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Yue WL, Ng KK, Liu S, Qian X, Chong JSX, Koh AJ, Ong MQW, Ting SKS, Ng ASL, Kandiah N, Yeo BTT, Zhou JH. Differential spatial working memory-related functional network reconfiguration in young and older adults. Netw Neurosci 2024; 8:395-417. [PMID: 38952809 PMCID: PMC11142455 DOI: 10.1162/netn_a_00358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 01/05/2024] [Indexed: 07/03/2024] Open
Abstract
Functional brain networks have preserved architectures in rest and task; nevertheless, previous work consistently demonstrated task-related brain functional reorganization. Efficient rest-to-task functional network reconfiguration is associated with better cognition in young adults. However, aging and cognitive load effects, as well as contributions of intra- and internetwork reconfiguration, remain unclear. We assessed age-related and load-dependent effects on global and network-specific functional reconfiguration between rest and a spatial working memory (SWM) task in young and older adults, then investigated associations between functional reconfiguration and SWM across loads and age groups. Overall, global and network-level functional reconfiguration between rest and task increased with age and load. Importantly, more efficient functional reconfiguration associated with better performance across age groups. However, older adults relied more on internetwork reconfiguration of higher cognitive and task-relevant networks. These reflect the consistent importance of efficient network updating despite recruitment of additional functional networks to offset reduction in neural resources and a change in brain functional topology in older adults. Our findings generalize the association between efficient functional reconfiguration and cognition to aging and demonstrate distinct brain functional reconfiguration patterns associated with SWM in aging, highlighting the importance of combining rest and task measures to study aging cognition.
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Affiliation(s)
- Wan Lin Yue
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore
- Integrative Sciences and Engineering Programme, NUS Graduate School, National University of Singapore
| | - Kwun Kei Ng
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore
| | - Siwei Liu
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore
| | - Xing Qian
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore
| | - Joanna Su Xian Chong
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore
| | - Amelia Jialing Koh
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore
| | - Marcus Qin Wen Ong
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore
| | | | | | - Nagaendran Kandiah
- National Neuroscience Institute, Singapore
- Neuroscience and Behavioural Disorders Programme, Duke-NUS Medical School, Singapore
| | - B. T. Thomas Yeo
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore
- Integrative Sciences and Engineering Programme, NUS Graduate School, National University of Singapore
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital
- Department of Electrical and Computer Engineering, N.1 Institute for Health and Memory Networks Program, National University of Singapore
| | - Juan Helen Zhou
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore
- Integrative Sciences and Engineering Programme, NUS Graduate School, National University of Singapore
- Neuroscience and Behavioural Disorders Programme, Duke-NUS Medical School, Singapore
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Hicks TH, Magalhães TNC, Jackson TB, Ballard HK, Herrejon IA, Bernard JA. Functional and Structural Cerebellar-Behavior Relationships in Aging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.19.598916. [PMID: 38979254 PMCID: PMC11230148 DOI: 10.1101/2024.06.19.598916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Healthy aging is associated with deficits in cognitive performance and brain changes, including in the cerebellum. Yet, the precise link between cerebellar function/structure and cognition in aging remains poorly understood. We explored this relationship in 138 healthy adults (aged 35-86, 53% female) using resting-state functional connectivity MRI (fcMRI), cerebellar volume, and cognitive and motor assessments in an aging sample. We expected to find negative relationships between lobular volume for with age, and positive relationships between specific lobular volumes with motor and cognition respectively. We predicted lower cerebellar fcMRI to cortical networks and circuits with increased age. Behaviorally, we expected higher cerebello-frontal fcMRI cerebellar connectivity with association areas to correlate with better behavioral performance. Behavioral tasks broadly assessed attention, processing speed, working memory, episodic memory, and motor abilities. Correlations were conducted between cerebellar lobules I-IV, V, Crus I, Crus II, vermis VI and behavioral measures. We found lower volumes with increased age as well as bidirectional cerebellar connectivity relationships with increased age, consistent with literature on functional connectivity and network segregation in aging. Further, we revealed unique associations for both cerebellar structure and connectivity with comprehensive behavioral measures in a healthy aging population. Our findings underscore cerebellar involvement in behavior during aging.
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Pan Y, Bi C, Kochunov P, Shardell M, Smith JC, McCoy RG, Ye Z, Yu J, Lu T, Yang Y, Lee H, Liu S, Gao S, Ma Y, Li Y, Chen C, Ma T, Wang Z, Nichols T, Hong LE, Chen S. Brain-wide functional connectome analysis of 40,000 individuals reveals brain networks that show aging effects in older adults. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.17.594743. [PMID: 38798606 PMCID: PMC11118564 DOI: 10.1101/2024.05.17.594743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
The functional connectome changes with aging. We systematically evaluated aging related alterations in the functional connectome using a whole-brain connectome network analysis in 39,675 participants in UK Biobank project. We used adaptive dense network discovery tools to identify networks directly associated with aging from resting-state fMRI data. We replicated our findings in 499 participants from the Lifespan Human Connectome Project in Aging study. The results consistently revealed two motor-related subnetworks (both permutation test p-values <0.001) that showed a decline in resting-state functional connectivity (rsFC) with increasing age. The first network primarily comprises sensorimotor and dorsal/ventral attention regions from precentral gyrus, postcentral gyrus, superior temporal gyrus, and insular gyrus, while the second network is exclusively composed of basal ganglia regions, namely the caudate, putamen, and globus pallidus. Path analysis indicates that white matter fractional anisotropy mediates 19.6% (p<0.001, 95% CI [7.6% 36.0%]) and 11.5% (p<0.001, 95% CI [6.3% 17.0%]) of the age-related decrease in both networks, respectively. The total volume of white matter hyperintensity mediates 32.1% (p<0.001, 95% CI [16.8% 53.0%]) of the aging-related effect on rsFC in the first subnetwork.
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Affiliation(s)
- Yezhi Pan
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
| | - Chuan Bi
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
| | - Peter Kochunov
- Department of Psychiatry and Behavioral Science, University of Texas Health Science Center Houston, Houston, United States of America
| | - Michelle Shardell
- Department of Epidemiology and Public Health and Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - J. Carson Smith
- Department of Kinesiology, University of Maryland, College Park, Maryland, United States of America
| | - Rozalina G. McCoy
- Division of Endocrinology, Diabetes, & Nutrition, Department of Medicine, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
| | - Zhenyao Ye
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
- Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
| | - Jiaao Yu
- Department of Mathematics, University of Maryland, College Park, Maryland, United States of America
| | - Tong Lu
- Department of Mathematics, University of Maryland, College Park, Maryland, United States of America
| | - Yifan Yang
- Department of Mathematics, University of Maryland, College Park, Maryland, United States of America
| | - Hwiyoung Lee
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
| | - Song Liu
- School of Computer Science and Technology, Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong, China
| | - Si Gao
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
| | - Yizhou Ma
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
| | - Yiran Li
- Department of Diagnostic Radiology & Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Chixiang Chen
- Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
| | - Tianzhou Ma
- Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, Maryland, United States of America
| | - Ze Wang
- Department of Diagnostic Radiology & Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
| | - Thomas Nichols
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - L. Elliot Hong
- Department of Psychiatry and Behavioral Science, University of Texas Health Science Center Houston, Houston, United States of America
| | - Shuo Chen
- Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
- Division of Biostatistics and Bioinformatics, Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore, Maryland, United States of America
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Mukli P, Pinto CB, Owens CD, Csipo T, Lipecz A, Szarvas Z, Peterfi A, Langley ACDCP, Hoffmeister J, Racz FS, Perry JW, Tarantini S, Nyúl-Tóth Á, Sorond FA, Yang Y, James JA, Kirkpatrick AC, Prodan CI, Toth P, Galindo J, Gardner AW, Sonntag WE, Csiszar A, Ungvari Z, Yabluchanskiy A. Impaired Neurovascular Coupling and Increased Functional Connectivity in the Frontal Cortex Predict Age-Related Cognitive Dysfunction. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2303516. [PMID: 38155460 PMCID: PMC10962492 DOI: 10.1002/advs.202303516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 11/19/2023] [Indexed: 12/30/2023]
Abstract
Impaired cerebrovascular function contributes to the genesis of age-related cognitive decline. In this study, the hypothesis is tested that impairments in neurovascular coupling (NVC) responses and brain network function predict cognitive dysfunction in older adults. Cerebromicrovascular and working memory function of healthy young (n = 21, 33.2±7.0 years) and aged (n = 30, 75.9±6.9 years) participants are assessed. To determine NVC responses and functional connectivity (FC) during a working memory (n-back) paradigm, oxy- and deoxyhemoglobin concentration changes from the frontal cortex using functional near-infrared spectroscopy are recorded. NVC responses are significantly impaired during the 2-back task in aged participants, while the frontal networks are characterized by higher local and global connection strength, and dynamic FC (p < 0.05). Both impaired NVC and increased FC correlate with age-related decline in accuracy during the 2-back task. These findings suggest that task-related brain states in older adults require stronger functional connections to compensate for the attenuated NVC responses associated with working memory load.
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Affiliation(s)
- Peter Mukli
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, 1122 NE 13th Street, Oklahoma City, OK, 73117, USA
- Vascular Cognitive Impairment and Neurodegeneration Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73117, USA
- Department of Physiology, Faculty of Medicine, Semmelweis University, Budapest, H-1094, Hungary
- International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, H-1085, Hungary
| | - Camila B Pinto
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, 1122 NE 13th Street, Oklahoma City, OK, 73117, USA
- Vascular Cognitive Impairment and Neurodegeneration Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73117, USA
| | - Cameron D Owens
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, 1122 NE 13th Street, Oklahoma City, OK, 73117, USA
- Vascular Cognitive Impairment and Neurodegeneration Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73117, USA
| | - Tamas Csipo
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, 1122 NE 13th Street, Oklahoma City, OK, 73117, USA
- Vascular Cognitive Impairment and Neurodegeneration Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73117, USA
- International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, H-1085, Hungary
- Department of Cardiology, Division of Clinical Physiology, Faculty of Medicine, University of Debrecen, Debrecen, H-4032, Hungary
| | - Agnes Lipecz
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, 1122 NE 13th Street, Oklahoma City, OK, 73117, USA
- Vascular Cognitive Impairment and Neurodegeneration Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73117, USA
- International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, H-1085, Hungary
| | - Zsofia Szarvas
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, 1122 NE 13th Street, Oklahoma City, OK, 73117, USA
- Vascular Cognitive Impairment and Neurodegeneration Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73117, USA
- International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, H-1085, Hungary
| | - Anna Peterfi
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, 1122 NE 13th Street, Oklahoma City, OK, 73117, USA
- Vascular Cognitive Impairment and Neurodegeneration Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73117, USA
- International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, H-1085, Hungary
| | - Ana Clara da Costa Pinaffi Langley
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, 1122 NE 13th Street, Oklahoma City, OK, 73117, USA
- Vascular Cognitive Impairment and Neurodegeneration Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73117, USA
| | - Jordan Hoffmeister
- Department of Cardiology, Division of Clinical Physiology, Faculty of Medicine, University of Debrecen, Debrecen, H-4032, Hungary
| | - Frigyes Samuel Racz
- Department of Physiology, Faculty of Medicine, Semmelweis University, Budapest, H-1094, Hungary
- Department of Neurology, Dell Medical School, University of Texas at Austin, Austin, TX, 78712, USA
| | - Jonathan W Perry
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, 1122 NE 13th Street, Oklahoma City, OK, 73117, USA
| | - Stefano Tarantini
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, 1122 NE 13th Street, Oklahoma City, OK, 73117, USA
- Vascular Cognitive Impairment and Neurodegeneration Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73117, USA
- International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, H-1085, Hungary
- Department of Health Promotion Sciences, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73104, USA
- Peggy and Charles Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73104, USA
| | - Ádám Nyúl-Tóth
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, 1122 NE 13th Street, Oklahoma City, OK, 73117, USA
- Vascular Cognitive Impairment and Neurodegeneration Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73117, USA
- International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, H-1085, Hungary
| | - Farzaneh A Sorond
- Department of Neurology, Division of Stroke and Neurocritical Care, Northwestern University Feinberg School of Medicine, 303 E. Chicago Ave., Chicago, IL, 60611, USA
| | - Yuan Yang
- Stephenson School of Biomedical Engineering, The University of Oklahoma, Tulsa, OK, 73019, USA
- Department of Physical Therapy and Human Movement Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
- Department of Rehabilitation Sciences, University of Oklahoma Health Science Center, Oklahoma City, OK, 73117, USA
| | - Judith A James
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, 1122 NE 13th Street, Oklahoma City, OK, 73117, USA
- Arthritis & Clinical Immunology Research Program, Oklahoma Medical Research Foundation, 825 NE 13th Street, Oklahoma City, OK, 73104, USA
- Department of Internal Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73117, USA
- Department of Pathology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73104, USA
| | | | - Calin I Prodan
- Veterans Affairs Medical Center, Oklahoma City, OK, 73104, USA
- Department of Neurology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73104, USA
| | - Peter Toth
- International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, H-1085, Hungary
- Department of Neurosurgery, Medical School, University of Pecs, Pecs, H-7623, Hungary
- Institute for Translational Medicine, Medical School, University of Pecs, Pecs, H-7624, Hungary
- ELKH-PTE Clinical Neuroscience MR Research Group, Pecs, H-7624, Hungary
| | - Juliette Galindo
- Department of Cardiology, Division of Clinical Physiology, Faculty of Medicine, University of Debrecen, Debrecen, H-4032, Hungary
| | - Andrew W Gardner
- Department of Physical Medicine and Rehabilitation, Penn State College of Medicine, 700 HMC Crescent Road, Hershey, PA, 17033, USA
| | - William E Sonntag
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, 1122 NE 13th Street, Oklahoma City, OK, 73117, USA
| | - Anna Csiszar
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, 1122 NE 13th Street, Oklahoma City, OK, 73117, USA
- Vascular Cognitive Impairment and Neurodegeneration Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73117, USA
- International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, H-1085, Hungary
- Peggy and Charles Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73104, USA
| | - Zoltan Ungvari
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, 1122 NE 13th Street, Oklahoma City, OK, 73117, USA
- Vascular Cognitive Impairment and Neurodegeneration Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73117, USA
- International Training Program in Geroscience, Doctoral School of Basic and Translational Medicine/Department of Public Health, Semmelweis University, Budapest, H-1085, Hungary
- Department of Health Promotion Sciences, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73104, USA
- Peggy and Charles Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73104, USA
| | - Andriy Yabluchanskiy
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, 1122 NE 13th Street, Oklahoma City, OK, 73117, USA
- Vascular Cognitive Impairment and Neurodegeneration Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73117, USA
- Department of Health Promotion Sciences, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73104, USA
- Peggy and Charles Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73104, USA
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Chong JSX, Chua KY, Ng KK, Chong SW, Leong RLF, Chee MWL, Koh WP, Zhou JH. Higher handgrip strength is linked to higher salience ventral attention functional network segregation in older adults. Commun Biol 2024; 7:214. [PMID: 38383572 PMCID: PMC10881588 DOI: 10.1038/s42003-024-05862-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 01/26/2024] [Indexed: 02/23/2024] Open
Abstract
Converging evidence suggests that handgrip strength is linked to cognition in older adults, and this may be subserved by shared age-related changes in brain function and structure. However, the interplay among handgrip strength, brain functional connectivity, and cognitive function remains poorly elucidated. Hence, our study sought to examine these relationships in 148 community-dwelling older adults. Specifically, we examined functional segregation, a measure of functional brain organization sensitive to ageing and cognitive decline, and its associations with handgrip strength and cognitive function. We showed that higher handgrip strength was related to better processing speed, attention, and global cognition. Further, higher handgrip strength was associated with higher segregation of the salience/ventral attention network, driven particularly by higher salience/ventral attention intra-network functional connectivity of the right anterior insula to the left posterior insula/frontal operculum and right midcingulate/medial parietal cortex. Importantly, these handgrip strength-related inter-individual differences in salience/ventral attention network functional connectivity were linked to cognitive function, as revealed by functional decoding and brain-cognition association analyses. Our findings thus highlight the importance of the salience/ventral attention network in handgrip strength and cognition, and suggest that inter-individual differences in salience/ventral attention network segregation and intra-network connectivity could underpin the handgrip strength-cognition relationship in older adults.
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Affiliation(s)
- Joanna Su Xian Chong
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Kevin Yiqiang Chua
- Integrative Sciences and Engineering Programme (ISEP), NUS Graduate School, National University of Singapore, Singapore, Singapore
| | - Kwun Kei Ng
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Shin Wee Chong
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ruth L F Leong
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Michael W L Chee
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Woon Puay Koh
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore, Singapore
| | - Juan Helen Zhou
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
- Integrative Sciences and Engineering Programme (ISEP), NUS Graduate School, National University of Singapore, Singapore, Singapore.
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.
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Chaudhary S, Hu S, Hu K, Dominguez JC, Chao HH, Li CSR. Sex differences in the effects of trait anxiety and age on resting-state functional connectivities of the amygdala. JOURNAL OF AFFECTIVE DISORDERS REPORTS 2023; 14:100646. [PMID: 38105798 PMCID: PMC10723810 DOI: 10.1016/j.jadr.2023.100646] [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] [Indexed: 12/19/2023] Open
Abstract
Background Numerous studies characterized how resting-state functional connectivities (rsFCs) of the amygdala were disrupted in emotional disorders and varied with emotional traits, including anxiety. With trait anxiety known to diminish with age, a critical issue concerns disambiguating the effects of age and anxiety on amygdala rsFCs in studying the neural bases of individual differences in anxiety. Methods Two-hundred adults (83 women) 19-85 years of age underwent fMRI and assessment for trait anxiety. Amygdala rsFC correlates were identified using multiple regression with age and anxiety in the same model for all and separately in men and women. The rsFC correlates were examined for age-anxiety interaction. Results Anxiety was negatively correlated with amygdala-temporooccipital gyri rsFC in all and in men alone. In women, amgydala rsFC with the thalamus/pallidum, angular/supramarginal gyri, inferior temporal gyrus, and posterior insula correlated positively and rsFC with calcarine cortex and caudate correlated negatively with anxiety. We also observed sex differences in age correlation of amgydala-posterior cingulate cortex/precuneus and -insula/temporoparietal rsFCs, with stronger associations in women. In women alone, anxiety and age interacted to determine amygdala rsFC with the thalamus/pallidum, calcarine cortex, and caudate, with older age associated with stronger correlation between anxiety and the rsFCs. Limitations The findings need to be validated in an independent sample and further explored using task-based data. Conclusion Highlighting anxiety- and age- specific as well as interacting correlates of amygdala rsFCs and sex differences in the correlates, the findings may shed light on the neural markers of anxiety.
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Affiliation(s)
- Shefali Chaudhary
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06519, USA
| | - Sien Hu
- Department of Psychology, State University of New York at Oswego, Oswego, NY 13126, USA
| | - Kesong Hu
- Department of Psychology, University of Arkansas, Little Rock, AR 72204, USA
| | | | - Herta H. Chao
- VA Connecticut Healthcare System, West Haven, CT 06516, USA
- Department of Medicine, Yale University School of Medicine, New Haven, CT 06519, USA
| | - Chiang-Shan R. Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06519, USA
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06520, USA
- Wu Tsai Institute, Yale University, New Haven, CT 06520, USA
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Qi W, Wen Z, Chen J, Capichioni G, Ando F, Chen ZS, Wang J, Yoncheva Y, Castellanos FX, Milad M, Goff DC. Aberrant resting-state functional connectivity of the globus pallidus interna in first-episode schizophrenia. Schizophr Res 2023; 261:100-106. [PMID: 37716202 DOI: 10.1016/j.schres.2023.09.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 04/05/2023] [Accepted: 09/04/2023] [Indexed: 09/18/2023]
Abstract
BACKGROUND The striatal-pallidal pathway plays an important role in cognitive control and modulation of behaviors. Globus pallidus interna (GPi), as a primary output structure, is crucial in modulating excitation and inhibition. Studies of GPi in psychiatric illnesses are lacking given the technical challenges of examining this small and functionally diverse subcortical structure. METHODS 71 medication-naïve first episode schizophrenia (FES) participants and 73 healthy controls (HC) were recruited at the Shanghai Mental Health Center. Clinical symptoms and imaging data were collected at baseline and, in a subset of patients, 8 weeks after initiating treatment. Resting-state functional connectivity of sub-regions of the GP were assessed using a novel mask that combines two atlases to create 8 ROIs in the GP. RESULTS Baseline imaging data from 63 FES patients and 55 HC met quality standards and were analyzed. FES patients exhibited less negative connectivity and increased positive connectivity between the right anterior GPi and several cortical and subcortical areas at baseline compared to HC (PFWE < 0.05). Positive functional connectivity between the right anterior GPi and several brain areas, including the right dorsal anterior cingulate gyrus, was associated with severity of positive symptoms (PFWE < 0.05) and predicted treatment response after 8 weeks (n = 28, adjusted R2 = 0.486, p < 0.001). CONCLUSIONS Our results implicate striatal-pallidal-thalamic pathways in antipsychotic efficacy. If replicated, these findings may reflect failure of neurodevelopmental processes in adolescence and early adulthood that decrease functional connectivity as an index of failure of the limbic/associative GPi to appropriately inhibit irrelevant signals in psychosis.
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Affiliation(s)
- Wei Qi
- Psychiatry Department, NYU Grossman School of Medicine, New York, NY, United States of America
| | - Zhenfu Wen
- Psychiatry Department, NYU Grossman School of Medicine, New York, NY, United States of America
| | - Jingyun Chen
- Clinical Consult Department, Icometrix, Boston, MA, United States of America
| | - Gillian Capichioni
- Psychiatry Department, NYU Grossman School of Medicine, New York, NY, United States of America
| | - Fumika Ando
- Psychiatry Department, NYU Grossman School of Medicine, New York, NY, United States of America
| | - Zhe Sage Chen
- Psychiatry Department, NYU Grossman School of Medicine, New York, NY, United States of America; Department of Biomedical Engineering, NYU Tandon School of Engineering, Brooklyn, NY, United States of America
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Yuliya Yoncheva
- Department of Child and Adolescent Psychiatry, NYU Grossman School of Medicine, New York, NY, United States of America
| | - Francisco X Castellanos
- Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, United States of America; Department of Child and Adolescent Psychiatry, NYU Grossman School of Medicine, New York, NY, United States of America
| | - Mohammed Milad
- Psychiatry Department, NYU Grossman School of Medicine, New York, NY, United States of America
| | - Donald C Goff
- Psychiatry Department, NYU Grossman School of Medicine, New York, NY, United States of America; Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, United States of America.
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8
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Turrini S, Wong B, Eldaief M, Press DZ, Sinclair DA, Koch G, Avenanti A, Santarnecchi E. The multifactorial nature of healthy brain ageing: Brain changes, functional decline and protective factors. Ageing Res Rev 2023; 88:101939. [PMID: 37116664 DOI: 10.1016/j.arr.2023.101939] [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: 11/15/2022] [Revised: 04/14/2023] [Accepted: 04/24/2023] [Indexed: 04/30/2023]
Abstract
As the global population faces a progressive shift towards a higher median age, understanding the mechanisms underlying healthy brain ageing has become of paramount importance for the preservation of cognitive abilities. The first part of the present review aims to provide a comprehensive look at the anatomical changes the healthy brain endures with advanced age, while also summarizing up to date findings on modifiable risk factors to support a healthy ageing process. Subsequently, we describe the typical cognitive profile displayed by healthy older adults, conceptualizing the well-established age-related decline as an impairment of four main cognitive factors and relating them to their neural substrate previously described; different cognitive trajectories displayed by typical Alzheimer's Disease patients and successful agers with a high cognitive reserve are discussed. Finally, potential effective interventions and protective strategies to promote cognitive reserve and defer cognitive decline are reviewed and proposed.
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Affiliation(s)
- Sonia Turrini
- Precision Neuroscience & Neuromodulation Program, Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Centro studi e ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia "Renzo Canestrari", Alma Mater Studiorum Università di Bologna, Campus di Cesena, Cesena, Italy
| | - Bonnie Wong
- Neuropsychology Program, Frontotemporal Disorders Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA , USA; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Mark Eldaief
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Daniel Z Press
- Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - David A Sinclair
- Blavatnik Institute, Department of Genetics, Paul F. Glenn Center for Biology of ageing Research, Harvard Medical School, Boston, MA, USA
| | - Giacomo Koch
- Stroke Unit, Department of Systems Medicine, University of Tor Vergata, Rome, Italy; Department of Clinical and Behavioural Neurology, Santa Lucia Foundation IRCCS, Rome, Italy
| | - Alessio Avenanti
- Centro studi e ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia "Renzo Canestrari", Alma Mater Studiorum Università di Bologna, Campus di Cesena, Cesena, Italy; Centro de Investigación en Neuropsicología y Neurociencias Cognitivas, Universidad Católica del Maule, Talca, Chile
| | - Emiliano Santarnecchi
- Precision Neuroscience & Neuromodulation Program, Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
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9
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da Silva PHR, de Leeuw FE, Zotin MCZ, Neto OMP, Leoni RF, Tuladhar AM. Cortical Thickness and Brain Connectivity Mediate the Relation Between White Matter Hyperintensity and Information Processing Speed in Cerebral Small Vessel Disease. Brain Topogr 2023:10.1007/s10548-023-00973-w. [PMID: 37273021 DOI: 10.1007/s10548-023-00973-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Accepted: 05/26/2023] [Indexed: 06/06/2023]
Abstract
White matter hyperintensities of presumed vascular origin (WMH) are the most common imaging feature of cerebral small vessel disease (cSVD) and are associated with cognitive impairment, especially information processing speed (IPS) deficits. However, it is unclear how WMH can directly impact IPS or whether the cortical thickness and brain connectivity mediate such association. In this study, it was evaluated the possible mediating roles of cortical thickness and brain (structural and functional) connectivity on the relationship between WMH (also considering its topography distribution) and IPS in 389 patients with cSVD from the RUN-DMC (Radboud University Nijmegen Diffusion tensor and Magnetic resonance imaging Cohort) database. Significant (p < 0.05 after multiple comparisons correction) associations of WMH volume and topography with cortical thickness, brain connectivity, and IPS performance in cSVD individuals were found. Additionally, cortical thickness and brain structural and functional connectivity were shown to mediate the association of WMH volume and location with IPS scores. More specifically, frontal cortical thickness, functional sensorimotor network, and posterior thalamic radiation tract were the essential mediators of WMH and IPS in this clinical group. This study provided insight into the mechanisms underlying the clinical relevance of white matter hyperintensities in information processing speed deficits in cSVD through cortical thinning and network disruptions.
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Affiliation(s)
| | - Frank-Erik de Leeuw
- Department of Neurology, Donders Center for Medical Neuroscience, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
| | - Maria Clara Zanon Zotin
- Department of Neurology, J. Philip Kistler Stroke Research Center, MGH, Boston, MA, USA
- Department of Medical Imaging, Hematology, and Clinical Oncology, Ribeirão Preto Medical School, Ribeirão Preto, Brazil
| | - Octavio Marques Pontes Neto
- Department of Neurosciences and Behavioural Sciences, Hospital das Clínicas-Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil
| | | | - Anil M Tuladhar
- Department of Neurology, Donders Center for Medical Neuroscience, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
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10
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Hua L, Gao F, Xia X, Guo Q, Zhao Y, Huang S, Yuan Z. Individual-specific functional connectivity improves prediction of Alzheimer's disease's symptoms in elderly people regardless of APOE ε4 genotype. Commun Biol 2023; 6:581. [PMID: 37258640 PMCID: PMC10232409 DOI: 10.1038/s42003-023-04952-6] [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: 02/15/2023] [Accepted: 05/18/2023] [Indexed: 06/02/2023] Open
Abstract
To date, reliable biomarkers remain unclear that could link functional connectivity to patients' symptoms for detecting and predicting the process from normal aging to Alzheimer's disease (AD) in elderly people with specific genotypes. To address this, individual-specific functional connectivity is constructed for elderly participants with/without APOE ε4 allele. Then, we utilize recursive feature selection-based machine learning to reveal individual brain-behavior relationships and to predict the symptom transition in different genotypes. Our findings reveal that compared with conventional atlas-based functional connectivity, individual-specific functional connectivity exhibits higher classification and prediction performance from normal aging to AD in both APOE ε4 groups, while no significant performance is detected when the data of two genotyping groups are combined. Furthermore, individual-specific between-network connectivity constitutes a major contributor to assessing cognitive symptoms. This study highlights the essential role of individual variation in cortical functional anatomy and the integration of brain and behavior in predicting individualized symptoms.
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Affiliation(s)
- Lin Hua
- Faculty of Health Sciences, University of Macau, Avenida da Universidade, Taipa, Macau, SAR 999078, China
- Centre for Cognitive and Brain Sciences, University of Macau, Avenida da Universidade, Taipa, Macau, SAR 999078, China
| | - Fei Gao
- Institute of Modern Languages and Linguistics, Fudan University, Shanghai, 200433, China
| | - Xiaoluan Xia
- Faculty of Health Sciences, University of Macau, Avenida da Universidade, Taipa, Macau, SAR 999078, China
- Centre for Cognitive and Brain Sciences, University of Macau, Avenida da Universidade, Taipa, Macau, SAR 999078, China
| | - Qiwei Guo
- Faculty of Health Sciences, University of Macau, Avenida da Universidade, Taipa, Macau, SAR 999078, China
- Centre for Cognitive and Brain Sciences, University of Macau, Avenida da Universidade, Taipa, Macau, SAR 999078, China
| | - Yonghua Zhao
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Avenida da Universidade, Taipa, Macau, SAR 999078, China
| | - Shaohui Huang
- Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Zhen Yuan
- Faculty of Health Sciences, University of Macau, Avenida da Universidade, Taipa, Macau, SAR 999078, China.
- Centre for Cognitive and Brain Sciences, University of Macau, Avenida da Universidade, Taipa, Macau, SAR 999078, China.
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11
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Fan Y, Wang L, Jiang H, Fu Y, Ma Z, Wu X, Wang Y, Song Y, Fan F, Lv Y. Depression circuit adaptation in post-stroke depression. J Affect Disord 2023; 336:52-63. [PMID: 37201899 DOI: 10.1016/j.jad.2023.05.016] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 04/22/2023] [Accepted: 05/06/2023] [Indexed: 05/20/2023]
Abstract
BACKGROUND Lesion locations of post-stroke depression (PSD) mapped to a depression circuit which centered by the left dorsolateral prefrontal cortex (DLPFC). However, it remains unknown whether the compensatory adaptations that may occur in this depression circuit due to the lesions in PSD. METHODS Rs-fMRI data were collected from 82 non-depressed stroke patients (Stroke), 39 PSD patients and 74 healthy controls (HC). We tested the existence of depression circuit, examined PSD-related alterations of DLPFC-seeded connectivity and their associations with depression severity, and analyzed the connectivity between each repetitive transcranial magnetic stimulation (rTMS) target and DLPFC to find the best treatment target for PSD. RESULTS We found that: 1) the left DLPFC showed significantly stronger connectivity to lesions of PSD than Stroke group; 2) in comparison to both Stroke and HC groups, PSD exhibited increased connectivity with DLPFC in bilateral lingual gyrus, contralesional superior frontal gyrus, precuneus, and middle frontal gyrus (MFG); 3) the connectivity between DLPFC and the contralesional lingual gyrus positively correlated with depression severity; 4) the rTMS target in center of MFG showed largest between-group difference in connectivity with DLPFC, and also reported the highest predicted clinical efficacy. LIMITATIONS Longitudinal studies are required to explore the alterations of depression circuit in PSD as the disease progress. CONCLUSION PSD underwent specific alterations in depression circuit, which may help to establish objective imaging markers for early diagnosis and interventions of the disease.
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Affiliation(s)
- Yanzi Fan
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang, China
| | - Luoyu Wang
- Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Haibo Jiang
- Department of Neurology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China
| | - Yanhui Fu
- Department of Neurology, Anshan Changda Hospital, Anshan, Liaoning, China
| | - Zhenqiang Ma
- Department of Neurology, Anshan Changda Hospital, Anshan, Liaoning, China
| | - Xiaoyan Wu
- Department of Image, Anshan Changda Hospital, Anshan, Liaoning 114005, China
| | - Yiying Wang
- Department of Ultrasonics, Anshan Changda Hospital, Anshan, Liaoning, China
| | - Yulin Song
- Department of Neurology, Anshan Changda Hospital, Anshan, Liaoning, China.
| | - Fengmei Fan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, China.
| | - Yating Lv
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang, China.
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12
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Singh P, Kumar Gandhi T, Kumar L. Reorganization of resting-state brain network functional connectivity across human brain developmental stages. Brain Res 2023; 1800:148196. [PMID: 36463956 DOI: 10.1016/j.brainres.2022.148196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 11/01/2022] [Accepted: 11/28/2022] [Indexed: 12/02/2022]
Abstract
Cognitive brain aging can either be healthy or degenerative in nature. Multiple alterations occur in brain networks with healthy aging. Much of this has yet to be investigated. This study seeks to understand the typical healthy human brain's developmental stages using a publicly available dataset from the human connectome project. As the human brain's developmental stage varies, we also intend to identify a pattern of reorganization in the resting state functional connectivity of several brain networks. The results are specifically presented based on the resting state BOLD signals of 1096 healthy volunteers between the age group of 7-89 years. The k-means clustering method has been used to determine the various human brain developmental stages. Using the t-SNE technique, the clusters are visually separated. BrainNet Viewer is used to study the changes in resting state functional connectivity of the entire brain as the human brain developmental stages vary. The age-related pattern of change in the resting state functional connectivity of six Dosenbasch brain networks that were grouped using the k-means elbow approach has been additionally presented. For performance evaluation, three metrics of brain network connection including network segregation, between network connectivity, and within-network connectivity are used. As the age cohort changes, a consistent pattern in the variance of these connection indices is seen for different Dosenbasch brain networks. Thus, the study's findings suggest that healthy aging causes a functional reorganization of the resting state brain network connections.
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Affiliation(s)
- Prerna Singh
- Bharti School of Telecommunication Technology and Management, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110096, India
| | - Tapan Kumar Gandhi
- Cadence Chair Professor of Automation & AI, Convenor, Computer Technology, Department of Electrical Engineering, Hauz Khas, New Delhi 110096, India; Bharti School of Telecommunication, Indian Institute of Technology, Delhi, Hauz Khas, New Delhi 110016, India.
| | - Lalan Kumar
- Department of Electrical Engineering, Bharti School of Telecommunication, New Delhi 110016, India; Yardi School of Artificial Intelligence, Indian Institute of Technology Delhi, New Delhi 110016, India
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13
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Yang X, Zhou X, Xin F, Becker B, Linden D, Hernaus D. Age-dependent changes in the dynamic functional organization of the brain at rest: a cross-cultural replication approach. Cereb Cortex 2023; 33:6394-6406. [PMID: 36642496 PMCID: PMC10183740 DOI: 10.1093/cercor/bhac512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 12/02/2022] [Accepted: 12/03/2022] [Indexed: 01/17/2023] Open
Abstract
Age-associated changes in brain function play an important role in the development of neurodegenerative diseases. Although previous work has examined age-related changes in static functional connectivity, accumulating evidence suggests that advancing age is especially associated with alterations in the dynamic interactions and transitions between different brain states, which hitherto have received less attention. Conclusions of previous studies in this domain are moreover limited by suboptimal replicability of resting-state functional magnetic resonance imaging (fMRI) and culturally homogenous cohorts. Here, we investigate the robustness of age-associated changes in dynamic functional connectivity (dFC) by capitalizing on the availability of fMRI cohorts from two cultures (Western European and Chinese). In both the LEMON (Western European) and SALD (Chinese) cohorts, we consistently identify two distinct states: a more frequent segregated within-network connectivity state (state I) and a less frequent integrated between-network connectivity state (state II). Moreover, in both these cohorts, older (55-80 years) compared to younger participants (20-35 years) exhibited lower occurrence of and spent less time in state I. Older participants also tended to exhibit more transitions between networks and greater variance in global efficiency. Overall, our cross-cultural replication of age-associated changes in dFC metrics implies that advancing age is robustly associated with a reorganization of dynamic brain activation that favors the use of less functionally specific networks.
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Affiliation(s)
- Xi Yang
- Department of Psychiatry & Neuropsychology, School for Mental Health and NeuroScience MHeNS, Maastricht University, Minderbroedersberg 4-6, 6211 LK Maastricht, The Netherlands
| | - Xinqi Zhou
- Institute of Brain and Psychological Sciences, Sichuan Normal University, 610066 Chengdu, Sichuan, China
| | - Fei Xin
- School of Psychology, Shenzhen University, 518060 Shenzhen, Guangdong, China
| | - Benjamin Becker
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Xiyuan Ave, West Hi-Tech Zone, 611731 Chengdu, Sichuan, China
| | - David Linden
- Department of Psychiatry & Neuropsychology, School for Mental Health and NeuroScience MHeNS, Maastricht University, Minderbroedersberg 4-6, 6211 LK Maastricht, The Netherlands
| | - Dennis Hernaus
- Department of Psychiatry & Neuropsychology, School for Mental Health and NeuroScience MHeNS, Maastricht University, Minderbroedersberg 4-6, 6211 LK Maastricht, The Netherlands
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14
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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: 29] [Impact Index Per Article: 29.0] [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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15
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Mijalkov M, Veréb D, Jamialahmadi O, Canal-Garcia A, Gómez-Ruiz E, Vidal-Piñeiro D, Romeo S, Volpe G, Pereira JB. Sex differences in multilayer functional network topology over the course of aging in 37543 UK Biobank participants. Netw Neurosci 2023; 7:351-376. [PMID: 37334001 PMCID: PMC10275214 DOI: 10.1162/netn_a_00286] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 10/06/2022] [Indexed: 07/27/2023] Open
Abstract
Aging is a major risk factor for cardiovascular and neurodegenerative disorders, with considerable societal and economic implications. Healthy aging is accompanied by changes in functional connectivity between and within resting-state functional networks, which have been associated with cognitive decline. However, there is no consensus on the impact of sex on these age-related functional trajectories. Here, we show that multilayer measures provide crucial information on the interaction between sex and age on network topology, allowing for better assessment of cognitive, structural, and cardiovascular risk factors that have been shown to differ between men and women, as well as providing additional insights into the genetic influences on changes in functional connectivity that occur during aging. In a large cross-sectional sample of 37,543 individuals from the UK Biobank cohort, we demonstrate that such multilayer measures that capture the relationship between positive and negative connections are more sensitive to sex-related changes in the whole-brain connectivity patterns and their topological architecture throughout aging, when compared to standard connectivity and topological measures. Our findings indicate that multilayer measures contain previously unknown information on the relationship between sex and age, which opens up new avenues for research into functional brain connectivity in aging.
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Affiliation(s)
- Mite Mijalkov
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Dániel Veréb
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Oveis Jamialahmadi
- Department of Molecular and Clinical Medicine, Goteborg University, Goteborg, Sweden
| | - Anna Canal-Garcia
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | | | | | - Stefano Romeo
- Department of Molecular and Clinical Medicine, Goteborg University, Goteborg, Sweden
- Cardiology Department, Sahlgrenska University Hospital, Gothenburg, Sweden
- Clinical Nutrition Unit, University Magna Graecia, Catanzaro, Italy
| | - Giovanni Volpe
- Department of Physics, Goteborg University, Goteborg, Sweden
| | - Joana B. Pereira
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
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16
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Setton R, Mwilambwe-Tshilobo L, Girn M, Lockrow AW, Baracchini G, Hughes C, Lowe AJ, Cassidy BN, Li J, Luh WM, Bzdok D, Leahy RM, Ge T, Margulies DS, Misic B, Bernhardt BC, Stevens WD, De Brigard F, Kundu P, Turner GR, Spreng RN. Age differences in the functional architecture of the human brain. Cereb Cortex 2022; 33:114-134. [PMID: 35231927 PMCID: PMC9758585 DOI: 10.1093/cercor/bhac056] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Revised: 01/04/2022] [Accepted: 01/26/2022] [Indexed: 11/12/2022] Open
Abstract
The intrinsic functional organization of the brain changes into older adulthood. Age differences are observed at multiple spatial scales, from global reductions in modularity and segregation of distributed brain systems, to network-specific patterns of dedifferentiation. Whether dedifferentiation reflects an inevitable, global shift in brain function with age, circumscribed, experience-dependent changes, or both, is uncertain. We employed a multimethod strategy to interrogate dedifferentiation at multiple spatial scales. Multi-echo (ME) resting-state fMRI was collected in younger (n = 181) and older (n = 120) healthy adults. Cortical parcellation sensitive to individual variation was implemented for precision functional mapping of each participant while preserving group-level parcel and network labels. ME-fMRI processing and gradient mapping identified global and macroscale network differences. Multivariate functional connectivity methods tested for microscale, edge-level differences. Older adults had lower BOLD signal dimensionality, consistent with global network dedifferentiation. Gradients were largely age-invariant. Edge-level analyses revealed discrete, network-specific dedifferentiation patterns in older adults. Visual and somatosensory regions were more integrated within the functional connectome; default and frontoparietal control network regions showed greater connectivity; and the dorsal attention network was more integrated with heteromodal regions. These findings highlight the importance of multiscale, multimethod approaches to characterize the architecture of functional brain aging.
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Affiliation(s)
- Roni Setton
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Laetitia Mwilambwe-Tshilobo
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Manesh Girn
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Amber W Lockrow
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Giulia Baracchini
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Colleen Hughes
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | | | | | - Jian Li
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Wen-Ming Luh
- National Institutes of Health, National Institute on Aging, Baltimore, MD, USA
| | - Danilo Bzdok
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- Department of Biomedical Engineering, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- School of Computer Science, McGill University, Montreal, QC, Canada
- Mila – Quebec Artificial Intelligence Institute, Montreal, QC, Canada
| | - Richard M Leahy
- Department of Electrical Engineering-Systems, University of Southern California, Los Angeles, CA, USA
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Daniel S Margulies
- Integrative Neuroscience and Cognition Center (UMR 8002), Centre National de la Recherche Scientifique (CNRS) and Université de Paris, Paris, France
| | - Bratislav Misic
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
| | - Boris C Bernhardt
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
| | - W Dale Stevens
- Department of Psychology, York University, Toronto, ON, Canada
| | - Felipe De Brigard
- Department of Philosophy, Duke University, Durham, NC, USA
- Department of Psychology and Neuroscience, Durham, NC, USA
| | - Prantik Kundu
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Gary R Turner
- Department of Psychology, York University, Toronto, ON, Canada
| | - R Nathan Spreng
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, McGill University, Montreal, QC, Canada
- Departments of Psychiatry and Psychology, McGill University, Montreal, QC, Canada
- Douglas Mental Health University Institute, Verdun, QC, Canada
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17
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Xia H, He Q, Chen A. Understanding cognitive control in aging: A brain network perspective. Front Aging Neurosci 2022; 14:1038756. [PMID: 36389081 PMCID: PMC9659905 DOI: 10.3389/fnagi.2022.1038756] [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: 09/07/2022] [Accepted: 10/17/2022] [Indexed: 12/03/2022] Open
Abstract
Cognitive control decline is a major manifestation of brain aging that severely impairs the goal-directed abilities of older adults. Magnetic resonance imaging evidence suggests that cognitive control during aging is associated with altered activation in a range of brain regions, including the frontal, parietal, and occipital lobes. However, focusing on specific regions, while ignoring the structural and functional connectivity between regions, may impede an integrated understanding of cognitive control decline in older adults. Here, we discuss the role of aging-related changes in functional segregation, integration, and antagonism among large-scale networks. We highlight that disrupted spontaneous network organization, impaired information co-processing, and enhanced endogenous interference promote cognitive control declines during aging. Additionally, in older adults, severe damage to structural network can weaken functional connectivity and subsequently trigger cognitive control decline, whereas a relatively intact structural network ensures the compensation of functional connectivity to mitigate cognitive control impairment. Thus, we propose that age-related changes in functional networks may be influenced by structural networks in cognitive control in aging (CCA). This review provided an integrative framework to understand the cognitive control decline in aging by viewing the brain as a multimodal networked system.
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Affiliation(s)
- Haishuo Xia
- Faculty of Psychology, Southwest University, Chongqing, China
| | - Qinghua He
- Faculty of Psychology, Southwest University, Chongqing, China
| | - Antao Chen
- School of Psychology, Shanghai University of Sport, Shanghai, China
- *Correspondence: Antao Chen,
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18
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Scheel N, Keller JN, Binder EF, Vidoni ED, Burns JM, Thomas BP, Stowe AM, Hynan LS, Kerwin DR, Vongpatanasin W, Rossetti H, Cullum CM, Zhang R, Zhu DC. Evaluation of noise regression techniques in resting-state fMRI studies using data of 434 older adults. Front Neurosci 2022; 16:1006056. [PMID: 36340768 PMCID: PMC9626831 DOI: 10.3389/fnins.2022.1006056] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 09/27/2022] [Indexed: 01/24/2023] Open
Abstract
Subject motion is a well-known confound in resting-state functional MRI (rs-fMRI) and the analysis of functional connectivity. Consequently, several clean-up strategies have been established to minimize the impact of subject motion. Physiological signals in response to cardiac activity and respiration are also known to alter the apparent rs-fMRI connectivity. Comprehensive comparisons of common noise regression techniques showed that the "Independent Component Analysis based strategy for Automatic Removal of Motion Artifacts" (ICA-AROMA) was a preferred pre-processing technique for teenagers and adults. However, motion and physiological noise characteristics may differ substantially for older adults. Here, we present a comprehensive comparison of noise-regression techniques for older adults from a large multi-site clinical trial of exercise and intensive pharmacological vascular risk factor reduction. The Risk Reduction for Alzheimer's Disease (rrAD) trial included hypertensive older adults (60-84 years old) at elevated risk of developing Alzheimer's Disease (AD). We compared the performance of censoring, censoring combined with global signal regression, non-aggressive and aggressive ICA-AROMA, as well as the Spatially Organized Component Klassifikator (SOCK) on the rs-fMRI baseline scans from 434 rrAD subjects. All techniques were rated based on network reproducibility, network identifiability, edge activity, spatial smoothness, and loss of temporal degrees of freedom (tDOF). We found that non-aggressive ICA-AROMA did not perform as well as the other four techniques, which performed table with marginal differences, demonstrating the validity of these techniques. Considering reproducibility as the most important factor for longitudinal studies, given low false-positive rates and a better preserved, more cohesive temporal structure, currently aggressive ICA-AROMA is likely the most suitable noise regression technique for rs-fMRI studies of older adults.
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Affiliation(s)
- Norman Scheel
- Department of Radiology, Michigan State University, East Lansing, MI, United States
| | - Jeffrey N. Keller
- Pennington Biomedical Research Center, Baton Rouge, LA, United States
| | - Ellen F. Binder
- Division of Geriatrics and Nutritional Science, Washington University School of Medicine, St. Louis, MO, United States
| | - Eric D. Vidoni
- Alzheimer’s Disease Center, University of Kansas, Fairway, KS, United States
| | - Jeffrey M. Burns
- Alzheimer’s Disease Center, University of Kansas, Fairway, KS, United States
| | - Binu P. Thomas
- UT Southwestern Medical Center, Dallas, TX, United States
| | - Ann M. Stowe
- Department of Neurology, University of Kentucky, Lexington, KY, United States
| | - Linda S. Hynan
- UT Southwestern Medical Center, Dallas, TX, United States
| | - Diana R. Kerwin
- Texas Health Presbyterian Hospital, Dallas, TX, United States
| | | | - Heidi Rossetti
- UT Southwestern Medical Center, Dallas, TX, United States
| | | | - Rong Zhang
- UT Southwestern Medical Center, Dallas, TX, United States,Texas Health Presbyterian Hospital, Dallas, TX, United States
| | - David C. Zhu
- Department of Radiology, Michigan State University, East Lansing, MI, United States,*Correspondence: David C. Zhu,
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19
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Stumme J, Krämer C, Miller T, Schreiber J, Caspers S, Jockwitz C. Interrelating differences in structural and functional connectivity in the older adult's brain. Hum Brain Mapp 2022; 43:5543-5561. [PMID: 35916531 PMCID: PMC9704795 DOI: 10.1002/hbm.26030] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 07/11/2022] [Accepted: 07/15/2022] [Indexed: 01/15/2023] Open
Abstract
In the normal aging process, the functional connectome restructures and shows a shift from more segregated to more integrated brain networks, which manifests itself in highly different cognitive performances in older adults. Underpinnings of this reorganization are not fully understood, but may be related to age-related differences in structural connectivity, the underlying scaffold for information exchange between regions. The structure-function relationship might be a promising factor to understand the neurobiological sources of interindividual cognitive variability, but remain unclear in older adults. Here, we used diffusion weighted and resting-state functional magnetic resonance imaging as well as cognitive performance data of 573 older subjects from the 1000BRAINS cohort (55-85 years, 287 males) and performed a partial least square regression on 400 regional functional and structural connectivity (FC and SC, respectively) estimates comprising seven resting-state networks. Our aim was to identify FC and SC patterns that are, together with cognitive performance, characteristic of the older adults aging process. Results revealed three different aging profiles prevalent in older adults. FC was found to behave differently depending on the severity of age-related SC deteriorations. A functionally highly interconnected system is associated with a structural connectome that shows only minor age-related decreases. Because this connectivity profile was associated with the most severe age-related cognitive decline, a more interconnected FC system in older adults points to a process of dedifferentiation. Thus, functional network integration appears to increase primarily when SC begins to decline, but this does not appear to mitigate the decline in cognitive performance.
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Affiliation(s)
- Johanna Stumme
- Institute of Neuroscience and Medicine (INM‐1), Research Centre JülichJülichGermany,Institute for Anatomy I, Medical Faculty & University Hospital DüsseldorfHeinrich Heine University DüsseldorfDüsseldorfGermany
| | - Camilla Krämer
- Institute of Neuroscience and Medicine (INM‐1), Research Centre JülichJülichGermany,Institute for Anatomy I, Medical Faculty & University Hospital DüsseldorfHeinrich Heine University DüsseldorfDüsseldorfGermany
| | - Tatiana Miller
- Institute of Neuroscience and Medicine (INM‐1), Research Centre JülichJülichGermany,Institute for Anatomy I, Medical Faculty & University Hospital DüsseldorfHeinrich Heine University DüsseldorfDüsseldorfGermany
| | - Jan Schreiber
- Institute of Neuroscience and Medicine (INM‐1), Research Centre JülichJülichGermany
| | - Svenja Caspers
- Institute of Neuroscience and Medicine (INM‐1), Research Centre JülichJülichGermany,Institute for Anatomy I, Medical Faculty & University Hospital DüsseldorfHeinrich Heine University DüsseldorfDüsseldorfGermany
| | - Christiane Jockwitz
- Institute of Neuroscience and Medicine (INM‐1), Research Centre JülichJülichGermany,Institute for Anatomy I, Medical Faculty & University Hospital DüsseldorfHeinrich Heine University DüsseldorfDüsseldorfGermany
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20
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Effects of aging on functional connectivity in a neurodegenerative risk cohort: resting state versus task measurement using near-infrared spectroscopy. Sci Rep 2022; 12:11262. [PMID: 35788629 PMCID: PMC9253312 DOI: 10.1038/s41598-022-13326-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 05/16/2022] [Indexed: 11/23/2022] Open
Abstract
Changes in functional brain organization are considered to be particularly sensitive to age-related effects and may precede structural cognitive decline. Recent research focuses on aging processes determined by resting state (RS) functional connectivity (FC), but little is known about differences in FC during RS and cognitive task conditions in elderly participants. The purpose of this study is to compare FC within and between the cognitive control (CCN) and dorsal attention network (DAN) at RS and during a cognitive task using functional near-infrared spectroscopy (fNIRS). In a matched, neurodegenerative high-risk cohort comprising early (n = 98; 50–65 y) and late (n = 98; 65–85 y) elder subjects, FC was measured at RS and during performance of the Trail Making Test (TMT) via fNIRS. Both, under RS and task conditions our results revealed a main effect for age, characterized by reduced FC for late elder subjects within the left inferior frontal gyrus. During performance of the TMT, negative correlations of age and FC were confirmed in various regions of the CCN and DAN. For the whole sample, FC of within-region connections was elevated, while FC between regions was decreased at RS. The results confirm a reorganization of functional brain connectivity with increasing age and cognitive demands.
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21
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Moghimi P, Dang AT, Do Q, Netoff TI, Lim KO, Atluri G. Evaluation of functional MRI-based human brain parcellation: a review. J Neurophysiol 2022; 128:197-217. [PMID: 35675446 DOI: 10.1152/jn.00411.2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Brain parcellations play a crucial role in the analysis of brain imaging data sets, as they can significantly affect the outcome of the analysis. In recent years, several novel approaches for constructing MRI-based brain parcellations have been developed with promising results. In the absence of ground truth, several evaluation approaches have been used to evaluate currently available brain parcellations. In this article, we review and critique methods used for evaluating functional brain parcellations constructed using fMRI data sets. We also describe how some of these evaluation methods have been used to estimate the optimal parcellation granularity. We provide a critical discussion of the current approach to the problem of identifying the optimal brain parcellation that is suited for a given neuroimaging study. We argue that the criteria for an optimal brain parcellation must depend on the application the parcellation is intended for. We describe a teleological approach to the evaluation of brain parcellations, where brain parcellations are evaluated in different contexts and optimal brain parcellations for each context are identified separately. We conclude by discussing several directions for further research that would result in improved evaluation strategies.
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Affiliation(s)
- Pantea Moghimi
- Department of Neurobiology, University of Chicago, Chicago, Illinois
| | - Anh The Dang
- Department of Electrical Engineering and Computer Science, University of Cincinnati, Cincinnati, Ohio
| | - Quan Do
- Department of Electrical Engineering and Computer Science, University of Cincinnati, Cincinnati, Ohio
| | - Theoden I Netoff
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota
| | - Kelvin O Lim
- Department of Psychiatry, University of Minnesota, Minneapolis, Minnesota
| | - Gowtham Atluri
- Department of Electrical Engineering and Computer Science, University of Cincinnati, Cincinnati, Ohio
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22
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Talesh Jafadideh A, Mohammadzadeh Asl B. Rest-fMRI based comparison study between autism spectrum disorder and typically control using graph frequency bands. Comput Biol Med 2022; 146:105643. [DOI: 10.1016/j.compbiomed.2022.105643] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 04/17/2022] [Accepted: 05/14/2022] [Indexed: 01/01/2023]
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23
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Bernard JA. Don't forget the little brain: A framework for incorporating the cerebellum into the understanding of cognitive aging. Neurosci Biobehav Rev 2022; 137:104639. [PMID: 35346747 PMCID: PMC9119942 DOI: 10.1016/j.neubiorev.2022.104639] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 02/28/2022] [Accepted: 03/23/2022] [Indexed: 12/22/2022]
Abstract
With the rapidly growing population of older adults, an improved understanding of brain and cognitive aging is critical, given the impacts on health, independence, and quality of life. To this point, we have a well-developed literature on the cortical contributions to cognition in advanced age. However, while this work has been foundational for our understanding of brain and behavior in older adults, subcortical contributions, particularly those from the cerebellum, have not been integrated into these models and frameworks. Incorporating the cerebellum into models of cognitive aging is an important step for moving the field forward. There has also been recent interest in this structure in Alzheimer's dementia, indicating that such work may be beneficial to our understanding of neurodegenerative disease. Here, I provide an updated overview of the cerebellum in advanced age and propose that it serves as a critical source of scaffolding or reserve for cortical function. Age-related impacts on cerebellar function further impact cortical processing, perhaps resulting in many of the activation patterns commonly seen in aging.
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Affiliation(s)
- Jessica A Bernard
- Department of Psychological and Brain Sciences, USA; Texas A&M Institute for Neuroscience, Texas A&M University, USA.
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24
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Subramaniapillai S, Rajagopal S, Ankudowich E, Pasvanis S, Misic B, Rajah MN. Age- and Episodic Memory-related Differences in Task-based Functional Connectivity in Women and Men. J Cogn Neurosci 2022; 34:1500-1520. [PMID: 35579987 DOI: 10.1162/jocn_a_01868] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Aging is associated with episodic memory decline and changes in functional brain connectivity. Understanding whether and how biological sex influences age- and memory performance-related functional connectivity has important theoretical implications for the cognitive neuroscience of memory and aging. Here, we scanned 161 healthy adults between 19 and 76 years of age in an event-related fMRI study of face-location spatial context memory. Adults were scanned while performing easy and difficult versions of the task at both encoding and retrieval. We used multivariate whole-brain partial least squares connectivity to test the hypothesis that there are sex differences in age- and episodic memory performance-related functional connectivity. We examined how individual differences in age and retrieval accuracy correlated with task-related connectivity. We then repeated this analysis after disaggregating the data by self-reported sex. We found that increased encoding and retrieval-related connectivity within the dorsal attention network (DAN), and between DAN and frontoparietal network and visual networks, were positively correlated to retrieval accuracy and negatively correlated with age in both sexes. We also observed sex differences in age- and performance-related functional connectivity: (a) Greater between-networks integration was apparent at both levels of task difficulty in women only, and (b) increased DAN-default mode network connectivity with age was observed in men and was correlated with poorer memory performance. Therefore, the neural correlates of age-related episodic memory decline differ in women and men and have important theoretical and clinical implications for the cognitive neuroscience of memory, aging, and dementia prevention.
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Affiliation(s)
- Sivaniya Subramaniapillai
- McGill University, Montréal, Quebéc, Canada.,Douglas Mental Health University Institute, Montréal, Quebéc, Canada
| | | | - Elizabeth Ankudowich
- McGill University, Montréal, Quebéc, Canada.,Douglas Mental Health University Institute, Montréal, Quebéc, Canada
| | | | - Bratislav Misic
- Douglas Mental Health University Institute, Montréal, Quebéc, Canada
| | - M Natasha Rajah
- McGill University, Montréal, Quebéc, Canada.,Douglas Mental Health University Institute, Montréal, Quebéc, Canada
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25
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Brown RM, Gruijters SLK, Kotz SA. Prediction in the aging brain: Merging cognitive, neurological, and evolutionary perspectives. J Gerontol B Psychol Sci Soc Sci 2022; 77:1580-1591. [PMID: 35429160 PMCID: PMC9434449 DOI: 10.1093/geronb/gbac062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Indexed: 12/02/2022] Open
Abstract
Although the aging brain is typically characterized by declines in a variety of cognitive functions, there has been growing attention to cognitive functions that may stabilize or improve with age. We integrate evidence from behavioral, computational, and neurological domains under the hypothesis that over the life span the brain becomes more effective at predicting (i.e., utilizing knowledge) compared to learning. Moving beyond mere description of the empirical literature—with the aim of arriving at a deeper understanding of cognitive aging—we provide potential explanations for a learning-to-prediction shift based on evolutionary models and principles of senescence and plasticity. The proposed explanations explore whether the occurrence of a learning-to-prediction shift can be explained by (changes in) the fitness effects of learning and prediction over the life span. Prediction may optimize (a) the allocation of limited resources across the life span, and/or (b) late-life knowledge transfer (social learning). Alternatively, late-life prediction may reflect a slower decline in prediction compared to learning. By discussing these hypotheses, we aim to provide a foundation for an integrative neurocognitive–evolutionary perspective on aging and to stimulate further theoretical and empirical work.
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Affiliation(s)
- Rachel M Brown
- Institute of Psychology, RWTH Aachen University, Aachen, Germany
| | - Stefan L K Gruijters
- Faculty of Psychology, Open University of the Netherlands, Heerlen, the Netherlands
| | - Sonja A Kotz
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
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26
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Murray T, O’Brien J, Sagiv N, Kumari V. Changes in functional connectivity associated with facial expression processing over the working adult lifespan. Cortex 2022; 151:211-223. [DOI: 10.1016/j.cortex.2022.03.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 01/06/2022] [Accepted: 03/01/2022] [Indexed: 11/03/2022]
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27
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Hengenius JB, Bohnen NI, Rosso A, Huppert TJ, Rosano C. Cortico-striatal functional connectivity and cerebral small vessel disease: Contribution to mild Parkinsonian signs. J Neuroimaging 2022; 32:352-362. [PMID: 34957653 PMCID: PMC9119198 DOI: 10.1111/jon.12949] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Revised: 11/01/2021] [Accepted: 11/01/2021] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND AND PURPOSE Mild Parkinsonian signs (MPS) are common in older adults. We hypothesized that MPS are associated with lower functional connectivity (FC) in dopamine-dependent cortico-striatal networks, and these associations vary with white matter hyperintensity (WMH), a risk factor for MPS. METHODS We examined resting-state functional MRI in 266 participants (mean age 83; 57% female; 41% African American) with data on MPS (Unified Parkinson's Disease Rating Scale), demographics, cognition, muscle-skeletal, and cardiometabolic health. FC between cortex and striatum was examined separately for sensorimotor, executive, and limbic functional subregions. Logistic regression tested the association of FC in each network with MPS, adjusted for covariates. Interactions of FC by WMH were tested; and analyses were repeated stratified by WMH above/below the median. RESULTS Compared to those without MPS, those with MPS had lower cortico-striatal FC in the left executive network (adjusted odds ratio [95% confidence interval], p-value: 0.188 [0.043, 0.824], .027). The interaction with WMH was p = .064; left executive FC was inversely associated with MPS for high WMH (0.077 [0.010, 0.599], .014) but not low WMH participants (1.245 [0.128, 12.132], .850). CONCLUSIONS MPS appear related to lower executive network FC, robust to adjustment for other risk factors, and stronger for those with higher burden of WMH. Future longitudinal studies should examine the interplay between cerebral small vessel disease and connectivity influencing MPS.
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Affiliation(s)
- James B. Hengenius
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Nicolaas I. Bohnen
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Andrea Rosso
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Theodore J. Huppert
- Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Caterina Rosano
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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28
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Network-specific differences in transient brain activity at rest are associated with age-related reductions in motor performance. Neuroimage 2022; 252:119025. [PMID: 35202812 DOI: 10.1016/j.neuroimage.2022.119025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 02/15/2022] [Accepted: 02/20/2022] [Indexed: 11/20/2022] Open
Abstract
Multiple functional changes occur in the brain with increasing age. Among those, older adults typically display more restricted fluctuations of brain activity, both during resting-state and task execution. These altered dynamic patterns have been linked to reduced task performance across multiple behavioral domains. Windowed functional connectivity, which is typically employed in the study of connectivity dynamics, however, might not be able to properly characterize moment-to-moment variations of individual networks. In the present study, we used innovation-driven co-activation patterns (ICAP) to overcome this limitation and investigate the length (duration) and frequency (innovation) in which various brain networks emerged across the adult lifespan (N= 92) during a resting-state period. We identified a link between increasing age and a tendency to engage brain areas with distinct functional associations simultaneously as a single network. The emergence of isolated and spatially well-defined visual, motor, frontoparietal, and posterior networks decreased with increased age. This reduction in dynamics of specialized networks mediated age-related performance decreases (i.e., increases in interlimb interference) in a bimanual motor task. Altogether, our findings demonstrated that older compared to younger adults tend to activate fewer network configurations, which include multiple functionally distinct brain areas. The reduction in independent emergence of functionally well-defined and task-relevant networks may reflect an expression of brain dedifferentiation and is likely associated with functional modulatory deficits, negatively impacting motor behavior.
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29
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Guardia T, Geerligs L, Tsvetanov KA, Ye R, Campbell KL. The role of the arousal system in age-related differences in cortical functional network architecture. Hum Brain Mapp 2022; 43:985-997. [PMID: 34713955 PMCID: PMC8764482 DOI: 10.1002/hbm.25701] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 10/04/2021] [Accepted: 10/17/2021] [Indexed: 01/10/2023] Open
Abstract
A common finding in the aging literature is that of the brain's decreased within- and increased between-network functional connectivity. However, it remains unclear what is causing this shift in network organization with age. Given the essential role of the ascending arousal system (ARAS) in cortical activation and previous findings of disrupted ARAS functioning with age, it is possible that age differences in ARAS functioning contribute to disrupted cortical connectivity. We test this possibility here using resting state fMRI data from over 500 individuals across the lifespan from the Cambridge Center for Aging and Neuroscience (Cam-CAN) population-based cohort. Our results show that ARAS-cortical connectivity declines with age and, consistent with our expectations, significantly mediates some age-related differences in connectivity within and between association networks (specifically, within the default mode and between the default mode and salience networks). Additionally, connectivity between the ARAS and association networks predicted cognitive performance across several tasks over and above the effects of age and connectivity within the cortical networks themselves. These findings suggest that age differences in cortical connectivity may be driven, at least in part, by altered arousal signals from the brainstem and that ARAS-cortical connectivity relates to cognitive performance with age.
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Affiliation(s)
- Tiago Guardia
- Department of PsychologyBrock UniversitySt. CatharinesOntarioCanada
| | - Linda Geerligs
- Donders Institute for Brain, Cognition, and BehaviourRadboud UniversityNijmegenThe Netherlands
| | | | - Rong Ye
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
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30
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Suárez-Méndez I, Bruña R, López-Sanz D, Montejo P, Montenegro-Peña M, Delgado-Losada ML, Marcos Dolado A, López-Higes R, Maestú F. Cognitive Training Modulates Brain Hypersynchrony in a Population at Risk for Alzheimer's Disease. J Alzheimers Dis 2022; 86:1185-1199. [PMID: 35180120 DOI: 10.3233/jad-215406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Recent studies demonstrated that brain hypersynchrony is an early sign of dysfunction in Alzheimer's disease (AD) that can represent a proxy for clinical progression. Conversely, non-pharmacological interventions, such as cognitive training (COGTR), are associated with cognitive gains that may be underpinned by a neuroprotective effect on brain synchrony. OBJECTIVE To study the potential of COGTR to modulate brain synchrony and to eventually revert the hypersynchrony phenomenon that characterizes preclinical AD. METHODS The effect of COGTR was examined in a sample of healthy controls (HC, n = 41, 22 trained) and individuals with subjective cognitive decline (SCD, n = 49, 24 trained). Magnetoencephalographic (MEG) activity and neuropsychological scores were acquired before and after a ten-week COGTR intervention aimed at improving cognitive function and daily living performance. Functional connectivity (FC) was analyzed using the phase-locking value. A mixed-effects ANOVA model with factors time (pre-intervention/post-intervention), training (trained/non-trained), and diagnosis (HC/SCD) was used to investigate significant changes in FC. RESULTS We found an average increase in alpha-band FC over time, but the effect was different in each group (trained and non-trained). In the trained group (HC and SCD), we report a reduction in the increase in FC within temporo-parietal and temporo-occipital connections. In the trained SCD group, this reduction was stronger and showed a tentative correlation with improved performance in different cognitive tests. CONCLUSION COGTR interventions could mitigate aberrant increases in FC in preclinical AD, promoting brain synchrony normalization in groups at a higher risk of developing dementia.
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Affiliation(s)
- Isabel Suárez-Méndez
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology (CTB), Universidad Politécnica de Madrid (UPM), Madrid, Spain.,Departamento de Estructura de la Materia, Física Térmica y Electrónica, Universidad Complutense de Madrid (UCM), Facultad de Ciencias Físicas, Madrid, Spain.,Department of Experimental Psychology, Faculty of Psychology, Complutense University of Madrid (UCM), Madrid, Spain
| | - Ricardo Bruña
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology (CTB), Universidad Politécnica de Madrid (UPM), Madrid, Spain.,Department of Experimental Psychology, Faculty of Psychology, Complutense University of Madrid (UCM), Madrid, Spain.,Networking Research Center on Bioengineering, Biomaterials, and Nanomedicine (CIBER-BBN), Madrid, Spain
| | - David López-Sanz
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology (CTB), Universidad Politécnica de Madrid (UPM), Madrid, Spain.,Department of Psychobiology, Faculty of Psychology, Complutense University of Madrid (UCM), Madrid, Spain
| | - Pedro Montejo
- Center for the Prevention of Cognitive Impairment (Madrid Salud), Madrid City Council, Spain
| | - Mercedes Montenegro-Peña
- Department of Experimental Psychology, Faculty of Psychology, Complutense University of Madrid (UCM), Madrid, Spain.,Center for the Prevention of Cognitive Impairment (Madrid Salud), Madrid City Council, Spain
| | - María Luisa Delgado-Losada
- Department of Experimental Psychology, Faculty of Psychology, Complutense University of Madrid (UCM), Madrid, Spain
| | | | - Ramón López-Higes
- Department of Experimental Psychology, Faculty of Psychology, Complutense University of Madrid (UCM), Madrid, Spain
| | - Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Center for Biomedical Technology (CTB), Universidad Politécnica de Madrid (UPM), Madrid, Spain.,Department of Experimental Psychology, Faculty of Psychology, Complutense University of Madrid (UCM), Madrid, Spain.,Networking Research Center on Bioengineering, Biomaterials, and Nanomedicine (CIBER-BBN), Madrid, Spain
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31
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Moss AS, Reibel DK, Wintering N, Vedaei F, Porter H, Khosravi M, Heholt J, Alizadeh M, Mohamed FB, Newberg AB. Cerebral Blood Flow and Brain Functional Connectivity Changes in Older Adults Participating in a Mindfulness-Based Stress Reduction Program. Behav Sci (Basel) 2022; 12:bs12020048. [PMID: 35200299 PMCID: PMC8869750 DOI: 10.3390/bs12020048] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 01/27/2022] [Accepted: 02/11/2022] [Indexed: 11/26/2022] Open
Abstract
There is a growing interest in the potential beneficial effects of mindfulness meditation training in protecting against age-related physical, emotional, and cognitive decline. The current prospective, single-center, single-arm study investigated if functional magnetic resonance imaging-based changes in cerebral blood flow and brain functional connectivity could be observed in 11 elderly adults (mean age 79) after participation in a Mindfulness-Based Stress Reduction (MBSR) program. The results showed significantly (p < 0.05) altered cerebral blood flow and functional connectivity in the cingulate gyrus, limbic structures, and subregions of the temporal and frontal lobes, similar to findings of other meditation-related studies in younger populations. Furthermore, these changes were also associated with significant improvements in depression symptoms. This study suggests that the MBSR program can potentially modify cerebral blood flow and connectivity in this population.
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Affiliation(s)
- Aleeze Sattar Moss
- Department of Integrative Medicine and Nutritional Sciences, Thomas Jefferson University, Philadelphia, PA 19107, USA; (A.S.M.); (D.K.R.); (N.W.); (H.P.); (M.K.)
| | - Diane K. Reibel
- Department of Integrative Medicine and Nutritional Sciences, Thomas Jefferson University, Philadelphia, PA 19107, USA; (A.S.M.); (D.K.R.); (N.W.); (H.P.); (M.K.)
| | - Nancy Wintering
- Department of Integrative Medicine and Nutritional Sciences, Thomas Jefferson University, Philadelphia, PA 19107, USA; (A.S.M.); (D.K.R.); (N.W.); (H.P.); (M.K.)
| | - Faezeh Vedaei
- Department of Radiology, Thomas Jefferson University, Philadelphia, PA 19107, USA; (F.V.); (M.A.); (F.B.M.)
| | - Hannah Porter
- Department of Integrative Medicine and Nutritional Sciences, Thomas Jefferson University, Philadelphia, PA 19107, USA; (A.S.M.); (D.K.R.); (N.W.); (H.P.); (M.K.)
| | - Mohsen Khosravi
- Department of Integrative Medicine and Nutritional Sciences, Thomas Jefferson University, Philadelphia, PA 19107, USA; (A.S.M.); (D.K.R.); (N.W.); (H.P.); (M.K.)
| | - Justin Heholt
- Department of Surgery, Allegheny General Hospital, Pittsburgh, PA 15212, USA;
| | - Mahdi Alizadeh
- Department of Radiology, Thomas Jefferson University, Philadelphia, PA 19107, USA; (F.V.); (M.A.); (F.B.M.)
| | - Feroze B. Mohamed
- Department of Radiology, Thomas Jefferson University, Philadelphia, PA 19107, USA; (F.V.); (M.A.); (F.B.M.)
| | - Andrew B. Newberg
- Department of Integrative Medicine and Nutritional Sciences, Thomas Jefferson University, Philadelphia, PA 19107, USA; (A.S.M.); (D.K.R.); (N.W.); (H.P.); (M.K.)
- Department of Radiology, Thomas Jefferson University, Philadelphia, PA 19107, USA; (F.V.); (M.A.); (F.B.M.)
- Correspondence:
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32
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Dockman RL, Carpenter JM, Diaz AN, Benbow RA, Filipov NM. Sex differences in behavior, response to LPS, and glucose homeostasis in middle-aged mice. Behav Brain Res 2022; 418:113628. [PMID: 34687827 PMCID: PMC8671369 DOI: 10.1016/j.bbr.2021.113628] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Revised: 10/03/2021] [Accepted: 10/09/2021] [Indexed: 12/23/2022]
Abstract
Sex and age have distinct influences and roles in behavior and immune reactivity; yet, most studies use adult male rodents with little attention to middle age, a time associated with key physiological transitions in both sexes. Thus, this study investigated sex differences during middle age in behavior, immune response to lipopolysaccharide (LPS), and glucose regulation in C57BL/6 mice with GFP-tagged monocytes/microglia. Behaviorally, males performed better in tests of motor function (Open Field [OF], Grip Strength, Sticker Removal, Gait, and Pole tests) and displayed less depressive- and anxiety-like behaviors across multiple mood tests (OF, Elevated Zero Maze, Sucrose Preference, and Swim test). However, females performed better in tests of cognition (Barnes Maze and Novel Object Recognition). Following behavioral assessment, mice were given LPS to characterize sex-dependent inflammagen responses. Females displayed greater sickness behavior in the OF, higher levels of peripheral cytokines, and subtle neuroinflammation in the cortex, striatum, and hippocampus. A separate middle-aged cohort was used for glucose tolerance and insulin sensitivity testing. Both sexes had excessive blood glucose rebound after insulin challenge, but displayed differences following glucose administration, where males had higher baseline glucose and females remained hyperglycemic. This study suggests that during middle-age male mice have better emotional regulation and motor function, but not cognitive ability than females. Further, males are less sensitive than females to the acute effects of LPS peripherally and centrally, but both sexes showed sex-specific impairments in blood glucose regulation. Overall, it appears that middle age is an important transition point with multiple sex differences, some of which are unique to this stage of life.
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Affiliation(s)
- Rachel L Dockman
- Department of Physiology and Pharmacology, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, United States
| | - Jessica M Carpenter
- Department of Physiology and Pharmacology, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, United States
| | - Alexa N Diaz
- Department of Physiology and Pharmacology, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, United States
| | - Robert A Benbow
- Department of Physiology and Pharmacology, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, United States
| | - Nikolay M Filipov
- Department of Physiology and Pharmacology, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, United States.
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33
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Chen Y, Tang JH, De Stefano LA, Wenger MJ, Ding L, Craft MA, Carlson BW, Yuan H. Electrophysiological resting state brain network and episodic memory in healthy aging adults. Neuroimage 2022; 253:118926. [PMID: 35066158 DOI: 10.1016/j.neuroimage.2022.118926] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 12/16/2021] [Accepted: 01/19/2022] [Indexed: 01/06/2023] Open
Abstract
Recent studies have emphasized the changes in large-scale brain networks related to healthy aging, with the ultimate purpose to aid in differentiating normal neurocognitive aging from neurodegenerative disorders that also arise with age. Emerging evidence from functional Magnetic Resonance Imaging (fMRI) indicates that connectivity patterns within specific brain networks, especially the Default Mode Network (DMN), distinguish those with Alzheimer's disease from healthy individuals. In addition, disruptive alterations in the large-scale brain systems that support high-level cognition are shown to accompany cognitive decline at the behavioral level, which is commonly observed in the aging populations, even in the absence of disease. Although fMRI is useful for assessing functional changes in brain networks, its high costs and limited accessibility discourage studies that need large populations. In this study, we investigated the aging-effect on large-scale networks of the human brain using high-density electroencephalography and electrophysiological source imaging, which is a less costly and more accessible alternative to fMRI. In particular, our study examined a group of healthy subjects in the age range from middle- to older-aged adults, which is an under-studied range in the literature. Employing a high-resolution computation model, our results revealed age associations in the connectivity pattern of DMN in a consistent manner with previous fMRI findings. Particularly, in combination with a standard battery of cognitive tests, our data showed that in the posterior cingulate / precuneus area of DMN higher brain connectivity was associated with lower performance on an episodic memory task. The findings demonstrate the feasibility of using electrophysiological imaging to characterize large-scale brain networks and suggest that changes in network connectivity are associated with normal aging.
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Affiliation(s)
- Yuxuan Chen
- School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, United States
| | - Julia H Tang
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States
| | - Lisa A De Stefano
- Department of Psychology, University of Oklahoma, Norman, OK, United States; Graduate Program in Cellular and Behavioral Neurobiology, University of Oklahoma, Norman, OK, United States
| | - Michael J Wenger
- Department of Psychology, University of Oklahoma, Norman, OK, United States; Graduate Program in Cellular and Behavioral Neurobiology, University of Oklahoma, Norman, OK, United States
| | - Lei Ding
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States; Institute for Biomedical Engineering, Science, and Technology, University of Oklahoma, Norman, OK, United States
| | - Melissa A Craft
- Fran and Earl Ziegler College of Nursing, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Barbara W Carlson
- Fran and Earl Ziegler College of Nursing, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Han Yuan
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States; Institute for Biomedical Engineering, Science, and Technology, University of Oklahoma, Norman, OK, United States.
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34
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Physical activity and fitness moderate the association between executive function and anti-correlated networks in the aging brain. SPORT SCIENCES FOR HEALTH 2022. [DOI: 10.1007/s11332-021-00887-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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35
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Doucet GE, Hamlin N, West A, Kruse JA, Moser DA, Wilson TW. Multivariate patterns of brain-behavior associations across the adult lifespan. Aging (Albany NY) 2022; 14:161-194. [PMID: 35013005 PMCID: PMC8791210 DOI: 10.18632/aging.203815] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 12/20/2021] [Indexed: 11/25/2022]
Abstract
The nature of brain-behavior covariations with increasing age is poorly understood. In the current study, we used a multivariate approach to investigate the covariation between behavioral-health variables and brain features across adulthood. We recruited healthy adults aged 20–73 years-old (29 younger, mean age = 25.6 years; 30 older, mean age = 62.5 years), and collected structural and functional MRI (s/fMRI) during a resting-state and three tasks. From the sMRI, we extracted cortical thickness and subcortical volumes; from the fMRI, we extracted activation peaks and functional network connectivity (FNC) for each task. We conducted canonical correlation analyses between behavioral-health variables and the sMRI, or the fMRI variables, across all participants. We found significant covariations for both types of neuroimaging phenotypes (ps = 0.0004) across all individuals, with cognitive capacity and age being the largest opposite contributors. We further identified different variables contributing to the models across phenotypes and age groups. Particularly, we found behavior was associated with different neuroimaging patterns between the younger and older groups. Higher cognitive capacity was supported by activation and FNC within the executive networks in the younger adults, while it was supported by the visual networks’ FNC in the older adults. This study highlights how the brain-behavior covariations vary across adulthood and provides further support that cognitive performance relies on regional recruitment that differs between older and younger individuals.
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Affiliation(s)
- Gaelle E Doucet
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE 68010, USA.,Department of Pharmacology and Neuroscience, Creighton University School of Medicine, Omaha, NE 68178, USA
| | - Noah Hamlin
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE 68010, USA
| | - Anna West
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE 68010, USA
| | - Jordanna A Kruse
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE 68010, USA
| | - Dominik A Moser
- Institute of Psychology, University of Bern, Bern, Switzerland.,Child and Adolescent Psychiatry, University Hospital Lausanne, Lausanne, Switzerland
| | - Tony W Wilson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE 68010, USA.,Department of Pharmacology and Neuroscience, Creighton University School of Medicine, Omaha, NE 68178, USA
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36
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Sampedro F, Aracil-Bolaños I, Carmona I Farrés C, Soler J, Schmidt C, Elices M, Pomarol-Clotet E, Salvador R, Vega D, Pascual JC. A Functional Connectivity Study to Investigate the Role of the Right Anterior Insula in Modulating Emotional Dysfunction in Borderline Personality Disorder. Psychosom Med 2022; 84:64-73. [PMID: 34611112 DOI: 10.1097/psy.0000000000001019] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE Previous imaging studies in patients with borderline personality disorder (BPD) have detected functional brain dysfunctions. Mindfulness training may improve the symptoms of BPD, although the neural mechanisms involved remain poorly understood. This study had several key aims: a) to investigate the role of right anterior insula (rAI) functional connectivity in modulating baseline emotional status in BPD, b) to compare differences in connectivity changes after mindfulness training versus interpersonal effectiveness intervention, and c) to explore the correlation between longitudinal changes in imaging data and clinical indicators. METHODS Thirty-eight patients with BPD underwent resting-state functional magnetic resonance imaging. Participants completed self-report clinical scales and participated in a dialectical-behavioral therapy (mindfulness versus interpersonal effectiveness modules). Changes in clinical and imaging variables were evaluated longitudinally after completion of the first 10-week sessions of psychotherapeutic intervention. RESULTS At baseline, the rAI was strongly connected with the other salience network nodes and anticorrelated with most core nodes of the default mode network (p < .05, corrected). The functional connectivity of the rAI correlated with emotional dysregulation and deficits in mindfulness capacities (p < .05, corrected). After completion of psychotherapeutic intervention, both groups (mindfulness and interpersonal effectiveness) showed divergent posttherapy functional connectivity changes, which were in turn associated with the clinical response. CONCLUSIONS The functional connectivity of the rAI seems to play an important role in emotion dysregulation and deficits in mindfulness capacities in individuals with BPD. Psychotherapy seems to modulate this functional connectivity, leading to beneficial changes in clinical variables.
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Affiliation(s)
- Frederic Sampedro
- From the Centro de Investigación en Red-Enfermedades Neurodegenerativas (CIBERNED) (Sampedro, Aracil-Bolaños); Movement Disorders Unit, Neurology Department (Aracil-Bolaños), Hospital de la Santa Creu I Sant Pau, IIB-Sant Pau, and Department of Psychiatry (Carmona i Farrés, Soler, Schmidt, Elices, Pascual), Hospital de la Santa Creu I Sant Pau, IIB-Sant Pau, Barcelona; Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM (Carmona i Farrés, Soler, Elices, Pomarol-Clotet, Salvador, Pascual), Madrid; Institute Mar of Medical Research (IMIM) (Elices); Department of Psychiatry and Legal Medicine, Autonomous University of Barcelona, UAB (Soler, Vega, Pascual); FIDMAG Germanes Hospitalàries Research Foundation (Pomarol-Clotet, Salvador); and Servicio de Salud Mental, Hospital de Igualada (Vega), Consorci Sanitari de l'Anoia, Igualada, Barcelona, Spain
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37
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Bernard JA. Understanding cerebellar function through network perspectives: A review of resting-state connectivity of the cerebellum. PSYCHOLOGY OF LEARNING AND MOTIVATION 2022. [DOI: 10.1016/bs.plm.2022.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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38
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Hebling Vieira B, Dubois J, Calhoun VD, Garrido Salmon CE. A deep learning based approach identifies regions more relevant than resting-state networks to the prediction of general intelligence from resting-state fMRI. Hum Brain Mapp 2021; 42:5873-5887. [PMID: 34587333 PMCID: PMC8596958 DOI: 10.1002/hbm.25656] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 08/26/2021] [Accepted: 08/27/2021] [Indexed: 11/30/2022] Open
Abstract
Prediction of cognitive ability latent factors such as general intelligence from neuroimaging has elucidated questions pertaining to their neural origins. However, predicting general intelligence from functional connectivity limit hypotheses to that specific domain, being agnostic to time‐distributed features and dynamics. We used an ensemble of recurrent neural networks to circumvent this limitation, bypassing feature extraction, to predict general intelligence from resting‐state functional magnetic resonance imaging regional signals of a large sample (n = 873) of Human Connectome Project adult subjects. Ablating common resting‐state networks (RSNs) and measuring degradation in performance, we show that model reliance can be mostly explained by network size. Using our approach based on the temporal variance of saliencies, that is, gradients of outputs with regards to inputs, we identify a candidate set of networks that more reliably affect performance in the prediction of general intelligence than similarly sized RSNs. Our approach allows us to further test the effect of local alterations on data and the expected changes in derived metrics such as functional connectivity and instantaneous innovations.
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Affiliation(s)
- Bruno Hebling Vieira
- InBrain Lab, Departamento de Física, Universidade de São Paulo, Ribeirão Preto, Brazil.,Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
| | - Julien Dubois
- Cedars-Sinai Medical Center, Los Angeles, California, USA.,Caltech, Pasadena, California, USA
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA.,The Mind Research Network, Albuquerque, New Mexico, USA.,School of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
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39
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Aracil-Bolaños I, Martínez-Horta S, González-de-Echávarri JM, Sampedro F, Pérez-Pérez J, Horta A, Campolongo A, Izquierdo C, Gómez-Ansón B, Pagonabarraga J, Kulisevsky J. Structure and Dynamics of Large-Scale Cognitive Networks in Huntington's Disease. Mov Disord 2021; 37:343-353. [PMID: 34752656 DOI: 10.1002/mds.28839] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 09/10/2021] [Accepted: 10/04/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Huntington's disease is a neurodegenerative disorder characterized by clinical alterations in the motor, behavioral, and cognitive domains. However, the structure and disruptions to large-scale brain cognitive networks have not yet been established. OBJECTIVE We aimed to profile changes in large-scale cognitive networks in premanifest and symptomatic patients with Huntington's disease. METHODS We prospectively recruited premanifest and symptomatic Huntington's disease mutation carriers as well as healthy controls. Clinical and sociodemographic data were obtained from all participants, and resting-state functional connectivity data, using both time-averaged and dynamic functional connectivity, was acquired from whole-brain and cognitively oriented brain parcellations. RESULTS A total of 64 gene mutation carriers and 23 healthy controls were included; 21 patients with Huntington's disease were classified as premanifest and 43 as symptomatic Huntington's disease. Compared with healthy controls, patients with Huntington's disease showed decreased network connectivity within the posterior hubs of the default-mode network and the medial prefrontal cortex, changes that correlated with cognitive (t = 2.25, P = 0.01) and disease burden scores (t = -2.42, P = 0.009). The salience network showed decreased functional connectivity between insular and supramarginal cortices and also correlated with cognitive (t = 2.11, P = 0.02) and disease burden scores (t = -2.35, P = 0.01). Dynamic analyses showed that network variability was decreased for default-central executive networks, a feature already present in premanifest mutation carriers (dynamic factor 8, P = 0.02). CONCLUSIONS Huntington's disease shows an early and widespread disruption of large-scale cognitive networks. Importantly, these changes are related to cognitive and disease burden scores, and novel dynamic functional analyses uncovered subtler network changes even in the premanifest stages.
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Affiliation(s)
- Ignacio Aracil-Bolaños
- Movement Disorders Unit, Neurology Department, Sant Pau Hospital, Barcelona, Spain.,Departament de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain.,Institut d'Investigacions Biomèdiques-Sant Pau, Barcelona, Spain.,Centro de Investigación en Red-Enfermedades Neurodegenerativas, Madrid, Spain
| | - Saül Martínez-Horta
- Movement Disorders Unit, Neurology Department, Sant Pau Hospital, Barcelona, Spain.,Departament de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain.,Institut d'Investigacions Biomèdiques-Sant Pau, Barcelona, Spain.,Centro de Investigación en Red-Enfermedades Neurodegenerativas, Madrid, Spain
| | - Jose M González-de-Echávarri
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation and Hospital del Mar Medical Research Institute, Barcelona, Spain
| | - Frederic Sampedro
- Movement Disorders Unit, Neurology Department, Sant Pau Hospital, Barcelona, Spain.,Departament de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain.,Institut d'Investigacions Biomèdiques-Sant Pau, Barcelona, Spain.,Centro de Investigación en Red-Enfermedades Neurodegenerativas, Madrid, Spain
| | - Jesús Pérez-Pérez
- Movement Disorders Unit, Neurology Department, Sant Pau Hospital, Barcelona, Spain.,Departament de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain.,Institut d'Investigacions Biomèdiques-Sant Pau, Barcelona, Spain.,Centro de Investigación en Red-Enfermedades Neurodegenerativas, Madrid, Spain
| | - Andrea Horta
- Movement Disorders Unit, Neurology Department, Sant Pau Hospital, Barcelona, Spain.,Departament de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain.,Institut d'Investigacions Biomèdiques-Sant Pau, Barcelona, Spain.,Centro de Investigación en Red-Enfermedades Neurodegenerativas, Madrid, Spain
| | - Antonia Campolongo
- Movement Disorders Unit, Neurology Department, Sant Pau Hospital, Barcelona, Spain.,Departament de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain.,Institut d'Investigacions Biomèdiques-Sant Pau, Barcelona, Spain.,Centro de Investigación en Red-Enfermedades Neurodegenerativas, Madrid, Spain
| | - Cristina Izquierdo
- Movement Disorders Unit, Neurology Department, Sant Pau Hospital, Barcelona, Spain.,Departament de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain.,Institut d'Investigacions Biomèdiques-Sant Pau, Barcelona, Spain.,Centro de Investigación en Red-Enfermedades Neurodegenerativas, Madrid, Spain
| | - Beatriz Gómez-Ansón
- Departament de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain.,Institut d'Investigacions Biomèdiques-Sant Pau, Barcelona, Spain.,Centro de Investigación en Red-Enfermedades Neurodegenerativas, Madrid, Spain.,Neuroradiology Unit, Sant Pau Hospital, Barcelona, Spain
| | - Javier Pagonabarraga
- Movement Disorders Unit, Neurology Department, Sant Pau Hospital, Barcelona, Spain.,Departament de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain.,Institut d'Investigacions Biomèdiques-Sant Pau, Barcelona, Spain.,Centro de Investigación en Red-Enfermedades Neurodegenerativas, Madrid, Spain
| | - Jaime Kulisevsky
- Movement Disorders Unit, Neurology Department, Sant Pau Hospital, Barcelona, Spain.,Departament de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain.,Institut d'Investigacions Biomèdiques-Sant Pau, Barcelona, Spain.,Centro de Investigación en Red-Enfermedades Neurodegenerativas, Madrid, Spain
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Stripeikyte G, Potheegadoo J, Progin P, Rognini G, Blondiaux E, Salomon R, Griffa A, Hagmann P, Faivre N, Do KQ, Conus P, Blanke O. Fronto-Temporal Disconnection Within the Presence Hallucination Network in Psychotic Patients With Passivity Experiences. Schizophr Bull 2021; 47:1718-1728. [PMID: 33823042 PMCID: PMC8530400 DOI: 10.1093/schbul/sbab031] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Psychosis, characterized by hallucinations and delusions, is a common feature of psychiatric disease, especially schizophrenia. One prominent theory posits that psychosis is driven by abnormal sensorimotor predictions leading to the misattribution of self-related events. This misattribution has been linked to passivity experiences (PE), such as loss of agency and, more recently, to presence hallucinations (PH), defined as the conscious experience of the presence of an alien agent while no person is actually present. PH has been observed in schizophrenia, Parkinson's disease, and neurological patients with brain lesions and, recently, the brain mechanisms of PH (PH-network) have been determined comprising bilateral posterior middle temporal gyrus (pMTG), inferior frontal gyrus (IFG), and ventral premotor cortex (vPMC). Given that the experience of an alien agent is a common feature of PE, we here analyzed the functional connectivity within the PH-network in psychotic patients with (N = 39) vs without PE (N = 26). We observed reduced fronto-temporal functional connectivity in patients with PE compared to patients without PE between the right pMTG and the right and left IFG of the PH-network. Moreover, when seeding from these altered regions, we observed specific alterations with brain regions commonly linked to auditory-verbal hallucinations (such as Heschl's gyrus). The present connectivity findings within the PH-network extend the disconnection hypothesis for hallucinations to the specific case of PH and associates the PH-network with key brain regions for frequent psychotic symptoms such as auditory-verbal hallucinations, showing that PH are relevant to the study of the brain mechanisms of psychosis and PE.
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Affiliation(s)
- Giedre Stripeikyte
- Center for Neuroprosthetics, Swiss Federal Institute of Technology (EPFL), Geneva, Switzerland
- Brain Mind Institute, Faculty of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
| | - Jevita Potheegadoo
- Center for Neuroprosthetics, Swiss Federal Institute of Technology (EPFL), Geneva, Switzerland
- Brain Mind Institute, Faculty of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
| | - Pierre Progin
- Center for Neuroprosthetics, Swiss Federal Institute of Technology (EPFL), Geneva, Switzerland
- Brain Mind Institute, Faculty of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
- Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV), University of Lausanne (UNIL), Lausanne, Switzerland
| | - Giulio Rognini
- Center for Neuroprosthetics, Swiss Federal Institute of Technology (EPFL), Geneva, Switzerland
- Brain Mind Institute, Faculty of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
| | - Eva Blondiaux
- Center for Neuroprosthetics, Swiss Federal Institute of Technology (EPFL), Geneva, Switzerland
- Brain Mind Institute, Faculty of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
| | - Roy Salomon
- Gonda Brain Research Center, Bar Ilan University (BIU), Ramat-Gan, Israel
| | - Alessandra Griffa
- Center for Neuroprosthetics, Swiss Federal Institute of Technology (EPFL), Geneva, Switzerland
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Patric Hagmann
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Nathan Faivre
- Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LPNC, 38000, Grenoble, France
| | - Kim Q Do
- Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV), University of Lausanne (UNIL), Lausanne, Switzerland
- Center for Psychiatric Neuroscience, Centre Hospitalier Universitaire Vaudois (CHUV), University of Lausanne (UNIL), Lausanne, Switzerland
| | - Philippe Conus
- Department of Psychiatry, Centre Hospitalier Universitaire Vaudois (CHUV), University of Lausanne (UNIL), Lausanne, Switzerland
| | - Olaf Blanke
- Center for Neuroprosthetics, Swiss Federal Institute of Technology (EPFL), Geneva, Switzerland
- Brain Mind Institute, Faculty of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
- Department of Neurology, University Hospital, Geneva, Switzerland
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41
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Wu C, Matias C, Foltynie T, Limousin P, Zrinzo L, Akram H. Dynamic Network Connectivity Reveals Markers of Response to Deep Brain Stimulation in Parkinson's Disease. Front Hum Neurosci 2021; 15:729677. [PMID: 34690721 PMCID: PMC8526554 DOI: 10.3389/fnhum.2021.729677] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 07/19/2021] [Indexed: 01/10/2023] Open
Abstract
Background: Neuronal loss in Parkinson's Disease (PD) leads to widespread neural network dysfunction. While graph theory allows for analysis of whole brain networks, patterns of functional connectivity (FC) associated with motor response to deep brain stimulation of the subthalamic nucleus (STN-DBS) have yet to be explored. Objective/Hypothesis: To investigate the distributed network properties associated with STN-DBS in patients with advanced PD. Methods: Eighteen patients underwent 3-Tesla resting state functional MRI (rs-fMRI) prior to STN-DBS. Improvement in UPDRS-III scores following STN-DBS were assessed 1 year after implantation. Independent component analysis (ICA) was applied to extract spatially independent components (ICs) from the rs-fMRI. FC between ICs was calculated across the entire time series and for dynamic brain states. Graph theory analysis was performed to investigate whole brain network topography in static and dynamic states. Results: Dynamic analysis identified two unique brain states: a relative hypoconnected state and a relative hyperconnected state. Time spent in a state, dwell time, and number of transitions were not correlated with DBS response. There were no significant FC findings, but graph theory analysis demonstrated significant relationships with STN-DBS response only during the hypoconnected state - STN-DBS was negatively correlated with network assortativity. Conclusion: Given the widespread effects of dopamine depletion in PD, analysis of whole brain networks is critical to our understanding of the pathophysiology of this disease. Only by leveraging graph theoretical analysis of dynamic FC were we able to isolate a hypoconnected brain state that contained distinct network properties associated with the clinical effects of STN-DBS.
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Affiliation(s)
- Chengyuan Wu
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, PA, United States
- Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, PA, United States
| | - Caio Matias
- Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, PA, United States
| | - Thomas Foltynie
- Unit of Functional Neurosurgery, UCL Institute of Neurology, London, United Kingdom
| | - Patricia Limousin
- Unit of Functional Neurosurgery, UCL Institute of Neurology, London, United Kingdom
| | - Ludvic Zrinzo
- Unit of Functional Neurosurgery, UCL Institute of Neurology, London, United Kingdom
- Victor Horsley Department of Neurosurgery, The National Hospital for Neurology and Neurosurgery, London, United Kingdom
| | - Harith Akram
- Unit of Functional Neurosurgery, UCL Institute of Neurology, London, United Kingdom
- Victor Horsley Department of Neurosurgery, The National Hospital for Neurology and Neurosurgery, London, United Kingdom
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42
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Bernard JA, Ballard HK, Jackson TB. Cerebellar Dentate Connectivity across Adulthood: A Large-Scale Resting State Functional Connectivity Investigation. Cereb Cortex Commun 2021; 2:tgab050. [PMID: 34527949 PMCID: PMC8436571 DOI: 10.1093/texcom/tgab050] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2021] [Revised: 06/20/2021] [Accepted: 07/19/2021] [Indexed: 12/23/2022] Open
Abstract
Cerebellar contributions to behavior in advanced age are of interest and importance, given its role in motor and cognitive performance. There are differences and declines in cerebellar structure in advanced age and cerebellar resting state connectivity is lower. However, the work on this area to date has focused on the cerebellar cortex. The deep cerebellar nuclei provide the primary cerebellar inputs and outputs to the cortex, as well as the spinal and vestibular systems. Dentate networks can be dissociated such that the dorsal region is associated with the motor cortex, whereas the ventral aspect is associated with the prefrontal cortex. However, whether dentato-thalamo-cortical networks differ across adulthood remains unknown. Here, using a large adult sample (n = 590) from the Cambridge Center for Ageing and Neuroscience, we investigated dentate connectivity across adulthood. We replicated past work showing dissociable resting state networks in the dorsal and ventral aspects of the dentate. In both seeds, we demonstrated that connectivity is lower with advanced age, indicating that connectivity differences extend beyond the cerebellar cortex. Finally, we demonstrated sex differences in dentate connectivity. This expands our understanding of cerebellar circuitry in advanced age and underscores the potential importance of this structure in age-related performance differences.
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Affiliation(s)
- Jessica A Bernard
- Department of Psychological and Brain Sciences, Texas A&M University, College Station, TX 77843, USA
| | - Hannah K Ballard
- Texas A&M Institute for Neuroscience, Texas A&M University, College Station, TX 77843, USA
| | - Trevor Bryan Jackson
- Department of Psychological and Brain Sciences, Texas A&M University, College Station, TX 77843, USA
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43
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Martin S, Saur D, Hartwigsen G. Age-Dependent Contribution of Domain-General Networks to Semantic Cognition. Cereb Cortex 2021; 32:870-890. [PMID: 34464442 PMCID: PMC8841593 DOI: 10.1093/cercor/bhab252] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 06/30/2021] [Accepted: 07/02/2021] [Indexed: 11/13/2022] Open
Abstract
Aging is characterized by a decline of cognitive control. In semantic cognition, this leads to the paradox that older adults usually show poorer task performance than young adults despite their greater semantic knowledge. So far, the underlying neural changes of these behavioral differences are poorly understood. In the current neuroimaging study, we investigated the interaction of domain-specific and domain-general networks during verbal semantic fluency in young and older adults. Across age groups, task processing was characterized by a strong positive integration within the multiple-demand as well as between the multiple-demand and the default mode network during semantic fluency. However, the behavioral relevance of strengthened connectivity differed between groups: While within-network functional connectivity in both networks predicted greater efficiency in semantic fluency in young adults, it was associated with slower performance in older adults. Moreover, only young adults profited from connectivity between networks for their semantic memory performance. Our results suggest that the functional coupling of usually anticorrelated networks is critical for successful task processing, independent of age, when access to semantic memory is required. Furthermore, our findings lend novel support to the notion of reduced efficiency in the aging brain due to neural dedifferentiation in semantic cognition.
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Affiliation(s)
- Sandra Martin
- Lise Meitner Research Group Cognition and Plasticity, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany.,Language & Aphasia Laboratory, Department of Neurology, University of Leipzig Medical Center, 04103 Leipzig, Germany
| | - Dorothee Saur
- Language & Aphasia Laboratory, Department of Neurology, University of Leipzig Medical Center, 04103 Leipzig, Germany
| | - Gesa Hartwigsen
- Lise Meitner Research Group Cognition and Plasticity, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany
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44
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Sevinc G, Rusche J, Wong B, Datta T, Kaufman R, Gutz SE, Schneider M, Todorova N, Gaser C, Thomalla G, Rentz D, Dickerson BD, Lazar SW. Mindfulness Training Improves Cognition and Strengthens Intrinsic Connectivity Between the Hippocampus and Posteromedial Cortex in Healthy Older Adults. Front Aging Neurosci 2021; 13:702796. [PMID: 34512305 PMCID: PMC8430251 DOI: 10.3389/fnagi.2021.702796] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 08/09/2021] [Indexed: 01/02/2023] Open
Abstract
Maintaining optimal cognitive functioning throughout the lifespan is a public health priority. Evaluation of cognitive outcomes following interventions to promote and preserve brain structure and function in older adults, and associated neural mechanisms, are therefore of critical importance. In this randomized controlled trial, we examined the behavioral and neural outcomes following mindfulness training (n = 72), compared to a cognitive fitness program (n = 74) in healthy, cognitively normal, older adults (65-80 years old). To assess cognitive functioning, we used the Preclinical Alzheimer Cognitive Composite (PACC), which combines measures of episodic memory, executive function, and global cognition. We hypothesized that mindfulness training would enhance cognition, increase intrinsic functional connectivity measured with magnetic resonance imaging (MRI) between the hippocampus and posteromedial cortex, as well as promote increased gray matter volume within those regions. Following the 8-week intervention, the mindfulness training group showed improved performance on the PACC, while the control group did not. Furthermore, following mindfulness training, greater improvement on the PACC was associated with a larger increase in intrinsic connectivity within the default mode network, particularly between the right hippocampus and posteromedial cortex and between the left hippocampus and lateral parietal cortex. The cognitive fitness training group did not show such effects. These findings demonstrate that mindfulness training improves cognitive performance in cognitively intact older individuals and strengthens connectivity within the default mode network, which is particularly vulnerable to aging affects. Clinical Trial Registration: [https://clinicaltrials.gov/ct2/show/NCT02628548], identifier [NCT02628548].
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Affiliation(s)
- Gunes Sevinc
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Johann Rusche
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- Kopf- und Neurozentrum, Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Bonnie Wong
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Tanya Datta
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Robert Kaufman
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Sarah E. Gutz
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- Program in Speech and Hearing Bioscience and Technology, Harvard Medical School, Boston, MA, United States
| | - Marissa Schneider
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Nevyana Todorova
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- Department of Behavioral Neuroscience, College of Science, Northeastern University, Boston, MA, United States
| | - Christian Gaser
- Department of Psychiatry and Neurology, Jena University Hospital, Jena, Germany
| | - Götz Thomalla
- Kopf- und Neurozentrum, Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Dorene Rentz
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Bradford D. Dickerson
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Sara W. Lazar
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
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45
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Soshi T, Andersson M, Kawagoe T, Nishiguchi S, Yamada M, Otsuka Y, Nakai R, Abe N, Aslah A, Igasaki T, Sekiyama K. Prefrontal Plasticity after a 3-Month Exercise Intervention in Older Adults Relates to Enhanced Cognitive Performance. Cereb Cortex 2021; 31:4501-4517. [PMID: 34009242 DOI: 10.1093/cercor/bhab102] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Revised: 03/29/2021] [Accepted: 03/30/2021] [Indexed: 01/24/2023] Open
Abstract
This study examined exercise intervention effects on older adults' brain structures and function. Brain data were analyzed from 47 healthy adults between 61 and 82 years of age who, in a previous study, showed cognitive improvement following a 3-month intervention. The participants were assigned to a motor exercise intervention group (n = 24), performing exercise training programs for a 12-week period, or a waiting control group (n = 23), abstaining from any exercise program. Structural analysis of the frontal cortex and hippocampus revealed increased gray matter volume and/or thickness in several prefrontal areas in the intervention group and reduced hippocampal gray matter volume in the control group. Importantly, the volume increase in the middle frontal sulcus in the intervention group was associated with a general cognitive improvement after the intervention. Functional analysis showed that the prefrontal functional connectivity during a working memory task differently changed in response to the intervention or waiting in the two groups. The functional connectivity decreased in the intervention group, whereas the corresponding connectivity increased in the control group, which was associated with maintaining cognitive performance. The current longitudinal findings indicate that short-term exercise intervention can induce prefrontal plasticity associated with cognitive performance in older adults.
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Affiliation(s)
- Takahiro Soshi
- Graduate School of Advanced Integrated Studies in Human Survivability, Kyoto University, Sakyo-ku, Kyoto 606-8306, Japan
| | | | - Toshikazu Kawagoe
- College of Contemporary Psychology, Rikkyo University, Niiza, Saitama 352-8558, Japan
| | - Shu Nishiguchi
- NTT DATA Institute of Management Consulting, Inc., Chiyoda-ku, Tokyo 102-0093, Japan
| | - Minoru Yamada
- Graduate School of Comprehensive Human Sciences, University of Tsukuba, Bunkyo-ku, Tokyo 112-0012, Japan
| | - Yuki Otsuka
- Kokoro Research Center, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan
| | - Ryusuke Nakai
- Kokoro Research Center, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan
| | - Nobuhito Abe
- Kokoro Research Center, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan
| | - Adibah Aslah
- Department of Human and Environmental Informatics, Kumamoto University, Chuo-ku, kumamoto 860-8555, Japan
| | - Tomohiko Igasaki
- Department of Human and Environmental Informatics, Kumamoto University, Chuo-ku, kumamoto 860-8555, Japan
| | - Kaoru Sekiyama
- Graduate School of Advanced Integrated Studies in Human Survivability, Kyoto University, Sakyo-ku, Kyoto 606-8306, Japan
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46
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Gorbach T, Lundquist A, de Luna X, Nyberg L, Salami A. A Hierarchical Bayesian Mixture Model Approach for Analysis of Resting-State Functional Brain Connectivity: An Alternative to Thresholding. Brain Connect 2021; 10:202-211. [PMID: 32308015 PMCID: PMC7310299 DOI: 10.1089/brain.2020.0740] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
This article proposes a Bayesian hierarchical mixture model to analyze functional brain connectivity where mixture components represent “positively connected” and “non-connected” brain regions. Such an approach provides a data-informed separation of reliable and spurious connections in contrast to arbitrary thresholding of a connectivity matrix. The hierarchical structure of the model allows simultaneous inferences for the entire population as well as for each individual subject. A new connectivity measure, the posterior probability of a given pair of brain regions of a specific subject to be connected given the observed correlation of regions' activity, can be computed from the model fit. The posterior probability reflects the connectivity of a pair of regions relative to the overall connectivity pattern of an individual, which is overlooked in traditional correlation analyses. This article demonstrates that using the posterior probability might diminish the effect of spurious connections on inferences, which is present when a correlation is used as a connectivity measure. In addition, simulation analyses reveal that the sparsification of the connectivity matrix using the posterior probabilities might outperform the absolute thresholding based on correlations. Therefore, we suggest that posterior probability might be a beneficial measure of connectivity compared with the correlation. The applicability of the introduced method is exemplified by a study of functional resting-state brain connectivity in older adults.
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Affiliation(s)
- Tetiana Gorbach
- Department of Statistics, Umeå School of Business, Economics and Statistics, Umeå University, Umeå, Sweden.,Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden.,Department of Integrative Medical Biology, Umeå University, Umeå, Sweden
| | - Anders Lundquist
- Department of Statistics, Umeå School of Business, Economics and Statistics, Umeå University, Umeå, Sweden.,Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Xavier de Luna
- Department of Statistics, Umeå School of Business, Economics and Statistics, Umeå University, Umeå, Sweden
| | - Lars Nyberg
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden.,Department of Radiation Sciences, Umeå University, Umeå, Sweden.,Department of Integrative Medical Biology, Umeå University, Umeå, Sweden
| | - Alireza Salami
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden.,Department of Radiation Sciences, Umeå University, Umeå, Sweden.,Department of Integrative Medical Biology, Umeå University, Umeå, Sweden.,Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden.,Wallenberg Centre for Molecular Medicine, Umeå University, Umeå, Sweden
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47
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Xifra-Porxas A, Kassinopoulos M, Mitsis GD. Physiological and motion signatures in static and time-varying functional connectivity and their subject identifiability. eLife 2021; 10:e62324. [PMID: 34342582 PMCID: PMC8378847 DOI: 10.7554/elife.62324] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Accepted: 08/02/2021] [Indexed: 02/06/2023] Open
Abstract
Human brain connectivity yields significant potential as a noninvasive biomarker. Several studies have used fMRI-based connectivity fingerprinting to characterize individual patterns of brain activity. However, it is not clear whether these patterns mainly reflect neural activity or the effect of physiological and motion processes. To answer this question, we capitalize on a large data sample from the Human Connectome Project and rigorously investigate the contribution of the aforementioned processes on functional connectivity (FC) and time-varying FC, as well as their contribution to subject identifiability. We find that head motion, as well as heart rate and breathing fluctuations, induce artifactual connectivity within distinct resting-state networks and that they correlate with recurrent patterns in time-varying FC. Even though the spatiotemporal signatures of these processes yield above-chance levels in subject identifiability, removing their effects at the preprocessing stage improves identifiability, suggesting a neural component underpinning the inter-individual differences in connectivity.
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Affiliation(s)
- Alba Xifra-Porxas
- Graduate Program in Biological and Biomedical Engineering, McGill University, Montréal, Canada
| | - Michalis Kassinopoulos
- Graduate Program in Biological and Biomedical Engineering, McGill University, Montréal, Canada
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48
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Snyder W, Uddin LQ, Nomi JS. Dynamic functional connectivity profile of the salience network across the life span. Hum Brain Mapp 2021; 42:4740-4749. [PMID: 34312945 PMCID: PMC8410581 DOI: 10.1002/hbm.25581] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 06/07/2021] [Accepted: 06/23/2021] [Indexed: 12/16/2022] Open
Abstract
The insular cortex and anterior cingulate cortex together comprise the salience or midcingulo-insular network, involved in detecting salient events and initiating control signals to mediate brain network dynamics. The extent to which functional coupling between the salience network and the rest of the brain undergoes changes due to development and aging is at present largely unexplored. Here, we examine dynamic functional connectivity (dFC) of the salience network in a large life span sample (n = 601; 6-85 years old). A sliding-window analysis and k-means clustering revealed five states of dFC formed with the salience network, characterized by either widespread asynchrony or different patterns of synchrony between the salience network and other brain regions. We determined the frequency, dwell time, total transitions, and specific state-to-state transitions for each state and subject, regressing the metrics with subjects' age to identify life span trends. A dynamic state characterized by low connectivity between the salience network and the rest of the brain had a strong positive quadratic relationship between age and both frequency and dwell time. Additional frequency, dwell time, total transitions, and state-to-state transition trends were observed with other salience network states. Our results highlight the metastable dynamics of the salience network and its role in the maturation of brain regions critical for cognition.
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Affiliation(s)
- William Snyder
- Program in Neuroscience, Bucknell University, Lewisburg, Pennsylvania
| | - Lucina Q Uddin
- Department of Psychology, University of Miami, Coral Gables, Florida.,Neuroscience Program, University of Miami Miller School of Medicine, Miami, Florida
| | - Jason S Nomi
- Department of Psychology, University of Miami, Coral Gables, Florida
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49
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Chen K, Li C, Sun W, Tao Y, Wang R, Hou W, Liu DQ. Hidden Markov Modeling Reveals Prolonged "Baseline" State and Shortened Antagonistic State across the Adult Lifespan. Cereb Cortex 2021; 32:439-453. [PMID: 34255827 DOI: 10.1093/cercor/bhab220] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 06/10/2021] [Accepted: 06/11/2021] [Indexed: 12/21/2022] Open
Abstract
The brain networks undergo functional reorganization across the whole lifespan, but the dynamic patterns behind the reorganization remain largely unclear. This study models the dynamics of spontaneous activity of large-scale networks using hidden Markov model (HMM), and investigates how it changes with age on two adult lifespan datasets of 176/157 subjects (aged 20-80 years). Results for both datasets showed that 1) older adults tended to spend less time on a state where default mode network (DMN) and attentional networks show antagonistic activity, 2) older adults spent more time on a "baseline" state with moderate-level activation of all networks, accompanied with lower transition probabilities from this state to the others and higher transition probabilities from the others to this state, and 3) HMM exhibited higher sensitivity in uncovering the age effects compared with temporal clustering method. Our results suggest that the aging brain is characterized by the shortening of the antagonistic instances between DMN and attention systems, as well as the prolongation of the inactive period of all networks, which might reflect the shift of the dynamical working point near criticality in older adults.
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Affiliation(s)
- Keyu Chen
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian 116029, China.,Key Laboratory of Brain and Cognitive Neuroscience, Dalian 116029, Liaoning Province, China
| | - Chaofan Li
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian 116029, China.,Key Laboratory of Brain and Cognitive Neuroscience, Dalian 116029, Liaoning Province, China
| | - Wei Sun
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian 116029, China.,Key Laboratory of Brain and Cognitive Neuroscience, Dalian 116029, Liaoning Province, China
| | - Yunyun Tao
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian 116029, China.,Key Laboratory of Brain and Cognitive Neuroscience, Dalian 116029, Liaoning Province, China
| | - Ruidi Wang
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian 116029, China.,Key Laboratory of Brain and Cognitive Neuroscience, Dalian 116029, Liaoning Province, China
| | - Wen Hou
- School of Mathematics, Liaoning Normal University, Dalian 116029, China
| | - Dong-Qiang Liu
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian 116029, China.,Key Laboratory of Brain and Cognitive Neuroscience, Dalian 116029, Liaoning Province, China
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50
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Podgórski P, Waliszewska-Prosół M, Zimny A, Sąsiadek M, Bladowska J. Resting-State Functional Connectivity of the Ageing Female Brain-Differences Between Young and Elderly Female Adults on Multislice Short TR rs-fMRI. Front Neurol 2021; 12:645974. [PMID: 34322076 PMCID: PMC8311596 DOI: 10.3389/fneur.2021.645974] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Accepted: 05/25/2021] [Indexed: 11/22/2022] Open
Abstract
Introduction: Age-related brain changes are one of the most important world health problems due to the rising lifespan and size of the elderly populations. The aim of the study was to assess the effect of ageing in women on coordinated brain activity between eight resting-state networks. Material and Methods: The study group comprised 60 healthy female volunteers who were divided into two age groups: younger women (aged 20–30 n = 30) and older women (aged 55–80 n = 30). Resting-state data were collected during a 15 min scan in the eyes-closed condition using a 3T MR scanner. Data were preprocessed and analysed using the CONN toolbox version 19.c. The large-scale network analysis included a priori selected regions of interest of the default mode, the sensorimotor, the visual, the salience, the dorsal attention, the fronto-parietal, the language, and the cerebellar network. Results: Within the visual, the default mode, the salience, and the sensorimotor network, the intra-network resting-state functional connectivity (RSFC) was significantly higher with increasing age. There was also a significant increase in the inter-network RSFC in older females compared to young females found in the following networks: sensorimotor lateral and salience, salience and language, salience and fronto-parietal, cerebellar anterior and default mode, cerebellar posterior and default mode, visual and sensorimotor lateral, visual and sensorimotor, visual lateral and default mode, language and cerebellar anterior, language and cerebellar posterior, fronto-parietal and cerebellar anterior, dorsal attention and sensorimotor, dorsal attention and default mode, sensorimotor superior, and salience. Compared to young females, elderly women presented bilaterally significantly lower inter-network RSFC of the salience supramarginal gyrus and cerebellar posterior, sensorimotor lateral, and cerebellar anterior network, and sensorimotor lateral and cerebellar posterior as well as sensorimotor superior and cerebellar posterior network. Conclusion: Increased RSFC between some brain networks including the visual, the default mode, the salience, the sensorimotor, the language, the fronto-parietal, the dorsal attention, and the cerebellar networks in elderly females may function as a compensation mechanism during the ageing process of the brain. To the best of our knowledge, this study is the first to report the importance of increase of cerebellar networks RSFC during healthy female ageing.
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Affiliation(s)
- Przemysław Podgórski
- Department of General and Interventional Radiology and Neuroradiology, Wroclaw Medical University, Wrocław, Poland
| | | | - Anna Zimny
- Department of General and Interventional Radiology and Neuroradiology, Wroclaw Medical University, Wrocław, Poland
| | - Marek Sąsiadek
- Department of General and Interventional Radiology and Neuroradiology, Wroclaw Medical University, Wrocław, Poland
| | - Joanna Bladowska
- Department of General and Interventional Radiology and Neuroradiology, Wroclaw Medical University, Wrocław, Poland
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