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.

Consensus paper: the role of the cerebellum in perceptual processes.

Various lines of evidence accumulated over the past 30 years indicate that the cerebellum, long recognized as essential for motor control, also has considerable influence on perceptual processes. In this paper, we bring together experts from psychology and neuroscience, with the aim of providing a succinct but comprehensive overview of key findings related to the involvement of the cerebellum in sensory perception. The contributions cover such topics as anatomical and functional connectivity, evolutionary and comparative perspectives, visual and auditory processing, biological motion perception, nociception, self-motion, timing, predictive processing, and perceptual sequencing. While no single explanation has yet emerged concerning the role of the cerebellum in perceptual processes, this consensus paper summarizes the impressive empirical evidence on this problem and highlights diversities as well as commonalities between existing hypotheses. In addition to work with healthy individuals and patients with cerebellar disorders, it is also apparent that several neurological conditions in which perceptual disturbances occur, including autism and schizophrenia, are associated with cerebellar pathology. A better understanding of the involvement of the cerebellum in perceptual processes will thus likely be important for identifying and treating perceptual deficits that may at present go unnoticed and untreated. This paper provides a useful framework for further debate and empirical investigations into the influence of the cerebellum on sensory perception.

Ecological constraints on the origin of neurones.

The basic functional characteristics of spiking neurones are remarkably similar throughout the animal kingdom. Their core design and function features were presumably established very early in their evolutionary history. Identifying the selection pressures that drove animals to evolve spiking neurones could help us interpret their design and function today. This paper provides a quantitative argument, based on ecology, that animals evolved neurones after they started eating each other, about 550 million years ago. We consider neurones as devices that aid an animal's foraging performance, but incur an energetic cost. We introduce an idealised stochastic model ecosystem of animals and their food, and obtain an analytic expression for the probability that an animal with a neurone will fix in a neurone-less population. Analysis of the fixation probability reveals two key results. First, a neurone will never fix if an animal forages low-value food at high density, even if that neurone incurs no cost. Second, a neurone will fix with high probability if an animal is foraging high-value food at low density, even if that neurone is expensive. These observations indicate that the transition from neurone-less to neurone-armed animals can be facilitated by a transition from filter-feeding or substrate grazing to episodic feeding strategies such as animal-on-animal predation (macrophagy).

Predation and the origin of neurones.

The core design of spiking neurones is remarkably similar throughout the animal kingdom. Their basic function as fast-signalling thresholding cells might have been established very early in their evolutionary history. Identifying the selection pressures that drove animals to evolve spiking neurones could help us interpret their design and function today. We review fossil, ecological and molecular evidence to investigate when and why animals evolved spiking neurones. Fossils suggest that animals evolved nervous systems soon after the advent of animal-on-animal predation, 550 million years ago (MYa). Between 550 and 525 MYa, we see the first fossil appearances of many animal innovations, including eyes. Animal behavioural complexity increased during this period as well, as evidenced by their traces, suggesting that nervous systems were an innovation of that time. Fossils further suggest that, before 550 MYa, animals were either filter feeders or microbial mat grazers. Extant sponges and Trichoplax perform these tasks using energetically cheaper alternatives than spiking neurones. Genetic evidence testifies that nervous systems evolved before the protostome-deuterostome split. It is less clear whether nervous systems evolved before the cnidarian-bilaterian split, so cnidarians and bilaterians might have evolved their nervous systems independently. The fossil record indicates that the advent of predation could fit into the window of time between those two splits, though molecular clock studies dispute this claim. Collectively, these lines of evidence indicate that animals evolved spiking neurones soon after they started eating each other. The first sensory neurones could have been threshold detectors that spiked in response to other animals in their proximity, alerting them to perform precisely timed actions, such as striking or fleeing.

Peripheral modulation of worker bee responses to queen mandibular pheromone.

It is generally accepted that young worker bees (Apis mellifera L.) are highly attracted to queen mandibular pheromone (QMP). Our results challenge this widely held view. We have found that unless young workers are exposed to QMP early in adult life, they, like foragers, avoid contact with this pheromone. Our data indicate that responses to QMP are regulated peripherally, at the level of the antennal sensory neurons, and that a window of opportunity exists in which QMP can alter a young bee's response to this critically important pheromone. Exposing young bees to QMP from the time of adult emergence reduces expression in the antennae of the D1-like dopamine receptor gene, Amdop1. Levels of Amdop3 transcript, on the other hand, and of the octopamine receptor gene Amoa1, are significantly higher in the antennae of bees strongly attracted to QMP than in bees showing no attraction to this pheromone. A decline in QMP attraction with age is accompanied by a fall in expression in worker antennae of the D2-like dopamine receptor, AmDOP3, a receptor that is selectively activated by QMP. Taken together, our findings suggest that QMP's actions peripherally not only suppress avoidance behavior, but also enhance attraction to QMP, thereby facilitating attendance of the queen.

Translations of Steinhausen's Publications Provide Insight Into Their Contributions to Peripheral Vestibular Neuroscience.

The quantitative relationship between angular head movement and semicircular canal function is most often referenced to the well-known torsion-pendulum model that predicts cupular displacement from input head acceleration. The foundation of this model can be traced back to Steinhausen's series of papers between 1927 and 1933 whereby he endeavored to document observations of cupular displacements that would directly infer movement of the endolymph resulting from angular rotation. He also was the first to establish the direct relationship between cupular displacement and compensatory eye movements. While the chronology of these findings, with their successes and pitfalls, are documented in Steinhausen's work, it reflects a fascinating journey that has been inaccessible to the non-German speaking community. Therefore, the present compilation of translations, with accompanying introduction and discussion, was undertaken to allow a larger component of the vestibular scientific community to gain insight into peripheral labyrinthine mechanics provided by this historical account.

Events in Early Nervous System Evolution.

We propose that neurons and nervous systems evolved among thin, motile, microbe-eating animals during the Ediacaran period (635-543 million years ago). Spiking neurons evolved from epithelial cells around the margins of Ediacaran microbial mat grazers that initially specialized to detect weak bioelectric fields of nearby animals and to trigger rapid withdrawal movements. According to this scenario, nervous systems are a consequence of two preceding animal innovations, external digestion and motility, which have co-evolved in concert with nervous systems ever since. We suggest that fundamental characteristics of modern nervous systems can be explained by studying how nervous systems originated during the Ediacaran period, as natural computers for predictive statistical inference given event-based sense data.

Dynamics and the single spike.

Responses of vestibular primary afferent neurons to head rotation exhibit fractional-order dynamics. As a consequence, the head tends to be in a localized region of its state-space at spike times of a particular neuron during arbitrary head movements, and single spikes can be interpreted as state measurements. We are developing a model of neural computations underlying trajectory prediction and control tasks, based on this experimental observation. This is a step toward a formal neural calculus in which single spikes are modeled realistically as the operands of neural computation.

Intra-session and inter-day reliability of forearm surface EMG during varying hand grip forces.

Surface electromyography (EMG) is widely used to evaluate forearm muscle function and predict hand grip forces; however, there is a lack of literature on its intra-session and inter-day reliability. The aim of this study was to determine reliability of surface EMG of finger and wrist flexor muscles across varying grip forces. Surface EMG was measured from six forearm flexor muscles of 23 healthy adults. Eleven of these subjects undertook inter-day test-retest. Six repetitions of five randomized isometric grip forces between 0% and 80% of maximum force (MVC) were recorded and normalized to MVC. Intra- and inter-day reliability were calculated through the intraclass correlation coefficient (ICC) and standard error of measurement (SEM). Normalized EMG produced excellent intra-session ICC of 0.90 when repeated measurements were averaged. Intra-session SEM was low at low grip forces, however, corresponding normalized SEM was high (23-45%) due to the small magnitude of EMG signals. This may limit the ability to evaluate finer forearm muscle function and hand grip forces in daily tasks. Combining EMG of functionally related muscles improved intra-session SEM, improving within-subject reliability without taking multiple measurements. Removing and replacing electrodes inter-day produced poor ICC (ICC < 0.50) but did not substantially affect SEM.

A method for analysing neural computation using receptive fields in state space.

The behaviour of spiking neurons which are involved in a control task can be quantified by mapping receptive fields in the state space of the control problem. These receptive fields link spikes, the operands of neural computation, to state variables, the operands of conventional control theory. They allow neural computation underlying control tasks to be quantitatively analysed, and meaningfully discussed in ordinary language, by providing a rigorous way to interpret single spikes as assertions about dynamical state.