Biomedical subjects

Tim Kiemel

Publications and source records attributed to Tim Kiemel.

13 recordsLinked to original sources

PubMed2006

The influence of sensory information on two-component coordination during quiet stance.

When standing quietly, human upright stance is typically approximated as a single segment inverted pendulum. In contrast, investigations, which perturb upright stance with support, surface translations or visual driving stimuli have shown that the body behaves like a two-segment pendulum, displaying both in-phase and anti-phase patterns between the upper and lower body. We have recently shown that these patterns co-exist during quiet stance; in-phase and anti-phase for frequencies below and above 1 Hz, respectively. Here we investigated whether the characteristics of these basic patterns were influenced by the addition or removal of sensory information. Ten healthy young subjects stood upright on a rigid platform with different combinations of sensory information: eyes were open or closed with or without light touch contact (<1N) of the right index fingertip with a 5 cm diameter rigid force plate. The in-phase and anti-phase pattern co-exist in both the anterior-posterior (AP) and medial-lateral (ML) directions of sway. The real part of trunk-leg complex coherence decreased with the addition of vision and light touch, corresponding to a transition from the in-phase to anti-phase pattern at a lower frequency. In the AP direction, the decrease was only observed at frequencies below 1 Hz where the in-phase pattern predominates. Additional sensory information had no observable effect at sway frequencies above 1 Hz, where the anti-phase pattern predominates. Both patterns are clearly the result of a double-linked inverted pendulum dynamics, but the coherence of the in-phase pattern is more susceptible to modulation by sensory information than the anti-phase pattern.

Adult↗

PubMed2006

Multisensory reweighting of vision and touch is intact in healthy and fall-prone older adults.

Unexplained falls in older adults are thought to arise from subtle deficits in multiple components of the postural control system, including peripheral sensory loss and central sensory processing. One commonly proposed central sensory processing deficit is a decline in the adaptive use of changing or conflicting sensory inputs for estimating body dynamics, i.e., multisensory reweighting. We examined the assumption of impaired multisensory reweighting in healthy and fall-prone older adults using quantitative methods that have previously demonstrated reweighting in young adults. Standing subjects were exposed to simultaneous medio-lateral oscillatory visual and fingertip touch inputs at varying relative amplitudes. No group differences in overall levels of vision and touch gain were found. Both healthy and fall-prone older adults demonstrated the same pattern of adaptive gain change as healthy young adults. Like the young adults, both elderly groups displayed clear evidence of intra- and inter-sensory reweighting to both vision and touch motion stimuli. These data suggest that, for small amplitude vision and touch stimuli, the central sensory reweighting adaptation process remains intact in healthy and fall-prone older adults with sufficiently intact peripheral sensation.

Accidental Falls↗

PubMed2006

Sensory reweighting with translational visual stimuli in young and elderly adults: the role of state-dependent noise.

The properties of sensory reweighting for control of human upright stance have primarily been investigated through experimental techniques such as sinusoidal driving of postural sway. However, other forms of visual inputs that are commonly encountered, such as translation, may produce different adaptive responses. We directly compared sinusoidal and translatory inputs at stimulus parameters that made stimulus velocity comparable with each type of stimulus. Young healthy individuals were compared with healthy elderly and elderly designated as "fall-prone" to investigate whether the hypothesized basis for poor balance control in the "fall-prone" elderly is related to their ability to reweight sensory inputs appropriately. Standing subjects were presented with visual displays which moved in the medial-lateral direction either by (1) oscillating at different amplitudes or (2) simultaneously oscillating and translating at different speeds. All three subject groups showed that increasing the amplitude of the oscillations led to a decrease in gain. Increasing translation speed led to decreases in gain only at speeds above 1 cm/s. This suggests that the nervous system is processing more than just stimulus velocity to determine the postural response. A model implementing "state-dependent noise", in which visual stimulus noise increases with relative speed, was developed to account for the difference between translation and oscillation. The weak group effects question the common view that the fall-prone elderly are deficient in sensory reweighting. One explanation for the apparent discrepancy is that the slow, small-amplitude visual stimuli used in this study probe the asymptotic dynamics of the postural response. If given enough time, even the fall-prone elderly are able to adapt to a new sensory environment appropriately. However, the asymptotic adaptive response may not be functional in terms of preventing falls.

Adaptation, Physiological↗

PubMed2006

Modeling the dynamics of sensory reweighting.

Reweighting sensory information adaptively is considered critical for flexible postural control, but little is known of the time scale of the reweighting process. We analyzed the transient dynamics of sensory reweighting in a previously published nonlinear adaptive model of sensory integration in the human postural control system. The model's dynamics of adaptation were tested in response to abrupt changes in the amplitude of the motion of the visual surround. In addition to qualitatively reproducing the correct asymptotic response to such changes in visual amplitude, as previously found, the model qualitatively reproduced the asymmetric transient response elucidated in recent experiments (Oie et al. in Gait Posture 2005). In particular, the model adapts at an initially rapid rate to a switch from low to high amplitude visual motion, but at an initially slower rate upon the return to low amplitude motion. The observed temporal asymmetry has potential functional value. Rapid downweighting of a visual stimulus that suddenly increases is necessary to prevent loss of upright equilibrium. A visual stimulus that decreases in amplitude does not pose a threat to upright balance, allowing for slower upweighting without functional consequence.

Adaptation, Physiological↗

PubMed2005

Slow dynamics of postural sway are in the feedback loop.

Postural sway is considered to have two fundamental stochastic components, a slow nonoscillatory component and a faster damped-oscillatory component. The slow component has been shown to account for the majority of sway variance during quiet stance. Postural control is generally viewed as a feedback loop in which sway is detected by sensory systems and appropriate motor commands are generated to stabilize the body's orientation. Whereas the mechanistic source for the damped-oscillatory sway component is most likely feedback control of an inverted pendulum, the underlying basis for the slow component is less clear. We investigated whether the slow process was inside or outside the feedback loop by providing standing subjects with sum-of-sines visual motion. Linear stochastic models were fit to the experimental sway trajectories to determine the stochastic structure of sway as well as the transfer function from visual motion to sway. The results supported a fifth-order stochastic model, consisting of a slow process and two damped-oscillatory components. Importantly, the slow process was determined to be inside the feedback loop. This supports the hypothesis that the slow component is due to errors in state estimation because state estimation is inside the feedback loop rather than a moving reference point or an exploratory process outside the feedback loop.

Adult↗

PubMed2005

Comparing internal models of the dynamics of the visual environment.

It is well known that the human postural control system responds to motion of the visual scene, but the implicit assumptions it makes about the visual environment and what quantities, if any, it estimates about the visual environment are unknown. This study compares the behavior of four models of the human postural control system to experimental data. Three include internal models that estimate the state of the visual environment, implicitly assuming its dynamics to be that of a linear stochastic process (respectively, a random walk, a general first-order process, and a general second-order process). In each case, all of the coefficients that describe the process are estimated by an adaptive scheme based on maximum likelihood. The fourth model does not estimate the state of the visual environment. It adjusts sensory weights to minimize the mean square of the control signal without making any specific assumptions about the dynamic properties of the environmental motion. We find that both having an internal model of the visual environment and its type make a significant difference in how the postural system responds to motion of the visual scene. Notably, the second-order process model outperforms the human postural system in its response to sinusoidal stimulation. Specifically, the second-order process model can correctly identify the frequency of the stimulus and completely compensate so that the motion of the visual scene has no effect on sway. In this case the postural control system extracts the same information from the visual modality as it does when the visual scene is stationary. The fourth model that does not simulate the motion of the visual environment is the only one that reproduces the experimentally observed result that, across different frequencies of sinusoidal stimulation, the gain with respect to the stimulus drops as the amplitude of the stimulus increases but the phase remains roughly constant. Our results suggest that the human postural control system does not estimate the state of the visual environment to respond to sinusoidal stimuli.

Algorithms↗

PubMed2004

A unified view of quiet and perturbed stance: simultaneous co-existing excitable modes.

When standing quietly, human upright stance is typically approximated as a single segment inverted pendulum. In contrast, investigations which perturb upright stance with support surface translations or visual driving stimuli have shown that the body behaves like a two-segment pendulum, displaying both in-phase and anti-phase patterns between the upper and lower body. Here we present evidence that a single-segment characterization of quiet stance is inadequate. Similar to perturbed stance, quiet stance has simultaneously co-existing in-phase and anti-phase patterns. Subjects stood with eyes closed in three sensory conditions: a fixed surface, a foam surface, and a sway-referenced surface. Spectral analysis showed that the body behaved like a multi-link pendulum with two co-existing modes. The angles of the trunk and leg segments were in-phase for frequencies below 1 Hz and anti-phase for frequencies above 1Hz. The shift from in-phase to anti-phase sway showed an abrupt change for the fixed and foam surfaces, but a gradual change for the sway-referenced condition with the trunk showing a phase lead over the legs. The coexistence of in-phase and anti-phase patterns during quiet stance suggests that the ankle and hip strategies are not extremes along a behavioral continuum of mixed strategies. They are "simultaneously co-existing excitable modes", both always present, but one of which may predominate depending upon the characteristics of the available sensory information, task or perturbation.

Adult↗

PubMed2004

Nonlinear postural control in response to visual translation.

Recent models of human postural control have focused on the nonlinear properties inherent to fusing sensory information from multiple modalities. In general, these models are underconstrained, requiring additional experimental data to clarify the properties of such nonlinearities. Here we report an experiment suggesting that new or multiple mechanisms may be needed to capture the integration of vision into the postural control scheme. Subjects were presented with visual displays whose motion consisted of two components: a constant-amplitude, 0.2 Hz oscillation, and constant-velocity translation from left to right at velocities between 0 cm/s and 4 cm/s. Postural sway variability increased systematically with translation velocity, but remained below that observed in the eyes-closed condition, indicating that the postural control system is able to use visual information to stabilize sway even at translation velocities as high as 4 cm/s. Gain initially increased as translation velocity increased from 0 cm/s to 1 cm/s and then decreased. The changes in gain and variability provided a clear indication of nonlinearity in the postural response across conditions, which were interpreted in terms of sensory reweighting. The fact that gain did not decrease at low translation velocities suggests that the postural control system is able to decompose relative visual motion into environmental motion and self-motion. The eventual decrease in gain suggests that nonlinearities in sensory noise levels (state-dependent noise) may also contribute to the sensory reweighting involved in postural control. These results provide important constraints and suggest that multiple mechanisms may be required to model the nonlinearities involved in sensory fusion for upright stance control.

Adult↗

PubMed2004

Controlling human upright posture: velocity information is more accurate than position or acceleration.

The problem of how the nervous system fuses sensory information from multiple modalities for upright stance control remains largely unsolved. It is well established that the visual, vestibular, and somatosensory modalities provide position and rate (e.g., velocity, acceleration) information for estimation of body dynamics. However, it is unknown whether any particular property dominates when multisensory information is fused. Our recent stochastic analysis of postural sway during quiet stance suggested that sensory input provides more accurate information about the body's velocity than its position or acceleration. Here we tested this prediction by degrading major sources of velocity information through removal/attenuation of sensory information from vision and proprioception. Experimental measures of postural sway were compared with model predictions to determine whether sway behavior was indicative of a deficit in velocity information rather than position or acceleration information. Subjects stood with eyes closed on a support surface that was 1) fixed, 2) foam, or 3) sway-referenced. Six measures characterizing the stochastic structure of postural sway behaved in a manner consistent with model predictions of degraded velocity information. Results were inconsistent with the effect of degrading only position or acceleration information. These findings support the hypothesis that velocity information is the most accurate form of sensory information used to stabilize posture during quiet stance. Our results are consistent with the assumption that changes in sway behavior resulting from commonly used experimental manipulations (e.g., foam, sway-referencing, eyes closed) are primarily attributed to loss of accurate velocity information.

Acceleration↗

PubMed2002

Limited control strategies with the loss of vestibular function.

When subjects stand on an unstable or compliant support surface, rather than a stable one, vestibular information becomes more important for the control of posture. We investigated how subjects with bilateral vestibular loss (BVL) controlled their upright posture, with and without light-touch contact at the fingertip, while standing on a support surface, sinusoidally rotating at different frequencies. Subjects stood with eyes closed on a platform that rotated +/-1.2 degrees around an axis directly beneath the midline of the ankle for frequencies ranging from 0.01 to 0.4 Hz for two sensory conditions: (1) with light, nonsupportive touch (less than 1 N vertical force) on a stationary surface; or (2) with the fingertip held in a position directly above the contact surface (no contact). Gain, phase, and variability of the center of mass (CoM) and the finger were analyzed to compare BVL subjects with healthy controls in the no-touch and light-touch conditions. Three important results were observed: First, CoM gain and variability of BVL subjects was distinctly higher than control subjects with no-touch contact, particularly at the higher platform frequencies. Second, with light-touch contact, BVL and control subjects showed equivalent gain, variability, and phase. Third, multiple relationships between the finger and the CoM were observed in control subjects, whereas BVL subjects implemented a single finger/CoM control scheme. The results are explained in terms of three interacting factors: the transfer function of the vestibular system, a sensory reweighting mechanism, and the inertial properties of the body. Moreover, multiple control strategies observed in control subjects suggest a more flexible control system than that of individuals with severely diminished vestibular function.

Aged↗

PubMed2002

Multisensory fusion and the stochastic structure of postural sway.

We analyze the stochastic structure of postural sway and demonstrate that this structure imposes important constraints on models of postural control. Linear stochastic models of various orders were fit to the center-of-mass trajectories of subjects during quiet stance in four sensory conditions: (i) light touch and vision, (ii) light touch, (iii) vision, and (iv) neither touch nor vision. For each subject and condition, the model of appropriate order was determined, and this model was characterized by the eigenvalues and coefficients of its autocovariance function. In most cases, postural-sway trajectories were similar to those produced by a third-order model with eigenvalues corresponding to a slow first-order decay plus a faster-decaying damped oscillation. The slow-decay fraction, which we define as the slow-decay autocovariance coefficient divided by the total variance, was usually near 1. We compare the stochastic structure of our data to two linear control-theory models: (i) a proportional-integral-derivative control model in which the postural system's state is assumed to be known, and (ii) an optimal-control model in which the system's state is estimated based on noisy multisensory information using a Kalman filter. Under certain assumptions, both models have eigenvalues consistent with our results. However, the slow-decay fraction predicted by both models is less than we observe. We show that our results are more consistent with a modification of the optimal-control model in which noise is added to the computations performed by the state estimator. This modified model has a slow-decay fraction near 1 in a parameter regime in which sensory information related to the body's velocity is more accurate than sensory information related to position and acceleration. These findings suggest that: (i) computation noise is responsible for much of the variance observed in postural sway, and (ii) the postural control system under the conditions tested resides in the regime of accurate velocity information.

Adult↗

PubMed2002

Multisensory fusion: simultaneous re-weighting of vision and touch for the control of human posture.

We examined the generally held belief that the postural control system is able to re-weight its available sensory inputs in order to optimize stance control in altered sensory environments. Our view is that previous accounts of sensory re-weighting provide only indirect evidence, which is subject to alternative explanations. The present results provide strong evidence for sensory re-weighting as the primary mechanism for changes observed in postural sway between conditions. Subjects were presented with small-amplitude, oscillatory visual and somatosensory stimuli at 0.20 and 0.28 Hz, respectively, in five conditions that manipulated the amplitudes of stimulus motion. Gain calculated in each trial with respect to each of the two stimuli was found to change systematically as stimulus motion amplitudes changed across condition. The observed pattern of gain rules out a constant-weight, linear account of posture and is consistent with the re-weighting hypothesis. Parameter fits of a third-order, linear stochastic model to postural sway trajectories in each condition showed that changes in gain across condition were primarily due to changes in coupling coefficients rather than changes in parameters that characterize the stability of the postural system. Visual gain was found to depend upon visual motion amplitude and touch gain was found to depend upon touch motion amplitude, indicating intra-modality dependencies. Visual gain also depended upon touch motion amplitude, indicating an inter-modality dependence. To our knowledge, simultaneous re-weighting of more than one sensory input has never been rigorously demonstrated. These techniques may be able to resolve the source of balance control deficits across populations with far more certainty than currently possible.

Adult↗

PubMedDate not supplied

Estimating the strength and direction of functional coupling in the lamprey spinal cord.

A method of estimating coupling strength between two neural oscillators based on their spikes trains (Kiemel and Cohen, J. Comput. Neurosci. 5: 267-284, 1998) is tested using simulated data and then applied to experimental data from the central pattern generator (CPG) for swimming in the lamprey. The method is tested using a model of two connectionist oscillators and a model of two endogenously bursting cells. For both models, the method provides useful estimates of the relative strength of coupling in each direction, as well as estimates of total strength. The method is applied to pairs of motor-nerve recordings from isolated 50-segment pieces of spinal cords from adult silver lampreys (Ichthyomyzon unicuspus). The strength and direction of coupling is estimated under control conditions and conditions in which intersegmental coupling between the two recording locations is weakened by hemisections of the spinal cords and/or chambers containing an inhibitory solution that blocks firing in postsynaptic cells. The relevance of these measures in constraining models of the CPG is discussed.

Action Potentials↗