Extraretinal Signals Research Articles

Gaze direction effects in the primary visual cortex are eccentricity-dependent

Event Abstract Back to Event Gaze direction effects in the primary visual cortex are eccentricity-dependent Simona Celebrini1*, Jean-Baptiste Durand1 and Yves Trotter1 1 Université de Toulouse, CerCo, UPS CNRS, UMR5549, France By integrating visual and eye position signals, V1 neurons with central receptive fields participate in the neuronal mechanisms underlying the localization of objects in space. Because of anatomical and functional differences in their cortical representations and the presence of vertical disparity in eccentric receptive fields, the foveal and peripheral visual fields might not be equally involved in this localization process. To evaluate their respective contributions, we compared the effects of similar gaze direction changes on responses of neurons located in the central and peripheral representations of V1. Single and multi unit recordings were made in dorsal and calcarine V1 on awake behaving monkeys performing a visual fixation task at different gaze eccentricities. Although we did not find a higher frequency of gain effects, we report larger gain values and a higher sensitivity to gaze direction in peripheral V1. We also report a clear influence of the receptive field egocentric eccentricity; peripheral V1 cells present a higher signal-to-noise ratio when responding to objects located in the straight-ahead position in space. This result suggests that egocentric information could be present at the level of single neurons in V1. Furthermore, we propose that eye position information implicated in visual gains, is mainly carried by extra retinal signal of sensory motor origin. Conference: 3rd Mediterranean Conference of Neuroscience , Alexandria, Egypt, 13 Dec - 16 Dec, 2009. Presentation Type: Oral Presentation Topic: Sensory systems Citation: Celebrini S, Durand J and Trotter Y (2009). Gaze direction effects in the primary visual cortex are eccentricity-dependent. Front. Neurosci. Conference Abstract: 3rd Mediterranean Conference of Neuroscience . doi: 10.3389/conf.neuro.01.2009.16.116 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 23 Nov 2009; Published Online: 23 Nov 2009. * Correspondence: Simona Celebrini, Université de Toulouse, CerCo, UPS CNRS, UMR5549, Toulouse, France, simona@cerco.ups-tlse.fr Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Simona Celebrini Jean-Baptiste Durand Yves Trotter Google Simona Celebrini Jean-Baptiste Durand Yves Trotter Google Scholar Simona Celebrini Jean-Baptiste Durand Yves Trotter PubMed Simona Celebrini Jean-Baptiste Durand Yves Trotter Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

A neural model of visually guided steering, obstacle avoidance, and route selection.

A neural model is developed to explain how humans can approach a goal object on foot while steering around obstacles to avoid collisions in a cluttered environment. The model uses optic flow from a 3-dimensional virtual reality environment to determine the position of objects on the basis of motion discontinuities and computes heading direction, or the direction of self-motion, from global optic flow. The cortical representation of heading interacts with the representations of a goal and obstacles so that the goal acts as an attractor of heading and obstacles act as repellers. In addition, the model maintains fixation on the goal object by generating smooth pursuit eye movements. Eye rotations can distort the optic flow field, complicating heading perception, and the model uses extraretinal signals to correct for this distortion and accurately represent heading. The model explains how motion processing mechanisms in cortical areas middle temporal, medial superior temporal, and posterior parietal cortex can be used to guide steering. The model quantitatively simulates human psychophysical data about visually guided steering, obstacle avoidance, and route selection.

Asymmetrical perception of motion smear in infantile nystagmus

Normal observers perceive less motion smear if a target moves in the opposite direction of a smooth eye movement than if the target moves to produce the same retinal image speed in the same direction as the eye movement. This study investigated whether a similar asymmetrical attenuation of perceived motion smear occurs in observers with infantile nystagmus (IN). Observers ( N = 3) viewed a laser spot that moved for 100 or 125 ms to the right or left at a speed between 5 and 60°/s during the slow phase of jerk IN. After each trial, the observer adjusted the length of a bright line to match the extent of the perceived smear. Across observers, the average duration of perceived smear was 39 and 106 ms, respectively, for relative motion of the laser spot in the opposite vs. the same direction as the IN slow phase. In one observer with periodic alternating nystagmus, the direction of spot motion that produced less perceived smear reversed with an alternation in the direction of the IN slow phase. The reduction of perceived motion smear for relative target motion in the opposite direction of IN slow phases is attributed to extra-retinal signals that accompany IN. As during normal eye movements, the reduction of perceived smear for this direction of relative motion should foster the perception of clarity in the stationary visual world.

The neural basis of smooth pursuit eye movements in the rhesus monkey brain

Smooth pursuit eye movements are performed in order to prevent retinal image blur of a moving object. Rhesus monkeys are able to perform smooth pursuit eye movements quite similar as humans, even if the pursuit target does not consist in a simple moving dot. Therefore, the study of the neuronal responses as well as the consequences of micro-stimulation and lesions in trained monkeys performing smooth pursuit is a powerful approach to understand the human pursuit system. The processing of visual motion is achieved in the primary visual cortex and the middle temporal area. Further processing including the combination of retinal image motion signals with extra-retinal signals such as the ongoing eye and head movement occurs in subsequent cortical areas as the medial superior temporal area, the ventral intraparietal area and the frontal and supplementary eye field. The frontal eye field especially contributes anticipatory signals which have a substantial influence on the execution of smooth pursuit. All these cortical areas send information to the pontine nuclei, which in turn provide the input to the cerebellum. The cerebellum contains two pursuit representations: in the paraflocculus/flocculus region and in the posterior vermis. While the first representation is most likely involved in the coordination of pursuit and the vestibular-ocular reflex, the latter is involved in the precise adjustments of the eye movements such as adaptation of pursuit initiation. The output of the cerebellum is directed to the moto-neurons of the extra-ocular muscles in the brainstem.

A Motion Illusion Reveals Mechanisms of Perceptual Stabilization

Visual illusions are valuable tools for the scientific examination of the mechanisms underlying perception. In the peripheral drift illusion special drift patterns appear to move although they are static. During fixation small involuntary eye movements generate retinal image slips which need to be suppressed for stable perception. Here we show that the peripheral drift illusion reveals the mechanisms of perceptual stabilization associated with these micromovements. In a series of experiments we found that illusory motion was only observed in the peripheral visual field. The strength of illusory motion varied with the degree of micromovements. However, drift patterns presented in the central (but not the peripheral) visual field modulated the strength of illusory peripheral motion. Moreover, although central drift patterns were not perceived as moving, they elicited illusory motion of neutral peripheral patterns. Central drift patterns modulated illusory peripheral motion even when micromovements remained constant. Interestingly, perceptual stabilization was only affected by static drift patterns, but not by real motion signals. Our findings suggest that perceptual instabilities caused by fixational eye movements are corrected by a mechanism that relies on visual rather than extraretinal (proprioceptive or motor) signals, and that drift patterns systematically bias this compensatory mechanism. These mechanisms may be revealed by utilizing static visual patterns that give rise to the peripheral drift illusion, but remain undetected with other patterns. Accordingly, the peripheral drift illusion is of unique value for examining processes of perceptual stabilization.

How does saccade adaptation affect visual perception?

Three signals are used to visually localize targets and stimulate saccades: (1) retinal location signals for intended saccade amplitude, (2) sensory-motor transform (SMT) of retinal signals to extra-ocular muscle innervation, and (3) estimates of eye position from extra-retinal signals. We investigated effects of adapting saccade amplitude to a double-step change in target location on perceived direction. In a flashed-pointing task, subjects pointed an unseen hand at a briefly displayed eccentric target without making a saccade. In a sustained-pointing task, subjects made a horizontal saccade to a double-step target. One second after the second step, they pointed an unseen hand at the final target position. After saccade-shortening adaptation, there was little change in hand-pointing azimuth toward the flashed target suggesting that most saccade adaptation was caused by changes in the SMT. After saccade-lengthening adaptation, there were small changes in hand-pointing azimuth to flashed targets, indicating that 1/3 of saccade adaptation was caused by changes in estimated retinal location signals and 2/3 by changes in the SMT. The sustained hand-pointing task indicated that estimates of eye position adapted inversely with changes of the SMT. Changes in perceived direction resulting from saccade adaptation are mainly influenced by extra-retinal factors with a small retinal component in the lengthening condition.

Cortical mechanisms of retinal and extraretinal smooth pursuit eye movements to different target velocities

Smooth pursuit eye movements (SPEM) are used to maintain focus upon moving targets. The generation of SPEM velocity is controlled by retinal information and extraretinal signals. Although there is a wealth of studies investigating retinal and extraretinal SPEM control, the main questions regarding the cortical mechanisms involved in the processing of SPEM to different stimulus velocities are still unresolved. We applied an innovative event-related fMRI-design by presenting target ramps at different velocities (5, 10, 15, 20°/s) with both continuous target presentation and intervals of target blanking. The stimulus parameters were integrated into the statistical model and eye movements were registered to confirm SPEM performance. Our results clearly demonstrate that in humans the oculomotor network (V5, frontal and supplementary eye fields, lateral intraparietal area) is engaged in the processing of retinal and extraretinal SPEM velocity. Within this network neural activity increases with increasing target velocity. During extraretinal SPEM, additional engagement of the dorsolateral prefrontal cortex, angular gyrus, parahippocampal gyrus and superior temporal gyrus occurs. These regions encode cognitive functions such as memory, attention and monitoring. The activation of the inferior parietal cortex seems to be related to the interaction between velocity and blanking thereby underlining its relevance for task switching and sensorimotor transformation.

A neural representation of depth from motion parallax in macaque visual cortex

Perception of depth is a fundamental challenge for the visual system, particularly for observers moving through their environment. The brain makes use of multiple visual cues to reconstruct the three-dimensional structure of a scene. One potent cue, motion parallax, frequently arises during translation of the observer because the images of objects at different distances move across the retina with different velocities. Human psychophysical studies have demonstrated that motion parallax can be a powerful depth cue, and motion parallax seems to be heavily exploited by animal species that lack highly developed binocular vision. However, little is known about the neural mechanisms that underlie this capacity. Here we show, by using a virtual-reality system to translate macaque monkeys (Macaca mulatta) while they viewed motion parallax displays that simulated objects at different depths, that many neurons in the middle temporal area (area MT) signal the sign of depth (near versus far) from motion parallax in the absence of other depth cues. To achieve this, neurons must combine visual motion with extra-retinal (non-visual) signals related to the animal's movement. Our findings suggest a new neural substrate for depth perception and demonstrate a robust interaction of visual and non-visual cues in area MT. Combined with previous studies that implicate area MT in depth perception based on binocular disparities, our results suggest that area MT contains a more general representation of three-dimensional space that makes use of multiple cues.

Human Visuospatial Updating After Passive Translations in Three-Dimensional Space

To maintain a stable representation of the visual environment as we move, the brain must update the locations of targets in space using extra-retinal signals. Humans can accurately update after intervening active whole-body translations. But can they also update for passive translations (i.e., without efference copy signals of an outgoing motor command)? We asked six head-fixed subjects to remember the location of a briefly flashed target (five possible targets were located at depths of 23, 33, 43, 63, and 150 cm in front of the cyclopean eye) as they moved 10 cm left, right, up, down, forward, or backward while fixating a head-fixed target at 53 cm. After the movement, the subjects made a saccade to the remembered location of the flash with a combination of version and vergence eye movements. We computed an updating ratio where 0 indicates no updating and 1 indicates perfect updating. For lateral and vertical whole-body motion, where updating performance is judged by the size of the version movement, the updating ratios were similar for leftward and rightward translations, averaging 0.84 +/- 0.28 (mean +/- SD) as compared with 0.51 +/- 0.33 for downward and 1.05 +/- 0.50 for upward translations. For forward/backward movements, where updating performance is judged by the size of the vergence movement, the average updating ratio was 1.12 +/- 0.45. Updating ratios tended to be larger for far targets than near targets, although both intra- and intersubject variabilities were smallest for near targets. Thus in addition to self-generated movements, extra-retinal signals involving otolith and proprioceptive cues can also be used for spatial constancy.

Perceptual Stability—Going with the Flow

Historically, inflow and outflow hypotheses have been formulated as the primary explanations for perceptual stability. Central to these hypotheses is the postulation that, following an intended eye movement, knowledge of eye position cancels the consequences of the retinal image motion. Here, we reconsider the evidence for the extra-retinal signal and discuss whether this cancellation approach is compatible with the available empirical evidence. In particular, we propose that visual-oculomotor processing is a distributed process and that population-coding models of sensorimotor transformations are critical elements that need to be incorporated in any comprehensive explanation of spatial constancy.

Simultaneous adaptation of retinal and extra-retinal motion signals

A number of models of motion perception include estimates of eye velocity to help compensate for the incidental retinal motion produced by smooth pursuit. The ‘classical’ model uses extra-retinal motor command signals to obtain the estimate. More recent ‘reference-signal’ models use retinal motion information to enhance the extra-retinal signal. The consequence of simultaneously adapting to pursuit and retinal motion is thought to favour the reference-signal model, largely because the perception of motion during pursuit (‘perceived stability’) changes despite the absence of a standard motion aftereffect. The current experiments investigated whether the classical model could also account for these findings. Experiment 1 replicated the changes to perceived stability and then showed how simultaneous motion adaptation changes perceived retinal speed (a velocity aftereffect). Contrary to claims made by proponents of the reference-signal model, adapting simultaneously to pursuit and retinal motion therefore alters the retinal motion inputs to the stability computation. Experiment 2 tested the idea that simultaneous motion adaptation sets up a competitive interaction between two types of velocity aftereffect, one retinal and one extra-retinal. The results showed that pursuit adaptation by itself drove perceived stability in one direction and that adding adapting retinal motion drove perceived stability in the other. Moreover, perceived stability changed in conditions that contained no mismatch between adapting pursuit and adapting retinal motion, contrary to the reference-signal account. Experiment 3 investigated whether the effects of simultaneous motion adaptation were directionally tuned. Surprisingly no tuning was found, but this was true for both perceived stability and retinal velocity aftereffect. The three experiments suggest that simultaneous motion adaptation alters perceived stability based on separable changes to retinal and extra-retinal inputs. Possible mechanisms underlying the extra-retinal velocity aftereffect are discussed.

A model of the mechanism for the perceived location of a single flash and two successive flashes presented around the time of a saccade

According to current accounts, the perceived location of a target flash presented in the dark around the time of a saccade comes largely from an extraretinal signal that begins to change before, and continues to change during and following the saccade. Opposed to this view, this study offers a model suggesting that the perception of a single flash or two successive flashes in association with a saccade is the result of the combined effects of flash retinal signal persistence and an extraretinal signal that begins concurrent with or shortly after the saccade. For a single flash, the retinal signal persistence interacting with the extraretinal signal is responsible for the perceived location of the flash. In the case of two flashes with a short inter-flash-interval, the temporal overlap of the first flash persistence with the second flash persistence is a major factor in determining the perceived location of both of the flashes, and as a consequence, the perceived separation between them.

Perisaccadic Compression Correlates with Saccadic Peak Velocity: Differential Association of Eye Movement Dynamics with Perceptual Mislocalization Patterns

Objects flashed around the onset of a saccadic eye movement are grossly mislocalized. Perisaccadic mislocalization has been related to a spatiotemporal misalignment of an extraretinal eye position signal with the corresponding saccade. Two phenomena have been observed: a systematic shift of perceived positions in saccade direction and an additional compression toward the saccade target. At present, it is unclear whether these two components of mislocalization are mediated by distinct mechanisms and how extraretinal signals may contribute to either of them. Moreover, the pattern and strength of perisaccadic mislocalization varies considerably across studies and even between subjects tested under identical conditions. Here, we investigated whether interindividual differences in saccade parameters are related to differences in mislocalization. We found that the individual strength of perceptual compression selectively correlates with the peak velocity of corresponding saccades. Other saccade parameters did not correlate with compression. No correlation was found between the shift component of perisaccadic mislocalization and any saccade parameter. This dissociation suggests that shift and compression components are, at least partially, mediated by distinct mechanisms. Because neuronal activity in the superior colliculus and downstream oculomotor areas has been shown to correlate with saccadic peak velocity, our findings support the notion that a reafferent extraretinal signal associated with saccadic motor commands may contribute to perisaccadic compression of perceived positions.

Computations for geometrically accurate visually guided reaching in 3-D space

A fundamental question in neuroscience is how the brain transforms visual signals into accurate three-dimensional (3-D) reach commands, but surprisingly this has never been formally modeled. Here, we developed such a model and tested its predictions experimentally in humans. Our visuomotor transformation model used visual information about current hand and desired target positions to compute the visual (gaze-centered) desired movement vector. It then transformed these eye-centered plans into shoulder-centered motor plans using extraretinal eye and head position signals accounting for the complete 3-D eye-in-head and head-on-shoulder geometry (i.e., translation and rotation). We compared actual memory-guided reaching performance to the predictions of the model. By removing extraretinal signals (i.e., eye-head rotations and the offset between the centers of rotation of the eye and head) from the model, we developed a compensation index describing how accurately the brain performs the 3-D visuomotor transformation for different head-restrained and head-unrestrained gaze positions as well as for eye and head roll. Overall, subjects did not show errors predicted when extraretinal signals were ignored. Their reaching performance was accurate and the compensation index revealed that subjects accounted for the 3-D visuomotor transformation geometry. This was also the case for the initial portion of the movement (before proprioceptive feedback) indicating that the desired reach plan is computed in a feed-forward fashion. These findings show that the visuomotor transformation for reaching implements an internal model of the complete eye-to-shoulder linkage geometry and does not only rely on feedback control mechanisms. We discuss the relevance of this model in predicting reaching behavior in several patient groups.

Translation Speed Compensation in the Dorsal Aspect of the Medial Superior Temporal Area

The dorsal aspect of the medial superior temporal area (MSTd) is involved in the computation of heading direction from the focus of expansion (FOE) of the visual image. Our laboratory previously found that MSTd neurons adjust their focus tuning curves to compensate for shifts in the FOE produced by eye rotation (Bradley et al., 1996) as well as for changes in pursuit speed (Shenoy et al., 2002). The translation speed of an observer also affects the shift of the FOE. To investigate whether MSTd neurons can adjust their focus tuning curves to compensate for varying translation speeds, we recorded extracellular responses from 93 focus-tuned MSTd neurons in two rhesus monkeys (Macaca mulatta) performing pursuit eye movements across displays of varying translation speeds. We found that MSTd neurons had larger shifts in their tuning curves for slow translation speeds and smaller shifts for fast translation speeds. These shifts aligned the focus tuning curves with the true heading direction and not with the retinal position of the FOE. Because the eye was pursuing at the same rate for varying translation speeds, these results indicate that retinal cues related both to translation speed and extraretinal signals from pursuit eye movements are used by MSTd neurons to compute heading direction.

Visual memory capacity in transsaccadic integration

How we perceive the visual world as stable and unified suggests the existence of transsaccadic integration that retains and integrates visual information from one eye fixation to another eye fixation across saccadic eye movements. However, the capacity of transsaccadic integration is still a subject of controversy. We tested our subjects' memory capacity of two basic visual features, i.e. luminance (Experiment 1) and orientation (Experiment 2), both within a single fixation (i.e. visual working memory) and between separate fixations (i.e. transsaccadic memory). Experiment 2 was repeated, but attention allocation was manipulated using attentional cues at either the target or distracter (Experiment 3). Subjects were able to retain 3-4 objects in transsaccadic memory for luminance and orientation; errors generally increased as saccade size increased; and, subjects were more accurate when attention was allocated to the same location as the impending target. These results were modelled by inputting a noisy extra-retinal signal into an eye-centered feature map. Our results suggest that transsaccadic memory has a similar capacity for storing simple visual features as basic visual memory, but this capacity is dependent both on the metrics of the saccade and allocation of attention.

Direction and extent of perceived motion smear during pursuit eye movement

Smooth pursuit eye movements superimpose additional motion on the retinal image of untracked visual targets, potentially leading to the perception of motion smear and a distortion of the perceived direction of motion. Previously, we demonstrated an attenuation of perceived motion smear when the untracked target moves in the opposite direction of an ongoing pursuit eye movement. In this study, the extent of perceived motion smear and the direction of perceived smear were compared for a single bright dot that moved in a wide range of directions with respective to horizontal pursuit at 8 deg/s. Comparable data were obtained during fixation as a control. The results indicate that a significant attenuation of perceived motion smear occurs when the dot’s motion includes a horizontal component in the opposite direction of eye movement. In contrast, the direction of perceived smear approximates the trajectory of the retinal image motion, during both fixation and pursuit. These results suggest a selective application of extra-retinal signals to compensate specific aspects of visual perception that results from the retinal image motion during smooth pursuit eye movements.

Spatial constancy and the brain: insights from neural networks

To form an accurate internal representation of visual space, the brain must accurately account for movements of the eyes, head or body. Updating of internal representations in response to these movements is especially important when remembering spatial information, such as the location of an object, since the brain must rely on non-visual extra-retinal signals to compensate for self-generated movements. We investigated the computations underlying spatial updating by constructing a recurrent neural network model to store and update a spatial location based on a gaze shift signal, and to do so flexibly based on a contextual cue. We observed a striking similarity between the patterns of behaviour produced by the model and monkeys trained to perform the same task, as well as between the hidden units of the model and neurons in the lateral intraparietal area (LIP). In this report, we describe the similarities between the model and single unit physiology to illustrate the usefulness of neural networks as a tool for understanding specific computations performed by the brain.

Additivity of Retinal and Pursuit Velocity in the Perceptions of Depth and Rigidity from Object-Produced Motion Parallax

Two psychophysical experiments were conducted to investigate the mechanism that generates stable depth structure from retinal motion combined with extraretinal signals from pursuit eye movements. Stimuli consisted of random dots that moved horizontally in one direction (ie stimuli had common motion on the retina), but at different speeds between adjacent rows. The stimuli were presented with different speeds of pursuit eye movements whose direction was opposite to that of the common retinal motion. Experiment 1 showed that the rows moving faster on the retina appeared closer when viewed without eye movements; however, they appeared farther when pursuit speed exceeded the speed of common retinal motion. The 'transition' speed of the pursuit eye movement was slightly, but consistently, larger than the speed of common retinal motion. Experiment 2 showed that parallax thresholds for perceiving relative motion between adjacent rows were minimum at the transition speed found in experiment 1. These results suggest that the visual system calculates head-centric velocity, by adding retinal velocity and pursuit velocity, to obtain a stable depth structure.

The pursuit theory of motion parallax

Although motion parallax is closely associated with observer head movement, the underlying neural mechanism appears to rely on a pursuit-like eye movement signal to disambiguate perceived depth sign from the ambiguous retinal motion information [Naji, J. J., & Freeman, T. C. A. (2004). Perceiving depth order during pursuit eye movement. Vision Research, 44, 3025–3034; Nawrot, M. (2003). Eye movements provide the extra-retinal signal required for the perception of depth from motion parallax. Vision Research, 43, 1553–1562]. Here, we outline the evidence for a pursuit signal in motion parallax and propose a simple neural network model for how the pursuit theory of motion parallax might function within the visual system. The first experiment demonstrates the crucial role that an extra-retinal pursuit signal plays in the unambiguous perception of depth from motion parallax. The second experiment demonstrates that identical head movements can generate opposite depth percepts, and even ambiguous percepts, when the pursuit signal is altered. The pursuit theory of motion parallax provides a parsimonious explanation for all of these observations.