Visual climbing fiber input to rabbit vestibulo-cerebellum: a source of direction-specific information

This chapter provides a review of early studies into the neural substrate for optokinetic-vestibular responses. Properties and connections of retinal and brainstem neurons contributing to optokinetic responses in the afoveate rabbit are summarized. Electrophysiological and lesion studies provide support for confluence of optokinetic and vestibular signals in the vestibular nucleus to provide the brain's estimate of self-rotation. Evidence for optokinetic-vestibular symbiosis in humans comes from the observation that individuals who have lost vestibular function show no optokinetic after-nystagmus in darkness, following full-field stimulus motion. An anatomical scheme for brainstem elaboration of optokinetic responses is proposed and cerebellar contributions are reviewed.

It is self-evident, once one thinks about it, that the vestibulo-ocular reflex must have caretaker systems that keep it operating correctly over the span of a lifetime. When a movement is not correct (e.g., in position, speed, direction) it is said to be dysmetric. For the vestibulo-ocular reflex (VOR), if eye velocity is not equal and opposite to head velocity within reasonable limits, one has vestibulo-ocular dysmetria. Consequently, the function of the caretaker systems is to eliminate vestibulo-ocular dysmetria. These systems are first required to act just after birth when the gain of the reflex is usually not normal, and must be initially calibrated; and then maintained as the animal grows older; and then in adult life an important function of the caretaker systems is the compensation required after damage. The mechanisms of this caretaker system and ensuring motor learning is the focus of this chapter.

Fifty years have passed since David Marr, Masao Ito, and James Albus proposed seminal models of cerebellar functions. These models share the essential concept that parallel-fiber-Purkinje-cell synapses undergo plastic changes, guided by climbing-fiber activities during sensorimotor learning. However, they differ in several important respects, including holistic versus complementary roles of the cerebellum, pattern recognition versus control as computational objectives, potentiation versus depression of synaptic plasticity, teaching signals versus error signals transmitted by climbing-fibers, sparse expansion coding by granule cells, and cerebellar internal models. In this review, we evaluate different features of the three models based on recent computational and experimental studies. While acknowledging that the three models have greatly advanced our understanding of cerebellar control mechanisms in eye movements and classical conditioning, we propose a new direction for computational frameworks of the cerebellum, that is, hierarchical reinforcement learning with multiple internal models.

Minimizing errors is an important aspect of learning. However, it is not enough merely to record if an error occurred. For efficient learning, information about the magnitude of errors is critical. Did my tennis swing completely miss the target or did I hit the ball, but not quite in the sweet spot? How can neurons – which have traditionally been thought of as binary units – signal the magnitude of an error? Here I review evidence that eyeblink conditioning – a basic form of motor learning – depends on graded signals from the inferior olive which guides plasticity in the cerebellum and ultimately tunes behavior. Specifically, evidence suggests that: (1) Error signals are conveyed to the cerebellum via the inferior olive; (2) Signals from the inferior olive are graded; (3) The strength of the olivary signal affects learning; (4) Cerebellar feedback influences the strength of the olivary signal. I end the review by exploring how graded error signals might explain some behavioral learning phenomena.

The vestibulo-cerebellum and the fastigial nucleus are the major cerebellar hubs involved in the control of vestibular signal processing. These structures connect with other brain areas to form information loops where vestibular, visual, and efference copy signals are processed for motor control and spatial navigation. Importantly, these neuronal networks can undergo plastic changes that enable the generation of new, more optimal, behaviors. Here, we review the literature on the connectivity between the cerebellum, brainstem and inferior olive as well as the information processing by these information loops relevant to the vestibulo-ocular reflex, optokinetic reflex, and spatial navigation.

Considerable theoretical and experimental effort has been dedicated to understanding how neural circuits detect visual motion. In primates, much is known about the cortical circuits that contribute to motion processing, but the role of the retina in this fundamental neural computation is poorly understood. Here, we used a combination of extracellular and whole-cell recording to test for motion sensitivity in the two main classes of output neurons in the primate retina—midget (parvocellular-projecting) and parasol (magnocellular-projecting) ganglion cells. We report that parasol, but not midget, ganglion cells are motion sensitive. This motion sensitivity is present in synaptic excitation and disinhibition from presynaptic bipolar cells and amacrine cells, respectively. Moreover, electrical coupling between neighboring bipolar cells and the nonlinear nature of synaptic release contribute to the observed motion sensitivity. Our findings indicate that motion computations arise far earlier in the primate visual stream than previously thought.