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Canal-Garcia A, Veréb D, Mijalkov M, Westman E, Volpe G, Pereira JB. Dynamic multilayer functional connectivity detects preclinical and clinical Alzheimer's disease. Cereb Cortex 2024; 34:bhad542. [PMID: 38212285 PMCID: PMC10839846 DOI: 10.1093/cercor/bhad542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 12/21/2023] [Accepted: 12/22/2023] [Indexed: 01/13/2024] Open
Abstract
Increasing evidence suggests that patients with Alzheimer's disease present alterations in functional connectivity but previous results have not always been consistent. One of the reasons that may account for this inconsistency is the lack of consideration of temporal dynamics. To address this limitation, here we studied the dynamic modular organization on resting-state functional magnetic resonance imaging across different stages of Alzheimer's disease using a novel multilayer brain network approach. Participants from preclinical and clinical Alzheimer's disease stages were included. Temporal multilayer networks were used to assess time-varying modular organization. Logistic regression models were employed for disease stage discrimination, and partial least squares analyses examined associations between dynamic measures with cognition and pathology. Temporal multilayer functional measures distinguished all groups, particularly preclinical stages, overcoming the discriminatory power of risk factors such as age, sex, and APOE ϵ4 carriership. Dynamic multilayer functional measures exhibited strong associations with cognition as well as amyloid and tau pathology. Dynamic multilayer functional connectivity shows promise as a functional imaging biomarker for both early- and late-stage Alzheimer's disease diagnosis.
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Affiliation(s)
- Anna Canal-Garcia
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm 17165, Sweden
| | - Dániel Veréb
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm 17165, Sweden
| | - Mite Mijalkov
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm 17165, Sweden
| | - Eric Westman
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm 17165, Sweden
| | - Giovanni Volpe
- Department of Physics, University of Gothenburg, Gothenburg 40530, Sweden
| | - Joana B Pereira
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm 17165, Sweden
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Li YL, Wu JJ, Li WK, Gao X, Wei D, Xue X, Hua XY, Zheng MX, Xu JG. Effects of individual metabolic brain network changes co-affected by T2DM and aging on the probabilities of T2DM: protective and risk factors. Cereb Cortex 2024; 34:bhad439. [PMID: 37991271 DOI: 10.1093/cercor/bhad439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 10/23/2023] [Accepted: 10/24/2023] [Indexed: 11/23/2023] Open
Abstract
Neuroimaging markers for risk and protective factors related to type 2 diabetes mellitus are critical for clinical prevention and intervention. In this work, the individual metabolic brain networks were constructed with Jensen-Shannon divergence for 4 groups (elderly type 2 diabetes mellitus and healthy controls, and middle-aged type 2 diabetes mellitus and healthy controls). Regional network properties were used to identify hub regions. Rich-club, feeder, and local connections were subsequently obtained, intergroup differences in connections and correlations between them and age (or fasting plasma glucose) were analyzed. Multinomial logistic regression was performed to explore effects of network changes on the probability of type 2 diabetes mellitus. The elderly had increased rich-club and feeder connections, and decreased local connection than the middle-aged among type 2 diabetes mellitus; type 2 diabetes mellitus had decreased rich-club and feeder connections than healthy controls. Protective factors including glucose metabolism in triangle part of inferior frontal gyrus, metabolic connectivity between triangle of the inferior frontal gyrus and anterior cingulate cortex, degree centrality of putamen, and risk factors including metabolic connectivities between triangle of the inferior frontal gyrus and Heschl's gyri were identified for the probability of type 2 diabetes mellitus. Metabolic interactions among critical brain regions increased in type 2 diabetes mellitus with aging. Individual metabolic network changes co-affected by type 2 diabetes mellitus and aging were identified as protective and risk factors for the likelihood of type 2 diabetes mellitus, providing guiding evidence for clinical interventions.
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Affiliation(s)
- Yu-Lin Li
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
| | - Jia-Jia Wu
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - Wei-Kai Li
- School of Mathematics and Statistics, Chongqing Jiaotong University, Chongqing 400074, China
| | - Xin Gao
- Shanghai Universal Medical Imaging Diagnostic Center, Shanghai 200233, China
| | - Dong Wei
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
| | - Xin Xue
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
| | - Xu-Yun Hua
- Department of Traumatology and Orthopedics, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - Mou-Xiong Zheng
- Department of Traumatology and Orthopedics, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
| | - Jian-Guang Xu
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
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Chen H, Wang H, Yu M, Duan B. Structure-decoupled functional connectome-based brain age prediction provides higher association to cognition. Neuroreport 2024; 35:42-48. [PMID: 37994631 PMCID: PMC10756698 DOI: 10.1097/wnr.0000000000001976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 11/02/2023] [Indexed: 11/24/2023]
Abstract
Brain age prediction as well as the prediction difference has been well examined to be a potential biomarker for brain disease or abnormal aging process. However, less knowledge was reported for the cognitive association within normal population. In this study, we proposed a novel approach to brain age prediction by structure-decoupled functional connectome. The original functional connectome was decomposed and decoupled into a structure-decoupled functional connectome using structural connectome harmonics. Our method was applied to a large dataset of normal aging individuals and achieved a high correlation between predicted and chronological age (r = 0.77). Both the original FC and structure-decoupled FC could be well-trained in a brain age prediction model. Significant remarkable relationships between the brain age prediction difference (predicted age minus chronological age) and cognitive scores were discovered. However, the brain age-predicted difference driven by structure-decoupled FC showed a stronger correction to the two cognitive scores (MMSE: r = -0.27, P -value = 0.002; MoCA: r = -0.32, P -value = 0.0003). Our findings suggest that our structure-decoupled functional connectivity approach could provide a more individual-specific functional network, leading to improved brain age prediction performance and a better understanding of cognitive decline in aging.
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Affiliation(s)
- Huan Chen
- Department of Internal Medicine, Huiqiao Medical Center, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Haiyan Wang
- Department of Internal Medicine, Huiqiao Medical Center, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Mingxia Yu
- Department of Internal Medicine, Huiqiao Medical Center, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Bin Duan
- Department of Internal Medicine, Huiqiao Medical Center, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
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Hotz I, Deschwanden PF, Mérillat S, Jäncke L. Associations between white matter hyperintensities, lacunes, entorhinal cortex thickness, declarative memory and leisure activity in cognitively healthy older adults: A 7-year study. Neuroimage 2023; 284:120461. [PMID: 37981203 DOI: 10.1016/j.neuroimage.2023.120461] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 11/02/2023] [Accepted: 11/16/2023] [Indexed: 11/21/2023] Open
Abstract
INTRODUCTION Cerebral small vessel disease (cSVD) is a growing epidemic that affects brain health and cognition. Therefore, a more profound understanding of the interplay between cSVD, brain atrophy, and cognition in healthy aging is of great importance. In this study, we examined the association between white matter hyperintensities (WMH) volume, number of lacunes, entorhinal cortex (EC) thickness, and declarative memory in cognitively healthy older adults over a seven-year period, controlling for possible confounding factors. Because there is no cure for cSVD to date, the neuroprotective potential of an active lifestyle has been suggested. Supporting evidence, however, is scarce. Therefore, a second objective of this study is to examine the relationship between leisure activities, cSVD, EC thickness, and declarative memory. METHODS We used a longitudinal dataset, which consisted of five measurement time points of structural MRI and psychometric cognitive ability and survey data, collected from a sample of healthy older adults (baseline N = 231, age range: 64-87 years, age M = 70.8 years), to investigate associations between cSVD MRI markers, EC thickness and verbal and figural memory performance. Further, we computed physical, social, and cognitive leisure activity scores from survey-based assessments and examined their associations with brain structure and declarative memory. To provide more accurate estimates of the trajectories and cross-domain correlations, we applied latent growth curve models controlling for potential confounders. RESULTS Less age-related thinning of the right (β = 0.92, p<.05) and left EC (β = 0.82, p<.05) was related to less declarative memory decline; and a thicker EC at baseline predicted less declarative memory loss (β = 0.54, p<.05). Higher baseline levels of physical (β = 0.24, p<.05), and social leisure activity (β = 0.27, p<.01) predicted less thinning of right EC. No relation was found between WMH or lacunes and declarative memory or between leisure activity and declarative memory. Higher education was initially related to more physical activity (β = 0.16, p<.05) and better declarative memory (β = 0.23, p<.001), which, however, declined steeper in participants with higher education (β = -.35, p<.05). Obese participants were less physically (β = -.18, p<.01) and socially active (β = -.13, p<.05) and had thinner left EC (β = -.14, p<.05) at baseline. Antihypertensive medication use (β = -.26, p<.05), and light-to-moderate alcohol consumption (β = -.40, p<.001) were associated with a smaller increase in the number of lacunes whereas a larger increase in the number of lacunes was observed in current smokers (β = 0.30, p<.05). CONCLUSIONS Our results suggest complex relationships between cSVD MRI markers (total WMH, number of lacunes, right and left EC thickness), declarative memory, and confounding factors such as antihypertensive medication, obesity, and leisure activitiy. Thus, leisure activities and having good cognitive reserve counteracting this neurodegeneration. Several confounding factors seem to contribute to the extent or progression/decline of cSVD, which needs further investigation in the future. Since there is still no cure for cSVD, modifiable confounding factors should be studied more intensively in the future to maintain or promote brain health and thus cognitive abilities in older adults.
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Affiliation(s)
- Isabel Hotz
- Dynamics of Healthy Aging, University Research Priority Program (URPP), University of Zurich, Stampfenbachstrasse 73, Zurich CH-8006, Switzerland.
| | - Pascal Frédéric Deschwanden
- Dynamics of Healthy Aging, University Research Priority Program (URPP), University of Zurich, Stampfenbachstrasse 73, Zurich CH-8006, Switzerland
| | - Susan Mérillat
- Dynamics of Healthy Aging, University Research Priority Program (URPP), University of Zurich, Stampfenbachstrasse 73, Zurich CH-8006, Switzerland
| | - Lutz Jäncke
- Dynamics of Healthy Aging, University Research Priority Program (URPP), University of Zurich, Stampfenbachstrasse 73, Zurich CH-8006, Switzerland
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Dong Q, Li J, Ju Y, Xiao C, Li K, Shi B, Zheng W, Zhang Y. Altered Relationship between Functional Connectivity and Fiber-Bundle Structure in High-Functioning Male Adults with Autism Spectrum Disorder. Brain Sci 2023; 13:1098. [PMID: 37509029 PMCID: PMC10377258 DOI: 10.3390/brainsci13071098] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 07/04/2023] [Accepted: 07/18/2023] [Indexed: 07/30/2023] Open
Abstract
Autism spectrum disorder (ASD) is a pervasive neurodevelopmental disorder characterized by abnormalities in structure and function of the brain. However, how ASD affects the relationship between fiber-bundle microstructures and functional connectivity (FC) remains unclear. Here, we analyzed structural and functional images of 26 high-functioning adult males with ASD, alongside 26 age-, gender-, and full-scale IQ-matched typically developing controls (TDCs) from the BNI dataset in the ABIDE database. We utilized fixel-based analysis to extract microstructural information from fiber tracts, which was then used to predict FC using a multilinear model. Our results revealed that the structure-function relationships in both ASD and TDC cohorts were strongly aligned in the primary cortex but decoupled in the high-order cortex, and the ASD patients exhibited reduced structure-function relationships throughout the cortex compared to the TDCs. Furthermore, we observed that the disrupted relationships in ASD were primarily driven by alterations in FC rather than fiber-bundle microstructures. The structure-function relationships in the left superior parietal cortex, right precentral and inferior temporal cortices, and bilateral insula could predict individual differences in clinical symptoms of ASD patients. These findings underscore the significance of altered relationships between fiber-bundle microstructures and FC in the etiology of ASD.
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Affiliation(s)
- Qiangli Dong
- Department of Psychiatry, Lanzhou University Second Hospital, Lanzhou 730000, China
| | - Jialong Li
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
| | - Yumeng Ju
- Department of Psychiatry & National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Chuman Xiao
- Department of Psychiatry & National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Kangning Li
- Department of Psychiatry & National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China
| | - Bin Shi
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
| | - Weihao Zheng
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
| | - Yan Zhang
- Department of Psychiatry & National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha 410011, China
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Kizilirmak JM, Soch J, Schütze H, Düzel E, Feldhoff H, Fischer L, Knopf L, Maass A, Raschick M, Schult A, Yakupov R, Richter A, Schott BH. The relationship between resting-state amplitude fluctuations and memory-related deactivations of the default mode network in young and older adults. Hum Brain Mapp 2023; 44:3586-3609. [PMID: 37051727 DOI: 10.1002/hbm.26299] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 03/09/2023] [Accepted: 03/20/2023] [Indexed: 04/14/2023] Open
Abstract
The default mode network (DMN) typically exhibits deactivations during demanding tasks compared to periods of relative rest. In functional magnetic resonance imaging (fMRI) studies of episodic memory encoding, increased activity in DMN regions even predicts later forgetting in young healthy adults. This association is attenuated in older adults and, in some instances, increased DMN activity even predicts remembering rather than forgetting. It is yet unclear whether this phenomenon is due to a compensatory mechanism, such as self-referential or schema-dependent encoding, or whether it reflects overall reduced DMN activity modulation in older age. We approached this question by systematically comparing DMN activity during successful encoding and tonic, task-independent, DMN activity at rest in a sample of 106 young (18-35 years) and 111 older (60-80 years) healthy participants. Using voxel-wise multimodal analyses, we assessed the age-dependent relationship between DMN resting-state amplitude (mean percent amplitude of fluctuation, mPerAF) and DMN fMRI signals related to successful memory encoding, as well as their modulation by age-related hippocampal volume loss, while controlling for regional grey matter volume. Older adults showed lower resting-state DMN amplitudes and lower task-related deactivations. However, a negative relationship between resting-state mPerAF and subsequent memory effect within the precuneus was observed only in young, but not older adults. Hippocampal volumes showed no relationship with the DMN subsequent memory effect or mPerAF. Lastly, older adults with higher mPerAF in the DMN at rest tend to show higher memory performance, pointing towards the importance of a maintained ability to modulate DMN activity in old age.
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Affiliation(s)
- Jasmin M Kizilirmak
- Cognitive Geriatric Psychiatry, German Center for Neurodegenerative Diseases, Göttingen, Germany
- Neurodidactics and NeuroLab, Institute for Psychology, University of Hildesheim, Hildesheim, Germany
- German Centre for Higher Education Research and Science Studies, Hannover, Germany
| | - Joram Soch
- Cognitive Geriatric Psychiatry, German Center for Neurodegenerative Diseases, Göttingen, Germany
- Bernstein Center for Computational Neuroscience, Berlin, Germany
| | - Hartmut Schütze
- Medical Faculty, Institute for Cognitive Neurology and Dementia Research, Otto-von-Guericke-University, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Emrah Düzel
- Medical Faculty, Institute for Cognitive Neurology and Dementia Research, Otto-von-Guericke-University, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
- German Center for Neurodegenerative Diseases, Magdeburg, Germany
| | | | | | - Lea Knopf
- Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Anne Maass
- German Center for Neurodegenerative Diseases, Magdeburg, Germany
| | | | - Annika Schult
- Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Renat Yakupov
- German Center for Neurodegenerative Diseases, Magdeburg, Germany
| | - Anni Richter
- Leibniz Institute for Neurobiology, Magdeburg, Germany
- Center for Intervention and Research on Adaptive and Maladaptive Brain Circuits Underlying Mental Health (C-I-R-C), Jena-Magdeburg-Halle, Germany
| | - Björn H Schott
- Cognitive Geriatric Psychiatry, German Center for Neurodegenerative Diseases, Göttingen, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
- Leibniz Institute for Neurobiology, Magdeburg, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
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Brain Macro-Structural Alterations in Aging Rats: A Longitudinal Lifetime Approach. Cells 2023; 12:cells12030432. [PMID: 36766774 PMCID: PMC9914014 DOI: 10.3390/cells12030432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 01/25/2023] [Accepted: 01/26/2023] [Indexed: 02/03/2023] Open
Abstract
Aging is accompanied by macro-structural alterations in the brain that may relate to age-associated cognitive decline. Animal studies could allow us to study this relationship, but so far it remains unclear whether their structural aging patterns correspond to those in humans. Therefore, by applying magnetic resonance imaging (MRI) and deformation-based morphometry (DBM), we longitudinally screened the brains of male RccHan:WIST rats for structural changes across their average lifespan. By combining dedicated region of interest (ROI) and voxel-wise approaches, we observed an increase in their global brain volume that was superimposed by divergent local morphologic alterations, with the largest aging effects in early and middle life. We detected a modality-dependent vulnerability to shrinkage across the visual, auditory, and somato-sensory cortical areas, whereas the piriform cortex showed partial resistance. Furthermore, shrinkage emerged in the amygdala, subiculum, and flocculus as well as in frontal, parietal, and motor cortical areas. Strikingly, we noticed the preservation of ectorhinal, entorhinal, retrosplenial, and cingulate cortical regions, which all represent higher-order brain areas and extraordinarily grew with increasing age. We think that the findings of this study will further advance aging research and may contribute to the establishment of interventional approaches to preserve cognitive health in advanced age.
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Li H, Zhang X, Sun X, Dong L, Lu H, Yue S, Zhang H. Functional networks in prolonged disorders of consciousness. Front Neurosci 2023; 17:1113695. [PMID: 36875660 PMCID: PMC9981972 DOI: 10.3389/fnins.2023.1113695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 01/25/2023] [Indexed: 02/19/2023] Open
Abstract
Prolonged disorders of consciousness (DoC) are characterized by extended disruptions of brain activities that sustain wakefulness and awareness and are caused by various etiologies. During the past decades, neuroimaging has been a practical method of investigation in basic and clinical research to identify how brain properties interact in different levels of consciousness. Resting-state functional connectivity within and between canonical cortical networks correlates with consciousness by a calculation of the associated temporal blood oxygen level-dependent (BOLD) signal process during functional MRI (fMRI) and reveals the brain function of patients with prolonged DoC. There are certain brain networks including the default mode, dorsal attention, executive control, salience, auditory, visual, and sensorimotor networks that have been reported to be altered in low-level states of consciousness under either pathological or physiological states. Analysis of brain network connections based on functional imaging contributes to more accurate judgments of consciousness level and prognosis at the brain level. In this review, neurobehavioral evaluation of prolonged DoC and the functional connectivity within brain networks based on resting-state fMRI were reviewed to provide reference values for clinical diagnosis and prognostic evaluation.
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Affiliation(s)
- Hui Li
- Rehabilitation Center, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.,Department of Neurorehabilitation, China Rehabilitation Research Center, Beijing, China.,University of Health and Rehabilitation Sciences, Qingdao, Shandong, China
| | - Xiaonian Zhang
- Department of Neurorehabilitation, China Rehabilitation Research Center, Beijing, China
| | - Xinting Sun
- Department of Neurorehabilitation, China Rehabilitation Research Center, Beijing, China
| | - Linghui Dong
- Rehabilitation Center, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.,Department of Neurorehabilitation, China Rehabilitation Research Center, Beijing, China.,University of Health and Rehabilitation Sciences, Qingdao, Shandong, China
| | - Haitao Lu
- Department of Neurorehabilitation, China Rehabilitation Research Center, Beijing, China
| | - Shouwei Yue
- Rehabilitation Center, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.,University of Health and Rehabilitation Sciences, Qingdao, Shandong, China
| | - Hao Zhang
- Rehabilitation Center, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.,Department of Neurorehabilitation, China Rehabilitation Research Center, Beijing, China.,University of Health and Rehabilitation Sciences, Qingdao, Shandong, China
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Yan Y, Fan G, Liao X, Zhao X. Research trends and hotspots on connectomes from 2005 to 2021: A bibliometric and latent Dirichlet allocation application study. Front Neurosci 2022; 16:1046562. [PMID: 36620450 PMCID: PMC9814013 DOI: 10.3389/fnins.2022.1046562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 12/06/2022] [Indexed: 12/24/2022] Open
Abstract
Background This study aimed to conduct a bibliometric analysis of publications on connectomes and illustrate its trends and hotspots using a machine-learning-based text mining algorithm. Methods Documents were retrieved from the Web of Science Core Collection (WoSCC) and Scopus databases and analyzed in Rstudio 1.3.1. Through quantitative and qualitative methods, the most productive and impactful academic journals in the field of connectomes were compared in terms of the total number of publications and h-index over time. Meanwhile, the countries/regions and institutions involved in connectome research were compared, as well as their scientific collaboration. The study analyzed topics and research trends by R package "bibliometrix." The major topics of connectomes were classified by Latent Dirichlet allocation (LDA). Results A total of 14,140 publications were included in the study. NEUROIMAGE ranked first in terms of publication volume (1,427 articles) and impact factor (h-index:122) among all the relevant journals. The majority of articles were published by developed countries, with the United States having the most. Harvard Medical School and the University of Pennsylvania were the two most productive institutions. Neuroimaging analysis technology and brain functions and diseases were the two major topics of connectome research. The application of machine learning, deep learning, and graph theory analysis in connectome research has become the current trend, while an increasing number of studies were concentrating on dynamic functional connectivity. Meanwhile, researchers have begun investigating alcohol use disorders and migraine in terms of brain connectivity in the past 2 years. Conclusion This study illustrates a comprehensive overview of connectome research and provides researchers with critical information for understanding the recent trends and hotspots of connectomes.
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Affiliation(s)
- Yangye Yan
- Tongji University School of Medicine, Shanghai Eastern Hospital Affiliated to Tongji University, Shanghai, China
| | - Guoxin Fan
- Department of Pain Medicine, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China,School of Biomedical Engineering, School of Medicine, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Shenzhen University, Shenzhen, China,Department of Spine Surgery, Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xiang Liao
- Department of Pain Medicine, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China,School of Biomedical Engineering, School of Medicine, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Shenzhen University, Shenzhen, China,*Correspondence: Xiang Liao,
| | - Xudong Zhao
- Clinical Research Center for Mental Disorders, Chinese-German Institute of Mental Health, Shanghai Pudong New Area Mental Health Center, School of Medicine, Tongji University, Shanghai, China,Xudong Zhao,
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10
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Lee WJ, Cho H, Baek MS, Kim HK, Lee JH, Ryu YH, Lyoo CH, Seong JK. Dynamic network model reveals distinct tau spreading patterns in early- and late-onset Alzheimer disease. Alzheimers Res Ther 2022; 14:121. [PMID: 36056405 PMCID: PMC9438183 DOI: 10.1186/s13195-022-01061-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 08/09/2022] [Indexed: 11/13/2022]
Abstract
BACKGROUND The clinical features of Alzheimer's disease (AD) vary substantially depending on whether the onset of cognitive deficits is early or late. The amount and distribution patterns of tau pathology are thought to play a key role in the clinical characteristics of AD, which spreads throughout the large-scale brain network. Here, we describe the differences between tau-spreading processes in early- and late-onset symptomatic individuals on the AD spectrum. METHODS We divided 74 cognitively unimpaired (CU) and 68 cognitively impaired (CI) patients receiving 18F-flortaucipir positron emission tomography scans into two groups by age and age at onset. Members of each group were arranged in a pseudo-longitudinal order based on baseline tau pathology severity, and potential interregional tau-spreading pathways were defined following the order using longitudinal tau uptake. We detected a multilayer community structure through consecutive tau-spreading networks to identify spatio-temporal changes in the propagation hubs. RESULTS In each group, ordered tau-spreading networks revealed the stage-dependent dynamics of tau propagation, supporting distinct tau accumulation patterns. In the young CU/early-onset CI group, tau appears to spread through a combination of three independent communities with partially overlapped territories, whose specific driving regions were the basal temporal regions, left medial and lateral temporal regions, and left parietal regions. For the old CU/late-onset CI group, however, continuation of major communities occurs in line with the appearance of hub regions in the order of bilateral entorhinal cortices, parahippocampal and fusiform gyri, and lateral temporal regions. CONCLUSION Longitudinal tau propagation depicts distinct spreading pathways of the early- and late-onset AD spectrum characterized by the specific location and appearance period of several hub regions that dominantly provide tau.
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Affiliation(s)
- Wha Jin Lee
- School of Biomedical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, South Korea
| | - Hanna Cho
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, 20 Eonjuro 63-gil, Gangnam-gu, Seoul, South Korea
| | - Min Seok Baek
- Department of Neurology, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju, Gangwon-do, South Korea
| | - Han-Kyeol Kim
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, 20 Eonjuro 63-gil, Gangnam-gu, Seoul, South Korea
| | - Jae Hoon Lee
- Department of Nuclear Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Young Hoon Ryu
- Department of Nuclear Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Chul Hyoung Lyoo
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, 20 Eonjuro 63-gil, Gangnam-gu, Seoul, South Korea.
| | - Joon-Kyung Seong
- School of Biomedical Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, South Korea.
- Department of Artificial Intelligence, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul, South Korea.
- Interdisciplinary Program in Precision Public Health, Korea University, Seoul, South Korea.
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11
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Oishi K, Soldan A, Pettigrew C, Hsu J, Mori S, Albert M, Oishi K. Changes in pairwise functional connectivity associated with changes in cognitive performance in cognitively normal older individuals: A two-year observational study. Neurosci Lett 2022; 781:136618. [PMID: 35398188 PMCID: PMC9990522 DOI: 10.1016/j.neulet.2022.136618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 03/15/2022] [Accepted: 04/03/2022] [Indexed: 10/18/2022]
Abstract
Neurobiological substrates of cognitive decline in cognitively normal older individuals have been investigated by resting-state functional magnetic resonance imaging, but little is known about the relationship between longitudinal changes in the whole brain. In this study, we examined two-year changes in functional connectivity among 80 gray matter areas and investigated the relationship to two-year changes in cognitive performance. A cross-validated permutation variable importance measure was applied to select features related to a change in cognitive performance. Age-corrected changes in eleven pairs of functional connections were selected as important features, all related to brain areas that belong to the default mode network. A linear regression model with cross-validation demonstrated a mean correlation coefficient of 0.55 between measured and predicted changes in the cognitive composite score. These results suggest that intra- and inter-network connections in the default mode network are associated with cognitive changes over two years among cognitively normal individuals.
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Affiliation(s)
- Kumiko Oishi
- Center for Imaging Science, The Johns Hopkins University, Whiting School of Engineering, The Johns Hopkins University, Baltimore, MD, USA
| | - Anja Soldan
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Corinne Pettigrew
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Johnny Hsu
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Susumu Mori
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Marilyn Albert
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kenichi Oishi
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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12
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Di Plinio S, Ebisch SJH. Probabilistically Weighted Multilayer Networks disclose the link between default mode network instability and psychosis-like experiences in healthy adults. Neuroimage 2022; 257:119291. [PMID: 35577023 DOI: 10.1016/j.neuroimage.2022.119291] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 05/01/2022] [Accepted: 05/04/2022] [Indexed: 11/30/2022] Open
Abstract
The brain is a complex system in which the functional interactions among its subunits vary over time. The trajectories of this dynamic variation contribute to inter-individual behavioral differences and psychopathologic phenotypes. Despite many methodological advancements, the study of dynamic brain networks still relies on biased assumptions in the temporal domain. The current paper has two goals. First, we present a novel method to study multilayer networks: by modelling intra-nodal connections in a probabilistic, biologically driven way, we introduce a temporal resolution of the multilayer network based on signal similarity across time series. This new method is tested on synthetic networks by varying the number of modules and the sources of noise in the simulation. Secondly, we implement these probabilistically weighted (PW) multilayer networks to study the association between network dynamics and subclinical, psychosis-relevant personality traits in healthy adults. We show that the PW method for multilayer networks outperforms the standard procedure in modular detection and is less affected by increasing noise levels. Additionally, the PW method highlighted associations between the temporal instability of default mode network connections and psychosis-like experiences in healthy adults. PW multilayer networks allow an unbiased study of dynamic brain functioning and its behavioral correlates.
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Affiliation(s)
- Simone Di Plinio
- Department of Neuroscience, Imaging, and Clinical Sciences, G D'Annunzio University of Chieti-Pescara, Chieti, Italy.
| | - Sjoerd J H Ebisch
- Department of Neuroscience, Imaging, and Clinical Sciences, G D'Annunzio University of Chieti-Pescara, Chieti, Italy; Institute for Advanced Biomedical Technologies (ITAB), G D'Annunzio University of Chieti-Pescara, Chieti, Italy
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13
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Li YL, Wu JJ, Ma J, Li SS, Xue X, Wei D, Shan CL, Hua XY, Zheng MX, Xu JG. Alteration of the Individual Metabolic Network of the Brain Based on Jensen-Shannon Divergence Similarity Estimation in Elderly Patients With Type 2 Diabetes Mellitus. Diabetes 2022; 71:894-905. [PMID: 35133397 DOI: 10.2337/db21-0600] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Accepted: 02/03/2022] [Indexed: 11/13/2022]
Abstract
The aim of this study was to investigate the interactive effect between aging and type 2 diabetes mellitus (T2DM) on brain glucose metabolism, individual metabolic connectivity, and network properties. Using a 2 × 2 factorial design, 83 patients with T2DM (40 elderly and 43 middle-aged) and 69 sex-matched healthy control subjects (HCs) (34 elderly and 35 middle-aged) underwent 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance scanning. Jensen-Shannon divergence was applied to construct individual metabolic connectivity and networks. The topological properties of the networks were quantified using graph theoretical analysis. The general linear model was used to mainly estimate the interaction effect between aging and T2DM on glucose metabolism, metabolic connectivity, and network. There was an interaction effect between aging and T2DM on glucose metabolism, metabolic connectivity, and regional metabolic network properties (all P < 0.05). The post hoc analyses showed that compared with elderly HCs and middle-aged patients with T2DM, elderly patients with T2DM had decreased glucose metabolism, increased metabolic connectivity, and regional metabolic network properties in cognition-related brain regions (all P < 0.05). Age and fasting plasma glucose had negative correlations with glucose metabolism and positive correlations with metabolic connectivity. Elderly patients with T2DM had glucose hypometabolism, strengthened functional integration, and increased efficiency of information communication mainly located in cognition-related brain regions. Metabolic connectivity pattern changes might be compensatory changes for glucose hypometabolism.
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Affiliation(s)
- Yu-Lin Li
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jia-Jia Wu
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jie Ma
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Si-Si Li
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xin Xue
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Dong Wei
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Chun-Lei Shan
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Engineering Research Center of Traditional Chinese Medicine Intelligent Rehabilitation, Ministry of Education, Shanghai, China
| | - Xu-Yun Hua
- Department of Traumatology and Orthopedics, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Mou-Xiong Zheng
- Department of Traumatology and Orthopedics, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Jian-Guang Xu
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
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14
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Rus-Oswald OG, Benner J, Reinhardt J, Bürki C, Christiner M, Hofmann E, Schneider P, Stippich C, Kressig RW, Blatow M. Musicianship-Related Structural and Functional Cortical Features Are Preserved in Elderly Musicians. Front Aging Neurosci 2022; 14:807971. [PMID: 35401149 PMCID: PMC8990841 DOI: 10.3389/fnagi.2022.807971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 01/25/2022] [Indexed: 11/13/2022] Open
Abstract
Background Professional musicians are a model population for exploring basic auditory function, sensorimotor and multisensory integration, and training-induced neuroplasticity. The brain of musicians exhibits distinct structural and functional cortical features; however, little is known about how these features evolve during aging. This multiparametric study aimed to examine the functional and structural neural correlates of lifelong musical practice in elderly professional musicians. Methods Sixteen young musicians, 16 elderly musicians (age >70), and 15 elderly non-musicians participated in the study. We assessed gray matter metrics at the whole-brain and region of interest (ROI) levels using high-resolution magnetic resonance imaging (MRI) with the Freesurfer automatic segmentation and reconstruction pipeline. We used BrainVoyager semiautomated segmentation to explore individual auditory cortex morphotypes. Furthermore, we evaluated functional blood oxygenation level-dependent (BOLD) activations in auditory and non-auditory regions by functional MRI (fMRI) with an attentive tone-listening task. Finally, we performed discriminant function analyses based on structural and functional ROIs. Results A general reduction of gray matter metrics distinguished the elderly from the young subjects at the whole-brain level, corresponding to widespread natural brain atrophy. Age- and musicianship-dependent structural correlations revealed group-specific differences in several clusters including superior, middle, and inferior frontal as well as perirolandic areas. In addition, the elderly musicians exhibited increased gyrification of auditory cortex like the young musicians. During fMRI, the elderly non-musicians activated predominantly auditory regions, whereas the elderly musicians co-activated a much broader network of auditory association areas, primary and secondary motor areas, and prefrontal and parietal regions like, albeit weaker, the young musicians. Also, group-specific age- and musicianship-dependent functional correlations were observed in the frontal and parietal regions. Moreover, discriminant function analysis could separate groups with high accuracy based on a set of specific structural and functional, mainly temporal and occipital, ROIs. Conclusion In conclusion, despite naturally occurring senescence, the elderly musicians maintained musicianship-specific structural and functional cortical features. The identified structural and functional brain regions, discriminating elderly musicians from non-musicians, might be of relevance for the aging musicians’ brain. To what extent lifelong musical activity may have a neuroprotective impact needs to be addressed further in larger longitudinal studies.
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Affiliation(s)
- Oana G. Rus-Oswald
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
- University Department of Geriatric Medicine FELIX PLATTER, Basel, Switzerland
- *Correspondence: Oana G. Rus-Oswald,
| | - Jan Benner
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
- Jan Benner,
| | - Julia Reinhardt
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
- Division of Diagnostic and Interventional Neuroradiology, Department of Radiology, University Hospital Basel, University of Basel, Basel, Switzerland
- Department of Cardiology and Cardiovascular Research Institute Basel, University Hospital Basel, University of Basel, Basel, Switzerland
- Department of Orthopedic Surgery and Traumatology, University Hospital of Basel, University of Basel, Basel, Switzerland
| | - Céline Bürki
- University Department of Geriatric Medicine FELIX PLATTER, Basel, Switzerland
| | - Markus Christiner
- Centre for Systematic Musicology, University of Graz, Graz, Austria
- Vitols Jazeps Latvian Academy of Music, Riga, Latvia
| | - Elke Hofmann
- Academy of Music, University of Applied Sciences and Arts Northwestern Switzerland (FHNW), Basel, Switzerland
| | - Peter Schneider
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
- Centre for Systematic Musicology, University of Graz, Graz, Austria
- Vitols Jazeps Latvian Academy of Music, Riga, Latvia
| | - Christoph Stippich
- Department of Neuroradiology and Radiology, Kliniken Schmieder, Allensbach, Germany
| | - Reto W. Kressig
- University Department of Geriatric Medicine FELIX PLATTER, Basel, Switzerland
| | - Maria Blatow
- Section of Neuroradiology, Department of Radiology and Nuclear Medicine, Neurocenter, Cantonal Hospital Lucerne, University of Lucerne, Lucerne, Switzerland
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15
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Gu S, Fotiadis P, Parkes L, Xia CH, Gur RC, Gur RE, Roalf DR, Satterthwaite TD, Bassett DS. Network controllability mediates the relationship between rigid structure and flexible dynamics. Netw Neurosci 2022; 6:275-297. [PMID: 36605890 PMCID: PMC9810281 DOI: 10.1162/netn_a_00225] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 12/15/2021] [Indexed: 01/07/2023] Open
Abstract
Precisely how the anatomical structure of the brain supports a wide range of complex functions remains a question of marked importance in both basic and clinical neuroscience. Progress has been hampered by the lack of theoretical frameworks explaining how a structural network of relatively rigid interareal connections can produce a diverse repertoire of functional neural dynamics. Here, we address this gap by positing that the brain's structural network architecture determines the set of accessible functional connectivity patterns according to predictions of network control theory. In a large developmental cohort of 823 youths aged 8 to 23 years, we found that the flexibility of a brain region's functional connectivity was positively correlated with the proportion of its structural links extending to different cognitive systems. Notably, this relationship was mediated by nodes' boundary controllability, suggesting that a region's strategic location on the boundaries of modules may underpin the capacity to integrate information across different cognitive processes. Broadly, our study provides a mechanistic framework that illustrates how temporal flexibility observed in functional networks may be mediated by the controllability of the underlying structural connectivity.
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Affiliation(s)
- Shi Gu
- Brain and Intelligence Group, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Panagiotis Fotiadis
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Linden Parkes
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Cedric H. Xia
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ruben C. Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Raquel E. Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - David R. Roalf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Theodore D. Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dani S. Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
- Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Santa Fe Institute, Santa Fe, NM, USA
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16
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Spatuzzi R, Vespa A, Fabbietti P, Ricciuti M, Rosati G, Guariniello L, Verrastro MAF, Attademo L, Giulietti MV. Elderly Helping Other Elderly: A Comparative Study of Family Caregiver Burden Between Patients With Dementia or Cancer at the End of Life. JOURNAL OF SOCIAL WORK IN END-OF-LIFE & PALLIATIVE CARE 2022; 18:96-108. [PMID: 35245165 DOI: 10.1080/15524256.2022.2042459] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
A new reality is being observed around the world as the population ages: family caregivers, who are themselves older adults helping their ill older relatives. The aim of this study is to assess the burden of the older family caregiver assisting older patients in his or her end-of-life who are suffering from dementia or cancer. In this context, the elderly person is involved in the dual role of patient and caregiver. In this comparative study, a total of 87 older family caregivers (age ≥ 65 years) completed the Caregiver Burden Inventory (CBI) measurement. The sample was divided into 2 subgroups based on the individuals' advanced disease: Alzheimer's disease (AD) or cancer. Compared to cancer caregivers, the AD subgroup reported significantly higher scores in the CBI-emotional subscale (P = 0.006), confirmed by the evaluation of the generalized linear model (multivariate). There were no significant differences in the other CBI subscales and overall scores. According to the findings of this study, elderly who help elderly with AD are at a higher risk of experiencing an emotional burden than cancer caregivers. This data could be considered in designing interventions to reduce the caregiver burden of older family caregivers as they provide informal end-of-life care.
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Affiliation(s)
- Roberta Spatuzzi
- UOSD CSM Vulture-Melfese, Department of Mental Health, ASP Basilicata, Potenza, Italy
| | - Anna Vespa
- Clinic of Internal Medicine and Geriatrics, Scientific and Technological Area, INRCA-IRCCS National Institute of Health and Science on Aging, Ancona, Italy
| | - Paolo Fabbietti
- Biostatistical Center, INRCA-IRCCS National Institute of Health and Science on Aging, Ancona, Italy
| | | | - Gerardo Rosati
- Medical Oncology Unit, "San Carlo" Hospital, Potenza, Italy
| | - Lorella Guariniello
- UOSD CSM Vulture-Melfese, Department of Mental Health, ASP Basilicata, Potenza, Italy
| | | | - Luigi Attademo
- Department of Mental Health, Hospital Psychiatric Service of Diagnosis and Care at "San Carlo" Hospital, ASP Basilicata, Italian NHS, Italy
| | - Maria Velia Giulietti
- Clinic of Internal Medicine and Geriatrics, Scientific and Technological Area, INRCA-IRCCS National Institute of Health and Science on Aging, Ancona, Italy
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17
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Serban CA, Barborica A, Roceanu AM, Mindruta I, Ciurea J, Pâslaru AC, Zăgrean AM, Zăgrean L, Moldovan M. A method to assess the default EEG macrostate and its reactivity to stimulation. Clin Neurophysiol 2021; 134:50-64. [PMID: 34973517 DOI: 10.1016/j.clinph.2021.12.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Revised: 08/23/2021] [Accepted: 12/04/2021] [Indexed: 11/16/2022]
Abstract
OBJECTIVE The default mode network (DMN) is deactivated by stimulation. We aimed to assess the DMN reactivity impairment by routine EEG recordings in stroke patients with impaired consciousness. METHODS Binocular light flashes were delivered at 1 Hz in 1-minute epochs, following a 1-minute baseline (PRE). The EEG was decomposed in a series of binary oscillatory macrostates by topographic spectral clustering. The most deactivated macrostate was labeled the default EEG macrostate (DEM). Its reactivity (DER) was quantified as the decrease in DEM occurrence probability during stimulation. A normalized DER index (DERI) was calculated as DER/PRE. The measures were compared between 14 healthy controls and 32 comatose patients under EEG monitoring following an acute stroke. RESULTS The DEM was mapped to the posterior DMN hubs. In the patients, these DEM source dipoles were 3-4 times less frequent and were associated with an increased theta activity. Even in a reduced 6-channel montage, a DER below 6.26% corresponding to a DERI below 0.25 could discriminate the patients with sensitivity and specificity well above 80%. CONCLUSION The method detected the DMN impairment in post-stroke coma patients. SIGNIFICANCE The DEM and its reactivity to stimulation could be useful to monitor the DMN function at bedside.
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Affiliation(s)
- Cosmin-Andrei Serban
- Physics Department, University of Bucharest, Romania; Termobit Prod SRL, Bucharest, Romania; FHC Inc, Bowdoin, ME, USA.
| | - Andrei Barborica
- Physics Department, University of Bucharest, Romania; Termobit Prod SRL, Bucharest, Romania; FHC Inc, Bowdoin, ME, USA.
| | | | - Ioana Mindruta
- Neurology Department, University Emergency Hospital, Bucharest, Romania.
| | - Jan Ciurea
- Department of Neurosurgery, Bagdasar-Arseni Emergency Hospital, Bucharest, Romania.
| | - Alexandru C Pâslaru
- Division of Physiology and Neuroscience, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
| | - Ana-Maria Zăgrean
- Division of Physiology and Neuroscience, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
| | - Leon Zăgrean
- Division of Physiology and Neuroscience, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
| | - Mihai Moldovan
- Termobit Prod SRL, Bucharest, Romania; Division of Physiology and Neuroscience, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania; Neuroscience, University of Copenhagen, Copenhagen, Denmark; Department of Clinical Neurophysiology, Rigshospitalet, Copenhagen, Denmark.
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18
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Moretto M, Silvestri E, Zangrossi A, Corbetta M, Bertoldo A. Unveiling whole-brain dynamics in normal aging through Hidden Markov Models. Hum Brain Mapp 2021; 43:1129-1144. [PMID: 34783122 PMCID: PMC8764474 DOI: 10.1002/hbm.25714] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 10/24/2021] [Accepted: 10/31/2021] [Indexed: 11/27/2022] Open
Abstract
During normal aging, the brain undergoes structural and functional changes. Many studies applied static functional connectivity (FC) analysis on resting state functional magnetic resonance imaging (rs‐fMRI) data showing a link between aging and the increase of between‐networks connectivity. However, it has been demonstrated that FC is not static but varies over time. By employing the dynamic data‐driven approach of Hidden Markov Models, this study aims to investigate how aging is related to specific characteristics of dynamic brain states. Rs‐fMRI data of 88 subjects, equally distributed in young and old were analyzed. The best model resulted to be with six states, which we characterized not only in terms of FC and mean BOLD activation, but also uncertainty of the estimates. We found two states were mostly occupied by young subjects, whereas three other states by old subjects. A graph‐based analysis revealed a decrease in strength with the increase of age, and an overall more integrated topology of states occupied by old subjects. Indeed, while young subjects tend to cycle in a loop of states characterized by a high segregation of the networks, old subjects' loops feature high integration, with a crucial intermediary role played by the dorsal attention network. These results suggest that the employed mathematical approach captures the complex and rich brain's dynamics underpinning the aging process.
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Affiliation(s)
- Manuela Moretto
- Department of Information Engineering, University of Padova, Padova, Italy.,Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Erica Silvestri
- Department of Information Engineering, University of Padova, Padova, Italy.,Padova Neuroscience Center, University of Padova, Padova, Italy
| | | | - Maurizio Corbetta
- Padova Neuroscience Center, University of Padova, Padova, Italy.,Department of Neuroscience, University of Padova, Padova, Italy
| | - Alessandra Bertoldo
- Department of Information Engineering, University of Padova, Padova, Italy.,Padova Neuroscience Center, University of Padova, Padova, Italy
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19
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Sele S, Liem F, Mérillat S, Jäncke L. Age-related decline in the brain: a longitudinal study on inter-individual variability of cortical thickness, area, volume, and cognition. Neuroimage 2021; 240:118370. [PMID: 34245866 DOI: 10.1016/j.neuroimage.2021.118370] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Revised: 06/28/2021] [Accepted: 07/05/2021] [Indexed: 12/21/2022] Open
Abstract
Magnetic Resonance Imaging (MRI) studies have shown that cortical volume declines with age. Although volume is a multiplicative measure consisting of thickness and area, few studies have focused on both its components. Information on decline variability and associations between person-specific changes of different brain metrics, brain regions, and cognition is sparse. In addition, the estimates have often been biased by the measurement error, because three repeated measures are minimally required to separate the measurement error from person-specific changes. With a sample size of N = 231, five repeated measures, and an observational time span of seven years, this study explores the associations between changes of different brain metrics, brain regions, and cognitive abilities in aging. Person-specific changes were obtained by latent growth curve models using Bayesian estimation. Our data indicate that both thickness and area are important contributors to volumetric changes. In most brain regions, area clearly declined on average over the years, while thickness showed only little decline. However, there was also substantial variation around the average slope in thickness and area. The correlation pattern of changes in thickness between brain regions was strong and largely homogenous. The pattern for changes in area was similar but weaker, indicating that factors affecting area may be more region-specific. Changes in thickness and volume were substantially correlated with changes in cognition. In some brain regions, changes in area were also related to changes in cognition. Overall, studying the associations between the trajectories of brain regions in different brain metrics provides insights into the regional heterogeneity of structural changes. SIGNIFICANCE STATEMENT: Many studies have described volumetric brain changes in aging. Few studies have focused on both its individual components: area and thickness. Longitudinal studies with three or more time points are highly needed, because they provide more precise average change estimates and, more importantly, allow us to quantify the associations between changes in the different brain metrics, brain regions, and other variables (e.g. cognitive abilities). Studying these associations is important because they can provide information regarding possible underlying factors of these changes. Our study, with a large sample size, five repeated measures, and an observational time span of seven years, provides new insights about the associations between person-specific changes in thickness, area, volume, and cognitive abilities.
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Affiliation(s)
- Silvano Sele
- Division Neuropsychology, Department of Psychology, University of Zurich, Zurich, Switzerland; University Research Priority Program "Dynamics of Healthy Aging", University of Zurich, Zurich, Switzerland.
| | - Franziskus Liem
- University Research Priority Program "Dynamics of Healthy Aging", University of Zurich, Zurich, Switzerland
| | - Susan Mérillat
- University Research Priority Program "Dynamics of Healthy Aging", University of Zurich, Zurich, Switzerland
| | - Lutz Jäncke
- Division Neuropsychology, Department of Psychology, University of Zurich, Zurich, Switzerland; University Research Priority Program "Dynamics of Healthy Aging", University of Zurich, Zurich, Switzerland.
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20
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Zhang L, Zhao J, Zhou Q, Liu Z, Zhang Y, Cheng W, Gong W, Hu X, Lu W, Bullmore ET, Lo CYZ, Feng J. Sensory, somatomotor and internal mentation networks emerge dynamically in the resting brain with internal mentation predominating in older age. Neuroimage 2021; 237:118188. [PMID: 34020018 DOI: 10.1016/j.neuroimage.2021.118188] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Revised: 04/15/2021] [Accepted: 05/17/2021] [Indexed: 10/21/2022] Open
Abstract
Age-related changes in the brain are associated with a decline in functional flexibility. Intrinsic functional flexibility is evident in the brain's dynamic ability to switch between alternative spatiotemporal states during resting state. However, the relationship between brain connectivity states, associated psychological functions during resting state, and the changes in normal aging remain poorly understood. In this study, we analyzed resting-state functional magnetic resonance imaging (rsfMRI) data from the Human Connectome Project (HCP; N = 812) and the UK Biobank (UKB; N = 6,716). Using signed community clustering to identify distinct states of dynamic functional connectivity, and text-mining of a large existing literature for functional annotation of each state, our findings from the HCP dataset indicated that the resting brain spontaneously transitions between three functionally specialized states: sensory, somatomotor, and internal mentation networks. The occurrence, transition-rate, and persistence-time parameters for each state were correlated with behavioural scores using canonical correlation analysis. We estimated the same brain states and parameters in the UKB dataset, subdivided into three distinct age ranges: 50-55, 56-67, and 68-78 years. We found that the internal mentation network was more frequently expressed in people aged 71 and older, whereas people younger than 55 more frequently expressed sensory and somatomotor networks. Furthermore, analysis of the functional entropy - a measure of uncertainty of functional connectivity - also supported this finding across the three age ranges. Our study demonstrates that dynamic functional connectivity analysis can expose the time-varying patterns of transition between functionally specialized brain states, which are strongly tied to increasing age.
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Affiliation(s)
- Lu Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China; Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China; Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States
| | - Jiajia Zhao
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Qunjie Zhou
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Zhaowen Liu
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, United States; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, United States
| | - Yi Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Wei Cheng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China
| | - Weikang Gong
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB), University of Oxford, Oxford OX3 9DU, United Kingdom
| | - Xiaoping Hu
- Department of Bioengineering, University of California, Riverside, CA, United States
| | - Wenlian Lu
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China; Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China; School of Mathematical Sciences, Fudan University, Shanghai, China
| | - Edward T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, United Kingdom; Cambridgeshire and Peterborough NHS Foundation Trust, Huntingdon PE29 3RJ, United Kingdom
| | - Chun-Yi Zac Lo
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China.
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China; Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China; Oxford Centre for Computational Neuroscience, Oxford, United Kingdom; Department of Computer Science, University of Warwick, Coventry, United Kingdom.
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21
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Strategies and cognitive reserve to preserve lexical production in aging. GeroScience 2021; 43:1725-1765. [PMID: 33970414 PMCID: PMC8492841 DOI: 10.1007/s11357-021-00367-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 04/09/2021] [Indexed: 10/28/2022] Open
Abstract
In the absence of any neuropsychiatric condition, older adults may show declining performance in several cognitive processes and among them, in retrieving and producing words, reflected in slower responses and even reduced accuracy compared to younger adults. To overcome this difficulty, healthy older adults implement compensatory strategies, which are the focus of this paper. We provide a review of mainstream findings on deficient mechanisms and possible neurocognitive strategies used by older adults to overcome the deleterious effects of age on lexical production. Moreover, we present findings on genetic and lifestyle factors that might either be protective or risk factors of cognitive impairment in advanced age. We propose that "aging-modulating factors" (AMF) can be modified, offering prevention opportunities against aging effects. Based on our review and this proposition, we introduce an integrative neurocognitive model of mechanisms and compensatory strategies for lexical production in older adults (entitled Lexical Access and Retrieval in Aging, LARA). The main hypothesis defended in LARA is that cognitive aging evolves heterogeneously and involves complementary domain-general and domain-specific mechanisms, with substantial inter-individual variability, reflected at behavioral, cognitive, and brain levels. Furthermore, we argue that the ability to compensate for the effect of cognitive aging depends on the amount of reserve specific to each individual which is, in turn, modulated by the AMF. Our conclusion is that a variety of mechanisms and compensatory strategies coexist in the same individual to oppose the effect of age. The role of reserve is pivotal for a successful coping with age-related changes and future research should continue to explore the modulating role of AMF.
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22
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Mikos A, Malagurski B, Liem F, Mérillat S, Jäncke L. Object-Location Memory Training in Older Adults Leads to Greater Deactivation of the Dorsal Default Mode Network. Front Hum Neurosci 2021; 15:623766. [PMID: 33716693 PMCID: PMC7952529 DOI: 10.3389/fnhum.2021.623766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 01/20/2021] [Indexed: 12/02/2022] Open
Abstract
Substantial evidence indicates that cognitive training can be efficacious for older adults, but findings regarding training-related brain plasticity have been mixed and vary depending on the imaging modality. Recent years have seen a growth in recognition of the importance of large-scale brain networks on cognition. In particular, task-induced deactivation within the default mode network (DMN) is thought to facilitate externally directed cognition, while aging-related decrements in this neural process are related to reduced cognitive performance. It is not yet clear whether task-induced deactivation within the DMN can be enhanced by cognitive training in the elderly. We previously reported durable cognitive improvements in a sample of healthy older adults (age range = 60-75) who completed 6 weeks of process-based object-location memory training (N = 36) compared to an active control training group (N = 31). The primary aim of the current study is to evaluate whether these cognitive gains are accompanied by training-related changes in task-related DMN deactivation. Given the evidence for heterogeneity of the DMN, we examine task-related activation/deactivation within two separate DMN branches, a ventral branch related to episodic memory and a dorsal branch more closely resembling the canonical DMN. Participants underwent functional magnetic resonance imaging (fMRI) while performing an untrained object-location memory task at four time points before, during, and after the training period. Task-induced (de)activation values were extracted for the ventral and dorsal DMN branches at each time point. Relative to visual fixation baseline: (i) the dorsal DMN was deactivated during the scanner task, while the ventral DMN was activated; (ii) the object-location memory training group exhibited an increase in dorsal DMN deactivation relative to the active control group over the course of training and follow-up; (iii) changes in dorsal DMN deactivation did not correlate with task improvement. These results indicate a training-related enhancement of task-induced deactivation of the dorsal DMN, although the specificity of this improvement to the cognitive task performed in the scanner is not clear.
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Affiliation(s)
- Ania Mikos
- University Research Priority Program “Dynamics of Healthy Aging”, University of Zurich, Zurich, Switzerland
| | - Brigitta Malagurski
- University Research Priority Program “Dynamics of Healthy Aging”, University of Zurich, Zurich, Switzerland
| | - Franziskus Liem
- University Research Priority Program “Dynamics of Healthy Aging”, University of Zurich, Zurich, Switzerland
| | - Susan Mérillat
- University Research Priority Program “Dynamics of Healthy Aging”, University of Zurich, Zurich, Switzerland
| | - Lutz Jäncke
- University Research Priority Program “Dynamics of Healthy Aging”, University of Zurich, Zurich, Switzerland
- Division of Neuropsychology, Institute of Psychology, University of Zurich, Zurich, Switzerland
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23
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Malagurski B, Liem F, Oschwald J, Mérillat S, Jäncke L. Longitudinal functional brain network reconfiguration in healthy aging. Hum Brain Mapp 2020; 41:4829-4845. [PMID: 32857461 PMCID: PMC7643380 DOI: 10.1002/hbm.25161] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Revised: 07/12/2020] [Accepted: 07/19/2020] [Indexed: 12/17/2022] Open
Abstract
Healthy aging is associated with changes in cognitive performance and functional brain organization. In fact, cross-sectional studies imply lower modularity and significant heterogeneity in modular architecture across older subjects. Here, we used a longitudinal dataset consisting of four occasions of resting-state-fMRI and cognitive testing (spanning 4 years) in 150 healthy older adults. We applied a graph-theoretic analysis to investigate the time-evolving modular structure of the whole-brain network, by maximizing the multilayer modularity across four time points. Global flexibility, which reflects the tendency of brain nodes to switch between modules across time, was significantly higher in healthy elderly than in a temporal null model. Further, global flexibility, as well as network-specific flexibility of the default mode, frontoparietal control, and somatomotor networks, were significantly associated with age at baseline. These results indicate that older age is related to higher variability in modular organization. The temporal metrics were not associated with simultaneous changes in processing speed or learning performance in the context of memory encoding. Finally, this approach provides global indices for longitudinal change across a given time span and it may contribute to uncovering patterns of modular variability in healthy and clinical aging populations.
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Affiliation(s)
- Brigitta Malagurski
- University Research Priority Program “Dynamics of Healthy Aging”University of ZurichZurichSwitzerland
| | - Franziskus Liem
- University Research Priority Program “Dynamics of Healthy Aging”University of ZurichZurichSwitzerland
| | - Jessica Oschwald
- University Research Priority Program “Dynamics of Healthy Aging”University of ZurichZurichSwitzerland
| | - Susan Mérillat
- University Research Priority Program “Dynamics of Healthy Aging”University of ZurichZurichSwitzerland
| | - Lutz Jäncke
- University Research Priority Program “Dynamics of Healthy Aging”University of ZurichZurichSwitzerland
- Division of Neuropsychology, Institute of PsychologyUniversity of ZurichZurichSwitzerland
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