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Motor control and aging: Links to age-related brain structural, functional, and biochemical effects
Open accessAbstract
Although connections between cognitive deficits and age-associated brain differences have been elucidated, relationships with motor performance are less well understood. Here, we broadly review age-related brain differences and motor deficits in older adults in addition to cognition-action theories. Age-related atrophy of the motor cortical regions and corpus callosum may precipitate or coincide with motor declines such as balance and gait deficits, coordination deficits, and movement slowing. Correspondingly, degeneration of neurotransmitter systems—primarily the dopaminergic system—may contribute to age-related gross and fine motor declines, as well as to higher cognitive deficits. In general, older adults exhibit involvement of more widespread brain regions for motor control than young adults, particularly the prefrontal cortex and basal ganglia networks. Unfortunately these same regions are the most vulnerable to age-related effects, resulting in an imbalance of “supply and demand”. Existing exercise, pharmaceutical, and motor training interventions may ameliorate motor deficits in older adults.
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Cites
The cholinergic hypothesis of geriatric memory dysfunction
Bartus, R. T., Dean, R. L., Beer, B., & Lippa, A. S. (1982) · Science · doi:10.1126/science.7046051 · Cited by 5,545
A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains
Good, C. D., Johnsrude, I. S., Ashburner, J., Henson, R. N. A., Friston, K. J., & Frackowiak, R. S. J. (2001) · NeuroImage · doi:10.1006/nimg.2001.0786 · Cited by 4,561
The adaptive brain: aging and neurocognitive scaffolding
Park, D. C., & Reuter-Lorenz, P. (2009) · Annual Review of Psychology · doi:10.1146/annurev.psych.59.103006.093656 · Cited by 2,790
Changes in grey matter induced by training
Draganski, B., Gaser, C., Busch, V., Schuierer, G., Bogdahn, U., & May, A. (2004) · Nature · doi:10.1038/427311a · Cited by 2,373
Mapping cortical change across the human life span
Sowell, E. R., Peterson, B. S., Thompson, P. M., Welcome, S. E., Henkenius, A. L., & Toga, A. W. (2003) · Nature Neuroscience · doi:10.1038/nn1008 · Cited by 2,328
Aerobic Exercise Training Increases Brain Volume in Aging Humans
Colcombe, S. J., Erickson, K. I., Scalf, P. E., Kim, J. S., Prakash, R., McAuley, E., Elavsky, S., Marquez, D. X., Hu, L., & Kramer, A. F. (2006) · The Journals of Gerontology Series A: Biological Sciences and Medical Sciences · doi:10.1093/gerona/61.11.1166 · Cited by 2,134
Thinning of the Cerebral Cortex in Aging
Salat, D. H. (2004) · Cerebral Cortex · doi:10.1093/cercor/bhh032 · Cited by 1,851
Song, S.-K., Sun, S.-W., Ju, W.-K., Lin, S.-J., Cross, A. H., & Neufeld, A. H. (2003) · NeuroImage · doi:10.1016/j.neuroimage.2003.07.005 · Cited by 1,738
Demyelination increases radial diffusivity in corpus callosum of mouse brain
Song, S.-K., Yoshino, J., Le, T. Q., Lin, S.-J., Sun, S.-W., Cross, A. H., & Armstrong, R. C. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.01.028 · Cited by 1,658
Cardiovascular fitness, cortical plasticity, and aging
Colcombe, S. J., Kramer, A. F., Erickson, K. I., Scalf, P., McAuley, E., Cohen, N. J., Webb, A., Jerome, G. J., Marquez, D. X., & Elavsky, S. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0400266101 · Cited by 1,648
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Hearing Impairment and Cognitive Energy: The Framework for Understanding Effortful Listening (FUEL)
Pichora-Fuller, M. K., Kramer, S. E., Eckert, M. A., Edwards, B., Hornsby, B. W. Y., Humes, L. E., Lemke, U., Lunner, T., Matthen, M., Mackersie, C. L., et al. (2016) · Ear & Hearing · doi:10.1097/aud.0000000000000312 · Cited by 1,318
Fragala, M. S., Cadore, E. L., Dorgo, S., Izquierdo, M., Kraemer, W. J., Peterson, M. D., & Ryan, E. D. (2019) · Journal of Strength and Conditioning Research · doi:10.1519/jsc.0000000000003230 · Cited by 1,290
The developmental trajectories of executive function from adolescence to old age.
Ferguson, H. J., Brunsdon, V. E. A., & Bradford, E. E. F. (2021) · Scientific Reports · doi:10.1038/s41598-020-80866-1 · Cited by 583
Loss of white matter integrity is associated with gait disorders in cerebral small vessel disease
de Laat, K. F., Tuladhar, A. M., van Norden, A. G. W., Norris, D. G., Zwiers, M. P., & de Leeuw, F.-E. (2011) · Brain · doi:10.1093/brain/awq343 · Cited by 296
Lee, J. K., Koppelmans, V., Riascos, R. F., Hasan, K. M., Pasternak, O., Mulavara, A. P., Bloomberg, J. J., & Seidler, R. D. (2019) · JAMA Neurology · doi:10.1001/jamaneurol.2018.4882 · Cited by 149
Self-citationAPOE Stabilization by Exercise Prevents Aging Neurovascular Dysfunction and Complement Induction
Soto, I., Graham, L. C., Richter, H. J., Simeone, S. N., Radell, J. E., Grabowska, W., Funkhouser, W. K., Howell, M. C., & Howell, G. R. (2015) · PLOS Biology · doi:10.1371/journal.pbio.1002279 · Cited by 140
Sarcopenia: Molecular Pathways and Potential Targets for Intervention
Pascual-Fernández, J., Fernández-Montero, A., Córdova-Martínez, A., Pastor, D., Martínez-Rodríguez, A., & Roche, E. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21228844 · Cited by 125
Decoding lifespan changes of the human brain using resting-state functional connectivity MRI
Wang, L., Su, L., Shen, H., & Hu, D. (2012) · PLoS ONE · doi:10.1371/journal.pone.0044530 · Cited by 115
Shaughnessy, K. A., Hackney, K. J., Clark, B. C., Kraemer, W. J., Terbizan, D. J., Bailey, R. R., & McGrath, R. (2020) · Journal of Alzheimer’s Disease · doi:10.3233/jad-190856 · Cited by 90
Aging-associated sensory decline and Alzheimer’s disease
Hong, S., Baek, S.-H., Lai, M. K. P., Arumugam, T. V., & Jo, D.-G. (2024) · Molecular Neurodegeneration · doi:10.1186/s13024-024-00776-y · Cited by 76
Age-related increases in reaction time result from slower preparation, not delayed initiation
Hardwick, R. M., Forrence, A. D., Costello, M. G., Zackowski, K., & Haith, A. M. (2022) · Journal of Neurophysiology · doi:10.1152/jn.00072.2022 · Cited by 66
Defining organizational contributions to sustaining an ageing workforce: a bibliometric review
Nagarajan, N. R., Wada, M., Fang, M. L., & Sixsmith, A. (2019) · European Journal of Ageing · doi:10.1007/s10433-019-00499-w · Cited by 61
Aging and speech understanding
Lee, J. Y. (2015) · Journal of Audiology and Otology · doi:10.7874/jao.2015.19.1.7 · Cited by 51
Luo, C., Zhang, X., Cao, X., Gan, Y., Li, T., Cheng, Y., Cao, W., Jiang, L., Yao, D., & Li, C. (2016) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2016.00032 · Cited by 33
Geng, Q., Zhai, H., Wang, L., Wei, H., & Hou, S. (2023) · Medicine · doi:10.1097/md.0000000000034254 · Cited by 33
Dissociating effects of subclinical anxiety and depression on cognitive control.
Ng (2012) · PubMed · doi:10.2478/v10053-008-0100-6 · Cited by 26
MotorBrain: A mobile app for the assessment of users’ motor performance in neurology
Vianello, A., Chittaro, L., Burigat, S., & Budai, R. (2017) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2017.02.012 · Cited by 17
Beauchet, O., Launay, C. P., Chabot, J., Levinoff, E. J., & Allali, G. (2016) · Journal of Alzheimer's Disease · doi:10.3233/jad-160604 · Cited by 15
Linnet, E., & Roser, M. E. (2012) · Psychology and Aging · doi:10.1037/a0024905 · Cited by 14
Sato, S. D., Shah, V. A., Fettrow, T., Hall, K. G., Tays, G. D., Cenko, E., Roy, A., Clark, D. J., Ferris, D. P., Hass, C. J., et al. (2025) · NeuroImage · doi:10.1016/j.neuroimage.2025.121155 · Cited by 6
Self-citationKim, B., Youm, C., Park, H., Choi, H., & Shin, S. (2024) · Frontiers in Public Health · doi:10.3389/fpubh.2024.1376736 · Cited by 4
Goldenkoff, E. R., Deluisi, J. A., Brissenden, J. A., Lee, T. G., Polk, T. A., Taylor, S. F., Hampstead, B. M., & Vesia, M. (2025) · Clinical Neurophysiology · doi:10.1016/j.clinph.2025.03.003 · Cited by 3
Metadata
- Authors
- Seidler, R. D., Bernard, J. A., Burutolu, T. B., Fling, B. W., Gordon, M. T., Gwin, J. T., Kwak, Y., & Lipps, D. B.
- Venue
- Neuroscience & Biobehavioral Reviews
- Publisher
- Elsevier BV
- Published
- 2010-04
- Volume
- 34
- Issue
- 5
- Pages
- 721-733
- ISSN
- 0149-7634 (ISSN-L)
- OpenAlex
- W2136406126
- Cited by
- 1,791
- References
- 17
- FWCI
- 13.25
- Type
- journal article
- Language
- en
- Open access
- green
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