Interpersonal motor synergy: coworking strategy depends on task constraints.

We investigated the role of task constraints on interpersonal interactions. Twenty-one pairs of coworkers performed a finger force production task on force sensors placed at two ends of a seesaw-like apparatus and matched a combined target force of 20 N for 23 s over 10 trials. There were two experimental conditions: 1) FIXED: the seesaw apparatus was mechanically held in place so that the only task constraint was to match the 20 N resultant force, and 2) MOVING: the lever in the apparatus was allowed to rotate freely around its fulcrum, acting like a seesaw, so an additional task constraint to (implicitly) balance the resultant moment was added. We hypothesized that the additional task constraint of moment stabilization imposed on the MOVING condition would deteriorate task performance compared with the FIXED condition; however, this was rejected, as the performance of the force matching task was similar between two conditions. We also hypothesized that the central nervous systems (CNSs) would employ distinct coworking strategies or interpersonal motor synergy (IPMS) between conditions to satisfy different task constraints, which was supported by our results. Negative covariance between coworker's forces in the FIXED condition suggested a force stabilization strategy, whereas positive covariance in the MOVING condition suggested a moment stabilization strategy, implying that independent CNSs adopt distinct IPMSs depending on task constraints. We speculate that in the absence of a central neural controller, shared visual and mechanical connections between coworkers may suffice to trigger modulations in the cerebellum of each CNS to satisfy competing task constraints.NEW & NOTEWORTHY To the best of our knowledge, this is the first study to investigate the coworking behavior or IPMS when an additional task constraint is imposed. Our proposed analytical framework quantifies IPMS and allows for investigating variability in offline (i.e., across multiple repetitions) and online (i.e., across time) control, which is novel in coworking research. Understanding variability while performing a task is essential, as repeating a task is not always possible, as in therapeutic contexts.

Multiple strategies to correct errors in foot placement and control speed in human walking.

Neural feedback plays a key role in maintaining locomotor stability in the face of perturbations. In this study, we systematically identified properties of neural feedback that contribute to stabilizing human walking by examining how the nervous system responds to small kinematic deviations away from the desired gait pattern. We collected data from 20 participants (9 men and 11 women). We simultaneously applied (1) small continuous mechanical perturbations, forces at the ankles that affected foot placement, and (2) small continuous sensory perturbations, movement of a virtual visual scene that produced the illusion of change in walking speed, to compare how neural feedback responds to actual and illusory kinematic deviations. We computed phase-dependent impulse response functions that describe kinematic and muscular responses to small brief perturbations to identify critical phases of the gait cycle when the nervous system modulates muscle activity. In addition to the known foot-placement strategies that counteract kinematic displacement, such as the modulation of the hamstring muscle group during swing, we identified phase-specific muscle modulations that compensated for the perturbations. In particular, our results suggested that an early-stance modulation of anterior leg muscles (i.e., dorsiflexors and quadriceps) is a general control mechanism that serves to control forward body propulsion and compensates for errors in foot placement. Another detected general compensatory strategy was the late-stance modulation of the rectus femoris and gastrocnemius muscles, which controls walking speed in the next cycle.

Sensory-Challenge Balance Exercises Improve Multisensory Reweighting in Fall-Prone Older Adults.

BACKGROUND AND PURPOSE: Multisensory reweighting (MSR) deficits in older adults contribute to fall risk. Sensory-challenge balance exercises may have value for addressing the MSR deficits in fall-prone older adults. The purpose of this study was to examine the effect of sensory-challenge balance exercises on MSR and clinical balance measures in fall-prone older adults. METHODS: We used a quasi-experimental, repeated-measures, within-subjects design. Older adults with a history of falls underwent an 8-week baseline (control) period. This was followed by an 8-week intervention period that included 16 sensory-challenge balance exercise sessions performed with computerized balance training equipment. Measurements, taken twice before and once after intervention, included laboratory measures of MSR (center of mass gain and phase, position, and velocity variability) and clinical tests (Activities-specific Balance Confidence Scale, Berg Balance Scale, Sensory Organization Test, Limits of Stability test, and lower extremity strength and range of motion). RESULTS: Twenty adults 70 years of age and older with a history of falls completed all 16 sessions. Significant improvements were observed in laboratory-based MSR measures of touch gain (P = 0.006) and phase (P = 0.05), Berg Balance Scale (P = 0.002), Sensory Organization Test (P = 0.002), Limits of Stability Test (P = 0.001), and lower extremity strength scores (P = 0.005). Mean values of vision gain increased more than those for touch gain, but did not reach significance. DISCUSSION AND CONCLUSIONS: A balance exercise program specifically targeting multisensory integration mechanisms improved MSR, balance, and lower extremity strength in this mechanistic study. These valuable findings provide the scientific rationale for sensory-challenge balance exercise to improve perception of body position and motion in space and potential reduction in fall risk.

Characterization of the encoding properties of intraspinal mechanosensory neurons in the lamprey.

Proprioceptive sensory inputs are an integral part of the closed-loop system of locomotion. In the lamprey, a model organism for vertebrate locomotion, such sensory inputs come from intraspinal mechanosensory cells called "edge cells". These edge cells synapse directly onto interneurons in the spinal central pattern generator (CPG) circuit and allow the CPG to adjust the motor output according to how the body is bending. However, the encoding properties of the edge cells have never been fully characterized. To identify these properties and better understand edge cells' role in locomotion, we isolated spinal cords of silver lampreys (Ichthyomyzon unicuspis) and recorded extracellularly from the lateral tracts where edge cell axons are located. We identified cells that responded to mechanical stimuli and used standard spike sorting algorithms to identify separate units, then examined how the cells respond to bending rate and bending angle. Although some cells respond to the bending angle, as was previously known, the strongest and most common responses were to bending velocity. These encoding properties will help us better understand how lampreys and other basal vertebrates adapt their locomotor rhythms to different water flow patterns, perturbations, or other unexpected changes in their environments.

A central processing sensory deficit with Parkinson's disease.

Parkinson's disease (PD) is a progressive degenerative disease manifested by tremor, rigidity, bradykinesia, and postural instability. Deficits in proprioceptive integration are prevalent in individuals with PD, even at early stages of the disease. These deficits have been demonstrated primarily during investigations of reaching. Here, we investigated how PD affects sensory fusion of multiple modalities during upright standing. We simultaneously perturbed upright stance with visual, vestibular, and proprioceptive stimulation, to understand how these modalities are reweighted so that overall feedback remains suited to stabilizing upright stance in individuals with PD. Eight individuals with PD stood in a visual cave with a moving visual scene at 0.2 Hz while an 80-Hz vibratory stimulus was applied bilaterally to their Achilles tendons (stimulus turns on-off at 0.28 Hz) and a ±1 mA bilateral monopolar galvanic stimulus was applied at 0.36 Hz. The visual stimulus was presented at different amplitudes (0.2°, 0.8° rotation about ankle axis) to measure: the change in gain (weighting) to vision, an intramodal effect; and a simultaneous change in gain to vibration and galvanic stimulation, both intermodal effects. Trunk/leg gain relative to vision decreased when visual amplitude was increased, reflecting an intramodal visual effect. In contrast, when vibration was turned on/off, leg gain relative to vision was equivalent in individuals with PD, indicating no reweighting of visual information when proprioception was disrupted through vibration (i.e., no intermodal effect). Trunk and leg angle gain relative to GVS also showed no reweighting in individuals with PD. These results are in contrast to previous results with healthy adults, who showed clear intermodal effects in the same paradigm, suggesting that individuals with PD not only have a proprioceptive deficit during standing, but also have a cross-modal sensory fusion deficit that is crucial for upright stance control.

Intersegmental coupling and recovery from perturbations in freely running cockroaches.

Cockroaches are remarkably stable runners, exhibiting rapid recovery from external perturbations. To uncover the mechanisms behind this important behavioral trait, we recorded leg kinematics of freely running animals in both undisturbed and perturbed trials. Functional coupling underlying inter-leg coordination was monitored before and during localized perturbations, which were applied to single legs via magnetic impulses. The resulting transient effects on all legs and the recovery times to normal pre-perturbation kinematics were studied. We estimated coupling architecture and strength by fitting experimental data to a six-leg-unit phase oscillator model. Using maximum-likelihood techniques, we found that a network with nearest-neighbor inter-leg coupling best fitted the data and that, although coupling strengths vary among preparations, the overall inputs entering each leg are approximately balanced and consistent. Simulations of models with different coupling strengths encountering perturbations suggest that the coupling schemes estimated from our experiments allow animals relatively fast and uniform recoveries from perturbations.

Function dictates the phase dependence of vision during human locomotion.

In human and animal locomotion, sensory input is thought to be processed in a phase-dependent manner. Here we use full-field transient visual scene motion toward or away from subjects walking on a treadmill. Perturbations were presented at three phases of walking to test 1) whether phase dependence is observed for visual input and 2) whether the nature of phase dependence differs across body segments. Results demonstrated that trunk responses to approaching perturbations were only weakly phase dependent and instead depended primarily on the delay from the perturbation. Recording of kinematic and muscle responses from both right and left lower limb allowed the analysis of six distinct phases of perturbation effects. In contrast to the trunk, leg responses were strongly phase dependent. Leg responses during the same gait cycle as the perturbation exhibited gating, occurring only when perturbations were applied in midstance. In contrast, during the postperturbation gait cycle, leg responses occurred at similar response phases of the gait cycle over a range of perturbation phases. These distinct responses reflect modulation of trunk orientation for upright equilibrium and modulation of leg segments for both hazard accommodation/avoidance and positional maintenance on the treadmill. Overall, these results support the idea that the phase dependence of responses to visual scene motion is determined by different functional tasks during walking.

Does visual feedback during walking result in similar improvements in trunk control for young and older healthy adults?

BACKGROUND: Most current applications of visual feedback to improve postural control are limited to a fixed base of support and produce mixed results regarding improved postural control and transfer to functional tasks. Currently there are few options available to provide visual feedback regarding trunk motion while walking. We have developed a low cost platform to provide visual feedback of trunk motion during walking. Here we investigated whether augmented visual position feedback would reduce trunk movement variability in both young and older healthy adults. METHODS: The subjects who participated were 10 young and 10 older adults. Subjects walked on a treadmill under conditions of visual position feedback and no feedback. The visual feedback consisted of anterior-posterior (AP) and medial-lateral (ML) position of the subject's trunk during treadmill walking. Fourier transforms of the AP and ML trunk kinematics were used to calculate power spectral densities which were integrated as frequency bins "below the gait cycle" and "gait cycle and above" for analysis purposes. RESULTS: Visual feedback reduced movement power at very low frequencies for lumbar and neck translation but not trunk angle in both age groups. At very low frequencies of body movement, older adults had equivalent levels of movement variability with feedback as young adults without feedback. Lower variability was specific to translational (not angular) trunk movement. Visual feedback did not affect any of the measured lower extremity gait pattern characteristics of either group, suggesting that changes were not invoked by a different gait pattern. CONCLUSIONS: Reduced translational variability while walking on the treadmill reflects more precise control maintaining a central position on the treadmill. Such feedback may provide an important technique to augment rehabilitation to minimize body translation while walking. Individuals with poor balance during walking may benefit from this type of training to enhance path consistency during over-ground locomotion.

Identification of neural feedback for upright stance in humans: stabilization rather than sway minimization.

A fundamental issue in motor control is how to determine the task goals for a given behavior. Here, we address this question by separately identifying the musculoskeletal and feedback components of the human postural control loop. Eighteen subjects were perturbed by two mechanical perturbations (gentle pulling from behind at waist and shoulder levels) and one sensory perturbation (movement of a virtual visual scene). Body kinematics was described by the leg and trunk segment angles in the sagittal plane. Muscle activations were described by ankle and hip EMG signals, with each EMG signal computed as a weighted sum of rectified EMG signals from multiple muscles at the given joint. The mechanical perturbations were used to identify feedback, defined as the mapping from the two segment angles to the two EMG signals. The sensory perturbation was used to estimate parameters in a mechanistic model of the plant, defined as the mapping from the two EMG signals to the two segment angles. Using the plant model and optimal control theory, we compared identified feedback to optimal feedback for a range of cost functions. Identified feedback was similar to feedback that stabilizes upright stance with near-minimum muscle activation, but was not consistent with feedback that substantially increases muscle activation to reduce movements of the body's center of mass or center of pressure. The results suggest that the common assumption of reducing sway may not apply to musculoskeletal systems that are inherently unstable.

Dynamics of inter-modality re-weighting during human postural control.

Flexible and stable postural control requires adaptation to changing environmental conditions, a process which requires re-weighting of multisensory stimuli. Recent studies, as well as predictions from a computational model, have indicated a reciprocal re-weighting relationship between modalities when a sensory stimulus changes amplitude. As one modality is down-weighted, another is up-weighted to compensate (and vice versa). The purpose of this study was to investigate the dynamics of intra- and inter-modality re-weighting process by examining postural responses to manipulation of proprioception and visual modalities simultaneously. Twenty-two young adults were placed in a visual cave and stood on a variable-pitch platform for thirteen trials of 250 s apiece. The platform was rotated at constant frequency of 0.4 Hz and amplitudes of 0.3 (low) or 1.5 (high) degrees. Platform amplitude was manipulated in two conditions: low-to-high or high-to-low. The visual stimulus was displayed at constant frequency of 0.35 Hz and amplitude of 0.08 degrees. The results showed both fast and slow changes in center of mass (CoM) response to the switch in platform amplitude. On both timescales, CoM response changed in a reciprocal manner relative to platform amplitude. When the platform amplitude increased (low-to-high condition), CoM response decreased relative to the platform and increased relative to the visual stimulus, indicating both intra-modality and inter-modality sensory re-weighting. In the high-to-low condition, however, there was no change in CoM response relative to visual stimulus, indicating that re-weighting may also be dependent on the absolute level of gain. Sway variability at frequencies other than the stimulus frequency also showed a reciprocal relationship with CoM gain relative to platform. Overall, these results indicate that dynamics of multisensory re-weighting is clearly more complicated than the schemes proposed by current adaptive models of human postural control.

Navigating sensory conflict in dynamic environments using adaptive state estimation.

Most conventional robots rely on controlling the location of the center of pressure to maintain balance, relying mainly on foot pressure sensors for information. By contrast,humans rely on sensory data from multiple sources, including proprioceptive, visual, and vestibular sources. Several models have been developed to explain how humans reconcile information from disparate sources to form a stable sense of balance. These models may be useful for developing robots that are able to maintain dynamic balance more readily using multiple sensory sources. Since these information sources may conflict, reliance by the nervous system on any one channel can lead to ambiguity in the system state. In humans, experiments that create conflicts between different sensory channels by moving the visual field or the support surface indicate that sensory information is adaptively reweighted. Unreliable information is rapidly down-weighted,then gradually up-weighted when it becomes valid again.Human balance can also be studied by building robots that model features of human bodies and testing them under similar experimental conditions. We implement a sensory reweighting model based on an adaptive Kalman filter in abipedal robot, and subject it to sensory tests similar to those used on human subjects. Unlike other implementations of sensory reweighting in robots, our implementation includes vision, by using optic flow to calculate forward rotation using a camera (visual modality), as well as a three-axis gyro to represent the vestibular system (non-visual modality), and foot pressure sensors (proprioceptive modality). Our model estimates measurement noise in real time, which is then used to recompute the Kalman gain on each iteration, improving the ability of the robot to dynamically balance. We observe that we can duplicate many important features of postural sw ay in humans, including automatic sensory reweighting,effects, constant phase with respect to amplitude, and a temporal asymmetry in the reweighting gains.

Entrainment ranges of forced phase oscillators.

In the vertebrate spinal cord, a neural circuit called the central pattern generator produces the basic locomotory rhythm. Short and long distance intersegmental connections serve to maintain coordination along the length of the body. As a way of examining the influence of such connections, we consider a model of a chain of coupled phase oscillators in which one oscillator receives a periodic forcing stimulus. For a certain range of forcing frequencies, the chain will match the stimulus frequency, a phenomenon called entrainment. Motivated by recent experiments in lampreys, we derive analytical expressions for the range of forcing frequencies that entrain the chain, and how that range depends on the forcing location. For short intersegmental connections, in which an oscillator is connected only to its nearest neighbors, we describe two ways in which entrainment is lost: internally, in which oscillators within the chain no longer oscillate at the same frequency; and externally, in which the the chain no longer has the same frequency as the forcing. By analyzing chains in which every oscillator is connected to every other oscillator (i.e., all-to-all connections), we show that the presence of connections with lengths greater than one do not necessarily change the entrainment ranges based on the nearest-neighbor model. We derive a criterion for the ratio of connection strengths under which the connections of length greater than one do not change the entrainment ranges produced in the nearest-neighbor model, provided entrainment is lost externally. However, when this criterion holds, the range of entrained frequencies is a monotonic function of forcing location, unlike experimental results, in which entrainment ranges are larger near the middle of the chain than at the ends. Numerically, we show that similar non-monotonic entrainment ranges are possible if the ratio criterion does not hold, suggesting that in the lamprey central pattern generator, intersegmental connection strengths are not a simple function of the connection length.

The many roles of vision during walking.

Vision can improve bipedal upright stability during standing and locomotion. However, during locomotion, vision supports additional behaviors such as gait cycle modulation, navigation, and obstacle avoidance. Here, we investigate how the multiple roles of vision are reflected in the dynamics of trunk control as the neural control problem changes from a fixed to a moving base of support. Subjects were presented with either low- or high-amplitude broadband visual stimuli during standing posture or while walking on a treadmill at 1 km/h and 5 km/h. Frequency response functions between visual scene motion (input) and trunk kinematics (output) revealed little or no change in the gain of trunk orientation in the standing posture and walking conditions. However, a dramatic increase in gain was observed in trunk (hip and shoulder) horizontal displacement from posture to locomotion. Such increases in gain may be interpreted as an increased coupling to visual scene motion. However, we believe that the increased gain reflects a decrease in stability due to a change of the control problem from standing to locomotion. Indeed, keeping the body upright with the use of vision during walking is complicated by the additional locomotor processes at work. Unlike during standing, vision plays many roles during locomotion, providing information for upright stability as well as body position relative to the external environment.

Optimal motor control may mask sensory dynamics.

Properties of neural controllers for closed-loop sensorimotor behavior can be inferred with system identification. Under the standard paradigm, the closed-loop system is perturbed (input), measurements are taken (output), and the relationship between input and output reveals features of the system under study. Here we show that under common assumptions made about such systems (e.g. the system implements optimal control with a penalty on mechanical, but not sensory, states) important aspects of the neural controller (its zeros mask the modes of the sensors) remain hidden from standard system identification techniques. Only by perturbing or measuring the closed-loop system "between" the sensor and the control can these features be exposed with closed-loop system identification methods; while uncommon, there exist noninvasive techniques such as galvanic vestibular stimulation that perturb between sensor and controller in this way.

On the derivation and tuning of phase oscillator models for lamprey central pattern generators.

Using phase response curves and averaging theory, we derive phase oscillator models for the lamprey central pattern generator from two biophysically-based segmental models. The first one relies on network dynamics within a segment to produce the rhythm, while the second contains bursting cells. We study intersegmental coordination and show that the former class of models shows more robust behavior over the animal's range of swimming frequencies. The network-based model can also easily produce approximately constant phase lags along the spinal cord, as observed experimentally. Precise control of phase lags in the network-based model is obtained by varying the relative strengths of its six different connection types with distance in a phase model with separate coupling functions for each connection type. The phase model also describes the effect of randomized connections, accurately predicting how quickly random network-based models approach the determinisitic model as the number of connections increases.

Coherence analysis of muscle activity during quiet stance.

Studies of muscle activation during perturbed standing have demonstrated that the typical patterns of coordination ("ankle strategy" and "hip strategy") are controlled through multiple muscles activated in a distal-to-proximal or proximal-to-distal temporal pattern. In contrast, quiet stance is thought to be maintained primarily through the ankle musculature. Recently, spectral analysis of inter-segment body motion revealed the coexistence of both ankle and hip patterns of coordination during quiet stance, with the predominating pattern dependent on the frequency of body sway. Here we use frequency domain techniques to determine if these patterns are associated with the same muscular patterns as observed during perturbed stance. Six of the seven muscles measured showed a linear relationship to the sway of at least one body segment, all being leg muscles. Muscle-segment phases were consistent with that required to resist gravity at low frequencies, with increasing phase lag as frequency increased. Visual information had effects only at frequencies below 0.5 Hz, where the shift from in-phase to anti-phase trunk-leg co-phase was observed. These results indicate that co-existence of the ankle and hip pattern during quiet stance involves only leg musculature. Anti-phase movement of the trunk relative to the legs at higher frequencies arises from indirect biomechanical control from posterior leg muscles.

Asymmetric adaptation with functional advantage in human sensorimotor control.

Human movement control is inherently stochastic, requiring continuous estimation of self-motion based upon noisy sensory inputs. The nervous system must determine which sensory signals are relevant on a time scale that enables successful behavior. In human stance control, failure to effectively adapt to changing sensory contexts could lead to injurious falls. Nonlinear changes in postural sway amplitude in response to changes in sensory environmental motion have indicated a dynamic changing of the weighting of the nervous system's multiple sensory inputs so that estimates are based upon the most relevant and accurate information available. However, the time scale of these changes is virtually unknown. Results here show systematic changes in postural gain when visual scene motion amplitude is increased or decreased abruptly, consistent with sensory re-weighting. However, this re-weighting displayed a temporal asymmetry. When visual motion increased, gain decreased within 5 s to a value near its asymptotic value. In contrast, when visual motion decreased, it took an additional 5 s for gain to increase by a similar absolute amount. Suddenly increasing visual motion amplitude threatens balance if gain remains high, and rapid down-weighting of the sensory signal is required to avoid falling. By contrast, slow up-weighting suggests a conservative CNS strategy. It may not be functional to rapidly up-weight with transient changes in the sensory environment. Only sustained changes necessitate the slower up-weighting process. Such results add to our understanding of adaptive processing, identifying a temporal asymmetry in sensory re-weighting dynamics that could be a general property of adaptive estimation in the nervous system.

The role of vestibular and somatosensory systems in intersegmental control of upright stance.

Upright stance was perturbed using sinusoidal platform rotations to see how vestibular and somatosensory information are used to control segment and intersegmental dynamics in subjects with bilateral vestibular loss (BVL) and healthy controls (C). Subjects stood with eyes closed on a rotating platform (+/-1.2 degrees) for frequencies ranging from 0.01-0.4 Hz in the presence and absence of light fingertip touch. Trunk movement relative to the platform of BVLs was higher than Cs at higher platform frequencies whereas leg movement relative to the platform was similar for both groups. With the addition of light touch, both groups showed similar trunk and leg segment movement relative to the platform. Trunk-leg coordination was in-phase for frequencies below 1 Hz and anti-phase above 1 Hz. Interestingly, BVLs showed evidence of a "legs-leading-trunk" relationship in the shift from in-phase to anti-phase around 1 Hz. Controls showed no preference for either segment to lead the coordinative shift from in- to anti-phase. The results suggest that the balance instability of BVL subjects stems from high variability of the trunk, rather than the legs. The high trunk variability may emerge from the "legs-leading" intersegmental relationship upon which BVLs rely. Because BVLs derive information about self-orientation primarily from the support surface when their eyes are closed, the legs initiate the shift to anti-phase trunk-leg coordination that is necessary for stable upright stance control. Higher trunk variability suggests that this strategy results in lower overall postural stability. Light touch substitutes for vestibular information, leading to lower trunk variability along with a trunk-leg phase shift similar to controls, without a preference for either segment to lead the shift. The results suggest that vestibulospinal control acts primarily to stabilize the trunk in space and to facilitate intersegmental dynamics.

A Tool to Quantify the Functional Impact of Oscillopsia.

BACKGROUND: Individuals with bilateral vestibular hypofunction (BVH) often report symptoms of oscillopsia during walking. Existing assessments of oscillopsia are limited to descriptions of severity and symptom frequency, neither of which provides a description of functional limitations attributed to oscillopsia. A novel questionnaire, the Oscillopsia Functional Impact scale (OFI) was developed to describe the impact of oscillopsia on daily life activities. Questions on the OFI ask how often individuals are able to execute specific activities considered to depend on gaze stability in an effort to link functional mobility impairments to oscillopsia for individuals with vestibular loss. METHODS: Subjective reports of oscillopsia and balance confidence were recorded for 21 individuals with BVH and 48 healthy controls. Spearman correlation coefficients were calculated to determine the relationship between the OFI and oscillopsia visual analog scale (OS VAS), oscillopsia severity questionnaire (OSQ), and Activities-Specific Balance Confidence scale to demonstrate face validity. Chronbach's α was calculated to determine internal validity for the items of the OFI. A one-way MANOVA was conducted with planned post hoc paired t-tests for group differences on all oscillopsia questionnaires using a corrected α = 0.0125. RESULTS: The OFI was highly correlated with measures of oscillopsia severity (OS VAS; r = 0.69, p < 0.001) and frequency (OSQ; r = 0.84, p < 0.001) and also with the Activities-Specific Balance Confidence scale (r = -0.84, p < 0.001). Cronbach's α for the OFI was 0.97. Individuals with BVH scored worse on all measures of oscillopsia and balance confidence compared to healthy individuals (p's < 0.001). CONCLUSION: The OFI appears to capture the construct of oscillopsia in the context of functional mobility. Combining with oscillopsia metrics that quantify severity and frequency allows for a more complete characterization of the impact of oscillopsia on an individual's daily behavior. The OFI discriminated individuals with BVH from healthy individuals.

Intra-auditory integration between pitch and loudness in humans: Evidence of super-optimal integration at moderate uncertainty in auditory signals.

When a person plays a musical instrument, sound is produced and the integrated frequency and intensity produced are perceived aurally. The central nervous system (CNS) receives defective afferent signals from auditory systems and delivers imperfect efferent signals to the motor system due to the noise in both systems. However, it is still little known about auditory-motor interactions for successful performance. Here, we investigated auditory-motor interactions as multi-sensory input and multi-motor output system. Subjects performed a constant force production task using four fingers in three different auditory feedback conditions, where either the frequency (F), intensity (I), or both frequency and intensity (FI) of an auditory tone changed with sum of finger forces. Four levels of uncertainty (high, moderate-high, moderate-low, and low) were conditioned by manipulating the feedback gain of the produced force. We observed performance enhancement under the FI condition compared to either F or I alone at moderate-high uncertainty. Interestingly, the performance enhancement was greater than the prediction of the Bayesian model, suggesting super-optimality. We also observed deteriorated synergistic multi-finger interactions as the level of uncertainty increased, suggesting that the CNS responded to increased uncertainty by changing control strategy of multi-finger actions.