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Van Ruitenbeek P, Santos Monteiro T, Chalavi S, King BR, Cuypers K, Sunaert S, Peeters R, Swinnen SP. Interactions between the aging brain and motor task complexity across the lifespan: balancing brain activity resource demand and supply. Cereb Cortex 2022; 33:6420-6434. [PMID: 36587289 PMCID: PMC10183738 DOI: 10.1093/cercor/bhac514] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 12/02/2022] [Accepted: 12/03/2022] [Indexed: 01/02/2023] Open
Abstract
The Compensation Related Utilization of Neural Circuits Hypothesis (CRUNCH) proposes a framework for understanding task-related brain activity changes as a function of healthy aging and task complexity. Specifically, it affords the following predictions: (i) all adult age groups display more brain activation with increases in task complexity, (ii) older adults show more brain activation compared with younger adults at low task complexity levels, and (iii) disproportionately increase brain activation with increased task complexity, but (iv) show smaller (or no) increases in brain activation at the highest complexity levels. To test these hypotheses, performance on a bimanual tracking task at 4 complexity levels and associated brain activation were assessed in 3 age groups (20-40, 40-60, and 60-80 years, n = 99). All age groups showed decreased tracking accuracy and increased brain activation with increased task complexity, with larger performance decrements and activation increases in the older age groups. Older adults exhibited increased brain activation at a lower complexity level, but not the predicted failure to further increase brain activity at the highest complexity level. We conclude that older adults show more brain activation than younger adults and preserve the capacity to deploy increased neural resources as a function of task demand.
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Affiliation(s)
- P Van Ruitenbeek
- KU Leuven, Movement Control and Neuroplasticity Research Group, Biomedical Sciences, Tervuursevest 101, box 1501, 3001, Leuven, Belgium.,Department of Neuropsychology and Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, the Netherlands
| | - T Santos Monteiro
- KU Leuven, Movement Control and Neuroplasticity Research Group, Biomedical Sciences, Tervuursevest 101, box 1501, 3001, Leuven, Belgium
| | - S Chalavi
- KU Leuven, Movement Control and Neuroplasticity Research Group, Biomedical Sciences, Tervuursevest 101, box 1501, 3001, Leuven, Belgium
| | - B R King
- KU Leuven, Movement Control and Neuroplasticity Research Group, Biomedical Sciences, Tervuursevest 101, box 1501, 3001, Leuven, Belgium.,Department of Health & Kinesiology; University of Utah, 250 South 1850 East, Salt Lake City, Utah 84112
| | - K Cuypers
- KU Leuven, Movement Control and Neuroplasticity Research Group, Biomedical Sciences, Tervuursevest 101, box 1501, 3001, Leuven, Belgium.,Neuroplasticity and Movement Control Research Group, Rehabilitation Research Institute (REVAL), Hasselt University, Agoralaan Gebouw A, 3590,Diepenbeek, Belgium
| | - S Sunaert
- KU Leuven, Department of Imaging and Pathology, Biomedical Sciences, UZ Herestraat 49, box 7003, 3000, Leuven, Belgium.,KU Leuven, Leuven Brain Institute (LBI), ON V Herestraat 49, box 1020, 3000, Leuven, Belgium
| | - R Peeters
- KU Leuven, Department of Imaging and Pathology, Biomedical Sciences, UZ Herestraat 49, box 7003, 3000, Leuven, Belgium.,KU Leuven, Leuven Brain Institute (LBI), ON V Herestraat 49, box 1020, 3000, Leuven, Belgium
| | - S P Swinnen
- KU Leuven, Movement Control and Neuroplasticity Research Group, Biomedical Sciences,Tervuursevest 101, box 1501, 3001, Leuven, Belgium.,KU Leuven, Leuven Brain Institute (LBI), ON V Herestraat 49, box 1020, 3000, Leuven, Belgium
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2
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Fabiani M, Asnakew BA, Bowie DC, Chism SM, Clements GM, Gardner JC, Islam SS, Rubenstein SL, Gratton G. A healthy mind in a healthy body: Effects of arteriosclerosis and other risk factors on cognitive aging and dementia. THE PSYCHOLOGY OF LEARNING AND MOTIVATION 2022; 77:69-123. [PMID: 37139101 PMCID: PMC10153623 DOI: 10.1016/bs.plm.2022.08.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
In this review we start from the assumption that, to fully understand cognitive aging, it is important to embrace a holistic view, integrating changes in bodily, brain, and cognitive functions. This broad view can help explain individual differences in aging trajectories and could ultimately enable prevention and remediation strategies. As the title of this review suggests, we claim that there are not only indirect but also direct effects of various organ systems on the brain, creating cascades of phenomena that strongly contribute to age-related cognitive decline. Here we focus primarily on the cerebrovascular system, because of its direct effects on brain health and close connections with the development and progression of Alzheimer's Disease and other types of dementia. We start by reviewing the main cognitive changes that are often observed in normally aging older adults, as well as the brain systems that support them. Second, we provide a brief overview of the cerebrovascular system and its known effects on brain anatomy and function, with a focus on aging. Third, we review genetic and lifestyle risk factors that may affect the cerebrovascular system and ultimately contribute to cognitive decline. Lastly, we discuss this evidence, review limitations, and point out avenues for additional research and clinical intervention.
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Affiliation(s)
- Monica Fabiani
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Champaign, IL, United States
- Psychology Department, University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | - Bethlehem A. Asnakew
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Champaign, IL, United States
- Psychology Department, University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | - Daniel C. Bowie
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Champaign, IL, United States
- Psychology Department, University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | - Sydney M. Chism
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Champaign, IL, United States
- Psychology Department, University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | - Grace M. Clements
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Champaign, IL, United States
- Psychology Department, University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | - Jennie C. Gardner
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Champaign, IL, United States
- Psychology Department, University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | - Samia S. Islam
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Champaign, IL, United States
- Psychology Department, University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | - Samantha L. Rubenstein
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Champaign, IL, United States
- Psychology Department, University of Illinois at Urbana-Champaign, Champaign, IL, United States
| | - Gabriele Gratton
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Champaign, IL, United States
- Psychology Department, University of Illinois at Urbana-Champaign, Champaign, IL, United States
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3
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Richmond LL, Sargent JQ, Zacks JM. Virtual navigation in healthy aging: Activation during learning and deactivation during retrieval predicts successful memory for spatial locations. Neuropsychologia 2022; 173:108298. [PMID: 35697090 PMCID: PMC10546223 DOI: 10.1016/j.neuropsychologia.2022.108298] [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: 06/17/2021] [Revised: 06/07/2022] [Accepted: 06/08/2022] [Indexed: 11/24/2022]
Abstract
Spatial navigation and spatial memory are two important skills for independent living, and are known to be compromised with age. Here, we investigate the neural correlates of successful spatial memory in healthy older adults in order to learn more about the neural underpinnings of maintenance of navigation skill into old age. Healthy older adults watched a video shot by a person navigating a route and were asked to remember objects along the route and then attempted to remember object locations by virtually pointing to the location of hidden objects from several locations along the route. Brain activity during watching and pointing was recorded with functional MRI. Larger activations in temporal and frontal regions during watching, and larger deactivations in superior parietal cortex and intraparietal sulcus during pointing, were associated with smaller location errors. These findings suggest that larger evoked responses during learning of spatial information coupled with larger deactivation of canonical spatial memory regions at retrieval are important for effective spatial memory in late life.
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Affiliation(s)
- Lauren L Richmond
- Department of Psychological and Brain Sciences, Washington University in St Louis, USA; Department of Psychology, Stony Brook University, USA.
| | | | - Jeffrey M Zacks
- Department of Psychological and Brain Sciences, Washington University in St Louis, USA
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McKay NS, Dincer A, Mehrotra V, Aschenbrenner AJ, Balota D, Hornbeck RC, Hassenstab J, Morris JC, Benzinger TLS, Gordon BA. Beta-amyloid moderates the relationship between cortical thickness and attentional control in middle- and older-aged adults. Neurobiol Aging 2022; 112:181-190. [PMID: 35227946 PMCID: PMC9208719 DOI: 10.1016/j.neurobiolaging.2021.12.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 12/13/2021] [Accepted: 12/28/2021] [Indexed: 12/13/2022]
Abstract
Although often unmeasured in studies of cognition, many older adults possess Alzheimer disease (AD) pathologies such as beta-amyloid (Aβ) deposition, despite being asymptomatic. We were interested in examining whether the behavior-structure relationship observed in later life was altered by the presence of preclinical AD pathology. A total of 511 cognitively unimpaired adults completed magnetic resonance imaging and three attentional control tasks; a subset (n = 396) also underwent Aβ-positron emissions tomography. A vertex-wise model was conducted to spatially represent the relationship between cortical thickness and average attentional control accuracy, while moderation analysis examined whether Aβ deposition impacted this relationship. First, we found that reduced cortical thickness in temporal, medial- and lateral-parietal, and dorsolateral prefrontal cortex, predicted worse performance on the attention task composite. Subsequent moderation analyses observed that levels of Aβ significantly influence the relationship between cortical thickness and attentional control. Our results support the hypothesis that preclinical AD, as measured by Aβ deposition, is partially driving what would otherwise be considered general aging in a cognitively normal adult population.
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Affiliation(s)
- Nicole S McKay
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO; Knight Alzheimer's Disease Research Center, Washington University in St. Louis, MO.
| | - Aylin Dincer
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO; Knight Alzheimer's Disease Research Center, Washington University in St. Louis, MO
| | | | - Andrew J Aschenbrenner
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, MO; Department of Neurology, Washington School of Medicine, St. Louis, MO
| | - David Balota
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, MO; Department of Psychological and Brain Sciences, Washington University in St. Louis, MO
| | - Russ C Hornbeck
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO; Knight Alzheimer's Disease Research Center, Washington University in St. Louis, MO
| | - Jason Hassenstab
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, MO; Department of Neurology, Washington School of Medicine, St. Louis, MO; Department of Psychological and Brain Sciences, Washington University in St. Louis, MO
| | - John C Morris
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, MO; Department of Neurology, Washington School of Medicine, St. Louis, MO
| | - Tammie L S Benzinger
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO; Knight Alzheimer's Disease Research Center, Washington University in St. Louis, MO
| | - Brian A Gordon
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO; Knight Alzheimer's Disease Research Center, Washington University in St. Louis, MO; Department of Psychological and Brain Sciences, Washington University in St. Louis, MO
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5
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Veldema J, Nowak DA, Gharabaghi A. Resting motor threshold in the course of hand motor recovery after stroke: a systematic review. J Neuroeng Rehabil 2021; 18:158. [PMID: 34732203 PMCID: PMC8564987 DOI: 10.1186/s12984-021-00947-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 10/13/2021] [Indexed: 12/24/2022] Open
Abstract
Background Resting motor threshold is an objective measure of cortical excitability. Numerous studies indicate that the success of motor recovery after stroke is significantly determined by the direction and extent of cortical excitability changes. A better understanding of this topic (particularly with regard to the level of motor impairment and the contribution of either cortical hemisphere) may contribute to the development of effective therapeutical strategies in this cohort. Objectives This systematic review collects and analyses the available evidence on resting motor threshold and hand motor recovery in stroke patients. Methods PubMed was searched from its inception through to 31/10/2020 on studies investigating resting motor threshold of the affected and/or the non-affected hemisphere and motor function of the affected hand in stroke cohorts. Results Overall, 92 appropriate studies (including 1978 stroke patients and 377 healthy controls) were identified. The analysis of the data indicates that severe hand impairment is associated with suppressed cortical excitability within both hemispheres and with great between-hemispheric imbalance of cortical excitability. Favorable motor recovery is associated with an increase of ipsilesional motor cortex excitability and reduction of between-hemispheric imbalance. The direction of change of contralesional motor cortex excitability depends on the amount of hand motor impairment. Severely disabled patients show an increase of contralesional motor cortex excitability during motor recovery. In contrast, recovery of moderate to mild hand motor impairment is associated with a decrease of contralesional motor cortex excitability. Conclusions This data encourages a differential use of rehabilitation strategies to modulate cortical excitability. Facilitation of the ipsilesional hemisphere may support recovery in general, whereas facilitation and inhibition of the contralesional hemisphere may enhance recovery in severe and less severely impaired patients, respectively.
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Affiliation(s)
- Jitka Veldema
- Institute for Neuromodulation and Neurotechnology, Department of Neurosurgery and Neurotechnology, University Hospital and University of Tübingen, Otfried-Mueller-Str.45, 72076, Tübingen, Germany.
| | - Dennis Alexander Nowak
- Department of Neurology, VAMED Hospital Kipfenberg, Konrad-Regler-Straße 1, 85110, Kipfenberg, Germany
| | - Alireza Gharabaghi
- Institute for Neuromodulation and Neurotechnology, Department of Neurosurgery and Neurotechnology, University Hospital and University of Tübingen, Otfried-Mueller-Str.45, 72076, Tübingen, Germany
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Yang MH, Yao ZF, Hsieh S. Multimodal neuroimaging analysis reveals age-associated common and discrete cognitive control constructs. Hum Brain Mapp 2019; 40:2639-2661. [PMID: 30779255 DOI: 10.1002/hbm.24550] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2018] [Revised: 01/06/2019] [Accepted: 02/04/2019] [Indexed: 12/29/2022] Open
Abstract
The aims of this study were to determine which cognitive control functions are most sensitive to cross-sectional age differences and to identify neural features in different neuroimaging modalities that associated cognitive control function across the adult lifespan. We employed a joint independent component analysis (jICA) approach to obtain common networks among three different brain-imaging modalities (i.e., structural MRI, resting-state functional MRI, and diffusion tensor imaging) in relation to the cognitive control function. We differentiated three distinct cognitive constructs: one common (across inhibition, shifting, and updating) and two specific (shifting, updating) factors. These common/specific constructs were transformed from three original performance indexes: (a) stop-signal reaction time, (b) switch-cost, and (c) performance sensitivity collected from 156 individuals aged 20 to 78 years old. The current results show that the cross-sectional age difference is associated with a wide spread of brain degeneration that is not limited to the frontal region. Crucially, these findings suggest there are some common and distinct joined multimodal components that correlate with the psychological constructs of common and discrete cognitive control functions, respectively. To support current findings, other fusion ICA models were also analyzed including, parallel ICA (para-ICA) and multiset canonical correlation analysis with jICA (mCCA + jICA). Dynamic interactions among these brain features across different brain modalities could serve as possible developmental mechanisms associated with these age effects.
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Affiliation(s)
- Meng-Heng Yang
- Department of Psychology, National Cheng Kung University, Tainan, Taiwan, Republic of China
| | - Zai-Fu Yao
- Brain and Cognition, Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
| | - Shulan Hsieh
- Department of Psychology, National Cheng Kung University, Tainan, Taiwan, Republic of China.,Institue of Allied Health Sciences, National Cheng Kung University, Tainan, Taiwan, Republic of China.,Department and Institute of Public Health, National Cheng Kung University, Tainan, Taiwan, Republic of China
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Gratton G, Cooper P, Fabiani M, Carter CS, Karayanidis F. Dynamics of cognitive control: Theoretical bases, paradigms, and a view for the future. Psychophysiology 2017; 55. [DOI: 10.1111/psyp.13016] [Citation(s) in RCA: 105] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Revised: 09/01/2017] [Accepted: 09/06/2017] [Indexed: 12/21/2022]
Affiliation(s)
- Gabriele Gratton
- Department of Psychology and Beckman InstituteUniversity of Illinois at Urbana‐ChampaignUrbana Illinois USA
| | - Patrick Cooper
- School of PsychologyUniversity of NewcastleNewcastle New South Wales Australia
| | - Monica Fabiani
- Department of Psychology and Beckman InstituteUniversity of Illinois at Urbana‐ChampaignUrbana Illinois USA
| | - Cameron S. Carter
- Departments of Psychiatry and PsychologyUniversity of California–DavisDavis California USA
| | - Frini Karayanidis
- School of PsychologyUniversity of NewcastleNewcastle New South Wales Australia
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8
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Sugiura M. Functional neuroimaging of normal aging: Declining brain, adapting brain. Ageing Res Rev 2016; 30:61-72. [PMID: 26988858 DOI: 10.1016/j.arr.2016.02.006] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2016] [Revised: 02/21/2016] [Accepted: 02/22/2016] [Indexed: 10/22/2022]
Abstract
Early functional neuroimaging research on normal aging brain has been dominated by the interest in cognitive decline. In this framework the age-related compensatory recruitment of prefrontal cortex, in terms of executive system or reduced lateralization, has been established. Further details on these compensatory mechanisms and the findings reflecting cognitive decline, however, remain the matter of intensive investigations. Studies in another framework where age-related neural alteration is considered adaptation to the environmental change are recently burgeoning and appear largely categorized into three domains. The age-related increase in activation of the sensorimotor network may reflect the alteration of the peripheral sensorimotor systems. The increased susceptibility of the network for the mental-state inference to the socioemotional significance may be explained by the age-related motivational shift due to the altered social perception. The age-related change in activation of the self-referential network may be relevant to the focused positive self-concept of elderly driven by a similar motivational shift. Across the domains, the concept of the self and internal model may provide the theoretical bases of this adaptation framework. These two frameworks complement each other to provide a comprehensive view of the normal aging brain.
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Muller AM, Mérillat S, Jäncke L. Small Changes, But Huge Impact? The Right Anterior Insula's Loss of Connection Strength during the Transition of Old to Very Old Age. Front Aging Neurosci 2016; 8:86. [PMID: 27242508 PMCID: PMC4861722 DOI: 10.3389/fnagi.2016.00086] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2015] [Accepted: 04/07/2016] [Indexed: 11/20/2022] Open
Abstract
A major contribution to our understanding of the aging brain comes either from studies comparing young with older adults or from studies investigating pathological aging and using the healthy aging older adults as control group. In consequence, we know relatively well, what distinguishes young from old brains or pathological aging from healthy but that does not mean that we really understand the structural and functional transformations characterizing the healthy aging brain. By analyzing task-free fMRI data from a large cross-sectional sample of 186 older adults (mean age = 70.4, 97 female), we aimed to elucidate age-related changes in the intrinsically active functional architecture of the brain in our study group covering an age range from 65 to 85 years. First, we conducted an intrinsic connectivity contrast analysis (ICC) in order to detect the brain regions whose degree of connectedness was significantly correlated with increasing age. Secondly, using connectivity analyses we investigated how the clusters highlighted by the ICC analysis functionally related to the other major resting-state networks. The most important finding was the right anterior insula's loss of connectedness in the older participants of the study group because of the region's causal role in the switching from the task-negative to the task-positive state of the brain. Further, we found a higher functional dedifferentiation of two of the brain's major intrinsic connectivity networks, the DMN, and the cingulo-opercular network, caused by a reduction of functional connection strength, especially in the frontal regions. At last, we showed that all these age-related changes have the potential to impair older adult's performance of working memory tasks.
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Affiliation(s)
- Angela M Muller
- University Research Priority Program, Dynamics of Healthy Aging, University of ZurichZurich, Switzerland; International Normal Aging and Plasticity Imaging Center, University of ZurichZurich, Switzerland
| | - Susan Mérillat
- University Research Priority Program, Dynamics of Healthy Aging, University of ZurichZurich, Switzerland; International Normal Aging and Plasticity Imaging Center, University of ZurichZurich, Switzerland
| | - Lutz Jäncke
- University Research Priority Program, Dynamics of Healthy Aging, University of ZurichZurich, Switzerland; International Normal Aging and Plasticity Imaging Center, University of ZurichZurich, Switzerland; Division Neuropsychology, Institute of Psychology, University of ZurichZurich, Switzerland; Center for Integrative Human Physiology, University of ZurichZurich, Switzerland
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Li HJ, Hou XH, Liu HH, Yue CL, Lu GM, Zuo XN. Putting age-related task activation into large-scale brain networks: A meta-analysis of 114 fMRI studies on healthy aging. Neurosci Biobehav Rev 2015; 57:156-74. [PMID: 26318367 DOI: 10.1016/j.neubiorev.2015.08.013] [Citation(s) in RCA: 123] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2015] [Revised: 08/23/2015] [Accepted: 08/24/2015] [Indexed: 11/24/2022]
Abstract
Normal aging is associated with cognitive decline and underlying brain dysfunction. Previous studies concentrated less on brain network changes at a systems level. Our goal was to examine these age-related changes of fMRI-derived activation with a common network parcellation of the human brain function, offering a systems-neuroscience perspective of healthy aging. We conducted a series of meta-analyses on a total of 114 studies that included 2035 older adults and 1845 young adults. Voxels showing significant age-related changes in activation were then overlaid onto seven commonly referenced neuronal networks. Older adults present moderate cognitive decline in behavioral performance during fMRI scanning, and hypo-activate the visual network and hyper-activate both the frontoparietal control and default mode networks. The degree of increased activation in frontoparietal network was associated with behavioral performance in older adults. Age-related changes in activation present different network patterns across cognitive domains. The systems neuroscience approach used here may be useful for elucidating the underlying network mechanisms of various brain plasticity processes during healthy aging.
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Affiliation(s)
- Hui-Jie Li
- Key Laboratory of Behavioral Science and Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Laboratory for Functional Connectome and Development, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China.
| | - Xiao-Hui Hou
- Key Laboratory of Behavioral Science and Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Laboratory for Functional Connectome and Development, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan 030001, China
| | - Han-Hui Liu
- Youth Work Department, China Youth University of Political Studies, Beijing 100089, China
| | - Chun-Lin Yue
- Institute of Sports Medicine, Soochow University, Suzhou 215006, China
| | - Guang-Ming Lu
- Department of Medical Imaging, Nanjing University School of Medicine, Nanjing 210002, China
| | - Xi-Nian Zuo
- Key Laboratory of Behavioral Science and Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Laboratory for Functional Connectome and Development, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Faculty of Psychology, Southwest University, Beibei, Chongqing 400715, China.
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