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      Harnessing neuroplasticity for clinical applications

      review-article
      1 , , 2 , 3 , 4 , 5 , 4 , 6 , 7 , 8 , 7 , 9 , 7 , 10 , 11 , 12 , 13 , 14 , 6 , 15 , 11 , 16 , 17 , 18 , 15 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 ,   20 , 27 , 20
      Brain
      Oxford University Press
      neuroplasticity, retraining, therapeutics, clinical assessment

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          Abstract

          Neuroplasticity can be defined as the ability of the nervous system to respond to intrinsic or extrinsic stimuli by reorganizing its structure, function and connections. Major advances in the understanding of neuroplasticity have to date yielded few established interventions. To advance the translation of neuroplasticity research towards clinical applications, the National Institutes of Health Blueprint for Neuroscience Research sponsored a workshop in 2009. Basic and clinical researchers in disciplines from central nervous system injury/stroke, mental/addictive disorders, paediatric/developmental disorders and neurodegeneration/ageing identified cardinal examples of neuroplasticity, underlying mechanisms, therapeutic implications and common denominators. Promising therapies that may enhance training-induced cognitive and motor learning, such as brain stimulation and neuropharmacological interventions, were identified, along with questions of how best to use this body of information to reduce human disability. Improved understanding of adaptive mechanisms at every level, from molecules to synapses, to networks, to behaviour, can be gained from iterative collaborations between basic and clinical researchers. Lessons can be gleaned from studying fields related to plasticity, such as development, critical periods, learning and response to disease. Improved means of assessing neuroplasticity in humans, including biomarkers for predicting and monitoring treatment response, are needed. Neuroplasticity occurs with many variations, in many forms, and in many contexts. However, common themes in plasticity that emerge across diverse central nervous system conditions include experience dependence, time sensitivity and the importance of motivation and attention. Integration of information across disciplines should enhance opportunities for the translation of neuroplasticity and circuit retraining research into effective clinical therapies.

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          Most cited references209

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          Cardiovascular fitness, cortical plasticity, and aging.

          Cardiovascular fitness is thought to offset declines in cognitive performance, but little is known about the cortical mechanisms that underlie these changes in humans. Research using animal models shows that aerobic training increases cortical capillary supplies, the number of synaptic connections, and the development of new neurons. The end result is a brain that is more efficient, plastic, and adaptive, which translates into better performance in aging animals. Here, in two separate experiments, we demonstrate for the first time to our knowledge, in humans that increases in cardiovascular fitness results in increased functioning of key aspects of the attentional network of the brain during a cognitively challenging task. Specifically, highly fit (Study 1) or aerobically trained (Study 2) persons show greater task-related activity in regions of the prefrontal and parietal cortices that are involved in spatial selection and inhibitory functioning, when compared with low-fit (Study 1) or nonaerobic control (Study 2) participants. Additionally, in both studies there exist groupwise differences in activation of the anterior cingulate cortex, which is thought to monitor for conflict in the attentional system, and signal the need for adaptation in the attentional network. These data suggest that increased cardiovascular fitness can affect improvements in the plasticity of the aging human brain, and may serve to reduce both biological and cognitive senescence in humans.
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            Aging gracefully: compensatory brain activity in high-performing older adults.

            Whereas some older adults show significant cognitive deficits, others perform as well as young adults. We investigated the neural basis of these different aging patterns using positron emission tomography (PET). In PET and functional MRI (fMRI) studies, prefrontal cortex (PFC) activity tends to be less asymmetric in older than in younger adults (Hemispheric Asymmetry Reduction in Old Adults or HAROLD). This change may help counteract age-related neurocognitive decline (compensation hypothesis) or it may reflect an age-related difficulty in recruiting specialized neural mechanisms (dedifferentiation hypothesis). To compare these two hypotheses, we measured PFC activity in younger adults, low-performing older adults, and high-performing older adults during recall and source memory of recently studied words. Compared to recall, source memory was associated with right PFC activations in younger adults. Low-performing older adults recruited similar right PFC regions as young adults, but high-performing older adults engaged PFC regions bilaterally. Thus, consistent with the compensation hypothesis and inconsistent with the dedifferentiation hypothesis, a hemispheric asymmetry reduction was found in high-performing but not in low-performing older adults. The results suggest that low-performing older adults recruited a similar network as young adults but used it inefficiently, whereas high-performing older adults counteracted age-related neural decline through a plastic reorganization of neurocognitive networks.
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              Computerized training of working memory in children with ADHD--a randomized, controlled trial.

              Deficits in executive functioning, including working memory (WM) deficits, have been suggested to be important in attention-deficit/hyperactivity disorder (ADHD). During 2002 to 2003, the authors conducted a multicenter, randomized, controlled, double-blind trial to investigate the effect of improving WM by computerized, systematic practice of WM tasks. Included in the trial were 53 children with ADHD (9 girls; 15 of 53 inattentive subtype), aged 7 to 12 years, without stimulant medication. The compliance criterion (>20 days of training) was met by 44 subjects, 42 of whom were also evaluated at follow-up 3 months later. Participants were randomly assigned to use either the treatment computer program for training WM or a comparison program. The main outcome measure was the span-board task, a visuospatial WM task that was not part of the training program. For the span-board task, there was a significant treatment effect both post-intervention and at follow-up. In addition, there were significant effects for secondary outcome tasks measuring verbal WM, response inhibition, and complex reasoning. Parent ratings showed significant reduction in symptoms of inattention and hyperactivity/impulsivity, both post-intervention and at follow-up. This study shows that WM can be improved by training in children with ADHD. This training also improved response inhibition and reasoning and resulted in a reduction of the parent-rated inattentive symptoms of ADHD.
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                Author and article information

                Journal
                Brain
                brainj
                brain
                Brain
                Oxford University Press
                0006-8950
                1460-2156
                June 2011
                9 April 2011
                9 April 2011
                : 134
                : 6
                : 1591-1609
                Affiliations
                1 Departments of Neurology and Anatomy & Neurobiology, University of California, Irvine, CA 92967, USA
                2 Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
                3 Department of Neurology, University of California Los Angeles, CA 90095, USA
                4 Departments of Psychiatry and Pathology & Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
                5 Biomedical Engineering, Neurology and Biokinesiology, University of Southern California, Los Angeles, CA 90089, USA
                6 National Institute of Mental Health, Rockville, MD 20852, USA
                7 National Institute of Neurological Disorders and Stroke, Bethesda, MD 20824, USA
                8 Departments of Physiology and Pharmacology, Oregon Health and Sciences University, Portland, OR, 97239, USA
                9 National Institute on Ageing, Bethesda, MD 20892-0001, USA
                10 Omneuron, Inc., Menlo Park, CA 94025, USA
                11 Departments of Neurogeriatrics and Pharmacology & Physiology, University of Rochester, Rochester, NY 14627, USA
                12 Department of Pediatrics, Georgetown University, Washington DC 20057, USA
                13 Department of Physiology and Biophysics, University of Washington, Seattle, WA, 98195, USA
                14 National Centre for Research Resources, Bethesda, MD, 20892, USA
                15 National Institute on Drug Abuse, Rockville, MD 20852, USA
                16 Department of Neurosciences, Medical University of South Carolina, Charleston, South Carolina 29425, USA
                17 Department of Neuroscience, University of Lethbridge, Lethbridge, AB T1K 3M4, Canada
                18 Department of Psychology, University of Illinois, Urbana-Champaign, IL, 61801, USA
                19 Departments of Psychiatry and Behavioral Sciences and Neurology, Emory University, Atlanta, GA 30322, USA
                20 Departments of Pediatrics, Physiology, and Psychiatry, University of California San Francisco, San Francisco, CA 94102, USA
                21 National Institute of Child Health and Human Development, Bethesda, MD, 20892, USA
                22 Berenson-Allen Centre for Non-invasive Brain Stimulation, Beth Israel Deaconess Medical and Harvard Medical School
                23 Departments of Psychology and Neuroscience, University of Michigan, Dearborn, MI 48128, USA
                24 Department of Neurology, Weill Cornell Medical College, Cornell University, New York 10065, USA
                25 Department of Speech, Language and Hearing Sciences, University of Colorado, Boulder, Colorado 80305, USA
                26 National Institute on Deafness and Other Communication Disorders, Bethesda, MD, 20892, USA
                27 Department of Psychiatry and Behavioral Sciences, Stanford University, Menlo Park, CA, USA
                Author notes
                Correspondence to: Steven C. Cramer, MD, UC Irvine Medical Centre, 101 The City Drive South, Bldg 53, Rm 203, Orange, CA 92868-4280, USA E-mail: scramer@ 123456uci.edu
                Article
                awr039
                10.1093/brain/awr039
                3102236
                21482550
                9353bcf4-5fed-4b79-b6a6-b4211bfc995c
                Published by Oxford University Press on behalf of Brain 2011.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 4 October 2010
                : 18 January 2011
                : 19 January 2011
                Page count
                Pages: 19
                Categories
                Review Article

                Neurosciences
                neuroplasticity,retraining,therapeutics,clinical assessment
                Neurosciences
                neuroplasticity, retraining, therapeutics, clinical assessment

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