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Behavioural Neurology
Volume 2015, Article ID 525901, 18 pages
http://dx.doi.org/10.1155/2015/525901
Research Article

Effects of Different Types of Cognitive Training on Cognitive Function, Brain Structure, and Driving Safety in Senior Daily Drivers: A Pilot Study

1Smart Ageing International Research Center, Institute of Development, Aging and Cancer, Tohoku University, Sendai 980-8575, Japan
2Division of Developmental Cognitive Neuroscience, Institute of Development, Aging and Cancer, Tohoku University, Sendai 980-8575, Japan
3Division of Medical Neuroimage Analysis, Department of Community Medical Supports, Tohoku Medical Megabank Organization, Tohoku University, Sendai 980-8575, Japan
4Department of Functional Brain Imaging, Institute of Development, Aging and Cancer, Tohoku University, Sendai 980-8575, Japan
5Japan Society for the Promotion of Science, Tokyo 102-8472, Japan
6Research Division 2, Mobility Services Laboratory, Nissan Motor Co., Ltd., Kanagawa 243-0123, Japan
7CAE and Testing Division 1, Vehicle Test and Measurement Technology Development, Nissan Motor Co., Ltd., Kanagawa 243-0192, Japan
8Research Division 2, Prototype and Test Department, Nissan Motor Co., Ltd., Kanagawa 243-0123, Japan

Received 11 November 2014; Accepted 21 February 2015

Academic Editor: Laura Piccardi

Copyright © 2015 Takayuki Nozawa 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. J. Oxley, J. Langford, and J. Charlton, “The safe mobility of older drivers: a challenge for urban road designers,” Journal of Transport Geography, vol. 18, no. 5, pp. 642–648, 2010. View at Publisher · View at Google Scholar · View at Scopus
  2. K. Inoue, T. Fukunaga, Y. Okazaki, and Y. Fujita, “Detailed discussion on evidence for the further prevention of traffic fatalities in Japan: a comparison of trends in three countries,” Medicine, Science and the Law, vol. 52, no. 2, pp. 93–95, 2012. View at Publisher · View at Google Scholar · View at Scopus
  3. J. Oxley and M. Whelan, “It cannot be all about safety: the benefits of prolonged mobility,” Traffic Injury Prevention, vol. 9, no. 4, pp. 367–378, 2008. View at Publisher · View at Google Scholar · View at Scopus
  4. K. J. Anstey, J. Wood, S. Lord, and J. G. Walker, “Cognitive, sensory and physical factors enabling driving safety in older adults,” Clinical Psychology Review, vol. 25, no. 1, pp. 45–65, 2005. View at Publisher · View at Google Scholar · View at Scopus
  5. J. D. Dawson, S. W. Anderson, E. Y. Uc, E. Dastrup, and M. Rizzo, “Predictors of driving safety in early Alzheimer disease,” Neurology, vol. 72, no. 6, pp. 521–527, 2009. View at Publisher · View at Google Scholar · View at Scopus
  6. E. D. Richardson and R. A. Marottoli, “Visual attention and driving behaviors among community-living older persons,” Journals of Gerontology Series A: Biological Sciences and Medical Sciences, vol. 58, no. 9, pp. M832–M836, 2003. View at Publisher · View at Google Scholar · View at Scopus
  7. M. Bédard, B. Weaver, P. Darzinš, and M. M. Porter, “Predicting driving performance in older adults: we are not there yet!,” Traffic Injury Prevention, vol. 9, no. 4, pp. 336–341, 2008. View at Publisher · View at Google Scholar · View at Scopus
  8. K. Ball, J. D. Edwards, and L. A. Ross, “The impact of speed of processing training on cognitive and everyday functions,” Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, vol. 62, no. 1, pp. 19–31, 2007. View at Publisher · View at Google Scholar · View at Scopus
  9. J. D. Edwards, P. B. Delahunt, and H. W. Mahncke, “Cognitive speed of processing training delays driving cessation,” Journals of Gerontology Series A: Biological Sciences and Medical Sciences, vol. 64, no. 12, pp. 1262–1267, 2009. View at Publisher · View at Google Scholar · View at Scopus
  10. J. D. Edwards, C. Myers, L. A. Ross et al., “The longitudinal impact of cognitive speed of processing training on driving mobility,” Gerontologist, vol. 49, no. 4, pp. 485–494, 2009. View at Publisher · View at Google Scholar · View at Scopus
  11. D. L. Roenker, G. M. Cissell, K. K. Ball, V. G. Wadley, and J. D. Edwards, “Speed-of-processing and driving simulator training result in improved driving performance,” Human Factors, vol. 45, no. 2, pp. 218–233, 2003. View at Publisher · View at Google Scholar · View at Scopus
  12. M. R. E. Romoser and D. L. Fisher, “The effect of active versus passive training strategies on improving older drivers' scanning in intersections,” Human Factors, vol. 51, no. 5, pp. 652–668, 2009. View at Publisher · View at Google Scholar · View at Scopus
  13. N. D. Cassavaugh and A. F. Kramer, “Transfer of computer-based training to simulated driving in older adults,” Applied Ergonomics, vol. 40, no. 5, pp. 943–952, 2009. View at Publisher · View at Google Scholar · View at Scopus
  14. D. Wolf, F. U. Fischer, J. Fesenbeckh et al., “Structural integrity of the corpus callosum predicts long-term transfer of fluid intelligence-related training gains in normal aging,” Human Brain Mapping, vol. 35, no. 1, pp. 309–318, 2014. View at Publisher · View at Google Scholar · View at Scopus
  15. A. Engvig, A. M. Fjell, L. T. Westlye et al., “Memory training impacts short-term changes in aging white matter: a longitudinal diffusion tensor imaging study,” Human Brain Mapping, vol. 33, no. 10, pp. 2390–2406, 2012. View at Publisher · View at Google Scholar · View at Scopus
  16. K. I. Erickson, M. W. Voss, R. S. Prakash et al., “Exercise training increases size of hippocampus and improves memory,” Proceedings of the National Academy of Sciences of the United States of America, vol. 108, no. 7, pp. 3017–3022, 2011. View at Publisher · View at Google Scholar · View at Scopus
  17. A. Engvig, A. M. Fjell, L. T. Westlye et al., “Effects of memory training on cortical thickness in the elderly,” NeuroImage, vol. 52, no. 4, pp. 1667–1676, 2010. View at Publisher · View at Google Scholar · View at Scopus
  18. 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
  19. 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
  20. V. Pieramico, R. Esposito, F. Sensi et al., “Combination training in aging individuals modifies functional connectivity and cognition, and is potentially affected by dopamine-related genes,” PLoS ONE, vol. 7, no. 8, Article ID e43901, 2012. View at Publisher · View at Google Scholar · View at Scopus
  21. J. L. Mozolic, S. Hayasaka, and P. J. Laurienti, “A cognitive training intervention increases resting cerebral blood flow in healthy older adults,” Frontiers in Human Neuroscience, vol. 4, article 16, 2010. View at Publisher · View at Google Scholar · View at Scopus
  22. C. Owsley, K. Ball, G. McGwin Jr. et al., “Visual processing impairment and risk of motor vehicle crash among older adults,” The Journal of the American Medical Association, vol. 279, no. 14, pp. 1083–1088, 1998. View at Publisher · View at Google Scholar · View at Scopus
  23. J. Verghese, A. LeValley, C. Derby et al., “Leisure activities and the risk of amnestic mild cognitive impairment in the elderly,” Neurology, vol. 66, no. 6, pp. 821–827, 2006. View at Publisher · View at Google Scholar · View at Scopus
  24. L. J. Tranter and W. Koutstaal, “Age and flexible thinking: an experimental demonstration of the beneficial effects of increased cognitively stimulating activity on fluid intelligence in healthy older adults,” Neuropsychology, Development, and Cognition, Section B: Aging and Cognition, vol. 15, no. 2, pp. 184–207, 2008. View at Publisher · View at Google Scholar · View at Scopus
  25. T. N. Akbaraly, F. Portet, S. Fustinoni et al., “Leisure activities and the risk of dementia in the elderly: results from the three-city study,” Neurology, vol. 73, no. 11, pp. 854–861, 2009. View at Publisher · View at Google Scholar · View at Scopus
  26. J. Verghese, R. B. Lipton, M. J. Katz et al., “Leisure activities and the risk of dementia in the elderly,” The New England Journal of Medicine, vol. 348, no. 25, pp. 2508–2516, 2003. View at Publisher · View at Google Scholar · View at Scopus
  27. D. Z. Hambrick, T. A. Salthouse, and E. J. Meinz, “Predictors of crossword puzzle proficiency and moderators of age-cognition relations,” Journal of Experimental Psychology: General, vol. 128, no. 2, pp. 131–164, 1999. View at Publisher · View at Google Scholar · View at Scopus
  28. T. A. Salthouse, “Mental exercise and mental aging—evaluating the validity of the ‘use it or lose it’ hypothesis,” Perspectives on Psychological Science, vol. 1, no. 1, pp. 68–87, 2006. View at Publisher · View at Google Scholar
  29. C. Schooler, “Use it—and keep it, longer, probably: a reply to salthouse,” Perspectives on Psychological Science, vol. 2, no. 1, pp. 24–29, 2007. View at Publisher · View at Google Scholar
  30. R. G. Burciu, N. Fritsche, O. Granert et al., “Brain changes associated with postural training in patients with cerebellar degeneration: a voxel-based morphometry study,” Journal of Neuroscience, vol. 33, no. 10, pp. 4594–4604, 2013. View at Publisher · View at Google Scholar · View at Scopus
  31. H. Takeuchi, Y. Taki, Y. Sassa et al., “Working memory training using mental calculation impacts regional gray matter of the frontal and parietal regions,” PLoS ONE, vol. 6, no. 8, Article ID e23175, 2011. View at Publisher · View at Google Scholar · View at Scopus
  32. L. Bezzola, S. Mérillat, C. Gaser, and L. Jäncke, “Training-induced neural plasticity in golf novices,” Journal of Neuroscience, vol. 31, no. 35, pp. 12444–12448, 2011. View at Publisher · View at Google Scholar · View at Scopus
  33. H. Takeuchi, Y. Taki, H. Hashizume et al., “Effects of training of processing speed on neural systems,” Journal of Neuroscience, vol. 31, no. 34, pp. 12139–12148, 2011. View at Publisher · View at Google Scholar · View at Scopus
  34. 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
  35. B. Lee, J.-Y. Park, W. H. Jung et al., “White matter neuroplastic changes in long-term trained players of the game of ‘Baduk’ (GO): a voxel-based diffusion-tensor imaging study,” NeuroImage, vol. 52, no. 1, pp. 9–19, 2010. View at Publisher · View at Google Scholar · View at Scopus
  36. M. Lövdén, N. C. Bodammer, S. Kühn et al., “Experience-dependent plasticity of white-matter microstructure extends into old age,” Neuropsychologia, vol. 48, no. 13, pp. 3878–3883, 2010. View at Publisher · View at Google Scholar · View at Scopus
  37. D. A. Ziegler, O. Piguet, D. H. Salat, K. Prince, E. Connally, and S. Corkin, “Cognition in healthy aging is related to regional white matter integrity, but not cortical thickness,” Neurobiology of Aging, vol. 31, no. 11, pp. 1912–1926, 2010. View at Publisher · View at Google Scholar · View at Scopus
  38. H. Takeuchi, A. Sekiguchi, Y. Taki et al., “Training of working memory impacts structural connectivity,” Journal of Neuroscience, vol. 30, no. 9, pp. 3297–3303, 2010. View at Publisher · View at Google Scholar · View at Scopus
  39. S. M. Smith, M. Jenkinson, H. Johansen-Berg et al., “Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data,” NeuroImage, vol. 31, no. 4, pp. 1487–1505, 2006. View at Publisher · View at Google Scholar · View at Scopus
  40. M. F. Folstein, S. E. Folstein, and P. R. McHugh, “‘Mini-mental state’. A practical method for grading the cognitive state of patients for the clinician,” Journal of Psychiatric Research, vol. 12, pp. 189–198, 1975. View at Google Scholar
  41. S. Classen, Y. Wang, A. M. Crizzle, S. M. Winter, and D. N. Lanford, “Gender differences among older drivers in a comprehensive driving evaluation,” Accident Analysis and Prevention, vol. 61, pp. 146–152, 2013. View at Publisher · View at Google Scholar · View at Scopus
  42. D. Moher, S. Hopewell, K. F. Schulz et al., “CONSORT 2010 explanation and elaboration: updated guidelines for reporting parallel group randomised trials,” International Journal of Surgery, vol. 10, no. 1, pp. 28–55, 2012. View at Publisher · View at Google Scholar · View at Scopus
  43. D. Wechsler, Wechsler Adult Intelligence Scale, The Psychological Corporation, San Antonio, Tex, USA, 3rd edition, 1997.
  44. B. Dubois, A. Slachevsky, I. Litvan, and B. Pillon, “The FAB: a frontal assessment battery at bedside,” Neurology, vol. 55, no. 11, pp. 1621–1626, 2000. View at Publisher · View at Google Scholar · View at Scopus
  45. M. Lezak, Neuropsychological Assessment, Oxford University Press, New York, NY, USA, 3rd edition, 1995.
  46. R. M. Reitan, “Validity of the trail making test as an indicator of organic brain damage,” Perceptual and Motor Skills, vol. 8, article 271, 1958. View at Google Scholar
  47. A. Smith, Symbol Digit Modalities Test Manual—Revised, Western Psychological Corporation, Los Angeles, Calif, USA, 1984.
  48. D. Wechsler, Wechsler Memory Scale, The Psychological Corporation, San Antonio, Tex, USA, 1987.
  49. A. Benton, The Revised Visual Retention Test: Clinical and Experimental Applications, The State University of Iowa, 1963.
  50. M.-S. Shin, S.-Y. Park, S.-R. Park, S.-H. Seol, and J. S. Kwon, “Clinical and empirical applications of the Rey-Osterrieth complex figure test,” Nature Protocols, vol. 1, no. 2, pp. 892–899, 2006. View at Publisher · View at Google Scholar · View at Scopus
  51. M. Schmidt, Rey Auditory Verbal Learning Test: RAVLT: A Handbook, Western Psychological Services, 1996.
  52. A. Benton, K. Hamsher, N. Varney, and O. Spreen, Judgement of Line Orientation, Oxford University Press, New York, NY, USA, 1983.
  53. M. Rizzo, D. V. McGehee, J. D. Dawson, and S. N. Anderson, “Simulated car crashes at intersections in drivers with Alzheimer disease,” Alzheimer Disease and Associated Disorders, vol. 15, no. 1, pp. 10–20, 2001. View at Publisher · View at Google Scholar · View at Scopus
  54. F. Schmiedek, M. Lövdén, and U. Lindenberger, “Hundred days of cognitive training enhance broad cognitive abilities in adulthood: findings from the COGITO study,” Frontiers in Aging Neuroscience, vol. 2, article 27, 2010. View at Publisher · View at Google Scholar · View at Scopus
  55. E. Y. Uc, M. Rizzo, S. W. Anderson, Q. Shi, and J. D. Dawson, “Driver landmark and traffic sign identification in early Alzheimer's disease,” Journal of Neurology, Neurosurgery and Psychiatry, vol. 76, no. 6, pp. 764–768, 2005. View at Publisher · View at Google Scholar · View at Scopus
  56. Y. Benjamini and Y. Hochberg, “Controlling the false discovery rate: a practical and powerful approach to multiple testing,” Journal of the Royal Statistical Society. Series B. Methodological, vol. 57, no. 1, pp. 289–300, 1995. View at Google Scholar · View at MathSciNet
  57. J. Ashburner, “A fast diffeomorphic image registration algorithm,” NeuroImage, vol. 38, no. 1, pp. 95–113, 2007. View at Publisher · View at Google Scholar · View at Scopus
  58. C. D. Good, I. S. Johnsrude, J. Ashburner, R. N. A. Henson, K. J. Friston, and R. S. J. Frackowiak, “A voxel-based morphometric study of ageing in 465 normal adult human brains,” NeuroImage, vol. 14, no. 1 I, pp. 21–36, 2001. View at Publisher · View at Google Scholar · View at Scopus
  59. S. Hayasaka, K. L. Phan, I. Liberzon, K. J. Worsley, and T. E. Nichols, “Nonstationary cluster-size inference with random field and permutation methods,” NeuroImage, vol. 22, no. 2, pp. 676–687, 2004. View at Publisher · View at Google Scholar · View at Scopus
  60. T. E. Nichols and A. P. Holmes, “Nonparametric permutation tests for functional neuroimaging: a primer with examples,” Human Brain Mapping, vol. 15, no. 1, pp. 1–25, 2002. View at Publisher · View at Google Scholar · View at Scopus
  61. S. M. Smith and T. E. Nichols, “Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference,” NeuroImage, vol. 44, no. 1, pp. 83–98, 2009. View at Publisher · View at Google Scholar · View at Scopus
  62. Takei Scientific Instruments, The instruction manual of cg400 driving aptitude test unit, September 2011 (Japanese).
  63. The Traffic Division of the Scientific Police Institute, National Police Agency System Guidelines, 1989 (Japanese).
  64. K. I. Erickson and A. F. Kramer, “Aerobic exercise effects on cognitive and neural plasticity in older adults,” British Journal of Sports Medicine, vol. 43, no. 1, pp. 22–24, 2009. View at Publisher · View at Google Scholar · View at Scopus
  65. E. J. A. Scherder, J. van Paasschen, J.-B. Deijen et al., “Physical activity and executive functions in the elderly with mild cognitive impairment,” Aging and Mental Health, vol. 9, no. 3, pp. 272–280, 2005. View at Publisher · View at Google Scholar · View at Scopus
  66. M. L. Kringelbach, “The human orbitofrontal cortex: linking reward to hedonic experience,” Nature Reviews Neuroscience, vol. 6, no. 9, pp. 691–702, 2005. View at Publisher · View at Google Scholar · View at Scopus
  67. K. Matsuo, M. Nicoletti, K. Nemoto et al., “A voxel-based morphometry study of frontal gray matter correlates of impulsivity,” Human Brain Mapping, vol. 30, no. 4, pp. 1188–1195, 2009. View at Publisher · View at Google Scholar · View at Scopus
  68. M. W. L. Chee, K. H. M. Chen, H. Zheng et al., “Cognitive function and brain structure correlations in healthy elderly East Asians,” NeuroImage, vol. 46, no. 1, pp. 257–269, 2009. View at Publisher · View at Google Scholar · View at Scopus
  69. M. Corbetta, G. Patel, and G. L. Shulman, “The reorienting system of the human brain: from environment to theory of mind,” Neuron, vol. 58, no. 3, pp. 306–324, 2008. View at Publisher · View at Google Scholar · View at Scopus
  70. A. K. Barbey, M. Koenigs, and J. Grafman, “Dorsolateral prefrontal contributions to human working memory,” Cortex, vol. 49, no. 5, pp. 1195–1205, 2013. View at Publisher · View at Google Scholar · View at Scopus
  71. M. D'Esposito, B. R. Postle, and B. Rypma, “Prefrontal cortical contributions to working memory: evidence from event-related fMRI studies,” Experimental Brain Research, vol. 133, no. 1, pp. 3–11, 2000. View at Publisher · View at Google Scholar · View at Scopus
  72. P. J. Olesen, H. Westerberg, and T. Klingberg, “Increased prefrontal and parietal activity after training of working memory,” Nature Neuroscience, vol. 7, no. 1, pp. 75–79, 2004. View at Publisher · View at Google Scholar · View at Scopus
  73. A. Turken, S. Whitfield-Gabrieli, R. Bammer, J. V. Baldo, N. F. Dronkers, and J. D. E. Gabrieli, “Cognitive processing speed and the structure of white matter pathways: convergent evidence from normal variation and lesion studies,” NeuroImage, vol. 42, no. 2, pp. 1032–1044, 2008. View at Publisher · View at Google Scholar · View at Scopus
  74. A. M. Owen, K. M. McMillan, A. R. Laird, and E. Bullmore, “N-back working memory paradigm: a meta-analysis of normative functional neuroimaging studies,” Human Brain Mapping, vol. 25, no. 1, pp. 46–59, 2005. View at Publisher · View at Google Scholar · View at Scopus
  75. M. Wallentin, A. Roepstorff, R. Glover, and N. Burgess, “Parallel memory systems for talking about location and age in precuneus, caudate and Broca's region,” NeuroImage, vol. 32, no. 4, pp. 1850–1864, 2006. View at Publisher · View at Google Scholar · View at Scopus
  76. S. J. G. Lewis, A. Dove, T. W. Bobbins, R. A. Barker, and A. M. Owen, “Striatal contributions to working memory: a functional magnetic resonance imaging study in humans,” European Journal of Neuroscience, vol. 19, no. 3, pp. 755–760, 2004. View at Publisher · View at Google Scholar · View at Scopus
  77. R. Kanai and G. Rees, “The structural basis of inter-individual differences in human behaviour and cognition,” Nature Reviews Neuroscience, vol. 12, no. 4, pp. 231–242, 2011. View at Publisher · View at Google Scholar · View at Scopus
  78. N. Raz, U. Lindenberger, K. M. Rodrigue et al., “Regional brain changes in aging healthy adults: general trends, individual differences and modifiers,” Cerebral Cortex, vol. 15, no. 11, pp. 1676–1689, 2005. View at Publisher · View at Google Scholar · View at Scopus
  79. A. M. Fjell, L. T. Westlye, I. Amlien et al., “High consistency of regional cortical thinning in aging across multiple samples,” Cerebral Cortex, vol. 19, no. 9, pp. 2001–2012, 2009. View at Publisher · View at Google Scholar · View at Scopus
  80. J. D. Edwards, V. G. Wadley, R. S. Myers, D. L. Roenker, G. M. Cissell, and K. K. Ball, “Transfer of a speed of processing intervention to near and far cognitive functions,” Gerontology, vol. 48, no. 5, pp. 329–340, 2002. View at Publisher · View at Google Scholar · View at Scopus
  81. S.-C. Li, F. Schmiedek, O. Huxhold, C. Röcke, J. Smith, and U. Lindenberger, “Working memory plasticity in old age: practice gain, transfer, and maintenance,” Psychology and Aging, vol. 23, no. 4, pp. 731–742, 2008. View at Publisher · View at Google Scholar · View at Scopus
  82. E. Dahlin, L. Nyberg, L. Bäckman, and A. S. Neely, “Plasticity of executive functioning in young and older adults: immediate training gains, transfer, and long-term maintenance,” Psychology and Aging, vol. 23, no. 4, pp. 720–730, 2008. View at Publisher · View at Google Scholar · View at Scopus
  83. E. Borella, B. Carretti, F. Riboldi, and R. De Beni, “Working memory training in older adults: evidence of transfer and maintenance effects,” Psychology and Aging, vol. 25, no. 4, pp. 767–778, 2010. View at Google Scholar · View at Scopus
  84. R. Nouchi, Y. Taki, H. Takeuchi et al., “Brain training game improves executive functions and processing speed in the elderly: a randomized controlled trial,” PLoS ONE, vol. 7, no. 1, Article ID e29676, 2012. View at Publisher · View at Google Scholar · View at Scopus
  85. Y. Brehmer, H. Westerberg, and L. Bäckman, “Working-memory training in younger and older adults: training gains, transfer, and maintenance,” Frontiers in Human Neuroscience, vol. 6, article 63, 2012. View at Publisher · View at Google Scholar · View at Scopus
  86. H. Sakai, M. Takahara, N. F. Honjo, S. Doi, N. Sadato, and Y. Uchiyama, “Regional frontal gray matter volume associated with executive function capacity as a risk factor for vehicle crashes in normal aging adults,” PLoS ONE, vol. 7, no. 9, Article ID e45920, 2012. View at Publisher · View at Google Scholar · View at Scopus
  87. K. Ball, D. B. Berch, K. F. Helmers et al., “Effects of cognitive training interventions with older adults: a randomized controlled trial,” The Journal of the American Medical Association, vol. 288, no. 18, pp. 2271–2281, 2002. View at Publisher · View at Google Scholar · View at Scopus
  88. S. L. Willis, S. L. Tennstedt, M. Marsiske et al., “Long-term effects of cognitive training on everyday functional outcomes in older adults,” The Journal of the American Medical Association, vol. 296, no. 23, pp. 2805–2814, 2006. View at Publisher · View at Google Scholar · View at Scopus
  89. C. Lustig, P. Shah, R. Seidler, and P. A. Reuter-Lorenz, “Aging, training, and the brain: a review and future directions,” Neuropsychology Review, vol. 19, no. 4, pp. 504–522, 2009. View at Publisher · View at Google Scholar · View at Scopus