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Jing Z. Liu

Bio: Jing Z. Liu is an academic researcher from Cleveland Clinic. The author has contributed to research in topics: Muscle fatigue & Electromyography. The author has an hindex of 23, co-authored 29 publications receiving 2580 citations. Previous affiliations of Jing Z. Liu include Cleveland Clinic Lerner Research Institute & Case Western Reserve University.

Papers
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Journal ArticleDOI
TL;DR: The similarity in the relationship between muscle output and fMRI signal in the cortical regions suggests that correlated or networked activation among a number of cortical fields may be necessary for controlling precise static force of finger muscles.
Abstract: The relationship between functional MRI (fMRI)-measured brain signal and muscle force and or electromyogram (EMG) is critical in interpreting fMRI data and understanding the control mechanisms of voluntary motor actions. We designed a system that could record joint force and surface EMG online with fMRI data. High-quality force and EMG data were obtained while maintaining the quality of the fMRI brain images. Using this system, we determined the relationship between fMRI-measured brain activation and handgrip force and between fMRI-measured brain signal and EMG of extrinsic finger muscles. Ten volunteers participated in the experiments (only seven subjects' data were analyzed due to excessive noise in the fMRI data of three subjects). The participants exerted 20%, 35%, 50%, 65%, and 80% of the maximal force. During each contraction period, handgrip force, surface EMG of the finger flexor and extensor muscles, and fMRI brain images were acquired. The degree of muscle activation (force and EMG) was directly proportional to the amplitude of the brain signal determined by fMRI in the entire brain and in a number of motor function-related cortical fields, including primary motor, sensory regions, supplementary motor area, premotor, prefrontal, parietal and cingulate cortices, and cerebellum. All the examined brain areas demonstrated a similar relationship between the fMRI signal and force. A stronger fMRI signal during higher force indicates that more cortical output neurons and/or interneurons may participate in generating descending commands and/or processing additional sensory information. The similarity in the relationship between muscle output and fMRI signal in the cortical regions suggests that correlated or networked activation among a number of cortical fields may be necessary for controlling precise static force of finger muscles.

298 citations

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TL;DR: It is concluded that the mental training employed by this study enhances the cortical output signal, which drives the muscles to a higher activation level and increases strength.

279 citations

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TL;DR: The results showed that the brain increased its output to reinforce the muscle for the continuation of the performance and possibly to process additional sensory information.
Abstract: During prolonged submaximal muscle contractions, electromyographic (EMG) signals typically increase as a result of increasing motor unit activities to compensate for fatigue-induced force loss in the muscle. It is thought that cortical signals driving the muscle to higher activation levels also increases, but this has never been experimentally demonstrated. The purpose of this study was to quantify brain activation during submaximal fatigue muscle contractions using functional magnetic resonance imaging (fMRI). Twelve volunteers performed a sustained handgrip contraction for 225 s and 320 intermittent handgrip contractions ( approximately 960 s) at 30% maximal level while their brain was imaged. For the sustained contraction, EMG signals of the finger flexor muscles increased linearly while the target force was maintained. The fMRI-measured cortical activities in the contralateral sensorimotor cortex increased sharply during the first 150 s, then plateaued during the last 75 s. For the intermittent contractions, the EMG signals increased during the first 660 s and then began to decline, while the handgrip force also showed a sign of decrease despite maximal effort to maintain the force. The fMRI signal of the contralateral sensorimotor area showed a linear rise for most part of the task and plateaued at the end. For both the tasks, the fMRI signals in the ipsilateral sensorimotor cortex, prefrontal cortex, cingulate gyrus, supplementary motor area, and cerebellum exhibited steady increases. These results showed that the brain increased its output to reinforce the muscle for the continuation of the performance and possibly to process additional sensory information.

246 citations

Journal ArticleDOI
TL;DR: The results suggest that MRCP represents cortical motor commands that scale the level of muscle activation, and was highly correlated with elbow-flexion force, rate of rising of force, and muscle EMG signals.
Abstract: The purpose of this study was to investigate the relationship between EEG-derived motor activity-related cortical potential (MRCP) and voluntary muscle activation. Eight healthy volunteers participated in two experimental sessions. In one session, subjects performed isometric elbow-flexion contractions at four intensity levels [10%, 35%, 60%, and 85% maximal voluntary contraction (MVC)]. In another session, a given elbow-flexion force (35% MVC) was generated at three different rates (slow, intermediate, and fast). Thirty to 40 contractions were performed at each force level or rate. EEG signals were recorded from the scalp overlying the supplementary motor area (SMA) and contralateral sensorimotor cortex, and EMG signals were recorded from the skin surface overlying the belly of the biceps brachii and brachioradialis muscles during all contractions. In each trial, the force was used as the triggering signal for MRCP averaging. MRCP amplitude was measured from the beginning to the peak of the negative slope. The magnitude of MRCP from both EEG recording locations (sensorimotor cortex and SMA) was highly correlated with elbow-flexion force, rate of rising of force, and muscle EMG signals. These results suggest that MRCP represents cortical motor commands that scale the level of muscle activation.

173 citations

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TL;DR: In this article, a dynamical model is presented as a framework for muscle activation, fatigue, and recovery by describing the effects of muscle fatigue and recovery in terms of two phenomenological parameters (F, R).

151 citations


Cited by
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Journal ArticleDOI
06 Jun 1986-JAMA
TL;DR: The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or her own research.
Abstract: I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

7,563 citations

Journal ArticleDOI
TL;DR: Recent studies examining spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal of functional magnetic resonance imaging as a potentially important and revealing manifestation of spontaneous neuronal activity are reviewed.
Abstract: The majority of functional neuroscience studies have focused on the brain's response to a task or stimulus. However, the brain is very active even in the absence of explicit input or output. In this Article we review recent studies examining spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal of functional magnetic resonance imaging as a potentially important and revealing manifestation of spontaneous neuronal activity. Although several challenges remain, these studies have provided insight into the intrinsic functional architecture of the brain, variability in behaviour and potential physiological correlates of neurological and psychiatric disease.

6,135 citations

Journal ArticleDOI
TL;DR: This eighth edition of exercise physiology is updated with the latest research in the field to give you easy to understand up to date coverage of how nutrition energy transfer and exercise training affect human performance.

1,328 citations

Journal ArticleDOI
TL;DR: This is the first meta-analysis of sex differences in the typical human brain and regional sex differences overlap with areas implicated in psychiatric conditions.

849 citations

Journal ArticleDOI
TL;DR: The aim of this review is to explain and to categorize the various algorithms into groups and their application in the field of medical signal analysis.

839 citations