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Guan Y, Li J, Wei Y, Shi PT, Yang C, Yun X, Quan Q, Wang WJ, Yu XG, Wei M. Brain functional connectivity alterations in patients with anterior cruciate ligament injury. Brain Res 2024; 1836:148956. [PMID: 38657888 DOI: 10.1016/j.brainres.2024.148956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 04/16/2024] [Accepted: 04/21/2024] [Indexed: 04/26/2024]
Abstract
Recent advancements in neuroimaging have illustrated that anterior cruciate ligament (ACL) injuries could impact the central nervous system (CNS), causing neuroplastic changes in the brain beyond the traditionally understood biomechanical consequences. While most of previous functional magnetic resonance imaging (fMRI) studies have focused on localized cortical activity changes post-injury, emerging research has suggested disruptions in functional connectivity across the brain. However, these prior investigations, albeit pioneering, have been constrained by two limitations: a reliance on small-sample participant cohorts, often limited to two to three patients, potentially limiting the generalizability of findings, and an adherence to region of interest based analysis, which may overlook broader network interactions. To address these limitations, our study employed resting-state fMRI to assess whole-brain functional connectivity in 15 ACL-injured patients, comparing them to matched controls using two distinct network analysis methods. Using Network-Based Statistics, we identified widespread reductions in connectivity that spanned across multiple brain regions. Further modular connectivity analysis showed significant decreases in inter-modular connectivity between the sensorimotor and cerebellar modules, and intra-modular connectivity within the default-mode network in ACL-injured patients. Our results thus highlight a shift from localized disruptions to network-wide dysfunctions, suggesting that ACL injuries induce widespread CNS changes. This enhanced understanding has the potential to stimulate the development of strategies aiming to restore functional connectivity and improve recovery outcomes.
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Affiliation(s)
- Yu Guan
- Department of Orthopedics, The Fourth Medical Center, Chinese PLA General Hospital, Beijing 100142, China; Medical School of Chinese PLA, Beijing 100853, China
| | - Ji Li
- Department of Orthopedics, The Fourth Medical Center, Chinese PLA General Hospital, Beijing 100142, China
| | - Yu Wei
- Department of Orthopedics, The Fourth Medical Center, Chinese PLA General Hospital, Beijing 100142, China
| | - Peng-Tao Shi
- Department of Orthopedics, The Fourth Medical Center, Chinese PLA General Hospital, Beijing 100142, China; Medical School of Chinese PLA, Beijing 100853, China
| | - Chen Yang
- Department of Orthopedics, The Fourth Medical Center, Chinese PLA General Hospital, Beijing 100142, China; Medical School of Chinese PLA, Beijing 100853, China
| | - Xing Yun
- Department of Orthopedics, The Fourth Medical Center, Chinese PLA General Hospital, Beijing 100142, China; Medical School of Chinese PLA, Beijing 100853, China
| | - Qi Quan
- Department of Orthopedics, The Fourth Medical Center, Chinese PLA General Hospital, Beijing 100142, China; Department of Orthopedic Surgery, Key Laboratory of Musculoskeletal Trauma &War Injuries PLA, Beijing Key Lab of Regenerative Medicine in Orthopedics, Chinese PLA General Hospital, Beijing 100853, China
| | - Wen-Juan Wang
- Department of Orthopedics, The Fourth Medical Center, Chinese PLA General Hospital, Beijing 100142, China
| | - Xin-Guang Yu
- Department of Neurosurgery, The First Medical Center, Chinese PLA General Hospital, Beijing 100853, China
| | - Min Wei
- Department of Orthopedics, The Fourth Medical Center, Chinese PLA General Hospital, Beijing 100142, China; Medical School of Chinese PLA, Beijing 100853, China.
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Kommula Y, Callow DD, Purcell JJ, Smith JC. Acute Exercise Improves Large-Scale Brain Network Segregation in Healthy Older Adults. Brain Connect 2024. [PMID: 38888008 DOI: 10.1089/brain.2024.0003] [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: 06/20/2024] Open
Abstract
Introduction: Age-related cognitive decline and mental health problems are accompanied by changes in resting-state functional connectivity (rsFC) indices, such as reduced brain network segregation. Meanwhile, exercise can improve cognition, mood, and neural network function in older adults. Studies on effects of exercise on rsFC outcomes in older adults have chiefly focused on changes after exercise training and suggest improved network segregation through enhanced within-network connectivity. However, effects of acute exercise on rsFC measures of neural network integrity in older adults, which presumably underlie changes observed after exercise training, have received less attention. In this study, we hypothesized that acute exercise in older adults would improve functional segregation of major cognition and affect-related brain networks. Methods: To test this, we analyzed rsFC data from 37 healthy and physically active older adults after they completed 30 min of moderate-to-vigorous intensity cycling and after they completed a seated rest control condition. Conditions were performed in a counterbalanced order across separate days in a within-subject crossover design. We considered large-scale brain networks associated with cognition and affect, including the frontoparietal network (FPN), salience network (SAL), default mode network (DMN), and affect-reward network (ARN). Results: We observed that after acute exercise, there was greater segregation between SAL and DMN, as well as greater segregation between SAL and ARN. Conclusion: These findings indicate that acute exercise in active older adults alters rsFC measures in key cognition and affect-related networks in a manner that opposes age-related dedifferentiation of neural networks that may be detrimental to cognition and mental health.
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Affiliation(s)
- Yash Kommula
- Department of Kinesiology, School of Public Health, University of Maryland, College Park, Maryland, USA
- Program in Neuroscience and Cognitive Science, University of Maryland, College Park, Maryland, USA
| | - Daniel D Callow
- Department of Kinesiology, School of Public Health, University of Maryland, College Park, Maryland, USA
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Jeremy J Purcell
- Department of Kinesiology, School of Public Health, University of Maryland, College Park, Maryland, USA
- Maryland Neuroimaging Center, University of Maryland, College Park, Maryland, USA
| | - J Carson Smith
- Department of Kinesiology, School of Public Health, University of Maryland, College Park, Maryland, USA
- Program in Neuroscience and Cognitive Science, University of Maryland, College Park, Maryland, USA
- Maryland Neuroimaging Center, University of Maryland, College Park, Maryland, USA
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Prince JB, Davis HL, Tan J, Muller-Townsend K, Markovic S, Lewis DMG, Hastie B, Thompson MB, Drummond PD, Fujiyama H, Sohrabi HR. Cognitive and neuroscientific perspectives of healthy ageing. Neurosci Biobehav Rev 2024; 161:105649. [PMID: 38579902 DOI: 10.1016/j.neubiorev.2024.105649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 03/17/2024] [Accepted: 03/30/2024] [Indexed: 04/07/2024]
Abstract
With dementia incidence projected to escalate significantly within the next 25 years, the United Nations declared 2021-2030 the Decade of Healthy Ageing, emphasising cognition as a crucial element. As a leading discipline in cognition and ageing research, psychology is well-equipped to offer insights for translational research, clinical practice, and policy-making. In this comprehensive review, we discuss the current state of knowledge on age-related changes in cognition and psychological health. We discuss cognitive changes during ageing, including (a) heterogeneity in the rate, trajectory, and characteristics of decline experienced by older adults, (b) the role of cognitive reserve in age-related cognitive decline, and (c) the potential for cognitive training to slow this decline. We also examine ageing and cognition through multiple theoretical perspectives. We highlight critical unresolved issues, such as the disparate implications of subjective versus objective measures of cognitive decline and the insufficient evaluation of cognitive training programs. We suggest future research directions, and emphasise interdisciplinary collaboration to create a more comprehensive understanding of the factors that modulate cognitive ageing.
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Affiliation(s)
- Jon B Prince
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia.
| | - Helen L Davis
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia
| | - Jane Tan
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia
| | - Katrina Muller-Townsend
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia
| | - Shaun Markovic
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia; Discipline of Psychology, Counselling and Criminology, Edith Cowan University, WA, Australia
| | - David M G Lewis
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia
| | | | - Matthew B Thompson
- School of Psychology, Murdoch University, WA, Australia; Centre for Biosecurity and One Health, Harry Butler Institute, Murdoch University, WA, Australia
| | - Peter D Drummond
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia
| | - Hakuei Fujiyama
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia; Centre for Molecular Medicine and Innovative Therapeutics, Murdoch University, WA, Australia
| | - Hamid R Sohrabi
- School of Psychology, Murdoch University, WA, Australia; Centre for Healthy Ageing, Health Futures Institute, Murdoch University, WA, Australia; School of Medical and Health Sciences, Edith Cowan University, WA, Australia; Department of Biomedical Sciences, Macquarie University, NSW, Australia.
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Sato SD, Shah VA, Fettrow T, Hall KG, Tays GD, Cenko E, Roy A, Clark DJ, Ferris DP, Hass CJ, Manini TM, Seidler RD. Resting state brain network segregation is associated with walking speed and working memory in older adults. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.07.592861. [PMID: 38766046 PMCID: PMC11100712 DOI: 10.1101/2024.05.07.592861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Older adults exhibit larger individual differences in walking ability and cognitive function than young adults. Characterizing intrinsic brain connectivity differences in older adults across a wide walking performance spectrum may provide insight into the mechanisms of functional decline in some older adults and resilience in others. Thus, the objectives of this study were to: (1) determine whether young adults and high- and low-functioning older adults show group differences in brain network segregation, and (2) determine whether network segregation is associated with working memory and walking function in these groups. The analysis included 21 young adults and 81 older adults. Older adults were further categorized according to their physical function using a standardized assessment; 54 older adults had low physical function while 27 were considered high functioning. Structural and functional resting state magnetic resonance images were collected using a Siemens Prisma 3T scanner. Working memory was assessed with the NIH Toolbox list sorting test. Walking speed was assessed with a 400 m-walk test at participants' self-selected speed. We found that network segregation in mobility-related networks (sensorimotor, vestibular, and visual networks) was higher in younger adults compared to older adults. There were no group differences in laterality effects on network segregation. We found multivariate associations between working memory and walking speed with network segregation scores. Higher right anterior cingulate cortex network segregation was associated with higher working memory function. Higher right sensorimotor, right vestibular, right anterior cingulate cortex, and lower left anterior cingulate cortex network segregation was associated with faster walking speed. These results are unique and significant because they demonstrate higher network segregation is largely related to higher physical function and not age alone.
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Affiliation(s)
- Sumire D Sato
- Department of Applied Kinesiology and Physiology, University of Florida, Gainesville, FL, USA
| | - Valay A Shah
- Department of Applied Kinesiology and Physiology, University of Florida, Gainesville, FL, USA
| | - Tyler Fettrow
- Department of Applied Kinesiology and Physiology, University of Florida, Gainesville, FL, USA
- NASA Langley Research Center, Hampton, VA, USA
| | - Kristina G Hall
- Department of Applied Kinesiology and Physiology, University of Florida, Gainesville, FL, USA
| | - Grant D Tays
- Department of Applied Kinesiology and Physiology, University of Florida, Gainesville, FL, USA
| | - Erta Cenko
- Department of Epidemiology, College of Public Health and Health Professions, and College of Medicine, University of Florida, Gainesville, FL, USA
| | - Arkaprava Roy
- Department of Biostatistics, University of Florida, Gainesville, FL, USA
| | - David J Clark
- Department of Neurology, University of Florida, Gainesville, FL, USA
- Brain Rehabilitation Research Center, Malcom Randall VA Medical Center, Gainesville, FL, USA
| | - Daniel P Ferris
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
| | - Chris J Hass
- Department of Applied Kinesiology and Physiology, University of Florida, Gainesville, FL, USA
| | - Todd M Manini
- Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL, USA
| | - Rachael D Seidler
- Department of Applied Kinesiology and Physiology, University of Florida, Gainesville, FL, USA
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Anthony M, Turnbull A, Tadin D, Lin FV. Positive affect disrupts neurodegeneration effects on cognitive training plasticity in older adults. Soc Cogn Affect Neurosci 2024; 19:nsae004. [PMID: 38252656 PMCID: PMC10939393 DOI: 10.1093/scan/nsae004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 11/02/2023] [Accepted: 01/18/2024] [Indexed: 01/24/2024] Open
Abstract
Cognitive training for older adults varies in efficacy, but it is unclear why some older adults benefit more than others. Positive affective experience (PAE), referring to high positive valence and/or stable arousal states across everyday scenarios, and associated functional networks can protect plasticity mechanisms against Alzheimer's disease neurodegeneration, which may contribute to training outcome variability. The objective of this study is to investigate whether PAE explains variability in cognitive training outcomes by disrupting the adverse effect of neurodegeneration on plasticity. The study's design is a secondary analysis of a randomized control trial of cognitive training with concurrent real or sham brain stimulation (39 older adults with mild cognitive impairment; mean age, 71). Moderation analyses, with change in episodic memory or executive function as the outcome, PAE or baseline resting-state connectivity as the moderator and baseline neurodegeneration as the predictor are the methods used in the study. The result of the study is that PAE stability and baseline default mode network (DMN) connectivity disrupted the effect of neurodegeneration on plasticity in executive function but not episodic memory. The study concludes that PAE stability and degree of DMN integrity both explained cognitive training outcome variability, by reducing the adverse effect of neurodegeneration on cognitive plasticity. We highlight the need to account for PAE, brain aging factors and their interactions with plasticity in cognitive training.
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Affiliation(s)
- Mia Anthony
- Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY 14627, USA
- Department of Psychiatry and Behavioral Science, Stanford University, Palo Alto, CA 94304, USA
| | - Adam Turnbull
- Department of Psychiatry and Behavioral Science, Stanford University, Palo Alto, CA 94304, USA
| | - Duje Tadin
- Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY 14627, USA
- Department of Neuroscience, University of Rochester Medical Center, Rochester, NY 14642, USA
- Department of Ophthalmology, University of Rochester Medical Center, Rochester, NY 14642, USA
- Center for Visual Science, University of Rochester, Rochester, NY 14627, USA
| | - F Vankee Lin
- Department of Psychiatry and Behavioral Science, Stanford University, Palo Alto, CA 94304, USA
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Pak V, Hashmi JA. Top-down threat bias in pain perception is predicted by higher segregation between resting-state networks. Netw Neurosci 2023; 7:1248-1265. [PMID: 38144683 PMCID: PMC10631789 DOI: 10.1162/netn_a_00328] [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: 11/14/2022] [Accepted: 06/23/2023] [Indexed: 12/26/2023] Open
Abstract
Top-down processes such as expectations have a strong influence on pain perception. Predicted threat of impending pain can affect perceived pain even more than the actual intensity of a noxious event. This type of threat bias in pain perception is associated with fear of pain and low pain tolerance, and hence the extent of bias varies between individuals. Large-scale patterns of functional brain connectivity are important for integrating expectations with sensory data. Greater integration is necessary for sensory integration; therefore, here we investigate the association between system segregation and top-down threat bias in healthy individuals. We show that top-down threat bias is predicted by less functional connectivity between resting-state networks. This effect was significant at a wide range of network thresholds and specifically in predefined parcellations of resting-state networks. Greater system segregation in brain networks also predicted higher anxiety and pain catastrophizing. These findings highlight the role of integration in brain networks in mediating threat bias in pain perception.
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Affiliation(s)
- Veronika Pak
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, QC, Canada
| | - Javeria Ali Hashmi
- Department of Anesthesia, Pain Management, and Perioperative Medicine, Nova Scotia Health Authority, Halifax, NS, Canada
- Dalhousie University, Halifax, NS, Canada
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Lyu W, Wu Y, Huang H, Chen Y, Tan X, Liang Y, Ma X, Feng Y, Wu J, Kang S, Qiu S, Yap PT. Aberrant dynamic functional network connectivity in type 2 diabetes mellitus individuals. Cogn Neurodyn 2023; 17:1525-1539. [PMID: 37969945 PMCID: PMC10640562 DOI: 10.1007/s11571-022-09899-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 09/11/2022] [Accepted: 10/09/2022] [Indexed: 11/24/2022] Open
Abstract
An increasing number of recent brain imaging studies are dedicated to understanding the neuro mechanism of cognitive impairment in type 2 diabetes mellitus (T2DM) individuals. In contrast to efforts to date that are limited to static functional connectivity, here we investigate abnormal connectivity in T2DM individuals by characterizing the time-varying properties of brain functional networks. Using group independent component analysis (GICA), sliding-window analysis, and k-means clustering, we extracted thirty-one intrinsic connectivity networks (ICNs) and estimated four recurring brain states. We observed significant group differences in fraction time (FT) and mean dwell time (MDT), and significant negative correlation between the Montreal Cognitive Assessment (MoCA) scores and FT/MDT. We found that in the T2DM group the inter- and intra-network connectivity decreases and increases respectively for the default mode network (DMN) and task-positive network (TPN). We also found alteration in the precuneus network (PCUN) and enhanced connectivity between the salience network (SN) and the TPN. Our study provides evidence of alterations of large-scale resting networks in T2DM individuals and shed light on the fundamental mechanisms of neurocognitive deficits in T2DM.
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Affiliation(s)
- Wenjiao Lyu
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong China
- Department of Radiology and Biomedical Research Imaging Center (BRIC), University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Ye Wu
- Department of Radiology and Biomedical Research Imaging Center (BRIC), University of North Carolina at Chapel Hill, Chapel Hill, NC USA
- School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu China
| | - Haoming Huang
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong China
| | - Yuna Chen
- Department of Endocrinology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong China
| | - Xin Tan
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong China
| | - Yi Liang
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong China
| | - Xiaomeng Ma
- Department of Radiology, Jingzhou First People’s Hospital of Hubei Province, Jingzhou, Hubei China
| | - Yue Feng
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong China
| | - Jinjian Wu
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong China
| | - Shangyu Kang
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong China
| | - Shijun Qiu
- Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong China
| | - Pew-Thian Yap
- Department of Radiology and Biomedical Research Imaging Center (BRIC), University of North Carolina at Chapel Hill, Chapel Hill, NC USA
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Spadone S, de Pasquale F, Chiacchiaretta P, Pavone L, Capotosto P, Delli Pizzi S, Digiovanni A, Sensi SL, Committeri G, Baldassarre A. Reduced Segregation of Brain Networks in Spatial Neglect After Stroke. Brain Connect 2023; 13:464-472. [PMID: 36128806 DOI: 10.1089/brain.2021.0184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Background/Purpose: To investigate the association between the degree of spatial neglect and the changes of brain system segregation (SyS; i.e., the ratio of the extent to which brain networks interact internally and with each other) after stroke. Methods: A cohort of 20 patients with right hemisphere lesion was submitted to neuropsychological assessment as well as to resting-state functional magnetic resonance imaging session at acute stage after stroke. The severity of spatial neglect was quantified using the Center of Cancellation (CoC) scores of the Bells cancellation test. For each patient, resting-state functional connectivity (FC) matrices were assessed by implementing a brain parcellation of nine networks that included the visual network, dorsal attention network (DAN), ventral attention network (VAN), sensorimotor network (SMN), auditory network, cingulo-opercular network, language network, frontoparietal network, and default mode network (DMN). For each patient and each network, we then computed the SyS derived by subtracting the between-network FC from the within-network FC (normalized by the within-network FC). Finally, for each network, the CoC scores were correlated with the SyS. Results: The correlational analyses indicated a negative association between CoC and SyS in the DAN, VAN, SMN, and DMN (q < 0.05 false discovery rate [FDR]-corrected). Patients with more severe spatial neglect exhibited lower SyS and vice versa. Conclusion: The loss of segregation in multiple and specific networks provides a functional framework for the deficits in spatial and nonspatial attention and motor/exploratory ability observed in neglect patients.
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Affiliation(s)
- Sara Spadone
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | | | - Piero Chiacchiaretta
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | | | - Paolo Capotosto
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Stefano Delli Pizzi
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Anna Digiovanni
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Stefano L Sensi
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Giorgia Committeri
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Antonello Baldassarre
- Department of Neuroscience, Imaging and Clinical Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
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Zientz J, Spence JS, Chung SSE, Nanda U, Chapman SB. Exploring how brain health strategy training informs the future of work. Front Psychol 2023; 14:1175652. [PMID: 37771803 PMCID: PMC10524270 DOI: 10.3389/fpsyg.2023.1175652] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 08/23/2023] [Indexed: 09/30/2023] Open
Abstract
Introduction The workplace typically affords one of the longest periods for continued brain health growth. Brain health is defined by the World Health Organization (WHO) as the promotion of optimal brain development, cognitive health, and well-being across the life course, which we expanded to also include connectedness to people and purpose. This work was motivated by prior work showing individuals, outside of an aggregate setting, benefitted from training as measured by significant performance gains on a holistic BrainHealth Index and its factors (i.e., clarity, connectedness, emotional balance). The current research was conducted during the changing remote work practices emerging post-pandemic to test whether a capacity-building training would be associated with significant gains on measures of brain health and components of burnout. The study also tested the influence of utilization of training modules and days in office for individuals to inform workplace practices. Methods We investigated whether 193 individuals across a firm's sites would improve on measures of brain health and burnout from micro-delivery of online tactical brain health strategies, combined with two individualized coaching sessions, and practical exercises related to work and personal life, over a six-month period. Brain health was measured using an evidenced-based measure (BrainHealth™ Index) with its components (clarity, connectedness, emotional balance) consistent with the WHO definition. Burnout was measured using the Maslach Burnout Inventory Human Services Survey. Days in office were determined by access to digital workplace applications from the firm's network. Regression analyses were used to assess relationships between change in BrainHealth factors and change in components of the Maslach Burnout Inventory. Results Results at posttest indicated that 75% of the individuals showed gains on a composite BrainHealth Index and across all three composite factors contributing to brain health. Benefits were directly tied to training utilization such that those who completed the core modules showed the greatest gains. The current results also found an association between gains on both the connectedness and emotional balance brain health factors and reduced on burnout components of occupational exhaustion and depersonalization towards one's workplace. We found that fewer days in the office were associated with greater gains in the clarity factor, but not for connectedness and emotional balance. Discussion These results support the value of a proactive, capacity-building training to benefit all employees to complement the more widespread limited offerings that address a smaller segment who need mental illness assistance programs. The future of work may be informed by corporate investment in focused efforts to boost collective brain capital through a human-centered, capacity-building approach. Efforts are underway to uncover the value of better brain health, i.e., Brainomics© - which includes economic, societal, and individual benefits.
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Affiliation(s)
- Jennifer Zientz
- Center for BrainHealth, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Dallas, TX, United States
| | - Jeffrey S. Spence
- Center for BrainHealth, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Dallas, TX, United States
| | | | | | - Sandra Bond Chapman
- Center for BrainHealth, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Dallas, TX, United States
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10
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Adams JN, Chappel-Farley MG, Yaros JL, Taylor L, Harris AL, Mikhail A, McMillan L, Keator DB, Yassa MA. Functional network structure supports resilience to memory deficits in cognitively normal older adults with amyloid-β pathology. Sci Rep 2023; 13:13953. [PMID: 37626094 PMCID: PMC10457346 DOI: 10.1038/s41598-023-40092-x] [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: 01/15/2023] [Accepted: 08/04/2023] [Indexed: 08/27/2023] Open
Abstract
Older adults may harbor large amounts of amyloid-β (Aβ) pathology, yet still perform at age-normal levels on memory assessments. We tested whether functional brain networks confer resilience or compensatory mechanisms to support memory in the face of Aβ pathology. Sixty-five cognitively normal older adults received high-resolution resting state fMRI to assess functional networks, 18F-florbetapir-PET to measure Aβ, and a memory assessment. We characterized functional networks with graph metrics of local efficiency (information transfer), modularity (specialization of functional modules), and small worldness (balance of integration and segregation). There was no difference in functional network measures between older adults with high Aβ (Aβ+) compared to those with no/low Aβ (Aβ-). However, in Aβ+ older adults, increased local efficiency, modularity, and small worldness were associated with better memory performance, while this relationship did not occur Aβ- older adults. Further, the association between increased local efficiency and better memory performance in Aβ+ older adults was localized to local efficiency of the default mode network and hippocampus, regions vulnerable to Aβ and involved in memory processing. Our results suggest functional networks with modular and efficient structures are associated with resilience to Aβ pathology, providing a functional target for intervention.
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Affiliation(s)
- Jenna N Adams
- Department of Neurobiology and Behavior, University of California, Irvine, 1400 Biological Sciences 3, Irvine, CA, 92697-3800, USA.
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, 92697, USA.
| | - Miranda G Chappel-Farley
- Department of Neurobiology and Behavior, University of California, Irvine, 1400 Biological Sciences 3, Irvine, CA, 92697-3800, USA
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, 92697, USA
| | - Jessica L Yaros
- Department of Neurobiology and Behavior, University of California, Irvine, 1400 Biological Sciences 3, Irvine, CA, 92697-3800, USA
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, 92697, USA
| | - Lisa Taylor
- Department of Psychiatry and Human Behavior, University of California, Irvine, 1418 Biological Sciences 3, Irvine, CA, 92697-3800, USA
| | - Alyssa L Harris
- Department of Neurobiology and Behavior, University of California, Irvine, 1400 Biological Sciences 3, Irvine, CA, 92697-3800, USA
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, 92697, USA
| | - Abanoub Mikhail
- Department of Neurobiology and Behavior, University of California, Irvine, 1400 Biological Sciences 3, Irvine, CA, 92697-3800, USA
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, 92697, USA
| | - Liv McMillan
- Department of Neurobiology and Behavior, University of California, Irvine, 1400 Biological Sciences 3, Irvine, CA, 92697-3800, USA
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, 92697, USA
| | - David B Keator
- Department of Psychiatry and Human Behavior, University of California, Irvine, 1418 Biological Sciences 3, Irvine, CA, 92697-3800, USA
| | - Michael A Yassa
- Department of Neurobiology and Behavior, University of California, Irvine, 1400 Biological Sciences 3, Irvine, CA, 92697-3800, USA.
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, 92697, USA.
- Department of Psychiatry and Human Behavior, University of California, Irvine, 1418 Biological Sciences 3, Irvine, CA, 92697-3800, USA.
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11
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Zdorovtsova N, Jones J, Akarca D, Benhamou E, The Calm Team, Astle DE. Exploring neural heterogeneity in inattention and hyperactivity. Cortex 2023; 164:90-111. [PMID: 37207412 DOI: 10.1016/j.cortex.2023.04.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 02/21/2023] [Accepted: 04/04/2023] [Indexed: 05/21/2023]
Abstract
Inattention and hyperactivity are cardinal symptoms of Attention Deficit Hyperactivity Disorder (ADHD). These characteristics have also been observed across a range of other neurodevelopmental conditions, such as autism and dyspraxia, suggesting that they might best be studied across diagnostic categories. Here, we evaluated the associations between inattention and hyperactivity behaviours and features of the structural brain network (connectome) in a large transdiagnostic sample of children (Centre for Attention, Learning, and Memory; n = 383). In our sample, we found that a single latent factor explains 77.6% of variance in scores across multiple questionnaires measuring inattention and hyperactivity. Partial Least-Squares (PLS) regression revealed that variability in this latent factor could not be explained by a linear component representing nodewise properties of connectomes. We then investigated the type and extent of neural heterogeneity in a subset of our sample with clinically-elevated levels of inattention and hyperactivity. Multidimensional scaling combined with k-means clustering revealed two neural subtypes in children with elevated levels of inattention and hyperactivity (n = 232), differentiated primarily by nodal communicability-a measure which demarcates the extent to which neural signals propagate through specific brain regions. These different clusters had similar behavioural profiles, which included high levels of inattention and hyperactivity. However, one of the clusters scored higher on multiple cognitive assessment measures of executive function. We conclude that inattention and hyperactivity are so common in children with neurodevelopmental difficulties because they emerge through multiple different trajectories of brain development. In our own data, we can identify two of these possible trajectories, which are reflected by measures of structural brain network topology and cognition.
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Affiliation(s)
- Natalia Zdorovtsova
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
| | - Jonathan Jones
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Danyal Akarca
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Elia Benhamou
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - The Calm Team
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Duncan E Astle
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK; Department of Psychiatry, University of Cambridge, Cambridge, UK
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12
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Deleglise A, Donnelly-Kehoe PA, Yeffal A, Jacobacci F, Jovicich J, Amaro E, Armony JL, Doyon J, Della-Maggiore V. Human motor sequence learning drives transient changes in network topology and hippocampal connectivity early during memory consolidation. Cereb Cortex 2023; 33:6120-6131. [PMID: 36587288 DOI: 10.1093/cercor/bhac489] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 11/03/2022] [Accepted: 11/20/2022] [Indexed: 01/02/2023] Open
Abstract
In the last decade, the exclusive role of the hippocampus in human declarative learning has been challenged. Recently, we have shown that gains in performance observed in motor sequence learning (MSL) during the quiet rest periods interleaved with practice are associated with increased hippocampal activity, suggesting a role of this structure in motor memory reactivation. Yet, skill also develops offline as memory stabilizes after training and overnight. To examine whether the hippocampus contributes to motor sequence memory consolidation, here we used a network neuroscience strategy to track its functional connectivity offline 30 min and 24 h post learning using resting-state functional magnetic resonance imaging. Using a graph-analytical approach we found that MSL transiently increased network modularity, reflected in an increment in local information processing at 30 min that returned to baseline at 24 h. Within the same time window, MSL decreased the connectivity of a hippocampal-sensorimotor network, and increased the connectivity of a striatal-premotor network in an antagonistic manner. Finally, a supervised classification identified a low-dimensional pattern of hippocampal connectivity that discriminated between control and MSL data with high accuracy. The fact that changes in hippocampal connectivity were detected shortly after training supports a relevant role of the hippocampus in early stages of motor memory consolidation.
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Affiliation(s)
- Alvaro Deleglise
- University of Buenos Aires, CONICET, Institute of Physiology and Biophysics (IFIBIO) Bernardo Houssay, Buenos Aires C1121ABG, Argentina
| | | | - Abraham Yeffal
- University of Buenos Aires, CONICET, Institute of Physiology and Biophysics (IFIBIO) Bernardo Houssay, Buenos Aires C1121ABG, Argentina
| | - Florencia Jacobacci
- University of Buenos Aires, CONICET, Institute of Physiology and Biophysics (IFIBIO) Bernardo Houssay, Buenos Aires C1121ABG, Argentina
| | - Jorge Jovicich
- Center for Mind/Brain Sciences, University of Trento, 38068 Trento, Italy
| | - Edson Amaro
- Plataforma de Imagens na Sala de Autopsia (PISA), Instituto de Radiologia, Facultade de Medicina, Universidade de Sao Paulo, Sao Paulo 05403-000, Brazil
| | - Jorge L Armony
- Douglas Mental Health Research Institute, McGill University, Montreal, QC H4H 1R3, Canada
| | - Julien Doyon
- McConnell Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC H3A 2B4, Canada
| | - Valeria Della-Maggiore
- University of Buenos Aires, CONICET, Institute of Physiology and Biophysics (IFIBIO) Bernardo Houssay, Buenos Aires C1121ABG, Argentina
- School of Science and Technology (ECyT), National University of San Martin, B1650 Villa Lynch, Buenos Aires, Argentina
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13
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Gallen CL, Hwang K, Chen AJW, Jacobs EG, Lee TG, D’Esposito M. Influence of goals on modular brain network organization during working memory. Front Behav Neurosci 2023; 17:1128610. [PMID: 37138661 PMCID: PMC10150932 DOI: 10.3389/fnbeh.2023.1128610] [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: 12/20/2022] [Accepted: 03/30/2023] [Indexed: 05/05/2023] Open
Abstract
Introduction Top-down control underlies our ability to attend relevant stimuli while ignoring irrelevant, distracting stimuli and is a critical process for prioritizing information in working memory (WM). Prior work has demonstrated that top-down biasing signals modulate sensory-selective cortical areas during WM, and that the large-scale organization of the brain reconfigures due to WM demands alone; however, it is not yet understood how brain networks reconfigure between the processing of relevant versus irrelevant information in the service of WM. Methods Here, we investigated the effects of task goals on brain network organization while participants performed a WM task that required participants to detect repetitions (e.g., 0-back or 1-back) and had varying levels of visual interference (e.g., distracting, irrelevant stimuli). We quantified changes in network modularity-a measure of brain sub-network segregation-that occurred depending on overall WM task difficulty as well as trial-level task goals for each stimulus during the task conditions (e.g., relevant or irrelevant). Results First, we replicated prior work and found that whole-brain modularity was lower during the more demanding WM task conditions compared to a baseline condition. Further, during the WM conditions with varying task goals, brain modularity was selectively lower during goal-directed processing of task-relevant stimuli to be remembered for WM performance compared to processing of distracting, irrelevant stimuli. Follow-up analyses indicated that this effect of task goals was most pronounced in default mode and visual sub-networks. Finally, we examined the behavioral relevance of these changes in modularity and found that individuals with lower modularity for relevant trials had faster WM task performance. Discussion These results suggest that brain networks can dynamically reconfigure to adopt a more integrated organization with greater communication between sub-networks that supports the goal-directed processing of relevant information and guides WM.
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Affiliation(s)
- Courtney L. Gallen
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States
- Department of Neurology, University of California, San Francisco, San Francisco, CA, United States
- Neuroscape Center, University of California, San Francisco, San Francisco, CA, United States
| | - Kai Hwang
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA, United States
| | - Anthony J.-W. Chen
- Department of Veterans Affairs, VA Northern California Health Care System, Martinez, CA, United States
| | - Emily G. Jacobs
- Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, CA, United States
| | - Taraz G. Lee
- Department of Psychology, University of Michigan, Ann Arbor, MI, United States
| | - Mark D’Esposito
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States
- Department of Veterans Affairs, VA Northern California Health Care System, Martinez, CA, United States
- Department of Psychology, University of California, Berkeley, Berkeley, CA, United States
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14
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Du Y, Wang G, Wang C, Zhang Y, Xi X, Zhang L, Liu M. Accurate module induced brain network construction for mild cognitive impairment identification with functional MRI. Front Aging Neurosci 2023; 15:1101879. [PMID: 36875703 PMCID: PMC9978189 DOI: 10.3389/fnagi.2023.1101879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 01/30/2023] [Indexed: 02/18/2023] Open
Abstract
Introduction Functional brain networks (FBNs) estimated from functional magnetic resonance imaging (fMRI) data has become a potentially useful way for computer-aided diagnosis of neurological disorders, such as mild cognitive impairment (MCI), a prodromal stage of Alzheimer's Disease (AD). Currently, Pearson's correlation (PC) is the most widely-used method for constructing FBNs. Despite its popularity and simplicity, the conventional PC-based method usually results in dense networks where regions-of-interest (ROIs) are densely connected. This is not accordance with the biological prior that ROIs may be sparsely connected in the brain. To address this issue, previous studies proposed to employ a threshold or l_1-regularizer to construct sparse FBNs. However, these methods usually ignore rich topology structures, such as modularity that has been proven to be an important property for improving the information processing ability of the brain. Methods To this end, in this paper, we propose an accurate module induced PC (AM-PC) model to estimate FBNs with a clear modular structure, by including sparse and low-rank constraints on the Laplacian matrix of the network. Based on the property that zero eigenvalues of graph Laplacian matrix indicate the connected components, the proposed method can reduce the rank of the Laplacian matrix to a pre-defined number and obtain FBNs with an accurate number of modules. Results To validate the effectiveness of the proposed method, we use the estimated FBNs to classify subjects with MCI from healthy controls. Experimental results on 143 subjects from Alzheimer's Disease Neuroimaging Initiative (ADNI) with resting-state functional MRIs show that the proposed method achieves better classification performance than previous methods.
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Affiliation(s)
- Yue Du
- School of Computer Science and Technology, Shandong Jianzhu University, Jinan, Shandong, China
- School of Mathematics Science, Liaocheng University, Liaocheng, Shandong, China
| | - Guangyu Wang
- School of Computer Science and Technology, Shandong Jianzhu University, Jinan, Shandong, China
- School of Mathematics Science, Liaocheng University, Liaocheng, Shandong, China
| | - Chengcheng Wang
- School of Mathematics Science, Liaocheng University, Liaocheng, Shandong, China
| | - Yangyang Zhang
- School of Mathematics Science, Liaocheng University, Liaocheng, Shandong, China
- School of Computer Science and Cyberspace Security, Hainan University, Haikou, Hainan, China
| | - Xiaoming Xi
- School of Computer Science and Technology, Shandong Jianzhu University, Jinan, Shandong, China
| | - Limei Zhang
- School of Computer Science and Technology, Shandong Jianzhu University, Jinan, Shandong, China
| | - Mingxia Liu
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
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15
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Augmentation of Cognitive Training With Vortioxetine Opens New Avenues for Targeting Age-Related Changes in Brain Connectivity. Am J Geriatr Psychiatry 2023; 31:398-400. [PMID: 36828690 DOI: 10.1016/j.jagp.2023.01.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Accepted: 01/30/2023] [Indexed: 02/10/2023]
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16
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Zhang S, Liu L, Zhang L, Ma L, Wu H, He X, Cao M, Li R. Evaluating the treatment outcomes of repetitive transcranial magnetic stimulation in patients with moderate-to-severe Alzheimer's disease. Front Aging Neurosci 2023; 14:1070535. [PMID: 36688172 PMCID: PMC9853407 DOI: 10.3389/fnagi.2022.1070535] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Accepted: 12/14/2022] [Indexed: 01/09/2023] Open
Abstract
The repetitive transcranial magnetic stimulation (rTMS) shows great potential in the treatment of Alzheimer's disease (AD). However, its treatment efficacy for AD patients in moderate to severe stage is relatively evaluated. Here, we proposed a randomized, sham-controlled, clinical trial of rTMS among 35 moderate-to-severe AD patients. A high frequency (10 Hz) stimulation of the left dorsal lateral prefrontal cortex (DLPFC), 60-session long treatment lasting for 3 months procedure was adopted in the trial. Each participant completed a battery of neuropsychological tests at baseline and post-treatment for evaluation of the rTMS therapeutic effect. Twelve of them completed baseline resting-state functional magnetic resonance imaging (fMRI) for exploration of the underlying neural contribution to individual difference in treatment outcomes. The result showed that the rTMS treatment significantly improved cognitive performance on the severe impairment battery (SIB), reduced psychiatric symptoms on the neuropsychiatric inventory (NPI), and improved the clinician's global impression of change (CIBIC-Plus). Furthermore, the result preliminarily proposed resting-state multivariate functional connectivity in the (para) hippocampal region as well as two clusters in the frontal and occipital cortices as a pre-treatment neuroimaging marker for predicting individual differences in treatment outcomes. The finding could brought some enlightenment and reference for the rTMS treatment of moderate and severe AD patients.
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Affiliation(s)
- Shouzi Zhang
- Department of Psychiatry, Beijing Geriatric Hospital, Beijing, China,*Correspondence: Shouzi Zhang, ✉
| | - Lixin Liu
- Department of Psychiatry, Beijing Geriatric Hospital, Beijing, China
| | - Li Zhang
- Department of Psychiatry, Beijing Geriatric Hospital, Beijing, China
| | - Li Ma
- Department of Psychiatry, Beijing Geriatric Hospital, Beijing, China
| | - Haiyan Wu
- Department of Psychiatry, Beijing Geriatric Hospital, Beijing, China
| | - Xuelin He
- Department of Psychiatry, Beijing Geriatric Hospital, Beijing, China
| | - Meng Cao
- Department of Psychiatry, Beijing Geriatric Hospital, Beijing, China
| | - Rui Li
- CAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China,Rui Li, ✉
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17
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Ziegler DA, Anguera JA, Gallen CL, Hsu WY, Wais PE, Gazzaley A. Leveraging technology to personalize cognitive enhancement methods in aging. NATURE AGING 2022; 2:475-483. [PMID: 35873177 PMCID: PMC9302894 DOI: 10.1038/s43587-022-00237-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
As population aging advances at an increasing rate, efforts to help people maintain or improve cognitive function late in life are critical. Although some studies have shown promise, the question of whether cognitive training is an effective tool for improving general cognitive ability remains incompletely explored, and study results to date have been inconsistent. Most approaches to cognitive enhancement in older adults have taken a 'one size fits all' tack, as opposed to tailoring interventions to the specific needs of individuals. In this Perspective, we argue that modern technology has the potential to enable large-scale trials of public health interventions to enhance cognition in older adults in a personalized manner. Technology-based cognitive interventions that rely on closed-loop systems can be tailored to individuals in real time and have the potential for global testing, extending their reach to large and diverse populations of older adults. We propose that the future of cognitive enhancement in older adults will rely on harnessing new technologies in scientifically informed ways.
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Affiliation(s)
- David A. Ziegler
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
- Neuroscape, University of California San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
- Correspondence should be addressed to David A. Ziegler or Adam Gazzaley. ;
| | - Joaquin A. Anguera
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
- Neuroscape, University of California San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA
| | - Courtney L. Gallen
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
- Neuroscape, University of California San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Wan-Yu Hsu
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Peter E. Wais
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
- Neuroscape, University of California San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Adam Gazzaley
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
- Neuroscape, University of California San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA
- Department of Physiology, University of California San Francisco, San Francisco, CA, USA
- Correspondence should be addressed to David A. Ziegler or Adam Gazzaley. ;
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18
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van Balkom TD, van den Heuvel OA, Berendse HW, van der Werf YD, Vriend C. Eight-week multi-domain cognitive training does not impact large-scale resting-state brain networks in Parkinson's disease. Neuroimage Clin 2022; 33:102952. [PMID: 35123203 PMCID: PMC8819471 DOI: 10.1016/j.nicl.2022.102952] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 12/23/2021] [Accepted: 01/26/2022] [Indexed: 11/25/2022]
Abstract
There is meta-analytic evidence for the efficacy of cognitive training (CT) in Parkinson's disease (PD). We performed a randomized controlled trial where we found small positive effects of CT on executive function and processing speed in individuals with PD (ntotal = 140). In this study, we assessed the effects of CT on brain network connectivity and topology in a subsample of the full study population (nmri = 86). Participants were randomized into an online multi-domain CT and an active control condition and performed 24 sessions of either intervention in eight weeks. Resting-state functional MRI scans were acquired in addition to extensive clinical and neuropsychological assessments pre- and post-intervention. In line with our preregistered analysis plan (osf.io/3st82), we computed connectivity between 'cognitive' resting-state networks and computed topological outcomes at the whole-brain and sub-network level. We assessed group differences after the intervention with mixed-model analyses adjusting for baseline performance and analyzed the association between network and cognitive performance changes with repeated measures correlation analyses. The final analysis sample consisted of 71 participants (n CT = 37). After intervention there were no group differences on between-network connectivity and network topological outcomes. No associations between neural network and neuropsychological performance change were found. CT increased segregated network topology in a small sub-sample of cognitively intact participants. Post-hoc nodal analyses showed post-intervention enhanced connectivity of both the dorsal anterior cingulate cortex and dorsolateral prefrontal cortex in the CT group. The results suggest no large-scale brain network effects of eight-week computerized CT, but rather localized connectivity changes of key regions in cognitive function, that potentially reflect the specific effects of the intervention.
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Affiliation(s)
- Tim D van Balkom
- Amsterdam UMC, Vrije Universiteit Amsterdam, Psychiatry, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, Netherlands.
| | - Odile A van den Heuvel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Psychiatry, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, Netherlands.
| | - Henk W Berendse
- Amsterdam UMC, Vrije Universiteit Amsterdam, Neurology, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, Netherlands.
| | - Ysbrand D van der Werf
- Amsterdam UMC, Vrije Universiteit Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, Netherlands.
| | - Chris Vriend
- Amsterdam UMC, Vrije Universiteit Amsterdam, Psychiatry, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, Netherlands.
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19
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Barollo F, Hassan M, Petersen H, Rigoni I, Ramon C, Gargiulo P, Fratini A. Cortical pathways during Postural Control: new insights from functional EEG source connectivity. IEEE Trans Neural Syst Rehabil Eng 2022; 30:72-84. [PMID: 34990367 DOI: 10.1109/tnsre.2022.3140888] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Postural control is a complex feedback system that relies on vast array of sensory inputs in order to maintain a stable upright stance. The brain cortex plays a crucial role in the processing of this information and in the elaboration of a successful adaptive strategy to external stimulation preventing loss of balance and falls. In the present work, the participants postural control system was challenged by disrupting the upright stance via a mechanical skeletal muscle vibration applied to the calves. The EEG source connectivity method was used to investigate the cortical response to the external stimulation and highlight the brain network primarily involved in high-level coordination of the postural control system. The cortical network reconfiguration was assessed during two experimental conditions of eyes open and eyes closed and the network flexibility (i.e. its dynamic reconfiguration over time) was correlated with the sample entropy of the stabilogram sway. The results highlight two different cortical strategies in the alpha band: the predominance of frontal lobe connections during open eyes and the strengthening of temporal-parietal network connections in the absence of visual cues. Furthermore, a high correlation emerges between the flexibility in the regions surrounding the right temporo-parietal junction and the sample entropy of the CoP sway, suggesting their centrality in the postural control system. These results open the possibility to employ network-based flexibility metrics as markers of a healthy postural control system, with implications in the diagnosis and treatment of postural impairing diseases.
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20
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Foo H, Thalamuthu A, Jiang J, Koch F, Mather KA, Wen W, Sachdev PS. Age- and Sex-Related Topological Organization of Human Brain Functional Networks and Their Relationship to Cognition. Front Aging Neurosci 2022; 13:758817. [PMID: 34975453 PMCID: PMC8718995 DOI: 10.3389/fnagi.2021.758817] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Accepted: 11/25/2021] [Indexed: 11/23/2022] Open
Abstract
Age and sex associated with changes in the functional brain network topology and cognition in large population of older adults have been poorly understood. We explored this question further by examining differences in 11 resting-state graph theory measures with respect to age, sex, and their relationships with cognitive performance in 17,127 United Kingdom Biobank participants (mean = 62.83 ± 7.41 years). Age was associated with an overall decrease in the effectiveness of network communication (i.e., integration) and loss of functional specialization (i.e., segregation) of specific brain regions. Sex differences were also observed, with women showing more efficient networks, which were less segregated than in men (FDR adjusted p < 0.05). The age-related changes were also more apparent in men than in women, which suggests that men may be more vulnerable to cognitive decline with age. Interestingly, while network segregation and strength of limbic network were only nominally associated with cognitive performance, the network measures collectively were significantly associated with cognition (FDR adjusted p ≤ 0.002). This may imply that individual measures may be inadequate to capture much of the variance in the neural activity or its output and need further refinement. The complexity of the organization of the functional brain may be shaped by the age and sex of an individual, which ultimately may influence the cognitive performance of older adults. Age and sex stratification may be used to inform clinical neuroscience research to identify older adults at risk of cognitive dysfunction.
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Affiliation(s)
- Heidi Foo
- Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, NSW, Australia
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, NSW, Australia
| | - Jiyang Jiang
- Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, NSW, Australia
| | - Forrest Koch
- Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, NSW, Australia
| | - Karen A Mather
- Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, NSW, Australia.,Neuroscience Research Australia, Randwick, NSW, Australia
| | - Wei Wen
- Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, NSW, Australia
| | - Perminder S Sachdev
- Centre for Healthy Brain Aging, CHeBA, School of Psychiatry, University of New South Wales Medicine, Kensington, NSW, Australia.,Neuropsychiatric Institute, Euroa Centre, Prince of Wales Hospital, Randwick, NSW, Australia
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21
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Yuan L, Ma X, Li D, Li Z, Ouyang L, Fan L, Yang Z, Zhang Z, Li C, He Y, Chen X. Abnormal Brain Network Interaction Associated With Positive Symptoms in Drug-Naive Patients With First-Episode Schizophrenia. Front Psychiatry 2022; 13:870709. [PMID: 35656348 PMCID: PMC9152123 DOI: 10.3389/fpsyt.2022.870709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 04/14/2022] [Indexed: 11/23/2022] Open
Abstract
Positive symptoms are marked features of schizophrenia, and emerging evidence has suggested that abnormalities of the brain network underlying these symptoms may play a crucial role in the pathophysiology of the disease. We constructed two brain functional networks based on the positive and negative correlations between positive symptom scores and brain connectivity in drug-naive patients with first-episode schizophrenia (FES, n = 45) by using a machine-learning approach (connectome-based predictive modeling, CPM). The accuracy of the model was r = 0.47 (p = 0.002). The positively and negatively associated network strengths were then compared among FES subjects, individuals at genetic high risk (GHR, n = 41) for schizophrenia, and healthy controls (HCs, n = 48). The results indicated that the positively associated network contained more cross-subnetwork connections (96.02% of 176 edges), with a focus on the default-mode network (DMN)-salience network (SN) and the DMN-frontoparietal task control (FPT) network. The negatively associated network had fewer cross-subnetwork connections (71.79% of 117 edges) and focused on the sensory/somatomotor hand (SMH)-Cingulo opercular task control (COTC) network, the DMN, and the visual network with significantly decreased connectivity in the COTC-SMH network in FES (FES < GHR, p = 0.01; FES < HC, p = 0.01). Additionally, the connectivity strengths of the right supplementary motor area (SMA) (p < 0.001) and the right precentral gyrus (p < 0.0001) were reduced in FES. To the best of our knowledge, this is the first study to generate two brain networks associated with positive symptoms by utilizing CPM in FES. Abnormal segregation, interactions of brain subnetworks, and impaired SMA might lead to salience attribution abnormalities and, thus, as a result, induce positive symptoms in schizophrenia.
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Affiliation(s)
- Liu Yuan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Xiaoqian Ma
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - David Li
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Zongchang Li
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Lijun Ouyang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Lejia Fan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Zihao Yang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Zhenmei Zhang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Chunwang Li
- Department of Radiology, Hunan Children's Hospital, Changsha, China
| | - Ying He
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
| | - Xiaogang Chen
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.,Mental Health Institute of Central South University, China National Technology Institute on Mental Disorders, Hunan Technology Institute of Psychiatry, Hunan Key Laboratory of Psychiatry and Mental Health, Changsha, China
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22
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Chaddock-Heyman L, Weng T, Loui P, Kienzler C, Weisshappel R, Drollette ES, Raine LB, Westfall D, Kao SC, Pindus DM, Baniqued P, Castelli DM, Hillman CH, Kramer AF. Brain network modularity predicts changes in cortical thickness in children involved in a physical activity intervention. Psychophysiology 2021; 58:e13890. [PMID: 34219221 PMCID: PMC8419073 DOI: 10.1111/psyp.13890] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 05/30/2021] [Accepted: 06/09/2021] [Indexed: 11/26/2022]
Abstract
Individual differences in brain network modularity at baseline can predict improvements in cognitive performance after cognitive and physical interventions. This study is the first to explore whether brain network modularity predicts changes in cortical brain structure in 8- to 9-year-old children involved in an after-school physical activity intervention (N = 62), relative to children randomized to a wait-list control group (N = 53). For children involved in the physical activity intervention, brain network modularity at baseline predicted greater decreases in cortical thickness in the anterior frontal cortex and parahippocampus. Further, for children involved in the physical activity intervention, greater decrease in cortical thickness was associated with improvements in cognitive efficiency. The relationships among baseline modularity, changes in cortical thickness, and changes in cognitive performance were not present in the wait-list control group. Our exploratory study has promising implications for the understanding of brain network modularity as a biomarker of intervention-related improvements with physical activity.
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Affiliation(s)
- Laura Chaddock-Heyman
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Psychology, Northeastern University, Boston, MA, USA
| | - Timothy Weng
- Department of Diagnostic Medicine, The University of Texas at Austin, Austin, TX, USA
| | - Psyche Loui
- Department of Psychology, Northeastern University, Boston, MA, USA
| | - Caitlin Kienzler
- Department of Psychology, University of Colorado, Denver, CO, USA
| | - Robert Weisshappel
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Eric S. Drollette
- Department of Kinesiology, University of North Carolina at Greensboro, Greensboro, North Carolina, USA
| | - Lauren B. Raine
- Department of Psychology, Northeastern University, Boston, MA, USA
| | - Daniel Westfall
- Department of Psychology, Northeastern University, Boston, MA, USA
| | - Shih-Chun Kao
- Health and Kinesiology, Purdue University, West Lafayette, IN, USA
| | - Dominika M. Pindus
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Kinesiology and Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Pauline Baniqued
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
- Brain and Creativity Institute, University of Southern California, Los Angeles, CA, USA
| | - Darla M. Castelli
- Department of Kinesiology and Health Education, The University of Texas at Austin, USA
| | - Charles H. Hillman
- Department of Psychology, Northeastern University, Boston, MA, USA
- Department of Physical Therapy, Movement, & Rehabilitation Sciences, Northeastern University, Boston, MA, USA
| | - Arthur F. Kramer
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Psychology, Northeastern University, Boston, MA, USA
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23
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Characterization of the Brain Functional Architecture of Psychostimulant Withdrawal Using Single-Cell Whole-Brain Imaging. eNeuro 2021; 8:ENEURO.0208-19.2021. [PMID: 34580158 PMCID: PMC8570684 DOI: 10.1523/eneuro.0208-19.2021] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Revised: 08/08/2021] [Accepted: 08/09/2021] [Indexed: 02/03/2023] Open
Abstract
Numerous brain regions have been identified as contributing to withdrawal behaviors, but it is unclear the way in which these brain regions as a whole lead to withdrawal. The search for a final common brain pathway that is involved in withdrawal remains elusive. To address this question, we implanted osmotic minipumps containing either saline, nicotine (24 mg/kg/d), cocaine (60 mg/kg/d), or methamphetamine (4 mg/kg/d) for one week in male C57BL/6J mice. After one week, the minipumps were removed and brains collected 8 h (saline, nicotine, and cocaine) or 12 h (methamphetamine) after removal. We then performed single-cell whole-brain imaging of neural activity during the withdrawal period when brains were collected. We used hierarchical clustering and graph theory to identify similarities and differences in brain functional architecture. Although methamphetamine and cocaine shared some network similarities, the main common neuroadaptation between these psychostimulant drugs was a dramatic decrease in modularity, with a shift from a cortical-driven to subcortical-driven network, including a decrease in total hub brain regions. These results demonstrate that psychostimulant withdrawal produces the drug-dependent remodeling of functional architecture of the brain and suggest that the decreased modularity of brain functional networks and not a specific set of brain regions may represent the final common pathway associated with withdrawal.
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24
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Lv N, Lefferts WK, Xiao L, Goldstein-Piekarski AN, Wielgosz J, Lavori PW, Simmons JM, Smyth JM, Stetz P, Venditti EM, Lewis MA, Rosas LG, Snowden MB, Ajilore OA, Suppes T, Williams LM, Ma J. Problem-solving therapy-induced amygdala engagement mediates lifestyle behavior change in obesity with comorbid depression: a randomized proof-of-mechanism trial. Am J Clin Nutr 2021; 114:2060-2073. [PMID: 34476464 PMCID: PMC8634561 DOI: 10.1093/ajcn/nqab280] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 08/04/2021] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Depression hinders obesity treatment; elucidating mechanisms may enable treatment enhancements. OBJECTIVES The aim was to investigate whether changes in neural targets in the negative affect circuit following psychotherapy mediate subsequent changes in weight and behaviors. METHODS Adults (n = 108) with obesity and depression were randomly assigned to usual care or an intervention that delivered problem-solving therapy (PST) for depression over 2 mo. fMRI for brain imaging was performed at baseline and 2 mo. BMI, physical activity, and diet were measured at baseline and 12 mo. Mediation analysis assessed between-group differences in neural target changes using t test and correlations between neural target changes and outcome changes (simple and interaction effect) using ordinary least-squares regression. RESULTS Compared with usual care, PST led to reductions in left amygdala activation (-0.75; 95% CI: -1.49, -0.01) and global scores of the negative affect circuit (-0.43; -0.81, -0.06), engaged by threat stimuli. Increases in amygdala activation and global circuit scores at 2 mo correlated with decreases in physical activity outcomes at 12 mo in the usual-care group; these relations were altered by PST. In relation to change in leisure-time physical activity, standardized β-coefficients were -0.67 in usual care and -0.01 in the intervention (between-group difference: 0.66; 0.02, 1.30) for change in left amygdala activation and -2.02 in usual care and -0.11 in the intervention (difference: 1.92; 0.64, 3.20) for change in global circuit scores. In relation to change in total energy expenditure, standardized β-coefficients were -0.65 in usual care and 0.08 in the intervention (difference: 0.73; 0.29, 1.16) for change in left amygdala activation and -1.65 in usual care and 0.08 in the intervention (difference: 1.74; 0.85, 2.63) for change in global circuit scores. Results were null for BMI and diet. CONCLUSIONS Short-term changes in the negative affect circuit engaged by threat stimuli following PST for depression mediated longer-term changes in physical activity. This trial was registered at www.clinicaltrials.gov as NCT02246413 (https://clinicaltrials.gov/ct2/show/NCT02246413).
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Affiliation(s)
- Nan Lv
- Institute of Health Research and Policy, University of Illinois at Chicago, Chicago, IL, USA
| | - Wesley K Lefferts
- Institute of Health Research and Policy, University of Illinois at Chicago, Chicago, IL, USA
| | - Lan Xiao
- Department of Epidemiology and Population Health, Stanford University, Palo Alto, CA, USA
| | - Andrea N Goldstein-Piekarski
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA,Sierra-Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Joseph Wielgosz
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA,Sierra-Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Philip W Lavori
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Janine M Simmons
- National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Joshua M Smyth
- Departments of Biobehavioral Health and Medicine, The Pennsylvania State University, University Park, PA, USA
| | - Patrick Stetz
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Elizabeth M Venditti
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Megan A Lewis
- Center for Communication Science, RTI International, Seattle, WA, USA
| | - Lisa G Rosas
- Department of Epidemiology and Population Health, Stanford University, Palo Alto, CA, USA,Department of Medicine, Stanford University, Palo Alto, CA, USA
| | - Mark B Snowden
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Harborview Medical Center, Seattle, WA, USA
| | - Olusola A Ajilore
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
| | - Trisha Suppes
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA,Sierra-Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Leanne M Williams
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA,Sierra-Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Jun Ma
- Address correspondence to JM (e-mail: )
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25
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Zhang Y, Jiang X, Qiao L, Liu M. Modularity-Guided Functional Brain Network Analysis for Early-Stage Dementia Identification. Front Neurosci 2021; 15:720909. [PMID: 34421530 PMCID: PMC8374334 DOI: 10.3389/fnins.2021.720909] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2021] [Accepted: 07/09/2021] [Indexed: 02/04/2023] Open
Abstract
Function brain network (FBN) analysis has shown great potential in identifying brain diseases, such as Alzheimer's disease (AD) and its prodromal stage, namely mild cognitive impairment (MCI). It is essential to identify discriminative and interpretable features from function brain networks, so as to improve classification performance and help us understand the pathological mechanism of AD-related brain disorders. Previous studies usually extract node statistics or edge weights from FBNs to represent each subject. However, these methods generally ignore the topological structure (such as modularity) of FBNs. To address this issue, we propose a modular-LASSO feature selection (MLFS) framework that can explicitly model the modularity information to identify discriminative and interpretable features from FBNs for automated AD/MCI classification. Specifically, the proposed MLFS method first searches the modular structure of FBNs through a signed spectral clustering algorithm, and then selects discriminative features via a modularity-induced group LASSO method, followed by a support vector machine (SVM) for classification. To evaluate the effectiveness of the proposed method, extensive experiments are performed on 563 resting-state functional MRI scans from the public ADNI database to identify subjects with AD/MCI from normal controls and predict the future progress of MCI subjects. Experimental results demonstrate that our method is superior to previous methods in both tasks of AD/MCI identification and MCI conversion prediction, and also helps discover discriminative brain regions and functional connectivities associated with AD.
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Affiliation(s)
- Yangyang Zhang
- School of Mathematics Science, Liaocheng University, Liaocheng, China
| | - Xiao Jiang
- School of Mathematics Science, Liaocheng University, Liaocheng, China.,School of Science and Technology, University of Camerino, Camerino, Italy
| | - Lishan Qiao
- School of Mathematics Science, Liaocheng University, Liaocheng, China
| | - Mingxia Liu
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
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26
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Pedersen R, Geerligs L, Andersson M, Gorbach T, Avelar-Pereira B, Wåhlin A, Rieckmann A, Nyberg L, Salami A. When functional blurring becomes deleterious: Reduced system segregation is associated with less white matter integrity and cognitive decline in aging. Neuroimage 2021; 242:118449. [PMID: 34358662 DOI: 10.1016/j.neuroimage.2021.118449] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 06/24/2021] [Accepted: 08/02/2021] [Indexed: 11/18/2022] Open
Abstract
Healthy aging is accompanied by progressive decline in cognitive performance and concomitant changes in brain structure and functional architecture. Age-accompanied alterations in brain function have been characterized on a network level as weaker functional connections within brain networks along with stronger interactions between networks. This phenomenon has been described as age-related differences in functional network segregation. It has been suggested that functional networks related to associative processes are particularly sensitive to age-related deterioration in segregation, possibly related to cognitive decline in aging. However, there have been only a few longitudinal studies with inconclusive results. Here, we used a large longitudinal sample of 284 participants between 25 to 80 years of age at baseline, with cognitive and neuroimaging data collected at up to three time points over a 10-year period. We investigated age-related changes in functional segregation among two large-scale systems comprising associative and sensorimotor-related resting-state networks. We found that functional segregation of associative systems declines in aging with exacerbated deterioration from the late fifties. Changes in associative segregation were positively associated with changes in global cognitive ability, suggesting that decreased segregation has negative consequences for domain-general cognitive functions. Age-related changes in system segregation were partly accounted for by changes in white matter integrity, but white matter integrity only weakly influenced the association between segregation and cognition. Together, these novel findings suggest a cascade where reduced white-matter integrity leads to less distinctive functional systems which in turn contributes to cognitive decline in aging.
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Affiliation(s)
- Robin Pedersen
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden; Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden; Wallenberg Centre for Molecular Medicine (WCMM), Umeå University, Umeå, Sweden.
| | - Linda Geerligs
- Donders Institute for Brain, Cognition and Behaviour, Radbound University, Nijmegen, the Netherlands
| | - Micael Andersson
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden; Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden; Department of Radiation Sciences, Umeå University, Umeå, Sweden
| | - Tetiana Gorbach
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden; Wallenberg Centre for Molecular Medicine (WCMM), Umeå University, Umeå, Sweden; Department of Statistics, Umeå School of Business, Economics and Statistics, Umeå University, Umeå, Sweden
| | - Bárbara Avelar-Pereira
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Stanford, California, USA; Aging Research Center (ARC), Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Anders Wåhlin
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden; Department of Radiation Sciences, Umeå University, Umeå, Sweden
| | - Anna Rieckmann
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden; Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden; Department of Radiation Sciences, Umeå University, Umeå, Sweden
| | - Lars Nyberg
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden; Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden; Wallenberg Centre for Molecular Medicine (WCMM), Umeå University, Umeå, Sweden; Department of Radiation Sciences, Umeå University, Umeå, Sweden
| | - Alireza Salami
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden; Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden; Wallenberg Centre for Molecular Medicine (WCMM), Umeå University, Umeå, Sweden; Aging Research Center (ARC), Karolinska Institutet and Stockholm University, Stockholm, Sweden
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27
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Abstract
This study aimed to summarize investigations that examined the benefits of dance on the neuroplasticity of older healthy adults, report structural and functional changes in the brain, and identify the strategies used in training protocols. The integrative review was perfomed in PubMed, Web of Science and Scopus databases, including randomized clinical trials, quasi-experimental, cross-sectional and cohort studies published in English, between 2010-2020. Twelve articles ware selected. Dance practice was associated with an improvement in functional connectivity, cognitive performance, and incresead brain volumes. Our results main supports studies on the plasticity induced by dance training in healthy older people.
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Affiliation(s)
- Marcelo de Maio Nascimento
- Physical Education, School of Physical Education, Federal University Vale Do São Francisco, Petrolina, PE-Brazil
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28
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Rao N, Mehta N, Patel P, Parikh PJ. Effects of aging on conditional visuomotor learning for grasping and lifting eccentrically weighted objects. J Appl Physiol (1985) 2021; 131:937-948. [PMID: 34264127 DOI: 10.1152/japplphysiol.00932.2020] [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
Explicit knowledge of object center of mass or CM location fails to guide anticipatory scaling of digit forces necessary for dexterous manipulation. We previously showed that allowing young adults to choose where to grasp the object entailed an ability to use arbitrary color cues about object CM location to gradually minimize object tilt across several trials. This conditional learning was achieved through accurate anticipatory modulation of digit position using the color cues. However, it remains unknown how aging affects the ability to use explicit color cues about object CM location to modulate digit placement for dexterous manipulation. We instructed healthy older and young adults to learn a manipulation task using arbitrary color cues about object CM location. Subjects were required to exert clockwise, counterclockwise, or no torque on the object according to the color cue and lift the object while minimizing its tilt. Older adults produced larger torque error during conditional learning trials, resulting in a slower rate of learning than young adults. Importantly, older adults showed impaired anticipatory modulation of digit position when information of the CM location was available via explicit color cues. The older adults also did not modulate their digit forces to compensate for this impairment. Interestingly, however, anticipatory modulation of digit position was intact in the same individuals when information of object CM location was implicitly conveyed from trial-to-trial. We discuss our findings in relation to age-dependent changes in processes and neural network essential for learning dexterous manipulation using arbitrary color cue about object property.NEW & NOTEWORTHY We studied whether older adults are able to predictively modulate digit position using arbitrary color cues indicating object center of mass location for dexterous manipulation. Older adults showed an impaired ability to modulate digit position using the color cues when compared with young adults. Interestingly, similar impairments were not found when same older individuals learned the task using implicit knowledge. Our findings suggest an age-related impairment specifically in the conditional learning mechanisms for dexterous manipulation.
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Affiliation(s)
- Nishant Rao
- Center for Neuromotor and Biomechanics Research, Department of Health and Human Performance, University of Houston, Houston, Texas
| | - Neha Mehta
- Center for Neuromotor and Biomechanics Research, Department of Health and Human Performance, University of Houston, Houston, Texas
| | - Pujan Patel
- Center for Neuromotor and Biomechanics Research, Department of Health and Human Performance, University of Houston, Houston, Texas.,The Biomedical Sciences Program, Texas A&M University, College Station, Texas
| | - Pranav J Parikh
- Center for Neuromotor and Biomechanics Research, Department of Health and Human Performance, University of Houston, Houston, Texas
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29
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Roheger M, Liebermann-Jordanidis H, Krohm F, Adams A, Kalbe E. Prognostic Factors and Models for Changes in Cognitive Performance After Multi-Domain Cognitive Training in Healthy Older Adults: A Systematic Review. Front Hum Neurosci 2021; 15:636355. [PMID: 33986652 PMCID: PMC8110835 DOI: 10.3389/fnhum.2021.636355] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 03/26/2021] [Indexed: 12/23/2022] Open
Abstract
Background: Cognitive Training (CT) may contribute to the maintenance and even enhancement of cognitive functions in healthy older adults. However, the question who benefits most from multi-domain CTs is still highly under-investigated. Objective: The goal is to investigate prognostic factors and models for changes in cognitive test performance in healthy older adults after a multi-domain CT. Methods: The data bases MEDLINE, Web of Science Core Collection, CENTRAL, and PsycInfo were searched up to July 2019. Studies investigating prognostic factors and/or models on cognitive outcomes (global cognition, memory, attention, executive functions, language, visuo-spatial abilities) after conducting a multi-domain CT in healthy older adults were included. Risk of Bias was assessed using the QUIPS and the PROBAST tool. Results: 23 prognostic factor and model studies were included. Results indicate a high heterogeneity regarding the conducted multi-domain CTs, the investigated prognostic factors, the investigated outcomes, and the used statistical approaches. Age and neuropsychological performance at study entry were the most investigated predictors, yet they show inconsistent results. Conclusion: Data on prognostic factors and models of changes after multi-domain CT are still too rare and inconsistent to draw clear conclusions due to statistical shortcomings and low reporting quality. Approaches for future research are outlined. Registration:https://www.crd.york.ac.uk/prospero/, ID: CRD42020147531
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Affiliation(s)
- Mandy Roheger
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany.,Department of Medical Psychology
- Neuropsychology and Gender Studies and Center for Neuropsychological Diagnostics and Intervention (CeNDI), Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Hannah Liebermann-Jordanidis
- Department of Medical Psychology
- Neuropsychology and Gender Studies and Center for Neuropsychological Diagnostics and Intervention (CeNDI), Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Fabian Krohm
- Department of Medical Psychology
- Neuropsychology and Gender Studies and Center for Neuropsychological Diagnostics and Intervention (CeNDI), Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Anne Adams
- Institute of Medical Statistics and Computational Biology, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Elke Kalbe
- Department of Medical Psychology
- Neuropsychology and Gender Studies and Center for Neuropsychological Diagnostics and Intervention (CeNDI), Faculty of Medicine and University Hospital Cologne, Cologne, Germany
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30
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Young LR, Zientz JE, Spence JS, Krawczyk DC, Chapman SB. Efficacy of Cognitive Training When Translated From the Laboratory to the Real World. Mil Med 2021; 186:176-183. [PMID: 33499529 DOI: 10.1093/milmed/usaa501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 07/29/2020] [Accepted: 11/16/2020] [Indexed: 11/12/2022] Open
Abstract
INTRODUCTION Research shows that cognitive performance and emotional well-being can be significantly strengthened. A high-performance brain training protocol, Strategic Memory Advanced Reasoning Training (SMART), was developed by cognitive neuroscientists at The University of Texas at Dallas Center for BrainHealth based on 25-plus years of scientific study. Randomized controlled trials with various populations have shown that training and use of nine "SMART" strategies for processing information can improve cognitive performance and psychological health. However, the multi-week intensive training used in the laboratory is not practical for widespread use outside the laboratory. This article examines the efficacy of SMART when translated outside the laboratory to two populations (military/veterans and law enforcement) that received SMART in condensed time frames. MATERIALS AND METHODS In two translation studies with healthy military personnel and veterans, 425 participants received between 6 and 10 hours of SMART over 2 days. In a third translation study, 74 healthy police officers received 9 hours of SMART over 3 days. Training was conducted by clinicians who taught the nine "SMART" strategies related to three core areas-strategic attention, integrated reasoning, and innovation-to groups of up to 25 participants. In all three translation studies, cognitive performance and psychological health data were collected before and immediately following the training. In one of the military/veteran studies, psychological health data were also collected 1 and 4 months following the training. RESULTS In both translations to military personnel and veterans, there were improvements in the complex cognitive domains of integrated reasoning (P < .0001) and innovation (P < .0001) immediately after undergoing SMART. In the translation to police officers, there were improvements in the cognitive domains of innovation (P = .02) and strategic attention (P = .005). Participants in all three translations saw statistically significant improvements in self-reported symptoms of psychological health. The improvements continued among a subset of participants who responded to the later requests for information. CONCLUSIONS The results of translating to these two populations provide evidence supporting the efficacy of SMART delivered in an abbreviated time frame. The improvements in two major domains of cognitive function demonstrate that strategies can be taught and immediately applied by those receiving the training. The immediate psychological health improvements may be transient; however, the continued improvements in psychological health observed in a subset of the participants suggest that benefits may be sustainable even at later intervals.
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Affiliation(s)
- Leanne R Young
- Applied Research Associates, Inc., Dallas, TX 75252, USA
| | - Jennifer E Zientz
- The University of Texas at Dallas Center for BrainHealth, Dallas, TX 75235, USA
| | - Jeffrey S Spence
- The University of Texas at Dallas Center for BrainHealth, Dallas, TX 75235, USA
| | - Daniel C Krawczyk
- The University of Texas at Dallas Center for BrainHealth, Dallas, TX 75235, USA
| | - Sandra B Chapman
- The University of Texas at Dallas Center for BrainHealth, Dallas, TX 75235, USA
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31
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Iordan AD, Moored KD, Katz B, Cooke KA, Buschkuehl M, Jaeggi SM, Polk TA, Peltier SJ, Jonides J, Reuter‐Lorenz PA. Age differences in functional network reconfiguration with working memory training. Hum Brain Mapp 2021; 42:1888-1909. [PMID: 33534925 PMCID: PMC7978135 DOI: 10.1002/hbm.25337] [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] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 12/21/2020] [Accepted: 12/22/2020] [Indexed: 12/16/2022] Open
Abstract
Demanding cognitive functions like working memory (WM) depend on functional brain networks being able to communicate efficiently while also maintaining some degree of modularity. Evidence suggests that aging can disrupt this balance between integration and modularity. In this study, we examined how cognitive training affects the integration and modularity of functional networks in older and younger adults. Twenty three younger and 23 older adults participated in 10 days of verbal WM training, leading to performance gains in both age groups. Older adults exhibited lower modularity overall and a greater decrement when switching from rest to task, compared to younger adults. Interestingly, younger but not older adults showed increased task-related modularity with training. Furthermore, whereas training increased efficiency within, and decreased participation of, the default-mode network for younger adults, it enhanced efficiency within a task-specific salience/sensorimotor network for older adults. Finally, training increased segregation of the default-mode from frontoparietal/salience and visual networks in younger adults, while it diffusely increased between-network connectivity in older adults. Thus, while younger adults increase network segregation with training, suggesting more automated processing, older adults persist in, and potentially amplify, a more integrated and costly global workspace, suggesting different age-related trajectories in functional network reorganization with WM training.
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Affiliation(s)
| | - Kyle D. Moored
- Department of Mental Health, Bloomberg School of Public HealthJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Benjamin Katz
- Department of Human Development and Family ScienceVirginia TechBlacksburgVirginiaUSA
| | | | | | - Susanne M. Jaeggi
- School of EducationUniversity of California‐IrvineIrvineCaliforniaUSA
| | - Thad A. Polk
- Department of PsychologyUniversity of MichiganAnn ArborMichiganUSA
| | - Scott J. Peltier
- Functional MRI LaboratoryUniversity of MichiganAnn ArborMichiganUSA
- Department of Biomedical EngineeringUniversity of MichiganAnn ArborMichiganUSA
| | - John Jonides
- Department of PsychologyUniversity of MichiganAnn ArborMichiganUSA
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32
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Muller AM, Meyerhoff DJ. Maladaptive brain organization at 1 month into abstinence as an indicator for future relapse in patients with alcohol use disorder. Eur J Neurosci 2021; 53:2923-2938. [PMID: 33630358 PMCID: PMC8252378 DOI: 10.1111/ejn.15161] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Revised: 02/22/2021] [Accepted: 02/23/2021] [Indexed: 12/11/2022]
Abstract
Abstinence is a lifelong endeavor, and the risk of a relapse is always present for patients with Alcohol Use Disorder (AUD). The aim of the study was to better understand specific characteristics of the intrinsic whole-brain-network architecture of 34 AUD patients that may support abstinence or relapse. We used Graph Theory Analysis (GTA) of resting-state fMRI data from treatment seekers at 1 month of abstinence and their follow-up data as abstainers or relapsers 3 months later, together with data from 30 light/non-drinking controls scanned at the same interval. We determined the group-specific intrinsic community configurations at both timepoints as well as the corresponding modularity Q, a GTA measure that quantifies how well individual network communities are separated from each other. Both AUD groups at both timepoints had community configurations significantly different from those of controls, but the three groups did not significantly differ in their Q values. However, relapsers showed a maladaptive community configuration at baseline, which became more similar to the controls' community organization after the relapsers had started consuming alcohol again during the study interval. Additionally, successful recovery from AUD was not associated with re-gaining the intrinsic brain organization found in light/non-drinkers, but with a re-configuration resulting in a new brain organization distinctly different from that of healthy controls. Resting-state fMRI provides useful measures reflecting neuroplastic adaptations related to AUD treatment outcome.
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Affiliation(s)
- Angela M Muller
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Dieter J Meyerhoff
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
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33
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Sinha N, Berg CN, Yassa MA, Gluck MA. Increased dynamic flexibility in the medial temporal lobe network following an exercise intervention mediates generalization of prior learning. Neurobiol Learn Mem 2021; 177:107340. [PMID: 33186745 PMCID: PMC7861122 DOI: 10.1016/j.nlm.2020.107340] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Revised: 07/29/2020] [Accepted: 11/01/2020] [Indexed: 11/28/2022]
Abstract
Recent work has conceptualized the brain as a network comprised of groups of sub-networks or modules. "Flexibility" of brain network(s) indexes the dynamic reconfiguration of comprising modules. Using novel techniques from dynamic network neuroscience applied to high-resolution resting-state functional magnetic resonance imaging (fMRI), the present study investigated the effects of an aerobic exercise intervention on the dynamic rearrangement of modular community structure-a measure of neural flexibility-within the medial temporal lobe (MTL) network. The MTL is one of the earliest brain regions impacted by Alzheimer's disease. It is also a major site of neuroplasticity that is sensitive to the effects of exercise. In a two-group non-randomized, repeated measures and matched control design with 34 healthy older adults, we observed an exercise-related increase in flexibility within the MTL network. Furthermore, MTL network flexibility mediated the beneficial effect aerobic exercise had on mnemonic flexibility, as measured by the ability to generalize past learning to novel task demands. Our results suggest that exercise exerts a rehabilitative and protective effect on MTL function, resulting in dynamically evolving networks of regions that interact in complex communication patterns. These reconfigurations may underlie exercise-induced improvements on cognitive measures of generalization, which are sensitive to subtle changes in the MTL.
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Affiliation(s)
- Neha Sinha
- Center for Molecular and Behavioral Neuroscience, Rutgers University-Newark, NJ, USA.
| | - Chelsie N Berg
- Center for Molecular and Behavioral Neuroscience, Rutgers University-Newark, NJ, USA.
| | - Michael A Yassa
- Center for the Neurobiology of Learning and Memory, Department of Neurobiology and Behavior, University of California, Irvine, CA, USA.
| | - Mark A Gluck
- Center for Molecular and Behavioral Neuroscience, Rutgers University-Newark, NJ, USA.
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Malagurski B, Liem F, Oschwald J, Mérillat S, Jäncke L. Longitudinal functional brain network reconfiguration in healthy aging. Hum Brain Mapp 2020; 41:4829-4845. [PMID: 32857461 PMCID: PMC7643380 DOI: 10.1002/hbm.25161] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Revised: 07/12/2020] [Accepted: 07/19/2020] [Indexed: 12/17/2022] Open
Abstract
Healthy aging is associated with changes in cognitive performance and functional brain organization. In fact, cross-sectional studies imply lower modularity and significant heterogeneity in modular architecture across older subjects. Here, we used a longitudinal dataset consisting of four occasions of resting-state-fMRI and cognitive testing (spanning 4 years) in 150 healthy older adults. We applied a graph-theoretic analysis to investigate the time-evolving modular structure of the whole-brain network, by maximizing the multilayer modularity across four time points. Global flexibility, which reflects the tendency of brain nodes to switch between modules across time, was significantly higher in healthy elderly than in a temporal null model. Further, global flexibility, as well as network-specific flexibility of the default mode, frontoparietal control, and somatomotor networks, were significantly associated with age at baseline. These results indicate that older age is related to higher variability in modular organization. The temporal metrics were not associated with simultaneous changes in processing speed or learning performance in the context of memory encoding. Finally, this approach provides global indices for longitudinal change across a given time span and it may contribute to uncovering patterns of modular variability in healthy and clinical aging populations.
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Affiliation(s)
- Brigitta Malagurski
- University Research Priority Program “Dynamics of Healthy Aging”University of ZurichZurichSwitzerland
| | - Franziskus Liem
- University Research Priority Program “Dynamics of Healthy Aging”University of ZurichZurichSwitzerland
| | - Jessica Oschwald
- University Research Priority Program “Dynamics of Healthy Aging”University of ZurichZurichSwitzerland
| | - Susan Mérillat
- University Research Priority Program “Dynamics of Healthy Aging”University of ZurichZurichSwitzerland
| | - Lutz Jäncke
- University Research Priority Program “Dynamics of Healthy Aging”University of ZurichZurichSwitzerland
- Division of Neuropsychology, Institute of PsychologyUniversity of ZurichZurichSwitzerland
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35
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Wang Y, Wang C, Miao P, Liu J, Wei Y, Wu L, Wang K, Cheng J. An imbalance between functional segregation and integration in patients with pontine stroke: A dynamic functional network connectivity study. NEUROIMAGE-CLINICAL 2020; 28:102507. [PMID: 33395996 PMCID: PMC7714678 DOI: 10.1016/j.nicl.2020.102507] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 10/24/2020] [Accepted: 11/12/2020] [Indexed: 11/04/2022]
Abstract
Pontine stroke patients show abnormal time-varying brain activity. Pontine stroke patients exist aberrant functional segregation and integration. The alterations of dFNC may lead to a poor functional recovery after stroke.
Background Previous studies on brain functional connectivity have revealed the neural physiopathology in patients with pontine stroke (PS). However, those studies focused only on the static features of intrinsic fluctuations, rather than on the time-varying effects throughout the entire scan. In the present study, we sought to explore the underlying mechanism of PS using the dynamic functional network connectivity (dFNC) method. Methods Resting-state functional magnetic resonance imaging (fMRI) data were collected from 58 patients with PS and 52 healthy controls (HC). Independent component analysis (ICA), the sliding window method, and k-means clustering analysis were performed to extract different functional networks, to calculate dFNC matrices, and to estimate distinct dynamic connectivity states. Additionally, temporal features were compared between the two groups in each state to explore the brain’s preference for different dynamic connectivity states in PS, and global and local efficiency were compared among states to explore the differences of topologic organization across different dFNC states. The correlations between clinical scales and the temporal features that differed between the two groups also were calculated. Results The dFNC analyses suggested four recurring states; in two of these states, the PS group showed a different duration from that of the HC group. Patients with PS spent significantly more time in a sparsely connected state (State 1), which was characterized by relatively low levels of connectivity within and between all brain networks. In contrast, patients with PS spent significantly less time in a highly segregated state (State 2), which was characterized by high levels of positive connectivities within primary perceptional domains and within higher cognitive control domains, and by high levels of negative inter-functional connectivities (inter-FCs) among primary perceptional and higher cognitive control domains. Additionally, the dwell time in State 2 was positively correlated with HC group’s long-term memory scores in the Rey Auditory Verbal Learning Test (RAVLT-L), whereas there was no correlation between the State-2 dwell time and RAVLT-L scores in the PS group. Furthermore, the sparsely connected state and the highly segregated state mentioned above had the highest global efficiency and the highest local efficiency among the four states, respectively. Conclusions In summary, we observed a preference in the aberrant brain for dynamic connectivity states with different network topologic organization in patients with PS, indicating abnormal functional segregation and integration of the whole brain and confirming the imperfection of functional network connectivity in patients with PS. These findings provide new evidence for the dynamic neural mechanisms underlying clinical symptoms in patients with PS.
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Affiliation(s)
- Yingying Wang
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Caihong Wang
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
| | - Peifang Miao
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingchun Liu
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Ying Wei
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Luobing Wu
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Kaiyu Wang
- GE Healthcare MR Research, Beijing, China
| | - Jingliang Cheng
- Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
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36
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Pläschke RN, Patil KR, Cieslik EC, Nostro AD, Varikuti DP, Plachti A, Lösche P, Hoffstaedter F, Kalenscher T, Langner R, Eickhoff SB. Age differences in predicting working memory performance from network-based functional connectivity. Cortex 2020; 132:441-459. [PMID: 33065515 PMCID: PMC7778730 DOI: 10.1016/j.cortex.2020.08.012] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Revised: 06/27/2020] [Accepted: 08/23/2020] [Indexed: 01/14/2023]
Abstract
Deterioration in working memory capacity (WMC) has been associated with normal aging, but it remains unknown how age affects the relationship between WMC and connectivity within functional brain networks. We therefore examined the predictability of WMC from fMRI-based resting-state functional connectivity (RSFC) within eight meta-analytically defined functional brain networks and the connectome in young and old adults using relevance vector machine in a robust cross-validation scheme. Particular brain networks have been associated with mental functions linked to WMC to a varying degree and are associated with age-related differences in performance. Comparing prediction performance between the young and old sample revealed age-specific effects: In young adults, we found a general unpredictability of WMC from RSFC in networks subserving WM, cognitive action control, vigilant attention, theory-of-mind cognition, and semantic memory, whereas in older adults each network significantly predicted WMC. Moreover, both WM-related and WM-unrelated networks were differently predictive in older adults with low versus high WMC. These results indicate that the within-network functional coupling during task-free states is specifically related to individual task performance in advanced age, suggesting neural-level reorganization. In particular, our findings support the notion of a decreased segregation of functional brain networks, deterioration of network integrity within different networks and/or compensation by reorganization as factors driving associations between individual WMC and within-network RSFC in older adults. Thus, using multivariate pattern regression provided novel insights into age-related brain reorganization by linking cognitive capacity to brain network integrity.
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Affiliation(s)
- Rachel N Pläschke
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
| | - Kaustubh R Patil
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Edna C Cieslik
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Alessandra D Nostro
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Deepthi P Varikuti
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Anna Plachti
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Patrick Lösche
- Leibniz Institute for International Educational Research (DIPF), Centre for Research on Human Development and Education, Frankfurt am Main, Germany
| | - Felix Hoffstaedter
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Tobias Kalenscher
- Comparative Psychology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Robert Langner
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Simon B Eickhoff
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
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Abstract
AbstractThe prospect of improving or maintaining cognitive functioning has provoked a steadily increasing number of cognitive training interventions over the last years, especially for clinical and elderly populations. However, there are discrepancies between the findings of the studies. One of the reasons behind these heterogeneous findings is that there are vast inter-individual differences in how people benefit from the training and in the extent that training-related gains are transferred to other untrained tasks and domains. In this paper, we address the value of incorporating neural measures to cognitive training studies in order to fully understand the mechanisms leading to inter-individual differences in training gains and their generalizability to other tasks. Our perspective is that it is necessary to collect multimodal neural measures in the pre- and post-training phase, which can enable us to understand the factors contributing to successful training outcomes. More importantly, this understanding can enable us to predict who will benefit from different types of interventions, thereby allowing the development of individually tailored intervention programs.
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38
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Chaddock-Heyman L, Weng TB, Kienzler C, Weisshappel R, Drollette ES, Raine LB, Westfall DR, Kao SC, Baniqued P, Castelli DM, Hillman CH, Kramer AF. Brain Network Modularity Predicts Improvements in Cognitive and Scholastic Performance in Children Involved in a Physical Activity Intervention. Front Hum Neurosci 2020; 14:346. [PMID: 33100988 PMCID: PMC7497763 DOI: 10.3389/fnhum.2020.00346] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Accepted: 08/04/2020] [Indexed: 01/23/2023] Open
Abstract
Introduction: Brain network modularity is a principle that quantifies the degree to which functional brain networks are divided into subnetworks. Higher modularity reflects a greater number of within-module connections and fewer connections between modules, and a highly modular brain is often interpreted as a brain that contains highly specialized brain networks with less integration between networks. Recent work in younger and older adults has demonstrated that individual differences in brain network modularity at baseline can predict improvements in performance after cognitive and physical interventions. The use of brain network modularity as a predictor of training outcomes has not yet been examined in children. Method: In the present study, we examined the relationship between baseline brain network modularity and changes (post-intervention performance minus pre-intervention performance) in cognitive and academic performance in 8- to 9-year-old children who participated in an after-school physical activity intervention for 9 months (N = 78) as well as in children in a wait-list control group (N = 72). Results: In children involved in the after-school physical activity intervention, higher modularity of brain networks at baseline predicted greater improvements in cognitive performance for tasks of executive function, cognitive efficiency, and mathematics achievement. There were no associations between baseline brain network modularity and performance changes in the wait-list control group. Discussion: Our study has implications for biomarkers of cognitive plasticity in children. Understanding predictors of cognitive performance and academic progress during child development may facilitate the effectiveness of interventions aimed to improve cognitive and brain health.
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Affiliation(s)
- Laura Chaddock-Heyman
- Beckman Institute, The University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Timothy B Weng
- Department of Diagnostic Medicine, The University of Texas at Austin, Austin, TX, United States
| | - Caitlin Kienzler
- Department of Psychology, University of Colorado, Denver, CO, United States
| | - Robert Weisshappel
- Beckman Institute, The University of Illinois at Urbana-Champaign, Urbana, IL, United States
| | - Eric S Drollette
- Department of Kinesiology, The University of North Carolina at Greensboro, Greensboro, NC, United States
| | - Lauren B Raine
- Department of Psychology, Northeastern University, Boston, MA, United States
| | - Daniel R Westfall
- Department of Psychology, Northeastern University, Boston, MA, United States
| | - Shih-Chun Kao
- Department of Psychology, Northeastern University, Boston, MA, United States
| | - Pauline Baniqued
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States.,Brain and Creativity Institute, University of Southern California, Los Angeles, CA, United States
| | - Darla M Castelli
- Department of Kinesiology and Health Education, The University of Texas at Austin, Austin, TX, United States
| | - Charles H Hillman
- Department of Psychology, Northeastern University, Boston, MA, United States.,Department of Physical Therapy, Movement, and Rehabilitation Sciences, Northeastern University, Boston, MA, United States
| | - Arthur F Kramer
- Beckman Institute, The University of Illinois at Urbana-Champaign, Urbana, IL, United States.,Department of Psychology, Northeastern University, Boston, MA, United States
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Smith LC, Kimbrough A. Leveraging Neural Networks in Preclinical Alcohol Research. Brain Sci 2020; 10:E578. [PMID: 32825739 PMCID: PMC7565429 DOI: 10.3390/brainsci10090578] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2020] [Revised: 08/17/2020] [Accepted: 08/18/2020] [Indexed: 12/25/2022] Open
Abstract
Alcohol use disorder is a pervasive healthcare issue with significant socioeconomic consequences. There is a plethora of neural imaging techniques available at the clinical and preclinical level, including magnetic resonance imaging and three-dimensional (3D) tissue imaging techniques. Network-based approaches can be applied to imaging data to create neural networks that model the functional and structural connectivity of the brain. These networks can be used to changes to brain-wide neural signaling caused by brain states associated with alcohol use. Neural networks can be further used to identify key brain regions or neural "hubs" involved in alcohol drinking. Here, we briefly review the current imaging and neurocircuit manipulation methods. Then, we discuss clinical and preclinical studies using network-based approaches related to substance use disorders and alcohol drinking. Finally, we discuss how preclinical 3D imaging in combination with network approaches can be applied alone and in combination with other approaches to better understand alcohol drinking.
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Affiliation(s)
- Lauren C. Smith
- Department of Psychiatry, School of Medicine, University of California San Diego, MC 0667, La Jolla, CA 92093, USA;
| | - Adam Kimbrough
- Department of Psychiatry, School of Medicine, University of California San Diego, MC 0667, La Jolla, CA 92093, USA;
- Department of Basic Medical Sciences, College of Veterinary Medicine, Purdue University, 625 Harrison Street, West Lafayette, IN 47907, USA
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40
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Saghayi M, Greenberg J, O’Grady C, Varno F, Hashmi MA, Bracken B, Matwin S, Lazar SW, Hashmi JA. Brain network topology predicts participant adherence to mental training programs. Netw Neurosci 2020; 4:528-555. [PMID: 32885114 PMCID: PMC7462432 DOI: 10.1162/netn_a_00136] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Accepted: 03/02/2020] [Indexed: 11/04/2022] Open
Abstract
Adherence determines the success and benefits of mental training (e.g., meditation) programs. It is unclear why some participants engage more actively in programs for mental training than others. Understanding neurobiological factors that predict adherence is necessary for understanding elements of learning and to inform better designs for new learning regimens. Clustering patterns in brain networks have been suggested to predict learning performance, but it is unclear whether these patterns contribute to motivational aspects of learning such as adherence. This study tests whether configurations of brain connections in resting-state fMRI scans can be used to predict adherence to two programs: meditation and creative writing. Results indicate that greater system segregation and clustering predict the number of practice sessions and class participation in both programs at a wide range of network thresholds (corrected p value < 0.05). At a local level, regions in subcortical circuitry such as striatum and accumbens predicted adherence in all subjects. Furthermore, there were also some important distinctions between groups: Adherence to meditation was predicted by connectivity within local network of the anterior insula and default mode network; and in the writing program, adherence was predicted by network neighborhood of frontal and temporal regions. Four machine learning methods were applied to test the robustness of the brain metric for classifying individual capacity for adherence and yielded reasonable accuracy. Overall, these findings underscore the fact that adherence and the ability to perform prescribed exercises is associated with organizational patterns of brain connectivity.
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Affiliation(s)
- Marzie Saghayi
- Department of Anesthesia, Pain Management, and Perioperative Medicine, Dalhousie University, NSHA, Halifax, Canada
| | | | - Christopher O’Grady
- Department of Anesthesia, Pain Management, and Perioperative Medicine, Dalhousie University, NSHA, Halifax, Canada
| | - Farshid Varno
- Faculty of Computer Science, Dalhousie University, Halifax, Canada
| | | | | | - Stan Matwin
- Faculty of Computer Science, Dalhousie University, Halifax, Canada
- Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland
| | - Sara W. Lazar
- Harvard Medical School, Mass General Hospital, Boston, MA, USA
| | - Javeria Ali Hashmi
- Department of Anesthesia, Pain Management, and Perioperative Medicine, Dalhousie University, NSHA, Halifax, Canada
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Gudmundsson L, Vohryzek J, Fornari E, Clarke S, Hagmann P, Crottaz-Herbette S. A brief exposure to rightward prismatic adaptation changes resting-state network characteristics of the ventral attentional system. PLoS One 2020; 15:e0234382. [PMID: 32584824 PMCID: PMC7316264 DOI: 10.1371/journal.pone.0234382] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Accepted: 05/26/2020] [Indexed: 12/02/2022] Open
Abstract
A brief session of rightward prismatic adaptation (R-PA) has been shown to alleviate neglect symptoms in patients with right hemispheric damage, very likely by switching hemispheric dominance of the ventral attentional network (VAN) from the right to the left and by changing task-related activity within the dorsal attentional network (DAN). We have investigated this very rapid change in functional organisation with a network approach by comparing resting-state connectivity before and after a brief exposure i) to R-PA (14 normal subjects; experimental condition) or ii) to plain glasses (12 normal subjects; control condition). A whole brain analysis (comprising 129 regions of interest) highlighted R-PA-induced changes within a bilateral, fronto-temporal network, which consisted of 13 nodes and 11 edges; all edges involved one of 4 frontal nodes, which were part of VAN. The analysis of network characteristics within VAN and DAN revealed a R-PA-induced decrease in connectivity strength between nodes and a decrease in local efficiency within VAN but not within DAN. These results indicate that the resting-state connectivity configuration of VAN is modulated by R-PA, possibly by decreasing its modularity.
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Affiliation(s)
- Louis Gudmundsson
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV), and University of Lausanne, Lausanne, Switzerland
- Neuropsychology and Neurorehabilitation Service, Centre Hospitalier Universitaire Vaudois (CHUV), and University of Lausanne, Lausanne, Switzerland
| | - Jakub Vohryzek
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV), and University of Lausanne, Lausanne, Switzerland
- Department of Psychiatry, Hedonia Research Group, University of Oxford, Oxford, United Kingdom
| | - Eleonora Fornari
- CIBM (Centre d'Imagerie Biomédicale), Dept. of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV), and University of Lausanne, Lausanne, Switzerland
| | - Stephanie Clarke
- Neuropsychology and Neurorehabilitation Service, Centre Hospitalier Universitaire Vaudois (CHUV), and University of Lausanne, Lausanne, Switzerland
| | - Patric Hagmann
- Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV), and University of Lausanne, Lausanne, Switzerland
- Signal Processing Lab 5 (LTS5), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Sonia Crottaz-Herbette
- Neuropsychology and Neurorehabilitation Service, Centre Hospitalier Universitaire Vaudois (CHUV), and University of Lausanne, Lausanne, Switzerland
- * E-mail:
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42
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The Effects of Cognitive Training on Brain Network Activity and Connectivity in Aging and Neurodegenerative Diseases: a Systematic Review. Neuropsychol Rev 2020; 30:267-286. [PMID: 32529356 PMCID: PMC7305076 DOI: 10.1007/s11065-020-09440-w] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Accepted: 05/03/2020] [Indexed: 12/12/2022]
Abstract
Cognitive training (CT) is an increasingly popular, non-pharmacological intervention for improving cognitive functioning in neurodegenerative diseases and healthy aging. Although meta-analyses support the efficacy of CT in improving cognitive functioning, the neural mechanisms underlying the effects of CT are still unclear. We performed a systematic review of literature in the PubMed, Embase and PsycINFO databases on controlled CT trials (N > 20) in aging and neurodegenerative diseases with pre- and post-training functional MRI outcomes up to November 23rd 2018 (PROSPERO registration number CRD42019103662). Twenty articles were eligible for our systematic review. We distinguished between multi-domain and single-domain CT. CT induced both increases and decreases in task-related functional activation, possibly indicative of an inverted U-shaped curve association between regional brain activity and task performance. Functional connectivity within ‘cognitive’ brain networks was consistently reported to increase after CT while a minority of studies additionally reported increased segregation of frontoparietal and default mode brain networks. Although we acknowledge the large heterogeneity in type of CT, imaging methodology, in-scanner task paradigm and analysis methods between studies, we propose a working model of the effects of CT on brain activity and connectivity in the context of current knowledge on compensatory mechanisms that are associated with aging and neurodegenerative diseases.
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Higgins JP, Elliott JM, Parrish TB. Brain Network Disruption in Whiplash. AJNR Am J Neuroradiol 2020; 41:994-1000. [PMID: 32499250 DOI: 10.3174/ajnr.a6569] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Accepted: 04/14/2020] [Indexed: 01/02/2023]
Abstract
BACKGROUND AND PURPOSE Whiplash-associated disorders frequently develop following motor vehicle collisions and often involve a range of cognitive and affective symptoms, though the neural correlates of the disorder are largely unknown. In this study, a sample of participants with chronic whiplash injuries were scanned by using resting-state fMRI to assess brain network changes associated with long-term outcome metrics. MATERIALS AND METHODS Resting-state fMRI was collected for 23 participants and used to calculate network modularity, a quantitative measure of the functional segregation of brain region communities. This was analyzed for associations with whiplash-associated disorder outcome metrics, including scales of neck disability, traumatic distress, depression, and pain. In addition to these clinical scales, cervical muscle fat infiltration was quantified by using Dixon fat-water imaging, which has shown promise as a biomarker for assessing disorder severity and predicting recovery in chronic whiplash. RESULTS An association was found between brain network structure and muscle fat infiltration, wherein lower network modularity was associated with larger amounts of cervical muscle fat infiltration after controlling for age, sex, body mass index, and scan motion (t = -4.02, partial R 2 = 0.49, P < .001). CONCLUSIONS This work contributes to the existing whiplash literature by examining a sample of participants with whiplash-associated disorder by using resting-state fMRI. Less modular brain networks were found to be associated with greater amounts of cervical muscle fat infiltration suggesting a connection between disorder severity and neurologic changes, and a potential role for neuroimaging in understanding the pathophysiology of chronic whiplash-associated disorders.
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Affiliation(s)
- J P Higgins
- From the Departments of Radiology (J.P.H., T.B.P.)
| | - J M Elliott
- Physical Therapy and Human Movement Sciences (J.M.E.), Feinberg School of Medicine, Northwestern University, Chicago, Illinois
- Discipline of Physiotherapy, Faculty of Health Sciences (J.M.E.), The University of Sydney and the Northern Sydney Local Health District; and The Kolling Research Institute, St. Leonards, NSW, Australia
| | - T B Parrish
- From the Departments of Radiology (J.P.H., T.B.P.)
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44
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Bonkhoff AK, Espinoza FA, Gazula H, Vergara VM, Hensel L, Michely J, Paul T, Rehme AK, Volz LJ, Fink GR, Calhoun VD, Grefkes C. Acute ischaemic stroke alters the brain's preference for distinct dynamic connectivity states. Brain 2020; 143:1525-1540. [PMID: 32357220 PMCID: PMC7241954 DOI: 10.1093/brain/awaa101] [Citation(s) in RCA: 55] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Revised: 01/26/2020] [Accepted: 02/16/2020] [Indexed: 01/01/2023] Open
Abstract
Acute ischaemic stroke disturbs healthy brain organization, prompting subsequent plasticity and reorganization to compensate for the loss of specialized neural tissue and function. Static resting state functional MRI studies have already furthered our understanding of cerebral reorganization by estimating stroke-induced changes in network connectivity aggregated over the duration of several minutes. In this study, we used dynamic resting state functional MRI analyses to increase temporal resolution to seconds and explore transient configurations of motor network connectivity in acute stroke. To this end, we collected resting state functional MRI data of 31 patients with acute ischaemic stroke and 17 age-matched healthy control subjects. Stroke patients presented with moderate to severe hand motor deficits. By estimating dynamic functional connectivity within a sliding window framework, we identified three distinct connectivity configurations of motor-related networks. Motor networks were organized into three regional domains, i.e. a cortical, subcortical and cerebellar domain. The dynamic connectivity patterns of stroke patients diverged from those of healthy controls depending on the severity of the initial motor impairment. Moderately affected patients (n = 18) spent significantly more time in a weakly connected configuration that was characterized by low levels of connectivity, both locally as well as between distant regions. In contrast, severely affected patients (n = 13) showed a significant preference for transitions into a spatially segregated connectivity configuration. This configuration featured particularly high levels of local connectivity within the three regional domains as well as anti-correlated connectivity between distant networks across domains. A third connectivity configuration represented an intermediate connectivity pattern compared to the preceding two, and predominantly encompassed decreased interhemispheric connectivity between cortical motor networks independent of individual deficit severity. Alterations within this third configuration thus closely resembled previously reported ones originating from static resting state functional MRI studies post-stroke. In summary, acute ischaemic stroke not only prompted changes in connectivity between distinct networks, but it also caused characteristic changes in temporal properties of large-scale network interactions depending on the severity of the individual deficit. These findings offer new vistas on the dynamic neural mechanisms underlying acute neurological symptoms, cortical reorganization and treatment effects in stroke patients.
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Affiliation(s)
- Anna K Bonkhoff
- Department of Neurology, University Hospital Cologne and Medical Faculty, University of Cologne, Germany
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre Juelich, Juelich, Germany
- Queen Square Institute of Neurology, University College London, London, UK
| | | | - Harshvardhan Gazula
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
| | - Victor M Vergara
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
| | - Lukas Hensel
- Department of Neurology, University Hospital Cologne and Medical Faculty, University of Cologne, Germany
| | - Jochen Michely
- Department of Neurology, University Hospital Cologne and Medical Faculty, University of Cologne, Germany
| | - Theresa Paul
- Department of Neurology, University Hospital Cologne and Medical Faculty, University of Cologne, Germany
| | - Anne K Rehme
- Department of Neurology, University Hospital Cologne and Medical Faculty, University of Cologne, Germany
| | - Lukas J Volz
- Department of Neurology, University Hospital Cologne and Medical Faculty, University of Cologne, Germany
| | - Gereon R Fink
- Department of Neurology, University Hospital Cologne and Medical Faculty, University of Cologne, Germany
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre Juelich, Juelich, Germany
| | - Vince D Calhoun
- The Mind Research Network, Albuquerque, New Mexico, USA
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
| | - Christian Grefkes
- Department of Neurology, University Hospital Cologne and Medical Faculty, University of Cologne, Germany
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Centre Juelich, Juelich, Germany
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45
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From Evaluation to Prediction: Behavioral Effects and Biological Markers of Cognitive Control Intervention. Neural Plast 2020; 2020:1869459. [PMID: 32184812 PMCID: PMC7060425 DOI: 10.1155/2020/1869459] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 11/25/2019] [Accepted: 01/30/2020] [Indexed: 12/02/2022] Open
Abstract
Although the intervention effectiveness of cognitive control is disputed, some methods, such as single-task training, integrated training, meditation, aerobic exercise, and transcranial stimulation, have been reported to improve cognitive control. This review of recent advances from evaluation to prediction of cognitive control interventions suggests that brain modularity may be an important candidate marker for informing clinical decisions regarding suitable interventions. The intervention effect of cognitive control has been evaluated by behavioral performance, transfer effect, brain structure and function, and brain networks. Brain modularity can predict the benefits of cognitive control interventions based on individual differences and is independent of intervention method, group, age, initial cognitive ability, and education level. The prediction of cognitive control intervention based on brain modularity should extend to task states, combine function and structure networks, and assign different weights to subnetwork modularity.
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46
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Gu S, Xia CH, Ciric R, Moore TM, Gur RC, Gur RE, Satterthwaite TD, Bassett DS. Unifying the Notions of Modularity and Core-Periphery Structure in Functional Brain Networks during Youth. Cereb Cortex 2020; 30:1087-1102. [PMID: 31504253 PMCID: PMC7132934 DOI: 10.1093/cercor/bhz150] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2019] [Revised: 06/14/2019] [Accepted: 06/17/2019] [Indexed: 02/06/2023] Open
Abstract
At rest, human brain functional networks display striking modular architecture in which coherent clusters of brain regions are activated. The modular account of brain function is pervasive, reliable, and reproducible. Yet, a complementary perspective posits a core-periphery or rich-club account of brain function, where hubs are densely interconnected with one another, allowing for integrative processing. Unifying these two perspectives has remained difficult due to the fact that the methodological tools to identify modules are entirely distinct from the methodological tools to identify core-periphery structure. Here, we leverage a recently-developed model-based approach-the weighted stochastic block model-that simultaneously uncovers modular and core-periphery structure, and we apply it to functional magnetic resonance imaging data acquired at rest in 872 youth of the Philadelphia Neurodevelopmental Cohort. We demonstrate that functional brain networks display rich mesoscale organization beyond that sought by modularity maximization techniques. Moreover, we show that this mesoscale organization changes appreciably over the course of neurodevelopment, and that individual differences in this organization predict individual differences in cognition more accurately than module organization alone. Broadly, our study provides a unified assessment of modular and core-periphery structure in functional brain networks, offering novel insights into their development and implications for behavior.
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Affiliation(s)
- Shi Gu
- School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Cedric Huchuan Xia
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Rastko Ciric
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Tyler M Moore
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ruben C Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Raquel E Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | | | - Danielle S Bassett
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Physics and Astronomy, College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Electrical and Systems Engineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Santa Fe Institute, 1399 Hyde Park Rd, Santa Fe, NM 87501 USA
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47
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Douw L, Quaak M, Fitzsimmons SM, de Wit SJ, van der Werf YD, van den Heuvel OA, Vriend C. Static and dynamic network properties of the repetitive transcranial magnetic stimulation target predict changes in emotion regulation in obsessive-compulsive disorder. Brain Stimul 2020; 13:318-326. [DOI: 10.1016/j.brs.2019.10.017] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Revised: 10/18/2019] [Accepted: 10/21/2019] [Indexed: 01/23/2023] Open
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48
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Vatansever D, Schröter M, Adapa RM, Bullmore ET, Menon DK, Stamatakis EA. Reorganisation of Brain Hubs across Altered States of Consciousness. Sci Rep 2020; 10:3402. [PMID: 32099008 PMCID: PMC7042369 DOI: 10.1038/s41598-020-60258-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2019] [Accepted: 01/31/2020] [Indexed: 12/12/2022] Open
Abstract
Patterns of functional interactions across distributed brain regions are suggested to provide a scaffold for the conscious processing of information, with marked topological alterations observed in loss of consciousness. However, establishing a firm link between macro-scale brain network organisation and conscious cognition requires direct investigations into neuropsychologically-relevant architectural modifications across systematic reductions in consciousness. Here we assessed both global and regional disturbances to brain graphs in a group of healthy participants across baseline resting state fMRI as well as two distinct levels of propofol-induced sedation. We found a persistent modular architecture, yet significant reorganisation of brain hubs that formed parts of a wider rich-club collective. Furthermore, the reduction in the strength of rich-club connectivity was significantly associated with the participants’ performance in a semantic judgment task, indicating the importance of this higher-order topological feature for conscious cognition. These results highlight a remarkable interplay between global and regional properties of brain functional interactions in supporting conscious cognition that is relevant to our understanding of clinical disorders of consciousness.
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Affiliation(s)
- D Vatansever
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, 200433, Shanghai, PR China. .,Division of Anaesthesia and Department of Clinical Neurosciences, School of Clinical Medicine, UK & Wolfson Brain Imaging Centre, University of Cambridge, CB2 0QQ, Cambridge, UK. .,Department of Psychiatry, School of Clinical Medicine, University of Cambridge, CB2 0QQ, Cambridge, UK.
| | - M Schröter
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, CB2 0QQ, Cambridge, UK.,Department of Biosystems Science and Engineering, Bio Engineering Laboratory, ETH Zurich, 4058, Basel, Switzerland
| | - R M Adapa
- Division of Anaesthesia and Department of Clinical Neurosciences, School of Clinical Medicine, UK & Wolfson Brain Imaging Centre, University of Cambridge, CB2 0QQ, Cambridge, UK
| | - E T Bullmore
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, CB2 0QQ, Cambridge, UK.,Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge Road, Fulbourn, CB21 5HH, Cambridge, UK
| | - D K Menon
- Division of Anaesthesia and Department of Clinical Neurosciences, School of Clinical Medicine, UK & Wolfson Brain Imaging Centre, University of Cambridge, CB2 0QQ, Cambridge, UK
| | - E A Stamatakis
- Division of Anaesthesia and Department of Clinical Neurosciences, School of Clinical Medicine, UK & Wolfson Brain Imaging Centre, University of Cambridge, CB2 0QQ, Cambridge, UK
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49
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Malagurski B, Liem F, Oschwald J, Mérillat S, Jäncke L. Functional dedifferentiation of associative resting state networks in older adults - A longitudinal study. Neuroimage 2020; 214:116680. [PMID: 32105885 DOI: 10.1016/j.neuroimage.2020.116680] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2019] [Revised: 02/21/2020] [Accepted: 02/23/2020] [Indexed: 12/12/2022] Open
Abstract
Healthy aging is associated with weaker functional connectivity within resting state brain networks and stronger functional interaction between these networks. This phenomenon has been characterized as reduced functional segregation and has been investigated mainly in cross-sectional studies. Here, we used a longitudinal dataset which consisted of four occasions of resting state fMRI and psychometric cognitive ability data, collected from a sample of healthy older adults (baseline N = 232, age range: 64-87 y, age M = 70.8 y), to investigate the functional segregation of several well-defined resting state networks encompassing the whole brain. We characterized the ratio of within-network and between-network correlations via the well-established segregation index. Our findings showed a decrease over a 4-year interval in the functional segregation of the default mode, frontoparietal control and salience ventral attention networks. In contrast, we showed an increase in the segregation of the limbic network over the same interval. More importantly, the rate of change in functional segregation of the frontoparietal control network was associated with the rate of change in processing speed. These findings support the hypothesis of functional dedifferentiation in healthy aging as well as its role in cognitive function in elderly.
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Affiliation(s)
- Brigitta Malagurski
- University Research Priority Program "Dynamics of Healthy Aging", University of Zurich, Zurich, Switzerland.
| | - Franziskus Liem
- University Research Priority Program "Dynamics of Healthy Aging", University of Zurich, Zurich, Switzerland
| | - Jessica Oschwald
- University Research Priority Program "Dynamics of Healthy Aging", University of Zurich, Zurich, Switzerland
| | - Susan Mérillat
- University Research Priority Program "Dynamics of Healthy Aging", University of Zurich, Zurich, Switzerland
| | - Lutz Jäncke
- University Research Priority Program "Dynamics of Healthy Aging", University of Zurich, Zurich, Switzerland; Division of Neuropsychology, Institute of Psychology, University of Zurich, Zurich, Switzerland
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50
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Kong TS, Gratton C, Low KA, Tan CH, Chiarelli AM, Fletcher MA, Zimmerman B, Maclin EL, Sutton BP, Gratton G, Fabiani M. Age-related differences in functional brain network segregation are consistent with a cascade of cerebrovascular, structural, and cognitive effects. Netw Neurosci 2020; 4:89-114. [PMID: 32043045 PMCID: PMC7006874 DOI: 10.1162/netn_a_00110] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Accepted: 09/21/2019] [Indexed: 01/09/2023] Open
Abstract
Age-related declines in cognition are associated with widespread structural and functional brain changes, including changes in resting-state functional connectivity and gray and white matter status. Recently we have shown that the elasticity of cerebral arteries also explains some of the variance in cognitive and brain health in aging. Here, we investigated how network segregation, cerebral arterial elasticity (measured with pulse-DOT-the arterial pulse based on diffuse optical tomography) and gray and white matter status jointly account for age-related differences in cognitive performance. We hypothesized that at least some of the variance in brain and cognitive aging is linked to reduced cerebrovascular elasticity, leading to increased cortical atrophy and white matter abnormalities, which, in turn, are linked to reduced network segregation and decreases in cognitive performance. Pairwise comparisons between these variables are consistent with an exploratory hierarchical model linking them, especially when focusing on association network segregation (compared with segregation in sensorimotor networks). These findings suggest that preventing or slowing age-related changes in one or more of these factors may induce a neurophysiological cascade beneficial for preserving cognition in aging.
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Affiliation(s)
- Tania S. Kong
- Beckman Institute, University of Illinois at Urbana-Champaign, IL, USA
- Psychology Department, University of Illinois at Urbana-Champaign, IL, USA
| | - Caterina Gratton
- Department of Psychology, Northwestern University, IL, USA
- Department of Neurology, Northwestern University, IL, USA
| | - Kathy A. Low
- Beckman Institute, University of Illinois at Urbana-Champaign, IL, USA
| | - Chin Hong Tan
- Beckman Institute, University of Illinois at Urbana-Champaign, IL, USA
- Division of Psychology, Nanyang Technological University, Singapore
- Department of Pharmacology, National University of Singapore, Singapore
| | - Antonio M. Chiarelli
- Beckman Institute, University of Illinois at Urbana-Champaign, IL, USA
- Department of Neuroscience, Imaging and Clinical Sciences, University G. D’Annunzio of Chieti-Pescara, Chieti, Italy
| | - Mark A. Fletcher
- Beckman Institute, University of Illinois at Urbana-Champaign, IL, USA
| | | | - Edward L. Maclin
- Beckman Institute, University of Illinois at Urbana-Champaign, IL, USA
| | - Bradley P. Sutton
- Beckman Institute, University of Illinois at Urbana-Champaign, IL, USA
- Department of Bioengineering, University of Illinois at Urbana-Champaign, IL, USA
| | - Gabriele Gratton
- Beckman Institute, University of Illinois at Urbana-Champaign, IL, USA
- Psychology Department, University of Illinois at Urbana-Champaign, IL, USA
| | - Monica Fabiani
- Beckman Institute, University of Illinois at Urbana-Champaign, IL, USA
- Psychology Department, University of Illinois at Urbana-Champaign, IL, USA
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