Table of Contents Author Guidelines Submit a Manuscript
Neural Plasticity
Volume 2015, Article ID 535618, 9 pages
http://dx.doi.org/10.1155/2015/535618
Research Article

Neural Plastic Effects of Cognitive Training on Aging Brain

1Laboratory of Neuropsychology, The University of Hong Kong, Hong Kong
2Laboratory of Social Cognitive Affective Neuroscience, The University of Hong Kong, Hong Kong
3Institute of Clinical Neuropsychology, The University of Hong Kong, Hong Kong
4Department of Medicine, The University of Hong Kong, Hong Kong
5Alzheimer’s Disease Research Network, The University of Hong Kong, Hong Kong
6Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong
7Fung Yiu King Hospital, Hong Kong
8Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong
9State Key Laboratory of Brain and Cognitive Science, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong

Received 1 December 2014; Revised 4 March 2015; Accepted 11 March 2015

Academic Editor: Ching P. Lin

Copyright © 2015 Natalie T. Y. Leung et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. A. May, “Experience-dependent structural plasticity in the adult human brain,” Trends in Cognitive Sciences, vol. 15, no. 10, pp. 475–482, 2011. View at Publisher · View at Google Scholar · View at Scopus
  2. B. Draganski, C. Gaser, V. Busch, G. Schuierer, U. Bogdahn, and A. May, “Neuroplasticity: changes in grey matter induced by training,” Nature, vol. 427, no. 6972, pp. 311–312, 2004. View at Publisher · View at Google Scholar · View at Scopus
  3. E. A. Maguire, D. G. Gadian, I. S. Johnsrude et al., “Navigation-related structural change in the hippocampi of taxi drivers,” Proceedings of the National Academy of Sciences of the United States of America, vol. 97, no. 8, pp. 4398–4403, 2000. View at Publisher · View at Google Scholar · View at Scopus
  4. T. F. Munte, E. Altenmuller, and L. Jancke, “The musician’s brain as a model of neuroplasticity,” Nature Reviews Neuroscience, vol. 3, pp. 473–478, 2002. View at Google Scholar
  5. J. Scholz, M. C. Klein, T. E. J. Behrens, and H. Johansen-Berg, “Training induces changes in white-matter architecture,” Nature Neuroscience, vol. 12, no. 11, pp. 1370–1371, 2009. View at Publisher · View at Google Scholar · View at Scopus
  6. T. M. C. Lee, M. K. Leung, W.-K. Hou et al., “Distinct neural activity associated with focused-attention meditation and loving-kindness meditation,” PLoS ONE, vol. 7, no. 8, Article ID e40054, 2012. View at Publisher · View at Google Scholar · View at Scopus
  7. M.-K. Leung, C. C. H. Chan, J. Yin, C.-F. Lee, K.-F. So, and T. M. C. Lee, “Increased gray matter volume in the right angular and posterior parahippocampal gyri in loving-kindness meditators,” Social Cognitive and Affective Neuroscience, vol. 8, no. 1, pp. 34–39, 2013. View at Publisher · View at Google Scholar · View at Scopus
  8. A. Lutz, H. A. Slagter, J. D. Dunne, and R. J. Davidson, “Attention regulation and monitoring in meditation,” Trends in Cognitive Sciences, vol. 12, no. 4, pp. 163–169, 2008. View at Publisher · View at Google Scholar · View at Scopus
  9. A. Lutz, J. Brefczynski-Lewis, T. Johnstone, and R. J. Davidson, “Regulation of the neural circuitry of emotion by compassion meditation: effects of meditative expertise,” PLoS ONE, vol. 3, no. 3, Article ID e1897, 2008. View at Publisher · View at Google Scholar · View at Scopus
  10. T. Hedden and J. D. E. Gabrieli, “Insights into the ageing mind: a view from cognitive neuroscience,” Nature Reviews Neuroscience, vol. 5, no. 2, pp. 87–96, 2004. View at Google Scholar · View at Scopus
  11. S. M. Resnick, D. L. Pham, M. A. Kraut, A. B. Zonderman, and C. Davatzikos, “Longitudinal magnetic resonance imaging studies of older adults: a shrinking brain,” The Journal of Neuroscience, vol. 23, no. 8, pp. 3295–3301, 2003. View at Google Scholar · View at Scopus
  12. D. H. Salat, R. L. Buckner, A. Z. Snyder et al., “Thinning of the cerebral cortex in aging,” Cerebral Cortex, vol. 14, no. 7, pp. 721–730, 2004. View at Publisher · View at Google Scholar · View at Scopus
  13. E. R. Sowell, B. S. Peterson, P. M. Thompson, S. E. Welcome, A. L. Henkenius, and A. W. Toga, “Mapping cortical change across the human life span,” Nature Neuroscience, vol. 6, no. 3, pp. 309–315, 2003. View at Publisher · View at Google Scholar · View at Scopus
  14. J. S. Damoiseaux, C. F. Beckmann, E. J. S. Arigita et al., “Reduced resting-state brain activity in the ‘default network’ in normal aging,” Cerebral Cortex, vol. 18, no. 8, pp. 1856–1864, 2008. View at Publisher · View at Google Scholar · View at Scopus
  15. F. Sambataro, V. P. Murty, J. H. Callicott et al., “Age-related alterations in default mode network: impact on working memory performance,” Neurobiology of Aging, vol. 31, no. 5, pp. 839–852, 2010. View at Publisher · View at Google Scholar · View at Scopus
  16. D. J. Madden, “Aging and visual attention,” Current Directions in Psychological Science, vol. 16, no. 2, pp. 70–74, 2007. View at Publisher · View at Google Scholar · View at Scopus
  17. L. Jenkins, J. Myerson, J. A. Joerding, and S. Hale, “Converging evidence that visuospatial cognition is more age-sensitive than verbal cognition,” Psychology and Aging, vol. 15, no. 1, pp. 157–175, 2000. View at Publisher · View at Google Scholar · View at Scopus
  18. E. Borella, B. Carretti, and R. de Beni, “Working memory and inhibition across the adult life-span,” Acta Psychologica, vol. 128, no. 1, pp. 33–44, 2008. View at Publisher · View at Google Scholar · View at Scopus
  19. K. L. Campbell, C. L. Grady, C. Ng, and L. Hasher, “Age differences in the frontoparietal cognitive control network: implications for distractibility,” Neuropsychologia, vol. 50, no. 9, pp. 2212–2223, 2012. View at Publisher · View at Google Scholar · View at Scopus
  20. L. Geerligs, E. Saliasi, N. M. Maurits, R. J. Renken, and M. M. Lorist, “Brain mechanisms underlying the effects of aging on different aspects of selective attention,” NeuroImage, vol. 91, pp. 52–62, 2014. View at Publisher · View at Google Scholar · View at Scopus
  21. T. M. Mani, J. S. Bedwell, and L. S. Miller, “Age-related decrements in performance on a brief continuous performance test,” Archives of Clinical Neuropsychology, vol. 20, no. 5, pp. 575–586, 2005. View at Publisher · View at Google Scholar · View at Scopus
  22. D. J. Madden, J. Spaniol, W. L. Whiting et al., “Adult age differences in the functional neuroanatomy of visual attention: a combined fMRI and DTI study,” Neurobiology of Aging, vol. 28, no. 3, pp. 459–476, 2007. View at Publisher · View at Google Scholar · View at Scopus
  23. V. S. Mattay, F. Fera, A. Tessitore et al., “Neurophysiological correlates of age-related changes in working memory capacity,” Neuroscience Letters, vol. 392, no. 1-2, pp. 32–37, 2006. View at Publisher · View at Google Scholar · View at Scopus
  24. L. G. Nilsson, “Memory function in normal aging,” Acta Neurologica Scandinavica, Supplement, vol. 107, no. 179, pp. 7–13, 2003. View at Google Scholar · View at Scopus
  25. L. Nyberg, S. B. Maitland, M. Rönnlund et al., “Selective adult age differences in an age-invariant multifactor model of declarative memory,” Psychology and Aging, vol. 18, no. 1, pp. 149–160, 2003. View at Publisher · View at Google Scholar · View at Scopus
  26. J. Persson, S. Pudas, J. Lind, K. Kauppi, L.-G. Nilsson, and L. Nyberg, “Longitudinal structure-function correlates in elderly reveal MTL dysfunction with cognitive decline,” Cerebral Cortex, vol. 22, no. 10, pp. 2297–2304, 2012. View at Publisher · View at Google Scholar · View at Scopus
  27. K. I. Erickson, S. J. Colcombe, R. Wadhwa et al., “Training-induced plasticity in older adults: Effects of training on hemispheric asymmetry,” Neurobiology of Aging, vol. 28, no. 2, pp. 272–283, 2007. View at Publisher · View at Google Scholar · View at Scopus
  28. R. Cabeza, “Hemispheric asymmetry reduction in older adults: the HAROLD model,” Psychology and Aging, vol. 17, no. 1, pp. 85–100, 2002. View at Publisher · View at Google Scholar · View at Scopus
  29. R. Cabeza, N. D. Anderson, J. K. Locantore, and A. R. McIntosh, “Aging gracefully: compensatory brain activity in high-performing older adults,” NeuroImage, vol. 17, no. 3, pp. 1394–1402, 2002. View at Publisher · View at Google Scholar · View at Scopus
  30. J. Boyke, J. Driemeyer, C. Gaser, C. Büchel, and A. May, “Training-induced brain structure changes in the elderly,” The Journal of Neuroscience, vol. 28, no. 28, pp. 7031–7035, 2008. View at Publisher · View at Google Scholar · View at Scopus
  31. S. J. Colcombe, K. I. Erickson, P. E. Scalf et al., “Aerobic exercise training increases brain volume in aging humans,” Journals of Gerontology—Series A Biological Sciences and Medical Sciences, vol. 61, no. 11, pp. 1166–1170, 2006. View at Publisher · View at Google Scholar · View at Scopus
  32. M. Buschkuehl, S. M. Jaeggi, S. Hutchison et al., “Impact of working memory training on memory performance in old-old adults,” Psychology and Aging, vol. 23, no. 4, pp. 743–753, 2008. View at Publisher · View at Google Scholar · View at Scopus
  33. H. W. Mahncke, B. B. Connor, J. Appelman et al., “Memory enhancement in healthy older adults using a brain plasticity-based training program: a randomized, controlled study,” Proceedings of the National Academy of Sciences of the United States of America, vol. 103, no. 33, pp. 12523–12528, 2006. View at Publisher · View at Google Scholar · View at Scopus
  34. H. Takeuchi, A. Sekiguchi, Y. Taki et al., “Training of working memory impacts structural connectivity,” The Journal of Neuroscience, vol. 30, no. 9, pp. 3297–3303, 2010. View at Publisher · View at Google Scholar · View at Scopus
  35. J. L. Mozolic, A. B. Long, A. R. Morgan, M. Rawley-Payne, and P. J. Laurienti, “A cognitive training intervention improves modality-specific attention in a randomized controlled trial of healthy older adults,” Neurobiology of Aging, vol. 32, no. 4, pp. 655–668, 2011. View at Publisher · View at Google Scholar · View at Scopus
  36. G. E. Smith, P. Housen, K. Yaffe et al., “A cognitive training program based on principles of brain plasticity: results from the improvement in memory with plasticity-based adaptive cognitive training (IMPACT) study,” Journal of the American Geriatrics Society, vol. 57, no. 4, pp. 594–603, 2009. View at Publisher · View at Google Scholar · View at Scopus
  37. D. E. Barnes, K. Yaffe, N. Belfor et al., “Computer-based cognitive training for mild cognitive impairment: results from a pilot randomized, controlled trial,” Alzheimer Disease and Associated Disorders, vol. 23, no. 3, pp. 205–210, 2009. View at Publisher · View at Google Scholar · View at Scopus
  38. A. C. Rosen, L. Sugiura, J. H. Kramer, S. Whitfield-Gabrieli, and J. D. Gabrieli, “Cognitive training changes hippocampal function in mild cognitive impairment: a Pilot Study,” Journal of Alzheimer's Disease, vol. 26, no. 3, pp. 349–357, 2011. View at Publisher · View at Google Scholar · View at Scopus
  39. S. Gauthier, B. Reisberg, M. Zaudig et al., “Mild cognitive impairment,” The Lancet, vol. 367, no. 9518, pp. 1262–1270, 2006. View at Publisher · View at Google Scholar · View at Scopus
  40. R. C. Petersen, “Mild cognitive impairment,” The New England Journal of Medicine, vol. 364, no. 23, pp. 2227–2234, 2011. View at Publisher · View at Google Scholar · View at Scopus
  41. Z. S. Nasreddine, N. A. Phillips, V. Bédirian et al., “The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment,” Journal of the American Geriatrics Society, vol. 53, no. 4, pp. 695–699, 2005. View at Publisher · View at Google Scholar · View at Scopus
  42. C. B. Dodrill and N. S. Thoreson, “Reliability of the lateral dominance examination,” Journal of Clinical and Experimental Neuropsychology, vol. 15, no. 2, pp. 183–190, 1993. View at Publisher · View at Google Scholar · View at Scopus
  43. L. Brown, R. J. Sherbenou, and S. K. Johnsen, Test of Nonverbal Intelligence, PRO-ED, Austin, Tex, USA, 3rd edition, 1997.
  44. R. P. Snaith and A. S. Zigmond, HADS: Hospital Anxiety and Depression Scale, NFER Nelson, Windsor, Canada, 1994.
  45. T. A. Salthouse, “The processing-speed theory of adult age differences in cognition,” Psychological Review, vol. 103, no. 3, pp. 403–428, 1996. View at Publisher · View at Google Scholar · View at Scopus
  46. A. Ardila, F. Ostrosky-Solis, M. Rosselli, and C. Gómez, “Age-related cognitive decline during normal aging: the complex effect of education,” Archives of Clinical Neuropsychology, vol. 15, no. 6, pp. 495–513, 2000. View at Publisher · View at Google Scholar · View at Scopus
  47. P. J. Modrego and J. Ferrández, “Depression in patients with mild cognitive impairment increases the risk of developing dementia of Alzheimer type: a prospective cohort study,” Archives of Neurology, vol. 61, no. 8, pp. 1290–1293, 2004. View at Publisher · View at Google Scholar · View at Scopus
  48. H. M. K. Tam, C. L. M. Lam, H. Huang, B. Wang, and T. M. C. Lee, “Age-related difference in relationships between cognitive processing speed and general cognitive status,” Applied Neuropsychology: Adult, vol. 22, no. 2, pp. 94–99, 2015. View at Publisher · View at Google Scholar
  49. J. A. Kleim and T. A. Jones, “Principles of experience-dependent neural plasticity: implications for rehabilitation after brain damage,” Journal of Speech, Language, and Hearing Research, vol. 51, no. 1, pp. S225–S239, 2008. View at Publisher · View at Google Scholar · View at Scopus
  50. K. Ball, D. B. Berch, K. F. Helmers et al., “Effects of cognitive training interventions with older adults: a randomized controlled trial,” Journal of the American Medical Association, vol. 288, no. 18, pp. 2271–2281, 2002. View at Publisher · View at Google Scholar · View at Scopus
  51. J. B. Pitcher, K. M. Ogston, and T. S. Miles, “Age and sex differences in human motor cortex input-output characteristics,” The Journal of Physiology, vol. 546, no. 2, pp. 605–613, 2003. View at Publisher · View at Google Scholar · View at Scopus
  52. S. L. Willis, S. L. Tennstedt, M. Marsiske et al., “Long-term effects of cognitive training on everyday functional outcomes in older adults,” Journal of the American Medical Association, vol. 296, no. 23, pp. 2805–2814, 2006. View at Publisher · View at Google Scholar · View at Scopus
  53. J. A. Anguera, J. Boccanfuso, J. L. Rintoul et al., “Video game training enhances cognitive control in older adults,” Nature, vol. 501, no. 7465, pp. 97–101, 2013. View at Publisher · View at Google Scholar · View at Scopus
  54. T. C. Y. Kwok, X. Bai, J. C. Y. Li, F. K. Y. Ho, and T. M. C. Lee, “Effectiveness of cognitive training in Chinese older people with subjective cognitive complaints: a randomized placebo-controlled trial,” International Journal of Geriatric Psychiatry, vol. 28, no. 2, pp. 208–215, 2013. View at Publisher · View at Google Scholar · View at Scopus