The Accessory Optic System

Simpson, John I.

doi:10.1146/annurev.ne.07.030184.000305

Cited by 512 publications

(298 citation statements)

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“…Therefore, we assume for simplification that the visually estimated eye angular velocity in space (r e ) and head linear velocity in space (v e ) are available as independent inputs (Droulez and Darlot 1989). (For details on optic flow processing, see Droulez and Cornilleau-Pe´re`s (1993) and Simpson (1984).) The visually estimated eye angular velocity in space r e is chosen opposite the retinal slip and the visually estimated head linear velocity in space v e results from the processing of image deformation.…”

Section: The Physical Variablesmentioning

confidence: 99%

“…The present work does not deal with the visual processing that separates the optic flow into self-motion and movement of the visual surround (Droulez and Cornilleau-Pe´re`s 1993;Simpson 1984). The angular and linear components of any visual movement are assumed to be available as separate stimuli measured by the visual system, using retinal slip and image deformation.…”

Section: A3 Angular Information In the Visual Systemmentioning

confidence: 99%

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Using sensory weighting to model the influence of canal, otolith and visual cues on spatial orientation and eye movements

Zupan

Merfeld

Darlot

2002

Biological Cybernetics

199

178

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The sensory weighting model is a general model of sensory integration that consists of three processing layers. First, each sensor provides the central nervous system (CNS) with information regarding a specific physical variable. Due to sensor dynamics, this measure is only reliable for the frequency range over which the sensor is accurate. Therefore, we hypothesize that the CNS improves on the reliability of the individual sensor outside this frequency range by using information from other sensors, a process referred to as "frequency completion." Frequency completion uses internal models of sensory dynamics. This "improved" sensory signal is designated as the "sensory estimate" of the physical variable. Second, before being combined, information with different physical meanings is first transformed into a common representation; sensory estimates are converted to intermediate estimates. This conversion uses internal models of body dynamics and physical relationships. Third, several sensory systems may provide information about the same physical variable (e.g., semicircular canals and vision both measure self-rotation). Therefore, we hypothesize that the "central estimate" of a physical variable is computed as a weighted sum of all available intermediate estimates of this physical variable, a process referred to as "multicue weighted averaging." The resulting central estimate is fed back to the first two layers. The sensory weighting model is applied to three-dimensional (3D) visual-vestibular interactions and their associated eye movements and perceptual responses. The model inputs are 3D angular and translational stimuli. The sensory inputs are the 3D sensory signals coming from the semicircular canals, otolith organs, and the visual system. The angular and translational components of visual movement are assumed to be available as separate stimuli measured by the visual system using retinal slip and image deformation. In addition, both tonic ("regular") and phasic ("irregular") otolithic afferents are implemented. Whereas neither tonic nor phasic otolithic afferents distinguish gravity from linear acceleration, the model uses tonic afferents to estimate gravity and phasic afferents to estimate linear acceleration. The model outputs are the internal estimates of physical motion variables and 3D slow-phase eye movements. The model also includes a smooth pursuit module. The model matches eye responses and perceptual effects measured during various motion paradigms in darkness (e.g., centered and eccentric yaw rotation about an earth-vertical axis, yaw rotation about an earth-horizontal axis) and with visual cues (e.g., stabilized visual stimulation or optokinetic stimulation).

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Section: The Physical Variablesmentioning

confidence: 99%

Section: A3 Angular Information In the Visual Systemmentioning

confidence: 99%

Using sensory weighting to model the influence of canal, otolith and visual cues on spatial orientation and eye movements

Zupan

Merfeld

Darlot

2002

Biological Cybernetics

199

178

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“…Previous studies in rabbits and monkeys showed that a dedicated set of brainstem visual nuclei, termed the "accessory optic system" (AOS) and the retinal ganglion cells (RGCs) that innervate them, are ideally configured to meet these requirements (Oyster et al, 1980;Simpson, 1984;Soodak and Simpson, 1988;Distler and Hoffmann, 2011). A major conclusion of that work and thus the prevailing view for more than three decades was that the primary source of drive to the AOS comes from a subset of directionselective RGCs that respond to increments in light (On-DSGCs) (Yonehara et al, 2009; for review, see Simpson, 1984;Schiller, 2010;Borst and Euler, 2011). Indeed, On-DSGCs respond to slow velocities and have large receptive fields, properties well suited for detecting retinal slip during slow head rotations.…”

Section: Introductionmentioning

confidence: 99%

Genetic Dissection of Retinal Inputs to Brainstem Nuclei Controlling Image Stabilization

et al. 2013

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When the head rotates, the image of the visual world slips across the retina. A dedicated set of retinal ganglion cells (RGCs) and brainstem visual nuclei termed the "accessory optic system" (AOS) generate slip-compensating eye movements that stabilize visual images on the retina and improve visual performance. Which types of RGCs project to each of the various AOS nuclei remain unresolved. Here we report a new transgenic mouse line, Hoxd10 -GFP, in which the RGCs projecting to all the AOS nuclei are fluorescently labeled. Electrophysiological recordings of Hoxd10 -GFP RGCs revealed that they include all three subtypes of On direction-selective RGCs (On-DSGCs), responding to upward, downward, or forward motion. Hoxd10 -GFP RGCs also include one subtype of On-Off DSGCs tuned for forward motion. Retrograde circuit mapping with modified rabies viruses revealed that the On-DSGCs project to the brainstem centers involved in both horizontal and vertical retinal slip compensation. In contrast, the On-Off DSGCs labeled in Hoxd10 -GFP mice projected to AOS nuclei controlling horizontal but not vertical image stabilization. Moreover, the forward tuned On-Off DSGCs appear physiologically and molecularly distinct from all previously genetically identified On-Off DSGCs. These data begin to clarify the cell types and circuits underlying image stabilization during self-motion, and they support an unexpected diversity of DSGC subtypes.

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“…The system works to integrate optic flow, i.e., the changes in the retinal images that occur when moving and that are important clues in sensing distance as well as body position (6,7). Stabilization is accomplished via the vestibuloocular and vestibulocollic reflexes that involve, when moving, the extraocular and neck muscles, respectively.…”

mentioning

confidence: 99%

The primate semicircular canal system and locomotion

Spoor

Garland

Krovitz³

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

336

631

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The semicircular canal system of vertebrates helps coordinate body movements, including stabilization of gaze during locomotion. Quantitative phylogenetically informed analysis of the radius of curvature of the three semicircular canals in 91 extant and recently extinct primate species and 119 other mammalian taxa provide support for the hypothesis that canal size varies in relation to the jerkiness of head motion during locomotion. Primate and other mammalian species studied here that are agile and have fast, jerky locomotion have significantly larger canals relative to body mass than those that move more cautiously.generalized least-squares analysis ͉ mammals ͉ vestibular system

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The Accessory Optic System

Cited by 512 publications

References 0 publications

Using sensory weighting to model the influence of canal, otolith and visual cues on spatial orientation and eye movements

Using sensory weighting to model the influence of canal, otolith and visual cues on spatial orientation and eye movements

Genetic Dissection of Retinal Inputs to Brainstem Nuclei Controlling Image Stabilization

The primate semicircular canal system and locomotion

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