12/24/2023] Open
Abstract
The association between plasma amyloid-beta protein (Aβ) and subjective cognitive decline (SCD) remains controversial. We aimed to explore the correlation between neuroimaging findings, plasma Aβ, and neuropsychological scales using data from 53 SCD patients and 46 age- and sex-matched healthy controls (HCs). Magnetic resonance imaging (MRI) was used to obtain neuroimaging data for a whole-brain voxel-based morphometry analysis and cortical functional network topological features. The SCD group had slightly lower Montreal Cognitive Assessment (MoCA) scores than the HC group. The Aβ42 levels were significantly higher in the SCD group than in the HC group (p < 0.05). The SCD patients demonstrated reduced volumes in the left hippocampus, right rectal gyrus (REC.R), and right precentral gyrus (PreCG.R); an increased percentage fluctuation in the left thalamus (PerAF); and lower average small-world coefficient (aSigma) and average global efficiency (aEg) values. Correlation analyses with Aβ and neuropsychological scales revealed significant positive correlations between the volumes of the HIP.L, REC.R, PreCG.R, and MoCA scores. The HIP.L volume and Aβ42 were negatively correlated, as were the REC.R volume and Aβ42/40. PerAF and aSigma were negatively and positively correlated with the MoCA scores, respectively. The aEg was positively correlated with Aβ42/40. SCD patients may exhibit alterations in plasma biomarkers and multi-parameter MRI that resemble those observed in Alzheimer's disease, offering a theoretical foundation for early clinical intervention in SCD.
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Affiliation(s)
- Qiaoqiao Xu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; (Q.X.); (J.Y.)
- Department of Neurology, The Third Affiliated Hospital of Anhui Medical University (Hefei City First People’s Hospital), Hefei 230061, China; (F.C.); (Z.N.)
| | - Jiajia Yang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; (Q.X.); (J.Y.)
| | - Fang Cheng
- Department of Neurology, The Third Affiliated Hospital of Anhui Medical University (Hefei City First People’s Hospital), Hefei 230061, China; (F.C.); (Z.N.)
| | - Zhiwen Ning
- Department of Neurology, The Third Affiliated Hospital of Anhui Medical University (Hefei City First People’s Hospital), Hefei 230061, China; (F.C.); (Z.N.)
| | - Chunhua Xi
- Department of Neurology, The Third Affiliated Hospital of Anhui Medical University (Hefei City First People’s Hospital), Hefei 230061, China; (F.C.); (Z.N.)
| | - Zhongwu Sun
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China; (Q.X.); (J.Y.)
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Wang Y, Li Y, Wang C, Lio CWJ, Ma Q, Liu B. CEMIG: prediction of the cis-regulatory motif using the de Bruijn graph from ATAC-seq. Brief Bioinform 2023; 25:bbad505. [PMID: 38189539 PMCID: PMC10772951 DOI: 10.1093/bib/bbad505] [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: 09/22/2023] [Revised: 11/21/2023] [Accepted: 12/03/2023] [Indexed: 01/09/2024] Open
Abstract
Sequence motif discovery algorithms enhance the identification of novel deoxyribonucleic acid sequences with pivotal biological significance, especially transcription factor (TF)-binding motifs. The advent of assay for transposase-accessible chromatin using sequencing (ATAC-seq) has broadened the toolkit for motif characterization. Nonetheless, prevailing computational approaches have focused on delineating TF-binding footprints, with motif discovery receiving less attention. Herein, we present Cis rEgulatory Motif Influence using de Bruijn Graph (CEMIG), an algorithm leveraging de Bruijn and Hamming distance graph paradigms to predict and map motif sites. Assessment on 129 ATAC-seq datasets from the Cistrome Data Browser demonstrates CEMIG's exceptional performance, surpassing three established methodologies on four evaluative metrics. CEMIG accurately identifies both cell-type-specific and common TF motifs within GM12878 and K562 cell lines, demonstrating its comparative genomic capabilities in the identification of evolutionary conservation and cell-type specificity. In-depth transcriptional and functional genomic studies have validated the functional relevance of CEMIG-identified motifs across various cell types. CEMIG is available at https://github.com/OSU-BMBL/CEMIG, developed in C++ to ensure cross-platform compatibility with Linux, macOS and Windows operating systems.
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Affiliation(s)
- Yizhong Wang
- School of Mathematics, Shandong University, Jinan, 250100, China
| | - Yang Li
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA
| | - Cankun Wang
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA
| | - Chan-Wang Jerry Lio
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA
- Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH, 43210, USA
| | - Qin Ma
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, 43210, USA
- Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH, 43210, USA
| | - Bingqiang Liu
- School of Mathematics, Shandong University, Jinan, 250100, China
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Nam KM, Gunawardena J. The linear framework II: using graph theory to analyse the transient regime of Markov processes. Front Cell Dev Biol 2023; 11:1233808. [PMID: 38020901 PMCID: PMC10656611 DOI: 10.3389/fcell.2023.1233808] [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: 06/02/2023] [Accepted: 10/02/2023] [Indexed: 12/01/2023] Open
Abstract
The linear framework uses finite, directed graphs with labelled edges to model biomolecular systems. Graph vertices represent chemical species or molecular states, edges represent reactions or transitions and edge labels represent rates that also describe how the system is interacting with its environment. The present paper is a sequel to a recent review of the framework that focussed on how graph-theoretic methods give insight into steady states as rational algebraic functions of the edge labels. Here, we focus on the transient regime for systems that correspond to continuous-time Markov processes. In this case, the graph specifies the infinitesimal generator of the process. We show how the moments of the first-passage time distribution, and related quantities, such as splitting probabilities and conditional first-passage times, can also be expressed as rational algebraic functions of the labels. This capability is timely, as new experimental methods are finally giving access to the transient dynamic regime and revealing the computations and information processing that occur before a steady state is reached. We illustrate the concepts, methods and formulas through examples and show how the results may be used to illuminate previous findings in the literature.
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Affiliation(s)
| | - Jeremy Gunawardena
- Department of Systems Biology, Harvard Medical School, Boston, MA, United States
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Tozer MG, Keith DA. Beyond central-tendency: If we agree discrete vegetation communities do not exist, should we investigate other methods of clustering? Ecol Evol 2023; 13:e10757. [PMID: 38020702 PMCID: PMC10659940 DOI: 10.1002/ece3.10757] [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: 08/31/2023] [Accepted: 10/08/2023] [Indexed: 12/01/2023] Open
Abstract
Clustering is indispensable in the quest for robust vegetation classification schemes that aim to partition, summarise and communicate patterns. However, clustering solutions are sensitive to methods and data and are therefore unstable, a feature that is usually attributed to noise. Viewed through a central-tendency lens, noise is defined as the degree of departure from type, which is problematic since vegetation types are abstractions of continua, and so noise can only be quantified relative to the particular solution at hand. Graph theory models the structure of vegetation data based on the interconnectivity of samples. Through a graph-theoretic lens, the causes of instability can be quantified in absolute terms via the degree of connectivity among objects. We simulated incremental increases in sampling intensity in a dataset over five iterations and assessed classification stability across successive solutions derived using algorithms implementing, respectively, models of central-tendency and interconnectivity. We used logistic regression to model the likelihood of a sample changing groups between iterations as a function of distance to the centroid and degree of interconnectivity. Our results show that the degree to which samples are interconnected is a more powerful predictor of instability than the degree to which they deviate from their nearest centroid. The removal of weakly interconnected samples resulted in more stable classifications, although solutions with many clusters were apparently inherently less stable than those with few clusters, and improvements in stability flowing from the removal of outliers declined as the number of clusters increased. Our results reinforce the fact that clusters abstracted from continuous data are inherently unstable and that the quest for stable, fine-scale classifications from large regional datasets is illusory. Nevertheless, our results show that using models better suited to the analysis of continuous data may yield more stable classifications of the available data.
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Affiliation(s)
- Mark G. Tozer
- NSW Department of Planning and EnvironmentParramattaNew South WalesAustralia
- School of Biological, Earth and Environmental Science, Centre for Ecosystem ScienceUniversity of NSWSydneyNew South WalesAustralia
| | - David A. Keith
- School of Biological, Earth and Environmental Science, Centre for Ecosystem ScienceUniversity of NSWSydneyNew South WalesAustralia
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Chappel-Farley MG, Adams JN, Betzel RF, Janecek JC, Sattari NS, Berisha DE, Meza NJ, Niknazar H, Kim S, Dave A, Chen IY, Lui KK, Neikrug AB, Benca RM, Yassa MA, Mander BA. Medial temporal lobe functional network architecture supports sleep-related emotional memory processing in older adults. bioRxiv 2023:2023.10.27.564260. [PMID: 37961192 PMCID: PMC10634911 DOI: 10.1101/2023.10.27.564260] [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] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Memory consolidation occurs via reactivation of a hippocampal index during non-rapid eye movement slow-wave sleep (NREM SWS) which binds attributes of an experience existing within cortical modules. For memories containing emotional content, hippocampal-amygdala dynamics facilitate consolidation over a sleep bout. This study tested if modularity and centrality-graph theoretical measures that index the level of segregation/integration in a system and the relative import of its nodes-map onto central tenets of memory consolidation theory and sleep-related processing. Findings indicate that greater network integration is tied to overnight emotional memory retention via NREM SWS expression. Greater hippocampal and amygdala influence over network organization supports emotional memory retention, and hippocampal or amygdala control over information flow are differentially associated with distinct stages of memory processing. These centrality measures are also tied to the local expression and coupling of key sleep oscillations tied to sleep-dependent memory consolidation. These findings suggest that measures of intrinsic network connectivity may predict the capacity of brain functional networks to acquire, consolidate, and retrieve emotional memories.
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Affiliation(s)
- Miranda G. Chappel-Farley
- Department of Neurobiology and Behavior, University of California Irvine, Irvine CA, 92697, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine CA, 92697, USA
| | - Jenna N. Adams
- Department of Neurobiology and Behavior, University of California Irvine, Irvine CA, 92697, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine CA, 92697, USA
| | - Richard F. Betzel
- Department of Psychological and Brain Sciences, University of Indiana Bloomington, Bloomington IN, 47405
| | - John C. Janecek
- Department of Neurobiology and Behavior, University of California Irvine, Irvine CA, 92697, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine CA, 92697, USA
| | - Negin S. Sattari
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine CA, 92697, USA
| | - Destiny E. Berisha
- Department of Neurobiology and Behavior, University of California Irvine, Irvine CA, 92697, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine CA, 92697, USA
| | - Novelle J. Meza
- Department of Neurobiology and Behavior, University of California Irvine, Irvine CA, 92697, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine CA, 92697, USA
| | - Hamid Niknazar
- Department of Cognitive Sciences, University of California Irvine, Irvine CA, 92697, USA
| | - Soyun Kim
- Department of Neurobiology and Behavior, University of California Irvine, Irvine CA, 92697, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine CA, 92697, USA
| | - Abhishek Dave
- Department of Cognitive Sciences, University of California Irvine, Irvine CA, 92697, USA
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine CA, 92697, USA
| | - Ivy Y. Chen
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine CA, 92697, USA
| | - Kitty K. Lui
- San Diego State University/University of California San Diego, Joint Doctoral Program in Clinical Psychology, San Diego, CA, 92093, USA
| | - Ariel B. Neikrug
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine CA, 92697, USA
| | - Ruth M. Benca
- Department of Neurobiology and Behavior, University of California Irvine, Irvine CA, 92697, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine CA, 92697, USA
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine CA, 92697, USA
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Department of Psychiatry, University of Wisconsin-Madison, Madison, 53706, WI, USA
- Department of Psychiatry and Behavioral Medicine, Wake Forest University, Winston-Salem, NC, 27109, USA
- Institute for Memory Impairments and Neurological Disorders, University of California Irvine, Irvine CA, 92697, USA
| | - Michael A. Yassa
- Department of Neurobiology and Behavior, University of California Irvine, Irvine CA, 92697, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine CA, 92697, USA
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine CA, 92697, USA
- Institute for Memory Impairments and Neurological Disorders, University of California Irvine, Irvine CA, 92697, USA
- Department of Neurology, University of California Irvine, Irvine CA, 92697, USA
| | - Bryce A. Mander
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine CA, 92697, USA
- Department of Cognitive Sciences, University of California Irvine, Irvine CA, 92697, USA
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine CA, 92697, USA
- Institute for Memory Impairments and Neurological Disorders, University of California Irvine, Irvine CA, 92697, USA
- Department of Pathology and Laboratory Medicine, University of California Irvine, Irvine CA, 92697, USA
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Liu H, Zheng H, Zhang G, Zhuang J, Li W, Wu B, Zheng W. A Graph Theory Study of Resting-State Functional MRI Connectivity in Children With Carbon Monoxide Poisoning. J Magn Reson Imaging 2023; 58:1452-1459. [PMID: 36994898 DOI: 10.1002/jmri.28706] [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: 07/16/2022] [Revised: 03/21/2023] [Accepted: 03/21/2023] [Indexed: 03/31/2023] Open
Abstract
BACKGROUND The effect of carbon monoxide (CO) poisoning on the topology of brain functional networks is unclear, especially in children whose brains are still developing. PURPOSE To investigate the topological alterations of the whole-brain functional connectome in children with CO poisoning and characterize its relationship with disease severity. STUDY TYPE Cross-sectional and prospective study. SUBJECTS A total of 26 patients with CO poisoning and 26 healthy controls. FIELD STRENGTH/SEQUENCE A 3.0 T MRI system/echo planar imaging (EPI) and 3D brain volume imaging (BRAVO) sequences. ASSESSMENT We used the network-based statistics (NBS) method to explore between-group differences in functional connectivity strength and a graph-theoretical-based analytic method to explore the topology of brain networks. STATISTICAL TESTS Student's t-test, chi-square test, NBS, Pearson correlation coefficient, and false discovery rate correction. The statistical significance threshold was set at P < 0.05. RESULTS The case group's brain functional network topology was impaired in comparison to the control group (reduced global efficiency and small-worldness, increased characteristic path length). According to node and edge analyses, the case group showed topologically damaged regions in the frontal lobe and basal ganglia, as well as neuronal circuits with weaker connections. Also, there was a significant correlation between the patients' coma time and the degree (r = -0.4564), efficiency (r = -0.4625), and characteristic path length (r = 0.4383) of the nodes in the left orbital inferior frontal gyrus. Carbon monoxide hemoglobin content (COHb) concentration and right rolandic operculum node characteristic path length (r = -0.3894) were significantly correlated. The node efficiency and node degree of the right middle frontal gyrus (r = 0.4447 and 0.4539) and right pallidum (r = 0.4136 and 0.4501) significantly correlated with the MMSE score. DATA CONCLUSION The brain network topology of CO poisoned children is damaged, which is manifested by reduced network integration and may lead to a series of clinical symptoms in patients. EVIDENCE LEVEL 2. TECHNICAL EFFICACY Stage 2.
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Affiliation(s)
- HongKun Liu
- Department of Radiology, Huizhou Central People's Hospital, Huizhou, Guangdong, China
| | - HongYi Zheng
- Department of Radiology, The Second Affiliated Hospital, Medical College of Shantou University, Shantou, Guangdong, China
| | - GengBiao Zhang
- Department of Radiology, The Second Affiliated Hospital, Medical College of Shantou University, Shantou, Guangdong, China
| | - JiaYan Zhuang
- Department of Radiology, The Second Affiliated Hospital, Medical College of Shantou University, Shantou, Guangdong, China
| | - WeiJia Li
- Department of Radiology, The Second Affiliated Hospital, Medical College of Shantou University, Shantou, Guangdong, China
| | - BiXia Wu
- Department of Radiology, The Second Affiliated Hospital, Medical College of Shantou University, Shantou, Guangdong, China
| | - WenBin Zheng
- Department of Radiology, The Second Affiliated Hospital, Medical College of Shantou University, Shantou, Guangdong, China
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Böhmer J, Reinhardt P, Garbusow M, Marxen M, Smolka MN, Zimmermann US, Heinz A, Bzdok D, Friedel E, Kruschwitz JD, Walter H. Aberrant functional brain network organization is associated with relapse during 1-year follow-up in alcohol-dependent patients. Addict Biol 2023; 28:e13339. [PMID: 37855075 DOI: 10.1111/adb.13339] [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: 02/17/2023] [Revised: 08/12/2023] [Accepted: 09/11/2023] [Indexed: 10/20/2023]
Abstract
Alcohol dependence (AD) is a debilitating disease associated with high relapse rates even after long periods of abstinence. Thus, elucidating neurobiological substrates of relapse risk is fundamental for the development of novel targeted interventions that could promote long-lasting abstinence. In the present study, we analysed resting-state functional magnetic resonance imaging (rsfMRI) data from a sample of recently detoxified patients with AD (n = 93) who were followed up for 12 months after rsfMRI assessment. Specifically, we employed graph theoretic analyses to compare functional brain network topology and functional connectivity between future relapsers (REL, n = 59), future abstainers (ABS, n = 28) and age- and gender-matched controls (CON, n = 83). Our results suggest increased whole-brain network segregation, decreased global network integration and overall blunted connectivity strength in REL compared with CON. Conversely, we found evidence for a comparable network architecture in ABS relative to CON. At the nodal level, REL exhibited decreased integration and decoupling between multiple brain systems compared with CON, encompassing regions associated with higher-order executive functions, sensory and reward processing. Among patients with AD, increased coupling between nodes implicated in reward valuation and salience attribution constitutes a particular risk factor for future relapse. Importantly, aberrant network organization in REL was consistently associated with shorter abstinence duration during follow-up, portending to a putative neural signature of relapse risk in AD. Future research should further evaluate the potential diagnostic value of the identified changes in network topology and functional connectivity for relapse prediction at the individual subject level.
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Affiliation(s)
- Justin Böhmer
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Pablo Reinhardt
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Maria Garbusow
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Michael Marxen
- Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany
- Collaborative Research Centre (SFB 940) "Volition and Cognitive Control", Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany
- Collaborative Research Centre (SFB 940) "Volition and Cognitive Control", Technische Universität Dresden, Dresden, Germany
| | - Ulrich S Zimmermann
- Department of Addiction Medicine and Psychotherapy, kbo-Isar-Amper-Klinikum München-Ost, Haar, Germany
- Department of Biomedical Engineering, Faculty of Medicine, McConnell Brain Imaging Centre (BIC), Montreal Neurological Institute (MNI), McGill University, Montreal, Canada
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Danilo Bzdok
- Department of Biomedical Engineering, Faculty of Medicine, McConnell Brain Imaging Centre (BIC), Montreal Neurological Institute (MNI), McGill University, Montreal, Canada
- Mila - Quebec Artificial Intelligence Institute, Montreal, Canada
| | - Eva Friedel
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Johann D Kruschwitz
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
- Collaborative Research Centre (SFB 940) "Volition and Cognitive Control", Technische Universität Dresden, Dresden, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
- Collaborative Research Centre (SFB 940) "Volition and Cognitive Control", Technische Universität Dresden, Dresden, Germany
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Zheng W, Wang X, Liu T, Hu B, Wu D. Preterm-birth alters the development of nodal clustering and neural connection pattern in brain structural network at term-equivalent age. Hum Brain Mapp 2023; 44:5372-5386. [PMID: 37539754 PMCID: PMC10543115 DOI: 10.1002/hbm.26442] [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: 03/09/2023] [Revised: 07/14/2023] [Accepted: 07/18/2023] [Indexed: 08/05/2023] Open
Abstract
Preterm-born neonates are prone to impaired neurodevelopment that may be associated with disrupted whole-brain structural connectivity. The present study aimed to investigate the longitudinal developmental pattern of the structural network from preterm birth to term-equivalent age (TEA), and identify how prematurity influences the network topological organization and properties of local brain regions. Multi-shell diffusion-weighted MRI of 28 preterm-born scanned a short time after birth (PB-AB) and at TEA (PB-TEA), and 28 matched term-born (TB) neonates in the Developing Human Connectome Project (dHCP) were used to construct structural networks through constrained spherical deconvolution tractography. Structural network development from preterm birth to TEA showed reduced shortest path length, clustering coefficient, and modularity, and more "connector" hubs linking disparate communities. Furthermore, compared with TB newborns, premature birth significantly altered the nodal properties (i.e., clustering coefficient, within-module degree, and participation coefficient) in the limbic/paralimbic, default-mode, and subcortical systems but not global topology at TEA, and we were able to distinguish the PB from TB neonates at TEA based on the nodal properties with 96.43% accuracy. Our findings demonstrated a topological reorganization of the structural network occurs during the perinatal period that may prioritize the optimization of global network organization to form a more efficient architecture; and local topology was more vulnerable to premature birth-related factors than global organization of the structural network, which may underlie the impaired cognition and behavior in PB infants.
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Affiliation(s)
- Weihao Zheng
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and EngineeringLanzhou UniversityLanzhouChina
| | - Xiaomin Wang
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and EngineeringLanzhou UniversityLanzhouChina
| | - Tingting Liu
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument ScienceZhejiang UniversityHangzhouChina
| | - Bin Hu
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and EngineeringLanzhou UniversityLanzhouChina
- School of Medical TechnologyBeijing Institute of TechnologyBeijingChina
- CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institutes for Biological SciencesChinese Academy of SciencesShanghaiChina
- Joint Research Center for Cognitive Neurosensor Technology of Lanzhou University & Institute of SemiconductorsChinese Academy of SciencesLanzhouChina
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument ScienceZhejiang UniversityHangzhouChina
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Reeves WD, Ahmed I, Jackson BS, Sun W, Brown ML, Williams CF, Davis CL, McDowell JE, Yanasak NE, Su S, Zhao Q. Characterization of Resting-State Functional Connectivity Changes in Hypertension by a Modified Difference Degree Test. Brain Connect 2023; 13:563-573. [PMID: 37597202 PMCID: PMC10664569 DOI: 10.1089/brain.2023.0001] [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] [Indexed: 08/21/2023] Open
Abstract
Introduction: Hypertension affects over a billion people worldwide, and the application of neuroimaging may elucidate changes brought about by the disease. We have applied a graph theory approach to examine the organizational differences in resting-state functional magnetic resonance imaging (rs-fMRI) data between hypertensive and normotensive participants. To detect these groupwise differences, we performed statistical testing using a modified difference degree test (DDT). Methods: Structural and rs-fMRI data were collected from a cohort of 52 total (29 hypertensive and 23 normotensive) participants. Functional connectivity maps were obtained by partial correlation analysis of participant rs-fMRI data. We modified the DDT null generation algorithm and validated the change through different simulation schemes and then applied this modified DDT to our experimental data. Results: Through a comparative analysis, the modified DDT showed higher true positivity rates (TPR) when compared with the base DDT while also maintaining false positivity rates below the nominal value of 5% in nearly all analytically thresholded trials. Applying the modified DDT to our rs-fMRI data showed differential organization in the hypertension group in the regions throughout the brain including the default mode network. These experimental findings agree with previous studies. Conclusions: While our findings agree with previous studies, the experimental results presented require more investigation to prove their link to hypertension. Meanwhile, our modification to the DDT results in higher accuracy and an increased ability to discern groupwise differences in rs-fMRI data. We expect this to be useful in studying groupwise organizational differences in future studies.
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Affiliation(s)
- William D. Reeves
- Department of Physics and Astronomy, University of Georgia Franklin College of Arts and Sciences, Athens, Georgia, USA
- University of Georgia Bio-Imaging Research Center, Athens, Georgia, USA
| | - Ishfaque Ahmed
- Department of Physics and Astronomy, University of Georgia Franklin College of Arts and Sciences, Athens, Georgia, USA
- University of Georgia Bio-Imaging Research Center, Athens, Georgia, USA
| | - Brooke S. Jackson
- Department of Psychology, University of Georgia Franklin College of Arts and Sciences, Athens, Georgia, USA
| | - Wenwu Sun
- Department of Physics and Astronomy, University of Georgia Franklin College of Arts and Sciences, Athens, Georgia, USA
- University of Georgia Bio-Imaging Research Center, Athens, Georgia, USA
| | - Michelle L. Brown
- Georgia Prevention Institute, Medical College of Georgia, Augusta, Georgia, USA
| | | | - Catherine L. Davis
- Georgia Prevention Institute, Medical College of Georgia, Augusta, Georgia, USA
| | - Jennifer E. McDowell
- University of Georgia Bio-Imaging Research Center, Athens, Georgia, USA
- Department of Psychology, University of Georgia Franklin College of Arts and Sciences, Athens, Georgia, USA
| | - Nathan E. Yanasak
- Department of Radiology and Imaging, Medical College of Georgia, Augusta, Georgia, USA
| | - Shaoyong Su
- Georgia Prevention Institute, Medical College of Georgia, Augusta, Georgia, USA
| | - Qun Zhao
- Department of Physics and Astronomy, University of Georgia Franklin College of Arts and Sciences, Athens, Georgia, USA
- University of Georgia Bio-Imaging Research Center, Athens, Georgia, USA
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Chen Q, Abrigo J, Deng M, Shi L, Wang YX, Chu WC. Structural Network Topology Reveals Higher Brain Resilience in Individuals with Preclinical Alzheimer's Disease. Brain Connect 2023; 13:553-562. [PMID: 37551987 PMCID: PMC10771874 DOI: 10.1089/brain.2023.0013] [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] [Indexed: 08/09/2023] Open
Abstract
Introduction: The diagnosis of Alzheimer's disease (AD) requires the presence of amyloid and tau pathology, but it remains unclear how they affect the structural network in the pre-clinical stage. We aimed to assess differences in topological properties in cognitively normal (CN) individuals with varying levels of amyloid and tau pathology, as well as their association with AD pathology burden. Methods: A total of 68 CN individuals were included and stratified by normal/abnormal (-/+) amyloid (A) and tau (T) status based on positron emission tomography results, yielding three groups: A-T- (n = 19), A+T- (n = 28), and A+T+ (n = 21). Topological properties were measured from structural connectivity. Group differences and correlations with A and T were evaluated. Results: Compared with the A-T- group, the A+T+ group exhibited changes in the structural network topology. At the global level, higher assortativity was shown in the A+T+ group and was correlated with greater tau burden (r = 0.29, p = 0.02), while no difference in global efficiency was found across the three groups. At the local level, the A+T+ group showed disrupted topological properties in the left hippocampus compared with the A-T- group, characterized by lower local efficiency (p < 0.01) and a lower clustering coefficient (p = 0.014). Conclusions: The increased linkage in the higher level architecture of the white matter network reflected by assortativity may indicate increased brain resilience in the early pathological state. Our results encourage further investigation of the topological properties of the structural network in pre-clinical AD.
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Affiliation(s)
- Qianyun Chen
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Jill Abrigo
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Min Deng
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Lin Shi
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Yi-Xiang Wang
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Winnie C.W. Chu
- Department of Imaging and Interventional Radiology, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China
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Campi G, Ricci A, Costa N, Genovesi F, Branca JJV, Paternostro F, Della Posta D. Dynamic Correlations and Disorder in the Masticatory Musculature Network. Life (Basel) 2023; 13:2107. [PMID: 38004247 PMCID: PMC10672239 DOI: 10.3390/life13112107] [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: 09/27/2023] [Revised: 10/17/2023] [Accepted: 10/21/2023] [Indexed: 11/26/2023] Open
Abstract
BACKGROUND Temporomandibular joint (TMJ) disorders, which affect millions of people worldwide, have multiple etiological factors that make an accurate diagnosis and effective treatments difficult. As a consequence, the gold standard diagnostic criteria for TMJ disorders remain elusive and often depend on subjective decisions. AIM In this context, the lack of a non-invasive quantitative methodology capable of assessing the functional physiological state and, consequently, identifying risk indicators for the early diagnosis of TMJ disorders must be tackled and resolved. METHODOLOGY In this work, we have studied the biomechanics and viscoelastic properties of the functional masticatory system by a non-invasive approach involving 52 healthy subjects, analysed by statistical-physics analysis applied to myotonic measurements on specific points of the masticatory system designing a TMJ network composed of 17 nodes and 20 links. RESULTS We find that the muscle tone and viscoelasticity of a specific cycle linking frontal, temporal, and mandibular nodes of the network play a prominent role in the physiological functionality of the system. At the same time, the functional state is characterised by a landscape of nearly degenerated levels of elasticity in all links of the network, making this parameter critically distributed and deviating from normal behaviour. CONCLUSIONS Time evolution and dynamic correlations between biomechanics and viscoelastic parameters measured on the different cycles of the network provide a quantitative framework associated with the functional state of the masticatory system. Our results are expected to contribute to enriching the taxonomy of this system, primarily based on clinical observations, patient symptoms, and expert consensus.
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Affiliation(s)
- Gaetano Campi
- Institute of Crystallography, CNR, Via Salaria Km 29.300, 00015 Monterotondo, Italy;
| | - Alessandro Ricci
- Duferco Corporate Innovation, Via Trevano 2A, 6900 Lugano, Switzerland;
| | - Nicola Costa
- The Anatomical Network APS, Via Fermo 2c, 00182 Rome, Italy; (N.C.); (D.D.P.)
| | | | - Jacopo Junio Valerio Branca
- Department of Experimental and Clinical Medicine, Anatomy and Histology Section, University of Florence, 50134 Florence, Italy;
| | - Ferdinando Paternostro
- Department of Experimental and Clinical Medicine, Anatomy and Histology Section, University of Florence, 50134 Florence, Italy;
| | - Daniele Della Posta
- The Anatomical Network APS, Via Fermo 2c, 00182 Rome, Italy; (N.C.); (D.D.P.)
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Yuasa K, Hirosawa T, Soma D, Furutani N, Kameya M, Sano M, Kitamura K, Ueda M, Kikuchi M. Eyes-state-dependent alterations of magnetoencephalographic connectivity associated with delayed recall in Alzheimer's disease via graph theory approach. Front Psychiatry 2023; 14:1272120. [PMID: 37941968 PMCID: PMC10628524 DOI: 10.3389/fpsyt.2023.1272120] [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: 08/03/2023] [Accepted: 10/10/2023] [Indexed: 11/10/2023] Open
Abstract
IntroductionAlzheimer’s disease (AD) is a neurodegenerative disorder characterized by memory impairment and cognitive decline. Electroencephalography (EEG) and magnetoencephalography (MEG) studies using graph theory show altered “Small-Worldness (SW)” properties in AD. This study aimed to investigate whether eye-state-dependent alterations in SW differ between patients with AD and healthy controls, considering the symptoms of AD.MethodsNineteen patients with AD and 24 healthy controls underwent MEG under different conditions (eyes-open [EO] and eyes-closed [EC]) and the Wechsler Memory Scale-Revised (WMS-R) with delayed recall. After the signal sources were mapped onto the Desikan–Killiany brain atlas, the statistical connectivity of five frequency bands (delta, theta, alpha, beta, and gamma) was calculated using the phase lag index (PLI), and binary graphs for each frequency band were constructed based on the PLI. Next, we measured SW as a graph metric and evaluated three points: the impact of AD and experimental conditions on SW, the association between SW and delayed recall, and changes in SW across experimental conditions correlated with delayed recall.ResultsSW in the gamma band was significantly lower in patients with AD (z = −2.16, p = 0.031), but the experimental conditions did not exhibit a significant effect in any frequency band. Next, in the AD group, higher scores on delayed recall correlated with diminished SW across delta, alpha, and beta bands in the EO condition. Finally, delayed recall scores significantly predicted relative differences in the SW group in the alpha band (t = −2.98, p = 0.009).DiscussionGiven that network studies could corroborate the results of previous power spectrum studies, our findings contribute to a multifaceted understanding of functional brain networks in AD, emphasizing that the SW properties of these networks change according to disease status, cognitive function, and experimental conditions.
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Affiliation(s)
- Keigo Yuasa
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan
| | - Tetsu Hirosawa
- Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Daiki Soma
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan
| | - Naoki Furutani
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan
| | - Masafumi Kameya
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan
| | - Masuhiko Sano
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan
| | - Koji Kitamura
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan
| | - Minehisa Ueda
- Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Mitsuru Kikuchi
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan
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Yang S, Wu Y, Sun L, Lu Y, Qian K, Kuang H, Meng J, Wu Y. Abnormal Topological Organization of Structural Covariance Networks in Patients with Temporal Lobe Epilepsy Comorbid Sleep Disorder. Brain Sci 2023; 13:1493. [PMID: 37891861 PMCID: PMC10605209 DOI: 10.3390/brainsci13101493] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 10/11/2023] [Accepted: 10/18/2023] [Indexed: 10/29/2023] Open
Abstract
OBJECTIVE The structural covariance network (SCN) alterations in patients with temporal lobe epilepsy and comorbid sleep disorder (PWSD) remain poorly understood. This study aimed to investigate changes in SCNs using structural magnetic resonance imaging. METHODS Thirty-four PWSD patients, thirty-three patients with temporal lobe epilepsy without sleep disorder (PWoSD), and seventeen healthy controls underwent high-resolution structural MRI imaging. Subsequently, SCNs were constructed based on gray matter volume and analyzed via graph-theoretical approaches. RESULTS PWSD exhibited significantly increased clustering coefficients, shortest path lengths, transitivity, and local efficiency. In addition, various distributions and numbers of SCN hubs were identified in PWSD. Furthermore, PWSD networks were less robust to random and target attacks than those of healthy controls and PWoSD patients. CONCLUSION This study identifies aberrant SCN changes in PWSD that may be related to the susceptibility of patients with epilepsy to sleep disorders.
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Affiliation(s)
| | | | | | | | | | | | | | - Yuan Wu
- Department of Neurology, The First Affiliated Hospital, Guangxi Medical University, Nanning 530021, China
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Dong Y, Jin L, Li M, Lian R, Wu G, Xu R, Zhang X, Du K, Jia T, Wang H, Zhao S. Crucial involvement of fast waves and Delta band in the brain network attributes of infantile epileptic spasms syndrome. Front Pediatr 2023; 11:1249789. [PMID: 37928352 PMCID: PMC10623136 DOI: 10.3389/fped.2023.1249789] [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: 06/29/2023] [Accepted: 09/28/2023] [Indexed: 11/07/2023] Open
Abstract
Objective This study aims to describe the characteristics of the brain network attributes in children diagnosed with Infantile Epileptic Spasms Syndrome (IESS) and to determine the influence exerted by adrenocorticotrophic hormone (ACTH) or methylprednisolone (MP) on network attributes. Methods In this retrospective cohort study, we recruited 19 infants diagnosed with IESS and 10 healthy subjects as the control from the Pediatric Neurology Department at the Third Affiliated Hospital of Zhengzhou University between October 2019 and December 2020. The first thirty-minute processed electroencephalograms (EEGs) were clipped and filtered into EEG frequency bands (2 s each). A comparative assessment was conducted between the IESS group and the controls as well as the pre- and post-treatment in the IESS group. Mutual information values for each EEG channel were collected and compared including characteristic path length (CPL), node degree (ND), clustering coefficient (CC), and betweenness centrality (BC), based on graph theory. Results Comparing the control group, in the IESS group, there was an increase in CPL of the Delta band, and a decrease in ND and CC of the Delta band during the waking period, contrary to those during the sleeping period (P < 0.05), a decreased in CPL of the fast waves and an increase in ND and CC (P < 0.05) in the sleep-wake cycle, and a decrease in ND and CC of the Theta band in the waking phase. Post-treatment compared with the pre-treatment, during the waking ictal phase, there was a noted decrease in CPL in the Delta band and fast waves, while an increase was observed in ND and CC (P < 0.05). Conclusions The Delta band and fast waves are crucial components of the network attributes in IESS. Significance This investigation provides a precise characterization of the brain network in children afflicted with IESS, and lays the groundwork for predicting the prognosis using graph theory.
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Affiliation(s)
- Yan Dong
- Department of Pediatrics, The Third Affiliated Hospital of Zheng Zhou University, Zhengzhou, China
- Henan Key Laboratory of Child Brain Injury and Henan Pediatric Clinical Research Center, Third Affiliated Hospital and Institute of Neuroscience of Zhengzhou University, Zhengzhou, China
| | - Liang Jin
- Department of Pediatrics, The Third Affiliated Hospital of Zheng Zhou University, Zhengzhou, China
| | - Mengchun Li
- Department of Pediatrics, The Third Affiliated Hospital of Zheng Zhou University, Zhengzhou, China
| | - Ruofei Lian
- Department of Pediatrics, The Third Affiliated Hospital of Zheng Zhou University, Zhengzhou, China
| | - Gongao Wu
- Department of Pediatrics, The Third Affiliated Hospital of Zheng Zhou University, Zhengzhou, China
| | - Ruijuan Xu
- Department of Pediatrics, The Third Affiliated Hospital of Zheng Zhou University, Zhengzhou, China
- Department of Pediatrics, Zhumadian Central Hospital, Zhumadian, China
| | - Xiaoli Zhang
- Department of Pediatrics, The Third Affiliated Hospital of Zheng Zhou University, Zhengzhou, China
| | - Kaixian Du
- Department of Pediatrics, The Third Affiliated Hospital of Zheng Zhou University, Zhengzhou, China
| | - Tianming Jia
- Department of Pediatrics, The Third Affiliated Hospital of Zheng Zhou University, Zhengzhou, China
| | - Haiyan Wang
- Department of Pediatrics, The Third Affiliated Hospital of Zheng Zhou University, Zhengzhou, China
| | - Shichao Zhao
- Department of Pediatrics, The Third Affiliated Hospital of Zheng Zhou University, Zhengzhou, China
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Feitosa JA, Casseb RF, Camargo A, Brandao AF, Li LM, Castellano G. Graph analysis of cortical reorganization after virtual reality-based rehabilitation following stroke: a pilot randomized study. Front Neurol 2023; 14:1241639. [PMID: 37869147 PMCID: PMC10587561 DOI: 10.3389/fneur.2023.1241639] [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] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 09/22/2023] [Indexed: 10/24/2023] Open
Abstract
Introduction Stroke is the leading cause of functional disability worldwide. With the increase of the global population, motor rehabilitation of stroke survivors is of ever-increasing importance. In the last decade, virtual reality (VR) technologies for rehabilitation have been extensively studied, to be used instead of or together with conventional treatments such as physiotherapy or occupational therapy. The aim of this work was to evaluate the GestureCollection VR-based rehabilitation tool in terms of the brain changes and clinical outcomes of the patients. Methods Two groups of chronic patients underwent a rehabilitation treatment with (experimental) or without (control) complementation with GestureCollection. Functional magnetic resonance imaging exams and clinical assessments were performed before and after the treatment. A functional connectivity graph-based analysis was used to assess differences between the connections and in the network parameters strength and clustering coefficient. Results Patients in both groups showed improvement in clinical scales, but there were more increases in functional connectivity in the experimental group than in the control group. Discussion The experimental group presented changes in the connections between the frontoparietal and the somatomotor networks, associative cerebellum and basal ganglia, which are regions associated with reward-based motor learning. On the other hand, the control group also had results in the somatomotor network, in its ipsilateral connections with the thalamus and with the motor cerebellum, which are regions more related to a purely mechanical activity. Thus, the use of the GestureCollection system was successfully shown to promote neuroplasticity in several motor-related areas.
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Affiliation(s)
- Jamille Almeida Feitosa
- Gleb Wataghin Institute of Physics, University of Campinas – UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology – BRAINN, Campinas, Brazil
| | - Raphael Fernandes Casseb
- Brazilian Institute of Neuroscience and Neurotechnology – BRAINN, Campinas, Brazil
- Neuroimaging Laboratory, Department of Neurology, University of Campinas – UNICAMP, Campinas, Brazil
| | - Alline Camargo
- Neuroimaging Laboratory, Department of Neurology, University of Campinas – UNICAMP, Campinas, Brazil
| | - Alexandre Fonseca Brandao
- Gleb Wataghin Institute of Physics, University of Campinas – UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology – BRAINN, Campinas, Brazil
| | - Li Min Li
- Brazilian Institute of Neuroscience and Neurotechnology – BRAINN, Campinas, Brazil
- Neuroimaging Laboratory, Department of Neurology, University of Campinas – UNICAMP, Campinas, Brazil
| | - Gabriela Castellano
- Gleb Wataghin Institute of Physics, University of Campinas – UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology – BRAINN, Campinas, Brazil
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Spadone S, de Pasquale F, Chiacchiaretta P, Pavone L, Capotosto P, Delli Pizzi S, Digiovanni A, Sensi SL, Committeri G, Baldassarre A. Reduced Segregation of Brain Networks in Spatial Neglect After Stroke. Brain Connect 2023; 13:464-472. [PMID: 36128806 DOI: 10.1089/brain.2021.0184] [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] [Indexed: 11/12/2022] Open
Abstract
Background/Purpose: To investigate the association between the degree of spatial neglect and the changes of brain system segregation (SyS; i.e., the ratio of the extent to which brain networks interact internally and with each other) after stroke. Methods: A cohort of 20 patients with right hemisphere lesion was submitted to neuropsychological assessment as well as to resting-state functional magnetic resonance imaging session at acute stage after stroke. The severity of spatial neglect was quantified using the Center of Cancellation (CoC) scores of the Bells cancellation test. For each patient, resting-state functional connectivity (FC) matrices were assessed by implementing a brain parcellation of nine networks that included the visual network, dorsal attention network (DAN), ventral attention network (VAN), sensorimotor network (SMN), auditory network, cingulo-opercular network, language network, frontoparietal network, and default mode network (DMN). For each patient and each network, we then computed the SyS derived by subtracting the between-network FC from the within-network FC (normalized by the within-network FC). Finally, for each network, the CoC scores were correlated with the SyS. Results: The correlational analyses indicated a negative association between CoC and SyS in the DAN, VAN, SMN, and DMN (q < 0.05 false discovery rate [FDR]-corrected). Patients with more severe spatial neglect exhibited lower SyS and vice versa. Conclusion: The loss of segregation in multiple and specific networks provides a functional framework for the deficits in spatial and nonspatial attention and motor/exploratory ability observed in neglect patients.
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Affiliation(s)
- Sara Spadone
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | | | - Piero Chiacchiaretta
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | | | - Paolo Capotosto
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Stefano Delli Pizzi
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Anna Digiovanni
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Stefano L Sensi
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Giorgia Committeri
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Antonello Baldassarre
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
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de Pasquale F, Chiacchiaretta P, Pavone L, Sparano A, Capotosto P, Grillea G, Committeri G, Baldassarre A. Brain Topological Reorganization Associated with Visual Neglect After Stroke. Brain Connect 2023; 13:473-486. [PMID: 34269620 PMCID: PMC10618825 DOI: 10.1089/brain.2020.0969] [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] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Background/Purpose: To identify brain hubs that are behaviorally relevant for neglect after stroke as well as to characterize their functional architecture of communication. Methods: Twenty acute right hemisphere damaged patients underwent neuropsychological and resting-state functional magnetic resonance imaging sessions. Spatial neglect was assessed by means of the Center of Cancellation on the Bells Cancellation Test. For each patient, resting-state functional connectivity matrices were derived by adopting a brain parcellation scheme consisting of 153 nodes. For every node, we extracted its betweenness centrality (BC) defined as the portion of all shortest paths in the connectome involving such node. Then, neglect hubs were identified as those regions showing a high correlation between their BC and neglect scores. Results: A first set of neglect hubs was identified in multiple systems including dorsal attention and ventral attention, default mode, and frontoparietal executive-control networks within the damaged hemisphere as well as in the posterior and anterior cingulate cortex. Such cortical regions exhibited a loss of BC and increased (i.e., less efficient) weighted shortest path length (WSPL) related to severe neglect. Conversely, a second group of neglect hubs found in visual and motor networks, in the undamaged hemisphere, exhibited a pathological increase of BC and reduction of WSPL associated with severe neglect. Conclusion: The topological reorganization of the brain in neglect patients might reflect a maladaptive shift in processing spatial information from higher level associative-control systems to lower level visual and sensory-motor processing areas after a right hemisphere lesion.
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Affiliation(s)
| | - Piero Chiacchiaretta
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | | | | | - Paolo Capotosto
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | | | - Giorgia Committeri
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Antonello Baldassarre
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
- IRCCS NEUROMED, Pozzilli, Italy
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Li F, Lu L, Li H, Liu Y, Chen H, Yuan F, Jiang H, Yin X, Chen YC. Disrupted resting-state functional connectivity and network topology in mild traumatic brain injury: an arterial spin labelling study. Brain Commun 2023; 5:fcad254. [PMID: 37829696 PMCID: PMC10567062 DOI: 10.1093/braincomms/fcad254] [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: 07/05/2023] [Revised: 08/21/2023] [Accepted: 09/29/2023] [Indexed: 10/14/2023] Open
Abstract
Mild traumatic brain injury can cause different degrees of cognitive impairment and abnormal brain structure and functional connectivity, but there is still a lack of research on the functional connectivity and topological organization of cerebral blood flow fluctuations. This study explored the cerebral blood flow, functional connectivity and topological organization of the cerebral blood flow network in acute mild traumatic brain injury patients. In total, 48 mild traumatic brain injury patients and 46 well-matched healthy controls underwent resting-state arterial spin labelling perfusion MRI and neuropsychological assessments. The functional connectivity and topological organization of the cerebral blood flow network were analysed. Then, the correlation between the changes in cerebral blood flow network characteristics and cognitive function was explored. Acute mild traumatic brain injury patients showed decreased cerebral blood flow in the right insula and increased cerebral blood flow in the right inferior temporal gyrus and left superior temporal gyrus. Abnormal cerebral blood flow network connection patterns mainly occur in sensorimotor network, default mode network, cingulo-opercular network and occipital network-related regions. Furthermore, mild traumatic brain injury disrupted the topological organization of the whole brain, which manifested as (i) reduced global efficiency; (ii) abnormal degree centrality, betweenness centrality, nodal clustering coefficient and nodal efficiency; and (iii) decreased intermodular connectivity between the occipital network and sensorimotor network. Finally, the change in network topology was correlated with the cognitive score of the mild traumatic brain injury. This study provided evidence of abnormal functional connectivity and network topology based on cerebral blood flow in acute mild traumatic brain injury patients, revealing their potential use as early markers for mild traumatic brain injury, which may contribute to both disease diagnosis and assessment.
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Affiliation(s)
- Fengfang Li
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China
| | - Liyan Lu
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China
| | - Hui Li
- Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008, China
| | - Yin Liu
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China
| | - Huiyou Chen
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China
| | - Fang Yuan
- Department of Neurosurgery, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200235, China
| | - Hailong Jiang
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China
| | - Xindao Yin
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China
| | - Yu-Chen Chen
- Department of Radiology, Nanjing First Hospital, Nanjing Medical University, Nanjing 210006, China
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Fountain-Jones NM, Silk M, Appaw RC, Hamede R, Rushmore J, VanderWaal K, Craft ME, Carver S, Charleston M. The spectral underpinnings of pathogen spread on animal networks. Proc Biol Sci 2023; 290:20230951. [PMID: 37727089 PMCID: PMC10509581 DOI: 10.1098/rspb.2023.0951] [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: 04/25/2023] [Accepted: 08/14/2023] [Indexed: 09/21/2023] Open
Abstract
Predicting what factors promote or protect populations from infectious disease is a fundamental epidemiological challenge. Social networks, where nodes represent hosts and edges represent direct or indirect contacts between them, are important in quantifying these aspects of infectious disease dynamics. However, how network structure and epidemic parameters interact in empirical networks to promote or protect animal populations from infectious disease remains a challenge. Here we draw on advances in spectral graph theory and machine learning to build predictive models of pathogen spread on a large collection of empirical networks from across the animal kingdom. We show that the spectral features of an animal network are powerful predictors of pathogen spread for a variety of hosts and pathogens and can be a valuable proxy for the vulnerability of animal networks to pathogen spread. We validate our findings using interpretable machine learning techniques and provide a flexible web application for animal health practitioners to assess the vulnerability of a particular network to pathogen spread.
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Affiliation(s)
| | - Mathew Silk
- CEFE, University of Montpellier, CNRS, EPHE, IRD, University of Paul Valéry Montpellier 3, Montpellier, France
- Centre for Ecology and Conservation, University of Exeter, Penryn Campus, Penryn, UK
| | - Raima Carol Appaw
- School of Natural Sciences, University of Tasmania, Hobart 7001, Australia
| | - Rodrigo Hamede
- School of Natural Sciences, University of Tasmania, Hobart 7001, Australia
| | - Julie Rushmore
- Odum School of Ecology, University of Georgia, Athens, GA, USA
| | - Kimberly VanderWaal
- Department of Veterinary Population Medicine, University of Minnesota, St Paul, MN, USA
| | - Meggan E. Craft
- Department of Ecology, Evolution, and Behavior, University of Minnesota, St Paul, MN, USA
| | - Scott Carver
- School of Natural Sciences, University of Tasmania, Hobart 7001, Australia
| | - Michael Charleston
- School of Natural Sciences, University of Tasmania, Hobart 7001, Australia
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81
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Liu Y, Wang X, Zhang C. Study on the regional risk classification method for the prevention and control of emerging infectious diseases based on directed graph theory. Front Public Health 2023; 11:1211291. [PMID: 37818307 PMCID: PMC10561095 DOI: 10.3389/fpubh.2023.1211291] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 09/05/2023] [Indexed: 10/12/2023] Open
Abstract
Background Emerging infectious diseases are a class of diseases that are spreading rapidly and are highly contagious. It seriously affects social stability and poses a significant threat to human health, requiring urgent measures to deal with them. Its outbreak will very easily lead to the large-scale spread of the virus, causing social problems such as work stoppages and traffic control, thereby causing social panic and psychological unrest, affecting human activities and social stability, and even endangering lives. It is essential to prevent and control the spread of infectious diseases effectively. Purpose We aim to propose an effective method to classify the risk level of a new epidemic region by using graph theory and risk classification methods to provide a theoretical reference for the comprehensive evaluation and determination of epidemic prevention and control, as well as risk level classification. Methods Using the graph theory method, we first define the network structure of social groups and construct the risk transmission network of the new epidemic region. Then, combined with the risk classification method, the classification of high, medium, and low risk levels of the new epidemic region is discussed from two cases with common and looped graph nodes, respectively. Finally, the reasonableness of the classification method is verified by simulation data. Results The directed weighted scale-free network can better describe the transmission law of an epidemic. Moreover, the proposed method of classifying the risk level of a region by using the correlation function between two regions and the risk value of the regional nodes can effectively evaluate the risk level of different regions in the new epidemic region. The experiments show that the number of medium and high risk nodes shows no increasing trend. The number of high-risk regions is relatively small compared to medium-risk regions, and the number of low-risk regions is the largest. Conclusions It is necessary to distinguish scientifically between the risk level of the epidemic area and the neighboring regions so that the constructed social network model of the epidemic region's spread risk can better describe the spread of the epidemic risk in the social network relations.
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Affiliation(s)
- Yong Liu
- School of Science, Xi'an University of Architecture and Technology, Xi'an, China
| | - Xiao Wang
- School of Science, Xi'an University of Architecture and Technology, Xi'an, China
| | - Chongqi Zhang
- School of Science, Xi'an University of Architecture and Technology, Xi'an, China
- School of Economics and Statistics, Guangzhou University, Guangzhou, China
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82
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Gao Y, Wang S, Xin H, Feng M, Zhang Q, Sui C, Guo L, Liang C, Wen H. Disrupted Gray Matter Networks Associated with Cognitive Dysfunction in Cerebral Small Vessel Disease. Brain Sci 2023; 13:1359. [PMID: 37891728 PMCID: PMC10605932 DOI: 10.3390/brainsci13101359] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 09/15/2023] [Accepted: 09/20/2023] [Indexed: 10/29/2023] Open
Abstract
This study aims to investigate the disrupted topological organization of gray matter (GM) structural networks in cerebral small vessel disease (CSVD) patients with cerebral microbleeds (CMBs). Subject-wise structural networks were constructed from GM volumetric features of 49 CSVD patients with CMBs (CSVD-c), 121 CSVD patients without CMBs (CSVD-n), and 74 healthy controls. The study used graph theory to analyze the global and regional properties of the network and their correlation with cognitive performance. We found that both the control and CSVD groups exhibited efficient small-world organization in GM networks. However, compared to controls, CSVD-c and CSVD-n patients exhibited increased global and local efficiency (Eglob/Eloc) and decreased shortest path lengths (Lp), indicating increased global integration and local specialization in structural networks. Although there was no significant global topology change, partially reorganized hub distributions were found between CSVD-c and CSVD-n patients. Importantly, regional topology in nonhub regions was significantly altered between CSVD-c and CSVD-n patients, including the bilateral anterior cingulate gyrus, left superior parietal gyrus, dorsolateral superior frontal gyrus, and right MTG, which are involved in the default mode network (DMN) and sensorimotor functional modules. Intriguingly, the global metrics (Eglob, Eloc, and Lp) were significantly correlated with MoCA, AVLT, and SCWT scores in the control group but not in the CSVD-c and CSVD-n groups. In contrast, the global metrics were significantly correlated with the SDMT score in the CSVD-s and CSVD-n groups but not in the control group. Patients with CSVD show a disrupted balance between local specialization and global integration in their GM structural networks. The altered regional topology between CSVD-c and CSVD-n patients may be due to different etiological contributions, which may offer a novel understanding of the neurobiological processes involved in CSVD with CMBs.
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Affiliation(s)
- Yian Gao
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China; (Y.G.); (C.S.)
| | - Shengpei Wang
- Research Center for Brain-Inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing 100040, China;
- University of Chinese Academy of Sciences, Beijing 101408, China
| | - Haotian Xin
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, No. 45 Chang-Chun St., Xicheng District, Beijing 100054, China; (H.X.); (M.F.)
| | - Mengmeng Feng
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, No. 45 Chang-Chun St., Xicheng District, Beijing 100054, China; (H.X.); (M.F.)
| | - Qihao Zhang
- Department of Radiology, Weill Cornell Medical College, New York. 407 East 61st Street, New York, NY 10044, USA;
| | - Chaofan Sui
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China; (Y.G.); (C.S.)
| | - Lingfei Guo
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging, Ministry of Education, Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, China; (Y.G.); (C.S.)
| | - Changhu Liang
- Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jing-Wu Road No. 324, Jinan 250021, China
| | - Hongwei Wen
- Key Laboratory of Cognition and Personality (Ministry of Education), Faculty of Psychology, Southwest University, Chongqing 400715, China
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Tyler S, Laforge C, Guzzo A, Nicolaï A, Maisuradze GG, Senet P. Einstein Model of a Graph to Characterize Protein Folded/Unfolded States. Molecules 2023; 28:6659. [PMID: 37764437 PMCID: PMC10536427 DOI: 10.3390/molecules28186659] [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: 08/15/2023] [Revised: 09/11/2023] [Accepted: 09/14/2023] [Indexed: 09/29/2023] Open
Abstract
The folded structures of proteins can be accurately predicted by deep learning algorithms from their amino-acid sequences. By contrast, in spite of decades of research studies, the prediction of folding pathways and the unfolded and misfolded states of proteins, which are intimately related to diseases, remains challenging. A two-state (folded/unfolded) description of protein folding dynamics hides the complexity of the unfolded and misfolded microstates. Here, we focus on the development of simplified order parameters to decipher the complexity of disordered protein structures. First, we show that any connected, undirected, and simple graph can be associated with a linear chain of atoms in thermal equilibrium. This analogy provides an interpretation of the usual topological descriptors of a graph, namely the Kirchhoff index and Randić resistance, in terms of effective force constants of a linear chain. We derive an exact relation between the Kirchhoff index and the average shortest path length for a linear graph and define the free energies of a graph using an Einstein model. Second, we represent the three-dimensional protein structures by connected, undirected, and simple graphs. As a proof of concept, we compute the topological descriptors and the graph free energies for an all-atom molecular dynamics trajectory of folding/unfolding events of the proteins Trp-cage and HP-36 and for the ensemble of experimental NMR models of Trp-cage. The present work shows that the local, nonlocal, and global force constants and free energies of a graph are promising tools to quantify unfolded/disordered protein states and folding/unfolding dynamics. In particular, they allow the detection of transient misfolded rigid states.
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Affiliation(s)
- Steve Tyler
- Laboratoire Interdisciplinaire Carnot de Bourgogne, UMR CNRS 6303, Université de Bourgogne, 21078 Dijon CEDEX, France
| | - Christophe Laforge
- Laboratoire Interdisciplinaire Carnot de Bourgogne, UMR CNRS 6303, Université de Bourgogne, 21078 Dijon CEDEX, France
| | - Adrien Guzzo
- Laboratoire Interdisciplinaire Carnot de Bourgogne, UMR CNRS 6303, Université de Bourgogne, 21078 Dijon CEDEX, France
| | - Adrien Nicolaï
- Laboratoire Interdisciplinaire Carnot de Bourgogne, UMR CNRS 6303, Université de Bourgogne, 21078 Dijon CEDEX, France
| | - Gia G. Maisuradze
- Baker Laboratory of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853, USA
| | - Patrick Senet
- Laboratoire Interdisciplinaire Carnot de Bourgogne, UMR CNRS 6303, Université de Bourgogne, 21078 Dijon CEDEX, France
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84
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Huang JJ, Feng XL, Dong YY, Zhang C, Xie LJ, Cheng JK, Gao TY. Construction of ecological security pattern in Ningbo based on remote sensing ecological index and graph theory knowledge. Ying Yong Sheng Tai Xue Bao 2023; 34:2489-2497. [PMID: 37899116 DOI: 10.13287/j.1001-9332.202309.027] [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] [Indexed: 10/31/2023]
Abstract
Constructing ecological security pattern and identifying ecological important areas are the focus of current research on regional ecological security. With Ningbo City as a case study area, we identified ecological sources by remote sensing ecological index, the ecological corridors and pinch point by circuit theory model, and the minimum spanning tree and cuts by graph theory algorithm. The results showed that there were 203 ecological sources in Ningbo, and that the main type of land cover was forest, including a small amount of paddy fields and flooded vegetation. There were 368 ecological corridors with a total length of 573.42 km, being dense in the southwest and sparse in the northeast. There were 91 ecological pinch points, which mainly distributed between coastal areas and closely related ecological sources. According to current situation, we put forward the optimization strategy with 187 primary corridors, 181 secondary corridors, 50 ecological restoration priority areas and 59 long-term ecological restoration areas. The optimization strategy combined with graph theory and circuit theory model would provide a refe-rence for the constructing of ecological security pattern.
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Affiliation(s)
- Jun-Jie Huang
- Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, Zhejiang, China
| | - Xiu-Li Feng
- Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, Zhejiang, China
| | - Yu-Yi Dong
- Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, Zhejiang, China
| | - Chi Zhang
- Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, Zhejiang, China
| | - Li-Jian Xie
- Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, Zhejiang, China
| | - Jun-Kai Cheng
- Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, Zhejiang, China
| | - Tian-Yu Gao
- Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, Zhejiang, China
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85
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Baxter LC, Limback-Stokin M, Patten KJ, Arreola AC, Locke DEC, Hu L, Zhou Y, Caselli RJ. Hippocampal connectivity and memory decline in cognitively intact APOE ε4 carriers. Alzheimers Dement 2023; 19:3806-3814. [PMID: 36906845 DOI: 10.1002/alz.13023] [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: 08/24/2022] [Revised: 02/06/2023] [Accepted: 02/07/2023] [Indexed: 03/13/2023]
Abstract
INTRODUCTION Resting-state functional magnetic resonance imaging (fMRI) graph theory may help detect subtle functional connectivity changes affecting memory prior to impairment. METHODS Cognitively normal apolipoprotein E (APOE) ε4 carriers/noncarriers underwent longitudinal cognitive assessment and one-time MRI. The relationship of left/right hippocampal connectivity and memory trajectory were compared between carriers/noncarriers. RESULTS Steepness of verbal memory decline correlated with decreased connectivity in the left hippocampus, only among APOE ε4 carriers. Right hippocampal metrics were not correlated with memory and there were no significant correlations in the noncarriers. Verbal memory decline correlated with left hippocampal volume loss for both carriers and noncarriers, with no other significant volumetric findings. DISCUSSION Findings support early hippocampal dysfunction in intact carriers, the AD disconnection hypothesis, and left hippocampal dysfunction earlier than the right. Combining lateralized graph theoretical metrics with a sensitive measure of memory trajectory allowed for detection of early-stage changes in APOE ε4 carriers before symptoms of mild cognitive impairment are present. HIGHLIGHTS Graph theory connectivity detects preclinical hippocampal changes in APOE ε4 carriers. The AD disconnection hypothesis was supported in unimpaired APOE ε4 carriers. Hippocampal dysfunction starts asymmetrically on the left.
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Affiliation(s)
- Leslie C Baxter
- Department of Psychiatry and Psychology, Mayo Clinic Arizona, Phoenix, Arizona, USA
| | | | - K Jakob Patten
- Department of Speech and Hearing Sciences, Arizona State University, Tempe, Arizona, USA
| | | | - Dona E C Locke
- Department of Psychiatry and Psychology, Mayo Clinic Arizona, Phoenix, Arizona, USA
| | - Leland Hu
- Department of Radiology, Mayo Clinic Arizona, Phoenix, Arizona, USA
| | - Yuxiang Zhou
- Department of Medical Physics, Mayo Clinic Arizona, Phoenix, Arizona, USA
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Theis N, Rubin J, Cape J, Iyengar S, Prasad KM. Threshold Selection for Brain Connectomes. Brain Connect 2023; 13:383-393. [PMID: 37166374 PMCID: PMC10517318 DOI: 10.1089/brain.2022.0082] [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] [Indexed: 05/12/2023] Open
Abstract
Introduction: Structural and functional brain connectomes represent macroscale data collected through techniques such as magnetic resonance imaging (MRI). Connectomes may contain noise that contributes to false-positive edges, thereby obscuring structure-function relationships and data interpretation. Thresholding procedures can be applied to reduce network density by removing low-signal edges, but there is limited consensus on appropriate selection of thresholds. This article compares existing thresholding methods and introduces a novel alternative "objective function" thresholding method. Methods: The performance of thresholding approaches, based on percolation and objective functions, is assessed by (1) computing the normalized mutual information (NMI) of community structure between a known network and a simulated, perturbed networks to which various forms of thresholding have been applied, and by (2) comparing the density and the clustering coefficient (CC) between the baseline and thresholded networks. An application to empirical data is provided. Results: Our proposed objective function-based threshold exhibits the best performance in terms of resulting in high similarity between the underlying networks and their perturbed, thresholded counterparts, as quantified by NMI and CC analysis on the simulated functional networks. Discussion: Existing network thresholding methods yield widely different results when graph metrics are subsequently computed. Thresholding based on the objective function maintains a set of edges such that the resulting network shares the community structure and clustering features present in the original network. This outcome provides a proof of principle that objective function thresholding could offer a useful approach to reducing the network density of functional connectivity data.
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Affiliation(s)
- Nicholas Theis
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Jonathan Rubin
- Department of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Joshua Cape
- Department of Statistics, University of Wisconsin–Madison, Madison, Wisconsin, USA
- Department of Statistics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Satish Iyengar
- Department of Statistics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Konasale M. Prasad
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
- VA Pittsburgh Healthcare System, Pittsburgh, Pennsylvania, USA
- Department of Bioengineering, University of Pittsburgh Swanson School of Engineering, Pittsburgh, Pennsylvania, USA
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87
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Pommy J, Conant L, Butts AM, Nencka A, Wang Y, Franczak M, Glass-Umfleet L. A graph theoretic approach to neurodegeneration: five data-driven neuropsychological subtypes in mild cognitive impairment. Neuropsychol Dev Cogn B Aging Neuropsychol Cogn 2023; 30:903-922. [PMID: 36648118 DOI: 10.1080/13825585.2022.2163973] [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] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 12/26/2022] [Indexed: 01/18/2023]
Abstract
Mild cognitive Impairment (MCI) is notoriously heterogenous in terms of clinical presentation, neuroimaging correlates, and subsequent progression. Predicting who will progress to dementia, which type of dementia, and over what timeframe is challenging. Previous work has attempted to identify MCI subtypes using neuropsychological measures in an effort to address this challenge; however, there is no consensus on approach, which may account for some of the variability. Using a hierarchical community detection approach, we examined cognitive subtypes within an MCI sample (from the Alzheimer's Disease Neuroimaging Initiative [ADNI] study). We then examined whether these subtypes were related to biomarkers (e.g., cortical volumes, fluorodeoxyglucose (FDG)-positron emission tomography (PET) hypometabolism) or clinical progression. We identified five communities (i.e., cognitive subtypes) within the MCI sample: 1) predominantly memory impairment, 2) predominantly language impairment, 3) cognitively normal, 4) multidomain, with notable executive dysfunction, 5) multidomain, with notable processing speed impairment. Community membership was significantly associated with 1) cortical volume in the hippocampus, entorhinal cortex, and fusiform cortex; 2) FDG PET hypometabolism in the posterior cingulate, angular gyrus, and inferior/middle temporal gyrus; and 3) conversion to dementia at follow up. Overall, community detection as an approach appears a viable method for identifying unique cognitive subtypes in a neurodegenerative sample that were linked to several meaningful biomarkers and modestly with progression at one year follow up.
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Affiliation(s)
- Jessica Pommy
- Department of Neurology, Medical College of Wisconsin, Milwaukee, United States
| | - L Conant
- Department of Neurology, Medical College of Wisconsin, Milwaukee, United States
| | - A M Butts
- Department of Neurology, Medical College of Wisconsin, Milwaukee, United States
| | - A Nencka
- Department of Radiology, Medical College of Wisconsin, Milwaukee, United States
| | - Y Wang
- Department of Radiology, Medical College of Wisconsin, Milwaukee, United States
| | - M Franczak
- Department of Neurology, Medical College of Wisconsin, Milwaukee, United States
| | - L Glass-Umfleet
- Department of Neurology, Medical College of Wisconsin, Milwaukee, United States
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Cook KM, De Asis-Cruz J, Basu SK, Andescavage N, Murnick J, Spoehr E, du Plessis AJ, Limperopoulos C. Ex-utero third trimester developmental changes in functional brain network organization in infants born very and extremely preterm. Front Neurosci 2023; 17:1214080. [PMID: 37719160 PMCID: PMC10502339 DOI: 10.3389/fnins.2023.1214080] [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: 04/28/2023] [Accepted: 08/22/2023] [Indexed: 09/19/2023] Open
Abstract
Introduction The latter half of gestation is a period of rapid brain development, including the formation of fundamental functional brain network architecture. Unlike in-utero fetuses, infants born very and extremely preterm undergo these critical maturational changes in the extrauterine environment, with growing evidence suggesting this may result in altered brain networks. To date, however, the development of functional brain architecture has been unexplored. Methods From a prospective cohort of preterm infants, graph parameters were calculated for fMRI scans acquired prior to reaching term equivalent age. Eight graph properties were calculated, Clustering Coefficient (C), Characteristic Path Length (L), Modularity (Q), Local Efficiency (LE), Global Efficiency (GE), Normalized Clustering (λ), Normalized Path Length (γ), and Small-Worldness (σ). Properties were first compared to values generated from random and lattice networks and cost efficiency was evaluated. Subsequently, linear mixed effect models were used to assess relationship with postmenstrual age and infant sex. Results A total of 111 fMRI scans were acquired from 85 preterm infants born at a mean GA 28.93 ± 2.8. Infants displayed robust small world properties as well as both locally and globally efficient networks. Regression models found that GE increased while L, Q, λ, γ, and σ decreased with increasing postmenstrual age following multiple comparison correction (r2Adj range 0.143-0.401, p < 0048), with C and LE exhibited trending increases with age. Discussion This is the first direct investigation on the extra-uterine formation of functional brain architecture in preterm infants. Importantly, our results suggest that changes in functional architecture with increasing age exhibit a different trajectory relative to in utero fetus. Instead, they exhibit developmental changes more similar to the early postnatal period in term born infants.
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Affiliation(s)
- Kevin M. Cook
- Developing Brain Institute, Children’s National Hospital, Washington, DC, United States
| | | | - Sudeepta K. Basu
- Developing Brain Institute, Children’s National Hospital, Washington, DC, United States
| | - Nickie Andescavage
- Developing Brain Institute, Children’s National Hospital, Washington, DC, United States
| | - Jonathan Murnick
- Department of Diagnostic Imaging & Radiology, Children’s National Health System, Children’s National Hospital, Washington, DC, United States
| | - Emma Spoehr
- Developing Brain Institute, Children’s National Hospital, Washington, DC, United States
| | - Adré J. du Plessis
- Prenatal Pediatrics Institute, Children’s National Hospital, Washington, DC, United States
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89
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Perraud E, Wang J, Dussiot A, Fouillet H, Mariotti F. Identifying the most Efficient Detailed Trajectories toward Healthy Diets-A Graph-Based Analysis. J Nutr 2023; 153:2744-2752. [PMID: 37479114 DOI: 10.1016/j.tjnut.2023.07.007] [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: 05/12/2023] [Revised: 07/11/2023] [Accepted: 07/17/2023] [Indexed: 07/23/2023] Open
Abstract
BACKGROUND Much effort has been devoted to defining healthy diets, which could lower the burden of disease and provide targets for populations. However, these target diets are far removed from current diets, so at best, the population is expected to move slowly along a trajectory. OBJECTIVE Our aim was to characterize the different possible trajectories toward a target diet and identify the most efficient one for health to point out the first dietary changes being the most urgent to implement. METHODS Using graph theory, we have developed a new method to represent in a graph all stepwise change trajectories toward a target healthy diet, with trajectories all avoiding risk of nutrient deficiency. Then, we have identified and characterized the trajectory with the highest value for long-term health. Observed male and female average diets are from the French representative survey INCA3, and target diets were set using multicriteria optimization. The best trajectories were found using the Dijkstra algorithm with the Health risk criteria based on epidemiological data. RESULTS Within ∼2.6M diets in the graphs, we found optimal trajectories that were rather similar for males and females regarding the most efficient changes in the first phase of the pathways. In particular, we found that a 1-step increase in the consumption of whole/semirefined bread (60 g) was the first step in all healthiest trajectories. In males, the subsequent decrease in red meat was immediately preceded by increases in legumes. CONCLUSIONS We show simple practical dietary changes that can be prioritized along an integral pathway that is the most efficient overall for health when transiting toward a distant healthy diet. We put forward a new method to analyze dietary strategy for public health transition and highlight the first critical steps to prioritize.
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Affiliation(s)
- Elie Perraud
- Université Paris-Saclay, AgroParisTech, INRAE, UMR PNCA, 91120, Palaiseau, France
| | - Juhui Wang
- Université Paris-Saclay, AgroParisTech, INRAE, UMR PNCA, 91120, Palaiseau, France
| | - Alison Dussiot
- Université Paris-Saclay, AgroParisTech, INRAE, UMR PNCA, 91120, Palaiseau, France
| | - Hélène Fouillet
- Université Paris-Saclay, AgroParisTech, INRAE, UMR PNCA, 91120, Palaiseau, France
| | - François Mariotti
- Université Paris-Saclay, AgroParisTech, INRAE, UMR PNCA, 91120, Palaiseau, France.
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Carozza S, Holmes J, Vértes PE, Bullmore E, Arefin TM, Pugliese A, Zhang J, Kaffman A, Akarca D, Astle DE. Early adversity changes the economic conditions of mouse structural brain network organization. Dev Psychobiol 2023; 65:e22405. [PMID: 37607894 PMCID: PMC10505050 DOI: 10.1002/dev.22405] [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: 11/24/2022] [Revised: 05/09/2023] [Accepted: 05/31/2023] [Indexed: 08/24/2023]
Abstract
Early adversity can change educational, cognitive, and mental health outcomes. However, the neural processes through which early adversity exerts these effects remain largely unknown. We used generative network modeling of the mouse connectome to test whether unpredictable postnatal stress shifts the constraints that govern the organization of the structural connectome. A model that trades off the wiring cost of long-distance connections with topological homophily (i.e., links between regions with shared neighbors) generated simulations that successfully replicate the rodent connectome. The imposition of early life adversity shifted the best-performing parameter combinations toward zero, heightening the stochastic nature of the generative process. Put simply, unpredictable postnatal stress changes the economic constraints that reproduce rodent connectome organization, introducing greater randomness into the development of the simulations. While this change may constrain the development of cognitive abilities, it could also reflect an adaptive mechanism that facilitates effective responses to future challenges.
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Affiliation(s)
- Sofia Carozza
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
| | - Joni Holmes
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
- School of PsychologyUniversity of East AngliaNorwichUK
| | | | - Ed Bullmore
- Department of PsychiatryUniversity of CambridgeCambridgeUK
- Department of Clinical Neurosciences, Wolfson Brain Imaging CentreUniversity of CambridgeCambridgeUK
| | - Tanzil M. Arefin
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of RadiologyNew York University School of MedicineNew YorkNew YorkUSA
| | - Alexa Pugliese
- Department of PsychiatryYale University School of MedicineNew HavenConnecticutUSA
| | - Jiangyang Zhang
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of RadiologyNew York University School of MedicineNew YorkNew YorkUSA
| | - Arie Kaffman
- Department of PsychiatryYale University School of MedicineNew HavenConnecticutUSA
| | - Danyal Akarca
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
| | - Duncan E. Astle
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
- Department of PsychiatryUniversity of CambridgeCambridgeUK
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91
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Javaheripour N, Wagner G, de la Cruz F, Walter M, Szycik GR, Tietze FA. Altered brain network organization in adults with Asperger's syndrome: decreased connectome transitivity and assortativity with increased global efficiency. Front Psychiatry 2023; 14:1223147. [PMID: 37701094 PMCID: PMC10494541 DOI: 10.3389/fpsyt.2023.1223147] [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: 05/16/2023] [Accepted: 07/26/2023] [Indexed: 09/14/2023] Open
Abstract
Introduction Autism spectrum disorder (ASD) is a neurodevelopmental disorder that persists into adulthood with both social and cognitive disturbances. Asperger's syndrome (AS) was a distinguished subcategory of autism in the DSM-IV-TR defined by specific symptoms including difficulties in social interactions, inflexible thinking patterns, and repetitive behaviour without any delay in language or cognitive development. Studying the functional brain organization of individuals with these specific symptoms may help to better understand Autism spectrum symptoms. Methods The aim of this study is therefore to investigate functional connectivity as well as functional network organization characteristics using graph-theory measures of the whole brain in male adults with AS compared to healthy controls (HC) (AS: n = 15, age range 21-55 (mean ± sd: 39.5 ± 11.6), HC: n = 15, age range 22-57 [mean ± sd: 33.5 ± 8.5]). Results No significant differences were found when comparing the region-by-region connectivity at the whole-brain level between the AS group and HC. However, measures of "transitivity," which reflect local information processing and functional segregation, and "assortativity," indicating network resilience, were reduced in the AS group compared to HC. On the other hand, global efficiency, which represents the overall effectiveness and speed of information transfer across the entire brain network, was increased in the AS group. Discussion Our findings suggest that individuals with AS may have alterations in the organization and functioning of brain networks, which could contribute to the distinctive cognitive and behavioural features associated with this condition. We suggest further research to explore the association between these altered functional patterns in brain networks and specific behavioral traits observed in individuals with AS, which could provide valuable insights into the underlying mechanisms of its symptomatology.
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Affiliation(s)
- Nooshin Javaheripour
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Gerd Wagner
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Center for Intervention and Research on Adaptive and Maladaptive Brain Circuits Underlying Mental Health (C-I-R-C), Jena, Germany
| | - Feliberto de la Cruz
- Department of Psychosomatic Medicine and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Martin Walter
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Center for Intervention and Research on Adaptive and Maladaptive Brain Circuits Underlying Mental Health (C-I-R-C), Jena, Germany
- Clinical Affective Neuroimaging Laboratory (CANLAB), Magdeburg, Germany
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
- Leibniz Institute for Neurobiology, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
- German Center for Mental Health (DZPG), Jena, Germany
| | - Gregor R. Szycik
- Department of Psychiatry and Psychotherapy, Hannover Medical School, Hannover, Germany
| | - Fabian-Alexander Tietze
- Department of Psychiatry and Psychotherapy, Jüdisches Krankenhaus Berlin—Berlin Jewish Hospital, Academic Teaching Hospital of the Charité—Universitätsmedizin Berlin, Berlin, Germany
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92
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Peng Y, Zheng Y, Yuan Z, Guo J, Fan C, Li C, Deng J, Song S, Qiao J, Wang J. The characteristics of brain network in patient with post-stroke depression under cognitive task condition. Front Neurosci 2023; 17:1242543. [PMID: 37655007 PMCID: PMC10467271 DOI: 10.3389/fnins.2023.1242543] [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: 06/19/2023] [Accepted: 08/04/2023] [Indexed: 09/02/2023] Open
Abstract
Objectives Post-stroke depression (PSD) may be associated with the altered brain network property. This study aimed at exploring the brain network characteristics of PSD under the classic cognitive task, i.e., the oddball task, in order to promote our understanding of the pathogenesis and the diagnosis of PSD. Methods Nineteen stroke survivors with PSD and 18 stroke survivors with no PSD (non-PSD) were recruited. The functional near-infrared spectroscopy (fNIRS) covering the dorsolateral prefrontal cortex was recorded during the oddball task state and the resting state. The brain network characteristics were extracted using the graph theory and compared between the PSD and the non-PSD subjects. In addition, the classification performance between the PSD and non-PSD subjects was evaluated using features in the resting and the task state, respectively. Results Compared with the resting state, more brain network characteristics in the task state showed significant differences between the PSD and non-PSD groups, resulting in better classification performance. In the task state, the assortativity, clustering coefficient, characteristic path length, and local efficiency of the PSD subjects was larger compared with the non-PSD subjects while the global efficiency of the PSD subjects was smaller than that of the non-PSD subjects. Conclusion The altered brain network properties associated with PSD in the cognitive task state were more distinct compared with the resting state, and the ability of the brain network to resist attack and transmit information was reduced in PSD patients in the task state. Significance This study demonstrated the feasibility and superiority of investigating brain network properties in the task state for the exploration of the pathogenesis and new diagnosis methods for PSD.
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Affiliation(s)
- Yu Peng
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Sciences and Technology, Institute of Biomedical Engineering, Xi’an Jiaotong University, Xi’an, China
- Department of Rehabilitation, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Yang Zheng
- The State Key Laboratory for Manufacturing Systems Engineering, School of Mechanical Engineering, Institute of Engineering and Medicine Interdisciplinary Studies, Xi’an Jiaotong University, Xi’an, China
| | - Ziwen Yuan
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Sciences and Technology, Institute of Biomedical Engineering, Xi’an Jiaotong University, Xi’an, China
- Department of Rehabilitation, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Jing Guo
- Department of Rehabilitation, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Chunyang Fan
- Department of Rehabilitation, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Chenxi Li
- Department of Military Medical Psychology, Air Force Medical University, Xi’an, China
| | - Jingyuan Deng
- Department of Rehabilitation, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Siming Song
- Department of Rehabilitation, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Jin Qiao
- Department of Rehabilitation, First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Jue Wang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Sciences and Technology, Institute of Biomedical Engineering, Xi’an Jiaotong University, Xi’an, China
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93
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Fthenakis ZG. A Generalized Nomenclature Scheme for Graphene Pores, Flakes, and Edges, and an Algorithm for Their Generation and Numbering. Nanomaterials (Basel) 2023; 13:2343. [PMID: 37630928 PMCID: PMC10459746 DOI: 10.3390/nano13162343] [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] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 08/02/2023] [Accepted: 08/09/2023] [Indexed: 08/27/2023]
Abstract
In the present study, we generalize our recently proposed nomenclature scheme for porous graphene structures to include graphene flakes and (periodic) edges, i.e., nanographenes and graphene nanoribbons. The proposed nomenclature scheme is a complete scheme that similarly treats all these structures. Beyond this generalization, we study the geometric features of graphene flakes and edges based on ideas from the graph theory, as well as the pore-flake duality. Based on this study, we propose an algorithm for the systematic generation, identification, and numbering of graphene pores, flakes, and edges. The algorithm and the nomenclature scheme can also be used for flakes and edges of similar honeycomb systems.
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Affiliation(s)
- Zacharias G. Fthenakis
- Istituto Nanoscienze, Consiglio Nazionale delle Ricerche (CNR), 56127 Pisa, Italy; or
- Theoretical and Physical Chemistry Institute, National Hellenic Research Foundation, 11635 Athens, Greece
- National Enterprise for nanoScience and nanoTechnology (NEST), Scuola Normale Superiore, 56127 Pisa, Italy
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94
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Kreitz S, Mennecke A, Konerth L, Rösch J, Nagel AM, Laun FB, Uder M, Dörfler A, Hess A. 3T vs. 7T fMRI: capturing early human memory consolidation after motor task utilizing the observed higher functional specificity of 7T. Front Neurosci 2023; 17:1215400. [PMID: 37638321 PMCID: PMC10448826 DOI: 10.3389/fnins.2023.1215400] [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: 05/01/2023] [Accepted: 07/17/2023] [Indexed: 08/29/2023] Open
Abstract
Objective Functional magnetic resonance imaging (fMRI) visualizes brain structures at increasingly higher resolution and better signal-to-noise ratio (SNR) as field strength increases. Yet, mapping the blood oxygen level dependent (BOLD) response to distinct neuronal processes continues to be challenging. Here, we investigated the characteristics of 7 T-fMRI compared to 3 T-fMRI in the human brain beyond the effect of increased SNR and verified the benefits of 7 T-fMRI in the detection of tiny, highly specific modulations of functional connectivity in the resting state following a motor task. Methods 18 healthy volunteers underwent two resting state and a stimulus driven measurement using a finger tapping motor task at 3 and 7 T, respectively. The SNR for each field strength was adjusted by targeted voxel size variation to minimize the effect of SNR on the field strength specific outcome. Spatial and temporal characteristics of resting state ICA, network graphs, and motor task related activated areas were compared. Finally, a graph theoretical approach was used to detect resting state modulation subsequent to a simple motor task. Results Spatial extensions of resting state ICA and motor task related activated areas were consistent between field strengths, but temporal characteristics varied, indicating that 7 T achieved a higher functional specificity of the BOLD response than 3 T-fMRI. Following the motor task, only 7 T-fMRI enabled the detection of highly specific connectivity modulations representing an "offline replay" of previous motor activation. Modulated connections of the motor cortex were directly linked to brain regions associated with memory consolidation. Conclusion These findings reveal how memory processing is initiated even after simple motor tasks, and that it begins earlier than previously shown. Thus, the superior capability of 7 T-fMRI to detect subtle functional dynamics promises to improve diagnostics and therapeutic assessment of neurological diseases.
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Affiliation(s)
- Silke Kreitz
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Angelika Mennecke
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Laura Konerth
- Institute for Pharmacology and Toxicology, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Julie Rösch
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Armin M. Nagel
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Frederik B. Laun
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Michael Uder
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Arnd Dörfler
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Andreas Hess
- Institute for Pharmacology and Toxicology, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Erlangen, Germany
- FAU NeW—Research Center for New Bioactive Compounds, Erlangen, Germany
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95
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Lv Y, He J, Xu W, Wang L. Design of Low-Density Parity-Check Code Pair for Joint Source-Channel Coding Systems Based on Graph Theory. Entropy (Basel) 2023; 25:1189. [PMID: 37628222 PMCID: PMC10453591 DOI: 10.3390/e25081189] [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] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 07/26/2023] [Accepted: 08/07/2023] [Indexed: 08/27/2023]
Abstract
In this article, a graph-theoretic method (taking advantage of constraints among sets associated with the corresponding parity-check matrices) is applied for the construction of a double low-density parity-check (D-LDPC) code (also known as LDPC code pair) in a joint source-channel coding (JSCC) system. Specifically, we pre-set the girth of the parity-check matrix for the LDPC code pair when jointly designing the two LDPC codes, which are constructed by following the set constraints. The constructed parity-check matrices for channel codes comprise an identity submatrix and an additional submatrix, whose column weights can be pre-set to be any positive integer numbers. Simulation results illustrate that the constructed D-LDPC codes exhibit significant performance improvement and enhanced flexible frame length (i.e., adaptability under various channel conditions) compared with the benchmark code pair.
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Affiliation(s)
- Yijie Lv
- Department of Information and Communication Engineering, Xiamen University, Xiamen 361005, China; (Y.L.); (L.W.)
| | - Jiguang He
- Technology Innovation Institute, Abu Dhabi P.O. Box 9639, United Arab Emirates;
- Centre for Wireless Communications, University of Oulu, 90014 Oulu, Finland
| | - Weikai Xu
- Department of Information and Communication Engineering, Xiamen University, Xiamen 361005, China; (Y.L.); (L.W.)
| | - Lin Wang
- Department of Information and Communication Engineering, Xiamen University, Xiamen 361005, China; (Y.L.); (L.W.)
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96
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Zhang X, Lai H, Li Q, Yang X, Pan N, He M, Kemp GJ, Wang S, Gong Q. Disrupted brain gray matter connectome in social anxiety disorder: a novel individualized structural covariance network analysis. Cereb Cortex 2023; 33:9627-9638. [PMID: 37381581 DOI: 10.1093/cercor/bhad231] [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] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Revised: 05/11/2023] [Accepted: 06/10/2023] [Indexed: 06/30/2023] Open
Abstract
Phenotyping approaches grounded in structural network science can offer insights into the neurobiological substrates of psychiatric diseases, but this remains to be clarified at the individual level in social anxiety disorder (SAD). Using a recently developed approach combining probability density estimation and Kullback-Leibler divergence, we constructed single-subject structural covariance networks (SCNs) based on multivariate morphometry (cortical thickness, surface area, curvature, and volume) and quantified their global/nodal network properties using graph-theoretical analysis. We compared network metrics between SAD patients and healthy controls (HC) and analyzed the relationship to clinical characteristics. We also used support vector machine analysis to explore the ability of graph-theoretical metrics to discriminate SAD patients from HC. Globally, SAD patients showed higher global efficiency, shorter characteristic path length, and stronger small-worldness. Locally, SAD patients showed abnormal nodal centrality mainly involving left superior frontal gyrus, right superior parietal lobe, left amygdala, right paracentral gyrus, right lingual, and right pericalcarine cortex. Altered topological metrics were associated with the symptom severity and duration. Graph-based metrics allowed single-subject classification of SAD versus HC with total accuracy of 78.7%. This finding, that the topological organization of SCNs in SAD patients is altered toward more randomized configurations, adds to our understanding of network-level neuropathology in SAD.
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Affiliation(s)
- Xun Zhang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Han Lai
- Department of Medical Psychology, Army Medical University, Chongqing 400038, China
| | - Qingyuan Li
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Xun Yang
- School of Public Affairs, Chongqing University, Chongqing 400044, China
| | - Nanfang Pan
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Min He
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Graham J Kemp
- Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L69 3BX, United Kingdom
| | - Song Wang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, China
| | - Qiyong Gong
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu 610041, China
- Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen 361000, China
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97
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Jadidi AF, Jensen W, Zarei AA, Lontis ER, Atashzar SF. From pulse width modulated TENS to cortical modulation: based on EEG functional connectivity analysis. Front Neurosci 2023; 17:1239068. [PMID: 37600002 PMCID: PMC10433172 DOI: 10.3389/fnins.2023.1239068] [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: 06/12/2023] [Accepted: 07/18/2023] [Indexed: 08/22/2023] Open
Abstract
Modulation in the temporal pattern of transcutaneous electrical nerve stimulation (TENS), such as Pulse width modulated (PWM), has been considered a new dimension in pain and neurorehabilitation therapy. Recently, the potentials of PWM TENS have been studied on sensory profiles and corticospinal activity. However, the underlying mechanism of PWM TENS on cortical network which might lead to pain alleviation is not yet investigated. Therefore, we recorded cortical activity using electroencephalography (EEG) from 12 healthy subjects and assessed the alternation of the functional connectivity at the cortex level up to an hour following the PWM TENS and compared that with the effect of conventional TENS. The connectivity between eight brain regions involved in sensory and pain processing was calculated based on phase lag index and spearman correlation. The alteration in segregation and integration of information in the network were investigated using graph theory. The proposed analysis discovered several statistically significant network changes between PWM TENS and conventional TENS, such as increased local strength and efficiency of the network in high gamma-band in primary and secondary somatosensory sources one hour following stimulation. Our findings regarding the long-lasting desired effects of PWM TENS support its potential as a therapeutic intervention in clinical research.
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Affiliation(s)
- Armita Faghani Jadidi
- Center for Neuroplasticity and Pain (CNAP), Department of Health Science and Technology, Aalborg University, Aalborg East, Denmark
| | - Winnie Jensen
- Center for Neuroplasticity and Pain (CNAP), Department of Health Science and Technology, Aalborg University, Aalborg East, Denmark
| | - Ali Asghar Zarei
- Center for Neuroplasticity and Pain (CNAP), Department of Health Science and Technology, Aalborg University, Aalborg East, Denmark
| | - Eugen Romulus Lontis
- Center for Neuroplasticity and Pain (CNAP), Department of Health Science and Technology, Aalborg University, Aalborg East, Denmark
| | - S. Farokh Atashzar
- Department of Electrical and Computer Engineering, New York University, New York, NY, United States
- Department of Mechanical and Aerospace Engineering, New York University, New York, NY, United States
- Department of Biomedical Engineering, New York University, New York, NY, United States
- NYU WIRELESS, New York University (NYU), New York, NY, United States
- NYU Center for Urban Science and Progress (CUSP), New York University (NYU), New York, NY, United States
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Abstract
Introduction: Regional hypermetabolism in Alzheimer's disease (AD), especially in the cerebellum, has been consistently observed but often neglected as an artefact produced by the commonly used proportional scaling procedure in the statistical parametric mapping. We hypothesize that the hypermetabolic regions are also important in disease pathology in AD. Methods: Using fluorodeoxyglucose (FDG)-positron emission tomography (PET) images from 88 AD subjects and 88 age-sex matched normal controls (NL) from the publicly available Alzheimer's Disease Neuroimaging Initiative database, we developed a general linear model-based classifier that differentiated AD patients from normal individuals (sensitivity = 87.50%, specificity = 82.95%). We constructed region-region group-wise correlation matrices and evaluated differences in network organization by using the graph theory analysis between AD and control subjects. Results: We confirmed that hypermetabolism found in AD is not an artefact by replicating it using white matter as the reference region. The role of the hypermetabolic regions has been further investigated by using the graph theory. The differences in betweenness centrality (BC) between AD and NL network were correlated with region weights of FDG PET-based AD classifier. In particular, the hypermetabolism in cerebellum was accompanied with higher BC. The brain regions with higher BC in AD network showed a progressive increase in FDG uptake over 2 years in prodromal AD patients (n = 39). Discussion: This study suggests that hypermetabolism found in AD may play an important role in forming the AD-related metabolic network. In particular, hypermetabolic cerebellar regions represent a good candidate for further investigation in altered network organization in AD.
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Affiliation(s)
- Vinay Gupta
- Graduate Program in Biomedical Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre, Winnipeg, Canada
| | - Samuel Booth
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre, Winnipeg, Canada
- Department of Human Anatomy and Cell Science, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada
| | - Ji Hyun Ko
- Graduate Program in Biomedical Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre, Winnipeg, Canada
- Department of Human Anatomy and Cell Science, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada
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Cai J, Xu M, Cai H, Jiang Y, Zheng X, Sun H, Sun Y, Sun Y. Task Cortical Connectivity Reveals Different Network Reorganizations between Mild Stroke Patients with Cortical and Subcortical Lesions. Brain Sci 2023; 13:1143. [PMID: 37626499 PMCID: PMC10452233 DOI: 10.3390/brainsci13081143] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 07/24/2023] [Accepted: 07/27/2023] [Indexed: 08/27/2023] Open
Abstract
Accumulating efforts have been made to investigate cognitive impairment in stroke patients, but little has been focused on mild stroke. Research on the impact of mild stroke and different lesion locations on cognitive impairment is still limited. To investigate the underlying mechanisms of cognitive dysfunction in mild stroke at different lesion locations, electroencephalograms (EEGs) were recorded in three groups (40 patients with cortical stroke (CS), 40 patients with subcortical stroke (SS), and 40 healthy controls (HC)) during a visual oddball task. Power envelope connectivity (PEC) was constructed based on EEG source signals, followed by graph theory analysis to quantitatively assess functional brain network properties. A classification framework was further applied to explore the feasibility of PEC in the identification of mild stroke. The results showed worse behavioral performance in the patient groups, and PECs with significant differences among three groups showed complex distribution patterns in frequency bands and the cortex. In the delta band, the global efficiency was significantly higher in HC than in CS (p = 0.011), while local efficiency was significantly increased in SS than in CS (p = 0.038). In the beta band, the small-worldness was significantly increased in HC compared to CS (p = 0.004). Moreover, the satisfactory classification results (76.25% in HC vs. CS, and 80.00% in HC vs. SS) validate the potential of PECs as a biomarker in the detection of mild stroke. Our findings offer some new quantitative insights into the complex mechanisms of cognitive impairment in mild stroke at different lesion locations, which may facilitate post-stroke cognitive rehabilitation.
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Affiliation(s)
- Jiaye Cai
- Department of Neurology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310020, China; (J.C.); (H.C.); (Y.J.); (X.Z.); (Y.S.)
| | - Mengru Xu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China
| | - Huaying Cai
- Department of Neurology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310020, China; (J.C.); (H.C.); (Y.J.); (X.Z.); (Y.S.)
| | - Yun Jiang
- Department of Neurology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310020, China; (J.C.); (H.C.); (Y.J.); (X.Z.); (Y.S.)
| | - Xu Zheng
- Department of Neurology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310020, China; (J.C.); (H.C.); (Y.J.); (X.Z.); (Y.S.)
| | - Hongru Sun
- Department of Electrocardiogram, Dongyang Traditional Chinese Medicine Hospital, Dongyang 322100, China;
| | - Yu Sun
- Department of Neurology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310020, China; (J.C.); (H.C.); (Y.J.); (X.Z.); (Y.S.)
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China
- MOE Frontiers Science Center for Brain Science and Brain-Machine Integration, Zhejiang University, Hangzhou 310058, China
- State Key Laboratory for Brain-Computer Intelligence, Zhejiang University, Hangzhou 310016, China
| | - Yi Sun
- Department of Neurology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310020, China; (J.C.); (H.C.); (Y.J.); (X.Z.); (Y.S.)
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Lu D, Wang X, Wei Y, Cui Y, Wang Y. Neural pathways of attitudes toward foreign languages predict academic performance. Front Psychol 2023; 14:1181989. [PMID: 37564316 PMCID: PMC10410274 DOI: 10.3389/fpsyg.2023.1181989] [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: 03/08/2023] [Accepted: 07/10/2023] [Indexed: 08/12/2023] Open
Abstract
Learning attitude is thought to impact students' academic achievement and success, but the underlying neurocognitive mechanisms of learning attitudes remain unclear. The purpose of the present study was to investigate the neural markers linked to attitudes toward foreign languages and how they contribute to foreign-language performance. Forty-one Chinese speakers who hold differentiated foreign language (English) attitudes were asked to complete an English semantic judgment task during a functional magnetic resonance imaging (fMRI) experiment. Multimethod brain imaging analyses showed that, compared with the positive attitude group (PAG), the negative attitude group (NAG) showed increased brain activation in the left STG and functional connectivity between the left STG and the right precentral gyrus (PCG), as well as changed functional segregation and integration of brain networks under the English reading task, after controlling for English reading scores. Mediation analysis further revealed that left STG activity and STG-PCG connectivity mediated the relationships between English attitudes and English reading performance. Taken together, these findings suggest that objective neural markers related to subjective foreign language attitudes (FLAs) exist and that attitude-related neural pathways play important roles in determining students' academic performance. Our findings provide new insights into the neurobiological mechanisms by which attitudes regulate academic performance.
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Affiliation(s)
- Di Lu
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China
| | - Xin Wang
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yaozhen Wei
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yue Cui
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yapeng Wang
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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