Visual jitter: evidence for visual-motion-based compensation of retinal slip due to small eye movements

The Differentiation of Self-Motion From External Motion Is a Prerequisite for Postural Control: A Narrative Review of Visual-Vestibular Interaction

The visual system is a source of sensory information that perceives environmental stimuli and interacts with other sensory systems to generate visual and postural responses to maintain postural stability. Although the three sensory systems; the visual, vestibular, and somatosensory systems work concurrently to maintain postural control, the visual and vestibular system interaction is vital to differentiate self-motion from external motion to maintain postural stability. The visual system influences postural control playing a key role in perceiving information required for this differentiation. The visual system’s main afferent information consists of optic flow and retinal slip that lead to the generation of visual and postural responses. Visual fixations generated by the visual system interact with the afferent information and the vestibular system to maintain visual and postural stability. This review synthesizes the roles of the visual system and their interaction with the vestibular system, to maintain postural stability.

Functional Connectivity in Developmental Dyslexia during Speed Discrimination

A universal signature of developmental dyslexia is literacy acquisition impairments. Besides, dyslexia may be related to deficits in selective spatial attention, in the sensitivity to global visual motion, speed processing, oculomotor coordination, and integration of auditory and visual information. Whether motion-sensitive brain areas of children with dyslexia can recognize different speeds of expanded optic flow and segregate the slow-speed from high-speed contrast of motion was a main question of the study. A combined event-related EEG experiment with optic flow visual stimulation and functional frequency-based graph approach (small-world propensity ϕ) were applied to research the responsiveness of areas, which are sensitive to motion, and also distinguish slow/fast -motion conditions on three groups of children: controls, untrained (pre-D) and trained dyslexics (post-D) with visual intervention programs. Lower ϕ at θ, α, γ1-frequencies (low-speed contrast) for controls than other groups represent that the networks rewire, expressed at β frequencies (both speed contrasts) in the post-D, whose network was most segregated. Functional connectivity nodes have not existed in pre-D at dorsal medial temporal area MT+/V5 (middle, superior temporal gyri), left-hemispheric middle occipital gyrus/visual V2, ventral occipitotemporal (fusiform gyrus/visual V4), ventral intraparietal (supramarginal, angular gyri), derived from θ-frequency network for both conditions. After visual training, compensatory mechanisms appeared to implicate/regain these brain areas in the left hemisphere through plasticity across extended brain networks. Specifically, for high-speed contrast, the nodes were observed in pre-D (θ-frequency) and post-D (β2-frequency) relative to controls in hyperactivity of the right dorsolateral prefrontal cortex, which might account for the attentional network and oculomotor control impairments in developmental dyslexia.

Achieving visual stability during smooth pursuit eye movements: Directional and confidence judgements favor a recalibration model

During smooth pursuit eye movements, the visual system is faced with the task of telling apart reafferent retinal motion from motion in the world. While an efference copy signal can be used to predict the amount of reafference to subtract from the image, an image-based adaptive mechanism can ensure the continued accuracy of this computation. Indeed, repeatedly exposing observers to background motion with a fixed direction relative to that of the target that is pursued leads to a shift in their point of subjective stationarity (PSS). We asked whether the effect of exposure reflects adaptation to motion contingent on pursuit direction, recalibration of a reference signal or both. A recalibration account predicts a shift in reference signal (i.e. predicted reafference), resulting in a shift of PSS, but no change in sensitivity. Results show that both directional judgements and confidence judgements about them favor a recalibration account, whereby there is an adaptive shift in the reference signal caused by the prevailing retinal motion during pursuit. We also found that the recalibration effect is specific to the exposed visual hemifield.

High-acuity vision from retinal image motion

A mathematical model and a possible neural mechanism are proposed to account for how fixational drift motion in the retina confers a benefit for the discrimination of high-acuity targets. We show that by simultaneously estimating object shape and eye motion, neurons in visual cortex can compute a higher quality representation of an object by averaging out non-uniformities in the retinal sampling lattice. The model proposes that this is accomplished by two separate populations of cortical neurons - one providing a representation of object shape and another representing eye position or motion - which are coupled through specific multiplicative connections. Combined with recent experimental findings, our model suggests that the visual system may utilize principles not unlike those used in computational imaging for achieving "super-resolution" via camera motion.

Interactions of flicker and motion

We present a series of novel observations about interactions between flicker and motion that lead to three distinct perceptual effects. We use the term flicker to describe alternating changes in a stimulus' luminance or color (i.e. a circle that flickers from black to white and visa-versa). When objects flicker, three distinct phenomena can be observed: (1) Flicker Induced Motion (FLIM) in which a single, stationary object, appears to move when it flickers at certain rates; (2) Flicker Induced Motion Suppression (FLIMS) in which a moving object appears to be stationary when it flickers at certain rates, and (3) Flicker-Induced Induced-Motion (FLIIM) in which moving objects that are flickering induce another flickering stationary object to appear to move. Across four psychophysical experiments, we characterize key stimulus parameters underlying these flicker-motion interactions. Interactions were strongest in the periphery and at flicker frequencies above 10 Hz. Induced motion occurred not just for luminance flicker, but for isoluminant color changes as well. We also found that the more physically moving objects there were, the more motion induction to stationary objects occurred. We present demonstrations that the effects reported here cannot be fully accounted for by eye movements: we show that the perceived motion of multiple stationary objects that are induced to move via flicker can appear to move independently and in random directions, whereas eye movements would have caused all of the objects to appear to move coherently. These effects highlight the fundamental role of spatiotemporal dynamics in the representation of motion and the intimate relationship between flicker and motion.

Spatial scaling of illusory motion perceived in a static figure

In a phenomenon known as the Rotating Snakes illusion (Kitaoka & Ashida, 2003), illusory motion is perceived in a static figure with a specially designed luminance profile. It is known that the strength of this illusion increases with eccentricity, suggesting that the underlying mechanism of the illusion has a spatial property that changes with eccentricity. If a change in receptive-field size of responsible neurons causes the eccentricity dependence of the illusion, its strength should be spatially scalable using a scaling factor that increases with eccentricity, because the receptive field size of neurons in visual areas with retinotopy generally obeys quantitative dependence on eccentricity. For the luminance micropatterns comprising the figure for the Rotating Snakes illusion, we varied eccentricity from 9 to 15 deg and spatial frequency from 0.25 to 1.6 cycles/deg, and measured illusion strength. Illusion strength was found to increase with decreasing spatial frequency and with increasing eccentricity. Furthermore, the profiles of illusion strength at different eccentricities were spatially scalable into a single parabola as a function of the spatially scaled visual angle. The estimated scaling factors linearly increased with eccentricity with a slope similar to the eccentricity dependence of the receptive field size of V1 neurons, suggesting the involvement of early visual areas in the generation of the illusion.

Masking of random-walk motion by flicker, and its role in the allocation of motion in the on-line jitter illusion

Typically, perceptual stabilization mechanisms make us unaware of the retinal image motion produced by the small, involuntary eye movements our eyes constantly make during fixation. The breakdown of perceptual stability is demonstrated by the on-line jitter illusion, in which a circular static pattern appears to jitter coherently when surrounded by a flickering annular pattern. Although both regions of the stimulus are subject to retinal motion from eye movements, the visual system attributes this motion to the central static region in the form of visual jitter, while the surrounding flickering region remains perceptually stable. We investigated factors influencing this allocation of motion and reference frame in the on-line jitter illusion. The flickering of the surround was found to impair the detection of simultaneous random-walk motion in this area, giving a detection reliability of around 80% for motion approximating that from fixational eye movements. Changes to spatial texture and location of flicker (centre vs. surrounding annulus) had little effect on the final percept. However, use of a nonconcentric stimulus resulted in a marked reduction in apparent jitter in all subjects. Our results suggest for the on-line jitter illusion, allocation of motion and reference frame is influenced by the general principle that, if one region surrounds another, the surrounding region tends to be allocated as the frame of reference. When this factor is controlled for, spatial textures, location of flicker, and the masking of motion by flicker have a smaller but measurable influence on the final percept.

Direction-specific fMRI adaptation reveals the visual cortical network underlying the "Rotating Snakes" illusion

The "Rotating Snakes" figure elicits a clear sense of anomalous motion in stationary repetitive patterns. We used an event-related fMRI adaptation paradigm to investigate cortical mechanisms underlying the illusory motion. Following an adapting stimulus (S1) and a blank period, a probe stimulus (S2) that elicited illusory motion either in the same or in the opposite direction was presented. Attention was controlled by a fixation task, and control experiments precluded explanations in terms of artefacts of local adaptation, afterimages, or involuntary eye movements. Recorded BOLD responses were smaller for S2 in the same direction than S2 in the opposite direction in V1-V4, V3A, and MT+, indicating direction-selective adaptation. Adaptation in MT+ was correlated with adaptation in V1 but not in V4. With possible downstream inheritance of adaptation, it is most likely that adaptation predominantly occurred in V1. The results extend our previous findings of activation in MT+ (I. Kuriki, H. Ashida, I. Murakami, and A. Kitaoka, 2008), revealing the activity of the cortical network for motion processing from V1 towards MT+. This provides evidence for the role of front-end motion detectors, which has been assumed in proposed models of the illusion.

Representation of perceptually invisible image motion in extrastriate visual area MT of macaque monkeys

Why does the world appear stable despite the visual motion induced by eye movements during fixation? We find that the answer must reside in how visual motion signals are interpreted by perception, because MT neurons in monkeys respond to the image motion caused by eye drifts in the presence of a stationary stimulus. Several features suggest a visual origin for the responses of MT neurons during fixation: spike-triggered averaging yields a peak image velocity in the preferred direction that precedes spikes by ∼60 ms; image velocity during fixation and firing rate show similar peaks in power at 4-5 Hz; and average MT firing during a period of fixation is related monotonically to the image speed along the preferred axis of the neurons 60 ms earlier. The percept caused by the responses of MT neurons during fixation depends on the distribution of activity across the population of neurons of different preferred speeds. For imposed stimulus motion, the population response peaks for neurons that prefer the actual target speed. For small image motions caused by eye drifts during fixation, the population response is large, but is noisy and does not show a clear peak. This representation of image motion in MT would be ignored if perception interprets the population response in the context of a prior of zero speed. Then, we would see a stable scene despite MT responses caused by eye drifts during fixation.

Spatiotemporal effects of microsaccades on population activity in the visual cortex of monkeys during fixation

During visual fixation, the eyes make fast involuntary miniature movements known as microsaccades (MSs). When MSs are executed they displace the visual image over the retina and can generate neural modulation along the visual pathway. However, the effects of MSs on neural activity have substantial variability and are not fully understood. By utilizing voltage-sensitive dye imaging, we imaged the spatiotemporal patterns induced by MSs in V1 and V2 areas of behaving monkeys while they were fixating and presented with visual stimuli. We then investigated the neuronal modulation dynamics, induced by MSs, under different visual stimulation. MSs induced monophasic or biphasic neural responses depending on stimulus size. These neural responses were accompanied by different spatiotemporal patterns of synchronization. Finally, we show that a local patch of population response evoked by a small stimulus was clearly shifted over the V1 retinotopic map after each MS. Our results demonstrate the lack of visual stability in V1 following MSs and help clarify the substantial variability reported for MSs effects on neuronal responses. The observed neural effects suggest that MSs are associated with a continuum of neuronal responses in V1 area reflecting diverse spatiotemporal dynamics.

Bayesian model of dynamic image stabilization in the visual system

Humans can resolve the fine details of visual stimuli although the image projected on the retina is constantly drifting relative to the photoreceptor array. Here we demonstrate that the brain must take this drift into account when performing high acuity visual tasks. Further, we propose a decoding strategy for interpreting the spikes emitted by the retina, which takes into account the ambiguity caused by retinal noise and the unknown trajectory of the projected image on the retina. A main difficulty, addressed in our proposal, is the exponentially large number of possible stimuli, which renders the ideal Bayesian solution to the problem computationally intractable. In contrast, the strategy that we propose suggests a realistic implementation in the visual cortex. The implementation involves two populations of cells, one that tracks the position of the image and another that represents a stabilized estimate of the image itself. Spikes from the retina are dynamically routed to the two populations and are interpreted in a probabilistic manner. We consider the architecture of neural circuitry that could implement this strategy and its performance under measured statistics of human fixational eye motion. A salient prediction is that in high acuity tasks, fixed features within the visual scene are beneficial because they provide information about the drifting position of the image. Therefore, complete elimination of peripheral features in the visual scene should degrade performance on high acuity tasks involving very small stimuli.

Event-related functional MRI of cortical activity evoked by microsaccades, small visually-guided saccades, and eyeblinks in human visual cortex

We used event-related functional magnetic resonance imaging (fMRI) to determine blood oxygen-level-dependent (BOLD) signal changes following microsaccades, visually-guided saccades, and eyeblinks in retinotopically mapped visual cortical areas V1-V3 and hMT+. A deconvolution analysis revealed a similar pattern of BOLD activation following a microsaccade, 0.16 degrees voluntary saccade, and 0.16 degrees displacement of the image under conditions of fixation. In all areas, an initial increase in BOLD signal peaking at approximately 4.5 s after the event was followed by a decline and decrease below baseline. This modulation appears most pronounced for microsaccades and small voluntary saccades in V1, diminishing in strength from V1 to V3. In contrast, 0.16 degrees real motion under conditions of fixation yields the same level of BOLD signal increase in V1 through V3. BOLD signal modulates parametrically with the size of voluntary saccades (0.16 degrees , 0.38 degrees , 0.82 degrees , 1.64 degrees , and 3.28 degrees ) in V1-V3, but not in hMT+. Eyeblinks generate larger modulation that peaks by 6.5 s, and dips below baseline by 10 s post-event, and also exhibits diminishing modulation from V1 to V3. Our results are consistent with the occurrence of transient neural excitation driven by changes in input to retinal ganglion cell receptive fields that are induced by microsaccades, visually-guided saccades, or small image shifts. The pattern of results in area hMT+ exhibits no significant modulation by microsaccades, relatively small modulation by eyeblinks, and substantial responses to saccades and background jumps, suggesting that spurious image motion signal arising from microsaccades and eyeblinks is relatively diminished by hMT+.

The effect of microsaccades on the correlation between neural activity and behavior in middle temporal, ventral intraparietal, and lateral intraparietal areas

It is widely reported that the activity of single neurons in visual cortex is correlated with the perceptual decision of the subject. The strength of this correlation has implications for the neuronal populations generating the percepts. Here we asked whether microsaccades, which are small, involuntary eye movements, contribute to the correlation between neural activity and behavior. We analyzed data from three different visual detection experiments, with neural recordings from the middle temporal (MT), lateral intraparietal (LIP), and ventral intraparietal (VIP) areas. All three experiments used random dot motion stimuli, with the animals required to detect a transient or sustained change in the speed or strength of motion. We found that microsaccades suppressed neural activity and inhibited detection of the motion stimulus, contributing to the correlation between neural activity and detection behavior. Microsaccades accounted for as much as 19% of the correlation for area MT, 21% for area LIP, and 17% for VIP. While microsaccades only explain part of the correlation between neural activity and behavior, their effect has implications when considering the neuronal populations underlying perceptual decisions.

The significance of microsaccades for vision and oculomotor control

Over the past decade several research groups have taken a renewed interest in the special role of a type of small eye movement, called 'microsaccades', in various visual processes, such as the activation of neurons in the central nervous system, or the prevention of image fading. As the study of microsaccades and their relation to visual processes goes back at least half a century, it seems appropriate to review the more recent reports in light of the history of research on maintained oculomotor fixation, in general, and on microsaccades in particular. Our review shows that there is no compelling evidence to support the view that microsaccades (or, fixation saccades more generally) serve a necessary role in improving oculomotor control or in keeping the visual world visible. The role of the retinal transients produced by small saccades during fixation needs to be evaluated in the context of both the brisk image motions present during active visual tasks performed by freely moving people, as well as the role of selective attention in modulating the strength of signals throughout the visual field.

Effects of fixational eye movements on retinal ganglion cell responses: a modelling study

Visual response properties of retinal ganglion cells (GCs), the retinal output neurons, are shaped by numerous processes and interactions within the retina. In particular, amacrine cells are known to form microcircuits that affect GC responses in specific ways. So far, relatively little is known about the influence of retinal processing on GC responses under naturalistic viewing conditions, in particular in the presence of fixational eye movements. Here we used a detailed model of the mammalian retina to investigate possible effects of fixational eye movements on retinal GC activity. Populations of linear, sustained (parvocellular, PC) and nonlinear, transient (magnocellular, MC) GCs were simulated during fixation of a star-shaped stimulus, and two distinct effects were found: (1) a fading of complete wedges of the star and (2) an apparent splitting of stimulus lines. Both effects only occur in MC-cells, and an analysis shows that fading is caused by an expression of the aperture problem in retinal GCs, and the splitting effect by spatiotemporal nonlinearities in the MC-cell receptive field. These effects strongly resemble perceived instabilities during fixation of the same stimulus, and we propose that these illusions may have a retinal origin. We further suggest that in this case two parallel retinal streams send conflicting, rather than complementary, information to the higher visual system, which here leads to a dominant influence of the MC pathway. Similar situations may be common during natural vision, since retinal processing involves numerous nonlinearities.

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.

A neural computation for visual acuity in the presence of eye movements

Humans can distinguish visual stimuli that differ by features the size of only a few photoreceptors. This is possible despite the incessant image motion due to fixational eye movements, which can be many times larger than the features to be distinguished. To perform well, the brain must identify the retinal firing patterns induced by the stimulus while discounting similar patterns caused by spontaneous retinal activity. This is a challenge since the trajectory of the eye movements, and consequently, the stimulus position, are unknown. We derive a decision rule for using retinal spike trains to discriminate between two stimuli, given that their retinal image moves with an unknown random walk trajectory. This algorithm dynamically estimates the probability of the stimulus at different retinal locations, and uses this to modulate the influence of retinal spikes acquired later. Applied to a simple orientation-discrimination task, the algorithm performance is consistent with human acuity, whereas naive strategies that neglect eye movements perform much worse. We then show how a simple, biologically plausible neural network could implement this algorithm using a local, activity-dependent gain and lateral interactions approximately matched to the statistics of eye movements. Finally, we discuss evidence that such a network could be operating in the primary visual cortex.

Like a camera, the eye projects an image of the world onto our retina. But unlike a camera, the eye continues to execute small, random movements, even when we fix our gaze. Consequently, the projected image jitters over the retina. In a camera, such jitter leads to a blurred image on the film. Interestingly, our visual acuity is many times sharper than expected from the motion blur. Apparently, the brain uses an active process to track the image through its jittering motion across the retina. Here, we propose an algorithm for how this can be accomplished. The algorithm uses realistic spike responses of optic nerve fibers to reconstruct the visual image, and requires no knowledge of the eye movement trajectory. Its performance can account for human visual acuity. Furthermore, we show that this algorithm could be implemented biologically by the neural circuits of primary visual cortex.

Even when we hold our gaze still, small eye movements jitter the visual image of the world across the retina. The authors show how a stable and sharp image might be recovered through neural processing in the visual cortex.

A positive correlation between fixation instability and the strength of illusory motion in a static display

A stationary pattern with asymmetrical luminance gradients can appear to move. We hypothesized that the source signal of this illusion originates in retinal image motions due to fixational eye movements. We investigated the inter-subject correlation between fixation instability and illusion strength. First, we demonstrated that the strength of the illusion can be quantified by the nulling technique. Second, we concurrently measured cancellation velocity and fixation instability for each subject, and found a positive correlation between them. The same relationship was also found within a single observer when the visual stimulus was artificially moved in the simulation of fixation instability. Third, we confirmed the same correlation with eye movements for a wider variety of illusory displays. These results suggest that fixational eye movements indeed play a relevant role in generating this motion illusion.

Fixational eye movements and motion perception

Small eye movements are necessary for maintained visibility of the static scene, but at the same time they randomly oscillate the retinal image, so the visual system must compensate for such motions to yield the stable visual world. According to the theory of visual stabilization based on retinal motion signals, objects are perceived to move only if their retinal images make spatially differential motions with respect to some baseline movement probably due to eye movements. Motion illusions favoring this theory are demonstrated, and psychophysical as well as brain-imaging studies on the illusions are reviewed. It is argued that perceptual stability is established through interactions between motion-energy detection at an early stage and spatial differentiation of motion at a later stage. As such, image oscillations originating in fixational eye movements go unnoticed perceptually, and it is also shown that image oscillations are, though unnoticed, working as a limiting factor of motion detection. Finally, the functional importance of non-differential, global motion signals are discussed in relation to visual stability during large-scale eye movements as well as heading estimation.

Fixational eye movements in normal and pathological vision

Most of our visual experience is driven by the eye movements we produce while we fixate our gaze. In a sense, our visual system thus has a built-in contradiction: when we direct our gaze at an object of interest, our eyes are never still. Therefore the perception, physiology, and computational modeling of fixational eye movements is critical to our understanding of vision in general, and also to the understanding of the neural computations that work to overcome neural adaptation in normal subjects as well as in clinical patients. Moreover, because we are not aware of our fixational eye movements, they can also help us understand the underpinnings of visual awareness. Research in the field of fixational eye movements faded in importance for several decades during the late 20th century. However, new electrophysiological and psychophysical data have now rejuvenated the field. The last decade has brought significant advances to our understanding of the neuronal and perceptual effects of fixational eye movements, with crucial implications for neural coding, visual awareness, and perception in normal and pathological vision. This chapter will review the type of neural activity generated by fixational eye movements at different levels in the visual system, as well as the importance of fixational eye movements for visual perception in normal vision and in visual disease. Special attention will be given to microsaccades, the fastest and largest type of fixational eye movement.

Function of the mammalian postorbital bar

Complete postorbital bars, bony arches that encompass the lateral aspect of the eye and form part of a circular orbit, have evolved homoplastically multiple times during mammalian evolution. Numerous functional hypotheses have been advanced for postorbital bars, the most promising being that postorbital bars function to stiffen the lateral orbit in taxa that have significant angular deviation between the temporal fossa and the bony orbit. Without a stiff lateral orbit the anterior temporalis muscle and fascia potentially would pull on the postorbital ligament, deform the orbit, and cause disruption of oculomotor precision. Morphometric data were collected on 1,329 specimens of 324 taxa from 16 orders of extant eutherian and metatherian mammals in order to test whether the orientation of the orbit relative to the temporal fossa is correlated with the replacement of the postorbital ligament with bone. The allometric and ecological influences on orbit orientation across mammals are also explored. The morphometric results corroborate the hypothesis: Shifts in orbit orientation relative to the temporal fossa are correlated with the size of the postorbital processes, which replace the ligament. The allometric and ecological factors that influence orbit orientation vary across taxa. Postorbital bars stiffen the lateral orbital wall. Muscle pulleys, ligaments, and other connective tissue attach to the lateral orbital wall, including the postorbital bar. Without a stiff lateral orbit, deformation due to temporalis contraction would displace soft tissues contributing to normal oculomotor function.

Two visual motion processing deficits in developmental dyslexia associated with different reading skills deficits

Developmental dyslexia is associated with deficits in the processing of visual motion stimuli, and some evidence suggests that these motion processing deficits are related to various reading subskills deficits. However, little is known about the mechanisms underlying such associations. This study lays a richer groundwork for exploration of such mechanisms by more comprehensively and rigorously characterizing the relationship between motion processing deficits and reading subskills deficits. Thirty-six adult participants, 19 of whom had a history of developmental dyslexia, completed a battery of visual, cognitive, and reading tests. This battery combined motion processing and reading subskills measures used across previous studies and added carefully matched visual processing control tasks. Results suggest that there are in fact two distinct motion processing deficits in developmental dyslexia, rather than one as assumed by previous research, and that each of these deficits is associated with a different type of reading subskills deficit. A deficit in detecting coherent motion is selectively associated with low accuracy on reading subskills tests, and a deficit in discriminating velocities is selectively associated with slow performance on these same tests. In addition, evidence from visual processing control tasks as well as self-reports of ADHD symptoms suggests that these motion processing deficits are specific to the domain of visual motion, and result neither from a broader visual deficit, nor from the sort of generalized attention deficit commonly comorbid with developmental dyslexia. Finally, dissociation between these two motion processing deficits suggests that they may have distinct neural and functional underpinnings. The two distinct patterns of motion processing and reading deficits demonstrated by this study may reflect separable underlying neurocognitive mechanisms of developmental dyslexia.

Correlations between fixation stability and visual motion sensitivity

To assess influences of fixational drift eye movements on motion detection, lower thresholds for motion and drift amplitudes were measured in normal subjects. The threshold was higher without visible surrounds than with a surround, and had a positive correlation with drift amplitude. The same effect, but more pronounced, was found when the surround was visible but flickered synchronously. In contrast, the correlation disappeared in the threshold with a static surround. These results suggest that, while spurious image motions by eye drift can have a detrimental effect, a mechanism tuned for differential motions normally counteracts it.

Optokinetic potential and the perception of head-centred speed

Extra-retinal information about eye velocity is thought to play an important role in compensating the retinal motion experienced during an eye movement. Evidently this compensation process is prone to error, since stimulus properties such as contrast and spatial frequency have marked effect on perceived motion with respect to the head. Here we investigate the suggestion, that 'optokinetic potential' [Perception 14 (1985) 631] may contribute to an explanation of these errors. First, we measured the optokinetic nystagmus induced by each stimulus so as to determine the optokinetic potential. Second, we determined the speed match between two patches of Gaussian blobs presented sequentially. Observers pursued the first pattern and kept their eyes stationary when viewing the second. For stimuli with identical contrast or spatial frequency, the pursued pattern was perceived to move slower than the non-pursued pattern (the Aubert-Fleischl phenomenon). Lowering the contrast or the spatial frequency of the non-pursued pattern resulted in a systematic decrease of its perceived speed. A further condition in which the contrast or spatial frequency of the pursued pattern was varied, resulted in no change to its perceived speed. Pursuit eye movements were recorded and found to be independent of stimulus properties. The results cast doubt on the idea that changing contrast or spatial frequency affects perceived head-centred speed by altering optokinetic potential.

Illusory jitter in a static stimulus surrounded by a synchronously flickering pattern

The eyes are always moving even during fixation, making the retinal image move concomitantly. While these motions activate early visual stages, they are excluded from one's perception. A striking illusion reported here renders them visible: a static pattern surrounded by a synchronously flickering pattern appears to move coherently in random directions. There was a positive correlation between the illusion and fixational eye movements. A simulation revealed that motion computation artificially creates a motion difference between center and surround, which is usually a cue to object motion but now a wrong cue to seeing eye movements of oneself on-line. Therefore, this novel illusion indicates that the visual system normally counteracts shaky visual inputs due to small eye movements by using retinal, as opposed to extraretinal, motion signals. As long as they comprise common image motions over space, they are interpreted as coming from a static outer world viewed through moving eyes. Such visual stability fails in the condition of artificial flicker, because common image motions due to eye movements are registered differently between flickering and non-flickering regions.

Motion perception during involuntary eye vibration

Retinal motion caused by reflexive or voluntary eye movements is rarely misinterpreted as object motion, as if the visual system discounted the contribution of these eye movements to retinal motion. Yet, involuntary eye movements caused by mechanical eye vibration is often interpreted as object motion unless the vibration has high frequency, in which case only image blur may be noticed. In these latter conditions, however, a light flickering above the fusion limit is vividly perceived to undergo oscillatory motion over its static surround. We determined the conditions of this phenomenon, showing that the perceived frequency of illusory oscillation equals the difference between flicker frequency and the frequency of vibration of the eyes. This outcome is explained as a result of the low-pass temporal frequency characteristic of vision, which further predicts that the same effect should occur if the flickering light is vibrated and observed with static eyes. This prediction was corroborated empirically. We also determined the minimal amplitude of oscillation required to perceive motion as a function of postural stability and the presence of static references, finding an amplitude threshold of approximately 1 arcmin with postural stability in dim-light conditions, which increases to approximately 2 arcmin with postural instability in the dark.

Detection of relative and uniform motion

We measured the lowest velocity (velocity threshold) for discriminating motion direction in relative and uniform motion stimuli, varying the contrast and the spatial frequency of the stimulus gratings. The results showed significant differences in the effects of contrast and spatial frequency on the threshold, as well as on the absolute threshold level between the two motion conditions, except when the contrast was 1% or lower. Little effect of spatial frequency was found for uniform motion, whereas a bandpass property with a peak at approximately 5 cycles per degree was found for relative motion. It was also found that contrast had little effect on uniform motion, whereas the threshold decreased with increases in contrast up to 85% for relative motion. These differences cannot be attributed to possible differences in eye movements between the relative and the uniform motion conditions, because the spatial-frequency characteristics differed in the two conditions even when the presentation duration was short enough to prevent eye movements. The differences also cannot be attributed to detecting positional changes, because the velocity threshold was not determined by the total distance of the stimulus movements. These results suggest that there are two different motion pathways: one that specializes in relative motion and one that specializes in uniform or global motion. A simulation showed that the difference in the response functions of the two possible pathways accounts for the differences in the spatial-frequency and contrast dependency of the velocity threshold.

The function of bursts of spikes during visual fixation in the awake primate lateral geniculate nucleus and primary visual cortex

When images are stabilized on the retina, visual perception fades. During voluntary visual fixation, however, constantly occurring small eye movements, including microsaccades, prevent this fading. We previously showed that microsaccades generated bursty firing in the primary visual cortex (area V-1) in the presence of stationary stimuli. Here we examine the neural activity generated by microsaccades in the lateral geniculate nucleus (LGN), and in the area V-1 of the awake monkey, for various functionally relevant stimulus parameters. During visual fixation, microsaccades drove LGN neurons by moving their receptive fields across a stationary stimulus, offering a likely explanation of how microsaccades block fading during normal fixation. Bursts of spikes in the LGN and area V-1 were associated more closely than lone spikes with preceding microsaccades, suggesting that bursts are more reliable than are lone spikes as neural signals for visibility. In area V-1, microsaccade-generated activity, and the number of spikes per burst, was maximal when the bar stimulus centered over a receptive field matched the cell's optimal orientation. This suggested burst size as a neural code for stimuli optimality (and not solely stimuli visibility). As expected, burst size did not vary with stimulus orientation in the LGN. To address the effectiveness of microsaccades in generating neural activity, we compared activity correlated with microsaccades to activity correlated with flashing bars. Onset responses to flashes were about 7 times larger than the responses to the same stimulus moved across the cells' receptive fields by microsaccades, perhaps because of the relative abruptness of flashes.

Human brain activity during illusory visual jitter as revealed by functional magnetic resonance imaging

One central problem in vision is how to compensate for retinal slip. A novel illusion (visual jitter) suggests the compensation mechanism is based solely on retinal motion. Adaptation to visual noise attenuates the motion signals used by the compensation stage, producing illusory jitter due to the undercompensation of retinal slip. Here, we investigated the neural substrate of retinal slip compensation during this illusion using high-field fMRI and retinotopic mapping in flattened cortical format. When jitter perception occurred, MR signal decreased in lower stages of the visual system but increased prominently in area MT+. In conclusion, visual areas as early as V1 are responsible for the adaptation stage, and MT+ is involved in the compensation stage. The present finding suggests the pathway from V1 to MT+ has an important role in stabilizing the visual world.