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Strike LT, Kerestes R, McMahon KL, de Zubicaray GI, Harding IH, Medland SE. Heritability of cerebellar subregion volumes in adolescent and young adult twins. Hum Brain Mapp 2024; 45:e26717. [PMID: 38798116 DOI: 10.1002/hbm.26717] [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: 01/02/2024] [Revised: 04/23/2024] [Accepted: 05/06/2024] [Indexed: 05/29/2024] Open
Abstract
Twin studies have found gross cerebellar volume to be highly heritable. However, whether fine-grained regional volumes within the cerebellum are similarly heritable is still being determined. Anatomical MRI scans from two independent datasets (QTIM: Queensland Twin IMaging, N = 798, mean age 22.1 years; QTAB: Queensland Twin Adolescent Brain, N = 396, mean age 11.3 years) were combined with an optimised and automated cerebellum parcellation algorithm to segment and measure 28 cerebellar regions. We show that the heritability of regional volumetric measures varies widely across the cerebellum (h 2 $$ {h}^2 $$ 47%-91%). Additionally, the good to excellent test-retest reliability for a subsample of QTIM participants suggests that non-genetic variance in cerebellar volumes is due primarily to unique environmental influences rather than measurement error. We also show a consistent pattern of strong associations between the volumes of homologous left and right hemisphere regions. Associations were predominantly driven by genetic effects shared between lobules, with only sparse contributions from environmental effects. These findings are consistent with similar studies of the cerebrum and provide a first approximation of the upper bound of heritability detectable by genome-wide association studies.
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Affiliation(s)
- Lachlan T Strike
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- School of Psychology and Counselling, Faculty of Health, Queensland University of Technology, Kelvin Grove, Queensland, Australia
- School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Rebecca Kerestes
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
| | - Katie L McMahon
- School of Clinical Sciences, Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Greig I de Zubicaray
- School of Psychology and Counselling, Faculty of Health, Queensland University of Technology, Kelvin Grove, Queensland, Australia
| | - Ian H Harding
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
- Cerebellum and Neurodegeneration, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- School of Psychology and Counselling, Faculty of Health, Queensland University of Technology, Kelvin Grove, Queensland, Australia
- School of Psychology, University of Queensland, Brisbane, Australia
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2
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Wang Y, Teng Y, Liu T, Tang Y, Liang W, Wang W, Li Z, Xia Q, Xu F, Liu S. Morphological changes in the cerebellum during aging: evidence from convolutional neural networks and shape analysis. Front Aging Neurosci 2024; 16:1359320. [PMID: 38694258 PMCID: PMC11061448 DOI: 10.3389/fnagi.2024.1359320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 03/06/2024] [Indexed: 05/04/2024] Open
Abstract
The morphology and function of the cerebellum are associated with various developmental disorders and healthy aging. Changes in cerebellar morphology during the aging process have been extensively investigated, with most studies focusing on changes in cerebellar regional volume. The volumetric method has been used to quantitatively demonstrate the decrease in the cerebellar volume with age, but it has certain limitations in visually presenting the morphological changes of cerebellar atrophy from a three-dimensional perspective. Thus, we comprehensively described cerebellar morphological changes during aging through volume measurements of subregions and shape analysis. This study included 553 healthy participants aged 20-80 years. A novel cerebellar localized segmentation algorithm based on convolutional neural networks was utilized to analyze the volume of subregions, followed by shape analysis for localized atrophy assessment based on the cerebellar thickness. The results indicated that out of the 28 subregions in the absolute volume of the cerebellum, 15 exhibited significant aging trends, and 16 exhibited significant sex differences. Regarding the analysis of relative volume, only 11 out of the 28 subregions of the cerebellum exhibited significant aging trends, and 4 exhibited significant sex differences. The results of the shape analysis revealed region-specific atrophy of the cerebellum with increasing age. Regions displaying more significant atrophy were predominantly located in the vermis, the lateral portions of bilateral cerebellar hemispheres, lobules I-III, and the medial portions of the posterior lobe. This atrophy differed between sexes. Men exhibited slightly more severe atrophy than women in most of the cerebellar regions. Our study provides a comprehensive perspective for observing cerebellar atrophy during the aging process.
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Affiliation(s)
- Yu Wang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, China
| | - Ye Teng
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, China
| | - Tianci Liu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, China
| | - Yuchun Tang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, China
| | - Wenjia Liang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, China
| | - Wenjun Wang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, China
| | - Zhuoran Li
- Department of Ultrasound, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Qing Xia
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, China
| | - Feifei Xu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, China
| | - Shuwei Liu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Provincial Key Laboratory of Mental Disorder, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, China
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3
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Arleo A, Bareš M, Bernard JA, Bogoian HR, Bruchhage MMK, Bryant P, Carlson ES, Chan CCH, Chen LK, Chung CP, Dotson VM, Filip P, Guell X, Habas C, Jacobs HIL, Kakei S, Lee TMC, Leggio M, Misiura M, Mitoma H, Olivito G, Ramanoël S, Rezaee Z, Samstag CL, Schmahmann JD, Sekiyama K, Wong CHY, Yamashita M, Manto M. Consensus Paper: Cerebellum and Ageing. CEREBELLUM (LONDON, ENGLAND) 2024; 23:802-832. [PMID: 37428408 PMCID: PMC10776824 DOI: 10.1007/s12311-023-01577-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 06/08/2023] [Indexed: 07/11/2023]
Abstract
Given the key roles of the cerebellum in motor, cognitive, and affective operations and given the decline of brain functions with aging, cerebellar circuitry is attracting the attention of the scientific community. The cerebellum plays a key role in timing aspects of both motor and cognitive operations, including for complex tasks such as spatial navigation. Anatomically, the cerebellum is connected with the basal ganglia via disynaptic loops, and it receives inputs from nearly every region in the cerebral cortex. The current leading hypothesis is that the cerebellum builds internal models and facilitates automatic behaviors through multiple interactions with the cerebral cortex, basal ganglia and spinal cord. The cerebellum undergoes structural and functional changes with aging, being involved in mobility frailty and related cognitive impairment as observed in the physio-cognitive decline syndrome (PCDS) affecting older, functionally-preserved adults who show slowness and/or weakness. Reductions in cerebellar volume accompany aging and are at least correlated with cognitive decline. There is a strongly negative correlation between cerebellar volume and age in cross-sectional studies, often mirrored by a reduced performance in motor tasks. Still, predictive motor timing scores remain stable over various age groups despite marked cerebellar atrophy. The cerebello-frontal network could play a significant role in processing speed and impaired cerebellar function due to aging might be compensated by increasing frontal activity to optimize processing speed in the elderly. For cognitive operations, decreased functional connectivity of the default mode network (DMN) is correlated with lower performances. Neuroimaging studies highlight that the cerebellum might be involved in the cognitive decline occurring in Alzheimer's disease (AD), independently of contributions of the cerebral cortex. Grey matter volume loss in AD is distinct from that seen in normal aging, occurring initially in cerebellar posterior lobe regions, and is associated with neuronal, synaptic and beta-amyloid neuropathology. Regarding depression, structural imaging studies have identified a relationship between depressive symptoms and cerebellar gray matter volume. In particular, major depressive disorder (MDD) and higher depressive symptom burden are associated with smaller gray matter volumes in the total cerebellum as well as the posterior cerebellum, vermis, and posterior Crus I. From the genetic/epigenetic standpoint, prominent DNA methylation changes in the cerebellum with aging are both in the form of hypo- and hyper-methylation, and the presumably increased/decreased expression of certain genes might impact on motor coordination. Training influences motor skills and lifelong practice might contribute to structural maintenance of the cerebellum in old age, reducing loss of grey matter volume and therefore contributing to the maintenance of cerebellar reserve. Non-invasive cerebellar stimulation techniques are increasingly being applied to enhance cerebellar functions related to motor, cognitive, and affective operations. They might enhance cerebellar reserve in the elderly. In conclusion, macroscopic and microscopic changes occur in the cerebellum during the lifespan, with changes in structural and functional connectivity with both the cerebral cortex and basal ganglia. With the aging of the population and the impact of aging on quality of life, the panel of experts considers that there is a huge need to clarify how the effects of aging on the cerebellar circuitry modify specific motor, cognitive, and affective operations both in normal subjects and in brain disorders such as AD or MDD, with the goal of preventing symptoms or improving the motor, cognitive, and affective symptoms.
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Affiliation(s)
- Angelo Arleo
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, F-75012, Paris, France
| | - Martin Bareš
- First Department of Neurology, Faculty of Medicine, Masaryk University and St. Anne's Teaching Hospital, Brno, Czech Republic
- Department of Neurology, School of Medicine, University of Minnesota, Minneapolis, USA
| | - Jessica A Bernard
- Department of Psychological and Brain Sciences, Texas A&M University, 4235 TAMU, College Station, TX, 77843, USA
- Texas A&M Institute for Neuroscience, Texas A&M University, College Station, TX, USA
| | - Hannah R Bogoian
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | - Muriel M K Bruchhage
- Department of Psychology, Stavanger University, Institute of Social Sciences, Kjell Arholms Gate 41, 4021, Stavanger, Norway
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Centre for Neuroimaging Sciences, Box 89, De Crespigny Park, London, PO, SE5 8AF, UK
- Rhode Island Hospital, Department for Diagnostic Imaging, 1 Hoppin St, Providence, RI, 02903, USA
- Department of Paediatrics, Warren Alpert Medical School of Brown University, 222 Richmond St, Providence, RI, 02903, USA
| | - Patrick Bryant
- Freie Universität Berlin, Fachbereich Mathematik und Informatik, Arnimallee 12, 14195, Berlin, Germany
| | - Erik S Carlson
- Department of Psychiatry and Behavioural Sciences, University of Washington, Seattle, WA, USA
- Geriatric Research, Education and Clinical Center, Veteran's Affairs Medical Center, Puget Sound, Seattle, WA, USA
| | - Chetwyn C H Chan
- Department of Psychology, The Education University of Hong Kong, New Territories, Tai Po, Hong Kong, China
| | - Liang-Kung Chen
- Center for Healthy Longevity and Aging Sciences, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan
- Center for Geriatric and Gerontology, Taipei Veterans General Hospital, Taipei, Taiwan
- Taipei Municipal Gan-Dau Hospital (managed by Taipei Veterans General Hospital), Taipei, Taiwan
| | - Chih-Ping Chung
- Center for Healthy Longevity and Aging Sciences, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Vonetta M Dotson
- Department of Psychology, Georgia State University, Atlanta, GA, USA
- Gerontology Institute, Georgia State University, Atlanta, GA, USA
| | - Pavel Filip
- Department of Neurology, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, USA
| | - Xavier Guell
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Laboratory for Neuroanatomy and Cerebellar Neurobiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Christophe Habas
- CHNO Des Quinze-Vingts, INSERM-DGOS CIC 1423, 28 rue de Charenton, 75012, Paris, France
- Université Versailles St Quentin en Yvelines, Paris, France
| | - Heidi I L Jacobs
- School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, PO BOX 616, 6200, MD, Maastricht, The Netherlands
- Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University, PO BOX 616, 6200, MD, Maastricht, The Netherlands
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Tatia M C Lee
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China
- Laboratory of Neuropsychology and Human Neuroscience, Department of Psychology, The University of Hong Kong, Hong Kong, China
| | - Maria Leggio
- Department of Psychology, Sapienza University of Rome, Rome, Italy
- Ataxia Laboratory, I.R.C.C.S. Santa Lucia Foundation, Rome, Italy
| | - Maria Misiura
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | - Hiroshi Mitoma
- Department of Medical Education, Tokyo Medical University, Tokyo, Japan
| | - Giusy Olivito
- Department of Psychology, Sapienza University of Rome, Rome, Italy
- Ataxia Laboratory, I.R.C.C.S. Santa Lucia Foundation, Rome, Italy
| | - Stephen Ramanoël
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, F-75012, Paris, France
- Université Côte d'Azur, LAMHESS, Nice, France
| | - Zeynab Rezaee
- Noninvasive Neuromodulation Unit, Experimental Therapeutics & Pathophysiology Branch, National Institute of Mental Health, NIH, Bethesda, USA
| | - Colby L Samstag
- Department of Psychiatry and Behavioural Sciences, University of Washington, Seattle, WA, USA
- Geriatric Research, Education and Clinical Center, Veteran's Affairs Medical Center, Puget Sound, Seattle, WA, USA
| | - Jeremy D Schmahmann
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Laboratory for Neuroanatomy and Cerebellar Neurobiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Ataxia Center, Cognitive Behavioural neurology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Kaoru Sekiyama
- Graduate School of Advanced Integrated Studies in Human Survivability, Kyoto University, Kyoto, Japan
| | - Clive H Y Wong
- Department of Psychology, The Education University of Hong Kong, New Territories, Tai Po, Hong Kong, China
| | - Masatoshi Yamashita
- Research Center for Child Mental Development, University of Fukui, Fukui, Japan
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Osaka, Japan
| | - Mario Manto
- Service de Neurologie, Médiathèque Jean Jacquy, CHU-Charleroi, Charleroi, Belgium.
- Service des Neurosciences, University of Mons, Mons, Belgium.
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4
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Bernard JA. Cerebello-Hippocampal Interactions in the Human Brain: A New Pathway for Insights Into Aging. CEREBELLUM (LONDON, ENGLAND) 2024:10.1007/s12311-024-01670-5. [PMID: 38438826 DOI: 10.1007/s12311-024-01670-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 02/14/2024] [Indexed: 03/06/2024]
Abstract
The cerebellum is recognized as being important for optimal behavioral performance across task domains, including motor function, cognition, and affect. Decades of work have highlighted cerebello-thalamo-cortical circuits, from both structural and functional perspectives. However, these circuits of interest have been primarily (though not exclusively) focused on targets in the cerebral cortex. In addition to these cortical connections, the circuit linking the cerebellum and hippocampus is of particular interest. Recently, there has been an increased interest in this circuit, thanks in large part to novel findings in the animal literature demonstrating that neuronal firing in the cerebellum impacts that in the hippocampus. Work in the human brain has provided evidence for interactions between the cerebellum and hippocampus, though primarily this has been in the context of spatial navigation. Given the role of both regions in cognition and aging, and emerging evidence indicating that the cerebellum is impacted in age-related neurodegenerative disease such as Alzheimer's, I propose that further attention to this circuit is warranted. Here, I provide an overview of cerebello-hippocampal interactions in animal models and from human imaging and outline the possible utility of further investigations to improve our understanding of aging and age-related cognitive decline.
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Affiliation(s)
- Jessica A Bernard
- Department of Psychological and Brain Sciences, Texas A&M University, College Station, TX, 77843-4235, USA.
- Texas A&M Institute for Neuroscience, Texas A&M University, College Station, TX, 77843-4235, USA.
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5
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Iskusnykh IY, Zakharova AA, Kryl’skii ED, Popova TN. Aging, Neurodegenerative Disorders, and Cerebellum. Int J Mol Sci 2024; 25:1018. [PMID: 38256091 PMCID: PMC10815822 DOI: 10.3390/ijms25021018] [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: 12/13/2023] [Revised: 01/05/2024] [Accepted: 01/11/2024] [Indexed: 01/24/2024] Open
Abstract
An important part of the central nervous system (CNS), the cerebellum is involved in motor control, learning, reflex adaptation, and cognition. Diminished cerebellar function results in the motor and cognitive impairment observed in patients with neurodegenerative disorders such as Alzheimer's disease (AD), vascular dementia (VD), Parkinson's disease (PD), Huntington's disease (HD), spinal muscular atrophy (SMA), amyotrophic lateral sclerosis (ALS), Friedreich's ataxia (FRDA), and multiple sclerosis (MS), and even during the normal aging process. In most neurodegenerative disorders, impairment mainly occurs as a result of morphological changes over time, although during the early stages of some disorders such as AD, the cerebellum also serves a compensatory function. Biological aging is accompanied by changes in cerebellar circuits, which are predominantly involved in motor control. Despite decades of research, the functional contributions of the cerebellum and the underlying molecular mechanisms in aging and neurodegenerative disorders remain largely unknown. Therefore, this review will highlight the molecular and cellular events in the cerebellum that are disrupted during the process of aging and the development of neurodegenerative disorders. We believe that deeper insights into the pathophysiological mechanisms of the cerebellum during aging and the development of neurodegenerative disorders will be essential for the design of new effective strategies for neuroprotection and the alleviation of some neurodegenerative disorders.
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Affiliation(s)
- Igor Y. Iskusnykh
- Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Anastasia A. Zakharova
- Department of Medical Biochemistry, Faculty of Biomedicine, Pirogov Russian National Research Medical University, Ostrovitianov St. 1, Moscow 117997, Russia
| | - Evgenii D. Kryl’skii
- Department of Medical Biochemistry, Molecular and Cell Biology, Voronezh State University, Universitetskaya Sq. 1, Voronezh 394018, Russia; (E.D.K.)
| | - Tatyana N. Popova
- Department of Medical Biochemistry, Molecular and Cell Biology, Voronezh State University, Universitetskaya Sq. 1, Voronezh 394018, Russia; (E.D.K.)
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Bernard JA, McOwen KM, Huynh AT. New Frontiers for the Understanding of Aging: The Power and Possibilities of Studying the Cerebellum. Curr Opin Behav Sci 2023; 54:101311. [PMID: 38496767 PMCID: PMC10939048 DOI: 10.1016/j.cobeha.2023.101311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Understanding behavior in aging has benefited greatly from cognitive neuroscience. Our foundational understanding of the brain in advanced age is based on what now amounts to several decades of work demonstrating differences in brain structure, network organization, and function. Earlier work in this field was focused primarily on the prefrontal cortex and hippocampus. More recent evidence has expanded our understanding of the aging brain to also implicate the cerebellum. Recent frameworks have suggested that the cerebellum may act as scaffolding for cortical function, and there is an emerging literature implicating the structure in Alzheimer's disease. At this juncture, there is evidence highlighting the potential importance of the cerebellum in advanced age, though the field of study is relatively nascent. Here, we provide an overview of key findings in the literature as it stands now and highlight several key future directions for study with respect to the cerebellum in aging.
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Affiliation(s)
- Jessica A. Bernard
- Department of Psychological and Brain Sciences
- Texas A&M Institute for Neuroscience
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7
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Xie C, Fong MCM, Ma MKH, Wang J, Wang WS. The retrogenesis of age-related decline in declarative and procedural memory. Front Psychol 2023; 14:1212614. [PMID: 37575428 PMCID: PMC10413564 DOI: 10.3389/fpsyg.2023.1212614] [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: 04/26/2023] [Accepted: 07/05/2023] [Indexed: 08/15/2023] Open
Abstract
The retrogenesis hypothesis proposes that the order of breakdown of cognitive abilities in older adults is the reverse of the developmental order of children. Declarative and procedural memory systems, however, have been empirically understudied regarding this issue. The current study aimed to investigate whether retrogenesis occurs in the developmental and decline order of the declarative and procedural memory systems. Besides, we further investigated whether retrogenesis occurs in declarative memory, which was tested through the recognition of familiar and unfamiliar items. Both questions were investigated by looking at 28 Chinese younger adults and 27 cognitively healthy Chinese older adults. The recognition memory task and the Serial Reaction Time Task were administered on two consecutive days in order to measure their declarative and procedural memory, respectively. The results showed older adults performed significantly worse than younger adults for both tasks on both days, suggesting a decline in both declarative and procedural memory. Moreover, older adults exhibited relatively preserved declarative memory compared to procedural memory. This does not follow the expectations of the retrogenesis hypothesis. However, older adults demonstrated superior performance and a steeper rate of forgetting for recognizing familiar items than unfamiliar items. This reverses the developmental order of different patterns in the declarative memory system. Overall, we conclude that retrogenesis occurs in the declarative memory system, while does not in the decline order of the two memory systems; this understanding can better help inform our broader understanding of memory aging.
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Affiliation(s)
- Chenwei Xie
- Department of Chinese and Bilingual Studies, Research Centre for Language, Cognition, and Neuroscience, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Manson Cheuk-Man Fong
- Department of Chinese and Bilingual Studies, Research Centre for Language, Cognition, and Neuroscience, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
- Research Institute for Smart Ageing, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Matthew King-Hang Ma
- Department of Chinese and Bilingual Studies, Research Centre for Language, Cognition, and Neuroscience, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - Juliahna Wang
- Department of Chinese and Bilingual Studies, Research Centre for Language, Cognition, and Neuroscience, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
| | - William Shiyuan Wang
- Department of Chinese and Bilingual Studies, Research Centre for Language, Cognition, and Neuroscience, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
- Research Institute for Smart Ageing, The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR, China
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8
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Wang Y, Chen L, Wu Z, Li T, Sun Y, Cheng J, Zhu H, Lin W, Wang L, Huang W, Li G. Longitudinal development of the cerebellum in human infants during the first 800 days. Cell Rep 2023; 42:112281. [PMID: 36964904 DOI: 10.1016/j.celrep.2023.112281] [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: 06/07/2022] [Revised: 11/24/2022] [Accepted: 03/03/2023] [Indexed: 03/26/2023] Open
Abstract
Revealing early dynamic development of the normative cerebellar structures contributes to exploring cerebellum-related neurodevelopmental disorders. Here, leveraging infant-tailored cerebellar image processing techniques, we studied the dynamic volumetric developmental trajectories of cerebellum and 27 cerebellar sub-regions and their relationships with behavioral scores based on 511 high-resolution structural MRI scans during the first 800 postnatal days. The ratio of the entire cerebellum to the intracranial volume increases rapidly at first and then peaks at 13 months after birth. Both the absolute and relative volumes of most cerebellar sub-structures exhibit rapid increase at first, then the relative volumes decrease slightly after arriving at peaks (except for X lobules). Each lobule depicts larger absolute volume in males than in females. The within-subject variation of the cerebellar volumetric percentile score is generally stable. The volumetric development of several lobules (e.g., V, Crus I, and Crus II) has a significantly positive correlation with fine motor skills during the age range examined.
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Affiliation(s)
- Ya Wang
- National Key Discipline of Human Anatomy, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China; Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Liangjun Chen
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Zhengwang Wu
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Tengfei Li
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yue Sun
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jiale Cheng
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Weili Lin
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Li Wang
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
| | - Wenhua Huang
- National Key Discipline of Human Anatomy, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.
| | - Gang Li
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
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9
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Jäschke D, Steiner KM, Chang DI, Claaßen J, Uslar E, Thieme A, Gerwig M, Pfaffenrot V, Hulst T, Gussew A, Maderwald S, Göricke SL, Minnerop M, Ladd ME, Reichenbach JR, Timmann D, Deistung A. Age-related differences of cerebellar cortex and nuclei: MRI findings in healthy controls and its application to spinocerebellar ataxia (SCA6) patients. Neuroimage 2023; 270:119950. [PMID: 36822250 DOI: 10.1016/j.neuroimage.2023.119950] [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: 10/14/2022] [Revised: 02/06/2023] [Accepted: 02/15/2023] [Indexed: 02/24/2023] Open
Abstract
Understanding cerebellar alterations due to healthy aging provides a reference point against which pathological findings in late-onset disease, for example spinocerebellar ataxia type 6 (SCA6), can be contrasted. In the present study, we investigated the impact of aging on the cerebellar nuclei and cerebellar cortex in 109 healthy controls (age range: 16 - 78 years) using 3 Tesla magnetic resonance imaging (MRI). Findings were compared with 25 SCA6 patients (age range: 38 - 78 years). A subset of 16 SCA6 (included: 14) patients and 50 controls (included: 45) received an additional MRI scan at 7 Tesla and were re-scanned after one year. MRI included T1-weighted, T2-weighted FLAIR, and multi-echo T2*-weighted imaging. The T2*-weighted phase images were converted to quantitative susceptibility maps (QSM). Since the cerebellar nuclei are characterized by elevated iron content with respect to their surroundings, two independent raters manually outlined them on the susceptibility maps. T1-weighted images acquired at 3T were utilized to automatically identify the cerebellar gray matter (GM) volume. Linear correlations revealed significant atrophy of the cerebellum due to tissue loss of cerebellar cortical GM in healthy controls with increasing age. Reduction of the cerebellar GM was substantially stronger in SCA6 patients. The volume of the dentate nuclei did not exhibit a significant relationship with age, at least in the age range between 18 and 78 years, whereas mean susceptibilities of the dentate nuclei increased with age. As previously shown, the dentate nuclei volumes were smaller and magnetic susceptibilities were lower in SCA6 patients compared to age- and sex-matched controls. The significant dentate volume loss in SCA6 patients could also be confirmed with 7T MRI. Linear mixed effects models and individual paired t-tests accounting for multiple comparisons revealed no statistical significant change in volume and susceptibility of the dentate nuclei after one year in neither patients nor controls. Importantly, dentate volumes were more sensitive to differentiate between SCA6 (Cohen's d = 3.02) and matched controls than the cerebellar cortex volume (d = 2.04). In addition to age-related decline of the cerebellar cortex and atrophy in SCA6 patients, age-related increase of susceptibility of the dentate nuclei was found in controls, whereas dentate volume and susceptibility was significantly decreased in SCA6 patients. Because no significant changes of any of these parameters was found at follow-up, these measures do not allow to monitor disease progression at short intervals.
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Affiliation(s)
- Dominik Jäschke
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen 45147, Germany; Department of Radiology and Nuclear Medicine, University Hospital Basel, Basel 4031, Switzerland
| | - Katharina M Steiner
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen 45147, Germany; LVR-Hospital Essen, Department of Psychiatry and Psychotherapy, Medical Faculty, University of Duisburg-Essen, Essen 45147, Germany
| | - Dae-In Chang
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen 45147, Germany; Clinic for Psychiatry, Psychotherapy and Preventive Medicine, LWL-University Hospital of the Ruhr-University Bochum, Bochum 44791, Germany
| | - Jens Claaßen
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen 45147, Germany; Fachklinik für Neurologie, MEDICLIN Klinik Reichshof, Reichshof-Eckenhagen 51580, Germany
| | - Ellen Uslar
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen 45147, Germany
| | - Andreas Thieme
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen 45147, Germany
| | - Marcus Gerwig
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen 45147, Germany
| | - Viktor Pfaffenrot
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University of Duisburg-Essen, Essen 45141, Germany
| | - Thomas Hulst
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen 45147, Germany; Erasmus University College, Rotterdam 3011 HP, the Netherlands
| | - Alexander Gussew
- University Clinic and Outpatient Clinic for Radiology, Department for Radiation Medicine, University Hospital Halle (Saale), Ernst-Grube-Str. 40, Halle (Saale) 06120, Germany
| | - Stefan Maderwald
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University of Duisburg-Essen, Essen 45141, Germany
| | - Sophia L Göricke
- Institute of Diagnostic and Interventional Neuroradiology, Essen University Hospital, University of Duisburg-Essen, Essen 45141, Germany
| | - Martina Minnerop
- Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, Juelich 52425, Germany; Department of Neurology, Center for Movement Disorders and Neuromodulation, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, Düsseldorf 40225, Germany; Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, Düsseldorf 40225, Germany
| | - Mark E Ladd
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University of Duisburg-Essen, Essen 45141, Germany; Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg 69120, Germany; Faculty of Physics and Astronomy and Faculty of Medicine, Heidelberg University, Heidelberg 69120, Germany
| | - Jürgen R Reichenbach
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital, Jena 07743, Germany
| | - Dagmar Timmann
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen 45147, Germany; Erwin L. Hahn Institute for Magnetic Resonance Imaging, University of Duisburg-Essen, Essen 45141, Germany
| | - Andreas Deistung
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen 45147, Germany; University Clinic and Outpatient Clinic for Radiology, Department for Radiation Medicine, University Hospital Halle (Saale), Ernst-Grube-Str. 40, Halle (Saale) 06120, Germany; Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital, Jena 07743, Germany.
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10
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Duan P, Xue Y, Han S, Zuo L, Carass A, Bernhard C, Hays S, Calabresi PA, Resnick SM, Duncan JS, Prince JL. RAPID BRAIN MENINGES SURFACE RECONSTRUCTION WITH LAYER TOPOLOGY GUARANTEE. PROCEEDINGS. IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING 2023; 2023:10.1109/isbi53787.2023.10230668. [PMID: 37990735 PMCID: PMC10660710 DOI: 10.1109/isbi53787.2023.10230668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2023]
Abstract
The meninges, located between the skull and brain, are composed of three membrane layers: the pia, the arachnoid, and the dura. Reconstruction of these layers can aid in studying volume differences between patients with neurodegenerative diseases and normal aging subjects. In this work, we use convolutional neural networks (CNNs) to reconstruct surfaces representing meningeal layer boundaries from magnetic resonance (MR) images. We first use the CNNs to predict the signed distance functions (SDFs) representing these surfaces while preserving their anatomical ordering. The marching cubes algorithm is then used to generate continuous surface representations; both the subarachnoid space (SAS) and the intracranial volume (ICV) are computed from these surfaces. The proposed method is compared to a state-of-the-art deformable model-based reconstruction method, and we show that our method can reconstruct smoother and more accurate surfaces using less computation time. Finally, we conduct experiments with volumetric analysis on both subjects with multiple sclerosis and healthy controls. For healthy and MS subjects, ICVs and SAS volumes are found to be significantly correlated to sex (p<0.01) and age (p ≤ 0.03) changes, respectively.
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Affiliation(s)
- Peiyu Duan
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, USA
- Department of Biomedical Engineering, Yale University, USA
| | - Yuan Xue
- Department of Electrical and Computer Engineering, Johns Hopkins University, USA
| | - Shuo Han
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, USA
| | - Lianrui Zuo
- Department of Electrical and Computer Engineering, Johns Hopkins University, USA
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, USA
| | - Aaron Carass
- Department of Electrical and Computer Engineering, Johns Hopkins University, USA
| | - Caitlyn Bernhard
- Department of Electrical and Computer Engineering, Johns Hopkins University, USA
| | - Savannah Hays
- Department of Electrical and Computer Engineering, Johns Hopkins University, USA
| | | | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, USA
| | - James S Duncan
- Department of Biomedical Engineering, Yale University, USA
| | - Jerry L Prince
- Department of Biomedical Engineering, Johns Hopkins School of Medicine, USA
- Department of Electrical and Computer Engineering, Johns Hopkins University, USA
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11
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Cooper CP, Shafer AT, Armstrong NM, An Y, Erus G, Davatzikos C, Ferrucci L, Rapp PR, Resnick SM. Associations of baseline and longitudinal change in cerebellum volume with age-related changes in verbal learning and memory. Neuroimage 2023; 272:120048. [PMID: 36958620 DOI: 10.1016/j.neuroimage.2023.120048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 03/17/2023] [Accepted: 03/20/2023] [Indexed: 03/25/2023] Open
Abstract
The cerebellum is involved in higher-order cognitive functions, e.g., learning and memory, and is susceptible to age-related atrophy. Yet, the cerebellum's role in age-related cognitive decline remains largely unknown. We investigated cross-sectional and longitudinal associations between cerebellar volume and verbal learning and memory. Linear mixed effects models and partial correlations were used to examine the relationship between changes in cerebellum volumes (total cerebellum, cerebellum white matter [WM], cerebellum hemisphere gray matter [GM], and cerebellum vermis subregions) and changes in verbal learning and memory performance among 549 Baltimore Longitudinal Study of Aging participants (2,292 visits). All models were adjusted by baseline demographic characteristics (age, sex, race, education), and APOE e4 carrier status. In examining associations between change with change, we tested an additional model that included either hippocampal (HC), cuneus, or postcentral gyrus (PoCG) volumes to assess whether cerebellar volumes were uniquely associated with verbal learning and memory. Cross-sectionally, the association of baseline cerebellum GM and WM with baseline verbal learning and memory was age-dependent, with the oldest individuals showing the strongest association between volume and performance. Baseline volume was not significantly associated with change in learning and memory. However, analysis of associations between change in volumes and changes in verbal learning and memory showed that greater declines in verbal memory were associated with greater volume loss in cerebellum white matter, and preserved GM volume in cerebellum vermis lobules VI-VII. The association between decline in verbal memory and decline in cerebellar WM volume remained after adjustment for HC, cuneus, and PoCG volume. Our findings highlight that associations between cerebellum volume and verbal learning and memory are age-dependent and regionally specific.
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Affiliation(s)
- C'iana P Cooper
- Neurocognitive Aging Section, Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, Maryland
| | - Andrea T Shafer
- Brain Aging and Behavior Section, Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, Maryland
| | - Nicole M Armstrong
- Brain Aging and Behavior Section, Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, Maryland; Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, Providence, Rhode Island
| | - Yang An
- Brain Aging and Behavior Section, Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, Maryland
| | - Guray Erus
- Section of Biomedical Image Analysis, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Christos Davatzikos
- Section of Biomedical Image Analysis, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Luigi Ferrucci
- Translational Gerontology Branch, Longitudinal Studies Section, National Institute on Aging, National Institutes of Health, Baltimore, Maryland
| | - Peter R Rapp
- Neurocognitive Aging Section, Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, Maryland
| | - Susan M Resnick
- Brain Aging and Behavior Section, Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, Maryland.
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12
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Faber J, Kügler D, Bahrami E, Heinz LS, Timmann D, Ernst TM, Deike-Hofmann K, Klockgether T, van de Warrenburg B, van Gaalen J, Reetz K, Romanzetti S, Oz G, Joers JM, Diedrichsen J, Reuter M, Garcia-Moreno H, Jacobi H, Jende J, de Vries J, Povazan M, Barker PB, Steiner KM, Krahe J. CerebNet: A fast and reliable deep-learning pipeline for detailed cerebellum sub-segmentation. Neuroimage 2022; 264:119703. [PMID: 36349595 PMCID: PMC9771831 DOI: 10.1016/j.neuroimage.2022.119703] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 10/18/2022] [Indexed: 11/07/2022] Open
Abstract
Quantifying the volume of the cerebellum and its lobes is of profound interest in various neurodegenerative and acquired diseases. Especially for the most common spinocerebellar ataxias (SCA), for which the first antisense oligonculeotide-base gene silencing trial has recently started, there is an urgent need for quantitative, sensitive imaging markers at pre-symptomatic stages for stratification and treatment assessment. This work introduces CerebNet, a fully automated, extensively validated, deep learning method for the lobular segmentation of the cerebellum, including the separation of gray and white matter. For training, validation, and testing, T1-weighted images from 30 participants were manually annotated into cerebellar lobules and vermal sub-segments, as well as cerebellar white matter. CerebNet combines FastSurferCNN, a UNet-based 2.5D segmentation network, with extensive data augmentation, e.g. realistic non-linear deformations to increase the anatomical variety, eliminating additional preprocessing steps, such as spatial normalization or bias field correction. CerebNet demonstrates a high accuracy (on average 0.87 Dice and 1.742mm Robust Hausdorff Distance across all structures) outperforming state-of-the-art approaches. Furthermore, it shows high test-retest reliability (average ICC >0.97 on OASIS and Kirby) as well as high sensitivity to disease effects, including the pre-ataxic stage of spinocerebellar ataxia type 3 (SCA3). CerebNet is compatible with FreeSurfer and FastSurfer and can analyze a 3D volume within seconds on a consumer GPU in an end-to-end fashion, thus providing an efficient and validated solution for assessing cerebellum sub-structure volumes. We make CerebNet available as source-code (https://github.com/Deep-MI/FastSurfer).
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Affiliation(s)
- Jennifer Faber
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany,Department of Neurology, University Hospital Bonn, Germany
| | - David Kügler
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Emad Bahrami
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany,Computer Science Department, University Bonn, Bonn, Germany
| | - Lea-Sophie Heinz
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Dagmar Timmann
- Department of Neurology, Center for Translational Neuro, and Behavioral Sciences (C-TNBS), University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Thomas M. Ernst
- Department of Neurology, Center for Translational Neuro, and Behavioral Sciences (C-TNBS), University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | | | - Thomas Klockgether
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany,Department of Neurology, University Hospital Bonn, Germany
| | - Bart van de Warrenburg
- Department of Neurology, Donders Institute for Brain, Cognition, and Behaviour, Radboud university medical center, Nijmegen, The Netherlands
| | - Judith van Gaalen
- Department of Neurology, Donders Institute for Brain, Cognition, and Behaviour, Radboud university medical center, Nijmegen, The Netherlands
| | - Kathrin Reetz
- Department of Neurology, RWTH Aachen University, Germany,JARA-Brain Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich, Germany
| | | | - Gulin Oz
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - James M. Joers
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Jorn Diedrichsen
- Departments of Computer Science and Statistical and Actuarial Sciences, Western University, London, ON, Canada
| | - ESMI MRI Study GroupGiuntiPaola1Garcia-MorenoHector1JacobiHeike3JendeJohann4de VriesJeroen5PovazanMichal6BarkerPeter B.6SteinerKatherina Marie8KraheJanna9Ataxia Centre, Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology & National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, UKDepartment of Neurology, University Hospital of Heidelberg, Heidelberg, GermanyDepartment of Neuroradiology, Heidelberg University Hospital, Heidelberg, GermanyDepartment of Neurology, Expertise Center Movement Disorders Groningen, University Medical Center Groningen, University of Groningen, The NetherlandsJohns Hopkins University School of Medicine, Baltimore, MD, U.S.Department of Neurology, Center for Translational Neuro, and Behavioral Sciences (C-TNBS), University Hospital Essen, University of Duisburg-Essen, Essen, GermanyDepartment of Neurology, RWTH Aachen University, Germany
| | - Martin Reuter
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany,A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA,Department of Radiology, Harvard Medical School, Boston, MA, USA,Corresponding author.
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13
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Martinez-Gutierrez E, Jimenez-Marin A, Stramaglia S, Cortes JM. The structure of anticorrelated networks in the human brain. FRONTIERS IN NETWORK PHYSIOLOGY 2022; 2:946380. [PMID: 36926060 PMCID: PMC10012996 DOI: 10.3389/fnetp.2022.946380] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 10/24/2022] [Indexed: 06/18/2023]
Abstract
During the performance of a specific task--or at rest--, the activity of different brain regions shares statistical dependencies that reflect functional connections. While these relationships have been studied intensely for positively correlated networks, considerably less attention has been paid to negatively correlated networks, a. k.a. anticorrelated networks (ACNs). Although the most celebrated of all ACNs is the default mode network (DMN), and has even been extensively studied in health and disease, for systematically all ACNs other than DMN, there is no comprehensive study yet. Here, we have addressed this issue by making use of three neuroimaging data sets: one of N = 192 healthy young adults to fully describe ACN, another of N = 40 subjects to compare ACN between two groups of young and old participants, and another of N = 1,000 subjects from the Human Connectome Project to evaluate the association between ACN and cognitive scores. We first provide a comprehensive description of the anatomical composition of all ACNs, each of which participated in distinct resting-state networks (RSNs). In terms of participation ranking, from highest to the lowest, the major anticorrelated brain areas are the precuneus, the anterior supramarginal gyrus and the central opercular cortex. Next, by evaluating a more detailed structure of ACN, we show it is possible to find significant differences in ACN between specific conditions, in particular, by comparing groups of young and old participants. Our main finding is that of increased anticorrelation for cerebellar interactions in older subjects. Finally, in the voxel-level association study with cognitive scores, we show that ACN has multiple clusters of significance, clusters that are different from those obtained from positive correlated networks, indicating a functional cognitive meaning of ACN. Overall, our results give special relevance to ACN and suggest their use to disentangle unknown alterations in certain conditions, as could occur in early-onset neurodegenerative diseases or in some psychiatric conditions.
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Affiliation(s)
- Endika Martinez-Gutierrez
- Biocruces-Bizkaia Health Research Institute, Barakaldo, Spain
- Dipartamento Interateneo di Fisica, Universita Degli Studi di Bari Aldo Moro, INFN, Bari, Italy
| | - Antonio Jimenez-Marin
- Biocruces-Bizkaia Health Research Institute, Barakaldo, Spain
- Biomedical Research Doctorate Program, University of the Basque Country, Leioa, Spain
| | - Sebastiano Stramaglia
- Dipartamento Interateneo di Fisica, Universita Degli Studi di Bari Aldo Moro, INFN, Bari, Italy
| | - Jesus M. Cortes
- Biocruces-Bizkaia Health Research Institute, Barakaldo, Spain
- Department of Cell Biology and Histology, University of the Basque Country, Leioa, Spain
- IKERBASQUE Basque Foundation for Science, Bilbao, Spain
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14
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Ballard HK, Jackson TB, Hicks TH, Bernard JA. The association of reproductive stage with lobular cerebellar network connectivity across female adulthood. Neurobiol Aging 2022; 117:139-150. [PMID: 35738086 PMCID: PMC10149146 DOI: 10.1016/j.neurobiolaging.2022.05.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 05/18/2022] [Accepted: 05/30/2022] [Indexed: 01/25/2023]
Abstract
Sex-specific differences in the aging cerebellum may be related to hormone changes with menopause. We evaluated the association between reproductive stage and lobular cerebellar network connectivity using data from the Cambridge Centre for Ageing and Neuroscience repository. We used raw structural and resting state neuroimaging data and information regarding age, sex, and menopause-related variables. Crus I and II and Lobules V and VI were our cerebellar seeds of interest. We characterized reproductive stage using the Stages of Reproductive Aging Workshop criteria. Results show that postmenopausal females have lower cerebello-striatal and cerebello-cortical connectivity, particularly in frontal regions, along with lower connectivity within the cerebellum, compared to reproductive females. Postmenopausal females also exhibit greater connectivity in some brain areas as well. Differences begin to emerge across transitional stages of menopause. Further, results reveal sex-specific differences in connectivity between female reproductive groups and age-matched male control groups. This suggests that menopause may be associated with cerebellar network connectivity in aging females, and sex differences in the aging brain may be related to this biological process.
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Affiliation(s)
- Hannah K Ballard
- Texas A&M Institute for Neuroscience, Texas A&M University, College Station, TX, USA.
| | - T Bryan Jackson
- Department of Psychological & Brain Sciences, Texas A&M University, College Station, TX, USA
| | - Tracey H Hicks
- Department of Psychological & Brain Sciences, Texas A&M University, College Station, TX, USA
| | - Jessica A Bernard
- Texas A&M Institute for Neuroscience, Texas A&M University, College Station, TX, USA; Department of Psychological & Brain Sciences, Texas A&M University, College Station, TX, USA
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15
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Hicks TH, Ballard HK, Sang H, Bernard JA. Age-volume associations in cerebellar lobules by sex and reproductive stage. Brain Struct Funct 2022; 227:2439-2455. [PMID: 35876952 PMCID: PMC10167909 DOI: 10.1007/s00429-022-02535-5] [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: 04/22/2022] [Accepted: 07/01/2022] [Indexed: 11/02/2022]
Abstract
The cerebellum has established associations with motor function and a well-recognized role in cognition. In advanced age, cognitive and motor impairments contribute to reduced quality of life and are more common. Regional cerebellar volume is associated with performance across these domains and sex hormones may influence this volume. Examining sex differences in regional cerebellar volume in conjunction with age, and in the context of reproductive stage stands to improve our understanding of cerebellar aging and pathology. Data from 508 healthy adults (ages 18-88; 47% female) from the Cambridge Centre for Ageing and Neuroscience database were used here. CERES was used to assess lobular volume in T1-weighted images. We examined sex differences in adjusted regional cerebellar volume while controlling for age. A subgroup of participants (n = 370, 50% female) was used to assess group differences in female reproductive stages as compared to age-matched males. Sex differences in adjusted volume were seen across most anterior and posterior cerebellar lobules. Most of these lobules had significant linear relationships with age in males and females. While there were no interactions between sex and reproductive stage groups, exploratory analyses in females alone revealed multiple regional differences by reproductive stage. We found sex differences in volume across much of the cerebellum, linear associations with age, and did not find an interaction for sex and reproductive stage on regional cerebellar volume. Longitudinal investigation into hormonal influences on cerebellar structure and function is warranted as hormonal changes with menopause may impact cerebellar volume over time.
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Affiliation(s)
- Tracey H Hicks
- Department of Psychological and Brain Sciences, Texas A&M University, 4235 TAMU, College Station, TX, 77840, USA.
| | - Hannah K Ballard
- Texas A&M University Institute for Neuroscience, 3474 TAMU, College Station, TX, 77843, USA
| | - Huiyan Sang
- Department of Statistics, Texas A&M University, 3143 TAMU, College Station, TX, 77843, USA
| | - Jessica A Bernard
- Department of Psychological and Brain Sciences, Texas A&M University, 4235 TAMU, College Station, TX, 77840, USA
- Texas A&M University Institute for Neuroscience, 3474 TAMU, College Station, TX, 77843, USA
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16
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Bernard JA. Don't forget the little brain: A framework for incorporating the cerebellum into the understanding of cognitive aging. Neurosci Biobehav Rev 2022; 137:104639. [PMID: 35346747 PMCID: PMC9119942 DOI: 10.1016/j.neubiorev.2022.104639] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 02/28/2022] [Accepted: 03/23/2022] [Indexed: 12/22/2022]
Abstract
With the rapidly growing population of older adults, an improved understanding of brain and cognitive aging is critical, given the impacts on health, independence, and quality of life. To this point, we have a well-developed literature on the cortical contributions to cognition in advanced age. However, while this work has been foundational for our understanding of brain and behavior in older adults, subcortical contributions, particularly those from the cerebellum, have not been integrated into these models and frameworks. Incorporating the cerebellum into models of cognitive aging is an important step for moving the field forward. There has also been recent interest in this structure in Alzheimer's dementia, indicating that such work may be beneficial to our understanding of neurodegenerative disease. Here, I provide an updated overview of the cerebellum in advanced age and propose that it serves as a critical source of scaffolding or reserve for cortical function. Age-related impacts on cerebellar function further impact cortical processing, perhaps resulting in many of the activation patterns commonly seen in aging.
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Affiliation(s)
- Jessica A Bernard
- Department of Psychological and Brain Sciences, USA; Texas A&M Institute for Neuroscience, Texas A&M University, USA.
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17
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Horn MJ, Gokcal E, Becker AJ, Das AS, Warren AD, Schwab K, Goldstein JN, Biffi A, Rosand J, Polimeni JR, Viswanathan A, Greenberg SM, Gurol ME. Cerebellar atrophy and its implications on gait in cerebral amyloid angiopathy. J Neurol Neurosurg Psychiatry 2022; 93:jnnp-2021-328553. [PMID: 35534189 PMCID: PMC10936558 DOI: 10.1136/jnnp-2021-328553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 04/06/2022] [Indexed: 11/04/2022]
Abstract
OBJECTIVE Recent data suggest that cerebral amyloid angiopathy (CAA) causes haemorrhagic lesions in cerebellar cortex as well as subcortical cerebral atrophy. However, the potential effect of CAA on cerebellar tissue loss and its clinical implications have not been investigated. METHODS Our study included 70 non-demented patients with probable CAA, 70 age-matched healthy controls (HCs) and 70 age-matched patients with Alzheimer's disease (AD). The cerebellum was segmented into percent of cerebellar subcortical volume (pCbll-ScV) and percent of cerebellar cortical volume (pCbll-CV) represented as percent (p) of estimated total intracranial volume. We compared pCbll-ScV and pCbll-CV between patients with CAA, HCs and those with AD. Gait velocity (metres/second) was used to investigate gait function in patients with CAA. RESULTS Patients with CAA had significantly lower pCbll-ScV compared with both HC (1.49±0.1 vs 1.73±0.2, p<0.001) and AD (1.49±0.1 vs 1.66±0.24, p<0.001) and lower pCbll-CV compared with HCs (6.03±0.5 vs 6.23±0.6, p=0.028). Diagnosis of CAA was independently associated with lower pCbll-ScV compared with HCs (p<0.001) and patients with AD (p<0.001) in separate linear regression models adjusted for age, sex and presence of hypertension. Lower pCbll-ScV was independently associated with worse gait velocity (β=0.736, 95% CI 0.28 to 1.19, p=0.002) in a stepwise linear regression analysis including pCbll-CV along with other relevant variables. INTERPRETATION Patients with CAA show more subcortical cerebellar atrophy than HC or patients with AD and more cortical cerebellar atrophy than HCs. Reduced pCbll-ScV correlated with lower gait velocity in regression models including other relevant variables. Overall, this study suggests that CAA causes cerebellar injury, which might contribute to gait disturbance.
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Affiliation(s)
- Mitchell J Horn
- J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Elif Gokcal
- J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Alex J Becker
- Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Alvin S Das
- J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Andrew D Warren
- J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Kristin Schwab
- J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Joshua N Goldstein
- Emergency Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Alessandro Biffi
- J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Jonathan Rosand
- J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Jonathan R Polimeni
- Athinoula A Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, USA
| | - Anand Viswanathan
- J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Steven M Greenberg
- J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - M Edip Gurol
- J Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
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18
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Brown RM, Gruijters SLK, Kotz SA. Prediction in the aging brain: Merging cognitive, neurological, and evolutionary perspectives. J Gerontol B Psychol Sci Soc Sci 2022; 77:1580-1591. [PMID: 35429160 PMCID: PMC9434449 DOI: 10.1093/geronb/gbac062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Indexed: 12/02/2022] Open
Abstract
Although the aging brain is typically characterized by declines in a variety of cognitive functions, there has been growing attention to cognitive functions that may stabilize or improve with age. We integrate evidence from behavioral, computational, and neurological domains under the hypothesis that over the life span the brain becomes more effective at predicting (i.e., utilizing knowledge) compared to learning. Moving beyond mere description of the empirical literature—with the aim of arriving at a deeper understanding of cognitive aging—we provide potential explanations for a learning-to-prediction shift based on evolutionary models and principles of senescence and plasticity. The proposed explanations explore whether the occurrence of a learning-to-prediction shift can be explained by (changes in) the fitness effects of learning and prediction over the life span. Prediction may optimize (a) the allocation of limited resources across the life span, and/or (b) late-life knowledge transfer (social learning). Alternatively, late-life prediction may reflect a slower decline in prediction compared to learning. By discussing these hypotheses, we aim to provide a foundation for an integrative neurocognitive–evolutionary perspective on aging and to stimulate further theoretical and empirical work.
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Affiliation(s)
- Rachel M Brown
- Institute of Psychology, RWTH Aachen University, Aachen, Germany
| | - Stefan L K Gruijters
- Faculty of Psychology, Open University of the Netherlands, Heerlen, the Netherlands
| | - Sonja A Kotz
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
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19
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Hupfeld KE, Geraghty JM, McGregor HR, Hass CJ, Pasternak O, Seidler RD. Differential Relationships Between Brain Structure and Dual Task Walking in Young and Older Adults. Front Aging Neurosci 2022; 14:809281. [PMID: 35360214 PMCID: PMC8963788 DOI: 10.3389/fnagi.2022.809281] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 01/31/2022] [Indexed: 12/13/2022] Open
Abstract
Almost 25% of all older adults experience difficulty walking. Mobility difficulties for older adults are more pronounced when they perform a simultaneous cognitive task while walking (i.e., dual task walking). Although it is known that aging results in widespread brain atrophy, few studies have integrated across more than one neuroimaging modality to comprehensively examine the structural neural correlates that may underlie dual task walking in older age. We collected spatiotemporal gait data during single and dual task walking for 37 young (18–34 years) and 23 older adults (66–86 years). We also collected T1-weighted and diffusion-weighted MRI scans to determine how brain structure differs in older age and relates to dual task walking. We addressed two aims: (1) to characterize age differences in brain structure across a range of metrics including volumetric, surface, and white matter microstructure; and (2) to test for age group differences in the relationship between brain structure and the dual task cost (DTcost) of gait speed and variability. Key findings included widespread brain atrophy for the older adults, with the most pronounced age differences in brain regions related to sensorimotor processing. We also found multiple associations between regional brain atrophy and greater DTcost of gait speed and variability for the older adults. The older adults showed a relationship of both thinner temporal cortex and shallower sulcal depth in the frontal, sensorimotor, and parietal cortices with greater DTcost of gait. Additionally, the older adults showed a relationship of ventricular volume and superior longitudinal fasciculus free-water corrected axial and radial diffusivity with greater DTcost of gait. These relationships were not present for the young adults. Stepwise multiple regression found sulcal depth in the left precentral gyrus, axial diffusivity in the superior longitudinal fasciculus, and sex to best predict DTcost of gait speed, and cortical thickness in the superior temporal gyrus to best predict DTcost of gait variability for older adults. These results contribute to scientific understanding of how individual variations in brain structure are associated with mobility function in aging. This has implications for uncovering mechanisms of brain aging and for identifying target regions for mobility interventions for aging populations.
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Affiliation(s)
- Kathleen E. Hupfeld
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, United States
| | - Justin M. Geraghty
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, United States
| | - Heather R. McGregor
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, United States
| | - C. J. Hass
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, United States
| | - Ofer Pasternak
- Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Rachael D. Seidler
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, United States
- University of Florida Norman Fixel Institute for Neurological Diseases, Gainesville, FL, United States
- *Correspondence: Rachael D. Seidler
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20
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Mouches P, Wilms M, Rajashekar D, Langner S, Forkert ND. Multimodal biological brain age prediction using magnetic resonance imaging and angiography with the identification of predictive regions. Hum Brain Mapp 2022; 43:2554-2566. [PMID: 35138012 PMCID: PMC9057090 DOI: 10.1002/hbm.25805] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 01/24/2022] [Accepted: 01/25/2022] [Indexed: 02/06/2023] Open
Abstract
Biological brain age predicted using machine learning models based on high-resolution imaging data has been suggested as a potential biomarker for neurological and cerebrovascular diseases. In this work, we aimed to develop deep learning models to predict the biological brain age using structural magnetic resonance imaging and angiography datasets from a large database of 2074 adults (21-81 years). Since different imaging modalities can provide complementary information, combining them might allow to identify more complex aging patterns, with angiography data, for instance, showing vascular aging effects complementary to the atrophic brain tissue changes seen in T1-weighted MRI sequences. We used saliency maps to investigate the contribution of cortical, subcortical, and arterial structures to the prediction. Our results show that combining T1-weighted and angiography MR data led to a significantly improved brain age prediction accuracy, with a mean absolute error of 3.85 years comparing the predicted and chronological age. The most predictive brain regions included the lateral sulcus, the fourth ventricle, and the amygdala, while the brain arteries contributing the most to the prediction included the basilar artery, the middle cerebral artery M2 segments, and the left posterior cerebral artery. Our study proposes a framework for brain age prediction using multimodal imaging, which gives accurate predictions and allows identifying the most predictive regions for this task, which can serve as a surrogate for the brain regions that are most affected by aging.
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Affiliation(s)
- Pauline Mouches
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.,Biomedical Engineering Program, University of Calgary, Calgary, Alberta, Canada
| | - Matthias Wilms
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - Deepthi Rajashekar
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.,Biomedical Engineering Program, University of Calgary, Calgary, Alberta, Canada
| | - Sönke Langner
- Institute for Diagnostic Radiology and Neuroradiology, Rostock University Medical Center, Rostock, Germany
| | - Nils D Forkert
- Department of Radiology, University of Calgary, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
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21
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Duan P, Han S, Zuo L, An Y, Liu Y, Alshareef A, Lee J, Carass A, Resnick SM, Prince JL. Cranial Meninges Reconstruction Based on Convolutional Networks and Deformable Models: Applications to Longitudinal Study of Normal Aging. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2022; 12032:1203215. [PMID: 36325254 PMCID: PMC9623767 DOI: 10.1117/12.2613146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
The cranial meninges are membranes enveloping the brain. The space between these membranes contains mainly cerebrospinal fluid. It is of interest to study how the volumes of this space change with respect to normal aging. In this work, we propose to combine convolutional neural networks (CNNs) with nested topology-preserving geometric deformable models (NTGDMs) to reconstruct meningeal surfaces from magnetic resonance (MR) images. We first use CNNs to predict implicit representations of these surfaces then refine them with NTGDMs to achieve sub-voxel accuracy while maintaining spherical topology and the correct anatomical ordering. MR contrast harmonization is used to match the contrasts between training and testing images. We applied our algorithm to a subset of healthy subjects from the Baltimore Longitudinal Study of Aging for demonstration purposes and conducted longitudinal statistical analysis of the intracranial volume (ICV) and subarachnoid space (SAS) volume. We found a statistically significant decrease in the ICV and an increase in the SAS volume with respect to normal aging.
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Affiliation(s)
- Peiyu Duan
- Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD 21218
| | - Shuo Han
- Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD 21218
| | - Lianrui Zuo
- Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD 20892
| | - Yang An
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD 20892
| | - Yihao Liu
- Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218
| | - Ahmed Alshareef
- Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218
| | - Junghoon Lee
- Department of Radiology, The Johns Hopkins School of Medicine, Baltimore, MD 21287
| | - Aaron Carass
- Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218
| | - Susan M. Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD 20892
| | - Jerry L. Prince
- Department of Biomedical Engineering, The Johns Hopkins University, Baltimore, MD 21218
- Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218
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22
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Fowler C, Goerzen D, Madularu D, Devenyi GA, Chakravarty MM, Near J. Longitudinal characterization of neuroanatomical changes in the Fischer 344 rat brain during normal aging and between sexes. Neurobiol Aging 2022; 109:216-228. [PMID: 34775212 DOI: 10.1016/j.neurobiolaging.2021.10.003] [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: 04/12/2021] [Revised: 08/23/2021] [Accepted: 10/07/2021] [Indexed: 10/20/2022]
Abstract
Animal models are widely used to study the pathophysiology of disease and to evaluate the efficacy of novel interventions, crucial steps towards improving disease outcomes in humans. The Fischer 344 (F344) wildtype rat is a common experimental background strain for transgenic models of disease and is one of the most frequently used models in aging research. Despite frequency of use, characterization of agerelated neuroanatomical change has not been performed in the F344 rat. To this end, we present a comprehensive longitudinal examination of morphometric change in 73 brain regions and at a voxel-wise level during normative aging in vivo in a mixed-sexcohort of F344 rats. We identified the greatest vulnerability to aging within the cortex, caudoputamen, hindbrain, and internal capsule, while the influence of sex was strongest in the caudoputamen, hippocampus, nucleus accumbens, and thalamus, many of which are implicated in memory and motor control circuits frequently affected by aging and neurodegenerative disease. These findings provide a baseline for neuroanatomical changes associated with aging in male and female F344 rats, to which data from transgenic models or other background strains can be compared.
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Affiliation(s)
- Caitlin Fowler
- Department of Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada; Centre d'Imagerie Cérébrale, Douglas Mental Health University Institute, Montreal, Quebec, Canada.
| | - Dana Goerzen
- Centre d'Imagerie Cérébrale, Douglas Mental Health University Institute, Montreal, Quebec, Canada.
| | - Dan Madularu
- Centre d'Imagerie Cérébrale, Douglas Mental Health University Institute, Montreal, Quebec, Canada; Center for Translational NeuroImaging, Northeastern University, Boston, MA, USA; Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Gabriel A Devenyi
- Centre d'Imagerie Cérébrale, Douglas Mental Health University Institute, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - M Mallar Chakravarty
- Department of Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada; Centre d'Imagerie Cérébrale, Douglas Mental Health University Institute, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Jamie Near
- Department of Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada; Centre d'Imagerie Cérébrale, Douglas Mental Health University Institute, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada
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23
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Bernard JA, Ballard HK, Jackson TB. Cerebellar Dentate Connectivity across Adulthood: A Large-Scale Resting State Functional Connectivity Investigation. Cereb Cortex Commun 2021; 2:tgab050. [PMID: 34527949 PMCID: PMC8436571 DOI: 10.1093/texcom/tgab050] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2021] [Revised: 06/20/2021] [Accepted: 07/19/2021] [Indexed: 12/23/2022] Open
Abstract
Cerebellar contributions to behavior in advanced age are of interest and importance, given its role in motor and cognitive performance. There are differences and declines in cerebellar structure in advanced age and cerebellar resting state connectivity is lower. However, the work on this area to date has focused on the cerebellar cortex. The deep cerebellar nuclei provide the primary cerebellar inputs and outputs to the cortex, as well as the spinal and vestibular systems. Dentate networks can be dissociated such that the dorsal region is associated with the motor cortex, whereas the ventral aspect is associated with the prefrontal cortex. However, whether dentato-thalamo-cortical networks differ across adulthood remains unknown. Here, using a large adult sample (n = 590) from the Cambridge Center for Ageing and Neuroscience, we investigated dentate connectivity across adulthood. We replicated past work showing dissociable resting state networks in the dorsal and ventral aspects of the dentate. In both seeds, we demonstrated that connectivity is lower with advanced age, indicating that connectivity differences extend beyond the cerebellar cortex. Finally, we demonstrated sex differences in dentate connectivity. This expands our understanding of cerebellar circuitry in advanced age and underscores the potential importance of this structure in age-related performance differences.
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Affiliation(s)
- Jessica A Bernard
- Department of Psychological and Brain Sciences, Texas A&M University, College Station, TX 77843, USA
| | - Hannah K Ballard
- Texas A&M Institute for Neuroscience, Texas A&M University, College Station, TX 77843, USA
| | - Trevor Bryan Jackson
- Department of Psychological and Brain Sciences, Texas A&M University, College Station, TX 77843, USA
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24
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Williams CM, Peyre H, Toro R, Ramus F. Neuroanatomical norms in the UK Biobank: The impact of allometric scaling, sex, and age. Hum Brain Mapp 2021; 42:4623-4642. [PMID: 34268815 PMCID: PMC8410561 DOI: 10.1002/hbm.25572] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 06/03/2021] [Accepted: 06/11/2021] [Indexed: 12/18/2022] Open
Abstract
Few neuroimaging studies are sufficiently large to adequately describe population‐wide variations. This study's primary aim was to generate neuroanatomical norms and individual markers that consider age, sex, and brain size, from 629 cerebral measures in the UK Biobank (N = 40,028). The secondary aim was to examine the effects and interactions of sex, age, and brain allometry—the nonlinear scaling relationship between a region and brain size (e.g., total brain volume)—across cerebral measures. Allometry was a common property of brain volumes, thicknesses, and surface areas (83%) and was largely stable across age and sex. Sex differences occurred in 67% of cerebral measures (median |β| = .13): 37% of regions were larger in males and 30% in females. Brain measures (49%) generally decreased with age, although aging effects varied across regions and sexes. While models with an allometric or linear covariate adjustment for brain size yielded similar significant effects, omitting brain allometry influenced reported sex differences in variance. Finally, we contribute to the reproducibility of research on sex differences in the brain by replicating previous studies examining cerebral sex differences. This large‐scale study advances our understanding of age, sex, and brain allometry's impact on brain structure and provides data for future UK Biobank studies to identify the cerebral regions that covary with specific phenotypes, independently of sex, age, and brain size.
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Affiliation(s)
- Camille Michèle Williams
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, Paris, France
| | - Hugo Peyre
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, Paris, France.,INSERM UMR 1141, Paris Diderot University, Paris, France.,Department of Child and Adolescent Psychiatry, Robert Debré Hospital, APHP, Paris, France
| | - Roberto Toro
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR 3571 CNRS, Paris, France.,Center for Research and Interdisciplinarity (CRI), INSERM U1284, Paris, France.,Université de Paris, Paris, France
| | - Franck Ramus
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, Paris, France
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25
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Faber J, Schaprian T, Berkan K, Reetz K, França MC, de Rezende TJR, Hong J, Liao W, van de Warrenburg B, van Gaalen J, Durr A, Mochel F, Giunti P, Garcia-Moreno H, Schoels L, Hengel H, Synofzik M, Bender B, Oz G, Joers J, de Vries JJ, Kang JS, Timmann-Braun D, Jacobi H, Infante J, Joules R, Romanzetti S, Diedrichsen J, Schmid M, Wolz R, Klockgether T. Regional Brain and Spinal Cord Volume Loss in Spinocerebellar Ataxia Type 3. Mov Disord 2021; 36:2273-2281. [PMID: 33951232 PMCID: PMC9521507 DOI: 10.1002/mds.28610] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 03/17/2021] [Accepted: 03/18/2021] [Indexed: 01/22/2023] Open
Abstract
Background: Given that new therapeutic options for spinocerebellar ataxias are on the horizon, there is a need for markers that reflect disease-related alterations, in particular, in the preataxic stage, in which clinical scales are lacking sensitivity. Objective: The objective of this study was to quantify regional brain volumes and upper cervical spinal cord areas in spinocerebellar ataxia type 3 in vivo across the entire time course of the disease. Methods: We applied a brain segmentation approach that included a lobular subsegmentation of the cerebellum to magnetic resonance images of 210 ataxic and 48 preataxic spinocerebellar ataxia type 3 mutation carriers and 63 healthy controls. In addition, cervical cord cross-sectional areas were determined at 2 levels. Results: The metrics of cervical spinal cord segments C3 and C2, medulla oblongata, pons, and pallidum, and the cerebellar anterior lobe were reduced in preataxic mutation carriers compared with controls. Those of cervical spinal cord segments C2 and C3, medulla oblongata, pons, midbrain, cerebellar lobules crus II and X, cerebellar white matter, and pallidum were reduced in ataxic compared with nonataxic carriers. Of all metrics studied, pontine volume showed the steepest decline across the disease course. It covaried with ataxia severity, CAG repeat length, and age. The multivariate model derived from this analysis explained 46.33% of the variance of pontine volume. Conclusion: Regional brain and spinal cord tissue loss in spinocerebellar ataxia type 3 starts before ataxia onset. Pontine volume appears to be the most promising imaging biomarker candidate for interventional trials that aim at slowing the progression of spinocerebellar ataxia type 3.
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Affiliation(s)
- Jennifer Faber
- DZNE, German Center for Neurodegenerative Diseases, Bonn, Germany.,Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Tamara Schaprian
- DZNE, German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Koyak Berkan
- DZNE, German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Kathrin Reetz
- Department of Neurology, RWTH Aachen University, Bonn, Germany.,JARA-Brain Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich, Jülich, Germany
| | - Marcondes Cavalcante França
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas, Brazil.,Department of Neurology, University of Campinas, Campinas, Brazil
| | - Thiago Junqueira Ribeiro de Rezende
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Campinas, Brazil.,Department of Neurology, University of Campinas, Campinas, Brazil
| | - Jiang Hong
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Weihua Liao
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, People's Republic of China
| | - Bart van de Warrenburg
- Department of Neurology, Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Judith van Gaalen
- Department of Neurology, Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Alexandra Durr
- Sorbonne Université, Paris Brain Institute, AP-HP, INSERM, CNRS, Pitié-Salpêtrière University Hospital, Paris, France
| | - Fanny Mochel
- Sorbonne Université, Paris Brain Institute, AP-HP, INSERM, CNRS, Pitié-Salpêtrière University Hospital, Paris, France
| | - Paola Giunti
- Ataxia Centre, Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, United Kingdom.,National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Hector Garcia-Moreno
- Ataxia Centre, Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, United Kingdom.,National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Ludger Schoels
- Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,German Centre for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Holger Hengel
- Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,German Centre for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Matthis Synofzik
- Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,German Centre for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Benjamin Bender
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany
| | - Gulin Oz
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
| | - James Joers
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Jereon J de Vries
- Department of Neurology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jun-Suk Kang
- Department of Neurology, Goethe University, Frankfurt am Main, Germany
| | | | - Heike Jacobi
- Department of Neurology, University Hospital of Heidelberg, Heidelberg, Germany
| | - Jon Infante
- Neurology Service, University Hospital Marques de Valdecilla-IDIVAL, University of Cantabria, Centro de Investigacion Biomedica en Red de Enfermedades Neurodegenerativas (CIBERNED), Santander, Spain
| | | | - Sandro Romanzetti
- JARA-Brain Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich, Jülich, Germany
| | - Jorn Diedrichsen
- Brain Mind Institute, Departmentof Computer Science, Department of Statistics, University of Western Ontario, London, Canada
| | - Matthias Schmid
- DZNE, German Center for Neurodegenerative Diseases, Bonn, Germany.,Institute of Medical Biometry, Informatics and Epidemiology, University Hospital Bonn, Bonn, Germany
| | | | - Thomas Klockgether
- DZNE, German Center for Neurodegenerative Diseases, Bonn, Germany.,Department of Neurology, University Hospital Bonn, Bonn, Germany
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26
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Romero JE, Coupe P, Lanuza E, Catheline G, Manjón JV. Toward a unified analysis of cerebellum maturation and aging across the entire lifespan: A MRI analysis. Hum Brain Mapp 2021; 42:1287-1303. [PMID: 33385303 PMCID: PMC7927303 DOI: 10.1002/hbm.25293] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 10/27/2020] [Accepted: 10/29/2020] [Indexed: 12/23/2022] Open
Abstract
Previous literature about the structural characterization of the human cerebellum is related to the context of a specific pathology or focused in a restricted age range. In fact, studies about the cerebellum maturation across the lifespan are scarce and most of them considered the cerebellum as a whole without investigating each lobule. This lack of study can be explained by the lack of both accurate segmentation methods and data availability. Fortunately, during the last years, several cerebellum segmentation methods have been developed and many databases comprising subjects of different ages have been made publically available. This fact opens an opportunity window to obtain a more extensive analysis of the cerebellum maturation and aging. In this study, we have used a recent state‐of‐the‐art cerebellum segmentation method called CERES and a large data set (N = 2,831 images) from healthy controls covering the entire lifespan to provide a model for 12 cerebellum structures (i.e., lobules I‐II, III, IV, VI, Crus I, Crus II, VIIB, VIIIA, VIIIB, IX, and X). We found that lobules have generally an evolution that follows a trajectory composed by a fast growth and a slow degeneration having sometimes a plateau for absolute volumes, and a decreasing tendency (faster in early ages) for normalized volumes. Special consideration is dedicated to Crus II, where slow degeneration appears to stabilize in elder ages for absolute volumes, and to lobule X, which does not present any fast growth during childhood in absolute volumes and shows a slow growth for normalized volumes.
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Affiliation(s)
- José E Romero
- Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, Valencia, Spain
| | - Pierrick Coupe
- CNRS, University of Bordeaux, Bordeaux INP, LABRI, UMR5800, Talence, France.,CNRS, EPHE PSL Research University of, INCIA, UMR 5283, University of Bordeaux, Bordeaux, France
| | - Enrique Lanuza
- Department of Cell Biology, University of Valencia, Valencia, Spain
| | - Gwenaelle Catheline
- CNRS, EPHE PSL Research University of, INCIA, UMR 5283, University of Bordeaux, Bordeaux, France
| | - José V Manjón
- Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, Valencia, Spain
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27
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Bernard JA, Nguyen AD, Hausman HK, Maldonado T, Ballard HK, Jackson TB, Eakin SM, Lokshina Y, Goen JRM. Shaky scaffolding: Age differences in cerebellar activation revealed through activation likelihood estimation meta-analysis. Hum Brain Mapp 2020; 41:5255-5281. [PMID: 32936989 PMCID: PMC7670650 DOI: 10.1002/hbm.25191] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Revised: 07/27/2020] [Accepted: 08/15/2020] [Indexed: 01/10/2023] Open
Abstract
Cognitive neuroscience research has provided foundational insights into aging, but has focused primarily on the cerebral cortex. However, the cerebellum is subject to the effects of aging. Given the importance of this structure in the performance of motor and cognitive tasks, cerebellar differences stand to provide critical insights into age differences in behavior. However, our understanding of cerebellar functional activation in aging is limited. Thus, we completed a meta‐analysis of neuroimaging studies across task domains. Unlike in the cortex where an increase in bilateral activation is seen during cognitive task performance with advanced age, there is less overlap in cerebellar activation across tasks in older adults (OAs) relative to young. Conversely, we see an increase in activation overlap in OAs during motor tasks. We propose that this is due to inputs for comparator processing in the context of control theory (cortical and spinal) that may be differentially impacted in aging. These findings advance our understanding of the aging mind and brain.
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Affiliation(s)
- Jessica A Bernard
- Department of Psychological and Brain Sciences, Texas A&M University, College Station, Texas, USA.,Texas A&M Institute for Neuroscience, Texas A&M University, College Station, Texas, USA
| | - An D Nguyen
- Department of Psychological and Brain Sciences, Texas A&M University, College Station, Texas, USA.,Department of Cognitive Science, Johns Hopkins University, Baltimore, Maryland, USA
| | - Hanna K Hausman
- Department of Psychological and Brain Sciences, Texas A&M University, College Station, Texas, USA.,Department of Clinical and Health Psychology, University of Florida, Gainesville, Florida, USA
| | - Ted Maldonado
- Department of Psychological and Brain Sciences, Texas A&M University, College Station, Texas, USA
| | - Hannah K Ballard
- Texas A&M Institute for Neuroscience, Texas A&M University, College Station, Texas, USA
| | - T Bryan Jackson
- Department of Psychological and Brain Sciences, Texas A&M University, College Station, Texas, USA
| | - Sydney M Eakin
- Department of Psychological and Brain Sciences, Texas A&M University, College Station, Texas, USA
| | - Yana Lokshina
- Texas A&M Institute for Neuroscience, Texas A&M University, College Station, Texas, USA
| | - James R M Goen
- Department of Psychological and Brain Sciences, Texas A&M University, College Station, Texas, USA
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28
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Fitzgerald M, Pritschet L, Santander T, Grafton ST, Jacobs EG. Cerebellar network organization across the human menstrual cycle. Sci Rep 2020; 10:20732. [PMID: 33244032 PMCID: PMC7691518 DOI: 10.1038/s41598-020-77779-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Accepted: 11/17/2020] [Indexed: 11/09/2022] Open
Abstract
The cerebellum contains the vast majority of neurons in the brain and houses distinct functional networks that constitute at least two homotopic maps of cerebral networks. It is also a major site of sex steroid hormone action. While the functional organization of the human cerebellum has been characterized, the influence of sex steroid hormones on intrinsic cerebellar network dynamics has yet to be established. Here we investigated the extent to which endogenous fluctuations in estradiol and progesterone alter functional cerebellar networks at rest in a woman densely sampled over a complete menstrual cycle (30 consecutive days). Edgewise regression analysis revealed robust negative associations between progesterone and cerebellar coherence. Graph theory metrics probed sex hormones' influence on topological brain states, revealing relationships between sex hormones and within-network integration in Ventral Attention, Dorsal Attention, and SomatoMotor Networks. Together these results suggest that the intrinsic dynamics of the cerebellum are intimately tied to day-by-day changes in sex hormones.
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Affiliation(s)
- Morgan Fitzgerald
- Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, CA, 93106, USA
| | - Laura Pritschet
- Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, CA, 93106, USA
| | - Tyler Santander
- Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, CA, 93106, USA
| | - Scott T Grafton
- Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, CA, 93106, USA
- Institute for Collaborative Biotechnologies, University of California, Santa Barbara, USA
- Neuroscience Research Institute, University of California, Santa Barbara, USA
| | - Emily G Jacobs
- Department of Psychological and Brain Sciences, University of California, Santa Barbara, Santa Barbara, CA, 93106, USA.
- Neuroscience Research Institute, University of California, Santa Barbara, USA.
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