Age- and Individual Specificity of Training Visual Short-term Spatial Memory



Cognitive training is known to increase the plasticity of the brain’s neural networks and reduce the expectation of cognitive dysfunction during aging. However, opinions differ regarding the age, individual and time range of the training efficiency. Thus, the aim of the work was to clearing the temporal dynamics of changes in the short-term visual spatial memory of older people in comparison with young people and the dependence on its baseline level. The study involved 65 people of retirement age (M = 65.8; SD = 7.5 years) (GR1) and 92 university students (M = 20.1; SD = 1.4 years) (GR2). To determine the spatial memory, we used a modified “Visual Patterns Test” technique posted on the website After a lecture on the methods of formation and implementation of cognitive resources, the study participants were asked to carry out memory training in a free mode at home in order to achieve a consistently maximum result. It is shown that by significantly lower values of short-term visual spatial memory in GR1 than in GR2 in the first testing session, to increase its efficiency, GR1 requires more than 80 sessions of training during some months, while GR2 requires 20 sessions during one-two weeks. The achievement of maximum memory indices occurs faster at its initially high values; however, the effect of training in the first sessions is more pronounced in persons with low memory values, regardless of age. It can be concluded that the effectiveness of spatial memory training at the initial stages is determined by the learning potential, and the realization of the compensatory resources of the brain, whereas the achievement of a result comparable to the young in the elderly is determined by the high level of executive control of behavior, which ensures long-term memory training.

General Information

Keywords: short-term visual spatial memory, cognitive training, age, temporal dynamics of memory, behavior control

Journal rubric: Cognitive Psychology

Article type: scientific article


Funding. The reported study was funded by Russian Foundation for Basic Research (RFBR), project No. 19-29-01017 and by Ministry of Science and Higher Education of Russian Federation, project No. FSUN-2020-0009.

Acknowledgements. The author is grateful to L.V. Belousova for assistance in forming the data file.

Received: 28.07.2020


For citation: Razumnikova O.M. Age- and Individual Specificity of Training Visual Short-term Spatial Memory. Eksperimental'naâ psihologiâ = Experimental Psychology (Russia), 2022. Vol. 15, no. 1, pp. 4–18. DOI: 10.17759/exppsy.2022150101. (In Russ., аbstr. in Engl.)


  1. Nutten J. Motivaziya, deistvie I perspektiva buduyuzhego. M.: Smysl, 2004. (In Russ.).
  2. Razumnikova O.M. Effects of aging brain and activation methods of its compensatory resources // Uspekhi fiziologicheskih nauk. 2015. Vol. 46. No. 2. P. 3—16 (In Russ.).
  3. Razumnikova O.M., Asanova N.V. Motivation inductors of behavior as reserves of successful aging // Advances in Gerontology. 2018. Vol. 31. No. 5. P. 737—742. (In Russ.).
  4. Razumnikova O.M., Asanova N.V. Relationship between inhibition control factors, successful training and health of students in the conditions of stress load of the educational process // Ekologiya cheloveka. 2019. No. 12. P. 46—52. DOI: 1033396/1728-0869-2019-12-46-52 (In Russ.).
  5. Acosta L.M., Goodman I.J., Heilman K.M. Unilateral perseveration // Cogn. Behav. Neurol. 2013. Vol. 26. № 4. P. 181—188.
  6. Beigneux K, Plaie T, Isingrini M. Aging effect on visual and spatial components of working memory // Int J Aging Hum Dev. 2007. Vol. 65. No. 4. P. 301—314. DOI:10.2190/AG.65.4.b
  7. Bissig D., Lustig C. Who benefits from memory training? Psychol Sci. 2007. Vol. 18. No. 8. P. 720—726. DOI:10.1111/j.1467-9280.2007.01966.x
  8. Borella E., Carretti B., Cantarella A., Riboldi F., Zavagnin M., DeBeni R. Benefits of training visuospatial working memory in young-old and old-old // Dev. Psychol. 2014. Vol. 50. P. 714—727. DOI: 10.1037/a0034293
  9. Brehmer Y., Westerberg H., Backman L. Working-memory training in younger and older adults: training gains, transfer, and maintenance // Front Hum Neurosci. 2012. No. 6. 63. DOI: 10.3389/fnhum.2012.00063
  10. Bråthen A.C.S., de Lange A-MG., Rohani D.A., Sneve M.H., Fjell A.M., Walhovd K.B. Multimodal cortical and hippocampal prediction of episodic-memory plasticity in young and older adults // Hum Brain MapP. 2018. Vol.39. No.11. P. 4480—4492. DOI:10.1002/hbm.24287
  11. Brooks J.O., Friedman L., Pearman A.M., Gray C., Yesavage J.A. Mnemonic training in older adults: Effects of age, length of training, and type of cognitive pretraining // Int Psychogeriatr. 1999. Vol. 11. No. 1. P. 75—84.
  12. Corbett A., Owen A., Hampshire A., et al. The effect of an online cognitive training package in healthy older adults: an online randomized controlled trial // J. Am. Med. Dir. Assoc. 2015. No. 16. P. 990—997.
  13. Craik F.I., Rose N.S. Memory encoding and aging: a neurocognitive perspective // Neurosci Biobehav Rev. 2012. Vol. 36. No. 7. P. 1729—1739. DOI:10.1016/j.neubiorev.2011.11.007
  14. de Lange A-M.G., Bråthen A.C.S., Rohani D.A., Grydeland H., Fjell A.M., Walhovd K.B. The effects of memory training on behavioral and microstructural plasticity in young and older adults // Hum Brain MapP. 2017. Vol. 38. No. 11. P. 5666—5680 DOI:10.1002/hbm.23756.
  15. Della Sala S, Gray C, Baddeley A, Allamano N, Wilson L. Pattern span: a tool for unwelding visuo-spatial memory // Neuropsychologia. 1999. Vol. 37. No. 10. P. 1189—1199. DOI:10.1016/s0028-3932(98)00159-6
  16. Fjell A.M., Walhovd K.B. Structural brain changes in aging: courses, causes and cognitive consequences // Rev. Neurosci. 2010. Vol. 21. P. 187—222. DOI:10.1515/REVNEURO.2010.21.3.187
  17. Franke K., Gaser C. Ten years of brain age as a neuroimaging biomarker of brain aging: What insights have we gained? // Front. Neurol. 2019. No 10. 789. DOI: 10.3389/fneur.2019.00789
  18. Fu L., Kessels Roy P.C., Maes Joseph H.R. The effect of cognitive training in older adults: be aware of CRUNCH // Aging, Neuropsychology, and Cognition. 2020. DOI: 10.1080/13825585.2019.1708251
  19. Green C. S., Strobach T., Schubert T. On methodological standards in training and transfer experiments // Psychological Research. 2014. Vol.78. P. 756—772. DOI: 10.1007/s00426-013-0535-3
  20. Greenwood P.M., Parasuraman R. Neuronal and cognitive plasticity: a neurocognitive framework for ameliorating cognitive aging // Front Aging Neurosci. 2010. No. 2. 150. DOI:10.3389/fnagi.2010.00150
  21. Goghari V.M., Krzyzanowski D., Yoon S., Dai Y., Toews D. Attitudes and beliefs toward computerized cognitive training in the general population // Front Psychol. 2020. No. 11. 503. DOI:10.3389/fpsyg.2020.00503
  22. Guye S., De Simoni C., von Bastian C. C. Do individual differences predict change in cognitive training performance? A latent growth curve modeling approach // Journal of Cognitive Enhancement. 2017. No. 1. P. 374—393. DOI:10.1007/s41465-017-0049-9
  23. Harvey P. D., McGurk S.R., Mahncke H., Wykes T. Controversies in computerized cognitive training // Biological Psychiatry: Cognitive Neuroscience and Neuroimaging. 2018. No. 3. P. 907—915.
  24. Hedden T., Schultz A.P. , Rieckmann A., Mormino E.C., Johnson K.A., Sperling R.A., Buckner R.L. Multiple brain markers are linked to age-related variation in cognition. Cereb Cortex. 2016. Vol. 26. P. 1388—1400.
  25. Jaeggi S.M., Buschkuehl M., Shah P. , Jonides J. The role of individual differences in cognitive training and transfer // Memory & Cognition. 2014. Vol. 42. P. 464—480. DOI:10.3758/s13421-013-0364-z
  26. Karbach J., Schubert T. Training-induced cognitive and neural plasticity // Front. Hum. Neurosci. 2013. No. 7. 48. DOI: 10.3389/fnhum.2013.00048
  27. Kelly M.E., Duff H., Kelly S. et al. The impact of social activities, social networks, social support and social relationships on the cognitive functioning of healthy older adults: a systematic review // Syst Rev. 2017. No. 6. 259. DOI: 10.1186/s13643-017-0632-2
  28. Klimova B. Computer-based cognitive training in aging // Front. Aging Neurosci. 2016. No. 8. 313. DOI: 10.3389/fnagi.2016.00313
  29. Kueider A.M., Parisi J.M., Gross A.L., Rebok G.W. Computerized cognitive training with older adults: A systematic review // PLoS ONE. 2012. Vol. 7. No.7. DOI:10.1371/journal.pone.0040588
  30. La Corte V., Sperduti M., Malherbe C., Vialatte F., Lion S., Gallarda T., Oppenheim C., Piolino P. Cognitive decline and reorganization of functional connectivity in healthy aging: The pivotal role of the salience network in the prediction of age and cognitive performances // Front. Aging Neurosci. 2016. No.8. 204. DOI: 10.3389/fnagi.2016.00204
  31. Lampit A., Hallock H., Valenzuela M. Computerized cognitive training in cognitively healthy older adults: a systematic review and meta- analysis of effect modifiers // PLoS Med. 2014. No. 11. e1001756. DOI: 10.1371/journal.pmed. 1001756
  32. Lee A.C., Yeung L.K., Barense M.D. The hippocampus and visual perception // Front Hum Neurosci. 2012. No. 6. 91. DOI:10.3389/fnhum.2012.00091
  33. Lövdén M., Brehmer Y., Li S-C., Lindenberger U. Training-induced compensation versus magnification of individual differences in memory performance. Front Hum Neurosci. 2012. No. 6. 141. DOI: 10.3389/fnhum.2012.00141
  34. Ludyga S., Gerber M., Puhse U., Looser V.N., Kamijo K. Systematic review and meta-analysis investigating moderators of long-term effects of exercise on cognition in healthy individuals // Nature Human Behaviour. 2020. No .4. P. 603—612. DOI:10.1038/s41562-020-0851-8
  35. Matysiak O., Kroemeke A., Brzezicka A. Working memory capacity as a predictor of cognitive training efficacy in the elderly population // Frontiers in Aging Neuroscience. 2019. No. 11. 126. DOI:10.3389/fnagi.2019.00126
  36. Melby-Lervåg M., Hulme C. Is working memory training effective? A meta-analytic review. Dev. Psychol. 2013. Vol. 49. P. 270—291. DOI: 10.1037/a002 8228
  37. Metzler-Baddeley C., Caeyenberghs K., Foley S., Jones D.K Task complexity, and location specific changes of cortical thickness in executive and salience networks after working memory training // Neuroimage. 2016. Vol.130. P. 48—62. DOI: 10.1016/j.neuroimage.2016.01.007
  38. Mitchell D.J., Cam-CAN (Cambridge Centre for Ageing and Neuroscience), Cusack R. Visual short-term memory through the lifespan: Preserved benefits of context and metacognition // Psychol Aging. 2018. Vol. 33. No. 5. P. 841—854. DOI:10.1037/pag0000265
  39. Mora F. Successful brain aging: plasticity, environmental enrichment, and lifestyle // Dialogues Clin Neurosci. 2013. Vol. 15. No. 1. P. 45—52.
  40. Olazarán J., Muñiz R., Reisberg B. et al. Benefits of cognitive-motor intervention in MCI and mild to moderate Alzheimer disease // Neurology. 2004. Vol. 63. No. 12. P. 2348—2353. DOI:10.1212/01.wnl.0000147478.03911.28
  41. Pertzov Y., Heider M., Liang Y., Husain M. Effects of healthy ageing on precision and binding of object location in visual short term memory // Psychol. Aging. 2015. Vol. 30. No. 1. P. 26—35. DOI:10.1037/a0038396
  42. Reuter-Lorenz P.A., Cappell K.A. Neurocognitive aging and the compensation hypothesis // Current Directions in Psychological Science. 2008. Vol. 17. No. 3. P. 177—182. DOI:10.1111/j.1467-8721.2008.00570.x
  43. Roheger M., Folkerts A-K., Krohm F., Skoetz N., Kalbe E. Prognostic factors for change in memory test performance after memory training in healthy older adults: a systematic review and outline of statistical challenges // Diagnostic and Prognostic Research. 2020. No. 4. 7. DOI:10.1186/s41512-020-0071-8
  44. Salthouse T.A. Decomposing age correlations on neuropsychological and cognitive variables // J Int Neuropsychol Soc. 2009. Vol. 15. P. 650—661.
  45. Thomas C., Baker C.I. Teaching an adult brain new tricks: A critical review of evidence for training dependent structural plasticity in humans // NeuroImage. 2013. No. 73. P. 225—236. DOI: 10.1016/j.neuroimage.2012.03.069
  46. Tsapanou A., Habeck C., Gazes Y., Razlighi Q., Sakhardande J., Stern Y., Salthouse T.A. Brain biomarkers and cognition across adulthood // Hum Brain MapP. 2019. Vol. 40. No. 13. P. 3832—3842. DOI:10.1002/hbm.24634
  47. Turunen M., Hokkanen L., Bäckman L., et al. Computer-based cognitive training for older adults: Determinants of adherence // PLoS ONE. 2019. Vol. 14. No. 7. e0219541. DOI: 10.1371/journal.pone.0219541
  48. Xuan B. From evaluation to prediction: Behavioral effects and biological markers of cognitive control intervention // Neural Plast. 2020. ID1869459. DOI:10.1155/2020/1869459
  49. Van Muijden J, Band GP, Hommel B Online games training aging brains: limited transfer to cognitive control functions // Front Hum Neurosci. 2012. No. 6. 221. DOI:10.3389/fnhum.2012.00221
  50. Van Petten C. Relationship between hippocampal volume and memory ability in healthy individuals across the lifespan: review and meta-analysis // Neuropsychologia. 2004. Vol. 42. P. 1394—1413.
  51. Wiegand I., Tollner T., Dyrholm M., Muller H.J., Bundesen C., Finke K. Neural correlates of age-related decline and compensation in visual attention capacity // Neurobiol. Aging. 2014. Vol.35. P. 2161—2173. 10.1016/j.neurobiolaging.2014.02.023
  52. Wolfson N.E., Kraiger K. Cognitive aging and training: the role of instructional coherence and advance organizers // ExP. Aging Res. 2014. Vol. 40. P. 164—186. DOI: 10.1080/0361073X.2014.882206
  53. Zammit A.R., Ezzati A., Katz M.J., Zimmerman M.E., Lipton M.L., Sliwinski M.J., Lipton R.B. The association of visual memory with hippocampal volume // PLoS One. 2017. Vol.12. No.11. e0187851. DOI: 10.1371/journal.pone.0187851
  54. Zinke K., Zeintl M., Rose N.S., Ptzmann J., Pydde A., Kliegel, M. Working memory training and transfer in older adults: effects of age, baseline performance, and training gains. Dev.Psychol. 2014. Vol. 50. P. 304—315. DOI: 10.1037/ a0032982

Information About the Authors

Olga M. Razumnikova, Doctor of Biology, Professor of the Department of Psychology and Pedagogic, Novosibirsk State Technical University, Novosibirsk, Russia, ORCID:, e-mail:



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