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Madden DJ, Merenstein JL, Mullin HA, Jain S, Rudolph MD, Cohen JR. Age-related differences in resting-state, task-related, and structural brain connectivity: graph theoretical analyses and visual search performance. Brain Struct Funct 2024:10.1007/s00429-024-02807-2. [PMID: 38856933 DOI: 10.1007/s00429-024-02807-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 05/13/2024] [Indexed: 06/11/2024]
Abstract
Previous magnetic resonance imaging (MRI) research suggests that aging is associated with a decrease in the functional interconnections within and between groups of locally organized brain regions (modules). Further, this age-related decrease in the segregation of modules appears to be more pronounced for a task, relative to a resting state, reflecting the integration of functional modules and attentional allocation necessary to support task performance. Here, using graph-theoretical analyses, we investigated age-related differences in a whole-brain measure of module connectivity, system segregation, for 68 healthy, community-dwelling individuals 18-78 years of age. We obtained resting-state, task-related (visual search), and structural (diffusion-weighted) MRI data. Using a parcellation of modules derived from the participants' resting-state functional MRI data, we demonstrated that the decrease in system segregation from rest to task (i.e., reconfiguration) increased with age, suggesting an age-related increase in the integration of modules required by the attentional demands of visual search. Structural system segregation increased with age, reflecting weaker connectivity both within and between modules. Functional and structural system segregation had qualitatively different influences on age-related decline in visual search performance. Functional system segregation (and reconfiguration) influenced age-related decline in the rate of visual evidence accumulation (drift rate), whereas structural system segregation contributed to age-related slowing of encoding and response processes (nondecision time). The age-related differences in the functional system segregation measures, however, were relatively independent of those associated with structural connectivity.
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Affiliation(s)
- David J Madden
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC, 27710, USA.
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, 27710, USA.
- Center for Cognitive Neuroscience, Duke University, Durham, NC, 27708, USA.
| | - Jenna L Merenstein
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC, 27710, USA
| | - Hollie A Mullin
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC, 27710, USA
- Department of Psychology, Pennsylvania State University, University Park, PA, 16802, USA
| | - Shivangi Jain
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC, 27710, USA
- AdventHealth Research Institute, Neuroscience Institute, Orlando, FL, 32804, USA
| | - Marc D Rudolph
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27514, USA
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, 27101, USA
| | - Jessica R Cohen
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27514, USA
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Potvin-Desrochers A, Atri A, Clouette J, Hepple RT, Taivassalo T, Paquette C. Resting-state Functional Connectivity of the Motor and Cognitive Areas is Preserved in Masters Athletes. Neuroscience 2024; 546:53-62. [PMID: 38522662 DOI: 10.1016/j.neuroscience.2024.03.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 03/16/2024] [Accepted: 03/19/2024] [Indexed: 03/26/2024]
Abstract
Aging is characterized by a decline in physical and cognitive functions, often resulting in decreased quality of life. Physical activity has been suggested to potentially slow down various aspects of the aging process, a theory that has been supported by studies of Masters Athletes (MA). For example, MA usually have better cognitive and physical functions than age-matched sedentary and healthy older adults (OA), making them a valuable model to gain insights into mechanisms that promote physical and cognitive function with aging. The purpose of this study was to identify differences in resting-state functional connectivity (rs-FC) of motor and cognitive regions between MA and OA and determine if these differences in the resting brain are associated with differences in cognitive and physical performance between groups. Fifteen MA (9 males) and 12 age-matched OA (six males) were included. rs-FC images were compared to identify significant between-groups differences in brain connectivity. There was higher connectivity between the cognitive and motor networks for the OA group, whereas the MA group had stronger connectivity between different regions within the same network, both for the cognitive and the motor networks. These results are in line with the literature suggesting that aging reduces the segregation between functional networks and causes regions within the same network to be less strongly connected. High-level physical activity practiced by the MA most likely contributes to attenuating aging-related changes in brain functional connectivity, preserving clearer boundaries between different functional networks, which may ultimately favor maintenance of efficient cognitive and sensorimotor processing.
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Affiliation(s)
- Alexandra Potvin-Desrochers
- Department of Kinesiology and Physical Education, McGill University, 475 Pine Ave., Montreal, Quebec, Canada; Jewish Rehabilitation Hospital Site of CISSS-Laval and Research Site of the Montreal Centre for Interdisciplinary Research in Rehabilitation (CRIR), 3205 Place Alton-Goldbloom, Laval, Quebec, Canada; Integrated Program in Neuroscience (IPN), McGill University, 1033 Pine Ave, Montreal, Quebec, Canada
| | - Alisha Atri
- Department of Kinesiology and Physical Education, McGill University, 475 Pine Ave., Montreal, Quebec, Canada; Jewish Rehabilitation Hospital Site of CISSS-Laval and Research Site of the Montreal Centre for Interdisciplinary Research in Rehabilitation (CRIR), 3205 Place Alton-Goldbloom, Laval, Quebec, Canada
| | - Julien Clouette
- Department of Kinesiology and Physical Education, McGill University, 475 Pine Ave., Montreal, Quebec, Canada; Jewish Rehabilitation Hospital Site of CISSS-Laval and Research Site of the Montreal Centre for Interdisciplinary Research in Rehabilitation (CRIR), 3205 Place Alton-Goldbloom, Laval, Quebec, Canada
| | - Russell T Hepple
- Department of Physical Therapy, University of Florida, 101 Newell Dr, Gainesville, FL, USA; Department of Physiology and Functional Genomics, University of Florida, 1600 SW Archer Rd, Gainesville, FL, USA
| | - Tanja Taivassalo
- Department of Physiology and Functional Genomics, University of Florida, 1600 SW Archer Rd, Gainesville, FL, USA
| | - Caroline Paquette
- Department of Kinesiology and Physical Education, McGill University, 475 Pine Ave., Montreal, Quebec, Canada; Jewish Rehabilitation Hospital Site of CISSS-Laval and Research Site of the Montreal Centre for Interdisciplinary Research in Rehabilitation (CRIR), 3205 Place Alton-Goldbloom, Laval, Quebec, Canada; Integrated Program in Neuroscience (IPN), McGill University, 1033 Pine Ave, Montreal, Quebec, Canada.
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Badji A, Cedres N, Muehlboeck JS, Khan W, Dhollander T, Barroso J, Ferreira D, Westman E. In vivo microstructural heterogeneity of white matter and cognitive correlates in aging using tissue compositional analysis of diffusion magnetic resonance imaging. Hum Brain Mapp 2024; 45:e26618. [PMID: 38414286 PMCID: PMC10899800 DOI: 10.1002/hbm.26618] [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: 08/09/2023] [Revised: 12/03/2023] [Accepted: 12/24/2023] [Indexed: 02/29/2024] Open
Abstract
BACKGROUND Age-related cognitive decline is linked to changes in the brain, particularly the deterioration of white matter (WM) microstructure that accelerates after the age of 60. WM deterioration is associated with mild cognitive impairment and dementia, but the origin and role of white matter signal abnormalities (WMSA) seen in standard MRI remain debated due to their heterogeneity. This study explores the potential of single-shell 3-tissue constrained spherical deconvolution (SS3T-CSD), a novel technique that models diffusion data in terms of gray matter (TG ), white matter (Tw ), and cerebrospinal fluid (TC ), to differentiate WMSA from normal-appearing white matter and better understand the interplay between changes in WM microstructure and decline in cognition. METHODS A total of 189 individuals from the GENIC cohort were included. MRI data, including T1-weighted and diffusion images, were obtained. Preprocessing steps were performed on the diffusion MRI data, followed by the SS3T-CSD. WMSA were segmented using FreeSurfer. Statistical analyses were conducted to assess the association between age, WMSA volume, 3-tissue signal fractions (Tw , TG , and TC ), and neuropsychological variables. RESULTS Participants above 60 years old showed worse cognitive performance and processing speed compared to those below 60 (p < .001). Age was negatively associated with Tw in normal-appearing white matter (p < .001) and positively associated with TG in both WMSA (p < .01) and normal-appearing white matter (p < .001). Age was also significantly associated with WMSA volume (p < .001). Higher processing speed was associated with lower Tw and higher TG , in normal-appearing white matter (p < .01 and p < .001, respectively), as well as increased WMSA volume (p < .001). Similarly, lower MMSE scores correlated with lower Tw and higher TG in normal-appearing white matter (p < .05). High cholesterol and hypertension were associated with higher WMSA volume (p < .05). CONCLUSION The microstructural heterogeneity within normal-appearing white matter and WMSA is associated with increasing age and cognitive variation, in cognitively unimpaired individuals. Furthermore, the 3-tissue signal fractions are more specific to potential white matter alterations than conventional MRI measures such as WMSA volume. These findings also support the view that the WMSA volumes may be more influenced by vascular risk factors than the 3-tissue metrics. Finally, the 3-tissue metrics were able to capture associations with cognitive tests and therefore capable of capturing subtle pathological changes in the brain in individuals who are still within the normal range of cognitive performance.
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Affiliation(s)
- Atef Badji
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Nira Cedres
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Las Palmas de Gran Canaria, España
| | - J-Sebastian Muehlboeck
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Wasim Khan
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Thijs Dhollander
- Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Jose Barroso
- Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Las Palmas de Gran Canaria, España
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Las Palmas de Gran Canaria, España
| | - Eric Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
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Schulz M, Petersen M, Cheng B, Thomalla G. Association of structural connectivity with functional brain network segregation in a middle-aged to elderly population. Front Aging Neurosci 2024; 16:1291162. [PMID: 38371399 PMCID: PMC10870644 DOI: 10.3389/fnagi.2024.1291162] [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: 09/08/2023] [Accepted: 01/03/2024] [Indexed: 02/20/2024] Open
Abstract
Introduction The deterioration of white matter pathways is one of the hallmarks of the ageing brain. In theory, this decrease in structural integrity leads to disconnection between regions of brain networks and thus to altered functional connectivity and a decrease in cognitive abilities. However, in many studies, associations between structural and functional connectivity are rather weak or not observed at all. System segregation, defined as the extent of partitioning between different resting state networks has increasingly gained attention in recent years as a new metric for functional changes in the aging brain. Yet there is a shortage of previous reports describing the association of structural integrity and functional segregation. Methods Therefore, we used a large a large sample of 2,657 participants from the Hamburg City Health Study, a prospective population-based study including participants aged 46-78 years from the metropolitan region Hamburg, Germany. We reconstructed structural and functional connectomes to analyze whether there is an association between age-related differences in structural connectivity and functional segregation, and whether this association is stronger than between structural connectivity and functional connectivity. In a second step, we investigated the relationship between functional segregation and executive cognitive function and tested whether this association is stronger than that between functional connectivity and executive cognitive function. Results We found a significant age-independent association between decreasing structural connectivity and decreasing functional segregation across the brain. In addition, decreasing functional segregation showed an association with decreasing executive cognitive function. On the contrary, no such association was observed between functional connectivity and structural connectivity or executive function. Discussion These results indicate that the segregation metric is a more sensitive biomarker of cognitive ageing than functional connectivity at the global level and offers a unique and more complementary network-based explanation.
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Affiliation(s)
- Maximilian Schulz
- Department of Neurology, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
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Madden DJ, Merenstein JL. Quantitative susceptibility mapping of brain iron in healthy aging and cognition. Neuroimage 2023; 282:120401. [PMID: 37802405 PMCID: PMC10797559 DOI: 10.1016/j.neuroimage.2023.120401] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 09/14/2023] [Accepted: 09/30/2023] [Indexed: 10/10/2023] Open
Abstract
Quantitative susceptibility mapping (QSM) is a magnetic resonance imaging (MRI) technique that can assess the magnetic properties of cerebral iron in vivo. Although brain iron is necessary for basic neurobiological functions, excess iron content disrupts homeostasis, leads to oxidative stress, and ultimately contributes to neurodegenerative disease. However, some degree of elevated brain iron is present even among healthy older adults. To better understand the topographical pattern of iron accumulation and its relation to cognitive aging, we conducted an integrative review of 47 QSM studies of healthy aging, with a focus on five distinct themes. The first two themes focused on age-related increases in iron accumulation in deep gray matter nuclei versus the cortex. The overall level of iron is higher in deep gray matter nuclei than in cortical regions. Deep gray matter nuclei vary with regard to age-related effects, which are most prominent in the putamen, and age-related deposition of iron is also observed in frontal, temporal, and parietal cortical regions during healthy aging. The third theme focused on the behavioral relevance of iron content and indicated that higher iron in both deep gray matter and cortical regions was related to decline in fluid (speed-dependent) cognition. A handful of multimodal studies, reviewed in the fourth theme, suggest that iron interacts with imaging measures of brain function, white matter degradation, and the accumulation of neuropathologies. The final theme concerning modifiers of brain iron pointed to potential roles of cardiovascular, dietary, and genetic factors. Although QSM is a relatively recent tool for assessing cerebral iron accumulation, it has significant promise for contributing new insights into healthy neurocognitive aging.
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Affiliation(s)
- David J Madden
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC 27710, USA; Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, USA; Center for Cognitive Neuroscience, Duke University, Durham, NC 27708, USA.
| | - Jenna L Merenstein
- Brain Imaging and Analysis Center, Duke University Medical Center, Box 3918, Durham, NC 27710, USA
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Huang P, Tint MT, Lee M, Ngoh ZM, Gluckman P, Chong YS, Han W, Fu Y, Wee CL, Fortier MV, Ang KK, Lee YS, Yap F, Eriksson JG, Meaney MJ, Tan AP. Functional activity of the caudate mediates the relation between early childhood microstructural variations and elevated metabolic syndrome scores. Neuroimage 2023; 278:120273. [PMID: 37473977 DOI: 10.1016/j.neuroimage.2023.120273] [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: 04/14/2023] [Revised: 06/10/2023] [Accepted: 07/11/2023] [Indexed: 07/22/2023] Open
Abstract
BACKGROUND Metabolic syndrome score in children assesses the risk of developing cardiovascular disease in future. We aim to probe the role of the caudate in relation to the metabolic syndrome score. Furthermore, using both functional and structural neuroimaging, we aim to examine the interplay between functional and structural measures. METHODS A longitudinal birth cohort study with functional and structural neuroimaging data obtained at 4.5, 6.0 and 7.5 years and metabolic syndrome scores at 8.0 years was used. Pearson correlation and linear regression was used to test for correlation fractional anisotropy (FA) and fractional amplitude of low frequency fluctuations (fALFF) of the caudate with metabolic syndrome scores. Mediation analysis was used to test if later brain measures mediated the relation between earlier brain measures and metabolic syndrome scores. Inhibitory control was also tested as a mediator of the relation between caudate brain measures and metabolic syndrome scores. RESULTS FA at 4.5 years and fALFF at 7.5 years of the left caudate was significantly correlated with metabolic syndrome scores. Post-hoc mediation analysis showed that fALFF at 7.5 years fully mediated the relation between FA at 4.5 years and metabolic syndrome scores. Inhibitory control was significantly correlated with fALFF at 7.5 years, but did not mediate the relation between fALFF at 7.5 years and metabolic syndrome scores. CONCLUSIONS We found that variations in caudate microstructure at 4.5 years predict later variation in functional activity at 7.5 years. This later variation in functional activity fully mediates the relation between microstructural changes in early childhood and metabolic syndrome scores at 8.0 years.
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Affiliation(s)
- Pei Huang
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore
| | - Mya Thway Tint
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore
| | - Marissa Lee
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore
| | - Zhen Ming Ngoh
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore; Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Peter Gluckman
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore; Centre for Human Evolution, Adaptation and Disease, Liggins Institute, University of Auckland, Auckland, New Zealand
| | - Yap Seng Chong
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore; Department of Obstetrics & Gynaecology, National University Hospital Singapore, Singapore
| | - Weiping Han
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Singapore; Center for Neuro-Metabolism and Regeneration Research, Guangzhou Regenerative Medicine and Health Guangdong Laboratory, Guangzhou, China; School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yu Fu
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Singapore
| | - Caroline Lei Wee
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Singapore
| | - Marielle V Fortier
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore; Department of Diagnostic and Interventional Radiology, KK Women's and Children's Hospital, Singapore
| | - Kai Keng Ang
- Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore; School of Computer Science and Engineering, Nanyang Technological University, Singapore
| | - Yung Seng Lee
- Department of Paedatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Fabian Yap
- Department of Paediatrics, Endocrinology Service, KK Women's and Children's Hospital, Singapore, Singapore
| | - Johan G Eriksson
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore; Department of Obstetrics and Gynaecology and Human Potential Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland; Folkhälsan Research Center, Helsinki, Finland
| | - Michael J Meaney
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore; Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada; Brain - Body Initiative, Agency for Science and Technology (A*STAR), Singapore
| | - Ai Peng Tan
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Singapore; Department of Diagnostic Imaging, National University Hospital Singapore, Singapore.
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Merenstein JL, Zhao J, Mullin HA, Rudolph MD, Song AW, Madden DJ. High-resolution multi-shot diffusion imaging of structural networks in healthy neurocognitive aging. Neuroimage 2023; 275:120191. [PMID: 37244322 PMCID: PMC10482115 DOI: 10.1016/j.neuroimage.2023.120191] [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: 03/17/2023] [Revised: 05/10/2023] [Accepted: 05/24/2023] [Indexed: 05/29/2023] Open
Abstract
Healthy neurocognitive aging has been associated with the microstructural degradation of white matter pathways that connect distributed gray matter regions, assessed by diffusion-weighted imaging (DWI). However, the relatively low spatial resolution of standard DWI has limited the examination of age-related differences in the properties of smaller, tightly curved white matter fibers, as well as the relatively more complex microstructure of gray matter. Here, we capitalize on high-resolution multi-shot DWI, which allows spatial resolutions < 1 mm3 to be achieved on clinical 3T MRI scanners. We assessed whether traditional diffusion tensor-based measures of gray matter microstructure and graph theoretical measures of white matter structural connectivity assessed by standard (1.5 mm3 voxels, 3.375 μl volume) and high-resolution (1 mm3 voxels, 1μl volume) DWI were differentially related to age and cognitive performance in 61 healthy adults 18-78 years of age. Cognitive performance was assessed using an extensive battery comprising 12 separate tests of fluid (speed-dependent) cognition. Results indicated that the high-resolution data had larger correlations between age and gray matter mean diffusivity, but smaller correlations between age and structural connectivity. Moreover, parallel mediation models including both standard and high-resolution measures revealed that only the high-resolution measures mediated age-related differences in fluid cognition. These results lay the groundwork for future studies planning to apply high-resolution DWI methodology to further assess the mechanisms of both healthy aging and cognitive impairment.
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Affiliation(s)
- Jenna L Merenstein
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, 27710, USA.
| | - Jiayi Zhao
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, 27710, USA
| | - Hollie A Mullin
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, 27710, USA
| | - Marc D Rudolph
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27514, USA
| | - Allen W Song
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, 27710, USA
| | - David J Madden
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, 27710, USA; Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, 27710, USA; Center for Cognitive Neuroscience, Duke University, Durham, NC, 27708, USA
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Age-related differences in frontoparietal activation for target and distractor singletons during visual search. Atten Percept Psychophys 2023; 85:749-768. [PMID: 36627473 PMCID: PMC10066832 DOI: 10.3758/s13414-022-02640-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/12/2022] [Indexed: 01/11/2023]
Abstract
Age-related decline in visual search performance has been associated with different patterns of activation in frontoparietal regions using functional magnetic resonance imaging (fMRI), but whether these age-related effects represent specific influences of target and distractor processing is unclear. Therefore, we acquired event-related fMRI data from 68 healthy, community-dwelling adults ages 18-78 years, during both conjunction (T/F target among rotated Ts and Fs) and feature (T/F target among Os) search. Some displays contained a color singleton that could correspond to either the target or a distractor. A diffusion decision analysis indicated age-related increases in sensorimotor response time across all task conditions, but an age-related decrease in the rate of evidence accumulation (drift rate) was specific to conjunction search. Moreover, the color singleton facilitated search performance when occurring as a target and disrupted performance when occurring as a distractor, but only during conjunction search, and these effects were independent of age. The fMRI data indicated that decreased search efficiency for conjunction relative to feature search was evident as widespread frontoparietal activation. Activation within the left insula mediated the age-related decrease in drift rate for conjunction search, whereas this relation in the FEF and parietal cortex was significant only for individuals younger than 30 or 44 years, respectively. Finally, distractor singletons were associated with significant parietal activation, whereas target singletons were associated with significant frontoparietal deactivation, and this latter effect increased with adult age. Age-related differences in frontoparietal activation therefore reflect both the overall efficiency of search and the enhancement from salient targets.
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Deery HA, Di Paolo R, Moran C, Egan GF, Jamadar SD. The older adult brain is less modular, more integrated, and less efficient at rest: A systematic review of large-scale resting-state functional brain networks in aging. Psychophysiology 2023; 60:e14159. [PMID: 36106762 PMCID: PMC10909558 DOI: 10.1111/psyp.14159] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 07/22/2022] [Accepted: 07/25/2022] [Indexed: 12/23/2022]
Abstract
The literature on large-scale resting-state functional brain networks across the adult lifespan was systematically reviewed. Studies published between 1986 and July 2021 were retrieved from PubMed. After reviewing 2938 records, 144 studies were included. Results on 11 network measures were summarized and assessed for certainty of the evidence using a modified GRADE method. The evidence provides high certainty that older adults display reduced within-network and increased between-network functional connectivity. Older adults also show lower segregation, modularity, efficiency and hub function, and decreased lateralization and a posterior to anterior shift at rest. Higher-order functional networks reliably showed age differences, whereas primary sensory and motor networks showed more variable results. The inflection point for network changes is often the third or fourth decade of life. Age effects were found with moderate certainty for within- and between-network altered patterns and speed of dynamic connectivity. Research on within-subject bold variability and connectivity using glucose uptake provides low certainty of age differences but warrants further study. Taken together, these age-related changes may contribute to the cognitive decline often seen in older adults.
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Affiliation(s)
- Hamish A. Deery
- Turner Institute for Brain and Mental HealthMonash UniversityMelbourneVictoriaAustralia
- Monash Biomedical ImagingMonash UniversityMelbourneVictoriaAustralia
| | - Robert Di Paolo
- Turner Institute for Brain and Mental HealthMonash UniversityMelbourneVictoriaAustralia
- Monash Biomedical ImagingMonash UniversityMelbourneVictoriaAustralia
| | - Chris Moran
- Peninsula Clinical School, Central Clinical SchoolMonash UniversityFrankstonVictoriaAustralia
- Department of Geriatric MedicinePeninsula HealthFrankstonVictoriaAustralia
| | - Gary F. Egan
- Turner Institute for Brain and Mental HealthMonash UniversityMelbourneVictoriaAustralia
- Monash Biomedical ImagingMonash UniversityMelbourneVictoriaAustralia
- Australian Research Council Centre of Excellence for Integrative Brain FunctionMelbourneVictoriaAustralia
| | - Sharna D. Jamadar
- Turner Institute for Brain and Mental HealthMonash UniversityMelbourneVictoriaAustralia
- Monash Biomedical ImagingMonash UniversityMelbourneVictoriaAustralia
- Australian Research Council Centre of Excellence for Integrative Brain FunctionMelbourneVictoriaAustralia
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Jiang R, Scheinost D, Zuo N, Wu J, Qi S, Liang Q, Zhi D, Luo N, Chung Y, Liu S, Xu Y, Sui J, Calhoun V. A Neuroimaging Signature of Cognitive Aging from Whole-Brain Functional Connectivity. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2201621. [PMID: 35811304 PMCID: PMC9403648 DOI: 10.1002/advs.202201621] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Revised: 06/02/2022] [Indexed: 05/14/2023]
Abstract
Cognitive decline is amongst one of the most commonly reported complaints during normal aging. Despite evidence that age and cognition are linked with similar neural correlates, no previous studies have directly ascertained how these two constructs overlap in the brain in terms of neuroimaging-based prediction. Based on a long lifespan healthy cohort (CamCAN, aged 19-89 years, n = 567), it is shown that both cognitive function (domains spanning executive function, emotion processing, motor function, and memory) and human age can be reliably predicted from unique patterns of functional connectivity, with models generalizable in two external datasets (n = 533 and n = 453). Results show that cognitive decline and normal aging both manifest decrease within-network connections (especially default mode and ventral attention networks) and increase between-network connections (somatomotor network). Whereas dorsal attention network is an exception, which is highly predictive on cognitive ability but is weakly correlated with aging. Further, the positively weighted connections in predicting fluid intelligence significantly mediate its association with age. Together, these findings offer insights into why normal aging is often associated with cognitive decline in terms of brain network organization, indicating a process of neural dedifferentiation and compensational theory.
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Affiliation(s)
- Rongtao Jiang
- Department of Radiology and Biomedical ImagingYale School of MedicineNew HavenCT06520USA
| | - Dustin Scheinost
- Department of Radiology and Biomedical ImagingYale School of MedicineNew HavenCT06520USA
- Interdepartmental Neuroscience ProgramYale UniversityNew HavenCT06520USA
- Department of Statistics and Data ScienceYale UniversityNew HavenCT06520USA
- Child Study CenterYale School of MedicineNew HavenCT06510USA
| | - Nianming Zuo
- Brainnetome Center and National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of SciencesBeijing100190P. R. China
- School of Artificial IntelligenceUniversity of Chinese Academy of SciencesBeijing100049P. R. China
| | - Jing Wu
- Department of Medical OncologyBeijing You‐An HospitalCapital Medical UniversityBeijing100069P. R. China
| | - Shile Qi
- College of Computer Science and TechnologyNanjing University of Aeronautics and AstronauticsNanjing211106P. R. China
| | - Qinghao Liang
- Department of Biomedical EngineeringYale UniversityNew HavenCT06520USA
| | - Dongmei Zhi
- State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijing100088P. R. China
| | - Na Luo
- Brainnetome Center and National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of SciencesBeijing100190P. R. China
- School of Artificial IntelligenceUniversity of Chinese Academy of SciencesBeijing100049P. R. China
| | - Young‐Chul Chung
- Department of PsychiatryJeonbuk National University Medical SchoolJeonju54907Republic of Korea
- Department of PsychiatryChonbuk National University HospitalJeonju54907Republic of Korea
| | - Sha Liu
- Department of Psychiatry and MDT Center for Cognitive Impairment and Sleep DisordersFirst HospitalFirst Clinical Medical College of Shanxi Medical UniversityTaiyuan030001P. R. China
| | - Yong Xu
- Department of Psychiatry and MDT Center for Cognitive Impairment and Sleep DisordersFirst HospitalFirst Clinical Medical College of Shanxi Medical UniversityTaiyuan030001P. R. China
| | - Jing Sui
- State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijing100088P. R. China
- Tri‐institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS)Georgia Institute of TechnologyEmory University and Georgia State UniversityAtlantaGA30303USA
| | - Vince Calhoun
- Tri‐institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS)Georgia Institute of TechnologyEmory University and Georgia State UniversityAtlantaGA30303USA
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11
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Yin W, Zhou X, Li C, You M, Wan K, Zhang W, Zhu W, Li M, Zhu X, Qian Y, Sun Z. The Clustering Analysis of Time Properties in Patients With Cerebral Small Vessel Disease: A Dynamic Connectivity Study. Front Neurol 2022; 13:913241. [PMID: 35795790 PMCID: PMC9251301 DOI: 10.3389/fneur.2022.913241] [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: 04/05/2022] [Accepted: 05/27/2022] [Indexed: 11/13/2022] Open
Abstract
PurposeThis study aimed to investigate the dynamic functional connectivity (DFC) pattern in cerebral small vessel disease (CSVD) and explore the relationships between DFC temporal properties and cognitive impairment in CSVD.MethodsFunctional data were collected from 67 CSVD patients, including 35 patients with subcortical vascular cognitive impairment (SVCI) and 32 cognitively unimpaired (CU) patients, as well as 35 healthy controls (HCs). The DFC properties were estimated by k-means clustering analysis. DFC strength analysis was used to explore the regional functional alterations between CSVD patients and HCs. Correlation analysis was used for DFC properties with cognition and SVD scores, respectively.ResultsThe DFC analysis showed three distinct connectivity states (state I: sparsely connected, state II: strongly connected, state III: intermediate pattern). Compared to HCs, CSVD patients exhibited an increased proportion in state I and decreased proportion in state II. Besides, CSVD patients dwelled longer in state I while dwelled shorter in state II. CSVD subgroup analyses showed that state I frequently occurred and dwelled longer in SVCI compared with CSVD-CU. Also, the internetwork (frontal-parietal lobe, frontal-occipital lobe) and intranetwork (frontal lobe, occipital lobe) functional activities were obviously decreased in CSVD. Furthermore, the fractional windows and mean dwell time (MDT) in state I were negatively correlated with cognition in CSVD but opposite to cognition in state II.ConclusionPatients with CSVD accounted for a higher proportion and dwelled longer mean time in the sparsely connected state, while presented lower proportion and shorter mean dwell time in the strongly connected state, which was more prominent in SVCI. The changes in the DFC are associated with altered cognition in CSVD. This study provides a better explanation of the potential mechanism of CSVD patients with cognitive impairment from the perspective of DFC.
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Affiliation(s)
- Wenwen Yin
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xia Zhou
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Chenchen Li
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Mengzhe You
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Ke Wan
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Wei Zhang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Wenhao Zhu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Mingxu Li
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xiaoqun Zhu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yinfeng Qian
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Zhongwu Sun
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
- *Correspondence: Zhongwu Sun
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12
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Fareri DS, Hackett K, Tepfer LJ, Kelly V, Henninger N, Reeck C, Giovannetti T, Smith DV. Age-Related Differences in Ventral Striatal and Default Mode Network Function During Reciprocated Trust. Neuroimage 2022; 256:119267. [PMID: 35504565 PMCID: PMC9308012 DOI: 10.1016/j.neuroimage.2022.119267] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 04/28/2022] [Accepted: 04/29/2022] [Indexed: 11/04/2022] Open
Abstract
Social relationships change across the lifespan as social networks narrow and motivational priorities shift to the present. Interestingly, aging is also associated with changes in executive function, including decision-making abilities, but it remains unclear how age-related changes in both domains interact to impact financial decisions involving other people. To study this problem, we recruited 50 human participants (Nyounger = 26, ages 18–34; Nolder = 24, ages 63–80) to play an economic trust game as the investor with three partners (friend, stranger, and computer) who played the role of investee. Investors underwent functional magnetic resonance imaging (fMRI) during the trust game while investees were seated outside of the scanner. Building on our previous work with younger adults showing both enhanced striatal responses and altered default-mode network (DMN) connectivity as a function of social closeness during reciprocated trust, we predicted that these relations would exhibit age-related differences. We found that striatal responses to reciprocated trust from friends relative to strangers and computers were blunted in older adults relative to younger adults, thus supporting our primary pre-registered hypothesis regarding social closeness. We also found that older adults exhibited enhanced DMN connectivity with the temporoparietal junction (TPJ) during reciprocated trust from friends compared to computers while younger adults exhibited the opposite pattern. Taken together, these results advance our understanding of age-related differences in sensitivity to social closeness in the context of trusting others.
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Affiliation(s)
- Dominic S Fareri
- Gordon F. Derner School of Psychology, Adelphi University, Garden City, NY, USA.
| | | | - Lindsey J Tepfer
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Victoria Kelly
- Department of Psychology, Temple University, Philadelphia, PA, USA
| | - Nicole Henninger
- Lew Klein College of Media and Communication, Temple University, Philadelphia, PA, USA
| | - Crystal Reeck
- Fox School of Business, Temple University, Philadelphia, PA, USA
| | | | - David V Smith
- Department of Psychology, Temple University, Philadelphia, PA, USA.
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13
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Hsieh S, Yang MH. Potential Diffusion Tensor Imaging Biomarkers for Elucidating Intra-Individual Age-Related Changes in Cognitive Control and Processing Speed. Front Aging Neurosci 2022; 14:850655. [PMID: 35557836 PMCID: PMC9087335 DOI: 10.3389/fnagi.2022.850655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Accepted: 03/24/2022] [Indexed: 11/24/2022] Open
Abstract
Cognitive aging, especially cognitive control, and processing speed aging have been well-documented in the literature. Most of the evidence was reported based on cross-sectional data, in which inter-individual age effects were shown. However, there have been some studies pointing out the possibility of overlooking intra-individual changes in cognitive aging. To systematically examine whether age-related differences and age-related changes might yield distinctive patterns, this study directly compared cognitive control function and processing speed between different cohorts versus follow-up changes across the adult lifespan. Moreover, considering that cognitive aging has been attributed to brain disconnection in white matter (WM) integrity, this study focused on WM integrity via acquiring diffusion-weighted imaging data with an MRI instrument that are further fitted to a diffusion tensor model (i.e., DTI) to detect water diffusion directionality (i.e., fractional anisotropy, FA; mean diffusivity, MD; radial diffusivity, RD; axial diffusivity, AxD). Following data preprocessing, 114 participants remained for further analyses in which they completed the two follow-up sessions (with a range of 1-2 years) containing a series of neuropsychology instruments and computerized cognitive control tasks. The results show that many significant correlations between age and cognitive control functions originally shown on cross-sectional data no longer exist on the longitudinal data. The current longitudinal data show that MD, RD, and AxD (especially in the association fibers of anterior thalamic radiation) are more strongly correlated to follow-up aging processes, suggesting that axonal/myelin damage is a more robust phenomenon for observing intra-individual aging processes. Moreover, processing speed appears to be the most prominent cognitive function to reflect DTI-related age (cross-sectional) and aging (longitudinal) effects. Finally, converging the results from regression analyses and mediation models, MD, RD, and AxD appear to be the representative DTI measures to reveal age-related changes in processing speed. To conclude, the current results provide new insights to which indicator of WM integrity and which type of cognitive changes are most representative (i.e., potentially to be neuroimaging biomarkers) to reflect intra-individual cognitive aging processes.
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Affiliation(s)
- Shulan Hsieh
- Cognitive Electrophysiology Laboratory: Control, Aging, Sleep, and Emotion, Department of Psychology, National Cheng Kung University, Tainan, Taiwan
- Institute of Allied Health Sciences, National Cheng Kung University, Tainan, Taiwan
- Department of Public Health, National Cheng Kung University, Tainan, Taiwan
| | - Meng-Heng Yang
- Cognitive Electrophysiology Laboratory: Control, Aging, Sleep, and Emotion, Department of Psychology, National Cheng Kung University, Tainan, Taiwan
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14
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Troutman SBW, Madden DJ, Diaz MT. Cerebral White Matter Mediation of Age-Related Differences in Picture Naming Across Adulthood. NEUROBIOLOGY OF LANGUAGE (CAMBRIDGE, MASS.) 2022; 3:272-286. [PMID: 35685085 PMCID: PMC9169883 DOI: 10.1162/nol_a_00065] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 01/02/2022] [Indexed: 06/15/2023]
Abstract
As people age, one of the most common complaints is difficulty with word retrieval. A wealth of behavioral research confirms such age-related language production deficits, yet the structural neural differences that relate to age-related language production deficits remains an open area of exploration. Therefore, the present study used a large sample of healthy adults across adulthood to investigate how age-related white matter differences in three key left-hemisphere language tracts may contribute to age-related differences in language ability. Specifically, we used diffusion tensor imaging to measure fractional anisotropy (FA) and radial diffusivity (RD) which are indicators of white matter structure. We then used a series of path models to test whether white matter from the superior longitudinal fasciculus (SLF), the inferior longitudinal fasciculus, and the frontal aslant tract (FAT) mediated age-related differences in one form of language production, picture naming. We found that FA, as well as RD from the SLF and FAT mediated the relation between age and picture naming performance, whereas a control tract (corticospinal) was not a mediator. Moreover, differences between mediation of picture naming and a control naming condition suggest that left SLF has a greater role in higher-order aspects of naming, such as semantic and lexical selection whereas left FAT is more sensitive to sensorimotor aspects of fluency or speech motor planning. These results suggest that dorsal white matter contributes to age-related differences in generating speech and may be particularly important in supporting word retrieval across adulthood.
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Affiliation(s)
- Sara B. W. Troutman
- Department of Psychology, Pennsylvania State University, University Park, PA, USA
| | - David J. Madden
- Brain Imaging and Analysis Center & Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA
- Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
| | - Michele T. Diaz
- Department of Psychology, Pennsylvania State University, University Park, PA, USA
- Social, Life, & Engineering Sciences Imaging Center, Pennsylvania State University, University Park, PA, USA
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15
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Schulz M, Mayer C, Schlemm E, Frey BM, Malherbe C, Petersen M, Gallinat J, Kühn S, Fiehler J, Hanning U, Twerenbold R, Gerloff C, Cheng B, Thomalla G. Association of Age and Structural Brain Changes With Functional Connectivity and Executive Function in a Middle-Aged to Older Population-Based Cohort. Front Aging Neurosci 2022; 14:782738. [PMID: 35283749 PMCID: PMC8916110 DOI: 10.3389/fnagi.2022.782738] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 01/06/2022] [Indexed: 01/02/2023] Open
Abstract
Aging is accompanied by structural brain changes that are thought to underlie cognitive decline and dementia. Yet little is known regarding the association between increasing age, structural brain damage, and alterations of functional brain connectivity. The aim of this study was to evaluate whether cortical thickness and white matter damage as markers of age-related structural brain changes are associated with alterations in functional connectivity in non-demented healthy middle-aged to older adults. Therefore, we reconstructed functional connectomes from resting-state functional magnetic resonance imaging (MRI) (rsfMRI) data of 976 subjects from the Hamburg City Health Study, a prospective population-based study including participants aged 45-74 years from the metropolitan region Hamburg, Germany. We performed multiple linear regressions to examine the association of age, cortical thickness, and white matter damage quantified by the peak width of skeletonized mean diffusivity (PSMD) from diffusion tensor imaging on whole-brain network connectivity and four predefined resting state networks (default mode, dorsal, salience, and control network). In a second step, we extracted subnetworks with age-related decreased functional connectivity from these networks and conducted a mediation analysis to test whether the effect of age on these networks is mediated by decreased cortical thickness or PSMD. We observed an independent association of higher age with decreased functional connectivity, while there was no significant association of functional connectivity with cortical thickness or PSMD. Mediation analysis identified cortical thickness as a partial mediator between age and default subnetwork connectivity and functional connectivity within the default subnetwork as a partial mediator between age and executive cognitive function. These results indicate that, on a global scale, functional connectivity is not determined by structural damage in healthy middle-aged to older adults. There is a weak association of higher age with decreased functional connectivity which, for specific subnetworks, appears to be mediated by cortical thickness.
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Affiliation(s)
- Maximilian Schulz
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Carola Mayer
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Eckhard Schlemm
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Benedikt M. Frey
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Caroline Malherbe
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Institute of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Marvin Petersen
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jürgen Gallinat
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Simone Kühn
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jens Fiehler
- Department of Neuroradiological Diagnostics and Intervention, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Uta Hanning
- Department of Neuroradiological Diagnostics and Intervention, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Raphael Twerenbold
- Department of Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- University Center of Cardiovascular Science, Department of Cardiology, University Heart and Vascular Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christian Gerloff
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Bastian Cheng
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Götz Thomalla
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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16
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Howard CM, Jain S, Cook AD, Packard LE, Mullin HA, Chen N, Liu C, Song AW, Madden DJ. Cortical iron mediates age-related decline in fluid cognition. Hum Brain Mapp 2022; 43:1047-1060. [PMID: 34854172 PMCID: PMC8764476 DOI: 10.1002/hbm.25706] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Revised: 10/20/2021] [Accepted: 10/21/2021] [Indexed: 01/19/2023] Open
Abstract
Brain iron dyshomeostasis disrupts various critical cellular functions, and age-related iron accumulation may contribute to deficient neurotransmission and cell death. While recent studies have linked excessive brain iron to cognitive function in the context of neurodegenerative disease, little is known regarding the role of brain iron accumulation in cognitive aging in healthy adults. Further, previous studies have focused primarily on deep gray matter regions, where the level of iron deposition is highest. However, recent evidence suggests that cortical iron may also contribute to cognitive deficit and neurodegenerative disease. Here, we used quantitative susceptibility mapping (QSM) to measure brain iron in 67 healthy participants 18-78 years of age. Speed-dependent (fluid) cognition was assessed from a battery of 12 psychometric and computer-based tests. From voxelwise QSM analyses, we found that QSM susceptibility values were negatively associated with fluid cognition in the right inferior temporal gyrus, bilateral putamen, posterior cingulate gyrus, motor, and premotor cortices. Mediation analysis indicated that susceptibility in the right inferior temporal gyrus was a significant mediator of the relation between age and fluid cognition, and similar effects were evident for the left inferior temporal gyrus at a lower statistical threshold. Additionally, age and right inferior temporal gyrus susceptibility interacted to predict fluid cognition, such that brain iron was negatively associated with a cognitive decline for adults over 45 years of age. These findings suggest that iron may have a mediating role in cognitive decline and may be an early biomarker of neurodegenerative disease.
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Affiliation(s)
- Cortney M. Howard
- Center for Cognitive NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Shivangi Jain
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
- Present address:
Department of Psychological and Brain SciencesUniversity of IowaIowa CityIowaUSA
| | - Angela D. Cook
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Lauren E. Packard
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Hollie A. Mullin
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
| | - Nan‐kuei Chen
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
- Present address:
Department of Biomedical EngineeringUniversity of ArizonaTucsonArizonaUSA
| | - Chunlei Liu
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
- Present address:
Department of Electrical Engineering and Computer SciencesUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - Allen W. Song
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
| | - David J. Madden
- Center for Cognitive NeuroscienceDuke UniversityDurhamNorth CarolinaUSA
- Brain Imaging and Analysis CenterDuke University Medical CenterDurhamNorth CarolinaUSA
- Department of Psychiatry and Behavioral SciencesDuke University Medical CenterDurhamNorth CarolinaUSA
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17
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Elhassanien MEM, El-Heneedy YAE, Ramadan KM, Kotait MA, Elkholy A, Elhamrawy MY, Bahnasy WS. Gait and balance impairments in patients with subcortical vascular cognitive impairment. THE EGYPTIAN JOURNAL OF NEUROLOGY, PSYCHIATRY AND NEUROSURGERY 2021. [DOI: 10.1186/s41983-021-00293-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Subcortical vascular cognitive impairment (SVCI) is a subtype of vascular cognitive impairment associated with extensive cerebral small vessel diseases (CSVDs) imaging biomarkers. The objectives of this work were to study the existence and patterns of gait and balance impairments in patients with SVCI due to CSVDs.
Methods
The study was conducted on 28 newly diagnosed SVCI patients and 22 healthy control subjects (HCS) submitted to the advanced activity of daily living scale (AADLs), Berg balance test (BBT), Montreal Cognitive Assessment Scale (MoCA), computerized dynamic posturography (CDP), vision-based 3-D skeletal data gait analysis, and brain MRI volumetric assessment.
Results
SVCI patients showed a significant decrease in AADLs as well as total cerebral white matter volume, total cerebral cortical volume, and mean cortical thickness which were proportional to the degree of cognitive impairment as measured by the MoCA score. Regarding CDP analysis, patients with SVCI revealed prolongation of cancelation time and spectral power for mid- and high frequencies in dynamic positions. In respect to gait analysis, there were significant decreases in mean stride length and mean cadence as well as increases in mean step width and left to right step length difference in the SVCI group compared to HCS while doing a single task. These variables get highly significant during the dual-task performance with a p value < 0.001 for each one.
Conclusion
Patients with SVCI suffer from gait and balance impairments that are proportional to the severity of their cognitive decline and greatly impair their ADLs.
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18
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Kumral D, Cesnaite E, Beyer F, Hofmann SM, Hensch T, Sander C, Hegerl U, Haufe S, Villringer A, Witte AV, Nikulin VV. Relationship between regional white matter hyperintensities and alpha oscillations in older adults. Neurobiol Aging 2021; 112:1-11. [PMID: 35007997 DOI: 10.1016/j.neurobiolaging.2021.10.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 09/22/2021] [Accepted: 10/12/2021] [Indexed: 11/17/2022]
Abstract
Aging is associated with increased white matter hyperintensities (WMHs) and with alterations of alpha oscillations (7-13 Hz). However, a crucial question remains, whether changes in alpha oscillations relate to aging per se or whether this relationship is mediated by age-related neuropathology like WMHs. Using a large cohort of cognitively healthy older adults (N = 907, 60-80 years), we assessed relative alpha power, alpha peak frequency, and long-range temporal correlations from resting-state EEG. We further associated these parameters with voxel-wise WMHs from 3T MRI. We found that a higher prevalence of WMHs in the superior and posterior corona radiata as well as in the thalamic radiation was related to elevated alpha power, with the strongest association in the bilateral occipital cortex. In contrast, we observed no significant relation of the WMHs probability with alpha peak frequency and long-range temporal correlations. Finally, higher age was associated with elevated alpha power via total WMH volume. We suggest that an elevated alpha power is a consequence of WMHs affecting a spatial organization of alpha sources.
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Affiliation(s)
- Deniz Kumral
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Institute of Psychology, Neuropsychology, University of Freiburg, Freiburg im Breisgau, Germany; Clinical Psychology and Psychotherapy Unit, Institute of Psychology, University of Freiburg, Freiburg im Breisgau, Germany.
| | - Elena Cesnaite
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Frauke Beyer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; CRC Obesity Mechanisms, Subproject A1, University of Leipzig, Leipzig, Germany
| | - Simon M Hofmann
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Tilman Hensch
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany; LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany; Department of Psychology, IU International University of Applied Sciences, Erfurt, Germany
| | - Christian Sander
- Department of Psychiatry and Psychotherapy, University of Leipzig Medical Center, Leipzig, Germany; LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Ulrich Hegerl
- Department of Psychiatry, Psychosomatics and Psychotherapy, Goethe University Frankfurt, Frankfurt, Germany
| | - Stefan Haufe
- Berlin Center for Advanced Neuroimaging, Charité - Universitätsmedizin Berlin, Berlin, Germany; Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Clinic for Cognitive Neurology, University Medical Center Leipzig, Germany
| | - A Veronica Witte
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; CRC Obesity Mechanisms, Subproject A1, University of Leipzig, Leipzig, Germany; Clinic for Cognitive Neurology, University Medical Center Leipzig, Germany
| | - Vadim V Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany; Centre for Cognition and Decision making, Institute for Cognitive Neuroscience, HSE University, Moscow, Russia; Neurophysics Group, Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
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19
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Hoagey DA, Lazarus LTT, Rodrigue KM, Kennedy KM. The effect of vascular health factors on white matter microstructure mediates age-related differences in executive function performance. Cortex 2021; 141:403-420. [PMID: 34130048 PMCID: PMC8319097 DOI: 10.1016/j.cortex.2021.04.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 12/11/2020] [Accepted: 04/08/2021] [Indexed: 01/03/2023]
Abstract
Even within healthy aging, vascular risk factors can detrimentally influence cognition, with executive functions (EF) particularly vulnerable. Fronto-parietal white matter (WM) connectivity in part, supports EF and may be particularly sensitive to vascular risk. Here, we utilized structural equation modeling in 184 healthy adults (aged 20-94 years of age) to test the hypotheses that: 1) fronto-parietal WM microstructure mediates age effects on EF; 2) higher blood pressure (BP) and white matter hyperintensity (WMH) burden influences this association. All participants underwent comprehensive cognitive and neuropsychological testing including tests of processing speed, executive function (with a focus on tasks that require switching and inhibition) and completed an MRI scanning session that included FLAIR imaging for semi-automated quantification of white matter hyperintensity burden and diffusion-weighted imaging for tractography. Structural equation models were specified with age (as a continuous variable) and blood pressure predicting within-tract WMH burden and fractional anisotropy predicting executive function and processing speed. Results indicated that fronto-parietal white matter of the genu of the corpus collosum, superior longitudinal fasciculus, and the inferior frontal occipital fasciculus (but not cortico-spinal tract) mediated the association between age and EF. Additionally, increased systolic blood pressure and white matter hyperintensity burden within these white matter tracts contribute to worsening white matter health and are important factors underlying age-brain-behavior associations. These findings suggest that aging brings about increases in both BP and WMH burden, which may be involved in the degradation of white matter connectivity and in turn, negatively impact executive functions as we age.
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Affiliation(s)
- David A Hoagey
- The University of Texas at Dallas, School of Behavioral and Brain Sciences, Center for Vital Longevity, Dallas, TX, USA
| | - Linh T T Lazarus
- Department of Psychology, Michigan State University, East Lansing, MI, USA
| | - Karen M Rodrigue
- The University of Texas at Dallas, School of Behavioral and Brain Sciences, Center for Vital Longevity, Dallas, TX, USA
| | - Kristen M Kennedy
- The University of Texas at Dallas, School of Behavioral and Brain Sciences, Center for Vital Longevity, Dallas, TX, USA.
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Courtney SM, Hinault T. When the time is right: Temporal dynamics of brain activity in healthy aging and dementia. Prog Neurobiol 2021; 203:102076. [PMID: 34015374 DOI: 10.1016/j.pneurobio.2021.102076] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 05/08/2021] [Accepted: 05/14/2021] [Indexed: 10/21/2022]
Abstract
Brain activity and communications are complex phenomena that dynamically unfold over time. However, in contrast with the large number of studies reporting neuroanatomical differences in activation relative to young adults, changes of temporal dynamics of neural activity during normal and pathological aging have been grossly understudied and are still poorly known. Here, we synthesize the current state of knowledge from MEG and EEG studies that aimed at specifying the effects of healthy and pathological aging on local and network dynamics, and discuss the clinical and theoretical implications of these findings. We argue that considering the temporal dynamics of brain activations and networks could provide a better understanding of changes associated with healthy aging, and the progression of neurodegenerative disease. Recent research has also begun to shed light on the association of these dynamics with other imaging modalities and with individual differences in cognitive performance. These insights hold great potential for driving new theoretical frameworks and development of biomarkers to aid in identifying and treating age-related cognitive changes.
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Affiliation(s)
- S M Courtney
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, 21218, USA; F.M. Kirby Research Center, Kennedy Krieger Institute, MD 21205, USA; Department of Neuroscience, Johns Hopkins University, MD 21205, USA
| | - T Hinault
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, 21218, USA; U1077 INSERM-EPHE-UNICAEN, Caen, France.
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21
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Schulz M, Malherbe C, Cheng B, Thomalla G, Schlemm E. Functional connectivity changes in cerebral small vessel disease - a systematic review of the resting-state MRI literature. BMC Med 2021; 19:103. [PMID: 33947394 PMCID: PMC8097883 DOI: 10.1186/s12916-021-01962-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 03/17/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Cerebral small vessel disease (CSVD) is a common neurological disease present in the ageing population that is associated with an increased risk of dementia and stroke. Damage to white matter tracts compromises the substrate for interneuronal connectivity. Analysing resting-state functional magnetic resonance imaging (fMRI) can reveal dysfunctional patterns of brain connectivity and contribute to explaining the pathophysiology of clinical phenotypes in CSVD. MATERIALS AND METHODS This systematic review provides an overview of methods and results of recent resting-state functional MRI studies in patients with CSVD. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) protocol, a systematic search of the literature was performed. RESULTS Of 493 studies that were screened, 44 reports were identified that investigated resting-state fMRI connectivity in the context of cerebral small vessel disease. The risk of bias and heterogeneity of results were moderate to high. Patterns associated with CSVD included disturbed connectivity within and between intrinsic brain networks, in particular the default mode, dorsal attention, frontoparietal control, and salience networks; decoupling of neuronal activity along an anterior-posterior axis; and increases in functional connectivity in the early stage of the disease. CONCLUSION The recent literature provides further evidence for a functional disconnection model of cognitive impairment in CSVD. We suggest that the salience network might play a hitherto underappreciated role in this model. Low quality of evidence and the lack of preregistered multi-centre studies remain challenges to be overcome in the future.
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Affiliation(s)
- Maximilian Schulz
- Department of Neurology, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | - Caroline Malherbe
- Department of Neurology, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
- Department of Computational Neuroscience, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | - Bastian Cheng
- Department of Neurology, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | - Götz Thomalla
- Department of Neurology, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | - Eckhard Schlemm
- Department of Neurology, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany.
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22
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Coelho A, Fernandes HM, Magalhães R, Moreira PS, Marques P, Soares JM, Amorim L, Portugal‐Nunes C, Castanho T, Santos NC, Sousa N. Reorganization of brain structural networks in aging: A longitudinal study. J Neurosci Res 2021; 99:1354-1376. [PMID: 33527512 PMCID: PMC8248023 DOI: 10.1002/jnr.24795] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 12/31/2020] [Indexed: 12/12/2022]
Abstract
Normal aging is characterized by structural and functional changes in the brain contributing to cognitive decline. Structural connectivity (SC) describes the anatomical backbone linking distinct functional subunits of the brain and disruption of this communication is thought to be one of the potential contributors for the age-related deterioration observed in cognition. Several studies already explored brain network's reorganization during aging, but most focused on average connectivity of the whole-brain or in specific networks, such as the resting-state networks. Here, we aimed to characterize longitudinal changes of white matter (WM) structural brain networks, through the identification of sub-networks with significantly altered connectivity along time. Then, we tested associations between longitudinal changes in network connectivity and cognition. We also assessed longitudinal changes in topological properties of the networks. For this, older adults were evaluated at two timepoints, with a mean interval time of 52.8 months (SD = 7.24). WM structural networks were derived from diffusion magnetic resonance imaging, and cognitive status from neurocognitive testing. Our results show age-related changes in brain SC, characterized by both decreases and increases in connectivity weight. Interestingly, decreases occur in intra-hemispheric connections formed mainly by association fibers, while increases occur mostly in inter-hemispheric connections and involve association, commissural, and projection fibers, supporting the last-in-first-out hypothesis. Regarding topology, two hubs were lost, alongside with a decrease in connector-hub inter-modular connectivity, reflecting reduced integration. Simultaneously, there was an increase in the number of provincial hubs, suggesting increased segregation. Overall, these results confirm that aging triggers a reorganization of the brain structural network.
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Affiliation(s)
- Ana Coelho
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
- ICVS/3B’s, PT Government Associate LaboratoryBraga/GuimarãesPortugal
- Clinical Academic Center – BragaBragaPortugal
| | - Henrique M. Fernandes
- Center for Music in the Brain (MIB)Aarhus UniversityAarhusDenmark
- Department of PsychiatryUniversity of OxfordOxfordUK
| | - Ricardo Magalhães
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
- ICVS/3B’s, PT Government Associate LaboratoryBraga/GuimarãesPortugal
- Clinical Academic Center – BragaBragaPortugal
| | - Pedro S. Moreira
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
- ICVS/3B’s, PT Government Associate LaboratoryBraga/GuimarãesPortugal
- Clinical Academic Center – BragaBragaPortugal
| | - Paulo Marques
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
- ICVS/3B’s, PT Government Associate LaboratoryBraga/GuimarãesPortugal
- Clinical Academic Center – BragaBragaPortugal
| | - José M. Soares
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
- ICVS/3B’s, PT Government Associate LaboratoryBraga/GuimarãesPortugal
- Clinical Academic Center – BragaBragaPortugal
| | - Liliana Amorim
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
- ICVS/3B’s, PT Government Associate LaboratoryBraga/GuimarãesPortugal
- Clinical Academic Center – BragaBragaPortugal
| | - Carlos Portugal‐Nunes
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
- ICVS/3B’s, PT Government Associate LaboratoryBraga/GuimarãesPortugal
- Clinical Academic Center – BragaBragaPortugal
| | - Teresa Castanho
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
- ICVS/3B’s, PT Government Associate LaboratoryBraga/GuimarãesPortugal
- Clinical Academic Center – BragaBragaPortugal
| | - Nadine Correia Santos
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
- ICVS/3B’s, PT Government Associate LaboratoryBraga/GuimarãesPortugal
- Clinical Academic Center – BragaBragaPortugal
| | - Nuno Sousa
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
- ICVS/3B’s, PT Government Associate LaboratoryBraga/GuimarãesPortugal
- Clinical Academic Center – BragaBragaPortugal
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23
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Hinault T, Mijalkov M, Pereira JB, Volpe G, Bakke A, Courtney SM. Age-related differences in network structure and dynamic synchrony of cognitive control. Neuroimage 2021; 236:118070. [PMID: 33887473 DOI: 10.1016/j.neuroimage.2021.118070] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 04/09/2021] [Accepted: 04/10/2021] [Indexed: 12/18/2022] Open
Abstract
Cognitive trajectories vary greatly across older individuals, and the neural mechanisms underlying these differences remain poorly understood. Here, we investigate the cognitive variability in older adults by linking the influence of white matter microstructure on the task-related organization of fast and effective communications between brain regions. Using diffusion tensor imaging and electroencephalography, we show that individual differences in white matter network organization are associated with network clustering and efficiency in the alpha and high-gamma bands, and that functional network dynamics partly explain individual differences in cognitive control performance in older adults. We show that older individuals with high versus low structural network clustering differ in task-related network dynamics and cognitive performance. These findings were corroborated by investigating magnetoencephalography networks in an independent dataset. This multimodal (fMRI and biological markers) brain connectivity framework of individual differences provides a holistic account of how differences in white matter microstructure underlie age-related variability in dynamic network organization and cognitive performance.
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Affiliation(s)
- T Hinault
- U1077 Inserm-Ephe-unicaen, Caen 14032, France; Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD 21218, United States.
| | - M Mijalkov
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm 17177, Sweden
| | - J B Pereira
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm 17177, Sweden; Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmo 47700, Sweden
| | - Giovanni Volpe
- Department of Physics, Goteborg University, Goteborg 41296, Sweden
| | - A Bakke
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21287, United States; F.M. Kirby Research Center, Kennedy Krieger Institute, Baltimore, MD 21287, United States
| | - S M Courtney
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD 21218, United States; F.M. Kirby Research Center, Kennedy Krieger Institute, Baltimore, MD 21287, United States; Department of Neuroscience, Johns Hopkins University, MD 21287, United States
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24
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Coelho A, Fernandes HM, Magalhães R, Moreira PS, Marques P, Soares JM, Amorim L, Portugal-Nunes C, Castanho T, Santos NC, Sousa N. Signatures of white-matter microstructure degradation during aging and its association with cognitive status. Sci Rep 2021; 11:4517. [PMID: 33633204 PMCID: PMC7907273 DOI: 10.1038/s41598-021-83983-7] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Accepted: 02/01/2021] [Indexed: 11/09/2022] Open
Abstract
Previous studies have shown an association between cognitive decline and white matter integrity in aging. This led to the formulation of a "disconnection hypothesis" in the aging-brain, which states that the disruption in cortical network communication may explain the cognitive decline during aging. Although some longitudinal studies have already investigated the changes occurring in white matter microstructure, most focused on specific white matter tracts. Our study aims to characterize the longitudinal whole-brain signatures of white matter microstructural change during aging. Furthermore, we assessed the relationship between distinct longitudinal alterations in white matter integrity and cognition. White matter microstructural properties were estimated from diffusion magnetic resonance imaging, and cognitive status characterized from extensive neurocognitive testing. The same individuals were evaluated at two timepoints, with a mean interval time of 52.8 months (SD = 7.24) between first and last assessment. Our results show that age is associated with a decline in cognitive performance and a degradation in white matter integrity. Additionally, significant associations were found between diffusion measures and different cognitive dimensions (memory, executive function and general cognition). Overall, these results suggest that age-related cognitive decline is related to white matter alterations, and thus give support to the "disconnected hypothesis" of the aging brain.
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Affiliation(s)
- Ana Coelho
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Campus Gualtar, 4710-057, Braga, Portugal
- ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal
- Clinical Academic Center-Braga, 4710-057, Braga, Portugal
| | - Henrique M Fernandes
- Center for Music in the Brain (MIB), Aarhus University, Aarhus, Denmark
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Ricardo Magalhães
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Campus Gualtar, 4710-057, Braga, Portugal
- ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal
- Clinical Academic Center-Braga, 4710-057, Braga, Portugal
| | - Pedro Silva Moreira
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Campus Gualtar, 4710-057, Braga, Portugal
- ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal
- Clinical Academic Center-Braga, 4710-057, Braga, Portugal
| | - Paulo Marques
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Campus Gualtar, 4710-057, Braga, Portugal
- ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal
- Clinical Academic Center-Braga, 4710-057, Braga, Portugal
| | - José M Soares
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Campus Gualtar, 4710-057, Braga, Portugal
- ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal
- Clinical Academic Center-Braga, 4710-057, Braga, Portugal
| | - Liliana Amorim
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Campus Gualtar, 4710-057, Braga, Portugal
- ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal
- Clinical Academic Center-Braga, 4710-057, Braga, Portugal
| | - Carlos Portugal-Nunes
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Campus Gualtar, 4710-057, Braga, Portugal
- ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal
- Clinical Academic Center-Braga, 4710-057, Braga, Portugal
| | - Teresa Castanho
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Campus Gualtar, 4710-057, Braga, Portugal
- ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal
- Clinical Academic Center-Braga, 4710-057, Braga, Portugal
| | - Nadine Correia Santos
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Campus Gualtar, 4710-057, Braga, Portugal
- ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal
- Clinical Academic Center-Braga, 4710-057, Braga, Portugal
| | - Nuno Sousa
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Campus Gualtar, 4710-057, Braga, Portugal.
- ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal.
- Clinical Academic Center-Braga, 4710-057, Braga, Portugal.
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25
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Eldin AESAMT, Bahnasy WS, Dabees NL, Fayed HAER. Cognitive and balance impairments in people with incidental white matter hyperintensities. THE EGYPTIAN JOURNAL OF NEUROLOGY, PSYCHIATRY AND NEUROSURGERY 2020. [DOI: 10.1186/s41983-020-00228-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
White matter hyperintensities (WMHs) is the most frequent type of cerebral small vessel diseases and a common incidental finding in MRI films of the geriatric population. The objectives of this work were to study the existence of occult cognitive and balance impairments in subjects with accidentally discovered WMHs.
Methods
The study was conducted on 44 subjects with accidentally discovered WMHs and 24 non-WMHs subjects submitted to the advanced activity of daily living scale (AADLs), a neurocognitive battery assessing different cognitive domains, Berg balance test (BBT), computerized dynamic posturography (CDP), and brain MRI diffusion tensor tractography (DTT).
Results
WMHs subjects showed a significant decrease in AADLs as well as visual and vestibular ratios of CDP. Regarding the neurocognitive battery, there were significant decreases in MoCA as well as arithmetic test and block design of Wechsler adult intelligence scale-IV in WMHs compared to non-WMHs subjects’ groups (p value < 0.001). Concerning Wisconsin Card Sorting subtests, each preservative response, preservative errors, non-preservative errors and trials to complete the 1st category showed a highly significant increase in WMHs compared to non-WMHs subjects (p values < 0.001). DTT showed a substantial reduction in fractional anisotropy (FA) of each corticospinal tract, thalamocortical connectivity, and arcuate fasciculi.
Conclusion
Subjects with WMHs have lower cognitive performance and subtle balance impairment which greatly impair their ADLs.
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26
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Madden DJ, Jain S, Monge ZA, Cook AD, Lee A, Huang H, Howard CM, Cohen JR. Influence of structural and functional brain connectivity on age-related differences in fluid cognition. Neurobiol Aging 2020; 96:205-222. [PMID: 33038808 PMCID: PMC7722190 DOI: 10.1016/j.neurobiolaging.2020.09.010] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2020] [Revised: 08/08/2020] [Accepted: 09/05/2020] [Indexed: 01/01/2023]
Abstract
We used graph theoretical measures to investigate the hypothesis that structural brain connectivity constrains the influence of functional connectivity on the relation between age and fluid cognition. Across 143 healthy, community-dwelling adults 19-79 years of age, we estimated structural network properties from diffusion-weighted imaging and functional network properties from resting-state functional magnetic resonance imaging. We confirmed previous reports of age-related decline in the strength and efficiency of structural networks, as well as in the connectivity strength within and between structural network modules. Functional networks, in contrast, exhibited age-related decline only in system segregation, a measure of the distinctiveness among network modules. Aging was associated with decline in a composite measure of fluid cognition, particularly tests of executive function. Functional system segregation was a significant mediator of age-related decline in executive function. Structural network properties did not directly influence the age-related decline in functional system segregation. The raw correlational data underlying the graph theoretical measures indicated that structural connectivity exerts a limited constraint on age-related decline in functional connectivity.
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Affiliation(s)
- David J Madden
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA; Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA; Center for Cognitive Neuroscience, Duke University, Durham, NC, USA.
| | - Shivangi Jain
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA
| | - Zachary A Monge
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA; Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
| | - Angela D Cook
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA
| | - Alexander Lee
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA
| | - Hua Huang
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA
| | - Cortney M Howard
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA; Center for Cognitive Neuroscience, Duke University, Durham, NC, USA
| | - Jessica R Cohen
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA; Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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27
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Zuo X, Zhuang J, Chen NK, Cousins S, Cunha P, Lad EM, Madden DJ, Potter G, Whitson HE. Relationship between neural functional connectivity and memory performance in age-related macular degeneration. Neurobiol Aging 2020; 95:176-185. [PMID: 32829250 DOI: 10.1016/j.neurobiolaging.2020.07.020] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2018] [Revised: 07/21/2020] [Accepted: 07/22/2020] [Indexed: 10/23/2022]
Abstract
Age-related macular degeneration (AMD) has been linked to memory deficits, with no established neural mechanisms. We collected resting-state brain functional magnetic resonance imaging and standardized verbal recall tests from 42 older adults with AMD and 41 age-matched controls. We used seed-based whole brain analysis to quantify the strength of functional connectivity between hubs of the default mode network and a network of medial temporal regions relevant for memory. Our results indicated neither memory performance nor network connectivity differed by AMD status. However, the AMD participants exhibited stronger relationships than the controls between memory performance and connectivity from the memory network hub (left parahippocampal) to 2 other regions: the left temporal pole and the right superior/middle frontal gyri. Also, the connectivity between the medial prefrontal cortex and posterior cingulate cortex of default mode network correlated more strongly with memory performance in AMD compared to control. We concluded that stronger brain-behavior correlation in AMD may suggest a role for region-specific connectivity in supporting memory in the context of AMD.
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Affiliation(s)
- Xintong Zuo
- Department of Internal Medicine, University of Hawaii, Honolulu, HI, USA; Center for the Study of Aging and Human Development, Duke University Medical Center, Durham, NC, USA
| | - Jie Zhuang
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA
| | - Nan-Kuei Chen
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA
| | - Scott Cousins
- Department of Ophthalmology, Duke University Medical Center, Durham, NC, USA
| | - Priscila Cunha
- Center for the Study of Aging and Human Development, Duke University Medical Center, Durham, NC, USA; Duke University School of Medicine, Durham, NC, USA
| | - Eleonora M Lad
- Department of Ophthalmology, Duke University Medical Center, Durham, NC, USA
| | - David J Madden
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC, USA; Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA
| | - Guy Potter
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA
| | - Heather E Whitson
- Center for the Study of Aging and Human Development, Duke University Medical Center, Durham, NC, USA; Department of Ophthalmology, Duke University Medical Center, Durham, NC, USA; Department of Medicine (Geriatrics), Duke University Medical Center, Durham, NC, USA; Geriatrics Research Education & Clinical Center, Durham VA Medical Center, Durham, NC, USA.
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28
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Frontoparietal structural properties mediate adult life span differences in executive function. Sci Rep 2020; 10:9066. [PMID: 32494018 PMCID: PMC7271169 DOI: 10.1038/s41598-020-66083-w] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Accepted: 05/15/2020] [Indexed: 02/02/2023] Open
Abstract
Executive function (EF) refers to a set of cognitive functions that support goal-directed behaviors. Recent findings have suggested that the frontoparietal network (FPN) subserves neural processes that are related to EF. However, the FPN structural and functional network properties that mediate age-related differences in EF components remain unclear. To this end, we used three experimental tasks to test the component processes of EF based on Miyake and Friedman’s model: one common EF component process (incorporating inhibition, shifting, and updating) and two specific EF component processes (shifting and updating). We recruited 126 healthy participants (65 females; 20 to 78 years old) who underwent both structural and functional MRI scanning. We tested a mediation path model of three structural and functional properties of the FPN (i.e., gray matter volume, white matter fractional anisotropy, and intra/internetwork functional connectivity) as mediators of age-related differences in the three EF components. The results indicated that age-related common EF component differences are mediated by regional gray matter volume changes in both hemispheres of the frontal lobe, which suggests that structural changes in the frontal lobe may have an indirect influence on age-related general elements of EF. These findings suggest that the FPN mediates age-related differences in specific components of EF.
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29
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Garcia-Egan PM, Preston-Campbell RN, Salminen LE, Heaps-Woodruff JM, Balla L, Cabeen RP, Laidlaw DH, Conturo TE, Paul RH. Behavioral inhibition corresponds to white matter fiber bundle integrity in older adults. Brain Imaging Behav 2020; 13:1602-1611. [PMID: 31209835 DOI: 10.1007/s11682-019-00144-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Little is known about the contribution of white matter integrity to inhibitory cognitive control, particularly in healthy aging. The present study examines the correspondence between white matter fiber bundle length and behavioral inhibition in 37 community-dwelling older adults (aged 51-78 years). Participants underwent neuroimaging with 3 Tesla MRI, and completed a behavioral test of inhibition (i.e., Go/NoGo task). Quantitative tractography derived from diffusion tensor imaging (qtDTI) was used to measure white matter fiber bundle lengths (FBLs) in tracts known to innervate frontal brain regions, including the anterior corpus callosum (AntCC), the cingulate gyrus segment of the cingulum bundle (CING), uncinate fasciculus (UNC), and the superior longitudinal fasciculus (SLF). Performance on the Go/NoGo task was measured by the number of commission errors standardized to reaction time. Hierarchical regression models revealed that shorter FBLs in the CING (p < 0.05) and the bilateral UNC (p < 0.01) were associated with lower inhibitory performance after adjusting for multiple comparisons, supporting a disconnection model of response inhibition in older adults. Prospective longitudinal studies are needed to examine the evolution of inhibitory errors in older adult populations and potential for therapeutic intervention.
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Affiliation(s)
- Paola M Garcia-Egan
- Department of Psychological Sciences, University of Missouri, St. Louis, MO, 63121, USA
| | | | - Lauren E Salminen
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, University of Southern California, Marina del Rey, CA, 90292, USA
| | | | - Lila Balla
- Missouri Institute of Mental Health, St. Louis, MO, 63134, USA
| | - Ryan P Cabeen
- Laboratory of Neuro Imaging, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, LosAngeles, CA, 90033, USA
| | - David H Laidlaw
- Department of Computer Science, Brown University, Providence, RI, 02906, USA
| | - Thomas E Conturo
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Robert H Paul
- Department of Psychological Sciences, University of Missouri, St. Louis, MO, 63121, USA.
- Missouri Institute of Mental Health, St. Louis, MO, 63134, USA.
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30
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Li X, Wang Y, Wang W, Huang W, Chen K, Xu K, Zhang J, Chen Y, Li H, Wei D, Shu N, Zhang Z. Age-Related Decline in the Topological Efficiency of the Brain Structural Connectome and Cognitive Aging. Cereb Cortex 2020; 30:4651-4661. [PMID: 32219315 DOI: 10.1093/cercor/bhaa066] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Revised: 02/14/2020] [Accepted: 02/28/2020] [Indexed: 12/12/2022] Open
Abstract
Brain disconnection model has been proposed as a possible neural mechanism for cognitive aging. However, the relationship between structural connectivity degeneration and cognitive decline with normal aging remains unclear. In the present study, using diffusion MRI and tractography techniques, we report graph theory-based analyses of the brain structural connectome in a cross-sectional, community-based cohort of 633 cognitively healthy elderly individuals. Comprehensive neuropsychological assessment of the elderly subjects was performed. The association between age, brain structural connectome, and cognition across elderly individuals was examined. We found that the topological efficiency, modularity, and hub integration of the brain structural connectome exhibited a significant decline with normal aging, especially in the frontal, parietal, and superior temporal regions. Importantly, network efficiency was positively correlated with attention and executive function in elderly subjects and had a significant mediation effect on the age-related decline in these cognitive functions. Moreover, nodal efficiency of the brain structural connectome showed good performance for the prediction of attention and executive function in elderly individuals. Together, our findings revealed topological alterations of the brain structural connectome with normal aging, which provides possible structural substrates underlying cognitive aging and sensitive imaging markers for the individual prediction of cognitive functions in elderly subjects.
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Affiliation(s)
- Xin Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- BABRI Centre, Beijing Normal University, Beijing 100875, China
| | - Yezhou Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- BABRI Centre, Beijing Normal University, Beijing 100875, China
| | - Wenxiao Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- BABRI Centre, Beijing Normal University, Beijing 100875, China
| | - Weijie Huang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- BABRI Centre, Beijing Normal University, Beijing 100875, China
| | - Kewei Chen
- BABRI Centre, Beijing Normal University, Beijing 100875, China
- Banner Alzheimer's Institute, Phoenix, AZ 85006, USA
| | - Kai Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- BABRI Centre, Beijing Normal University, Beijing 100875, China
| | - Junying Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- BABRI Centre, Beijing Normal University, Beijing 100875, China
- Institute of Basic Research in Clinical Medicine, China Academy of Traditional Chinese Medicine, Beijing 10070, China
| | - Yaojing Chen
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- BABRI Centre, Beijing Normal University, Beijing 100875, China
| | - He Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- BABRI Centre, Beijing Normal University, Beijing 100875, China
- Institute of Basic Research in Clinical Medicine, China Academy of Traditional Chinese Medicine, Beijing 10070, China
| | - Dongfeng Wei
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- BABRI Centre, Beijing Normal University, Beijing 100875, China
- Institute of Basic Research in Clinical Medicine, China Academy of Traditional Chinese Medicine, Beijing 10070, China
| | - Ni Shu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- BABRI Centre, Beijing Normal University, Beijing 100875, China
| | - Zhanjun Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- BABRI Centre, Beijing Normal University, Beijing 100875, China
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31
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Shen KK, Welton T, Lyon M, McCorkindale AN, Sutherland GT, Burnham S, Fripp J, Martins R, Grieve SM. Structural core of the executive control network: A high angular resolution diffusion MRI study. Hum Brain Mapp 2019; 41:1226-1236. [PMID: 31765057 PMCID: PMC7267982 DOI: 10.1002/hbm.24870] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Revised: 10/27/2019] [Accepted: 11/05/2019] [Indexed: 12/28/2022] Open
Abstract
Executive function (EF) is a set of cognitive capabilities considered essential for successful daily living, and is negatively affected by ageing and neurodegenerative conditions. Underpinning EF performance are functional nodes in the executive control network (ECN), while the structural connectivity underlying this network is not well understood. In this paper, we evaluated the structural white matter tracts that interconnect the ECN and investigated their relationship to the EF performance. Using high‐angular resolution diffusion MRI data, we performed tractography analysis of structural connectivity in a cognitively normal cohort (n = 140), specifically targeting the connectivity between ECN nodes. Our data revealed the presence of a strongly‐connected “structural core” of the ECN comprising three components: interhemispheric frontal connections, a fronto‐parietal subnetwork and fronto‐striatal connections between right dorsolateral prefrontal cortex and right caudate. These pathways were strongly correlated with EF performance (p = .003). Post‐hoc analysis of subregions within the significant ECN connections showed that these effects were driven by a highly specific subset of interconnected cortical regions. The structural core subnetwork of the functional ECN may be an important feature crucial to a better future understanding of human cognition and behaviour.
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Affiliation(s)
- Kai-Kai Shen
- Australian eHealth Research Centre, CSIRO, Floreat, Western Australia, Australia.,Department of Biomedical Sciences, Macquarie University, Sydney, New South Wales, Australia.,Sydney Translational Imaging Laboratory, Heart Research Institute, Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia
| | - Thomas Welton
- Sydney Translational Imaging Laboratory, Heart Research Institute, Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia
| | - Matthew Lyon
- Sydney Translational Imaging Laboratory, Heart Research Institute, Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia
| | - Andrew N McCorkindale
- Sydney Translational Imaging Laboratory, Heart Research Institute, Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia
| | - Greg T Sutherland
- Faculty of Medicine and Health, Charles Perkins Centre and School of Medical Sciences, University of Sydney, Sydney, New South Wales, Australia
| | - Samantha Burnham
- Australian eHealth Research Centre, CSIRO, Floreat, Western Australia, Australia
| | - Jurgen Fripp
- Australian eHealth Research Centre, CSIRO, Floreat, Western Australia, Australia
| | - Ralph Martins
- Department of Biomedical Sciences, Macquarie University, Sydney, New South Wales, Australia
| | - Stuart M Grieve
- Sydney Translational Imaging Laboratory, Heart Research Institute, Charles Perkins Centre, University of Sydney, Sydney, New South Wales, Australia.,Department of Radiology, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia
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32
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Wang S, Jiaerken Y, Yu X, Shen Z, Luo X, Hong H, Sun J, Xu X, Zhang R, Zhou Y, Lou M, Huang P, Zhang M. Understanding the association between psychomotor processing speed and white matter hyperintensity: A comprehensive multi-modality MR imaging study. Hum Brain Mapp 2019; 41:605-616. [PMID: 31675160 PMCID: PMC7267958 DOI: 10.1002/hbm.24826] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Revised: 09/22/2019] [Accepted: 10/02/2019] [Indexed: 01/01/2023] Open
Abstract
Cognitive processing speed is crucial for human cognition and declines with aging. White matter hyperintensity (WMH), a common sign of WM vascular damage in the elderly, is closely related to slower psychomotor processing speed. In this study, we investigated the association between WMH and psychomotor speed changes through a comprehensive assessment of brain structural and functional features. Multi-modal MRIs were acquired from 60 elderly adults. Psychomotor processing speeds were assessed using the Trail Making Test Part A (TMT-A). Linear regression analyses were performed to assess the associations between TMT-A and brain features, including WMH volumes in five cerebral regions, diffusivity parameters in the major WM tracts, regional gray matter volume, and brain activities across the whole brain. Hierarchical regression analysis was used to demonstrate the contribution of each index to slower psychomotor processing speed. Linear regression analysis demonstrated that WMH volume in the occipital lobe and fractional anisotropy of the forceps major, an occipital association tract, were associated with TMT-A. Besides, resting-state brain activities in the visual cortex connected to the forceps major were associated with TMT-A. Hierarchical regression showed fractional anisotropy of the forceps major and regional brain activities were significant predictors of TMT-A. The occurrence of WMH, combined with the disruption of passing-through fiber integrity and altered functional activities in areas connected by this fiber, are associated with a decline of psychomotor processing speed. While the causal relationship of this WMH-Tract-Function-Behavior link requires further investigation, this study enhances our understanding of these complex mechanisms.
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Affiliation(s)
- Shuyue Wang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yeerfan Jiaerken
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xinfeng Yu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Zhujing Shen
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiao Luo
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Hui Hong
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Jianzhong Sun
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Ruiting Zhang
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Ying Zhou
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Min Lou
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
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Power MC, Su D, Wu A, Reid RI, Jack CR, Knopman DS, Coresh J, Huang J, Kantarci K, Sharrett AR, Gottesman RG, Griswold ME, Mosley TH. Association of white matter microstructural integrity with cognition and dementia. Neurobiol Aging 2019; 83:63-72. [PMID: 31585368 PMCID: PMC6914220 DOI: 10.1016/j.neurobiolaging.2019.08.021] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Revised: 08/07/2019] [Accepted: 08/21/2019] [Indexed: 10/26/2022]
Abstract
Late-life measures of white matter (WM) microstructural integrity may predict cognitive status, cognitive decline, and incident mild cognitive impairment (MCI) or dementia. We considered participants of the Atherosclerosis Risk in Communities study who underwent cognitive assessment and neuroimaging in 2011-2013 and were followed through 2016-2017 (n = 1775 for analyses of prevalent MCI and dementia, baseline cognitive performance, and longitudinal cognitive change and n = 889 for analyses of incident MCI, dementia, or death). Cross-sectionally, both overall WM fractional anisotropy and overall WM mean diffusivity were strongly associated with baseline cognitive performance and risk of prevalent MCI or dementia. Longitudinally, greater overall WM mean diffusivity was associated with accelerated cognitive decline, as well as incident MCI, incident dementia, and mortality, but WM fractional anisotropy was not robustly associated with cognitive change or incident cognitive impairment. Both cross-sectional and longitudinal associations were attenuated after additionally adjusting for likely downstream pathologic changes. Increased WM mean diffusivity may provide an early indication of dementia pathogenesis.
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Affiliation(s)
- Melinda C Power
- Department of Epidemiology and Biostatistics, Milken Institute School of Public Health, George Washington University, Washington, DC, USA.
| | - Dan Su
- Department of Data Science, JD Bower School of Population Health, University of Mississippi Medical Center, Jackson, MS, USA
| | - Aozhou Wu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Robert I Reid
- Department of Information Technology, Mayo Clinic, Rochester, MN, USA
| | | | | | - Joe Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Juebin Huang
- Department of Neurology, University of Mississippi Medical Center, Jackson, MS, USA
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - A Richey Sharrett
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Rebecca G Gottesman
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
| | - Mike E Griswold
- Department of Data Science, JD Bower School of Population Health, University of Mississippi Medical Center, Jackson, MS, USA
| | - Thomas H Mosley
- Department of Neurology, University of Mississippi Medical Center, Jackson, MS, USA; Department of Geriatrics, University of Mississippi Medical Center, Jackson, MS, USA
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34
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Sanfratello L, Houck JM, Calhoun VD. Dynamic Functional Network Connectivity in Schizophrenia with Magnetoencephalography and Functional Magnetic Resonance Imaging: Do Different Timescales Tell a Different Story? Brain Connect 2019; 9:251-262. [PMID: 30632385 DOI: 10.1089/brain.2018.0608] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
The importance of how brain networks function together to create brain states has become increasingly recognized. Therefore, an investigation of eyes-open resting-state dynamic functional network connectivity (dFNC) of healthy controls (HC) versus that of schizophrenia patients (SP) via both functional magnetic resonance imaging (fMRI) and a novel magnetoencephalography (MEG) pipeline was completed. The fMRI analysis used a spatial independent component analysis (ICA) to determine the networks on which the dFNC was based. The MEG analysis utilized a source space activity estimate (minimum norm estimate [MNE]/dynamic statistical parametric mapping [dSPM]) whose result was the input to a spatial ICA, on which the networks of the MEG dFNC were based. We found that dFNC measures reveal significant differences between HC and SP, which depended on the imaging modality. Consistent with previous findings, a dFNC analysis predicated on fMRI data revealed HC and SP remain in different overall brain states (defined by a k-means clustering of network correlations) for significantly different periods of time, with SP spending less time in a highly connected state. The MEG dFNC, in contrast, revealed group differences in more global statistics: SP changed between meta-states (k-means cluster states that are allowed to overlap in time) significantly more often and to states that were more different, relative to HC. MEG dFNC also revealed a highly connected state where a significant difference was observed in interindividual variability, with greater variability among SP. Overall, our results show that fMRI and MEG reveal between-group functional connectivity differences in distinct ways, highlighting the utility of using each of the modalities individually, or potentially a combination of modalities, to better inform our understanding of disorders such as schizophrenia.
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Affiliation(s)
| | - Jon M Houck
- 1 The Mind Research Network, Albuquerque, New Mexico.,2 Center on Alcoholism, Substance Abuse, and Addictions, University of New Mexico, Albuquerque, New Mexico
| | - Vince D Calhoun
- 1 The Mind Research Network, Albuquerque, New Mexico.,2 Center on Alcoholism, Substance Abuse, and Addictions, University of New Mexico, Albuquerque, New Mexico.,3 Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, New Mexico
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35
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Response-level processing during visual feature search: Effects of frontoparietal activation and adult age. Atten Percept Psychophys 2019; 82:330-349. [PMID: 31376024 PMCID: PMC6995405 DOI: 10.3758/s13414-019-01823-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Previous research suggests that feature search performance is relatively resistant to age-related decline. However, little is known regarding the neural mechanisms underlying the age-related constancy of feature search. In this experiment, we used a diffusion decision model of reaction time (RT), and event-related functional magnetic resonance imaging (fMRI) to investigate age-related differences in response-level processing during visual feature search. Participants were 80 healthy, right-handed, community-dwelling individuals, 19–79 years of age. Analyses of search performance indicated that targets accompanied by response-incompatible distractors were associated with a significant increase in the nondecision-time (t0) model parameter, possibly reflecting the additional time required for response execution. Nondecision time increased significantly with increasing age, but no age-related effects were evident in drift rate, cautiousness (boundary separation, a), or in the specific effects of response compatibility. Nondecision time was also associated with a pattern of activation and deactivation in frontoparietal regions. The relation of age to nondecision time was indirect, mediated by this pattern of frontoparietal activation and deactivation. Response-compatible and -incompatible trials were associated with specific patterns of activation in the medial and superior parietal cortex, and frontal eye field, but these activation effects did not mediate the relation between age and search performance. These findings suggest that, in the context of a highly efficient feature search task, the age-related influence of frontoparietal activation is operative at a relatively general level, which is common to the task conditions, rather than at the response level specifically.
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36
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Maghsudi H, Schütze M, Maudsley AA, Dadak M, Lanfermann H, Ding XQ. Age-related Brain Metabolic Changes up to Seventh Decade in Healthy Humans : Whole-brain Magnetic Resonance Spectroscopic Imaging Study. Clin Neuroradiol 2019; 30:581-589. [PMID: 31350597 DOI: 10.1007/s00062-019-00814-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Accepted: 07/03/2019] [Indexed: 12/28/2022]
Abstract
PURPOSE To study brain metabolic changes under normal aging and to collect reference data for the study of neurodegenerative diseases. METHODS A total of 55 healthy subjects aged 20-70 years (n ≥ 5 per age decade for each gender) underwent whole-brain magnetic resonance spectroscopic imaging at 3T after completing a DemTect test and the Beck depressions inventory II to exclude cognitive impairment and mental disorder. Regional concentrations of N-acetylaspartate (NAA), choline-containing compounds (Cho), total creatine (tCr), glutamine and glutamate (Glx), and myo-inositol (mI) were determined in 12 brain regions of interest (ROIs). The two-sided t‑test was used to estimate gender differences and linear regression analysis was carried out to estimate age dependence of brain regional metabolite contents. RESULTS Brain regional metabolite concentrations changed with age in the majority of selected brain regions. The NAA decreased in 8 ROIs with a rate varying from -4.9% to -1.9% per decade, reflecting a general reduction of brain neuronal function or volume and density in older age; Cho increased in 4 ROIs with a rate varying from 4.3% to 6.1%; tCr and mI increased in one ROI (4.2% and 8.2% per decade, respectively), whereas Glx decreased in one ROI (-5.1% per decade), indicating an inhomogeneous increase of cell membrane turnover (Cho) with altered energy metabolism (tCr) and glutamatergic neuronal activity (Glx) as well as function of glia cell (mI) in normal aging brain. CONCLUSION Healthy aging up to the seventh decade of life is associated with regional dependent alterations of brain metabolism. These results provide a reference database for future studies of patients.
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Affiliation(s)
- Helen Maghsudi
- Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany.
| | - Martin Schütze
- Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - Andrew A Maudsley
- Department of Radiology, University of Miami School of Medicine, Miami, FL, USA
| | - Mete Dadak
- Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - Heinrich Lanfermann
- Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - Xiao-Qi Ding
- Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
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37
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Hinault T, Larcher K, Bherer L, Courtney SM, Dagher A. Age-related differences in the structural and effective connectivity of cognitive control: a combined fMRI and DTI study of mental arithmetic. Neurobiol Aging 2019; 82:30-39. [PMID: 31377538 DOI: 10.1016/j.neurobiolaging.2019.06.013] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Revised: 06/06/2019] [Accepted: 06/30/2019] [Indexed: 11/19/2022]
Abstract
Cognitive changes with aging are highly variable across individuals. This study investigated whether cognitive control performance might depend on preservation of structural and effective connectivity in older individuals. Specifically, we tested inhibition following working memory (WM) updating and maintenance. We analyzed diffusion tensor imaging and functional magnetic resonance imaging data in thirty-four young adults and thirty-four older adults, who performed an arithmetic verification task during functional magnetic resonance imaging. Results revealed larger arithmetic interference in older adults relative to young adults after WM updating, whereas both groups showed similar interference after WM maintenance. In both groups, arithmetic interference was associated with larger activations and stronger effective connectivity among bilateral anterior cingulate, bilateral inferior frontal gyrus, and left angular gyrus, with larger activations of frontal regions in older adults than in younger adults. In older adults, preservation of frontoparietal structural microstructure, especially involving the inferior frontaloccipital fasciculus, was associated with reduced interference, and stronger task-related effective connectivity. These results highlight how both structural and functional changes in the cognitive control network contribute to individual variability in performance during aging.
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Affiliation(s)
- Thomas Hinault
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, USA; McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montréal, QC, Canada.
| | - Kevin Larcher
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Louis Bherer
- Departement de Médecine, Université de Montréal, Montréal, QC, Canada; Centre de recherche de l'institut de cardiologie de Montréal, Montréal, QC, Canada; Centre de recherche de l'institut universitaire de gériatrie de Montréal, Montréal, QC, Canada
| | - Susan M Courtney
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, USA; Department of Neuroscience, Johns Hopkins University, Baltimore, MD, USA; F.M. Kirby Research Center, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Alain Dagher
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montréal, QC, Canada
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38
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Sanfratello L, Houck J, Calhoun V. Relationship between MEG global dynamic functional network connectivity measures and symptoms in schizophrenia. Schizophr Res 2019; 209:129-134. [PMID: 31130399 PMCID: PMC6661190 DOI: 10.1016/j.schres.2019.05.007] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Revised: 02/22/2019] [Accepted: 05/05/2019] [Indexed: 01/14/2023]
Abstract
An investigation of differences in dynamic functional network connectivity (dFNC) of healthy controls (HC) versus that of schizophrenia patients (SP) was completed, using eyes-open resting state MEG data. The MEG analysis utilized a source-space activity estimate (MNE/dSPM) whose result was the input to a group spatial independent component analysis (ICA), on which the networks of our MEG dFNC analysis were based. We have previously reported that our MEG dFNC revealed that SP change between brain meta-states (repeating patterns of network correlations which are allowed to overlap in time) significantly more often and to states which are more different, relative to HC. Here, we extend our previous work to investigate the relationship between symptomology in SP and four meta-state metrics. We found a significant correlation between positive symptoms and the two meta-state metrics which showed significant differences between HC and SP. These two statistics quantified 1) how often individuals change state and 2) the total distance traveled within the state-space. We additionally found that a clustering of the meta-state metrics divides SP into groups which vary in symptomology. These results indicate specific relationships between symptomology and brain function for SP.
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Affiliation(s)
| | - J.M. Houck
- The Mind Research Network,The University of New Mexico
| | - V.D. Calhoun
- The Mind Research Network,The University of New Mexico
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Abstract
The global population is ageing at an accelerating speed. The ability to perform working memory tasks together with rapid processing becomes increasingly difficult with increases in age. With increasing national average life spans and a rise in the prevalence of age-related disease, it is pertinent to discuss the unique perspectives that can be gained from imaging the aged brain. Differences in structure, function, blood flow, and neurovascular coupling are present in both healthy aged brains and in diseased brains and have not yet been explored to their full depth in contemporary imaging studies. Imaging methods ranging from optical imaging to magnetic resonance imaging (MRI) to newer technologies such as photoacoustic tomography each offer unique advantages and challenges in imaging the aged brain. This paper will summarize first the importance and challenges of imaging the aged brain and then offer analysis of potential imaging modalities and their representative applications. The potential breakthroughs in brain imaging are also envisioned.
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Affiliation(s)
- Hannah Humayun
- Photoacoustic Imaging Laboratory, Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Junjie Yao
- Photoacoustic Imaging Laboratory, Department of Biomedical Engineering, Duke University, Durham, NC, USA
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40
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The many ages of man: diverse approaches to assessing ageing-related biological and psychological measures and their relationship to chronological age. Curr Opin Psychiatry 2019; 32:130-137. [PMID: 30461440 DOI: 10.1097/yco.0000000000000473] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
PURPOSE OF REVIEW Chronological age is a crude measure and may not be the best indicator of the ageing process. Establishing valid and reliable biomarkers to understand the true effect of ageing is of great interest. We provide an overview of biological and psychological characteristics that change with age and can potentially serve as markers of the ageing process, and discuss if an integration of these characteristics may more accurately measure the true age of a person. We also describe the clinicopathological continuum of these ageing-related changes. RECENT FINDINGS Ageing-related changes in the biological and psychological systems of the body have been studied to varying degrees and with differing emphases. Despite the development of ageing indices, there is no single indicator that can holistically estimate the ageing process. Differential ageing of bodily systems remains poorly understood, and valid methods have not been developed for composite markers of biological and psychological processes. SUMMARY The ageing process is complex and heterogeneous. Incorporating biological and psychological measures may improve accuracy in reflecting an individual's 'true age,' and elucidate why some people age successfully, whereas others show ageing-related decline and disease.
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Huang CC, Yang AC, Chou KH, Liu ME, Fang SC, Chen CC, Tsai SJ, Lin CP. Nonlinear pattern of the emergence of white matter hyperintensity in healthy Han Chinese: an adult lifespan study. Neurobiol Aging 2018; 67:99-107. [DOI: 10.1016/j.neurobiolaging.2018.03.012] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2017] [Revised: 02/25/2018] [Accepted: 03/10/2018] [Indexed: 12/24/2022]
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42
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Su YS, Chen JT, Tang YJ, Yuan SY, McCarrey AC, Goh JOS. Age-related differences in striatal, medial temporal, and frontal involvement during value-based decision processing. Neurobiol Aging 2018; 69:185-198. [PMID: 29909176 DOI: 10.1016/j.neurobiolaging.2018.05.019] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2017] [Revised: 05/12/2018] [Accepted: 05/14/2018] [Indexed: 11/26/2022]
Abstract
Appropriate neural representation of value and application of decision strategies are necessary to make optimal investment choices in real life. Normative human aging alters neural selectivity and control processing in brain regions implicated in value-based decision processing including striatal, medial temporal, and frontal areas. However, the specific neural mechanisms of how these age-related functional brain changes modulate value processing in older adults remain unclear. Here, young and older adults performed a lottery-choice functional magnetic resonance imaging experiment in which probabilities of winning different magnitudes of points constituted expected values of stakes. Increasing probability of winning modulated striatal responses in young adults, but modulated medial temporal and ventromedial prefrontal areas instead in older adults. Older adults additionally engaged higher responses in dorso-medio-lateral prefrontal cortices to more unfavorable stakes. Such extrastriatal involvement mediated age-related increase in risk-taking decisions. Furthermore, lower resting-state functional connectivity between lateral prefrontal and striatal areas also predicted lottery-choice task risk-taking that was mediated by higher functional connectivity between prefrontal and medial temporal areas during the task, with this mediation relationship being stronger in older than younger adults. Overall, we report evidence of a systemic neural mechanistic change in processing of probability in mixed-lottery values with age that increases risk-taking of unfavorable stakes in older adults. Moreover, individual differences in age-related effects on baseline frontostriatal communication may be a central determinant of such subsequent age differences in value-based decision neural processing and resulting behaviors.
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Affiliation(s)
- Yu-Shiang Su
- Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan; Taiwan International Graduate Program in Interdisciplinary Neuroscience, National Taiwan University and Academia Sinica, Taipei, Taiwan
| | - Jheng-Ting Chen
- Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Yong-Jheng Tang
- Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Shu-Yun Yuan
- Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Anna C McCarrey
- Department of Psychology, Idaho State University, Pocatello, ID, USA
| | - Joshua Oon Soo Goh
- Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan; Department of Psychology, National Taiwan University, Taipei, Taiwan; Neurobiology and Cognitive Science Center, National Taiwan University, Taipei, Taiwan; Center for Artificial Intelligence and Advanced Robotics, National Taiwan University, Taipei, Taiwan; Laboratory of Behavioral Neuroscience, Intramural Research Program, National Institute on Aging, Baltimore, MD, USA.
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43
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Nilsonne G, Tamm S, Schwarz J, Almeida R, Fischer H, Kecklund G, Lekander M, Fransson P, Åkerstedt T. Intrinsic brain connectivity after partial sleep deprivation in young and older adults: results from the Stockholm Sleepy Brain study. Sci Rep 2017; 7:9422. [PMID: 28842597 PMCID: PMC5573389 DOI: 10.1038/s41598-017-09744-7] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2016] [Accepted: 07/31/2017] [Indexed: 12/13/2022] Open
Abstract
Sleep deprivation has been reported to affect intrinsic brain connectivity, notably reducing connectivity in the default mode network. Studies to date have however shown inconsistent effects, in many cases lacked monitoring of wakefulness, and largely included young participants. We investigated effects of sleep deprivation on intrinsic brain connectivity in young and older participants. Participants aged 20–30 (final n = 30) and 65–75 (final n = 23) years underwent partial sleep deprivation (3 h sleep) in a cross-over design, with two 8-minutes eyes-open resting state functional magnetic resonance imaging (fMRI) runs in each session, monitored by eye-tracking. We assessed intrinsic brain connectivity using independent components analysis (ICA) as well as seed-region analyses of functional connectivity, and also analysed global signal variability, regional homogeneity, and the amplitude of low-frequency fluctuations. Sleep deprivation caused increased global signal variability. Changes in investigated resting state networks and in regional homogeneity were not statistically significant. Younger participants had higher connectivity in most examined networks, as well as higher regional homogeneity in areas including anterior and posterior cingulate cortex. In conclusion, we found that sleep deprivation caused increased global signal variability, and we speculate that this may be caused by wake-state instability.
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Affiliation(s)
- Gustav Nilsonne
- Stockholm University, Stress Research Institute, Stockholm, Sweden. .,Karolinska Institutet, Department of Clinical Neuroscience, Stockholm, Sweden.
| | - Sandra Tamm
- Stockholm University, Stress Research Institute, Stockholm, Sweden.,Karolinska Institutet, Department of Clinical Neuroscience, Stockholm, Sweden
| | - Johanna Schwarz
- Stockholm University, Stress Research Institute, Stockholm, Sweden.,Karolinska Institutet, Department of Clinical Neuroscience, Stockholm, Sweden
| | - Rita Almeida
- Karolinska Institutet, Department of Neuroscience, Stockholm, Sweden
| | - Håkan Fischer
- Stockholm University, Department of Psychology, Stockholm, Sweden
| | - Göran Kecklund
- Stockholm University, Stress Research Institute, Stockholm, Sweden
| | - Mats Lekander
- Stockholm University, Stress Research Institute, Stockholm, Sweden.,Karolinska Institutet, Department of Clinical Neuroscience, Stockholm, Sweden
| | - Peter Fransson
- Karolinska Institutet, Department of Clinical Neuroscience, Stockholm, Sweden
| | - Torbjörn Åkerstedt
- Stockholm University, Stress Research Institute, Stockholm, Sweden.,Karolinska Institutet, Department of Clinical Neuroscience, Stockholm, Sweden
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