OPINION ARTICLE published: 11 April 2014 HUMAN NEUROSCIENCE doi: 10.3389/fnhum.2014.00218 Harnessing the neuroplastic potential of the human brain & the future of cognitive rehabilitation

Jyoti Mishra* and Adam Gazzaley*

Department of Neurology, Physiology and Psychiatry, University of California, San Francisco, San Francisco, CA, USA *Correspondence: [email protected]; [email protected]

Edited by: Guido P.H. Band, Leiden University, Netherlands Reviewed by: Geert Van Boxtel, Tilburg University, Netherlands

Keywords: cognitive training, neurotherapeutics, cognitive control, neuroplasticity, closed loop

Neuroplasticity is the remarkable abil- maximal positive plasticity in selectively transfer of benefit to untrained cogni- ityofthebrainthatallowsustolearn targeted neural systems; we envision such tive abilities (Tallal et al., 1996; Temple and adapt to our environment. Many activities will in turn generate “far trans- et al., 2003; Stevens et al., 2008; Smith studies have now shown that plasticity fer of benefit” to generalized cognition and et al., 2009; Ball et al., 2010; Berry et al., is retained throughout the lifespan from thereby improve the human condition. 2010; Anderson et al., 2013; Anguera infancytoveryoldage(Merzenich et al., In today’s modern technological and et al., 2013; Mishra et al., 2013; Wolinsky 1991; Merzenich and DeCharms, 1996; internet-connected era, individuals are et al., 2013). Furthermore, in two of Greenwood and Parasuraman, 2010; May, increasingly engaging with cognitive train- our training studies we find neurobe- 2011; Bavelier et al., 2012). Enriching life ing software to improve cognitive func- havioral correlations that relate on-task experiences, including literacy, prolonged tion. In fact over the past 10–15 years, neuroplasticity to broader improvements engagement in the arts, sciences and several companies have become estab- in untrained aspects of cognition. Other music, meditation and aerobic physical lished proponents and marketers of such researchers have also reported positive activities have all been shown to engender software, transforming it into a multi- findings and transfer of training effects to positive neuroplasticity that boosts cog- million dollar industry with exponential untrained cognitive abilities in the con- nitive function and/or prevents cognitive projected future growth. The fact that text of custom-designed working memory loss (Vance et al., 2010; Hayes et al., 2013; this technology is easily accessible over exercises (Klingberg, 2010; Rutledge et al., Matta Mello Portugal et al., 2013; Newberg the internet to the home-setting, and at 2012), task-switching training (Karbach et al., 2013; Zatorre, 2013). Unfortunately, low-cost, has facilitated it’s mass adop- and Kray, 2009), as well as for a specific just as enriching experiences generate pos- tion. Scientifically, however, not all “brain genre of commercially available games, i.e., itive plasticity, negative plasticity ensues training” is made equal. All too often, action video games (Bavelier et al., 2012) in impoverished settings. For instance, basic cognitive neuroscience experimental (although it is difficult to make strong rec- many studies now show that low socio- paradigms are embedded in commercial ommendations about many off-the-shelf economic, resource-poor environments, “brain training” approaches with add-on games given concerns over violent con- which are associated with stress, violence visual graphic skins that attempt to maxi- tent). From these studies we are coming and abuse within families and commu- mize user-engagement; a process known as to understand some of the design princi- nities, have detrimental effects on cogni- gamification. Although these experimen- ples that may govern the development of tionandneuralfunction(D’Angiulli et al., tal paradigms had been originally devel- effective neuroplasticity-targeted training, 2012; McEwen and Morrison, 2013). As opedtounderstandcognition,thatdoes as well as the scientific evaluation meth- cognitive neuroscientists we observe both not mean that they are also the best ods that can be used to provide convinc- positive and negative aspects of plasticity tools to engender positive neuroplastic- ing proof of the efficacy of the training in neural systems, in functional changes ity. It is no surprise then that some sci- intervention. Here, we summarize some of of neural activations, neural oscillations entific investigations have uncovered that these principles that have emerged from and strength of connectivity between brain generic brain training approaches yield two of our published training studies that regions, in structural changes in gray mat- no positive cognitive outcomes (Owen now inform the development and evalu- ter volume and white matter integrity, and et al., 2010). However, a blanket state- ation of our next generation of training importantly in the relationship between ment that all cognitive training is inef- tools. such neuroplastic changes and concomi- fectiveisalsounfair.Inrecentyears, In our first training study in older tant cognitive/behavioral changes. As we development and evaluation of cognitive adults, we simply trained visual per- come to understand various facets of plas- training approaches in many labs, includ- ceptual discrimination of Gabor patches ticity, it drives further the quest to develop ing our own, has revealed evidence for that had built-in directed motion ani- new activities/interventions that engender positive neuroplasticity, as well as for mation (Berry et al., 2010). Ten hours

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of training improved on-task perception population cohort. These factors, along training group, the study included an relative to performance changes in a with the heterogeneity of tested popula- active single-task training control, as well non-training (no-contact) control group. tions, very small training doses on mul- as a no-contact control group. The single- Interestingly, the training also benefitted tiple cognitive exercises, and the use of task training control performed the exact delayed-recognition working memory of assessment measures that are insensitive to same tasks as the training group of visual an untrained motion direction task. Not detect training related benefits in the tested discrimination and driving, except that only was working memory performance population, all may contribute to a fail- task engagement was not concurrent. This improved, electroencephalography (EEG) ure to observe positive impact (e.g., Owen active control directly tested our hypoth- neural recordings showed that training et al., 2010). esis that only training in a setting that evoked more efficient sensory encoding Whilerewardcyclesandadaptivepro- stresses cognitive control via a high inter- of the stimuli, which correlated with the gressions are key components of software ference environment would show signif- working memory performance gains. This design, it is equally important to tailor icant cognitive gains. Outcomes of the finding that 10 h of simple perceptual these game mechanics toward improving “Neuroracer” multitasking training were training engendered transfer of benefits specific deficits observed in a population not achieved in the active control group to working memory aligns with recent cohort. For instance, Anguera et al. (2013) or in the no-contact group, the latter understanding that perceptual training showed that deficient cognitive control being critical for assessing practice effects improves signal to noise contrast, which abilities, such as working memory and sus- due to repeated evaluations. Thus, the then leads to refined encoding at multi- tained attention, in healthy older adults “Neuroracer” study highlighted that rig- pleneuralscalesandhence,atleastsome can be enhanced by specifically training orous scientific evaluation of a cogni- degree of generalized cognitive benefits on a multitasking performance-adaptive tive training approach requires appropri- (Vinogradov et al., 2012). and rewarding video game, “Neuroracer.” atecontrolgroups,andoftenmorethan We are now gaining an appreciation “Neuroracer” implements visual discrimi- one control group, especially if we want that the observed gains in our percep- nation training in a go-no-go task for col- to understand the underlying mechanisms tual training study, and in similar studies ored shape targets, with the added demand of training effectiveness. Indeed longi- performedbyotherlabs,someofwhich of simultaneously driving on a virtual tudinal data collection is arduous, but have shown long-lasting cognitive bene- road. “Neuroracer” evidenced extensive without randomized, controlled and sin- fits (Willis et al., 2006; Rebok et al., 2014), gains such that healthy older adults who gle/double blinded enrollments, we cannot may be mediated by two fundamental multi-tasked 175% worse than younger convince ourselves of the significance of design elements that drive neuroplastic- adults on a first assessment, achieved sig- the results of new interventions. This is ity. 1) Training incorporated continuous nificant post-training performance levels especially appropriate for healthy popula- performance feedback at multiple levels on the game itself that surpassed those tions, while single-arm feasibility trials do of game play providing repeated cycles of young adults by +44%. Importantly, remain informative as a first pass in cog- of reward to the user 2) Training was training on “Neuroracer” transferred to nitively impaired populations. In addition, adaptive to the trainee’s in-the-moment untrained measures of sustained atten- we should also implement expectation bias game performance; i.e., adaptivity was tion and working memory in the setting measures for all participants, which con- incorporated using psychophysical stair- of interference, with EEG-based neural firm that all study groups anticipate the case functions that enhance training chal- recordings showing that plasticity of mid- same level of influence of their assigned lenge in response to accurate performance line frontal theta (mf theta) neural oscilla- intervention on the outcome measures, andreduceitforinaccurateperformance. tions may be a mediator of these cognitive thus assuring appropriate placebo con- The up-down step ratio in such stair- improvements. trol (Boot et al., 2013). Finally, adequately cases is often chosen to maintain over- Whilewehavetestedsomeaspectsof powered large sample size studies and all task challenge at 75–85%, at which sound game design, as described, other investigations that measure sustainability point the user is optimally engaged but not aspects of high-level video games may con- of the cognitive gains and underlying neu- frustrated. Thus, continuous performance tribute to their success and we look ahead roplasticity in yearly follow-ups are rare feedback rewards and adaptive task chal- to assessing these empirically. For example, and need to be performed more often lenge uniquely personalize the training to immersion, fun, real-world features, con- to address the long-term efficacy of cog- the cognitive capacity of each individual, tinuous performance, 3D environments, nitive interventions. Such rigor is con- and allows abilities to improve over time. virtual reality, high-levels of art, story, and vention in pharmaceutical clinical trials, Overall we have found these features to music facilitate sustained performance and and its adoption for video game test- be critically important in generating pos- better compliance, and also deeper engage- ing, along with safety evaluations that itive neuroplasticity and cognitive bene- ment that we suspect maximally harnesses detect potential side effects such as game- fit. Note, it is important to realize that plasticity. Evaluation of the influence of addiction, would promote a path toward casual game software is often not designed these features on training effectiveness FDA approvals and medical prescription to provide the optimal dose of repetitive requires careful scientific study design. For of such technologies. rewards nor incorporate adaptive progres- this, the “Neuroracer”studyadoptedarig- Equipped with our growing under- sions specifically targeted to the cognitive orous three-armed randomized controlled standing of how to design cognitive domains that may be deficient in a given design. In addition to the multitasking training approaches to target plasticity

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in specific neural circuits, we are now neuro-digital closed loop, albeit driven by healthcare interventions for neuropsychi- embarking on the development of the next ongoing scalp EEG oscillations as opposed atric populations in need of cognitive generation training technologies. We envi- to task-related neural processes as we envi- remediation. sion these advances to include combin- sion. ACKNOWLEDGMENTS ing behavior-digital closed loops that link We are aware that unlike traditional behavioral performance metrics to adap- cognitive training, a neuro-digital closed This work was supported by the National tive modulations of a training task on a loop approach is not feasible as a mainstay Institute of Health grants 5R01AG040333 digital platform, with neuro-digital closed in the home setting at present. Yet, with (Adam Gazzaley), 5R24TW007988-05 loops that link neural performance mea- rapid developments of mobile EEG tech- subaward VUMC38412 (Jyoti Mishra). surestoadaptivegamemechanics.For nology (Stopczynski et al., 2013), as well We would like to thank Joaquin Anguera example, the “Neuroracer” training study as advances in the real-time computational for his feedback on this opinion article. discovered that neuroplasticity of midline power available on consumer devices such as laptops and tablets, we expect that REFERENCES frontal theta (enhanced mf theta post- Anderson, S., White-Schwoch, T., Parbery-Clark, training) is a key neural factor that cor- deployment in the home environment will A., and Kraus, N. (2013). Reversal of age- relates with transferred cognitive gains. In be a reality within a few years. Neuro- related neural timing delays with training. Proc. order to test whether mf theta plastic- digital closed loops are also an exciting Natl. Acad. Sci. U.S.A. 110, 4357–4362. doi: ity is truly causal in enabling improved way to achieve personalized therapeutics, 10.1073/pnas.1213555110 as each feedback loop is customized to the Anguera, J. A., Boccanfuso, J., Rintoul, J. L., Al- cognition, we are now developing neuro- Hashimi, O., Faraji, F., Janowich, J., et al. (2013). digital closed loops that directly target individual user’s neural capacities in the Video game training enhances cognitive con- mf theta activity. More specifically, tech- moment. While here we have provided a trol in older adults. Nature 501, 97–101. doi: nological development is being directed simplistic example of a closed loop tied 10.1038/nature12486 to task-related mf theta activation, one Arns, M., Heinrich, H., and Strehl, U. (2014). at real-time EEG-based recordings that Evaluation of neurofeedback in ADHD: The long occur simultaneous with the cognitive task can conceive of more sophisticated neural and winding road. Biol. Psychol. 95, 108–115. doi: training (Delorme et al., 2011; Makeig targets, including frontal-posterior effec- 10.1016/j.neubiorev.2013.09.015 et al., 2012; Kothe and Makeig, 2013). tive connectivity based on task interaction Ball, K., Edwards, J. D., Ross, L. A., and McGwin, The goal is for these measurements to be dynamics. Further advances in this field G. Jr. (2010). Cognitive training decreases motor are expected as neuroscientists collaborate vehicle collision involvement of older drivers. JAm event-locked to task stimuli, account for Geriatr Soc, 58, 2107–2113. doi: 10.1111/j.1532- ocular and muscle-related artifacts, and with neural engineers, who have predom- 5415.2010.03138.x use source localization algorithms (Mullen inantly focused related efforts on neu- Bavelier, D., Green, C. S., Pouget, A., and Schrater, et al., 2013) so that they can be directly roprosthetic development (Borton et al., P. (2012). Brain plasticity through the life span: integrated in the game environment to 2013). Neuro-engineers have designed effi- learning to learn and action video games. Annu. cient closed loop decoding algorithms for Rev. Neurosci. 35, 391–416. doi: 10.1146/annurev- guide reward feedback to the user and neuro-060909-152832 adaptivity of task challenge in real-time. brain-machine interfaces in animal model Berry,A.S.,Zanto,T.P.,Clapp,W.C.,Hardy,J.L., We hypothesize that using neural perfor- systems, and these techniques are now ripe Delahunt, P. B., Mahncke, H. W., et al. (2010). mance as the driver for task-adaptivity foradoptioninhumans(Carmena, 2013). The influence of perceptual training on working Finally, especially beneficial for clinical memory in older adults. PLoS ONE 5:e11537. doi: will generate more rapid, efficient and 10.1371/journal.pone.0011537 specific circuit plasticity than is currently populations that exhibit weakened neural Boot, W. R., Simons, D. J., Stothart, C., and Stutts, obtained using behavior-adaptive cogni- responsivity, another intriguing step will C. (2013). The pervasive problem with placebos in tive training approaches. This hypothe- be the integration of neuro-digital closed psychology: why active control groups are not suf- sis is borne out of data, which shows loop systems with transcranial electrical ficient to rule out placebo effects. Perspect. Psychol. current stimulation or even deep brain Sci. 8, 445–454. doi: 10.1177/1745691613491271 that single-trial behavioral performance Borton, D., Micera, S., Millán, J. D. R., and is predicted by neural measures such as stimulation technologies (Coffman et al., Courtine, G. (2013). Personalized neuroprosthet- mf-theta oscillations preceding the behav- 2013), which may provide a needed plas- ics. Sci. Transl. Med. 5, 210rv2. doi: 10.1126/sci- ior. Thus the neuro-digital closed loop ticity boost to impaired brain regions. translmed.3005968 offersthepotentialtoselectivelytrain To achieve the goals of our field and Carmena, J. M. (2013). Advances in neuroprosthetic learning and control. PLoS Biol. 11, e1001561. doi: and refine the bottleneck neural processes fully harness the potential of neuroplastic- 10.1371/journal.pbio.1001561 that govern the final behavioral outcome. ity for cognitive benefit, we look forward Coffman, B. A., Clark, V. P., and Parasuraman, R. Importantly, by directly embedding task- to continued technological development, (2013). Battery powered thought: Enhancement related neural activity in a closed loop, such as neuro-digital closed loops, and of attention, learning, and memory in healthy this approach can provide missing causal their integration with emerging design adults using transcranial direct current stim- ulation. Neuroimage 85(Pt. 3), 895–908. doi: evidence between neuroplasticity and cog- principles of cognitive training games. 10.1016/j.neuroimage.2013.07.083 nitive benefits. This line of investigation is These technologies validated using ran- D’Angiulli, A., Lipina, S. J., and Olesinska, A. especially promising in the light of accu- domized, controlled scientific evaluation (2012). Explicit and implicit issues in the mulating scientific evidence of the value methodologies will generate new under- developmental cognitive neuroscience of social inequality. Front. Hum. Neurosci. 6:254. doi: of conventional neurofeedback approaches standing of how to translate cognitive neu- 10.3389/fnhum.2012.00254 (Gruzelier, 2013; Wang and Hsieh, 2013; roscience discoveries into new educational Delorme, A., Mullen, T., Kothe, C., Akalin Acar, Arns et al., 2014), which also creates a tools for healthy populations and mental Z., Bigdely-Shamlo, N., Vankov, A., et al. (2011).

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EEGLAB, SIFT, NFT, BCILAB, and ERICA: new in the brain. Prog. Brain Res. 207, 351–377. doi: Vance, D. E., Roberson, A. J., McGuinness, T. M., tools for advanced EEG processing. Comput. Intell. 10.1016/B978-0-444-63327-9.00013-8 and Fazeli, P. L. (2010). How neuroplasticity and Neurosci. 2011, 130714. doi: 10.1155/2011/130714 Mullen, T., Kothe, C., Chi, Y. M., Ojeda, A., Kerth, cognitive reserve protect cognitive functioning. Greenwood, P. M., and Parasuraman, R. (2010). T., Makeig, S., et al. (2013). Real-time modeling J. Psychosoc. Nurs. Ment. Health Serv. 48, 23–30. Neuronal and cognitive plasticity: a neurocog- and 3D visualization of source dynamics and con- doi: 10.3928/02793695-20100302-01 nitive framework for ameliorating cognitive nectivity using wearable EEG. Conf. Proc. IEEE Vinogradov, S., Fisher, M., and de Villers-Sidani, aging. Front. Aging Neurosci. 2:150. doi: Eng. Med. Biol. Soc. Conf. 2013, 2184–2187. doi: E. (2012). Cognitive training for impaired 10.3389/fnagi.2010.00150 10.1109/EMBC.2013.6609968 neural systems in neuropsychiatric illness. Gruzelier, J. H. (2013). EEG-neurofeedback Newberg, A. B., Serruya, M., Wintering, N., Moss, A. Neuropsychopharmacology 37, 43–76. doi: for optimising performance. I: a review of S., Reibel, D., and Monti, D. A. (2013). Meditation 10.1038/npp.2011.251 cognitive and affective outcome in healthy and neurodegenerative diseases. Ann. N.Y. Acad. Wang, J.-R., and Hsieh, S. (2013). Neurofeedback participants. Neurosci. Biobehav. Rev. doi: Sci. 1307, 112–123. doi: 10.1111/nyas.12187 training improves attention and working memory 10.1016/j.neubiorev.2013.09.015. [Epub ahead of Owen,A.M.,Hampshire,A.,Grahn,J.A.,Stenton, performance. Clin. Neurophysiol. 124, 2406–2420. print]. R., Dajani, S., Burns, A. S., et al. (2010). Putting doi: 10.1016/j.clinph.2013.05.020 Hayes, S. M., Hayes, J. P., Cadden, M., and brain training to the test. Nature 465, 775–778. doi: Willis, S. L., Tennstedt, S. L., Marsiske, M., Ball, Verfaellie, M. (2013). A review of cardiores- 10.1038/nature09042 K., Elias, J., Koepke, K. M., et al. (2006). Long- piratory fitness-related neuroplasticity in the Rebok, G. W., Ball, K., Guey, L. T., Jones, R. N., term effects of cognitive training on everyday aging brain. Front. Aging Neurosci. 5:31. doi: Kim, H.-Y., King, J. W., et al. (2014). Ten-Year functional outcomes in older adults. J. Am. Med. 10.3389/fnagi.2013.00031 effects of the advanced cognitive training for Assoc. 296, 2805–2814. doi: 10.1001/jama.296. Karbach, J., and Kray, J. (2009). How useful is exec- independent and vital elderly cognitive training 23.2805 utive control training? Age differences in near trial on cognition and everyday functioning in Wolinsky, F. D., Vander Weg, M. W., Howren, M. and far transfer of task-switching training.Dev. older adults. J. Am. Geriatr. Soc. 62, 16–24. doi: B., Jones, M. P., and Dotson, M. M. (2013). A Sci. 12, 978–990. doi: 10.1111/j.1467-7687.2009. 10.1111/jgs.12607 randomized controlled trial of cognitive training 00846.x Rutledge,K.J.,vandenBos,W.,McClure,S.M., using a visual speed of processing intervention in Klingberg, T. (2010). Training and plasticity of work- and Schweitzer, J. B. (2012). Training cognition in middle aged and older adults. PloS ONE 8:e61624. ing memory. Trends Cogn. Sci. 14, 317–324. doi: ADHD: current findings, borrowed concepts, and doi: 10.1371/journal.pone.0061624 10.1016/j.tics.2010.05.002 future directions. Neurotherapeutics 9, 542–558. Zatorre, R. J. (2013). Predispositions and plasticity Kothe, C. A., and Makeig, S. (2013). BCILAB: a plat- doi: 10.1007/s13311-012-0134-9 in music and speech learning: neural correlates form for brain-computer interface development. Smith, G. E., Housen, P., Yaffe, K., Ruff, R., Kennison, and implications. Science 342, 585–589. doi: J. Neural Eng. 10, 056014. doi: 10.1088/1741- R. F., Mahncke, H. W., et al. (2009). A cognitive 10.1126/science.1238414 2560/10/5/056014 training program based on principles of brain Makeig, S., Kothe, C., Mullen, T., Bigdely- plasticity: results from the Improvement in Conflict of Interest Statement: Jyoti Mishra is a Shamlo, N., and Kreutz-Delgado, K. (2012). Memory with Plasticity-based Adaptive Cognitive part-time scientist at the Brain Plasticity Institute, Evolving signal processing for brain–computer Training (IMPACT) study. J. Am. Geriatr. PositScience, a company that develops cognitive interfaces. Proc. IEEE 100, 1567–1584. doi: Soc. 57, 594–603. doi: 10.1111/j.1532-5415. training software. Adam Gazzaley is co-founder and 10.1109/JPROC.2012.2185009 2008.02167 chiefscienceadvisorofAkiliInteractiveLabs,acom- Matta Mello Portugal, E., Cevada, T., Sobral Stevens, C., Fanning, J., Coch, D., Sanders, L., pany that develops cognitive training software. Jyoti Monteiro-Junior, R., Teixeira Guimarães, T., and Neville, H. (2008). Neural mechanisms of Mishra and Adam Gazzaley have a patent pending da Cruz Rubini, E., Lattari, E., et al. (2013). selective auditory attention are enhanced by for “Methods of Suppressing Irrelevant Stimuli.” Neuroscience of exercise: from neurobiology computerized training: electrophysiological evi- Adam Gazzaley has a patent pending for a game- mechanisms to mental health. Neuropsychobiology dence from language-impaired and typically devel- based cognitive training intervention: “Enhancing 68, 1–14. doi: 10.1159/000350946 oping children. Brain Res. 1205, 55–69. doi: cognition in the presence of distraction and/or May, A. (2011). Experience-dependent structural 10.1016/j.brainres.2007.10.108 interruption.” plasticity in the adult human brain. Trends Cogn. Stopczynski, A., Stahlhut, C., Petersen, M. K., Sci. 15, 475–482. doi: 10.1016/j.tics.2011.08.002 Larsen, J. E., Jensen, C. F., Ivanova, M. G., Received: 30 December 2013; accepted: 27 March 2014; McEwen, B. S., and Morrison, J. H. (2013). The brain et al. (2013). Smartphones as pocketable labs: published online: 11 April 2014. on stress: vulnerability and plasticity of the pre- Visions for mobile brain imaging and neuro- Citation: Mishra J and Gazzaley A (2014) Harnessing frontal cortex over the life course. Neuron 79, feedback. Int. J. Psychophysiol. 91, 54–66. doi: the neuroplastic potential of the human brain & the 16–29. doi: 10.1016/j.neuron.2013.06.028 10.1016/j.ijpsycho.2013.08.007 future of cognitive rehabilitation. Front. Hum. Neurosci. Merzenich, M. M., and DeCharms, R. (1996). “Neural Tallal, P., Miller, S. L., Bedi, G., Byma, G., Wang, 8:218. doi: 10.3389/fnhum.2014.00218 representations, experience, and change,” in The X., Nagarajan, S. S., et al. (1996). Language This article was submitted to the journal Frontiers in Mind-Brain Continuum,eds. R. Llinas and P. comprehension in language-learning impaired Human Neuroscience. Churchland (Boston, MA: The MIT Press), 61–81. children improved with acoustically modified Copyright © 2014 Mishra and Gazzaley. This is an Merzenich, M. M., Recanzone, G. H., and Jenkins, W. speech. Science 271, 81–84. doi: 10.1126/sci- open-access article distributed under the terms of the (1991). “How the brain functionally rewires itself,” ence.271.5245.81 Creative Commons Attribution License (CC BY). The in Natural and Artificial Parallel Computations, eds. Temple, E., Deutsch, G. K., Poldrack, R. A., Miller, use, distribution or reproduction in other forums is per- M. Arbib and J. A. Robinson (New York, NY: MIT S. L., Tallal, P., Merzenich, M. M., et al. (2003). mitted, provided the original author(s) or licensor are Press). Neural deficits in children with dyslexia amelio- credited and that the original publication in this journal Mishra, J., Anguera, J. A., Ziegler, D. A., and Gazzaley, rated by behavioral remediation: evidence from is cited, in accordance with accepted academic practice. A. (2013). A cognitive framework for under- functional MRI. Proc. Natl. Acad. Sci. U.S.A. 100, No use, distribution or reproduction is permitted which standing and improving interference resolution 2860–2865. doi: 10.1073/pnas.0030098100 does not comply with these terms.

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