Guang H. Yue

Effects of aging on hand function

OBJECTIVES: The purpose of this study was to quantify age‐induced changes in handgrip and finger‐pinch strength, ability to maintain a steady submaximal finger pinch force and pinch posture, speed in relocating small objects with finger grip, and ability to discriminate two identical mechanical stimuli applied to the finger tip.

Relationship between motor activity-related cortical potential and voluntary muscle activation.

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.

A dynamical model of muscle activation, fatigue, and recovery.

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), we develop a set of dynamical equations to describe the behavior of muscles as a group of motor units activated by voluntary effort. This model provides a macroscopic view for understanding biophysical mechanisms of voluntary drive, fatigue effect, and recovery in stimulating, limiting, and modulating the force output from muscles. The model is investigated under the condition in which brain effort is assumed to be constant. Experimental validation of the model is performed by fitting force data measured from healthy human subjects during a 3-min sustained maximal voluntary handgrip contraction. The experimental results confirm a theoretical inference from the model regarding the possibility of maximal muscle force production, and suggest that only 97% of the true maximal force can be reached under maximal voluntary effort, assuming that all motor units can be recruited voluntarily. The effects of different motor unit types, time-dependent brain effort, sources of artifacts, and other factors that could affect the model are discussed. The applications of the model are also discussed.

Distinct brain activation patterns for human maximal voluntary eccentric and concentric muscle actions.

Eccentric muscle contractions generate greater force at a lower level of activation and subject muscles to more severe damage than do concentric actions. A recent investigation has revealed that electroencephalogram (EEG)-derived movement-related cortical potential (MRCP) is greater and occurs earlier for controlling human eccentric than concentric submaximal muscle contractions. However, whether the central nervous system (CNS) control signals for high-intensity or maximal-effort eccentric movements differ from those for concentric actions is unknown. The purpose of this study was to determine whether the MRCP signals differ between the two types of maximal-effort contractions. Eight volunteers performed 40 maximal voluntary eccentric and 40 maximal voluntary concentric elbow flexor contractions on a Kin-Com isokinetic dynamometer. Scalp EEG signals (62 channels) were measured along with force, joint angle, and electromyographic (EMG) signals of the performing muscles. MRCP-based two-dimensional brain maps were created to illustrate spatial and temporal distributions of the MRCP signals. Although the level of elbow flexor muscle activity was lower during eccentric than concentric movements, MRCP-indicated cortical activation was greater both in amplitude and area dimension for the eccentric task. Detailed comparisons of individual electrode signals suggested that eccentric movements needed a significantly longer time for early preparation and a significantly greater magnitude of cortical activity for later movement execution. The extra preparation time and higher amplitude of activation may reflect CNS activities that account for the higher risk of injury, higher degree of movement difficulty, and unique motor unit activation pattern associated with maximal-level eccentric muscle actions.

Simultaneous measurement of human joint force, surface electromyograms, and functional MRI-measured brain activation

Functional magnetic resonance imaging (fMRI) has been increasingly used in studying human brain function given its non-invasive feature and good spatial resolution. However, difficulties in acquiring data from peripheral (e.g. information from muscle) during fMRI studies of motor function hinder interpretation of fMRI data and designing more sophisticated investigations. Here we describe a system that was designed to concurrently measure handgrip force, surface electromyograms (EMG) of finger flexor and extensor muscles, and fMRI of human brain. The system included a pressure transducer built in a hydraulic environment, a heavily shielded EMG recording element, and a visual feedback structure for online monitoring of force and/or EMG signal, by the subject positioned in the scanner during an fMRI experiment. System evaluation and subsequent fMRI motor function studies have indicated that by using this system, high quality force and EMG signals can be recorded without sacrificing the quality of the fMRI data.

A three-dimensional fractal analysis method for quantifying white matter structure in human brain

Fractal dimension (FD) is increasingly used to quantify complexity of brain structures. Previous research that analyzed FD of human brain mainly focused on two-dimensional measurements. In this study, we developed a three-dimensional (3D) box-counting method to measure FD of human brain white matter (WM) interior structure, WM surface and WM general structure simultaneously. This method, which firstly incorporates a shape descriptor (3D skeleton) representing interior structure and combines the three features, provides a more comprehensive characterization of WM structure. WM FD of different brain segments was computed to test robustness of the method. FDs of fractal phantoms were computed to test the accuracy of the method. The consistency of the computed and theoretical FD values suggests that our method is accurate in measuring FDs of fractals. Statistical analysis was performed to examine sensitivity of the method in detecting WM structure differences in a number of young and old subjects. FD values of the WM skeleton and surface were significantly greater in young than old individuals, indicating more complex WM structures in young people. These results suggest that our method is accurate in quantifying three-dimensional brain WM structures and sensitive in detecting age-related degeneration of the structures.

Nonlinear cortical modulation of muscle fatigue: A functional MRI study

Muscle fatigue has been studied for over a century, but almost no data are available to indicate how the brain perceives fatigue and modulates its signals to the fatiguing muscle. In this study, brain activation was measured by functional magnetic resonance imaging (fMRI) during a sustained (2-min) maximal-effort handgrip contraction while handgrip force and finger muscle electromyographic (EMG) data were recorded simultaneously by a magnetic resonance environment-adapted force-EMG measurement system. The results showed decoupled progresses in brain and muscle activities when muscle was fatigued and correlated behaviors among the cortical areas being analyzed. While handgrip force and EMG signals declined in parallel during the course of muscle fatigue, fMRI-measured brain activities first substantially increased and then decreased. This similar signal modulation occurred not only in the primary sensorimotor areas but also in the secondary and association cortices (supplementary motor, prefrontal, and cingulate areas). The nonlinear changes of brain signal may reflect an early adjustment to strengthen the descending command for force-loss compensation and subsequent inhibition by sensory feedback as fatigue became more severe. The close association in the activation pattern in many cortical regions may reflect integrated processing of information in the brain.

Quantifying degeneration of white matter in normal aging using fractal dimension

Although degeneration of brain white matter (WM) in aging is a well-recognized problem, its quantification has mainly relied on volumetric measurements, which lack detail in describing the degenerative adaptation. In this study, WM structural complexity was evaluated in healthy old and young adults by analyzing the three-dimensional fractal dimension (FD) of WM segmented from magnetic resonance images of brain. FDs detected in the old were significantly smaller than in the young subjects. Specifically, WM interior structure complexity degenerated in the left hemisphere in old men but in the right hemisphere in old women. Men showed more complex WM patterns than women. An asymmetrical (right-greater-than-left-hemisphere) complexity pattern was observed in the interior and general structures of WM, yet the surface complexity was symmetrical across WM structures of the two hemispheres. WM volumes were also measured, but no significant decline was found with aging. These results suggest that the deterioration of WM complexity is not uniformly distributed between the genders and across brain hemispheres.

Fractal Dimension in Human Cerebellum Measured by Magnetic Resonance Imaging

Fractal dimension has been used to quantify the structures of a wide range of objects in biology and medicine. We measured fractal dimension of human cerebellum (CB) in magnetic resonance images of 24 healthy young subjects (12 men and 12 women). CB images were resampled to a series of image sets with different 3D resolutions. At each resolution, the skeleton of the CB white matter was obtained and the number of pixels belonging to the skeleton was determined. Fractal dimension of the CB skeleton was calculated using the box-counting method. The results indicated that the CB skeleton is a highly fractal structure, with a fractal dimension of 2.57 +/- 0.01. No significant difference in the CB fractal dimension was observed between men and women.

Effects of surface EMG rectification on power and coherence analyses: an EEG and MEG study.

Coherence between electromyography (EMG) and electroencephalography (EEG) or magnetoencephalography (MEG) is frequently examined to gain insights on neuromuscular binding. Commonly, EMG signals are rectified before coherence is computed. However, the appropriateness of EMG rectification in computing EMG-EEG/MEG coherence has never been validated. Since rectification is a non-linear operation and alters the EMG power spectrum, such a validation is important to ensure the accuracy of coherence calculation. In this study we experimentally investigated the effects of EMG rectification on EMG power spectra and its coherence with EEG/MEG signals. Subjects performed sustained isometric index finger abduction at approximately 5-10% maximal voluntary force (in both EEG-EMG and MEG-EMG experiments) and index finger tapping at approximately 2-4Hz (in EEG-EMG experiment only). Bipolar surface EMG data from the first dorsal interosseus (FDI) and EEG/MEG signals from the contralateral primary sensorimotor area (C3) were recorded simultaneously. Power spectra and coherence with the EEG/MEG were calculated before and after EMG rectification. The results show that rectification shifts EMG power to lower frequencies, possibly enhancing peaks of motor unit firing. Coherences with the EEG/MEG signals were not significantly changed by EMG rectification, indicating EMG rectification is overall an appropriate procedure in power and coherence analyses.