Model for the translational vestibuloocular reflex (VOR)

Nondestructive and objective assessment of the vestibular function in rodent models: A review

The normal function of the vestibular system is crucial for the sense of balance. The techniques used to assess the vestibular function plays a vital role in the research of the vestibular system. In this article, we have systematically reviewed some popular methods employing vestibular reflexes and vestibular evoked potentials for assessing the vestibular function in rodent models. These vestibular reflexes and vestibular evoked potentials to effective stimuli have been used as nondestructive and objective functional measures. The main types of vestibular reflexes include the vestibulo-ocular reflex (VOR), vestibulocollic reflex (VCR), and vestibulo-sympathetic reflex (VSR). They are all capable of indicating the functions of the semicircular canals and otoliths. However, the VOR assessment is much more prevalently used because of the relatively stereotypical inputoutput relationship and simple motion pattern of the ocular response. In contrast, the complicated motion pattern and small gain of the VCR response, as well as the undesired component possibly contributed from the acceleration receptors outside the labyrinths in the VSR response, restrict the widespread applications of VCR and VSR in the assessment of the vestibular system. The vestibular evoked myogenic potentials (VEMPs) and vestibular sensory evoked potentials (VsEPs) are the two typical evoked potentials that have been also employed for evaluating the vestibular function. Through exploiting different types of the VEMPs, the saccular and utricular functions can be evaluated separately. The sound-induced VEMPs, moreover, are capable of noninvasively assessing the unilateral vestibular function. The VsEPs, via the morphology of their signal waveforms, enable the access to the location-specific information that indicates the functional statuses of different components within the vestibular neural pathway.

The cerebellar nodulus/uvula integrates otolith signals for the translational vestibulo-ocular reflex

Background

The otolith-driven translational vestibulo-ocular reflex (tVOR) generates compensatory eye movements to linear head accelerations. Studies in humans indicate that the cerebellum plays a critical role in the neural control of the tVOR, but little is known about mechanisms of this control or the functions of specific cerebellar structures. Here, we chose to investigate the contribution of the nodulus and uvula, which have been shown by prior studies to be involved in the processing of otolith signals in other contexts.

Methodology/Principal Findings

We recorded eye movements in two rhesus monkeys during steps of linear motion along the interaural axis before and after surgical lesions of the cerebellar uvula and nodulus. The lesions strikingly reduced eye velocity during constant-velocity motion but had only a small effect on the response to initial head acceleration. We fit eye velocity to a linear combination of head acceleration and velocity and to a dynamic mathematical model of the tVOR that incorporated a specific integrator of head acceleration. Based on parameter optimization, the lesion decreased the gain of the pathway containing this new integrator by 62%. The component of eye velocity that depended directly on head acceleration changed little (gain decrease of 13%). In a final set of simulations, we compared our data to the predictions of previous models of the tVOR, none of which could account for our experimental findings.

Conclusions/ Significance

Our results provide new and important information regarding the neural control of the tVOR. Specifically, they point to a key role for the cerebellar nodulus and uvula in the mathematical integration of afferent linear head acceleration signals. This function is likely to be critical not only for the tVOR but also for the otolith-mediated reflexes that control posture and balance.

Internal models and neural computation in the vestibular system

The vestibular system is vital for motor control and spatial self-motion perception. Afferents from the otolith organs and the semicircular canals converge with optokinetic, somatosensory and motor-related signals in the vestibular nuclei, which are reciprocally interconnected with the vestibulocerebellar cortex and deep cerebellar nuclei. Here, we review the properties of the many cell types in the vestibular nuclei, as well as some fundamental computations implemented within this brainstem-cerebellar circuitry. These include the sensorimotor transformations for reflex generation, the neural computations for inertial motion estimation, the distinction between active and passive head movements, as well as the integration of vestibular and proprioceptive information for body motion estimation. A common theme in the solution to such computational problems is the concept of internal models and their neural implementation. Recent studies have shed new insights into important organizational principles that closely resemble those proposed for other sensorimotor systems, where their neural basis has often been more difficult to identify. As such, the vestibular system provides an excellent model to explore common neural processing strategies relevant both for reflexive and for goal-directed, voluntary movement as well as perception.

A reevaluation of the inverse dynamic model for eye movements

To construct an appropriate motor command from signals that provide a representation of desired action, the nervous system must take into account the dynamic characteristics of the motor plant to be controlled. In the oculomotor system, signals specifying desired eye velocity are thought to be transformed into motor commands by an inverse dynamic model of the eye plant that is shared for all types of eye movements and implemented by a weighted combination of eye velocity and position signals. Neurons in the prepositus hypoglossi and adjacent medial vestibular nuclei (PH-BT neurons) were traditionally thought to encode the "eye position" component of this inverse model. However, not only are PH-BT responses inconsistent with this theoretical role, but compensatory eye movement responses to translation do not show evidence for processing by a common inverse dynamic model. Prompted by these discrepancies between theoretical notions and experimental observations, we reevaluated these concepts using multiple-frequency rotational and translational head movements. Compatible with the notion of a common inverse model, we show that PH-BT responses are unique among all premotor cell types in bearing a consistent relationship to the motor output during eye movements driven by different sensory stimuli. However, because their responses are dynamically identical to those of motoneurons, PH-BT neurons do not simply represent an internal component of the inverse model, but rather its output. They encode and distribute an estimate of the motor command, a signal critical for accurate motor execution and learning.

Interaural Translational VOR: Suppression, Enhancement, and Cognitive Control

We investigated the influence of cognitive factors on the early response of the interaural translational vestibuloocular reflex (tVOR) in six normal subjects. Variables were prior knowledge of direction of head motion and the position of the fixation target relative to the head [head-fixed (HF) or space-fixed (SF)]. A manually driven device provided a step-like head translation (∼35 mm distance, peak acceleration, 0.6–1.3 g). Subjects looked at the SF or HF target located 15 cm in front of their heads in otherwise complete darkness. The testing paradigms were: random interleaving of SF and HF targets with unknown direction of head movement, known target location with random head direction (SFR or HFR), and known target location with known head direction (SFP or HFP). Timing was always unpredictable. A “gain” of the slow phase was calculated with respect to ideal performance (maintained fixation of the SF target, recorded/ideal eye velocity computed at time of peak head velocity). At such times, there were no significant differences in gain between HF and SF trials in the random condition; the average gain was ∼36% of ideal. On the other hand, responses in the SFR and HFR conditions differed as early as 20 ms after the head began moving. Average gain was higher (0.43 ± 0.11 vs. 0.34 ± 0.14; means ± SD, P < 0.05) for each subject in the SFR than the HFR condition. For SFP and HFP, the responses differed from the onset of head motion. Average slow-phase gain was higher (0.49 ± 0.12 vs. 0.31 ± 0.12, P < 0.02) for each subject in SFP than in HFP. The timing of corrective saccades during the tVOR was also influenced by cognitive factors. Visual error signals seemed to be more important for triggering saccades in HF trials, whereas preprogramming, probably based on labyrinthine information, seemed to be more important in SF trials. Simulations showed that the changes in slow-phase gain with cognition could be reproduced with simple parametric adjustments of the gain of activity from otolith afferents and suggest that higher-level cognitive control of the VOR could occur as early as the synapse of peripheral afferents on neurons in the vestibular nuclei, either directly from higher level centers or via the cerebellum. In sum, the tVOR—both in its slow-phase response and the saccadic corrections—is subject to “higher-level” cognitive influences including knowledge of where the line of sight must point during head motion and the impending direction of head motion.

Three dimensional spatial-temporal convergence of otolith related signals in vestibular only neurons in squirrel monkeys

Spatio-temporal convergence (STC) properties of 19 vestibular only neurons' responses to translational head movements were examined in an alert, behaving squirrel monkey. In addition to standard tests that included 1.2 Hz yaw/pitch/roll rotations and inter-aural/naso-occipital/dorso-ventral translations, we also observed responses to translations along multiple directions in several orthogonal planes. Neural responses were fitted first by a model that permitted STC in all planes, characterized by a non-zero minimum and a gradual shift of phase. We then evaluated statistically whether models with fewer independent dynamic parameters yielded equally satisfactory results. The responses of 13 neurons were adequately fit by simple cosine models (1-D) as well as models that allowed complex STC behavior. Of the six neurons exhibiting STC, five could be modeled with two independent phase parameters (2-D) while the remaining neuron required a model with three independent phase parameters (3-D). The maximum translation sensitivity and phase, Smax and varphimax, and minimum translation sensitivity and phase, Smin and varphimin, were estimated from the reconstructed sensitivity and phase surfaces. The tuning ratio, Smin/Smax, in STC neurons was>0.40 while in 1-D neurons it was <0.25. Furthermore, the maximum response vectors of most 1-D neurons lay within 20 degrees of either the horizontal or sagittal plane while those of STC neurons lay >20 degrees from both planes. No difference in other response properties, such as varphimax or rotational responses, was found between neurons exhibiting STC and the simple cosine tuning. Our results suggest that the STC behavior observed in otolith-related vestibular neurons probably arises from summing inputs from afferents, with diverse response dynamics, innervating different otolith macula.

An Integrative Neural Network for Detecting Inertial Motion and Head Orientation

The ability to navigate in the world and execute appropriate behavioral responses depends critically on the contribution of the vestibular system to the detection of motion and spatial orientation. A complicating factor is that otolith afferents equivalently encode inertial and gravitational accelerations. Recent studies have demonstrated that the brain can resolve this sensory ambiguity by combining signals from both the otoliths and semicircular canal sensors, although it remains unknown how the brain integrates these sensory contributions to perform the nonlinear vector computations required to accurately detect head movement in space. Here, we illustrate how a physiologically relevant, nonlinear integrative neural network could be used to perform the required computations for inertial motion detection along the interaural head axis. The proposed model not only can simulate recent behavioral observations, including a translational vestibuloocular reflex driven by the semicircular canals, but also accounts for several previously unexplained characteristics of central neural responses such as complex otolith–canal convergence patterns and the prevalence of dynamically processed otolith signals. A key model prediction, implied by the required computations for tilt–translation discrimination, is a coordinate transformation of canal signals from a head-fixed to a spatial reference frame. As a result, cell responses may reflect canal signal contributions that cannot be easily detected or distinguished from otolith signals. New experimental protocols are proposed to characterize these cells and identify their contributions to spatial motion estimation. The proposed theoretical framework makes an essential first link between the computations for inertial acceleration detection derived from the physical laws of motion and the neural response properties predicted in a physiologically realistic network implementation.

Eyes on Target: What Neurons Must do for the Vestibuloocular Reflex During Linear Motion

A gaze-stabilization reflex that has been conserved throughout evolution is the rotational vestibuloocular reflex (RVOR), which keeps images stable on the entire retina during head rotation. An ethological newer reflex, the translational or linear VOR (TVOR), provides fast foveal image stabilization during linear motion. Whereas the sensorimotor processing has been extensively studied in the RVOR, much less is currently known about the neural organization of the TVOR. Here we summarize the computational problems faced by the system and the potential solutions that might be used by brain stem and cerebellar neurons participating in the VORs. First and foremost, recent experimental and theoretical evidence has shown that, contrary to popular beliefs, the sensory signals driving the TVOR arise from both the otolith organs and the semicircular canals. Additional unresolved issues include a scaling by both eye position and vergence angle as well as the temporal transformation of linear acceleration signals into eye-position commands. Behavioral differences between the RVOR and TVOR, as well as distinct differences in neuroanatomical and neurophysiological properties, raise multiple functional questions and computational issues, only some of which are readily understood. In this review, we provide a summary of what is known about the functional properties and neural substrates for this oculomotor system and outline some specific hypotheses about how sensory information is centrally processed to create motor commands for the VORs.

Resolution of sensory ambiguities for gaze stabilization requires a second neural integrator

The ability to simultaneously move in the world and maintain stable visual perception depends critically on the contribution of vestibulo-ocular reflexes (VORs) to gaze stabilization. It is traditionally believed that semicircular canal signals drive compensatory responses to rotational head disturbances (rotational VOR), whereas otolith signals compensate for translational movements [translational VOR (TVOR)]. However, a sensory ambiguity exists because otolith afferents are activated similarly during head translations and reorientations relative to gravity (i.e., tilts). Extra-otolith cues are, therefore, necessary to ensure that dynamic head tilts do not elicit a TVOR. To investigate how extra-otolith signals contribute, we characterized the temporal and viewing distance-dependent properties of a TVOR elicited in the absence of a lateral acceleration stimulus to the otoliths during combined translational/rotational motion. We show that, in addition to otolith signals, angular head position signals derived by integrating sensory canal information drive the TVOR. A physiological basis for these results is proposed in a model with two distinct integration steps. Upstream of the well known oculomotor velocity-to-position neural integrator, the model incorporates a separate integration element that could represent the "velocity storage integrator," whose functional role in the oculomotor system has so far remained controversial. We propose that a key functional purpose of the velocity storage network is to temporally integrate semicircular canal signals, so that they may be used to extract translation information from ambiguous otolith afferent signals in the natural and functionally relevant bandwidth of head movements.

Asymmetric integration recorded from vestibular-only cells in response to position transients

Angular and translational accelerations excite the semicircular canals and otolith organs, respectively. While canal afferents approximately encode head angular velocity due to the biomechanical integration performed by the canals, otolith signals have been found to approximate head translational acceleration. Because central vestibular pathways require velocity and position signals for their operation, the question has been raised as to how the integration of the otolith signals is accomplished. We recorded responses from 62 vestibular-only neurons in the vestibular nucleus of two monkeys to position transients in the naso-occipital and interaural orientations and varying directions in between. Responses to the transients were directionally asymmetric; one direction elicited a response that approximated the integral of the acceleration of the stimulus. In the opposite direction, the cells simply encoded the acceleration of the motion. We present a model that suggests that a neural integrator is not needed. Instead a neuron with a long membrane time constant and an excitatory postsynaptic potential duration that increases with the firing rate of the presynaptic cell can emulate the observed behavior.

Neural processing of gravitoinertial cues in humans. III. Modeling tilt and translation responses

All linear accelerometers measure gravitoinertial force, which is the sum of gravitational force (tilt) and inertial force due to linear acceleration (translation). Neural strategies must exist to elicit tilt and translation responses from this ambiguous cue. To investigate these neural processes, we developed a model of human responses and simulated a number of motion paradigms used to investigate this tilt/translation ambiguity. In this model, the separation of GIF into neural estimates of gravity and linear acceleration is accomplished via an internal model made up of three principal components: 1) the influence of rotational cues (e.g., semicircular canals) on the neural representation of gravity, 2) the resolution of gravitoinertial force into neural representations of gravity and linear acceleration, and 3) the neural representation of the dynamics of the semicircular canals. By combining these simple hypotheses within the internal model framework, the model mimics human responses to a number of different paradigms, ranging from simple paradigms, like roll tilt, to complex paradigms, like postrotational tilt and centrifugation. It is important to note that the exact same mechanisms can explain responses induced by simple movements as well as by more complex paradigms; no additional elements or hypotheses are needed to match the data obtained during more complex paradigms. Therefore these modeled response characteristics are consistent with available data and with the hypothesis that the nervous system uses internal models to estimate tilt and translation in the presence of ambiguous sensory cues.

Human gaze stabilization during active head translations

This study investigated how binocular gaze is controlled to compensate for self-generated translational movements of the head where geometric requirements dictate that the ideal gaze signal needs to be modulated by the inverse of target distance. Binocular gaze (eye plus head) was measured for visual and remembered targets at various distances in six human subjects during active head translations at frequencies of 0.25, 0.5, 1.0, and 1.5 Hz. We found that, during head translations, gaze changes were achieved by a combination of eye and head rotations. Accordingly, stabilization performance was characterized by the gaze response parameters sensitivity and phase, where sensitivity is defined as the ratio of gaze velocity and translational eye velocity and where phase refers to the phase delay of gaze velocity relative to translational eye velocity. In the analysis, we used a binocular coordinate system yielding a version and a vergence component. We examined how frequency and target distance, estimated from the vergence angle, affected sensitivity and phase of the version component of the gaze signal and compared the results to the requirements for ideal performance. The relation between gaze sensitivity and the inverse of distance was characterized by a linear regression analysis. The ratio of the slope of the linear regression and the slope required for ideal stabilization provided a measure for the degree of "distance compensation." The results show that distance compensation was better for a visual target than for remembered targets in darkness, and behaved according to low-pass characteristics in both target conditions. It declined from 1.00 to 0.84 for visual targets and from 0.87 to 0.57 for remembered targets in the frequency range 0.25-1.5 Hz. The intercept obtained from the regression yielded the gaze response at zero vergence and specified a "default sensitivity" of gaze compensation. Default sensitivity increased with frequency from 0.02 at 0.25 Hz to 0.10 degrees/cm at 1.5 Hz for visual targets and from 0.04 to 0.16 degrees/cm in darkness. The phase delays of the gaze response increased on average from 2 to 7 degrees in the frequency range 0.25-1.5 Hz. In comparison with earlier passive studies, active translation compensation in the dark is superior at all frequencies where comparison was possible. We conclude that a nonvestibular signal with low-pass characteristics contributes to gaze during active head translations.

Differential sensorimotor processing of vestibulo-ocular signals during rotation and translation

Rotational and translational vestibulo-ocular reflexes (RVOR and TrVOR) function to maintain stable binocular fixation during head movements. Despite similar functional roles, differences in behavioral, neuroanatomical, and sensory afferent properties suggest that the sensorimotor processing may be partially distinct for the RVOR and TrVOR. To investigate the currently poorly understood neural correlates for the TrVOR, the activities of eye movement-sensitive neurons in the rostral vestibular nuclei were examined during pure translation and rotation under both stable gaze and suppression conditions. Two main conclusions were made. First, the 0.5 Hz firing rates of cells that carry both sensory head movement and motor-like signals during rotation were more strongly related to the oculomotor output than to the vestibular sensory signal during translation. Second, neurons the firing rates of which increased for ipsilaterally versus contralaterally directed eye movements (eye-ipsi and eye-contra cells, respectively) exhibited distinct dynamic properties during TrVOR suppression. Eye-ipsi neurons demonstrated relatively flat dynamics that was similar to that of the majority of vestibular-only neurons. In contrast, eye-contra cells were characterized by low-pass filter dynamics relative to linear acceleration and lower sensitivities than eye-ipsi cells. In fact, the main secondary eye-contra neuron in the disynaptic RVOR pathways (position-vestibular-pause cell) that exhibits a robust modulation during RVOR suppression did not modulate during TrVOR suppression. To explain these results, a simple model is proposed that is consistent with the known neuroanatomy and postulates differential projections of sensory canal and otolith signals onto eye-contra and eye-ipsi cells, respectively, within a shared premotor circuitry that generates the VORs.