OpenEyeSim: A biomechanical model for simulation of closed- loop visual perception

We introduce OpenEyeSim, a detailed three-dimensional biomechanical model of the human extraocular eye muscles including a visualization of a virtual environment. The main purpose of OpenEyeSim is to serve as a platform for developing models of the joint learning of visual representations and eye-movement control in the perception-action cycle. The architecture and dynamic muscle properties are based on measurements of the human oculomotor system. We show that our model can reproduce different types of eye movements. Additionally, our model is able to calculate metabolic costs of eye movements. It is also able to simulate different eye disorders, such as different forms of strabismus. We propose OpenEyeSim as a platform for studying many of the complexities of oculomotor control and learning during normal and abnormal visual development

Neural Representations for Sensory-Motor Control, II: Learning a Head-Centered Visuomotor Representation of 3-D Target Position

A neural network model is described for how an invariant head-centered representation of 3-D target position can be autonomously learned by the brain in real time. Once learned, such a target representation may be used to control both eye and limb movements. The target representation is derived from the positions of both eyes in the head, and the locations which the target activates on the retinas of both eyes. A Vector Associative Map, or YAM, learns the many-to-one transformation from multiple combinations of eye-and-retinal position to invariant 3-D target position. Eye position is derived from outflow movement signals to the eye muscles. Two successive stages of opponent processing convert these corollary discharges into a. head-centered representation that closely approximates the azimuth, elevation, and vergence of the eyes' gaze position with respect to a cyclopean origin located between the eyes. YAM learning combines this cyclopean representation of present gaze position with binocular retinal information about target position into an invariant representation of 3-D target position with respect to the head. YAM learning can use a teaching vector that is externally derived from the positions of the eyes when they foveate the target. A YAM can also autonomously discover and learn the invariant representation, without an explicit teacher, by generating internal error signals from environmental fluctuations in which these invariant properties are implicit. YAM error signals are computed by Difference Vectors, or DVs, that are zeroed by the YAM learning process. YAMs may be organized into YAM Cascades for learning and performing both sensory-to-spatial maps and spatial-to-motor maps. These multiple uses clarify why DV-type properties are computed by cells in the parietal, frontal, and motor cortices of many mammals. YAMs are modulated by gating signals that express different aspects of the will-to-act. These signals transform a single invariant representation into movements of different speed (GO signal) and size (GRO signal), and thereby enable YAM controllers to match a planned action sequence to variable environmental conditions.National Science Foundation (IRI-87-16960, IRI-90-24877); Office of Naval Research (N00014-92-J-1309

Aerospace Medicine and Biology: A continuing supplement 180, May 1978

This special bibliography lists 201 reports, articles, and other documents introduced into the NASA scientific and technical information system in April 1978

Using Knowledge of Development to Promote Recovery of Function after Brain Damage

Knowledge of normal development of brain–behavior relations plays an important role in understanding how the plasticity of the nervous system can be used to promote recovery of function following brain damage. Aspects of the other articles in this issue are used in justification of the value of such developmental knowledge. Also, the development of amblyopia and its remediation in adulthood is discussed as a model for developing other techniques for ensuring recovery of function after stroke. Although the articles in this issue establish an excellent context for improving actual recovery of function (rather than compensation for deficits), much still needs to be discovered about how we can use developmental knowledge, along with knowledge of the plasticity of the nervous system, to improve remediation techniques

Ocular biomechanics modelling for visual fatigue assessment in virtual environments

The study objectively quantifies visual fatigue caused by immersion in virtual reality. Visual fatigue assessment is done through ocular biomechanics modelling and eye tracking to analyse eye movement and muscle forces into a visual fatigue index

The Refraction Assessment and the Electronic Trial Frame Measurement during Standing or Sitting Position Can Affect Postural Stability

Vision has been shown to influence body posture. The purpose of this study is to investi‐ gate the correlations between visual acuity and body postural control both in a standing and seated position. This cohort study included 37 patients examined using Adaptica’s (Italy) Kaleidos and VisionFit. Objective refraction was measured with Kaleidos both in a standing and seated position by the same operator and in the same environmental conditions. The parameters obtained with the device were binocular refraction, monocular refraction, pupil distance, pupil size, head tilt, gaze, phorias, and tropias. The results obtained were then subjectively tested using VisionFit: an elec‐ tronic trial frame with phoropter functionalities. The study’s outcome revealed that the differences in the visual acuity parameters obtained in standing and seated positions were statistically signifi‐ cant; the Student’s t‐test showed a p‐value < 0.001 in all parameter averages. Automated refraction is widely being performed and postural control can affect the visual acuity parameters; therefore, it is relevant to consider the possibility of measuring in orthostatism. It might be appropriate to take into account the possibility of measuring in orthostatism and wearing trial frames in orthostatic conditions as well as walking freely around the room, looking outside of a window, sitting, and readin

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 182, July 1978

This bibliography lists 165 reports, articles, and other documents introduced into the NASA scientific and technical information system in June 1978

Modelo mecánico de los músculos extrínsecos del globo ocular

The mathematical modeling of the physiological behavior of extraocular muscles in ocular rotation, contributes to the learning of the oculomotor system and the development of technologies for the control of devices, through the precise prediction of the ocular displacement path. We propose in this article a mechanical model of eye movement, which incorporates the physiological properties of extraocular muscles in the force-elongation relationship and the action of agonist and antagonist muscles. An easy to understand model is presented that allows the analysis of forces applied in muscle contraction, the variation of extraocular muscle length, which generates rotation of the eye and the vector interpretation of the direction in the space towards which the eye directs the view, in movements of adduction, abduction, elevation and depression. The proposed model allows a simplification of the mathematical description, compared with other models, in relation to the action of the mechanical elements (springs and dampers) that represent the anatomical and physiological components of the contractile mechanics of the extraocular muscles. The implementation of the proposed model could serve in the future in the development of technologies that emulate horizontal or vertical eye movements for the control of devices.El modelamiento matemático del comportamiento fisiológico de los músculos extraoculares en la rotación ocular, contribuye en el aprendizaje del sistema oculomotor y en el desarrollo de tecnologías para el control de dispositivos, a través de la predicción precisa de la trayectoria de desplazamiento ocular. Nosotros proponemos en el presente artículo un modelo mecánico del movimiento ocular, que incorpora las propiedades fisiológicas de los músculos extraoculares en la relación de fuerza-elongación y la acción de los músculos agonistas y antagonistas. Se presenta un modelo de fácil comprensión que permite el análisis de fuerzas aplicadas en la contracción muscular, la variación de longitud del musculo extraocular, que genera rotación del ojo y la interpretación vectorial de la dirección en el espacio hacia donde el ojo dirige la vista en movimientos de aducción, abducción, elevación y depresión. El modelo propuesto permite una simplificación de la descripción matemática, frente a otros modelos, de la acción de los elementos mecánicos (resortes y amortiguadores) que representan los componentes anatómicos y fisiológicos de los músculos extraoculares. La implementación del modelo propuesto podría servir a futuro en el desarrollo de tecnologías que emulen movimientos oculares horizontales u verticales para el control de dispositivos

Aerospace Medicine and Biology: A continuing bibliography with indexes

This bibliography lists 253 reports, articles, and other documents introduced into the NASA scientific and technical information system in October 1975

A Vector-Integration-to-Endpoint Model for Performance of Viapoint Movements

Viapoint (VP) movements are movements to a desired point that are constrained to pass through an intermediate point. Studies have shown that VP movements possess properties, such as smooth curvature around the VP, that are not explicable by treating VP movements as strict concatenations of simpler point-to-point (PTP) movements. Such properties have led some theorists to propose whole-trajectory optimization models, which imply that the entire trajectory is pre-computed before movement initiation. This paper reports new experiments conducted to systematically compare VP with PTP trajectories. Analyses revealed a statistically significant early directional deviation in VP movements but no associated curvature change. An explanation of this effect is offered by extending the Vector-Integration-To-Endpoint (VITE) model (Bullock and Grossberg, 1988), which postulates that voluntary movement trajectories emerge as internal gating signals control the integration of continuously computed vector commands based on the evolving, perceptible difference between desired and actual position variables. The model explains the observed trajectories of VP and PTP movements as emergent properties of a dynamical system that does not precompute entire trajectories before movement initiation. The new model includes a working memory and a stage sensitive to time-to-contact information. These cooperate to control serial performance. The structural and functional relationships proposed in the model are consistent with available data on forebrain physiology and anatomy.Office of Naval Research (N00014-92-J-1309, N00014-93-1-1364, N0014-95-1-0409