Beta-Adrenergic Modulation of Tremor and Corticomuscular Coherence in Humans

Coherence between the bioelectric activity of sensorimotor cortex and contralateral muscles can be observed around 20 Hz. By contrast, physiological tremor has a dominant frequency around 10 Hz. Although tremor has multiple sources, it is partly central in origin, reflecting a component of motoneuron discharge at this frequency. The motoneuron response to ∼20 Hz descending input could be altered by non-linear interactions with ∼10 Hz motoneuron firing. We investigated this further in eight healthy human subjects by testing the effects of the beta-adrenergic agents propranolol (non-selective β-antagonist) and salbutamol (β₂-agonist), which are known to alter the size of physiological tremor. Corticomuscular coherence was assessed during an auxotonic precision grip task; tremor was quantified using accelerometry during index finger extension. Experiments with propranolol used a double-blind, placebo-controlled crossover design. A single oral dose of propranolol (40 mg) significantly increased beta band (15.3–32.2 Hz) corticomuscular coherence compared with placebo, but reduced tremor in the 6.2–11.9 Hz range. Salbutamol (2.5 mg) was administered by inhalation. Whilst salbutamol significantly increased tremor amplitude as expected, it did not change corticomuscular coherence. The opposite direction of the effects of propranolol on corticomuscular coherence and tremor, and the fact that salbutamol enhances tremor but does not affect coherence, implies that the magnitude of corticomuscular coherence is little influenced by non-linear interactions with 10 Hz oscillations in motoneurons or the periphery. Instead, we suggest that propranolol and salbutamol may affect both tremor and corticomuscular coherence partly via a central site of action.     

Cross-spectral analysis of physiological tremor and muscle activity

We investigate the relationship between the extensor electromyogram (EMG) and tremor time series in physiological hand tremor by cross-spectral analysis. Special attention is directed to the phase spectrum and the effects of observational noise. We calculate the theoretical phase spectrum for a second-order linear stochastic process and compare the results to measured tremor data recorded from subjects who did not show a synchronized EMG activity in the corresponding extensor muscle. The results show that physiological tremor is well described by the proposed model and that the measured EMG represents a Newtonian force by which the muscle acts on the hand. Received: 7 October 1996 / Accepted in revised form: 29 January 1998     

The impact of localized fatigue on contralateral tremor and muscle activity is exacerbated by standing posture

Physiological tremor is an inherent feature of the motor system that is influenced by intrinsic (neuromuscular) and/or extrinsic (task) factors. Given that tremor must be accounted for during the performance of many fine motor skills; there is a requirement to clarify how different factors interact to influence tremor. This study was designed to assess the impact localized fatigue of a single arm and stance position had on bilateral physiological tremor and forearm muscle activity. Results demonstrated that unilateral fatigue produced bilateral increases in tremor and wrist extensor activity. For example, fatigue resulted in increases in extensor activity across both exercised (increased 8–10% MVC) and the non-exercised arm (increased 3–7% MVC). The impact of fatigue was not restricted to changes in tremor/EMG amplitude, with altered hand–finger coupling observed within both arms. Within the exercised arm, cross-correlation values decreased (pre-exercise r = 0.62–0.64; post-exercise r = 0.37–0.43) while coupling increased within the non-exercised arm (pre-exercise r = 0.51–0.55; post-exercise r = 0.62–0.67). While standing posture alone had no significant impact on tremor/EMG dynamics, the tremor and muscle increases seen with fatigue were more pronounced when standing. Together these results demonstrate that the combination of postural and fatigue factors can influence both tremor/EMG outputs and the underlying coordinative coupling dynamics.     

Frequency and displacement amplitude relations for normal hand tremor.

Spectral analysis of hand tremor records obtained from normal subjects during continuous extension of the hand for 15-45 min revealed that the root-mean-square (rms) displacement amplitude of the tremor increased from control levels of about 30 mum to levels on the order of 100-1,000 times control. Associated with this increase in the displacement was a systematic decrease in the hand tremor frequency from control values of 8-9 Hz to values of 4-6 Hz. Spectral analysis of demodulated extensor EMG records indicated a consistent relation between EMG modulation amplitude at the tremor frequency and the tremor displacement amplitude for tremor records with rms displacement above about 100 mum. No consistent relation was found between these two variables for tremor records with displacements below 100 mum. Consideration of both mechanical and neural reflex effects indicated that a viscoelastic-mass mechanism primarily determined the small-amplitude (less than 100 mum) tremors, while the large displacement tremors may have involved both mechanical and neural feed back factors.     

Muscle activation characteristics associated with differences in physiological tremor amplitude between the dominant and non-dominant hand

The aim of this study was to assess differences in physiological tremor amplitude of the hand between the dominant and non-dominant side of right-handed individuals. Mechanical loading of the hand and frequency analysis were used in an attempt to identify the physiological mechanisms involved in observed differences. Seventeen healthy right-handed adults participated in a single session where physiological tremor of the outstretched left and right hands was recorded under different loading conditions (0 g up to 5614 g). Physiological tremor amplitude was quantified through accelerometry and electromyographic (EMG) signals of wrist extensor and flexor muscles were also recorded. The main findings were: ～30% greater amplitude of fluctuations in acceleration for the non-dominant compared with the dominant hand, no difference in the frequency content of acceleration or demodulated EMG signals between dominant and non-dominant sides across all loads, and condition-dependent associations between the amplitude of fluctuations in acceleration and EMG amplitude and frequency content. These associations suggest a potential role of central modulation of neural activity to explain dominance-related differences in physiological tremor amplitude of the hand.     

The effect of changes in joint angle on the characteristics of physiological tremor

IntroductionPhysiological tremor, as a whole, can be influenced by changes in muscle activity. However, the origin of low-frequency physiological tremor oscillations has yet to be conclusively determined. It is possible that by experimentally manipulating muscular activity, a better determination of the origin of those low-frequency oscillations can be achieved. It was demonstrated that changes in joint angle modify characteristics of muscular activity. As such, we hypothesize that changes in wrist-joint angle will alter the characteristics of low-frequency physiological tremor oscillations.ObjectiveAssess the influence of changes in joint angle of the wrist on characteristics of physiological finger tremor.MethodsPhysiological finger tremor was recorded (n = 25) using a laser displacement system while the arm and hand were supported. The relative angle between the dorsum of the hand and the forearm was altered between conditions (135°, 180°, 225° and 270°), while the hand and the finger remained parallel to the ground. EMG of the extensors and flexors were also recorded.ResultsTremor amplitude was significantly altered by changes in wrist-joint angle. This was especially the case for lower frequency oscillations. In addition, electromyography properties of forearm muscles were also significantly modified by changes in wrist-joint angles.ConclusionsThis study demonstrates that changes in wrist-joint angle modify the characteristics of physiological finger tremor. This should be taken into account when interpreting tremor data as well as when developing tools to minimize tremor.     

Changes in kinematic and EMG variability while practicing a maximal performance task.

This paper examines changes in the variability of electromyographic (EMG) activity and kinematics as a result of practicing a maximal performance task. Eight subjects performed rapid elbow flexion to a target in the horizontal plane. Four hundred trials were distributed equally over four practice sessions. A potentiometer at the elbow axis of rotation of a manipulandum recorded the angular displacement. The EMG activity of the biceps and the triceps brachii was monitored using Beckman surface electrodes. Limb speed increased while both target error and trajectory (velocity versus position) variability decreased. There was an increase in the absolute measure of total EMG variability (the first standard deviation at each point of the biceps and triceps waveform multiplied together). However, the coefficient of variation (the first standard deviation divided by the mean and the result multiplied by 100) of the mean amplitude value of the individual EMG bursts decreased. The variability of triceps motor time also decreased while the variability biceps motor time remained unchanged. The results demonstrated a clear relationship between kinematic and EMG variability. The EMG and the trajectory data suggest that practice resulted in greater central nervous system control over both the spatial-temporal aspects of movement and the magnitude of the biceps and triceps muscle force-impulses.     

Physiological and pathological oscillatory networks in the human motor system.

Human brain functions are heavily contingent on neural interactions both at the single neuron and the neural population or system level. Accumulating evidence from neurophysiological studies strongly suggests that coupling of oscillatory neural activity provides an important mechanism to establish neural interactions. With the availability of whole-head magnetoencephalography (MEG) macroscopic oscillatory activity can be measured non-invasively from the human brain with high temporal and spatial resolution. To localise, quantify and map oscillatory activity and interactions onto individual brain anatomy we have developed the 'dynamic imaging of coherent sources' (DICS) method which allows to identify and analyse cerebral oscillatory networks from MEG recordings. Using this approach we have characterized physiological and pathological oscillatory networks in the human sensorimotor system. Coherent 8 Hz oscillations emerge from a cerebello-thalamo-premotor-motor cortical network and exert an 8 Hz oscillatory drive on the spinal motor neurons which can be observed as a physiological tremulousness of the movement termed movement discontinuities. This network represents the neurophysiological substrate of a discrete mode of motor control. In parkinsonian resting tremor we have identified an extensive cerebral network consisting of primary motor and lateral premotor cortex, supplementary motor cortex, thalamus/basal ganglia, posterior parietal cortex and secondary somatosensory cortex, which are entrained in the tremor or twice the tremor rhythm. This low frequency entrapment of motor areas likely plays an important role in the pathophysiology of parkinsonian motor symptoms. Finally, studies on patients with postural tremor in hepatic encephalopathy revealed that this type of tremor results from a pathologically slow thalamocortical and cortico-muscular coupling during isometric hold tasks. In conclusion, the analysis of oscillatory cerebral networks provides new insights into physiological mechanisms of motor control and pathophysiological mechanisms of tremor disorders.     

Neuromuscular fatigue during maximal concurrent hand grip and elbow flexion or extension.

The objective was to investigate muscle fatigue measuring changes in force output and force tremor and electromyographic activity (EMG) during two sustained maximal isometric contractions for 60s: (1) concurrent hand grip and elbow flexion (HG and EF); or (2) hand grip and elbow extension (HG and EE). Each force tremor amplitude was decomposed into four frequency bands (1-3, 4-10, 11-20, and 21-50Hz). Surface EMGs were recorded from the flexor digitorum superficialis (FDS), extensor digitorum (ED), biceps brachii (BB) and lateral head of triceps brachii (TB). The HG and EF forces for the HG and EF and the HG force for the HG and EE declined rapidly, whereas the EE force remained almost constant near to the initial value for the first 40s and then declined. The decrease in EMG amplitude was observed not for the FDS muscle but for the ED muscle. The HG tremor amplitude for each frequency band showed similar decreasing rate, whereas the decreases in EF and EE tremor amplitudes for the lower band (below 10Hz) were slower than those for the higher band (above 11Hz). The neuromuscular mechanisms underlying muscle fatigue during sustained maximal concurrent contractions of hand grip and elbow flexion or extension are discussed.     

Atypical task-invariant organization of multi-segment tremors in patients with Parkinson’s disease during manual tracking

The objective of the study was to investigate the interplay between involuntary tremulous activities and task performance under volitional control for patients with Parkinson’s disease (PD) during position tracking. A volunteer sample of nine untreated patients and nine age-matched healthy subjects participated in this study. They performed a sinusoidal tracking maneuver with a shoulder and a static pointing task; meanwhile, a position trace of the index and accelerometer data in the upper limb were recorded to characterize tracking performance and postural–kinetic tremors. In reference to postural tremor, the kinetic tremor of control subjects during tracking was considerably modulated, leading to a lower regularity and greater spectral deviation. In contrast, patients with PD demonstrated greater postural and kinetic tremors than control subjects, and tremulous movements of the patients were comparatively task-invariant. The prominent coherence peak, which occurred at 8–12 Hz in control subjects, was atypically presented at 5–8 Hz for PD patients with poorer tracking performance. Functionally, congruency of position tracking was related to amplitude of kinetic tremor after subtracting from amplitude of postural tremor. In conclusion, task-dependent organization of tremulous movements was impaired in patients with PD. The inferior tracking performance of the patients correlated implicitly with kinetic tremor, signifying some sharing of neural substrates for manual tracking and tremor generation.     

Force Control Is Related to Low-Frequency Oscillations in Force and Surface EMG

Force variability during constant force tasks is directly related to oscillations below 0.5 Hz in force. However, it is unknown whether such oscillations exist in muscle activity. The purpose of this paper, therefore, was to determine whether oscillations below 0.5 Hz in force are evident in the activation of muscle. Fourteen young adults (21.07±2.76 years, 7 women) performed constant isometric force tasks at 5% and 30% MVC by abducting the left index finger. We recorded the force output from the index finger and surface EMG from the first dorsal interosseous (FDI) muscle and quantified the following outcomes: 1) variability of force using the SD of force; 2) power spectrum of force below 2 Hz; 3) EMG bursts; 4) power spectrum of EMG bursts below 2 Hz; and 5) power spectrum of the interference EMG from 10–300 Hz. The SD of force increased significantly from 5 to 30% MVC and this increase was significantly related to the increase in force oscillations below 0.5 Hz (R ² = 0.82). For both force levels, the power spectrum for force and EMG burst was similar and contained most of the power from 0–0.5 Hz. Force and EMG burst oscillations below 0.5 Hz were highly coherent (coherence = 0.68). The increase in force oscillations below 0.5 Hz from 5 to 30% MVC was related to an increase in EMG burst oscillations below 0.5 Hz (R ² = 0.51). Finally, there was a strong association between the increase in EMG burst oscillations below 0.5 Hz and the interference EMG from 35–60 Hz (R ² = 0.95). In conclusion, this finding demonstrates that bursting of the EMG signal contains low-frequency oscillations below 0.5 Hz, which are associated with oscillations in force below 0.5 Hz.     

Influence of amplitude cancellation on the simulated surface electromyogram.

The purpose of the study was to quantify the influence of selected motor unit properties and patterns of activity on amplitude cancellation in the simulated surface electromyogram (EMG). The study involved computer simulations of a motor unit population with physiologically defined recruitment and rate coding characteristics that activated muscle fibers whose potentials were recorded on the skin over the muscle. Amplitude cancellation was quantified as the percent difference in signal amplitude when motor unit potentials were summed before and after rectification. The simulations involved varying the level of activation for the motor unit population, the recording configuration, the upper limit of motor unit recruitment, peak discharge rates, the amount of motor unit synchronization, muscle fiber length, the thickness of the subcutaneous tissue, and the motor unit properties that change with advancing age. The results confirmed a previous experimental report (Day SJ and Hulliger M, J Neurophysiol 86: 2144-2158, 2001) that amplitude cancellation in the surface EMG can reach 62% at maximal activation. A decrease in the range of amplitudes of the motor unit potentials, as can occur during fatiguing contractions, increased amplitude cancellation up to approximately 85%. Differences in the amount of amplitude cancellation were observed across all simulated conditions, and resulted in substantial changes in the absolute magnitude of the EMG signal. The most profound factors influencing amplitude cancellation were the number of active motor units and the duration of the action potentials. The effects of amplitude cancellation were minimal (<5%) when the EMG amplitude was normalized to maximal values, with the exception of variations in peak discharge rate and recruitment range, which resulted in differences up to 17% in the normalized EMG signal across conditions. These results indicate the amount of amplitude cancellation that can occur in various experimental conditions and its influence on absolute and relative measures of EMG amplitude.     

Modeling nonlinear errors in surface electromyography due to baseline noise: A new methodology

The surface electromyographic (EMG) signal is often contaminated by some degree of baseline noise. It is customary for scientists to subtract baseline noise from the measured EMG signal prior to further analyses based on the assumption that baseline noise adds linearly to the observed EMG signal. The stochastic nature of both the baseline and EMG signal, however, may invalidate this assumption. Alternately, “true” EMG signals may be either minimally or nonlinearly affected by baseline noise. This information is particularly relevant at low contraction intensities when signal-to-noise ratios (SNR) may be lowest. Thus, the purpose of this simulation study was to investigate the influence of varying levels of baseline noise (approximately 2–40% maximum EMG amplitude) on mean EMG burst amplitude and to assess the best means to account for signal noise. The simulations indicated baseline noise had minimal effects on mean EMG activity for maximum contractions, but increased nonlinearly with increasing noise levels and decreasing signal amplitudes. Thus, the simple baseline noise subtraction resulted in substantial error when estimating mean activity during low intensity EMG bursts. Conversely, correcting EMG signal as a nonlinear function of both baseline and measured signal amplitude provided highly accurate estimates of EMG amplitude. This novel nonlinear error modeling approach has potential implications for EMG signal processing, particularly when assessing co-activation of antagonist muscles or small amplitude contractions where the SNR can be low.     

Physiological evidence for central modulation of voice tremor

The present report presents an attempt to define the physiological parameter used to describe “voice tremor” in psychological stress evaluating machines, and to find its sources. This parameter was found to be a low frequency (5–20 Hz) random process which frequency modulates the vocal cord waveform and (independently) affects the frequency range of the third speech formant. The frequency variations in unstressed speakers were found to be the result of forced muscular undulations driven by central nervous signals and not of a passive resonant phenomenon. In this paper various physiological and clinical experiments which lead to the above conclusions are discussed. a) It is shown that induced muscular activity in the vocal tract and vocal cord regions can generate tremor in the voice. b) It is shown that relaxed subjects exhibit significant tremor correlation between spontaneously generated speech and EMG, with the EMG leading the speech tremor. c) Tremor in the electrical activity recorded from muscles overlapping vocal tract area was correlated with third formant demodulated signal and vocal cord demodulated pitch tremor was correlated with first formant demodulated tremor. d) Enhanced tremor was found in Parkinson patients and diminished tremor in patients with some traumatic brain injuries.     

Surface electromyography as a tool to assess the responses of car passengers to lateral accelerations: Part I. Extraction of relevant muscular activities from noisy recordings

The aim of this paper is to develop a method to extract relevant activities from surface electromyography (SEMG) recordings under difficult experimental conditions with a poor signal to noise ratio. High amplitude artifacts, the QRS complex, low frequency noise and white noise significantly alter EMG characteristics. The CEM algorithm proved to be useful for segmentation of SEMG signals into high amplitude artifacts (HAA), phasic activity (PA) and background postural activity (BA) classes. This segmentation was performed on signal energy, with classes belonging to a χ² distribution. Ninety-five percent of HAA events and 96.25% of BA events were detected, and the remaining noise was then identified using AR modeling, a classification based upon the position of the coordinates of the pole of highest module. This method eliminated 91.5% of noise and misclassified only 3.3% of EMG events when applied to SEMG recorded on passengers subjected to lateral accelerations.     

Single motor unit and fiber action potentials during fatigue

Muscle fatigue is defined as a loss of tension development during constant stimulation. Although the relationship is not well documented, muscle fatigue has been inferred from electromyogram (EMG) signals. The purpose of this study was to determine the relationship between the amplitude and duration of single motor unit action potentials (MUAPs) and the loss of tension development (fatigue) in the medial gastrocnemius muscles of cats. Single motor units were fatigued by continuous stimulation at 10 or 80 Hz or with trains of 40-Hz stimuli. When motor units were stimulated at 10 Hz and with trains at 40 Hz (low frequency), tension declined and remained depressed during recovery. The changes in the MUAP correlated poorly with changes in tension. During and after stimulation at 80 Hz (high frequency), changes in the amplitude and duration of MUAPs correlated highly with changes in tension development. Since the EMG signal is dependent on a summation and cancellation of individual MUAPs, the EMG provides a reasonable estimate of high-frequency fatigue but an unreliable measure of low-frequency fatigue.     

Analyzing the dynamics of hand tremor time series

We investigate physiological, essential and parkinsonian hand tremor measured by the acceleration of the streched hand. Methods from the theory of dynamical systems and from stochastics are used. It turns out that the physiological tremor can be described as a linear stochastic process, and that the parkinsonian tremor is nonlinear and deterministic, even chaotic. The essential tremor adopts a middle position, it is nonlinear and stochastic.     

Multichannel thin-film electrode for intramuscular electromyographic recordings.

It is currently not possible to record electromyographic (EMG) signals from many locations concurrently inside the muscle in a single wire electrode system. We developed a thin-film wire electrode system for multichannel intramuscular EMG recordings. The system was fabricated using a micromachining process, with a silicon wafer as production platform for polyimide-based electrodes. In the current prototype, the flexible polymer structure is 220 microm wide, 10 microm thick, and 1.5 cm long, and it has eight circular platinum-platinum chloride recording sites of 40-microm diameter distributed along the front and back surfaces with 1,500-microm intersite spacing. The system prototype was tested in six experiments where the electrode was implanted into the medial head of the gastrocnemius muscle of rabbits, perpendicular to the pennation angle of the muscle fibers. Asynchronous motor unit activity was induced by eliciting the withdrawal reflex or sequential crushes of the sciatic nerve using a pair of forceps. Sixty-seven motor units were identified from these recordings. In the bandwidth 200 Hz to 5 kHz, the peak-to-peak amplitude of the action potentials of the detected motor units was 75 +/- 12 muV and the root mean square of the noise was 1.6 +/- 0.4 muV. The noise level and amplitude of the action potentials were similar for measures separated by up to 40 min. The experimental tests demonstrated that thin film is a promising technology for a new type of flexible-wire intramuscular EMG recording system with multiple detection sites.     

Motor unit activity and surface electromyogram power spectrum during increasing force of contraction

Twelve male subjects were tested to determine the relationship between motor unit (MU) activities and surface electromyogram (EMG) power spectral parameters with contractions increasing linearly from zero to 80% of maximal voluntary contraction (MVC). Intramuscular spike and surface EMG signals recorded simultaneously from biceps brachii were analyzed by means of a computer-aided intramuscular MU spike amplitude-frequency (ISAF) histogram and an EMG frequency power spectral analysis. All measurements were made in triplicate and averaged. Results indicate that there were highly significant increases in surface EMG amplitude (71 +/- 31.3 to 505 +/- 188 microV, p less than 0.01) and mean power frequency (89 +/- 13.3 to 123 +/- 23.5 Hz, p less than 0.01) with increasing force. These changes were accompanied by progressive increases in the firing frequency of MU's initially recruited, and of newly recruited MU's with relatively larger spike amplitudes. The group data in the ISAF histograms revealed significant increases in mean spike amplitude (412 +/- 79 to 972 +/- 117 microV, p less than 0.01) and mean firing frequency (17.8 +/- 5.4 to 24.7 +/- 4.1 Hz, p less than 0.01). These data suggest that surface EMG spectral analysis can provide a sensitive measure of the relative changes in MU activity during increasing force output.     

Features of parkinsonian and essential tremor of the human hand

Using spectral, wavelet, multifractal, and recurrence analyses we examined the features of involuntary shaking (tremor) that occur during the performance of a given motor task. The task was to maintain the efforts of fingers under isometric conditions by a healthy subject, a patient with primary bilateral parkinsonism, and a patient with essential tremor syndrome. The physiological tremor was characterized by the lowest amplitude, a broad power spectrum, the lowest energy of the wavelet spectrum, the highest degree of multifractality, the lowest degree of determinism, and the highest entropy of the recurrence time density. In the case of the essential tremor we observed a significant enhancement of the wavelet spectrum energy and a decrease of the oscillation complexity. This was evident via the occurrence of clear peaks in the power spectra, a decrease in the degree of multifractality, the emergence of a quasi-periodic structure in the recurrence diagrams, an increase in determinism and a decrease of the entropy of recurrence time density. All these trends were increased for the parkinsonian tremor data. These characteristics enable us to quantitatively estimate the degree of deviation of motor function from the healthy case.