Frank Huethe

Beta-Range EEG-EMG Coherence With Isometric Compensation for Increasing Modulated Low-Level Forces

Corticomuscular synchronization has been shown to occur in beta (15-30 Hz) and gamma range (30-45 Hz) during isometric compensation of static and dynamic (periodically modulated) low-level forces, respectively. However, it is still unknown to what extent these synchronization processes in beta and gamma range are modified with increasing modulated force. We addressed this question by investigating the corticomuscular coherence (CMC) between the electroencephalogram (EEG) and electromyogram (EMG) from the first dorsal interosseus muscle (FDI) as well as the cortical and muscular spectral power during a visuomotor task where different levels of a dynamic (modulated) force were used. Seven healthy right-handed female subjects compensated dynamic forces at 8, 16, and 24% of the maximal voluntary contraction (MVC) isometrically with their right index finger. Under the three conditions investigated, we found a broad-band CMC comprising both beta and gamma range and peaking at approximately 22 Hz within the beta band. This broad-band coherence increased linearly with higher force level. A separate analysis of the gamma range CMC did not show significant modulation of the CMC by the force levels. EEG and EMG spectral power did not show any significant difference among the three force conditions. Our results favor the view that the function of beta range CMC is not specific for low-level static forces only. The sensorimotor system may resort to stronger and also broader beta-range CMC to generate stable corticospinal interaction during increased force level, as well as when compensating for dynamic modulated forces. This finding re-enforces the importance of the beta-range EEG-EMG coherence in sensorimotor integration.

Improved Sensorimotor Performance via Stochastic Resonance

Several studies about noise-enhanced balance control in humans support the hypothesis that stochastic resonance can enhance the detection and transmission in sensorimotor system during a motor task. The purpose of the present study was to extend these findings in a simpler and controlled task. We explored whether a particular level of a mechanical Gaussian noise (0–15 Hz) applied on the index finger can improve the performance during compensation for a static force generated by a manipulandum. The finger position was displayed on a monitor as a small white point in the center of a gray circle. We considered a good performance when the subjects exhibited a low deviation from the center of this circle and when the performance had less variation over time. Several levels of mechanical noise were applied on the manipulandum. We compared the performance between zero noise (ZN), optimal noise (ON), and high noise (HN). In all subjects (8 of 8) the data disclosed an inverted U-like graph between the inverse of the mean variation in position and the input noise level. In other words, the mean variation was significantly smaller during ON than during ZN or HN. The findings suggest that the application of a tactile-proprioceptive noise can improve the stability in sensorimotor performance via stochastic resonance. Possible explanations for this improvement in motor precision are an increase of the peripheral receptors sensitivity and of the internal stochastic resonance, causing a better sensorimotor integration and an increase in corticomuscular synchronization.

Dopamine release in human neocortical slices: Characterization of inhibitory autoreceptors and of nicotinic acetylcholine receptor-evoked release

The autoinhibitory control of electrically evoked release of [3H]-dopamine and the properties of that induced by nicotinic receptor (nAChR) stimulation were studied in slices of the human neocortex. In both models [3H]-dopamine release was action potential-induced and exocytotic. The selective dopamine D2 receptor agonist (-)-quinpirole reduced electrically evoked release of [3H]-dopamine, yielding IC50 and I(max) values of 23 nM and 76%, respectively. Also, the effects of several other subtype-selective dopamine receptor ligands confirmed that the terminal dopamine autoreceptor belongs to the D2 subtype. The autoinhibitory feedback control was slightly operative under stimulation conditions of 90 pulses and 3 Hz, with a biophase concentration of endogenous dopamine of 3.6 nM, and was enhanced under blockade of dopamine reuptake. [3H]-dopamine release evoked in an identical manner in mouse neocortical slices was not inhibited by (-)-quinpirole, suggesting the absence of dopamine autoreceptors in this tissue and underlining an important species difference. Also, nAChR stimulation-induced release of [3H]-dopamine revealed a species difference: [3H]-dopamine release was evoked in human, but not in rat neocortical slices. The nAChRs inducing [3H]-dopamine release most probably belong to the alpha3/beta2subtype, according to the potencies and efficacies of subtype-selective nAChR ligands. Part of these receptors may be located on glutamatergic neurons.

Corticospinal interaction during isometric compensation for modulated forces with different frequencies

BackgroundDuring isometric compensation of modulated low-level forces corticomuscular coherence (CMC) has been shown to occur in high-beta or gamma-range. The influence of the frequency of force modulation on CMC has up to now remained unexplored. We addressed this question by investigating CMC, motor performance, and cortical spectral power during a visuomotor task in which subjects had to compensate a modulated force of 8% of the maximum voluntary contraction exerted on their right index finger. The effect of three frequencies of force modulation (0.6, 1.0 and 1.6 Hz) was tested. EEG, EMG from first dorsal interosseus, hand flexor and extensor muscles, and finger position were recorded in eight right-handed women.ResultsFive subjects showed CMC in gamma- (28-45 Hz) and three in beta-range (15-30 Hz). Beta- and gamma-range CMC and cortical motor spectral power were not modulated by the various frequencies. However, a sharp bilateral CMC peak at 1.6 Hz was observed, but only in the five gamma-range CMC subjects. The performance error increased linearly with the frequency.ConclusionsOur findings suggest that the frequency of force modulation has no effect on the beta- and gamma-range CMC during isometric compensation for modulated forces at 8% MVC. The beta- and gamma-range CMC may be related to interindividual differences and possibly to strategy differences.

Broad-band Gaussian noise is most effective in improving motor performance and is most pleasant

Modern attempts to improve human performance focus on stochastic resonance (SR). SR is a phenomenon in non-linear systems characterized by a response increase of the system induced by a particular level of input noise. Recently, we reported that an optimum level of 0–15 Hz Gaussian noise applied to the human index finger improved static isometric force compensation. A possible explanation was a better sensorimotor integration caused by increase in sensitivity of peripheral receptors and/or of internal SR. The present study in 10 subjects compares SR effects in the performance of the same motor task and on pleasantness, by applying three Gaussian noises chosen on the sensitivity of the fingertip receptors (0–15 Hz mostly for Merkel receptors, 250–300 Hz for Pacini corpuscles and 0–300 Hz for all). We document that only the 0–300 Hz noise induced SR effect during the transitory phase of the task. In contrast, the motor performance was improved during the stationary phase for all three noise frequency bandwidths. This improvement was stronger for 0–300 Hz and 250–300 Hz than for 0–15 Hz noise. Further, we found higher degree of pleasantness for 0–300 Hz and 250–300 Hz noise bandwidths than for 0–15 Hz. Thus, we show that the most appropriate Gaussian noise that could be used in haptic gloves is the 0–300 Hz, as it improved motor performance during both stationary and transitory phases. In addition, this noise had the highest degree of pleasantness and thus reveals that the glabrous skin can also forward pleasant sensations.

Suppression of enhanced physiological tremor via stochastic noise: initial observations.

Enhanced physiological tremor is a disabling condition that arises because of unstable interactions between central tremor generators and the biomechanics of the spinal stretch reflex. Previous work has shown that peripheral input may push the tremor-related spinal and cortical systems closer to anti-phase firing, potentially leading to a reduction in tremor through phase cancellation. The aim of the present study was to investigate whether peripherally applied mechanical stochastic noise can attenuate enhanced physiological tremor and improve motor performance. Eight subjects with enhanced physiological tremor performed a visuomotor task requiring the right index finger to compensate a static force generated by a manipulandum to which Gaussian noise (3–35 Hz) was applied. The finger position was displayed on-line on a monitor as a small white dot which the subjects had to maintain in the center of a larger green circle. Electromyogram (EMG) from the active hand muscles and finger position were recorded. Performance was measured by the mean absolute deviation of the white dot from the zero position. Tremor was identified by the acceleration in the frequency range 7–12 Hz. Two different conditions were compared: with and without superimposed noise at optimal amplitude (determined at the beginning of the experiment). The application of optimum noise reduced tremor (accelerometric amplitude and EMG activity) and improved the motor performance (reduced mean absolute deviation from zero). These data provide the first evidence of a significant reduction of enhanced physiological tremor in the human sensorimotor system due to application of external stochastic noise.

Enhanced corticomuscular coherence by external stochastic noise

Noise can have beneficial effects as shown by the stochastic resonance (SR) phenomenon which is characterized by performance improvement when an optimal noise is added. Modern attempts to improve human performance utilize this phenomenon. The purpose of the present study was to investigate whether performance improvement by addition of optimum noise (ON) is related to increased cortical motor spectral power (SP) and increased corticomuscular coherence. Eight subjects performed a visuomotor task requiring to compensate with the right index finger a static force (SF) generated by a manipulandum on which Gaussian noise was applied. The finger position was displayed on-line on a monitor as a small white dot which the subjects had to maintain in the center of a green bigger circle. Electroencephalogram from the contralateral motor area, electromyogram from active muscles and finger position were recorded. The performance was measured by the mean absolute deviation (MAD) of the white dot from the zero position. ON compared to the zero noise condition induced an improvement in motor accuracy together with an enhancement of cortical motor SP and corticomuscular coherence in beta-range. These data suggest that the improved sensorimotor performance via SR is consistent with an increase in the cortical motor SP and in the corticomuscular coherence.

The strength of the corticospinal coherence depends on the predictability of modulated isometric forces

Isometric compensation of predictably frequency-modulated low forces is associated with corticomuscular coherence (CMC) in beta and low gamma range. It remains unclear how the CMC is influenced by unpredictably modulated forces, which create a mismatch between expected and actual sensory feedback. We recorded electroencephalography from the contralateral hand motor area, electromyography (EMG), and the motor performance of 16 subjects during a visuomotor task in which they had to isometrically compensate target forces at 8% of the maximum voluntary contraction with their right index finger. The modulated forces were presented with predictable or unpredictable frequencies. We calculated the CMC, the cortical motor alpha-, beta-, and gamma-range spectral powers (SP), and the task-related desynchronization (TRD), as well as the EMG SP and the performance. We found that in the unpredictable condition the CMC was significantly lower and associated with lower cortical motor SP, stronger TRD, higher EMG SP, and worse performance. The findings suggest that due to the mismatch between predicted and actual sensory feedback leading to higher computational load and less stationary motor state, the unpredictable modulation of the force leads to a decrease in corticospinal synchrony, an increase in cortical and muscle activation, and a worse performance.

Human Equilibrium Control Principles Implemented into a Biped Humanoid Robot

We describe how human equilibrium control principles, which were derived from neurophysiological experiments, can be implemented in a biped humanoid robot (‘PostuRob’). Stance control in humans uses sensorbased feedback which involves mainly three sensors that measure: (1) body motion in space (vestibular system), (2) body motion with respect to the feet (ankle angle proprioception), and (3) torque between body and feet (ankle torque proprioception). The sensor signals are not used directly for feedback, but instead are used to internally reconstruct the physical stimuli in the outside world by means of sensor fusions. These reconstructions yield internal estimates of the external force fields such as gravity, the external contact forces (e.g. push), and support surface motion. The estimates are fed into an ankle angle proprioceptive feedback loop. By way of the signal fusions the robot’s control adjusts to the external stimulus situations, a fact that allows for low loop gain and robust control. This control differs from that of the biped robots described in the literature. They tend to use a global stability measure such as the COP (centre of pressure) or ZMP (zero moment point) and this control does not adjust to the external stimulus situation. Our PostuRob is used in a biorobotics approach to better understand stance control deficits of neurological patients and the effects of therapy and rehabilitation.