Reversed Visual Motion and Self-Sustaining Eye Oscillations

Perception ◽  
1997 ◽  
Vol 26 (7) ◽  
pp. 823-830 ◽  
Author(s):  
Lothar Spillmann ◽  
Stuart Anstis ◽  
Anne Kurtenbach ◽  
Ian Howard

A random-dot field undergoing counterphase flicker paradoxically appears to move in the same direction as head and eye movements, ie opposite to the optic-flow field. The effect is robust and occurs over a wide range of flicker rates and pixel sizes. The phenomenon can be explained by reversed phi motion caused by apparent pixel movement between successive retinal images. The reversed motion provides a positive feedback control of the display, whereas under normal conditions retinal signals provide a negative feedback. This altered polarity invokes self-sustaining eye movements akin to involuntary optokinetic nystagmus.

1998 ◽  
Vol 79 (3) ◽  
pp. 1461-1480 ◽  
Author(s):  
Markus Lappe ◽  
Martin Pekel ◽  
Klaus-Peter Hoffmann

Lappe, Markus, Martin Pekel, and Klaus-Peter Hoffmann. Optokinetic eye movements elicited by radial optic flow in the macaque monkey. J. Neurophysiol. 79: 1461–1480, 1998. We recorded spontaneous eye movements elicited by radial optic flow in three macaque monkeys using the scleral search coil technique. Computer-generated stimuli simulated forward or backward motion of the monkey with respect to a number of small illuminated dots arranged on a virtual ground plane. We wanted to see whether optokinetic eye movements are induced by radial optic flow stimuli that simulate self-movement, quantify their parameters, and consider their effects on the processing of optic flow. A regular pattern of interchanging fast and slow eye movements with a frequency of 2 Hz was observed. When we shifted the horizontal position of the focus of expansion (FOE) during simulated forward motion (expansional optic flow), median horizontal eye position also shifted in the same direction but only by a smaller amount; for simulated backward motion (contractional optic flow), median eye position shifted in the opposite direction. We relate this to a change in Schlagfeld typically observed in optokinetic nystagmus. Direction and speed of slow phase eye movements were compared with the local flow field motion in gaze direction (the foveal flow). Eye movement direction matched well the foveal motion. Small systematic deviations could be attributed to an integration of the global motion pattern. Eye speed on average did not match foveal stimulus speed, as the median gain was only ∼0.5–0.6. The gain was always lower for expanding than for contracting stimuli. We analyzed the time course of the eye movement immediately after each saccade. We found remarkable differences in the initial development of gain and directional following for expansion and contraction. For expansion, directional following and gain were initially poor and strongly influenced by the ongoing eye movement before the saccade. This was not the case for contraction. These differences also can be linked to properties of the optokinetic system. We conclude that optokinetic eye movements can be elicited by radial optic flow fields simulating self-motion. These eye movements are linked to the parafoveal flow field, i.e., the motion in the direction of gaze. In the retinal projection of the optic flow, such eye movements superimpose retinal slip. This results in complex retinal motion patterns, especially because the gain of the eye movement is small and variable. This observation has special relevance for mechanisms that determine self-motion from retinal flow fields. It is necessary to consider the influence of eye movements in optic flow analysis, but our results suggest that direction and speed of an eye movement should be treated differently.


2021 ◽  
Vol 33 (2) ◽  
pp. 248-262
Author(s):  
Alireza Soltani ◽  
Mohsen Rakhshan ◽  
Robert J. Schafer ◽  
Brittany E. Burrows ◽  
Tirin Moore

Primate vision is characterized by constant, sequential processing and selection of visual targets to fixate. Although expected reward is known to influence both processing and selection of visual targets, similarities and differences between these effects remain unclear mainly because they have been measured in separate tasks. Using a novel paradigm, we simultaneously measured the effects of reward outcomes and expected reward on target selection and sensitivity to visual motion in monkeys. Monkeys freely chose between two visual targets and received a juice reward with varying probability for eye movements made to either of them. Targets were stationary apertures of drifting gratings, causing the end points of eye movements to these targets to be systematically biased in the direction of motion. We used this motion-induced bias as a measure of sensitivity to visual motion on each trial. We then performed different analyses to explore effects of objective and subjective reward values on choice and sensitivity to visual motion to find similarities and differences between reward effects on these two processes. Specifically, we used different reinforcement learning models to fit choice behavior and estimate subjective reward values based on the integration of reward outcomes over multiple trials. Moreover, to compare the effects of subjective reward value on choice and sensitivity to motion directly, we considered correlations between each of these variables and integrated reward outcomes on a wide range of timescales. We found that, in addition to choice, sensitivity to visual motion was also influenced by subjective reward value, although the motion was irrelevant for receiving reward. Unlike choice, however, sensitivity to visual motion was not affected by objective measures of reward value. Moreover, choice was determined by the difference in subjective reward values of the two options, whereas sensitivity to motion was influenced by the sum of values. Finally, models that best predicted visual processing and choice used sets of estimated reward values based on different types of reward integration and timescales. Together, our results demonstrate separable influences of reward on visual processing and choice, and point to the presence of multiple brain circuits for the integration of reward outcomes.


2020 ◽  
Vol 123 (2) ◽  
pp. 571-586 ◽  
Author(s):  
Angela Mastropasqua ◽  
James Dowsett ◽  
Marianne Dieterich ◽  
Paul C. J. Taylor

The right frontal eye field (rFEF) is associated with visual perception and eye movements. rFEF is activated during optokinetic nystagmus (OKN), a reflex that moves the eye in response to visual motion (optokinetic stimulation, OKS). It remains unclear whether rFEF plays causal perceptual and/or oculomotor roles during OKS and OKN. To test this, participants viewed a leftward-moving visual scene of vertical bars and judged whether a flashed dot was moving. Single pulses of transcranial magnetic stimulation (TMS) were applied to rFEF on half of trials. In half of blocks, to explore oculomotor control, participants performed an OKN in response to the OKS. rFEF TMS, during OKN, made participants more accurate on trials when the dot was still, and it slowed eye movements. In separate blocks, participants fixated during OKS. This not only controlled for eye movements but also allowed the use of EEG to explore the FEF’s role in visual motion discrimination. In these blocks, by contrast, leftward dot motion discrimination was impaired, associated with a disruption of the frontal-posterior balance in alpha-band oscillations. None of these effects occurred in a control site (M1) experiment. These results demonstrate multiple related yet dissociable causal roles of the right FEF during optokinetic stimulation. NEW & NOTEWORTHY This study demonstrates causal roles of the right frontal eye field (FEF) in motion discrimination and eye movement control during visual scene motion: previous work had only examined other stimuli and eye movements such as saccades. Using combined transcranial magnetic stimulation and EEG and a novel optokinetic stimulation motion-discrimination task, we find evidence for multiple related yet dissociable causal roles within the FEF: perceptual processing during optokinetic stimulation, generation of the optokinetic nystagmus, and the maintenance of alpha oscillations.


2004 ◽  
Vol 91 (3) ◽  
pp. 1314-1326 ◽  
Author(s):  
Hilary W. Heuer ◽  
Kenneth H. Britten

The medial superior temporal area of extrastriate cortex (MST) contains signals selective for nonuniform patterns of motion often termed “optic flow.” The presence of such tuning, however, does not necessarily imply involvement in perception. To quantify the relationship between these selective neuronal signals and the perception of optic flow, we designed a discrimination task that allowed us to simultaneously record neuronal and behavioral sensitivities to near-threshold optic flow stimuli tailored to MST cells' preferences. In this two-alternative forced-choice task, we controlled the salience of globally opposite patterns (e.g., expansion and contraction) by varying the coherence of the motion. Using these stimuli, we could both relate the sensitivity of neuronal signals in MST to the animal's behavioral sensitivity and also measure trial-by-trial correlation between neuronal signals and behavioral choices. Neurons in MST showed a wide range of sensitivities to these complex motion stimuli. Many neurons had sensitivities equal or superior to the monkey's threshold. On the other hand, trial-by-trial correlation between neuronal discharge and choice (“choice probability”) was weak or nonexistent in our data. Together, these results lead us to conclude that MST contains sufficient information for threshold judgments of optic flow; however, the role of MST activity in optic flow discriminations may be less direct than in other visual motion tasks previously described by other laboratories.


10.1167/6.6.1 ◽  
2010 ◽  
Vol 6 (6) ◽  
pp. 1-1 ◽  
Author(s):  
D. Yang ◽  
M. Zhu ◽  
R. W. Hertle

2004 ◽  
Vol 21 (6) ◽  
pp. 895-904 ◽  
Author(s):  
AARON P. JOHNSON ◽  
W. JON. P. BARNES ◽  
MARTIN W.S. MACAULEY

Using a novel suite of computer-generated visual stimuli that mimicked components of optic flow, the visual responses of the tropical land crab,Cardisoma guanhumi, were investigated. We show that crabs are normally successful in distinguishing the rotational and translational components of the optic flow field, showing strong optokinetic responses to the former but not the latter. This ability was not dependant on the orientation of the crab, occurring both in “forwards-walking” and “sideways-walking” configurations. However, under conditions of low overall light intensity and/or low object/background contrast, the separation mechanism shows partial failure causing the crab to generate compensatory eye movements to translation, particularly in response to low-frequency (low-velocity) stimuli. Using this discovery, we then tested the ability of crabs to separate rotational and translational components in a combined rotation/translation flow field under different conditions. We demonstrate that, while crabs can successfully separate such a combined flow field under normal circumstances, showing compensatory eye movements only to the rotational component, they are unable to make this separation under conditions of low overall light intensity and low object/background contrast. Here, the responses to both flow-field components show summation when they are in phase, but, surprisingly, there is little reduction in the amplitude of responses to rotation when the translational component is in antiphase. Our results demonstrate that the crab's visual system finds separation of flow-field components a harder task than detection of movement, since the former shows partial failure at light intensities and/or object/background contrasts at which movement of the world around the crab is still generating high-gain optokinetic responses.


2000 ◽  
Vol 84 (2) ◽  
pp. 818-826 ◽  
Author(s):  
Urmen D. Upadhyay ◽  
William K. Page ◽  
Charles J. Duffy

Self-movement creates the patterned visual motion of optic flow with a focus of expansion (FOE) that indicates heading direction. During pursuit eye movements, depth cues create a retinal flow field that contains multiple FOEs, potentially complicating heading perception. Paradoxically, human heading perception during pursuit is improved by depth cues. We have studied medial superior temporal (MST) neurons to see whether their heading selectivity is also improved under these conditions. The responses of 134 MST neurons were recorded during the presentation of optic flow stimuli containing one or three speed-defined depth planes. During pursuit, multiple depth-plane stimuli evoked larger responses (71% of neurons) and stronger heading selectivity (70% of neurons). Responses to the three speed-defined depth-planes presented separately showed that most neurons (54%) preferred one of the planes. Responses to multiple depth-plane stimuli were larger than the averaged responses to the three component planes, suggesting enhancing interactions between depth-planes. Thus speed preferences create selective responses to one of many depth-planes in the retinal flow field. The presence of multiple depth-planes enhances those responses. These properties might improve heading perception during pursuit and contribute to relative depth perception.


2004 ◽  
Vol 21 (6) ◽  
pp. 905-911 ◽  
Author(s):  
AARON P. JOHNSON ◽  
W. JON. P. BARNES ◽  
MARTIN W.S. MACAULEY

Although a number of global mechanisms have been proposed over the years that explain how crabs might separate the rotational and translational components of their optic flow field, there has been no evidence to date that local mechanisms such as motion parallax are used in this separation. We describe here a study that takes advantage of a recently developed suite of computer-generated visual stimuli that creates a three-dimensional world surrounding the crab in which we can simulate translational and rotational optic flow. We show that, while motion parallax is not the only mechanism used in flow-field separation, it does play a role in the recognition of translational optic flow fields in that, under conditions of low overall light intensity and low contrast ratio when crabs find the distinction between rotation and translation harder, smaller eye movements occur in response to translation when motion parallax cues are present than when they are absent. Thus, motion parallax is one of many cues that crabs use to separate rotational and translational optic flow by showing compensatory eye movements to only the former.


2020 ◽  
Author(s):  
Hiu Mei Chow ◽  
Jonas Knöll ◽  
Matthew Madsen ◽  
Miriam Spering

AbstractWhen we move through our environment, objects in the visual scene create optic flow patterns on the retina. Even though optic flow is ubiquitous in everyday life, it is not well understood how our eyes naturally respond to it. In small groups of human and non-human primates, optic flow triggers intuitive, uninstructed eye movements to the pattern’s focus of expansion (Knöll, Pillow & Huk, 2018). Here we investigate whether such intuitive oculomotor responses to optic flow are generalizable to a larger group of human observers, and how eye movements are affected by motion signal strength and task instructions. Observers (n = 43) viewed expanding or contracting optic flow constructed by a cloud of moving dots radiating from or converging toward a focus of expansion that could randomly shift. Results show that 84% of observers tracked the focus of expansion with their eyes without being explicitly instructed to track. Intuitive tracking was tuned to motion signal strength: saccades landed closer to the focus of expansion and smooth tracking was more accurate when dot contrast, motion coherence, and translational speed were high. Under explicit tracking instruction, the eyes aligned with the focus of expansion more closely than without instruction. Our results highlight the sensitivity of intuitive eye movements as indicators of visual motion processing in dynamic contexts.


2020 ◽  
Author(s):  
Alireza Soltani ◽  
Mohsen Rakhshan ◽  
Robert J Schafer ◽  
Brittany E Burrows ◽  
Tirin Moore

AbstractPrimate vision is characterized by constant, sequential processing and selection of visual targets to fixate. Although expected reward is known to influence both processing and selection of visual targets, similarities and differences between these effects remains unclear mainly because they have been measured in separate tasks. Using a novel paradigm, we simultaneously measured the effects of reward outcomes and expected reward on target selection and sensitivity to visual motion in monkeys. Monkeys freely chose between two visual targets and received a juice reward with varying probability for eye movements made to either of them. Targets were stationary apertures of drifting gratings, causing the endpoints of eye movements to these targets to be systematically biased in the direction of motion. We used this motion-induced bias as a measure of sensitivity to visual motion on each trial. We then performed different analyses to explore effects of objective and subjective reward values on choice and sensitivity to visual motion in order to find similarities and differences between reward effects on these two processes. Specifically, we used different reinforcement learning models to fit choice behavior and estimate subjective reward values based on the integration of reward outcomes over multiple trials. Moreover, to compare the effects of subjective reward value on choice and sensitivity to motion directly, we considered correlations between each of these variables and integrated reward outcomes on a wide range of timescales. We found that in addition to choice, sensitivity to visual motion was also influenced by subjective reward value, even though the motion was irrelevant for receiving reward. Unlike choice, however, sensitivity to visual motion was not affected by objective measures of reward value. Moreover, choice was determined by the difference in subjective reward values of the two options whereas sensitivity to motion was influenced by the sum of values. Finally, models that best predicted visual processing and choice used sets of estimated reward values based on different types of reward integration and timescales. Together, our results demonstrate separable influences of reward on visual processing and choice, and point to the presence of multiple brain circuits for integration of reward outcomes.


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