Processing of angular motion and gravity information through an internal model

Modeling the effect of gravity on periodic alternating nystagmus

Periodic alternating nystagmus (PAN) is a rare oscillatory ocular motor disorder. The effects of gravity on the dynamic behavior of PAN can be studied by monitoring the nystagmus while changing head orientation. Previous studies of patients with PAN reached different conclusions about the effect of changing the orientation of the head relative to gravity on the ongoing PAN, either no effect or a damping of the nystagmus within several minutes. What neuronal circuits could account for the difference in the effects of gravity among PAN patients? We modeled how the brain resolves the tilt-translation ambiguity in normal individuals and added an unstable, oscillatory vestibular system generating PAN. PAN was suppressed in our patient in ear-down positions, in a similar pattern to that of a previously reported patient. This effect was simulated by reducing the gain of the projection of the "rotation feedback" loop to the velocity-storage integrator to approximately 5% of its normal value. With normal "rotation feedback" PAN is expected to dissipate quickly as soon as the head is rotated away from upright position. Moreover, by disconnecting the rotation feedback completely (gain = zero) the model simulated PAN that was reported to be unaffected by gravity. Thus, understanding the effect of this single parameter, the gain of the rotation feedback, can explain the observed variability among our own and previous studies.

The otolith vermis: A systems neuroscience theory of the Nodulus and Uvula

The Nodulus and Uvula (NU) (lobules X and IX of the cerebellar vermis) form a prominent center of vestibular information processing. Over decades, fundamental and clinical research on the NU has uncovered many aspects of its function. Those include the resolution of a sensory ambiguity inherent to inertial sensors in the inner ear, the otolith organs; the use of gravity signals to sense head rotations; and the differential processing of self-generated and externally imposed head motion. Here, I review these works in the context of a theoretical framework of information processing called the internal model hypothesis. I propose that the NU implements a forward internal model to predict the activation of the otoliths, and outputs sensory predictions errors to correct internal estimates of self-motion or to drive learning. I show that a Kalman filter based on this framework accounts for various functions of the NU, neurophysiological findings, as well as the clinical consequences of NU lesions. This highlights the role of the NU in processing information from the otoliths and supports its denomination as the "otolith" vermis.

Simple spike dynamics of Purkinje cells in the macaque vestibulo-cerebellum during passive whole-body self-motion

Theories of cerebellar functions posit that the cerebellum implements internal models for online correction of motor actions and sensory estimation. As an example of such computations, an internal model resolves a sensory ambiguity where the peripheral otolith organs in the inner ear sense both head tilts and translations. Here we exploit the response dynamics of two functionally coupled Purkinje cell types in the vestibular part of the caudal vermis (lobules IX and X) to understand their role in this computation. We find that one population encodes tilt velocity, whereas the other, translation-selective, population encodes linear acceleration. We predict that an intermediate neuronal type should temporally integrate the output of tilt-selective cells into a tilt position signal.

The Brain Compass: A Perspective on How Self-Motion Updates the Head Direction Cell Attractor

Head direction cells form an internal compass signaling head azimuth orientation even without visual landmarks. This property is generated by a neuronal ring attractor that is updated using rotation velocity cues. The properties and origin of this velocity drive remain, however, unknown. We propose a quantitative framework whereby this drive represents a multisensory self-motion estimate computed through an internal model that uses sensory prediction errors of vestibular, visual, and somatosensory cues to improve on-line motor drive. We show how restraint-dependent strength of recurrent connections within the attractor can explain differences in head direction cell firing between free foraging and restrained passive rotation. We also summarize recent findings on how gravity influences azimuth coding, indicating that the velocity drive is not purely egocentric. Finally, we show that the internal compass may be three-dimensional and hypothesize that the additional vertical degrees of freedom use global allocentric gravity cues.

Characteristics and mechanism of apogeotropic central positional nystagmus

Here we characterize persistent apogeotropic type of central positional nystagmus, and compare it with the apogeotropic nystagmus of benign paroxysmal positional vertigo involving the lateral canal. Nystagmus was recorded in 27 patients with apogeotropic type of central positional nystagmus (22 with unilateral and five with diffuse cerebellar lesions) and 20 patients with apogeotropic nystagmus of benign paroxysmal positional vertigo. They were tested while sitting, while supine with the head straight back, and in the right and left ear-down positions. The intensity of spontaneous nystagmus was similar while sitting and supine in apogeotropic type of central positional nystagmus, but greater when supine in apogeotropic nystagmus of benign paroxysmal positional vertigo. In central positional nystagmus, when due to a focal pathology, the lesions mostly overlapped in the vestibulocerebellum (nodulus, uvula, and tonsil). We suggest a mechanism for apogeotropic type of central positional nystagmus based on the location of lesions and a model that uses the velocity-storage mechanism. During both tilt and translation, the otolith organs can relay the same gravito-inertial acceleration signal. This inherent ambiguity can be resolved by a 'tilt-estimator circuit' in which information from the semicircular canals about head rotation is combined with otolith information about linear acceleration through the velocity-storage mechanism. An example of how this mechanism works in normal subjects is the sustained horizontal nystagmus that is produced when a normal subject is rotated at a constant speed around an axis that is tilted away from the true vertical (off-vertical axis rotation). We propose that when the tilt-estimator circuit malfunctions, for example, with lesions in the vestibulocerebellum, the estimate of the direction of gravity is erroneously biased away from true vertical. If the bias is toward the nose, when the head is turned to the side while supine, there will be sustained, unwanted, horizontal positional nystagmus (apogeotropic type of central positional nystagmus) because of an inappropriate feedback signal indicating that the head is rotating when it is not.

Central positional nystagmus: Characteristics and model-based explanations

The central vestibular system operates to precisely estimate the rotational velocity and gravity orientation using the inherently ambiguous information from peripheral vestibular system. Therefore, any lesions disrupting this function can generate positional nystagmus. Central positional nystagmus (CPN) can be classified into the paroxysmal (transient) and persistent forms. The paroxysmal CPN has the features suggesting a semicircular canal origin regarding the latency, duration, and direction of nystagmus. Patients with paroxysmal CPN commonly show several different types of nystagmus classified according to the provoking positioning. The persistent form of CPN mostly appears as downbeat nystagmus while prone or supine, or apogeotropic or geotropic horizontal nystagmus when the head is turned to either side while supine. CPN may be ascribed to erroneous neural processing within the velocity-storage circuit that functions in estimating angular head velocity, gravity direction, and inertia. Paroxysmal CPN appears to be post-rotatory rebound nystagmus due to lesions involving the cerebellar nodulus and uvula. In contrast, persistent CPN may arise from erroneous gravity estimation. The overlap of lesion location responsible for both paroxysmal and persistent CPN may account for the frequent coexistence of both forms of nystagmus in a single patient.

Gravito-inertial ambiguity resolved through head stabilization

It has been frequently observed that humans and animals spontaneously stabilize their heads with respect to the gravitational vertical during body movements even in the absence of vision. The interpretations of this intriguing behaviour have so far not included the need, for survival, to robustly estimate verticality. Here we use a mechanistic model of the head/otolith organ to analyse the possibility for this system to render verticality 'observable', a fundamental prerequisite to the determination of the angular position and acceleration of the head from idiothetic, inertial measurements. The intrinsically nonlinear head-vestibular dynamics is shown to generally lack observability unless the head is stabilized in orientation by feedback. Thus, our study supports the hypothesis that a central function of the physiologically costly head stabilization strategy is to enable an organism to estimate the gravitational vertical and head acceleration during locomotion. Moreover, our result exhibits a rare peculiarity of certain nonlinear systems to fortuitously alter their observability properties when feedback is applied.

A unified internal model theory to resolve the paradox of active versus passive self-motion sensation

Brainstem and cerebellar neurons implement an internal model to accurately estimate self-motion during externally generated (‘passive’) movements. However, these neurons show reduced responses during self-generated (‘active’) movements, indicating that predicted sensory consequences of motor commands cancel sensory signals. Remarkably, the computational processes underlying sensory prediction during active motion and their relationship to internal model computations during passive movements remain unknown. We construct a Kalman filter that incorporates motor commands into a previously established model of optimal passive self-motion estimation. The simulated sensory error and feedback signals match experimentally measured neuronal responses during active and passive head and trunk rotations and translations. We conclude that a single sensory internal model can combine motor commands with vestibular and proprioceptive signals optimally. Thus, although neurons carrying sensory prediction error or feedback signals show attenuated modulation, the sensory cues and internal model are both engaged and critically important for accurate self-motion estimation during active head movements.

When seated in a car, we can detect when the vehicle begins to move even with our eyes closed. Structures in the inner ear called the vestibular, or balance, organs enable us to sense our own movement. They do this by detecting head rotations, accelerations and gravity. They then pass this information on to specialized vestibular regions of the brain.

Experiments using rotating chairs and moving platforms have shown that passive movements – such as car journeys and rollercoaster rides – activate the brain’s vestibular regions. But recent work has revealed that voluntary movements – in which individuals start the movement themselves – activate these regions far less than passive movements. Does this mean that the brain ignores signals from the inner ear during voluntary movements? Another possibility is that the brain predicts in advance how each movement will affect the vestibular organs in the inner ear. It then compares these predictions with the signals it receives during the movement. Only mismatches between the two activate the brain’s vestibular regions.

To test this theory, Laurens and Angelaki created a mathematical model that compares predicted signals with actual signals in the way the theory proposes. The model accurately predicts the patterns of brain activity seen during both active and passive movement. This reconciles the results of previous experiments on active and passive motion. It also suggests that the brain uses similar processes to analyze vestibular signals during both types of movement.

These findings can help drive further research into how the brain uses sensory signals to refine our everyday movements. They can also help us understand how people recover from damage to the vestibular system. Most patients with vestibular injuries learn to walk again, but have difficulty walking on uneven ground. They also become disoriented by passive movement. Using the model to study how the brain adapts to loss of vestibular input could lead to new strategies to aid recovery.

Cerebellum estimates the sensory state of the body

A recent neurophysiology study provides data from the cerebellar vermis/nodulus, where neurons encode translation of the head, even when these translations are induced via an illusion. These data provide new neurophysiological evidence that the cerebellum is important for computations involving internal models of motion, estimating the state of the body.

Computation of linear acceleration through an internal model in the macaque cerebellum

A combination of theory and behavioral findings has supported a role for internal models in the resolution of sensory ambiguities and sensorimotor processing. Although the cerebellum has been proposed as a candidate for implementation of internal models, concrete evidence from neural responses is lacking. Here we exploit un-natural motion stimuli, which induce incorrect self-motion perception and eye movements, to explore the neural correlates of an internal model proposed to compensate for Einstein’s equivalence principle and generate neural estimates of linear acceleration and gravity. We show that caudal cerebellar vermis Purkinje cells and cerebellar nuclei neurons selective for actual linear acceleration also encode erroneous linear acceleration, as expected from the internal model hypothesis, even when no actual linear acceleration occurs. These findings provide strong evidence that the cerebellum might be involved in the implementation of internal models that mimic physical principles to interpret sensory signals, as previously hypothesized by theorists.

The functional significance of velocity storage and its dependence on gravity

Research in the vestibular field has revealed the existence of a central process, called 'velocity storage', that is activated by both visual and vestibular rotation cues and is modified by gravity, but whose functional relevance during natural motion has often been questioned. In this review, we explore spatial orientation in the context of a Bayesian model of vestibular information processing. In this framework, deficiencies/ambiguities in the peripheral vestibular sensors are compensated for by central processing to more accurately estimate rotation velocity, orientation relative to gravity, and inertial motion. First, an inverse model of semicircular canal dynamics is used to reconstruct rotation velocity by integrating canal signals over time. However, its low-frequency bandwidth is limited to avoid accumulation of noise in the integrator. A second internal model uses this reconstructed rotation velocity to compute an internal estimate of tilt and inertial acceleration. The bandwidth of this second internal model is also restricted at low frequencies to avoid noise accumulation and drift of the tilt/translation estimator over time. As a result, low-frequency translation can be erroneously misinterpreted as tilt. The time constants of these two integrators (internal models) can be conceptualized as two Bayesian priors of zero rotation velocity and zero linear acceleration, respectively. The model replicates empirical observations like 'velocity storage' and 'frequency segregation' and explains spatial orientation (e.g., 'somatogravic') illusions. Importantly, the functional significance of this network, including velocity storage, is found during short-lasting, natural head movements, rather than at low frequencies with which it has been traditionally studied.