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Consensus Paper: Cerebellum and Ageing

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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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Data Availability

The data shown in the figures are available on request.

Abbreviations

AD::

Alzheimer’s disease

APP:

Amyloid precursor protein

CES-D:

Center of epidemiology studies depression scale

ctDCS:

Cerebellar transcranial direct current stimulation

DAN:

Dorsal attention network

DMN:

Default mode network

FC:

Functional connectivity

fNIRS:

Functional near-infrared spectroscopy

GMV:

Grey matter volume

ILAS :

I-LAN longitudinal aging study

MCI:

Mild cognitive impairment

MF:

Mossy fiber

NIBS :

Non invasive brain stimulation

PCDS:

Physio-cognitive decline syndrome

PS:

Processing speed

SN:

Salience network

SNPs:

Single-nucleotide polymorphisms

VFM:

Volume fraction myelin

WMH:

White matter hyperintensities.

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Funding

KS and MY are supported by the Japan Society for the Promotion of Science through a Grant-in-Aid for Scientific Research (21H04422).

VMD is supported by the National Institute on Aging (U19AG073172, U19AG065169, R21AG077307), the National Science Foundation (2112455), and the Alzheimer’s Association (AARG-NTF-21-852145).

JAB is supported by the National Institute on Aging (R01AG064010).

Author information

Authors and Affiliations

  1. Sorbonne Université, INSERM, CNRS, Institut de la Vision, 17 rue Moreau, F-75012, Paris, France

    Angelo Arleo & Stephen Ramanoël

  2. First Department of Neurology, Faculty of Medicine, Masaryk University and St. Anne’s Teaching Hospital, Brno, Czech Republic

    Martin Bareš

  3. Department of Neurology, School of Medicine, University of Minnesota, Minneapolis, USA

    Martin Bareš

  4. Department of Psychological and Brain Sciences, Texas A&M University, 4235 TAMU, College Station, TX, 77843, USA

    Jessica A. Bernard

  5. Texas A&M Institute for Neuroscience, Texas A&M University, College Station, TX, USA

    Jessica A. Bernard

  6. Department of Psychology, Georgia State University, Atlanta, GA, USA

    Hannah R. Bogoian, Vonetta M. Dotson & Maria Misiura

  7. Department of Psychology, Stavanger University, Institute of Social Sciences, Kjell Arholms Gate 41, 4021, Stavanger, Norway

    Muriel M. K. Bruchhage

  8. King’s College London, Institute of Psychiatry, Psychology and Neuroscience, Centre for Neuroimaging Sciences, Box 89, De Crespigny Park, London, PO, SE5 8AF, UK

    Muriel M. K. Bruchhage

  9. Rhode Island Hospital, Department for Diagnostic Imaging, 1 Hoppin St, Providence, RI, 02903, USA

    Muriel M. K. Bruchhage

  10. Department of Paediatrics, Warren Alpert Medical School of Brown University, 222 Richmond St, Providence, RI, 02903, USA

    Muriel M. K. Bruchhage

  11. Freie Universität Berlin, Fachbereich Mathematik und Informatik, Arnimallee 12, 14195, Berlin, Germany

    Patrick Bryant

  12. Department of Psychiatry and Behavioural Sciences, University of Washington, Seattle, WA, USA

    Erik S. Carlson & Colby L. Samstag

  13. Geriatric Research, Education and Clinical Center, Veteran’s Affairs Medical Center, Puget Sound, Seattle, WA, USA

    Erik S. Carlson & Colby L. Samstag

  14. Department of Psychology, The Education University of Hong Kong, New Territories, Tai Po, Hong Kong, China

    Chetwyn C. H. Chan & Clive H. Y. Wong

  15. Center for Healthy Longevity and Aging Sciences, National Yang Ming Chiao Tung University College of Medicine, Taipei, Taiwan

    Liang-Kung Chen & Chih-Ping Chung

  16. Center for Geriatric and Gerontology, Taipei Veterans General Hospital, Taipei, Taiwan

    Liang-Kung Chen

  17. Taipei Municipal Gan-Dau Hospital (managed by Taipei Veterans General Hospital), Taipei, Taiwan

    Liang-Kung Chen

  18. Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan

    Chih-Ping Chung

  19. Gerontology Institute, Georgia State University, Atlanta, GA, USA

    Vonetta M. Dotson

  20. Department of Neurology, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic

    Pavel Filip

  21. Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, USA

    Pavel Filip

  22. Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA

    Xavier Guell & Jeremy D. Schmahmann

  23. Laboratory for Neuroanatomy and Cerebellar Neurobiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA

    Xavier Guell & Jeremy D. Schmahmann

  24. CHNO Des Quinze-Vingts, INSERM-DGOS CIC 1423, 28 rue de Charenton, 75012, Paris, France

    Christophe Habas

  25. Université Versailles St Quentin en Yvelines, Paris, France

    Christophe Habas

  26. School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, PO BOX 616, 6200, MD, Maastricht, The Netherlands

    Heidi I.L. Jacobs

  27. Faculty of Psychology and Neuroscience, Department of Cognitive Neuroscience, Maastricht University, PO BOX 616, 6200, MD, Maastricht, The Netherlands

    Heidi I.L. Jacobs

  28. Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA

    Heidi I.L. Jacobs

  29. Jissen Women’s University, Tokyo, Japan

    Shinji Kakei

  30. State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China

    Tatia M. C. Lee

  31. Laboratory of Neuropsychology and Human Neuroscience, Department of Psychology, The University of Hong Kong, Hong Kong, China

    Tatia M. C. Lee

  32. Department of Psychology, Sapienza University of Rome, Rome, Italy

    Maria Leggio & Giusy Olivito

  33. Ataxia Laboratory, I.R.C.C.S. Santa Lucia Foundation, Rome, Italy

    Maria Leggio & Giusy Olivito

  34. Department of Medical Education, Tokyo Medical University, Tokyo, Japan

    Hiroshi Mitoma

  35. Université Côte d’Azur, LAMHESS, Nice, France

    Stephen Ramanoël

  36. Noninvasive Neuromodulation Unit, Experimental Therapeutics & Pathophysiology Branch, National Institute of Mental Health, NIH, Bethesda, USA

    Zeynab Rezaee

  37. Ataxia Center, Cognitive Behavioural neurology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA

    Jeremy D. Schmahmann

  38. Graduate School of Advanced Integrated Studies in Human Survivability, Kyoto University, Kyoto, Japan

    Kaoru Sekiyama

  39. Research Center for Child Mental Development, University of Fukui, Fukui, Japan

    Masatoshi Yamashita

  40. United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Osaka, Japan

    Masatoshi Yamashita

  41. Service de Neurologie, Médiathèque Jean Jacquy, CHU-Charleroi, Charleroi, Belgium

    Mario Manto

  42. Service des Neurosciences, University of Mons, Mons, Belgium

    Mario Manto

Author notes

  1. Christophe Habas is deceased. This paper is dedicated to his/her memory.

    • Christophe Habas
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  1. Angelo Arleo
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Contributions

Concept and preparation: MM. Draft: all. Discussion, corrections, and approval of the final version: all.

Corresponding author

Correspondence to Mario Manto.

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Ethical Approval

Regarding the data presented in the “Cerebellum and the Physio-cognitive Decline Syndrome (Chih-Ping Chung, Liang-Kung Chen)” section, the Institutional Review Board of National Yang Ming University, Taipei, Taiwan, approved the study (IRB No. YM109161F). Regarding data presented in the “What Potential Does Lifelong Musical Instrument Training Possess To Avoid Age-Related Cerebellar Atrophy? (Masatoshi Yamashita, Kaoru Sekiyama)” section, the Institutional Review Board of Fukui University approved the study (IRB No. 29-P-7). All participants provided written informed consent. All methods were carried out in accordance with relevant guidelines and regulations.

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Arleo, A., Bareš, M., Bernard, J.A. et al. Consensus Paper: Cerebellum and Ageing. Cerebellum 23, 802–832 (2024). https://doi.org/10.1007/s12311-023-01577-7

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