Optimizing the vertebrate vestibular semicircular canal: could we balance any better?

Caloric and galvanic vestibular stimulation for the treatment of Parkinson's disease: rationale and prospects

Introduction: Deeply embedded within the inner ear, the sensory organs of the vestibular system are exquisitely sensitive to the orientation and movement of the head. This information constrains aspects of autonomic reflex control as well as higher-level processes involved in cognition and affect. The anatomical pathways that underline these functional interactions project to many cortical and sub-cortical brain areas, and the question arises as to whether they can be therapeutically harnessed.Areas covered: The body of work reviewed here indicates that the controlled application of galvanic or thermal current to the vestibular end-organs can modulate activity throughout the ascending vestibular network and, under appropriate conditions, reduce motor and non-motor symptoms associated with Parkinson's disease, a disease of growing prevalence and continued unmet clinical need.Expert opinion: The appeal of vestibular stimulation in Parkinson's disease is underpinned by its noninvasive nature, favorable safety profile, and capacity for home-based administration. Clinical adoption now rests on the demonstration of cost-effectiveness and on the commercial availability of suitable devices, many of which are only permitted for research use or lack functionality. Dose optimization and mechanisms-of-action studies are also needed, along with a broader awareness amongst physicians of its therapeutic potential.

Models of vestibular semicircular canal afferent neuron firing activity

Semicircular canal afferent neurons transmit information about head rotation to the brain. Mathematical models of how they do this have coevolved with concepts of how brains perceive the world. A 19th-century "camera" metaphor, in which sensory neurons project an image of the world captured by sense organs into the brain, gave way to a 20th-century view of sensory nerves as communication channels providing inputs to dynamical control systems. Now, in the 21st century, brains are being modeled as Bayesian observers who infer what is happening in the world given noisy, incomplete, and distorted sense data. The semicircular canals of the vestibular apparatus provide an experimentally accessible, low-dimensional system for developing and testing dynamical Bayesian generative models of sense data. In this review, we summarize advances in mathematical modeling of information transmission by semicircular canal afferent sensory neurons since the first such model was proposed nearly a century ago. Models of information transmission by vestibular afferent neurons may provide a foundation for developing realistic models of how brains perceive the world by inferring the causes of sense data.

A Low-Power ASIC Signal Processor for a Vestibular Prosthesis

A low-power ASIC signal processor for a vestibular prosthesis (VP) is reported. Fabricated with TI 0.35 μm CMOS technology and designed to interface with implanted inertial sensors, the digitally assisted analog signal processor operates extensively in the CMOS subthreshold region. During its operation the ASIC encodes head motion signals captured by the inertial sensors as electrical pulses ultimately targeted for in-vivo stimulation of vestibular nerve fibers. To achieve this, the ASIC implements a coordinate system transformation to correct for misalignment between natural sensors and implanted inertial sensors. It also mimics the frequency response characteristics and frequency encoding mappings of angular and linear head motions observed at the peripheral sense organs, semicircular canals and otolith. Overall the design occupies an area of 6.22 mm (2) and consumes 1.24 mW when supplied with ± 1.6 V.

Vestibular humanoid postural control

Many of our motor activities require stabilization against external disturbances. This especially applies to biped stance since it is inherently unstable. Disturbance compensation is mainly reactive, depending on sensory inputs and real-time sensor fusion. In humans, the vestibular system plays a major role. When there is no visual space reference, vestibular-loss clearly impairs stance stability. Most humanoid robots do not use a vestibular system, but stabilize upright body posture by means of center of pressure (COP) control. We here suggest using in addition a vestibular sensor and present a biologically inspired vestibular sensor along with a human-inspired stance control mechanism. We proceed in two steps. First, in an introductory review part, we report on relevant human sensors and their role in stance control, focusing on own models of transmitter fusion in the vestibular sensor and sensor fusion in stance control. In a second, experimental part, the models are used to construct an artificial vestibular system and to embed it into the stance control of a humanoid. The robot's performance is investigated using tilts of the support surface. The results are compared to those of humans. Functional significance of the vestibular sensor is highlighted by comparing vestibular-able with vestibular-loss states in robot and humans. We show that a kinematic body-space sensory feedback (vestibular) is advantageous over a kinetic one (force cues) for dynamic body-space balancing. Our embodiment of human sensorimotor control principles into a robot is more than just bionics. It inspired our biological work (neurorobotics: 'learning by building', proof of principle, and more). We envisage a future clinical use in the form of hardware-in-the-loop simulations of neurological symptoms for improving diagnosis and therapy and designing medical assistive devices.

Modeling sensorimotor control of human upright stance

We model human postural control of upright stance during external disturbances and voluntary lean. Our focus is on how data from various sensors are combined to estimate these disturbances. Whereas most current engineering models of multisensory estimation rely on "internal observers" and complex processing, we compute our estimates by simple sensor fusion mechanisms, i.e., weighted sums of sensory signals combined with thresholds. We show with simulations that this simple device mimics human-like postural behavior in a wide range of situations and diseases. We have now embodied our mechanism in a biped humanoid robot to show that it works in the real world with complex, noisy, and imperfectly known sensors and effectors. On the other hand, we find that the more complex, internal-observer approach, when applied to bipedal posture, can also yield human-like behavior. We suggest that humans use both mechanisms: simple, fast sensor fusions with thresholding for automatic reactions (default mechanism), and more complex methods for voluntary movements. We suggest also that the fusion with thresholding mechanisms are optimized during phylogenesis but are mainly hardwired in any one organism, whereas sensorimotor learning and optimization is mainly a domain of the internal observers.

Biomechanical modeling of semicircular canals for fabricating a biomimetic vestibular system

This paper presents a biomechanical model of the semicircular canals of the human vestibular system and the design of a 3D biomimetic structure that mimics the biological system. Starting from anatomical and physiological data, mechanical and structural parameters have been identified and a mathematical model has been formulated, by considering the semicircular organ as a canal filled by a liquid. The mathematical and mechanical models were used to simulate the behavior of the semicircular canals under known conditions of angular velocity and acceleration along three axes. Furthermore, the membrane inside the semicircular canals was simulated to understand what the mechanical properties of the membrane are and if polymeric materials can reproduce the mechanical characteristics of the biological organ. The results obtained from the model allow to design a biomimetic organ, as a part of a biomimetic vestibular system, by following this biomechatronic approach.

Relationship of semicircular canal size to vestibular-nerve afferent sensitivity in mammals

The relationship between semicircular canal radius of curvature and afferent sensitivity has not been experimentally determined. We characterized mouse semicircular canal afferent responses to sinusoidal head rotations to facilitate interspecies and intraspecies comparisons of canal size to sensitivity. The interspecies experiment compared the horizontal canal afferent responses among animals ranging in size from mouse to rhesus monkey. The intraspecies experiment compared afferent responses from the larger anterior canal to those from the smaller horizontal canal of mice. The responses of mouse vestibular-nerve afferents showed a low- and high-frequency phase lead and high-frequency gain enhancement. Regular horizontal-canal afferents showed a sensitivity to 0.5-Hz sinusoidal rotations of 0.10 +/- 0.03 (SD) spike . s(-1)/deg . s(-1) and high-gain irregular afferents showed a sensitivity of 0.25 +/- 0.11 spike . s(-1)/deg . s(-1). The interspecies comparison showed that the sensitivity of regular afferents was related to the radius of curvature R according to the formula G(r) = 0.23R - 0.09 (r(2) = 0.86) and the sensitivity of irregular afferents was related to radius according to the formula G(i) = 0.32R + 0.01 (r(2) = 0.67). The intraspecies comparison showed that regularly firing anterior canal afferents were significantly more sensitive than those from the relatively smaller horizontal canal, with G(r) = 0.25R. This suggests that canal radius of curvature is closely related to afferent sensitivity both among and within species. If the relationship in humans is similar to that demonstrated here, the sensitivity of their regular vestibular-nerve afferents to 0.5-Hz rotations is likely to be about 0.67 spike . s(-1)/deg . s(-1) and of their high-gain irregular afferents about 1.06 spikes . s(-1)/deg . s(-1).

Semicircular canal geometry, afferent sensitivity, and animal behavior

The geometry of the semicircular canals has been used in evolutionary studies to predict the behaviors of extinct animals. These predictions have relied on an assumption that the responses of the canals can be determined from their dimensions, and that an organism's behavior can be determined from these responses. However, the relationship between a canal's sensitivity and its size is not well known. An intraspecies comparison among canal responses in each of three species (cat, squirrel monkey, and pigeon) was undertaken to evaluate various models of canal function and determine how their dimensions may be related to afferent physiology. All models predicted the responses of the cat afferents, but the models performed less well for squirrel monkey and pigeon. Possible causes for this discrepancy include incorrectly assuming that afferent responses accurately represent canal function or errors in current biophysical models of the canals. These findings leave open the question as to how reliably canal anatomy can be used to estimate afferent responses and how closely afferent responses are related to behavior. Other labyrinthine features, such as orientation of the horizontal canal, which is reliably held near earth-horizontal across many species, may be better to use when extrapolating the posture and related behavior of extinct animals from labyrinthine morphology.

Stochastic resonance in the mechanoelectrical transduction of hair cells

In transducing mechanical stimuli into electrical signals, at least some hair cells in vertebrate auditory and vestibular systems respond optimally to weak periodic signals at natural, nonzero noise intensities. We understand this stochastic resonance by constructing a faithful mechanical model reflecting the hair cell geometry and described by a nonlinear stochastic differential equation. This Langevin description elucidates the mechanism of hair cell stochastic resonance while supporting the hypothesis that noise plays a functional role in hearing.