Abstract
The cerebellum supports higher-order cognition, such as working memory and executive function (EF) both directly and through connection with prefrontal areas via cortical loops. Thus, age-related degradation to white matter connectivity comprising cerebello-thalamo-cortical (CTC) loops may underlie age-related differences in EF. In 190 healthy adults (aged 20–94 years) we collected diffusion tensor imaging scans and multiple tests of working memory and EF. Deterministic tractography was used to generate CTC tracts from which white matter metrics (mean, radial, axial diffusivities) were extracted. General linear model results indicated that reduced white matter integrity (i.e., higher diffusivity) was associated with significantly poorer EF performance in an age-dependent fashion. Specifically, we find evidence of an accelerated rate of increased diffusivity with increasing age across the adult lifespan. Higher mean, radial, and axial diffusivities (MD, RD, AD, respectively) in fronto-cerebellar white matter tracts were also associated with lower EF scores in older, but not younger, adults. These findings suggest CTC white matter connectivity is important for executive function performance and lend mechanistic evidence to the role of the cerebellum in age-related differences in higher-order cognitive operations.
Similar content being viewed by others
Data availability
Data and code from this study is publicly available at https://osf.io/248nq/?view_only=f5ec11d96dd544ce81811c610dded0de.
References
Argyropoulos, G. P. D. et al. The Cerebellar Cognitive Affective/Schmahmann Syndrome: a Task Force Paper. Cerebellum 19(1), 102–125 (2020).
Schmahmann, J. D. An emerging concept. The cerebellar contribution to higher function. Arch. Neurol. 48(11), 1178–1187 (1991).
Schmahmann, J. D. & Sherman, J. C. Cerebellar cognitive affective syndrome. Int. Rev. Neurobiol. 41, 433–440 (1997).
Desmond, J. E. et al. Lobular patterns of cerebellar activation in verbal working-memory and finger-tapping tasks as revealed by functional MRI. J. Neurosci. 17(24), 9675–9685 (1997).
Guell, X. & Schmahmann, J. Cerebellar functional anatomy: A didactic summary based on human fMRI evidence. Cerebellum 19(1), 1–5 (2020).
Schmahmann, J. D. The cerebellum and cognition. Neurosci. Lett. 688, 62–75 (2019).
Stoodley, C. J. & Schmahmann, J. D. Functional topography in the human cerebellum: A meta-analysis of neuroimaging studies. Neuroimage 44(2), 489–501 (2009).
Schall, U. et al. Functional brain maps of Tower of London performance: A positron emission tomography and functional magnetic resonance imaging study. Neuroimage 20(2), 1154–1161 (2003).
Rao, S. M. et al. Functional MRI evidence for subcortical participation in conceptual reasoning skills. NeuroReport 8(8), 1987–1993 (1997).
Liddle, P. F., Kiehl, K. A. & Smith, A. M. Event-related fMRI study of response inhibition. Hum. Brain Mapp. 12(2), 100–109 (2001).
Ernst, M. Decision-making in a risk-taking task: A PET study. Neuropsychopharmacology 26(5), 682–691 (2002).
King, M. et al. Functional boundaries in the human cerebellum revealed by a multi-domain task battery. Nat. Neurosci. 22(8), 1371–1378 (2019).
Bernard, J. A. et al. Disrupted cortico-cerebellar connectivity in older adults. Neuroimage 83, 103–119 (2013).
Bernard, J. A. et al. Shaky scaffolding: Age differences in cerebellar activation revealed through activation likelihood estimation meta-analysis. Hum. Brain Mapp. 41(18), 5255–5281 (2020).
Bernard, J. A. & Seidler, R. D. Relationships between regional cerebellar volume and sensorimotor and cognitive function in young and older adults. Cerebellum 12(5), 721–737 (2013).
Hausman, H. K. et al. From synchrony to asynchrony: Cerebellar-basal ganglia functional circuits in young and older adults. Cereb. Cortex 30(2), 718–729 (2020).
Alexander, G. E. et al. Regional network of magnetic resonance imaging gray matter volume in healthy aging. NeuroReport 17(10), 951–956 (2006).
Raz, N. et al. Trajectories of brain aging in middle-aged and older adults: Regional and individual differences. Neuroimage 51(2), 501–511 (2010).
Hoogendam, Y. Y. et al. Determinants of cerebellar and cerebral volume in the general elderly population. Neurobiol Aging 33(12), 2774–2781 (2012).
Raz, N. et al. Differential brain shrinkage over 6 months shows limited association with cognitive practice. Brain Cogn. 82(2), 171–180 (2013).
Bennett, I. J. et al. Age-related differences in multiple measures of white matter integrity: A diffusion tensor imaging study of healthy aging. Hum. Brain Mapp. 31(3), 378–390 (2010).
Cavallari, M. et al. Mobility impairment is associated with reduced microstructural integrity of the inferior and superior cerebellar peduncles in elderly with no clinical signs of cerebellar dysfunction. Neuroimage Clin. 2, 332–340 (2013).
Kafri, M. et al. High-level gait disorder: Associations with specific white matter changes observed on advanced diffusion imaging. J. Neuroimaging 23(1), 39–46 (2013).
Paitel, E. R. et al. Cerebellar white matter microstructure is associated with age, cerebrospinal fluid amyloid beta levels, and cognition in cognitively unimpaired older adults. Hum. Brain Mapp. 46(16), e70398 (2025).
Song, S. K. et al. Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia. Neuroimage 20(3), 1714–1722 (2003).
Webb, C.E., et al., Age-related degradation of optic radiation white matter predicts visual, but not verbal executive functions. Apert Neuro, 2022. 2.
Cohen, J. A power primer. Psychol. Bull. 112(1), 155–159 (1992).
Radloff, L. S. The CES-D scale. Appl. Psychol. Meas. 1(3), 385–401 (1977).
Folstein, M. F., Folstein, S. E. & McHugh, P. R. Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J. Psychiatr. Res. 12(3), 189–198 (1975).
Smith, S. M. Fast robust automated brain extraction. Hum. Brain Mapp. 17(3), 143–155 (2002).
Avants, B. B. et al. A reproducible evaluation of ANTs similarity metric performance in brain image registration. Neuroimage 54(3), 2033–2044 (2011).
Oguz, I. et al. DTIPrep: Quality control of diffusion-weighted images. Front. Neuroinform. 8, 4 (2014).
Leemans, A. & Jones, D. K. The B-matrix must be rotated when correcting for subject motion in DTI data. Magn. Reson. Med. 61(6), 1336–1349 (2009).
Yeh, F. C. et al. Deterministic diffusion fiber tracking improved by quantitative anisotropy. PLoS ONE 8(11), e80713 (2013).
Delis, D.C., E. Kaplan, and J.H. Kramer, Delis-Kaplan Executive Function System. 2012.
Daneman, M. & Carpenter, P. A. Individual differences in working memory and reading. J. Verbal Learn. Verbal Behav. 19(4), 450–466 (1980).
Wechsler, D., Wechsler Adult Intelligence Scale--Fourth Edition. 2012.
Bates, D., et al., Fitting Linear Mixed-Effects Models Usinglme4. Journal of Statistical Software, 2015. 67(1).
R Core Team, R: A Language and Environment for Statistical Computing. 2025.
Long, J.A., interactions: Comprehensive, User-Friendly Toolkit for Probing Interactions. 2024.
Kim, S., ppcor: Partial and Semi-Partial (Part) Correlation. 2015.
Johnson, P. O. & Neyman, J. Tests of certain linear hypotheses and their application to some educational problems. Statistical Research Memoirs 1, 57–93 (1936).
Bennett, I. J. & Madden, D. J. Disconnected aging: Cerebral white matter integrity and age-related differences in cognition. Neuroscience 276, 187–205 (2014).
Kennedy, K. M. & Raz, N. Aging white matter and cognition: Differential effects of regional variations in diffusion properties on memory, executive functions, and speed. Neuropsychologia 47(3), 916–927 (2009).
Madden, D. J. et al. Diffusion tensor imaging of cerebral white matter integrity in cognitive aging. Biochim Biophys Acta 1822(3), 386–400 (2012).
Raz, N. & Rodrigue, K. M. Differential aging of the brain: Patterns, cognitive correlates and modifiers. Neurosci. Biobehav. Rev. 30(6), 730–748 (2006).
Damoiseaux, J. S. et al. White matter tract integrity in aging and Alzheimer’s disease. Hum. Brain Mapp. 30(4), 1051–1059 (2009).
Sexton, C. E. et al. Accelerated changes in white matter microstructure during aging: a longitudinal diffusion tensor imaging study. J Neurosci 34(46), 15425–15436 (2014).
Abe, O. et al. Aging in the CNS: Comparison of gray/white matter volume and diffusion tensor data. Neurobiol. Aging 29(1), 102–116 (2008).
Habas, C. et al. Distinct cerebellar contributions to intrinsic connectivity networks. J. Neurosci. 29(26), 8586–8594 (2009).
Seeley, W. W. et al. Dissociable intrinsic connectivity networks for salience processing and executive control. J. Neurosci. 27(9), 2349–2356 (2007).
Rice, L. C. et al. Disrupted executive cerebro-cerebellar functional connectivity in alcohol use disorder. Alcohol Clin Exp Res (Hoboken) 48(1), 33–47 (2024).
Ravnkilde, B. et al. Putative tests of frontal lobe function: A PET-study of brain activation during Stroop’s Test and verbal fluency. J. Clin. Exp. Neuropsychol. 24(4), 534–547 (2002).
Peterburs, J. et al. The role of the cerebellum for feedback processing and behavioral switching in a reversal-learning task. Brain Cogn. 125, 142–148 (2018).
Greening, S. G., Finger, E. C. & Mitchell, D. G. Parsing decision making processes in prefrontal cortex: Response inhibition, overcoming learned avoidance, and reversal learning. Neuroimage 54(2), 1432–1441 (2011).
Berlijn, A. M. et al. The role of the human cerebellum for learning from and processing of external feedback in non-motor learning: A systematic review. Cerebellum 23(4), 1532–1551 (2024).
Balsters, J. H. et al. Cerebellum and cognition: evidence for the encoding of higher order rules. Cereb Cortex 23(6), 1433–1443 (2013).
Yao, C. et al. Hyperconnectivity and connectome gradient dysfunction of Cerebello-Thalamo-Cortical circuitry in Alzheimer’s disease spectrum disorders. Cerebellum 24(2), 43 (2025).
Rabinovici, G. D., Stephens, M. L. & Possin, K. L. Executive dysfunction. Continuum (Minneap. Minn.). 21(3 Behavioral Neurology and Neuropsychiatry), 646–659 (2015).
Ribeiro, M. et al. White matter tracts and executive functions: A review of causal and correlation evidence. Brain 147(2), 352–371 (2024).
Baumann, O. et al. Consensus paper: The role of the cerebellum in perceptual processes. Cerebellum 14(2), 197–220 (2015).
Koziol, L. F. et al. Consensus paper: The cerebellum’s role in movement and cognition. Cerebellum 13(1), 151–177 (2014).
Palesi, F. et al. Contralateral cerebello-thalamo-cortical pathways with prominent involvement of associative areas in humans in vivo. Brain Struct. Funct. 220(6), 3369–3384 (2015).
Chen, S. H. & Desmond, J. E. Cerebrocerebellar networks during articulatory rehearsal and verbal working memory tasks. Neuroimage 24(2), 332–338 (2005).
Peterburs, J. et al. Working memory and verbal fluency deficits following cerebellar lesions: Relation to interindividual differences in patient variables. Cerebellum 9(3), 375–383 (2010).
Stoodley, C. J., Valera, E. M. & Schmahmann, J. D. Functional topography of the cerebellum for motor and cognitive tasks: An fMRI study. Neuroimage 59(2), 1560–1570 (2012).
Lazar, M. Working memory: How important is white matter?. Neuroscientist 23(2), 197–210 (2017).
Sternberg, S. High-speed scanning in human memory. Science 153(3736), 652–654 (1966).
Cairo, T. A. et al. The influence of working memory load on phase specific patterns of cortical activity. Brain Res. Cogn. Brain Res. 21(3), 377–387 (2004).
Kirschen, M. P. et al. Load- and practice-dependent increases in cerebro-cerebellar activation in verbal working memory: an fMRI study. Neuroimage 24(2), 462–472 (2005).
Bohland, J. W. & Guenther, F. H. An fMRI investigation of syllable sequence production. Neuroimage 32(2), 821–841 (2006).
Harvey, P. D. Domains of cognition and their assessment. Dialogues Clin. Neurosci. 21(3), 227–237 (2019).
Funding
This study was supported by the National Institutes of Health grant from the National Institute on Aging (2R01AG-036818).
Author information
Authors and Affiliations
Contributions
Writing (Original Draft Preparation)- JNK; Writing (Review & Editing)- JNK; DAH, KMK, KMR; Methodology- JNK, AO, DAH, KMK; Formal Analysis- JNK, AO, KMK; Visualization- JNK; Supervision- KMK, KMR; Funding Acquisition- KMK, KMR.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Kraft, J.N., Ortega, A., Hoagey, D.A. et al. Age-related cerebello-thalamo-cortical white matter degradation and executive function performance across the lifespan. Sci Rep (2026). https://doi.org/10.1038/s41598-026-39822-8
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41598-026-39822-8


