Harnessing the neuroplastic potential of the human brain & the future of cognitive rehabilitation

Frontiers in Human Neuroscience

Volumn 8, Issue 1 APR, 2014, Pages

  Mishra, Jyoti ^a   Gazzaley, Adam ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; COGNITIVE REHABILITATION; ELECTROENCEPHALOGRAPHY; EXECUTIVE FUNCTION; GAME; HUMAN; MENTAL PERFORMANCE; NERVE CELL PLASTICITY; REWARD; TASK PERFORMANCE; WORKING MEMORY;

EID: 84898435693     PISSN: 16625161     EISSN: None     Source Type: Journal    
DOI: 10.3389/fnhum.2014.00218     Document Type: Article

References (41)

1. Anderson, S., White-Schwoch, T., Parbery-Clark, A., and Kraus, N. (2013). Reversal of age- related neural timing delays with training. Proc. Natl. Acad. Sci. [J.S.A. 110, 4357-4362. doi: 10.1073/pnas.1213555110.
2. Anguera, J. A., Boccanfuso, J., Rintoul, J. L., Al- Hashimi, O., Faraji, F., Janowich, J., et al. (2013). Video game training enhances cognitive control in older adults. Nature 501, 97-101. doi: 10.1038/nature12486.
3. Arns, M., Heinrich, H., and Strehl, U. (2014). Evaluation of neurofeedback in ADHD: The long and winding road. Biol. Psychol. 95, 108-115. doi: 10.1016/j.neubiorev.2013.09.015.
4. Ball, K., Edwards, J. D., Ross, L. A., and McGwin, G. Jr. (2010). Cognitive training decreases motor vehicle collision involvement of older drivers. J Am Geriatr Soc, 58, 2107-2113. doi: 10.1111/j.1532- 5415.2010.03138.x
5. Bavelier, D., Green, C. S., Pouget, A., and Schrater, P. (2012). Brain plasticity through the life span: learning to learn and action video games. Annu. Rev. Neurosci. 35, 391-416. doi: 10.1146/annurev- neuro-060909-152832.
6. Berry, A. S., Zanto, T. P., Clapp, W. C., Hardy, J. L., Delahunt, P. B., Mahncke, H. W., et al. (2010). The influence of perceptual training on working memory in older adults. PLoS ONE 5:e11537. doi: 10.1371/journal.pone.0011537.
7. Boot, W. R., Simons, D. J., Stothart, C., and Stutts, C. (2013). The pervasive problem with placebos in psychology: why active control groups are not sufficient to rule out placebo effects. Perspect. Psychol. Sci. 8,445-454. doi: 10.1177/1745691613491271.
8. Borton, D., Micera, S., Millan, J. D. R., and Courtine, G. (2013). Personalized neuroprosthetics. Sci. Transl. Med. 5, 210rv2. doi: 10.1126/sci- translmed.3005968.
9. Carmena, J. M. (2013). Advances in neuroprosthetic learning and control. PLoS Biol. 11, e1001561. doi: 10.1371/journal.pbio.1001561.
10. Coffman, B. A., Clark, V. P., and Parasuraman, R. (2013). Battery powered thought: Enhancement of attention, learning, and memory in healthy adults using transcranial direct current stimulation. Neuroimage 85(Pt. 3), 895-908. doi: 10.1016/j.neuroimage.2013.07.083.
11. D'Angiulli, A., Lipina, S. J., and Olesinska, A. (2012). Explicit and implicit issues in the developmental cognitive neuroscience of social inequality. Front. Hum. Neurosci. 6:254. doi: 10.3389/fnhum.2012.00254.
12. Delorme, A., Mullen, T., Kothe, C., Akalin Acar, Z., Bigdely-Shamlo, N., Vankov, A., et al. (2011). EEGLAB, SIFT, NFT, BCILAB, and ERICA: new tools for advanced EEG processing. Comput. Intell. Neurosci. 2011, 130-714. doi: 10.1155/2011/130714.
13. Greenwood, P. M., and Parasuraman, R. (2010). Neuronal and cognitive plasticity: a neurocog- nitive framework for ameliorating cognitive aging. Front. Aging Neurosci. 2:150. doi: 10.3389/fnagi.2010.00150.
14. Gruzelier, J. H. (2013). EEG-neurofeedback for optimising performance. I: a review of cognitive and affective outcome in healthy participants. Neurosci. Biobehav. Rev. doi: 10.1016/j.neubiorev.2013.09.015. [Epub ahead of print].
15. Hayes, S. M., Hayes, J. P., Cadden, M., and Verfaellie, M. (2013). A review of cardiorespiratory fitness-related neuroplasticity in the aging brain. Front. Aging Neurosci. 5:31. doi: 10.3389/fnagi.2013.00031.
16. Karbach, J., and Kray, J. (2009). How useful is executive control training? Age differences in near and far transfer of task-switching training. Dev. Sci. 12, 978-990. doi: 10.1111/j.1467-7687.2009. 00846.x
17. Klingberg, T. (2010). Training and plasticity of working memory. Trends Cogn. Sci. 14, 317-324. doi: 10.1016/j.tics.2010.05.002.
18. Kothe, C. A., and Makeig, S. (2013). BCILAB: a platform for brain-computer interface development. J. Neural Eng. 10, 056014. doi: 10.1088/17412560/10/5/056014.
19. Makeig, S., Kothe, C., Mullen, T., Bigdely- Shamlo, N., and Kreutz-Delgado, K. (2012). Evolving signal processing for brain-computer interfaces. Proc. IEEE 100, 1567-1584. doi: 10.1109/JPROC.2012.2185009.
20. Matta Mello Portugal, E., Cevada, T., Sobral Monteiro-Junior, R., Teixeira Guimaraes, T., da Cruz Rubini, E., Lattari, E., et al. (2013). Neuroscience of exercise: from neurobiology mechanisms to mental health. Neuropsychobiology 68, 1-14. doi: 10.1159/000350946.
21. May, A. (2011). Experience-dependent structural plasticity in the adult human brain. Trends Cogn. Sci. 15, 475-482. doi: 10.1016/j.tics.2011.08.002.
22. McEwen, B. S., and Morrison, J. H. (2013). The brain on stress: vulnerability and plasticity of the pre- frontal cortex over the life course. Neuron 79, 16-29. doi: 10.1016/j.neuron.2013.06.028.
23. Merzenich, M. M., and DeCharms, R. (1996). "Neural representations, experience, and change," in The Mind-Brain Continuum, eds. R. Llinas and P. Churchland (Boston, MA: The MIT Press), 61-81.
24. Merzenich, M. M., Recanzone, G. H., and Jenkins, W. (1991). "How the brain functionally rewires itself," in NaturalandArtificialParallel Computations, eds. M. Arbib and J. A. Robinson (New York, NY: MIT Press).
25. Mishra, J., Anguera, J. A., Ziegler, D. A., and Gazzaley, A. (2013). A cognitive framework for understanding and improving interference resolution in the brain. Prog. Brain Res. 207, 351-377. doi: 10.1016/B978-0-444-63327-9.00013-8.
26. Mullen, T., Kothe, C., Chi, Y. M., Ojeda, A., Kerth, T., Makeig, S., et al. (2013). Real-time modeling and 3D visualization of source dynamics and connectivity using wearable EEG. Conf. Proc. IEEE Eng. Med. Biol. Soc. Conf. 2013, 2184-2187. doi: 10.1109/EMBC.2013.6609968.
27. Newberg, A. B., Serruya, M., Wintering, N., Moss, A. S., Reibel, D., and Monti, D. A. (2013). Meditation and neurodegenerative diseases. Ann. N.Y. Acad. Sci. 1307, 112-123. doi: 10.1111/nyas.12187.
28. Owen, A. M., Hampshire, A., Grahn, J. A., Stenton, R., Dajani, S., Burns, A. S., et al. (2010). Putting brain training to the test. Nature 465, 775-778. doi: 10.1038/nature09042.
29. Rebok, G. W., Ball, K., Guey, L. T., Jones, R. N., Kim, H.-Y., King, J. W., et al. (2014). Ten-Year effects of the advanced cognitive training for independent and vital elderly cognitive training trial on cognition and everyday functioning in older adults. J. Am. Geriatr. Soc. 62, 16-24. doi: 10.1111/jgs.12607.
30. Rutledge, K. J., van den Bos, W., McClure, S. M., and Schweitzer, J. B. (2012). Training cognition in ADHD: current findings, borrowed concepts, and future directions. Neurotherapeutics 9, 542-558. doi: 10.1007/s13311-012-0134-9.
31. Smith, G. E., Housen, P., Yaffe, K., Ruff, R., Kennison, R. F., Mahncke, H. W., et al. (2009). A cognitive training program based on principles of brain plasticity: results from the Improvement in Memory with Plasticity-based Adaptive Cognitive Training (IMPACT) study. J. Am. Geriatr. Soc. 57, 594-603. doi: 10.1111/j.1532-5415. 2008.02167
32. Stevens, C., Fanning, J., Coch, D., Sanders, L., and Neville, H. (2008). Neural mechanisms of selective auditory attention are enhanced by computerized training: electrophysiological evidence from language-impaired and typically developing children. Brain Res. 1205, 55-69. doi: 10.1016/j.brainres.2007.10.108.
33. Stopczynski, A., Stahlhut, C., Petersen, M. K., Larsen, J. E., Jensen, C. F., Ivanova, M. G., et al. (2013). Smartphones as pocketable labs: Visions for mobile brain imaging and neurofeedback. Int. J. Psychophysiol. 91, 54-66. doi: 10.1016/j.ijpsycho.2013.08.007.
34. Tallal, P., Miller, S. L., Bedi, G., Byma, G., Wang, X., Nagarajan, S. S., et al. (1996). Language comprehension in language-learning impaired children improved with acoustically modified speech. Science 271, 81-84. doi: 10.1126/sci- ence.271.5245.81.
35. Temple, E., Deutsch, G. K., Poldrack, R. A., Miller, S. L., Tallal, P., Merzenich, M. M., et al. (2003). Neural deficits in children with dyslexia ameliorated by behavioral remediation: evidence from functional MRI. Proc. Natl. Acad. Sci. U.S.A. 100, 2860-2865. doi: 10.1073/pnas.0030098100
36. Vance, D. E., Roberson, A. J., McGuinness, T. M., and Fazeli, P. L. (2010). How neuroplasticity and cognitive reserve protect cognitive functioning. J. Psychosoc. Nurs. Ment. Health Serv. 48, 23-30. doi: 10.3928/02793695-20100302-01.
37. Vinogradov, S., Fisher, M., and de Villers-Sidani, E. (2012). Cognitive training for impaired neural systems in neuropsychiatric illness. Neuropsychopharmacology 37, 43-76. doi: 10.1038/npp.2011.251.
38. Wang, J.-R., and Hsieh, S. (2013). Neurofeedback training improves attention and working memory performance. Clin. Neurophysiol. 124, 2406-2420. doi: 10.1016/j.clinph.2013.05.020.
39. Willis, S. L., Tennstedt, S. L., Marsiske, M., Ball, K., Elias, J., Koepke, K. M., et al. (2006). Longterm effects of cognitive training on everyday functional outcomes in older adults. J. Am. Med. Assoc. 296, 2805-2814. doi: 10.1001/jama.296. 23.2805
40. Wolinsky, F. D., Vander Weg, M. W., Howren, M. B., Jones, M. P., and Dotson, M. M. (2013). A randomized controlled trial of cognitive training using a visual speed of processing intervention in middle aged and older adults. PloS ONE 8:e61624. doi: 10.1371/journal.pone.0061624.
41. Zatorre, R. J. (2013). Predispositions and plasticity in music and speech learning: neural correlates and implications. Science 342, 585-589. doi: 10.1126/science.1238414