Failure to improve task performance after visuomotor training with error reduction feedback for young adults.

Visual feedback that reinforces accurate movements may motivate skill acquisition by promoting self-confidence. This study investigated neuromuscular adaptations to visuomotor training with visual feedback with virtual error reduction. Twenty-eight young adults (24.6 ± 1.6 years) were assigned to error reduction (ER) (n = 14) and control (n = 14) groups to train on a bi-rhythmic force task. The ER group received visual feedback and the displayed errors were 50% of the real errors in size. The control group was trained with visual feedback with no reduction in errors. Training-related differences in task accuracy, force behaviors, and motor unit discharge were contrasted between the two groups. The tracking error of the control group progressively declined, whereas the tracking error of the ER group was not evidently reduced in the practice sessions. In the post-test, only the control group exhibited significant task improvements with smaller error size (p = .015) and force enhancement at the target frequencies (p = .001). The motor unit discharge of the control group was training-modulated, as indicated by a reduction of the mean inter-spike interval (p = .018) and smaller low-frequency discharge fluctuations (p = .017) with enhanced firing at the target frequencies of the force task (p = .002). In contrast, the ER group showed no training-related modulation of motor unit behaviors. In conclusion, for young adults, ER feedback does not induce neuromuscular adaptations to the trained visuomotor task, which is conceptually attributable to intrinsic error dead-zones.

Quick balance skill improvement after short-term training with error amplification feedback for older adults.

This study investigated behavioral and cortical mechanisms for short-term postural training with error amplification (EA) feedback in the elderly. Thirty-six elderly subjects (65.7 ± 2.2 years) were grouped (control and EA, n = 18) for training in stabilometer balance under visual guidance. During the training session (8 training rounds of 60 s in Day 2), the EA group received visual feedback that magnified errors to twice the real size, whereas the control group received visual feedback that displayed real errors. Scalp EEG and kinematic data of the stabilometer plate and ankle joint were recorded in the pre-test (Day 1) and post-test (Day 3). The EA group (-46.5 ± 4.7%) exhibited greater post-training error reduction than that of the control group (-27.1 ± 4.0%)(p = 0.020), together with a greater decline in kinematic coupling between the stabilometer plate and ankle joint (EA: -26.6 ± 4.8%, control: 2.3 ± 8.6%, p = 0.023). In contrast to the control group, the EA group manifested greater reductions in mean phase-lag index (PLI) connectivity in the theta (4-7 Hz)(p = 0.011) and alpha (8-12 Hz) (p = 0.027) bands. Only the EA group showed post-training declines in the mean PLI in the theta and alpha bands. Minimal spanning tree analysis revealed that EA-based training led to increases in the diameter (p = 0.002) and average eccentricity (p = 0.004) of the theta band for enhanced performance monitoring and reduction in the leaf fraction (p = 0.030) of the alpha band for postural response with enhanced automaticity. In conclusion, short-term EA training optimizes balance skill, favoring multi-segment coordination for the elderly, which is linked to more sophisticated error monitoring with less attentive control over the stabilometer stance.

Cortical reorganization to improve dynamic balance control with error amplification feedback.

BACKGROUND: Error amplification (EA), virtually magnify task errors in visual feedback, is a potential neurocognitive approach to facilitate motor performance. With regional activities and inter-regional connectivity of electroencephalography (EEG), this study investigated underlying cortical mechanisms associated with improvement of postural balance using EA. METHODS: Eighteen healthy young participants maintained postural stability on a stabilometer, guided by two visual feedbacks (error amplification (EA) vs. real error (RE)), while stabilometer plate movement and scalp EEG were recorded. Plate dynamics, including root mean square (RMS), sample entropy (SampEn), and mean frequency (MF) were used to characterize behavioral strategies. Regional cortical activity and inter-regional connectivity of EEG sub-bands were characterized to infer neural control with relative power and phase-lag index (PLI), respectively. RESULTS: In contrast to RE, EA magnified the errors in the visual feedback to twice its size during stabilometer stance. The results showed that EA led to smaller RMS of postural fluctuations with greater SampEn and MF than RE did. Compared with RE, EA altered cortical organizations with greater regional powers in the mid-frontal cluster (theta, 4-7 Hz), occipital cluster (alpha, 8-12 Hz), and left temporal cluster (beta, 13-35 Hz). In terms of the phase-lag index of EEG between electrode pairs, EA significantly reduced long-range prefrontal-parietal and prefrontal-occipital connectivity of the alpha/beta bands, and the right tempo-parietal connectivity of the theta/alpha bands. Alternatively, EA augmented the fronto-centro-parietal connectivity of the theta/alpha bands, along with the right temporo-frontal and temporo-parietal connectivity of the beta band. CONCLUSION: EA alters postural strategies to improve stance stability on a stabilometer with visual feedback, attributable to enhanced error processing and attentional release for target localization. This study provides supporting neural correlates for the use of virtual reality with EA during balance training.

Changes in postural strategy of the lower limb under mechanical knee constraint on an unsteady stance surface.

Joint constraint could limit the available degrees of freedom in a kinematic chain for maintaining postural stability. This study investigated adaptive changes in postural synergy due to bracing of bilateral knee joints, usually thought to have a trifling impact on upright stance. Twenty-four young adults were requested to maintain balance on a stabilometer plate as steadily as possible while wearing a pair of knee orthoses, either unlocked (the non-constraint (NC) condition) or locked to restrict knee motion (the knee constraint (KC) condition). Knee constraint led to a significant increase in the regularity of the stabilometer angular velocity. More than 95% of the variance properties of the joint angular velocities in the lower limb were explained by the first and second principal components (PC1 and PC2), which represented the ankle strategy and the combined knee and hip strategy, respectively. In addition to the increase trend in PC1 regularity, knee constraint enhanced the mutual information of the stabilometer angular velocity and PC1 (MISTBV-PC1) but reduced the mutual information of the stabilometer angular velocity and PC2 (MISTBV-PC2). The MISTBV-PC1 was also positively correlated to stance steadiness on the stabilometer in the KC condition. In summary, in the knee constraint condition, postural synergy on the stabilometer was reorganized to increase reliance on ankle strategies to maintain equilibrium. In particular, a stable stabilometer stance under knee constraint is associated with a high level of coherent ankle-stabilometer interaction.

Adaptation of kinematic synergy and postural control to mechanical ankle constraint on an unsteady stance surface.

Joint constraint interferes with the coordinative structure in joint movements used to optimize postural stability. This study aimed to investigate changes in postural synergy when the ankle joints were bilaterally braced during a stabilometer stance. Twenty-four young adults stood on a stabilometer plate while wearing a pair of ankle-foot orthoses, which were either unlocked or locked to restrict ankle motion (the ankle constraint (AC) and non-constraint (NC) conditions). Although ankle constraint did not significantly affect the dynamics of the stabilometer movements, the size and regularity of the first principal component (PC1), which explained more than 80% of the variance of joint movements in the lower limb, were increased. In addition, PC1 exhibited higher communalities with angular movements of the knee and hip joints in the AC condition than in the NC condition. Those subjects who exhibited a constraint-induced increase in postural sway (the I group) showed greater increases in the size and regularity of PC1 than did those who exhibited reduced postural sway during ankle constraint (the D group). Constraint-induced changes in postural synergy were group-dependent. Only the I group exhibited an increase of communality of PC1 with the hip angular movement following bilateral ankle constraint. In summary, bilateral ankle constraint altered the coordination solution, with increasing reliance on compensatory knee movement to maintain a balanced posture on the stabilometer. However, accessory hip movement due to ankle constraint was not economical and was disadvantageous to stance stability.

Perceptual influences of error size on voluntary force control during a compound sinusoidal force task.

Visual feedback that provides error information is critical to task quality and motor adjustments. This study investigated how the size of perceived errors via visual feedback affected rate control and force gradation strategy of a designate force task. Fourteen young adults coupled force exertions to a compound sinusoidal signal (0.2 Hz and 0.5 Hz) that fluctuated around a mean level of 30% of maximal voluntary contraction, when the size of execution errors were differently scaled with the error amplification factors. In the low (LAF) and high (HAF) amplification factor conditions, the execution errors in the visual display half and double of the real errors, respectively. The visualized error was the real errors in the medium amplification factor (MAF) condition. In addition to a phase-lead of force output, the LAF condition that virtually reduced the size of error feedback associated with a poorer task accuracy than the MAF and HAF conditions. Virtual increase in error size of visual feedback selectively suppressed the fast target force at 0.5 Hz. In addition, complexity and high-frequency components (>0.75 Hz) of force outputs multiplied progressively with increasing error size. Error-enhancing feedback suppressed fast target force, accentuating the use of error information to tune force output, whereas error-reducing feedback enhanced fast target force in favor of predictive force control.

Paradigm Shifts in Voluntary Force Control and Motor Unit Behaviors with the Manipulated Size of Visual Error Perception.

The detection of error information is an essential prerequisite of a feedback-based movement. This study investigated the differential behavior and neurophysiological mechanisms of a cyclic force-tracking task using error-reducing and error-enhancing feedback. The discharge patterns of a relatively large number of motor units (MUs) were assessed with custom-designed multi-channel surface electromyography following mathematical decomposition of the experimentally-measured signals. Force characteristics, force-discharge relation, and phase-locking cortical activities in the contralateral motor cortex to individual MUs were contrasted among the low (LSF), normal (NSF), and high scaling factor (HSF) conditions, in which the sizes of online execution errors were displayed with various amplification ratios. Along with a spectral shift of the force output toward a lower band, force output with a more phase-lead became less irregular, and tracking accuracy was worse in the LSF condition than in the HSF condition. The coherent discharge of high phasic (HP) MUs with the target signal was greater, and inter-spike intervals were larger, in the LSF condition than in the HSF condition. Force-tracking in the LSF condition manifested with stronger phase-locked EEG activity in the contralateral motor cortex to discharge of the (HP) MUs (LSF > NSF, HSF). The coherent discharge of the (HP) MUs during the cyclic force-tracking predominated the force-discharge relation, which increased inversely to the error scaling factor. In conclusion, the size of visualized error gates motor unit discharge, force-discharge relation, and the relative influences of the feedback and feedforward processes on force control. A smaller visualized error size favors voluntary force control using a feedforward process, in relation to a selective central modulation that enhance the coherent discharge of (HP) MUs.

An Increase in Postural Load Facilitates an Anterior Shift of Processing Resources to Frontal Executive Function in a Postural-Suprapostural Task.

Increase in postural-demand resources does not necessarily degrade a concurrent motor task, according to the adaptive resource-sharing hypothesis of postural-suprapostural dual-tasking. This study investigated how brain networks are organized to optimize a suprapostural motor task when the postural load increases and shifts postural control into a less automatic process. Fourteen volunteers executed a designated force-matching task from a level surface (a relative automatic process in posture) and from a stabilometer board while maintaining balance at a target angle (a relatively controlled process in posture). Task performance of the postural and suprapostural tasks, synchronization likelihood (SL) of scalp EEG, and graph-theoretical metrics were assessed. Behavioral results showed that the accuracy and reaction time of force-matching from a stabilometer board were not affected, despite a significant increase in postural sway. However, force-matching in the stabilometer condition showed greater local and global efficiencies of the brain networks than force-matching in the level-surface condition. Force-matching from a stabilometer board was also associated with greater frontal cluster coefficients, greater mean SL of the frontal and sensorimotor areas, and smaller mean SL of the parietal-occipital cortex than force-matching from a level surface. The contrast of supra-threshold links in the upper alpha and beta bands between the two stance conditions validated load-induced facilitation of inter-regional connections between the frontal and sensorimotor areas, but that contrast also indicated connection suppression between the right frontal-temporal and the parietal-occipital areas for the stabilometer stance condition. In conclusion, an increase in stance difficulty alters the neurocognitive processes in executing a postural-suprapostural task. Suprapostural performance is not degraded by increase in postural load, due to (1) increased effectiveness of information transfer, (2) an anterior shift of processing resources toward frontal executive function, and (3) cortical dissociation of control hubs in the parietal-occipital cortex for neural economy.

A microprocessor-based multichannel subsensory stochastic resonance electrical stimulator.

Stochastic resonance electrical stimulation is a novel intervention which provides potential benefits for improving postural control ability in the elderly, those with diabetic neuropathy, and stroke patients. In this paper, a microprocessor-based subsensory white noise electrical stimulator for the applications of stochastic resonance stimulation is developed. The proposed stimulator provides four independent programmable stimulation channels with constant-current output, possesses linear voltage-to-current relationship, and has two types of stimulation modes, pulse amplitude and width modulation.

Measurement of intrinsic optical backscattering characteristics of cells using fiber-guided near infrared light.

BACKGROUND: Intrinsic optical signals (IOS), which reflect changes in transmittance and scattering light, have been applied to characterize the physiological conditions of target biological tissues. Backscattering approaches allow mounting of the source and detector on the same side of a sample which creates a more compact physical layout of device. This study presents a compact backscattering design using fiber-optic guided near-infrared (NIR) light to measure the amplitude and phase changes of IOS under different osmotic challenges. METHODS: High-frequency intensity-modulated light was guided via optic fiber, which was controlled by micromanipulator to closely aim at a minimum cluster of cortical neurons. Several factors including the probe design, wavelength selection, optimal measuring distance between the fiber-optical probe and cells were considered. Our experimental setup was tested in cultured cells to observe the relationship between the changes in backscattered NIR light and cellular IOS, which is believed mainly caused by cell volume changes in hypo/hyperosmotic solutions (+/- 20, +/- 40 and +/- 60 mOsm). RESULTS: The critical parameters of the current setup including the optimal measuring distance from fiber-optical probe to target tissue and the linear relationship between backscattering intensity and cell volume were determined. The backscattering intensity was found to be inversely proportional to osmotic changes. However, the phase shift exhibited a nonlinear feature and reached a plateau at hyperosmotic solution. CONCLUSIONS: Our study indicated that the backscattering NIR light guided by fiber-optical probe makes it a potential alternative for continuous observation of intrinsic optical properties of cell culture under varied physical or chemical challenges.

Performance evaluation and enhancement of lung sound recognition system in two real noisy environments.

This study investigates the problems associated with lung sound recognition under noisy conditions. Firstly, the effects of noise on the lung sound feature representation and the classification performance are analyzed. Two kinds of feature representations, autoregressive and mel-frequency cepstral coefficients, are used to characterize the lung sound signals. Dynamic time warping is used to categorize the lung sounds to one of the three: normal, wheezes, or crackles. Our experimental results indicate that additive noise produces a mismatch between training and recognition environments and deteriorates the classification performance with a decrease in the SNR levels. In order to compensate the degrading effect of noise on the lung sound recognition, a dual sensor spectral subtraction algorithm is applied to the lung sound signals before the extraction of lung sound features. It is observed that the proposed algorithm is capable of providing adequate performance in terms of noise suppression and lung sound signal enhancement.