It is well known that to strengthen a muscle one should perform training involving heavy loads or resistance. Recently we have found that substantial voluntary strength gains can be achieved with training involving low resistance but strong mental effort. In contrast, individuals who trained with the same low-intensity contractions but with low mental effort had no improvement in strength. Based on these preliminary findings, we hypothesize that muscle strength improvements depend primarily on the level of mental effort during training, not the training intensity (resistance) per se. The reason that high-intensity training always increases strength is because mental effort is high during high-intensity muscle contractions.
Aim 1 of the project is to compare the effects of training with different levels of mental effort on the improvement in muscle strength. Four groups of elderly subjects (greater than or equal to 65 years) will participate in a 12-week training study involving elbow-flexor muscles. One group will be trained with an intensity near the level of maximal voluntary contraction (MVC group); a second group will be trained with high mental-effort, low muscle-intensity elbow-flexion contractions (LME group); and the fourth (control) group will not be trained will participate in the strength tests. We expect that the strength improvement after training will be: MVC group > HME group > LME group = control group. We also expect that the strength increase in the MVC and HME groups will result in an improvement in daily living function.
Aim 2 is determine the neural mechanisms underlying muscle strength improvements. We hypothesize that an increase in the central nervous system (CNS) drive is the primary mechanism that mediates strength improvements induced by low-intensity training (HME group). To evaluate the CNS drive, four measurements will be made using the same subjects and groups as in Ami 1: brain activation level examined by functional MRI (fMRI) and EEG-derived motor activity-related cortical potential (MRCP), surface EMG signals, and the MRI T2 relaxation time obtained from the trained muscles. We expect to find that after training: (1) the brain activation level (fMRI and MRCP), EMG, and MRI T2 will significantly increase in the MVC and HME groups; and (2) the amplitude of increases in these measurements will be: MVC group = HME group > LME group = control group. The knowledge gained from these studies will substantially advance the current understanding of mechanisms underlying human voluntary muscle strengthening and will have direct application in neuromuscular rehabilitation for older adults and individuals who are physically handicapped and unable to perform repeated, forceful muscle contractions.

Agency
National Institute of Health (NIH)
Institute
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Type
Research Project (R01)
Project #
1R01HD036725-01A1
Application #
2879652
Study Section
Geriatrics and Rehabilitation Medicine (GRM)
Program Officer
Ansel, Beth
Project Start
1999-09-27
Project End
2003-05-31
Budget Start
1999-09-27
Budget End
2000-05-31
Support Year
1
Fiscal Year
1999
Total Cost
Indirect Cost
Name
Cleveland Clinic Lerner
Department
Type
DUNS #
017730458
City
Cleveland
State
OH
Country
United States
Zip Code
44195
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
Zhang, Luduan; Butler, Andrew J; Sun, Chang-Kai et al. (2008) Fractal dimension assessment of brain white matter structural complexity post stroke in relation to upper-extremity motor function. Brain Res 1228:229-40
Liu, Jing Z; Lewandowski, Beth; Karakasis, Chris et al. (2007) Shifting of activation center in the brain during muscle fatigue: an explanation of minimal central fatigue? Neuroimage 35:299-307
Zhang, Luduan; Dean, David; Liu, Jing Z et al. (2007) Quantifying degeneration of white matter in normal aging using fractal dimension. Neurobiol Aging 28:1543-55
Boyd, Lara A; Vidoni, Eric D; Daly, Janis J (2007) Answering the call: the influence of neuroimaging and electrophysiological evidence on rehabilitation. Phys Ther 87:684-703
Yao, Bing; Salenius, Stephen; Yue, Guang H et al. (2007) Effects of surface EMG rectification on power and coherence analyses: an EEG and MEG study. J Neurosci Methods 159:215-23
Daly, Janis J; Fang, Yin; Perepezko, Elizabeth M et al. (2006) Prolonged cognitive planning time, elevated cognitive effort, and relationship to coordination and motor control following stroke. IEEE Trans Neural Syst Rehabil Eng 14:168-71
Zhang, Luduan; Liu, Jing Z; Dean, David et al. (2006) A three-dimensional fractal analysis method for quantifying white matter structure in human brain. J Neurosci Methods 150:242-53
Liu, Jing Z; Yao, Bing; Siemionow, Vlodek et al. (2005) Fatigue induces greater brain signal reduction during sustained than preparation phase of maximal voluntary contraction. Brain Res 1057:113-26
Shan, Zu Y; Liu, Jing Z; Sahgal, Vinod et al. (2005) Selective atrophy of left hemisphere and frontal lobe of the brain in old men. J Gerontol A Biol Sci Med Sci 60:165-74

Showing the most recent 10 out of 25 publications