1. Orienting movements, consisting of coordinated eye and head displacements, direct the visual axis to the source of a sensory stimulus. A recent hypothesis suggests that the CNS may control gaze position (gaze = eye-relative-to-space = eye-relative-to-head + head-relative-to-space) by the use of a feedback circuit wherein an internally derived representation of gaze motor error drives both eye and head premotor circuits. In this paper we examine the effect of behavioral task on the individual and summed trajectories of horizontal eye- and head-orienting movements to gain more insight into how the eyes and head are coupled and controlled in different behavioral situations. 2. Cats whose heads were either restrained (head-fixed) or unrestrained (head-free) were trained to make orienting movements of any desired amplitude in a simple cat-and-mouse game we call the barrier paradigm. A rectangular opaque barrier was placed in front of the hungry animal who either oriented to a food target that was visible to one side of the barrier or oriented to a location on an edge of the barrier where it predicted the target would reappear from behind the barrier. 3. The dynamics (e.g., maximum velocity) and duration of eye- and head-orienting movements were affected by the task. Saccadic eye movements (head-fixed) elicited by the visible target attained greater velocity and had shorter durations than comparable amplitude saccades directed toward the predicted target. A similar observation has been made in human and monkey. In addition, when the head was unrestrained both the eye and head movements (and therefore gaze movements) were faster and shorter in the visible- compared with the predicted-target conditions. Nevertheless, the relative contributions of the eye and head to the overall gaze displacement remained task independent: i.e., the distance traveled by the eye and head movements was determined by the size of the gaze shift only. This relationship was maintained because the velocities of the eye and head movements covaried in the different behavioral situations. Gaze-velocity profiles also had characteristic shapes that were dependent on task. In the predicted-target condition these profiles tended to have flattened peaks, whereas when the target was visible the peaks were sharper. 4. Presentation of a visual cue (e.g., reappearance of food target) immediately before (less than 50 ms) the onset of a gaze shift to a predicted target triggered a midflight increase in first the eye- and, after approximately 20 ms, the head-movement velocity.(ABSTRACT TRUNCATED AT 400 WORDS)

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It is argued that vestibular internuclear commissural pathways are functionally important in the vestibuloocular reflex (VOR), particularly since they appear to be modulated during nystagmus. A bilateral approach to VOR modeling is essential to an effective study of the effects of commissural connections on response dynamics. A bilateral model of the VOR central pathways is proposed, with three main postulates: neural filters (NF) on each side of the brain stem, each linked to tonic cells in the ipsilateral vestibular nuclei in negative feedback loops; strong coupling between these bilateral loops by reciprocal commissural connections that significantly affect response dynamics; and modulation of this coupling by inhibitory burst neurons during fast phases. Mathematical analysis of this model shows that the NF need not be good integrators. During slow-phase operation, commissural pathways provide a positive-feedback effect that improves the effective integration function of the bilateral system beyond that of the NF in each side. Analysis suggests that the time constant of the NF might even be as small as that of the eye plant (approximately 0.24 s), so that the NF might be considered to be internal models of the eye plant rather than pseudointegrators. In the model, modulation of commissural gains by burst cells is shown to be sufficient to cause the system to switch between a compensatory position-tracking mode (slow phases) and an anticompensatory velocity-tracking mode (fast phases) during nystagmus. The model simulates a number of behavioral and neurophysiological findings, such as a) tonic vestibular nuclei (VN) cells have sensitivities and decay times larger than primary vestibular fibers, and their response polarity may reverse after section of superficial commissural fibers; b) effective VOR integration deteriorates after cerebellectomy or commissurectomy; c) peak fast-phase eye velocity is modulated by the vestibular signal as well as by fast-phase amplitude. The model accounts for the modulation of central VN responses during nystagmus and, as a result, simulations strongly imply that envelopes of slow-phase eye velocity or smoothed central firing rates will depend on fast-phase strategy and, hence, may not always yield accurate estimates of VOR dynamics. Similarly, the model predicts that "apparent" disassociation between central and ocular responses may occur because of interactions during nystagmus, despite appropriate behavior within slow-phase segments (since VN responses are not simple estimates of eye velocity).(ABSTRACT TRUNCATED AT 400 WORDS)

The objective of system identification methods is to construct a mathematical model of a dynamical system in order to describe adequately the input-output relationship observed in that system. Over the past several decades, mathematical models have been employed frequently in the oculomotor field, and their use has contributed greatly to our understanding of how information flows through the implicated brain regions. However, the existing analyses of oculomotor neural discharges have not taken advantage of the power of optimization algorithms that have been developed for system identification purposes. In this article, we employ these techniques to specifically investigate the "burst generator" in the brainstem that drives saccadic eye movements. The discharge characteristics of a specific class of neurons, inhibitory burst neurons (IBNs) that project monosynaptically to ocular motoneurons, are examined. The discharges of IBNs are analyzed using different linear and nonlinear equations that express a neuron's firing frequency and history (i.e., the derivative of frequency), in terms of quantities that describe a saccade trajectory, such as eye position, velocity, and acceleration. The variance accounted for by each equation can be compared to choose the optimal model. The methods we present allow optimization across multiple saccade trajectories simultaneously. We are able to investigate objectively how well a specific equation predicts a neuron's discharge pattern as well as whether increasing the complexity of a model is justifiable. In addition, we demonstrate that these techniques can be used both to provide an objective estimate of a neuron's dynamic latency and to test whether a neuron's initial firing rate (expressed as an initial condition) is a function of a quantity describing a saccade trajectory (such as initial eye position).