Evidence is accumulating that training with mental imagery of strong muscle contractions enhances descending command (from the brain) and strengthens muscle output. This finding has substantial application in medical rehabilitation because although it is unsafe or difficult for many cognitively healthy patients and frail older adults who suffer muscle weakness to undergo conventional strength training, it is possible for them to use their mind to strengthen their muscles. Two major obstacles to the implementation of mental training of this type are the inability of investigators to monitor the mental processes of the subjects directly and the difficulty of many subjects, especially those with reduced cognitive ability (e.g., old people), to mentally contract a muscle "strongly" without any feedback about relevant brain activity. It has recently been shown that power of scalp EEG frequencies is linearly correlated to the intensity of muscle contraction. Furthermore, the EEG oscillation power increases proportionally with intensity of intended (mental) muscle contractions. These findings indicate that the EEG power signal reflects brain activities controlling muscle force;this offers the possibility of using the EEG frequency power as an objective parameter for monitoring quality of the mental training and maximizing the outcome result. Our overall hypothesis is that in given subjects with muscle morphology and coordination unchanged, the amount of strength is directly related to the magnitude of brain signal driving the muscle;mental training with the cortical signal feedback can more effectively enhance the brain signal and increase muscle strength.
Aim 1 will determine whether mental training by monitoring the power of EEG frequency is superior in allowing gain in muscle strength to mental training without such feedback in older adults.
Aim 2 will examine potential neural mechanisms that mediate mental training-induced strength improvements. It is hypothesized that the mental training group with the EEG feedback will exhibit greater cortical signal change and gain more strength than the group with no such EEG feedback;the amount of neural adaptation will correlate significantly with strength increases.
This study will develop and evaluate a new mental training method for muscle strengthening. The method will enable older adults and others with reduced motor and cognitive abilities to effectively improve brain function and increase muscle strength without undergoing conventional strength training such as lifting heavy weights.
|Jiang, Changhao; Ranganathan, Vinoth K; Zhang, Junmei et al. (2016) Motor effort training with low exercise intensity improves muscle strength and descending command in aging. Medicine (Baltimore) 95:e3291|
|Jiang, Zhiguo; Wang, Xiao-Feng; Yue, Guang H (2016) Strengthened Corticosubcortical Functional Connectivity during Muscle Fatigue. Neural Plast 2016:1726848|
|Bayram, Mehmed Bugrahan; Siemionow, Vlodek; Yue, Guang H (2015) Weakening of Corticomuscular Signal Coupling During Voluntary Motor Action in Aging. J Gerontol A Biol Sci Med Sci 70:1037-43|
|Sankarasubramanian, Vishwanath; Roelle, Sarah M; Bonnett, Corin E et al. (2015) Reproducibility of transcranial magnetic stimulation metrics in the study of proximal upper limb muscles. J Electromyogr Kinesiol 25:754-64|
|Plow, Ela B; Varnerin, Nicole; Cunningham, David A et al. (2014) Age-related weakness of proximal muscle studied with motor cortical mapping: a TMS study. PLoS One 9:e89371|
|Plow, Ela B; Cunningham, David A; Bonnett, Corin et al. (2013) Neurophysiological correlates of aging-related muscle weakness. J Neurophysiol 110:2563-73|
|Cunningham, David A; Machado, Andre; Yue, Guang H et al. (2013) Functional somatotopy revealed across multiple cortical regions using a model of complex motor task. Brain Res 1531:25-36|
|Yao, Wan X; Ranganathan, Vinoth K; Allexandre, Didier et al. (2013) Kinesthetic imagery training of forceful muscle contractions increases brain signal and muscle strength. Front Hum Neurosci 7:561|
|Wang, Xiao-Feng; Jiang, Zhiguo; Daly, Janis J et al. (2012) A generalized regression model for region of interest analysis of fMRI data. Neuroimage 59:502-10|
|Wang, X F; Yang, Qi; Fan, Zhaozhi et al. (2009) Assessing time-dependent association between scalp EEG and muscle activation: A functional random-effects model approach. J Neurosci Methods 177:232-40|
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