Maintenance and Updating of Verbal and Nonverbal Material in Working Memory in Healthy Ageing

PDF (Rus)

Recieved: 11/20/2025

Accepted: 02/11/2026

Published: 03/13/2026

Keywords: working memory; verbal material; nonverbal material; maintenance; updating; elderly; healthy ageing

Pages: 144–158

DOI: 10.11621/npj.2026.0211

Available online: 13.03.2026

To cite this article:

Panikratova, Y.R., Korolkova, O.A., Pchelintseva, M.E., Smirnova, A.V., Mening, S.M., Sinitsyn, V.E., Pechenkova, E.V. (2026). Maintenance and Updating of Verbal and Nonverbal Material in Working Memory in Healthy Ageing. National Psychological Journal, 21(2) , 144–158. https://doi.org/10.11621/npj.2026.0211

Copied to Clipboard

Copy

Panikratova, Y.R. Moscow Center for Continuous Mathematical Education, Institute of Biological Psychiatry, Mental Health Research Center

Korolkova, O.A. Moscow Center for Continuous Mathematical Education, Institute for Experimental Psychology, Moscow State University of Psychology and Education

Pchelintseva, M.E. Moscow Center for Continuous Mathematical Education, National Research University Higher School of Economics

Smirnova, A.V. Moscow Center for Continuous Mathematical Education

Mening, S.M. Moscow Center for Continuous Mathematical Education, National Research University Higher School of Economics

Sinitsyn, V.E. Moscow Center for Continuous Mathematical Education, University Clinic, Lomonosov Moscow State University

Pechenkova, E.V. Moscow Center for Continuous Mathematical Education, National Research University Higher School of Economics

Abstract

Background. Working memory (WM) declines with ageing. Despite a large body of relevant studies, changes in verbal and nonverbal WM, relevant specifically for healthy aging, and their brain correlates, remain understudied.

Objectives. Our study aimed to analyse changes in maintenance and updating of verbal and nonverbal material in WM in healthy ageing (i.e., the absence of cognitive decline, neurological and mental disorders, as well as the history of cardiovascular and cerebrovascular events and oncological diseases).

Study Participants. The final groups were equivalent in terms of education level and gender composition and comprised 16 older (65.7 ± 4.4 years) and 16 younger (23.3 ± 4.9 years) right-handed participants.

Methods. We analysed the behavioural data from the project wherein the brain activity was registered via functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) while the participants performed maximally comparable verbal and nonverbal versions of the Sternberg and n-back tasks developed by us earlier. This was done to overcome the methodological limitations of previous studies which used verbal and nonverbal WM tasks that addressed different processes (e.g., updating of verbal or maintenance of non-verbal material in WM), and had different structure, stimuli, and difficulty. Neurophysiological data were not analysed in the current article.

Results. Older participants demonstrated slower responses in all tasks than the younger participants. Response accuracy in the Sternberg task and the 0-back task was independent of age, whereas it decreased in the 2-back task by 5–10% in the older participants compared to the younger group. Some evidence in favour of a more prominent decrease of nonverbal vs. verbal WM in older participants was observed.

Conclusions. Maintenance of material in WM is not affected by healthy ageing. Decline in updating observed in high WM load may be considered as a true age-related change of WM.

References

Aurtenetxe, S., García-Pacios, J., del Rio, D., López, M.E., Pineda-Pardo, J.A., Marcos, A., Delgado Losada, M.L., López-Frutos, J.M., Maestú, F. (2016). Interference impacts working memory in mild cognitive impairment. Frontiers in Neuroscience, 10, 443. https://doi.org/10.3389/fnins.2016.00443

Baddeley, A., Hitch, G., Allen, R. (2020). A multicomponent model of working memory. In: R.H. Logie, V. Camos, N. Cowan, (eds.). Working memory: State of the science. (pp. 10–43). Oxford: Oxford University Press.

Bao, R., Chang, S., Liu, R., Wang, Y., Guan, Y. (2025). Research status of visuospatial dysfunction and spatial navigation. Frontiers in Aging Neuroscience, 17, 1609620. https://doi.org/10.3389/fnagi.2025.1609620

Bates, D., Mächler, M., Bolker, B., Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1), 1–48. https://doi.org/10.18637/jss.v067.i01

Camino-Pontes, B., Gonzalez-Lopez, F., Santamaria-Gomez, G., Sutil-Jimenez, A.J., Sastre-Barrios, C., Sastre-Barrios, C., Fernandez de Pierola, I., Cortes, J.M. (2023). One-year prediction of cognitive decline following cognitive-stimulation from real-world data. Journal of Neuropsychology, 17(2), 302–318. https://doi.org/10.1111/jnp.12307

Cerella, J., DiCara, R., Williams, D., Bowles, N. (1986). Relations between information processing and intelligence in elderly adults. Intelligence, 10(1), 75–91. https://doi.org/10.1016/0160-2896(86)90028-0

Cohen, R.A., Marsiske, M.M., Smith, G.E. (2019). Neuropsychology of aging. Handbook of Clinical Neurology, 167, 149–180. https://doi.org/10.1016/B978-0-12-804766-8.00010-8

Cowan, N., Morey, C.C., Naveh-Benjamin, M. (2020). An embedded-processes approach to working memory: How is it distinct from other approaches, and to what ends? In: R.H. Logie, V. Camos, N. Cowan, (eds.). Working memory: State of the science. (pp. 44–84). Oxford: Oxford University Press.

Cramer, S.C., Richards, L.G., Bernhardt, J., Duncan, P. (2023). Cognitive deficits after stroke. Stroke, 54(1), 5–9. https://doi.org/10.1161/STROKEAHA.122.041775

Hale, S., Rose, N.S., Myerson, J., Strube, M.J., Sommers, M., Tye-Murray, N., Spehar, B. (2011). The structure of working memory abilities across the adult life span. Psychology and Aging, 26(1), 92–110. https://doi.org/10.1037/a0021483

Hardwick, R.M., Forrence, A.D., Costello, M.G., Zackowski, K., Haith, A.M. (2022). Age-related increases in reaction time result from slower preparation, not delayed initiation. Journal of Neurophysiology, 128(3), 582–592. https://doi.org/10.1152/jn.00072.2022

Hardy, S.J., Krull, K.R., Wefel, J.S., Janelsins, M. (2018). Cognitive changes in cancer survivors. American Society of Clinical Oncology Educational Book, 38, 795–806. https://doi.org/10.1200/EDBK_201179

Hidalgo-Lopez, E., Noachtar, I., Pletzer, B.A. (2025). N-back task revisited: Comparing the neural correlates of updating and interference control. Imaging Neuroscience, (3). https://doi.org/10.1162/IMAG.a.1025

Hothorn, T., Bretz, F., Westfall, P. (2008). Simultaneous inference in general parametric models. Biometrical Journal, 50(3), 346–363. https://doi.org/10.1002/bimj.200810425

Johansen, M.C., Ye, W., Gross, A., Gottesman, R.F., Han, D., Whitney, R., Briceño, E.M. et al. (2023). Association between acute myocardial infarction and cognition. JAMA Neurology, 80(7), 723–731. https://doi.org/10.1001/jamaneurol.2023.1331

Johnson, W., Logie, R.H., Brockmole, J.R. (2010). Working memory tasks differ in factor structure across age cohorts: Implications for dedifferentiation. Intelligence, 38(5), 513–528. https://doi.org/10.1016/j.intell.2010.06.005

Kirchner, W.K. (1958). Age differences in short-term retention of rapidly changing information. Journal of Experimental Psychology, 55(4), 352–358. https://doi.org/10.1037/h0043688

Kirova, A.M., Bays, R.B., Lagalwar, S. (2015). Working memory and executive function decline across normal aging, mild cognitive impairment, and Alzheimer’s disease. BioMed Research International, 2015(6), 1–9. https://doi.org/10.1155/2015/748212

Korolkova, O.A., Smirnova, A.V., Panikratova, Y.R., Pchelintseva, M.E., Mening, S.M. et al. (in press). Comparable tasks to study brain correlates of verbal and nonverbal working memory via fMRI and MEG. Herald of the Russian Academy of Sciences.

Kuznetsova, A., Brockhoff, P.B., Christensen, R.H.B. (2017). lmerTest package: Tests in linear mixed effects models. Journal of Statistical Software, 82(13), 1–26. https://doi.org/10.18637/jss.v082.i13

Lange, M., Joly, F., Vardy, J., Ahles, T., Dubois, M., Tron, L., Winocur, G., De Ruiter, M.B., Castel, H. (2019). Cancer-related cognitive impairment: an update on state of the art, detection, and management strategies in cancer survivors. Annals of Oncology, 30(12), 1925–1940. https://doi.org/10.1093/annonc/mdz410

Li, G., Chen, Y., Le, T.M., Wang, W., Tang, X., Li, C.-S.R. (2021). Neural correlates of individual variation in two-back working memory and the relationship with fluid intelligence. Scientific Reports, 11, 9980. https://doi.org/10.1038/s41598-021-89433-8

Logie, R.H., Belletier, C., Doherty, J.M. (2020). Integrating theories of working memory. In: R.H. Logie, V. Camos, N. Cowan, (eds.). Working Memory: State of the science. (pp. 389–430). Oxford: Oxford University Press.

Lugtmeijer, S., Lammers, N.A., de Haan, E.H.F., de Leeuw, F.E., Kessels, R.P.C. (2021). Post-stroke working memory dysfunction: A meta-analysis and systematic review. Neuropsychology Review, 31(4), 202–219. https://doi.org/10.1007/s11065-020-09462-4

Ma, W.J., Husain, M., Bays, P.M. (2014). Changing concepts of working memory. Nature Neuroscience, 17, 347–356. https://doi.org/10.1038/nn.3655

Nasreddine, Z.S., Phillips, N.A., Bedirian, V., Charbonneau, S., Whitehead, V., Collin, I., Cummings, J.L., Chertkow, H. (2005). The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. Journal of the American Geriatrics Society, 53(4), 695–699. https://doi.org/10.1111/j.1532-5415.2005.53221.x

Naveh-Benjamin, M., Cowan, N. (2023). The roles of attention, executive function and knowledge in cognitive ageing of working memory. Nature Reviews Psychology, 2, 151–165. https://doi.org/10.1038/s44159-023-00149-0

Oldfield, R.C. (1971). The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia, 9(1), 97–113. https://doi.org/10.1016/0028-3932(71)90067-4

Owen, A.M., McMillan, K.M., Laird, A.R., Bullmore, E. (2005). N-back working memory paradigm: A meta-analysis of normative functional neuroimaging studies. Human Brain Mapping, 25, 46–59. https://doi.org/10.1002/hbm.20131

Peirce, J., Gray, J.R., Simpson, S., MacAskill, M., Höchenberger, R., Sogo, H., Kastman, E., Lindeløv, J.K. (2019). PsychoPy2: Experiments in behavior made easy. Behavior Research Methods, 51, 195–203. https://doi.org/10.3758/s13428-018-01193-y

Pillai, J.A., Bonner-Jackson, A., Walker, E., Mourany, L., Cummings, J.L. (2014). Higher working memory predicts slower functional decline in autopsy-confirmed Alzheimer’s disease. Dementia and Geriatric Cognitive Disorders, 38(3–4), 224–233. https://doi.org/10.1159/000362715

Posner, M.I., Boies, S.J., Eichelman, W.H., Taylor, R.L. (1969). Retention of visual and name codes of single letters. Journal of Experimental Psychology, 79(1), 1–16. https://doi.org/10.1037/h0026947

Raimo, S., Maggi, G., Ilardi, C.R., Cavallo, N.D., Torchia, V., Pilgrom, M.A., Cropano, M., Roldán-Tapia, M.D., Santangelo, G. (2024). The relation between cognitive functioning and activities of daily living in normal aging, mild cognitive impairment, and dementia: A meta-analysis. Neurological Science, 45(6), 2427–2443. https://doi.org/10.1007/s10072-024-07366-2

Reuter-Lorenz, P.A., Sylvester, C.-Y.C. (2005). The cognitive neuroscience of working memory and aging. In: R. Cabeza, L. Nyberg, D. Park, (eds.). Cognitive Neuroscience of Aging: Linking Cognitive and Cerebral Aging. (pp. 186–217). Oxford: Oxford University Press.

Sabahi, Z., Farhoudi, M., Naseri, A., Talebi, M. (2022). Working memory assessment using cambridge neuropsychological test automated battery can help in the diagnosis of mild cognitive impairment: A systematic review and meta-analysis. Dementia and Neuropsychologia, 16(4), 444–456. https://doi.org/10.1590/1980-5764-dn-2022-0006

Sternberg, S. (1966). High-speed scanning in human memory. Science, 153(3736), 652–654. https://doi.org/10.1126/science.153.3736.652

Tang, E.Y., Amiesimaka, O., Harrison, S.L., Green, E., Price, C., Robinson, L., Siervo, M., Stephan, B.C. (2018). Longitudinal effect of stroke on cognition: A systematic review. Journal of the American Heart Association, 7(2). https://doi.org/10.1161/JAHA.117.006443

Vidal, C., Content, A., Chetail, F. (2017). BACS: The Brussels Artificial Character Sets for studies in cognitive psychology and neuroscience. Behavior Research Methods, 49(6), 2093–2112. https://doi.org/10.3758/s13428-016-0844-8

To cite this article:

Panikratova, Y.R., Korolkova, O.A., Pchelintseva, M.E., Smirnova, A.V., Mening, S.M., Sinitsyn, V.E., Pechenkova, E.V.. Maintenance and Updating of Verbal and Nonverbal Material in Working Memory in Healthy Ageing. // National Psychological Journal 2026. 2. Pages144–158. doi: 10.11621/npj.2026.0211

Copied to Clipboard

Copy