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Animals typically rely on vision to direct their locomotion through the environment. Flies, who move in three dimensions while in flight, have evolved the fastest visual system in the animal kingdom to help them stabilize their flight posture and trajectories (Autrum, 1958). Partly for this reason, they have been the subject of extensive research on the neuronal basis of motion vision, the component of visual function involved in detecting movement within a scene. Using a variety of techniques, including electrophysiology, genetic manipulation, and behavioral analysis, researchers have started to unravel the earliest stages of motion processing (Clark et al., 2011; Eichner et al., 2011). Visual motion processing in the fly begins with the elementary motion detectors (EMDs), which are units sensitive to one direction of motion over a small receptive field. The identities of the cells involved in this computation are under active research, and a complete picture has yet to emerge. For over four decades, however, the identity of one set of downstream cells that receive input from the EMDs has been known (Braitenberg, 1972). These cells, located in the lobula plate of the optic lobe of the fly, are called the horizontal system (HS) and vertical system (VS) cells.

Active sensation poses unique challenges to sensory systems because moving the sensor necessarily alters the input sensory stream. Sensory input quality is additionally compromised if the sensor moves rapidly, as during rapid eye movements, making the period immediately after the movement critical for recovering reliable sensation. Here, we studied this immediate postmovement interval for the case of microsaccades during fixation, which rapidly jitter the “sensor” exactly when it is being voluntarily stabilized to maintain clear vision. We characterized retinal-image slip in monkeys immediately after microsaccades by analyzing postmovement ocular drifts. We observed enhanced ocular drifts by up to ∼28% relative to premicrosaccade levels, and for up to ∼50 ms after movement end. Moreover, we used a technique to trigger full-field image motion contingent on real-time microsaccade detection, and we used the initial ocular following response to this motion as a proxy for changes in early visual motion processing caused by microsaccades. When the full-field image motion started during microsaccades, ocular following was strongly suppressed, consistent with detrimental retinal effects of the movements. However, when the motion started after microsaccades, there was up to ∼73% increase in ocular following speed, suggesting an enhanced motion sensitivity. These results suggest that the interface between even the smallest possible saccades and “fixation” includes a period of faster than usual image slip, as well as an enhanced responsiveness to image motion, and that both of these phenomena need to be considered when interpreting the pervasive neural and perceptual modulations frequently observed around the time of microsaccades.

Contains fulltext : 126208.pdf (Publisher’s version ) (Open Access) Registration of ego-motion is important to accurately navigate through space. Movements of the head and eye relative to space are registered through the vestibular system and optical flow, respectively. Here, we address three questions concerning the visual registration of self-rotation. (1) Eye-in-head movements provide a link between the motion signals received by sensors in the moving eye and sensors in the moving head. How are these signals combined into an ego-rotation percept? We combined optic flow of simulated forward and rotational motion of the eye with different levels of eye-in-head rotation for a stationary head. We dissociated simulated gaze rotation and head rotation by different levels of eye-in-head pursuit. We found that perceived rotation matches simulated head- not gaze-rotation. This rejects a model for perceived self-rotation that relies on the rotation of the gaze line. Rather, eye-in-head signals serve to transform the optic flow's rotation information, that specifies rotation of the scene relative to the eye, into a rotation relative to the head. This suggests that transformed visual self-rotation signals may combine with vestibular signals. (2) Do transformed visual self-rotation signals reflect the arrangement of the semi-circular canals (SCC)? Previously, we found sub-regions within MST and V6(+) that respond to the speed of the simulated head rotation. Here, we re-analyzed those Blood oxygenated level-dependent (BOLD) signals for the presence of a spatial dissociation related to the axes of visually simulated head rotation, such as have been found in sub-cortical regions of various animals. Contrary, we found a rather uniform BOLD response to simulated rotation along the three SCC axes. (3) We investigated if subject's sensitivity to the direction of the head rotation axis shows SCC axes specifcity. We found that sensitivity to head rotation is rather uniformly distributed, suggesting that in human cortex, visuo-vestibular integration is not arranged into the SCC frame.

1. Neurons that are selectively sensitive to the direction of motion of elongated contours have been found in several cortical areas in many species. However, in the striate cortex of the cat and monkey, and the extrastriate posteromedial lateral suprasylvian visual area of the cat, such cells are generally component motion selective, signaling only the direction of movement orthogonal to the preferred orientation; a direction that is not necessarily the same as the motion of the entire pattern or texture of which the cell's preferred contour is part. The primate extrastriate middle temporal area is the only cortical region currently known to contain a substantial population of pattern-motion-selective cells that respond to the shared vector of motion of mixtures of contours. 2. From analyzing published data on the connectivity of the cat's cortex, we predicted that the anterior ectosylvian visual area (AEV), situated within the anterior ectosylvian sulcus, might be a higher-order motion processing area and thus likely to contain pattern-motion-selective neurons. This paper presents the results of a study on neuronal responses in AEV. 3. Ninety percent of AEV cells that responded strongly to drifting grating and/or plaid stimuli were directionally selective (directionality index > 0.5). For this group, the mean directionality index was 0.75. Moreover, 55% of these cells were unequivocally classified as pattern motion selective and only one neuron was classified as definitely component motion selective. Thus high-level pattern motion coding occurs in the cat extrastriate cortex and is not limited to the primate middle temporal area. 4. AEV contains a heterogeneous population of directionally selective cells. There was no clear relation between the degree of directional selectivity for plaids or gratings and the degree of selectivity for pattern motion or component motion. Nevertheless, 28% of the highly responsive cells were both more strongly modulated by plaids than gratings and more pattern motion selective than component motion selective. Such cells could correspond to a population of "selection units" signaling the salience of local motion information. 5. AEV lacks global retinotopic order but the preferred direction of motion of neurons (rather than axis of motion, as in the middle temporal area and the posteromedial lateral suprasylvian visual area) is mapped systematically across the cortex. Our data are compatible with AEV being a nonretinotopic, feature-mapped area in which cells representing similar parts of "motion space" are brought together on the cortical sheet.

The ability of infants to discriminate between opposite directions of motion was assessed using forced-choice preferential looking between a random-dot pattern which was segregated into regions which moved in opposite directions, and a uniform pattern in which all the dots moved in the same direction. The first experiment measured velocity thresholds ( νmin and νmax) for direction discrimination; between 10 and 13 weeks νmin decreased, while at the same time νmax increased. The second experiment explored possible implications of this expanding velocity range for direction discrimination by younger infants. One-month-olds showed no evidence for direction discrimination at any of a number of test velocities in the range 1–43 deg/sec. The 1-month-olds were also tested with two additional conditions: they could discriminate between moving and static patterns at velocities of 10 deg/sec or above, and they could also discriminate between coherent and incoherent motion at velocities of 21 deg/sec or below. Neither of these discriminations depends on sensitivity to the direction of the coherent motion. The results suggest that 1-month-olds may not be sensitive to the direction of visual motion.

A model of local image encoding is described which explicitly incorporates quantitative data about the number density, bandwidth and receptive field organisation of neurons involved in motion detection. The model solves the problem of extracting local velocity on the basis of inputs tuned to spatiotemporal frequency and sensitive to contrast. The spatiotemporally tuned, opponent motion filters are followed by a compressive non-linearity and comprise a first stage. The inter-stage signals are interpreted as those from single neurons and the second stage is modelled as a neural-network layer. The second stage uses semilinear units and models the effect of lateral, on-centre off-surround, intra-layer connections. Characterisation of the first stage leads to a clarification of the concept of the psychophysical 'channel' and its relation to physiological data. The quantitative parametrisation of the model allows the simulation of several psychophysical phenomena which are reported in a companion paper.

Introduction: Altered visual processing has been observed in adult migraineurs. But because visual processing has not been studied in paediatric cases, it is not known whether such visual system alterations are already present in early development. We therefore used a dynamic visual task to investigate motion detection threshold in paediatric migraine. Methods: Fourteen migraineurs and 21 controls participated in the study (age range: 8–17 years). The minimal percentage of coherently moving dot stimuli at which subjects were still able to detect coherent movement (absolute threshold) was determined using a random dot kinematogram paradigm. Results: Motion coherence detection threshold was higher in migraineurs ( p Conclusions: Children with migraine exhibit a delayed development of visual motion processing. This might be a useful supplementary biomarker in paediatric migraine.

We have used optical imaging based on intrinsic signals to explore the functional architecture of owl monkey area MT, a cortical region thought to be involved primarily in visual motion processing. As predicted by previous single-unit reports, we found cortical maps specific for the direction of moving visual stimuli. However, these direction maps were not distributed uniformly across all of area MT. Within the direction-specific regions, the activation produced by stimuli moving in opposite directions overlapped significantly. We also found that stimuli of differing shapes, moving in the same direction, activated different cortical regions within area MT, indicating that direction of motion is not the only parameter according to which area MT of owl monkey is organized. Indeed, we found clear evidence for a robust organization for orientation in area MT. Across all of MT, orientation preference changes smoothly, except at isolated line- or point-shaped discontinuities. Generally, paired regions of opposing direction preference were encompassed within a single orientation domain. The degree of segregation in the orientation maps was 3-5 times that found in direction maps. These results suggest that area MT, like V1 and V2, has a rich and multidimensional functional organization, and that orientation, a shape variable, is one of these dimensions.

Agency plays an important role in self-recognition from motion. Here, we investigated whether our own movements benefit from preferential processing even when the task is unrelated to self-recognition, and does not involve agency judgments. Participants searched for a moving target defined by its known shape among moving distractors, while continuously moving the computer mouse with one hand. They thereby controlled the motion of one item, which was randomly either the target or any of the distractors, while the other items followed pre-recorded motion pathways. Performance was more accurate and less prone to degradation as set size increased when the target was the self-controlled item. An additional experiment confirmed that participant-controlled motion was not physically more salient than motion recorded offline. We found no evidence that self-controlled items captured attention. Taken together, these results suggest that visual events are perceived more accurately when they are the consequences of our actions, even when self-motion is task irrelevant.

We present a model for recovering the direction of heading of an observer who is moving relative to a scene that may contain self-moving objects. The model builds upon an algorithm proposed by Rieger and Lawton, based on earlier work by Longuet-Higgins and Prazdny. The algorithm uses velocity differences computed in regions of high depth variation to locate the focus of expansion, which indicates the observer's heading direction. We relate the behavior of the model to psychophysical observations regarding the ability of human observers to judge heading direction, and show how the model copes with self-moving objects in the environment.

To interact with our dynamic environment, the brain merges motion information from auditory and visual senses. However, not only “natural” auditory MOTION, but also “metaphoric” de/ascending PITCH and SPEECH (e.g., “left/right”), influence the visual motion percept. Here, we systematically investigate whether these three classes of direction signals influence visual motion perception through shared or distinct neural mechanisms. In a visual-selective attention paradigm, subjects discriminated the direction of visual motion at several levels of reliability, with an irrelevant auditory stimulus being congruent, absent, or incongruent. Although the natural, metaphoric, and linguistic auditory signals were equally long and adjusted to induce a comparable directional bias on the motion percept, they influenced visual motion processing at different levels of the cortical hierarchy. A significant audiovisual interaction was revealed for MOTION in left human motion complex (hMT+/V5+) and for SPEECH in right intraparietal sulcus. In fact, the audiovisual interaction gradually decreased in left hMT+/V5+ for MOTION > PITCH > SPEECH and in right intraparietal sulcus for SPEECH > PITCH > MOTION. In conclusion, natural motion signals are integrated in audiovisual motion areas, whereas the influence of culturally learnt signals emerges primarily in higher-level convergence regions.

This chapter addresses three different aspects related to visual motion processing by means of second-order motion stimuli. The first question discussed is whether there is a need for separate mechanisms underlying the execution of action and perception elicited by these motion stimuli. Second, light is shed on the neuronal responses to second-order motion stimuli recorded from the middle temporal (MT) and medial superior temporal (MST) areas. While neuronal responses are recorded, the monkeys performed a psychophysical task and reported the direction of stimulus movements. Third and final, the perception of biological motion in man and monkeys and its relationship to second-order motion is addressed.

Neuronal adaptation has been studied extensively in visual motion-sensitive neurons of the fly Calliphora vicina, a model system in which the computational principles of visual motion processing are amenable on a single-cell level. Evidenced by several recent papers, the original idea had to be dismissed that motion adaptation adjusts velocity coding to the current stimulus range by a simple parameter change in the motion detection scheme. In contrast, linear encoding of velocity modulations and total information rates might even go down in the course of adaptation. Thus it seems that rather than improving absolute velocity encoding motion adaptation might bring forward an efficient extraction of those features in the visual input signal that are most relevant for visually guided course control and obstacle avoidance.

Smooth pursuit eye movements enable us to focus our eyes on moving objects by utilizing well-established mechanisms of visual motion processing, sensorimotor transformation and cognition. Novel smooth pursuit tasks and quantitative measurement techniques can help unravel the different smooth pursuit components and complex neural systems involved in its control. The maintenance of smooth pursuit is driven by a combination of the prediction of target velocity and visual feedback about performance quality, thus a combination of retinal and extraretinal information that has to be integrated in various networks. Different models of smooth pursuit with specific in- and output parameters have been developed for a better understanding of the underlying neurophysiological mechanisms and to make quantitative predictions that can be tested in experiments. Functional brain imaging and neurophysiological studies have defined motion sensitive visual area V5, frontal (FEF) and supplementary (SEF) eye fields as core cortical smooth pursuit regions. In addition, a dense neural network is involved in the adjustment of an optimal smooth pursuit response by integrating also extraretinal information. These networks facilitate interaction of the smooth pursuit system with multiple other visual and non-visual sensorimotor systems on the cortical and subcortical level. Future studies with fMRI advanced techniques (e.g., event-related fMRI) promise to provide an insight into how smooth pursuit eye movements are linked to specific brain activation. Applying this approach to neurological and also mental illness can reveal distinct disturbances within neural networks being present in these disorders and also the impact of medication on this circuitry.

Humans demonstrate an amazing ability for intercepting and catching moving targets, most noticeably in fast-speed ball games. However, the few studies exploring the neural bases of interception in humans and the classical studies on visual motion processing and visuomotor interactions have reported rather long latencies of cortical activations that cannot explain the performances observed in most natural interceptive actions. The aim of our experiment was twofold: (1) describe the spatio-temporal unfolding of cortical activations involved in catching a moving target and (2) provide evidence that fast cortical responses can be elicited by a visuomotor task with high temporal constraints and decide if these responses are task or stimulus dependent. Neuromagnetic brain activity was recorded with whole-head coverage while subjects were asked to catch a free-falling ball or simply pay attention to the ball trajectory. A fast, likely stimulus-dependent, propagation of neural activity was observed along the dorsal visual pathway in both tasks. Evaluation of latencies of activations in the main cortical regions involved in the tasks revealed that this entire network of regions was activated within 40 msec. Moreover, comparison of experimental conditions revealed similar patterns of activation except in contralateral sensorimotor regions where common and catch-specific activations were differentiated.

Motion visual evoked potentials (motion VEPs) have been used since the late 1960s to investigate the properties of human visual motion processing, and continue to be a popular tool with a possible future in clinical diagnosis. This review first provides a synopsis of the characteristics of motion VEPs and then summarizes important methodological aspects. A subsequent overview illustrates how motion VEPs have been applied to study basic functions of human motion processing and shows perspectives for their use as a diagnostic tool.

The correlation model of motion detection has been used to describe visual motion processing in the pretectum and accessory optic system (AOS). One feature of correlation detectors is that they are tuned to a particular temporal frequency (TF) independent of the spatial frequency (SF) but not to a particular stimulus speed (speed = TF/SF). Previous work has suggested that a subset of neurons in the AOS and pretectum of pigeons show apparent speed tuning. However, this study used relatively liberal between-groups statistics to assess speed tuning. From studies of the motion-sensitive neurons in primate cortex, a rigorous within-groups test of speed tuning has been offered. A meta-analysis of the spatiotemporal tuning of units in the AOS and pretectum of pigeons using this within-groups analysis of speed tuning has been performed. We conclude that speed tuning in the AOS and pretectum is rarer than previously estimated, and there is remarkable diversity in the impact of SF on tuning for speed. In total, 18.6% of the units showed significant speed tuning whereas 39.8% showed significant SF/TF independence. However, many cells (41.5%) fell along a continuum between speed tuning and SF/TF independence. This diversity has also been noted in primate cortex and may reflect a general property of motion-sensitive systems.

We have previously shown that some visual motion areas can be specifically recruited by auditory motion processing in blindfolded sighted subjects [Poirier, C., Collignon, O., De Volder, A.G., Renier, L., Vanlierde, A., Tranduy, D., Scheiber, C., 2005. Specific activation of V5 brain area by auditory motion processing: an fMRI study. Brain Res. Cogn. Brain Res. 25, 650-658]. The present fMRI study investigated whether auditory motion processing may recruit the same brain areas in early blind subjects. The task consisted of simultaneously determining both the nature of a sound stimulus (pure tone or complex sound) and the presence or absence of its movement. When a movement was present, blind subjects had to identify its direction. Auditory motion processing, as compared to static sound processing, activated the brain network of auditory and visual motion processing classically observed in sighted subjects. Accordingly, brain areas previously considered as specific to visual motion processing could be specifically recruited in blind people by motion stimuli presented through the auditory modality. This indicates that the occipital cortex of blind people could be organized in a modular way, as in sighted people. The similarity of these results with those we previously observed in sighted subjects suggests that occipital recruitment in blind people could be mediated by the same anatomical connections as in sighted subjects.

In the last decade, much has been learned about the influence of attention on visual motion processing. Many studies have shown that directing spatial attention to a motion stimulus or attending to a particular feature of a motion stimulus significantly alters the processing of that stimulus. In this review, we begin by discussing results from human psychophysical experiments investigating the effects of attention on motion perception. This is followed by a summary of single-unit neurophysiological experiments in monkeys and functional magnetic resonance imaging (fMRI) studies in humans investigating the effects of attention on neural motion responses. In the last section, we discuss the results of experiments that have attempted to establish links between psychophysical and neural effects of attention.

Behavioral experiments suggest that insects make use of the apparent image speed on their compound eyes to navigate through obstacles, control flight speed, land smoothly, and measure the distance they have flown. However, the vast majority of electrophysiological recordings from motion-sensitive insect neurons show responses which are tuned in spatial and temporal frequency and are thus unable to unambiguously represent image speed. We suggest that this contradiction may be resolved at an early stage of visual motion processing using nondirectional motion sensors that respond proportionally to image speed until their peak response. We describe and characterize a computational model of these sensors and propose a model by which a spatial collation of such sensors could be used to generate speed-dependent behavior.

An internal sense of eye position is necessary to maintain the constancy of the visual world in spite of movements of the eyes. Neuroimaging studies have localized human homologs of monkey visual motion processing areas in MT/MST and also in the collateral sulcus (V4), an area that codes features within objects. We show that these two areas have a baseline fMRI signal that is modulated by eye position and that the preferred direction of the eye position signal is different in the two areas; increasing for ipsiversive eye positions in MT/MST and increasing for contraversive eye positions within the collateral sulcus. This baseline modulation is a true eye position signal; one that is present in the absence of visual motion stimuli. The difference in the preferred direction of the eye position signal may reflect the different transformations in these two areas; a transformation from a retinotopic (eye-centered) to an egocentric coordinate frame necessary for guiding action and to an object-centered frame for object recognition.

Visual motion processing enables moving fruit flies to stabilize their course and altitude and to approach selected objects. Earlier attempts to identify task-specific pathways between two photoreceptor systems (peripheral retinula cells 1–6, and central retinula cells 7+8) and three steering parameters (wingstroke asymmetry, abdomen deflection, hindleg deflection) attributed course control and object fixation to peripheral retinula cells 1–6-mediated simultaneous reactions of these parameters. The present investigation includes first results from fixed flying or freely walking ninaE 17 mutants which cannot synthesize the peripheral retinula cells 1–6 photoreceptor-specific opsin. Retention of about 12% of the normal course control and about 58% of the object fixation in these flies suggests partial input sharing for both responses and, possibly, a specialization for large-field (peripheral retinula cells 1–6) and small-field (central retinula cells 7+8) motion. Such signals must be combined to perceive relative motion between an object and its background. The combining links found in larger species might explain a previously neglected interdependence of course control and object fixation in Drosophila. – Output decomposition revealed an unexpected orchestration of steering. Wingstroke asymmetry and abdomen deflection do not contribute in fixed proportions to the yaw torque of the flight system. Different steering modes seem to be selected according to their actual efficiency under closed-loop conditions and to the degree of intended turning. An easy experimental access to abdominal steering is introduced.

Current thinking on the type of inputs that drive ‘visual’ areas might need to be reassessed in the light of findings presented at the June meeting of the Organisation for Human Brain Mapping in Brighton. Two studies, one using PET and the other using fMRI, showed that that the visual cortical area, V5, responds to a moving tactile stimulus as well as to visual motion. These findings shed light on how the brain combines information from different senses. Francis McGlone, who collaborated on both studies, explained to TICS, ‘we sense the motion of objects through sight, sound and touch and like many perceptual operations, sensations from two or more different modalities can combine to produce a unified percept. There are various possible ways in which the brain might do this. Our findings provide evidence for the existence of a neuroanatomical convergence of both tactile and visual processing of motion in the human MT/V5 complex, an area with known specialization for visual motion processing. To the best of our knowledge, these data provide among the first evidence that MT participates in tactile processing.’ HJB

We found that the motion aftereffect measured using a directionally ambiguous counterphase grating (flicker MAE) can be stronger when it is measured for the non-adapted eye than when measured for the adapted eye. The monocularly viewed adaptation stimulus was the movement of a missing-fundamental grating (2 f +3 f motion), for which the movement of the higher-order spatial structure was dominantly perceived, while the first-order structure was physically moving in the opposite direction. For observers who perceived the MAE consistently in the direction opposite to the movement of the higher-order structures, the MAE was larger for the non-adapted eye than for the adapted eye. This finding of ‘over-100% transfer’ invalidates the standard view that the IOT is a direct measure of the binocularity of the adapted neurones. In addition, the finding provides convincing support for the hypothesis that the flicker MAE reflects adaptation at multiple processing stages

In insects, as in vertebrates, neuroanatomical, electrophysiological, and modelling studies have provided insights regarding identities and connections among neurones that accomplish elementary motion detection. These studies include intracellular recordings from identified wide-field neurones that collate local information about motion, intracellular recordings from identified, mainly non-spiking small-field neurones that are candidates for a cardinal role in motion detection, and comparative anatomical studies of retinotopic neurones that are evolutionarily conserved across taxa. Nevertheless, many important features of motion processing in insects have yet to be revealed. This review concentrates on two questions: what are the identities and relationships among neurones that participate in elementary motion detection? And, are there distinct functional classes of elementary motion detectors (EMDs) in insects?

The smooth pursuit system is traditionally employed using a single small target moving on a homogeneous background. It still is not fully understood, however, how accurate tracking is sustained in the presence of a structured background, which will activate global motion processing in the opposite direction as a consequence of the ongoing eye movement. To further study this interaction, we used brief shifts of a textured background injected at various times during the initiation of smooth pursuit. While shifts opposite to the target direction did not alter smooth pursuit performance, those in the same direction resulted in a marked transient perturbation of the pursuit. These results suggest a simple yet limited mechanism that adjusts the sensitivity of global motion processing.

Table 1Colocalization of Functional Neuroimaging Studies Investigating Differences between Dyslexics and Controls During Phonological and Visual Motion Processing TasksRhyme JudgmentVisual MotionAuthorRumsey et al.Rumsey et al.Rumsey et al.Paulesu et al.Shaywitz et al.Eden et al.Demb et al.(1992)(1997)(1996)(1996)(1998)*(1996)*(1997)*Response typeDecision makingPronunciationDecision makingDecision makingDecision makingNoneNone(button press)(button press)(button press)(button press)#STMRegion (Brodmann area)MTV/V5(19/37) L+50 −70 +05 C--- CR+52 −75 +08 C--- CInferior parietalSupramarginal(39/40) L--- C−28 −32 +44 C−44 −40 +28 C−46 −44 +24 #CR+52 −22 +28 C+40 −62 +28 C+/−47 +/−45 +/−33 CTemporalSuperior temporal(42/22) L−52 −30 +12 C−44 −22 +04 CR+44 −20 −04 C+/−53 +/−43 +/−11 CMedial temporal(21/37) L--- C−54 −22 −04 C−50 −56 +08 CR+46 −58 −08 CInferior temporal/Fusiform L−42 −28 −16 C−48 −40 −16 CR--- C+50 −34 −20 C+48 −30 −20 COccipitalStriate/extrastriate(17/18) L−10 −92 00 D−24 −84 −04 D+/−08 +/−89 +/−03 CR+/−36 +/−80 +/−05 CFunctional brain imaging studies employing PET or fMRI (*) that have identified differences between dyslexics and controls in the posterior areas of the brain during phonological processing or visual motion processing. “C” and “D” denote which of the two groups (controls or dyslexics, respectively) showed greater activation. Talairach coordinates correspond to distance in millimeters from the anterior commissure (+ corresponds to right hemisphere; − corresponds to left hemisphere). Phonological processing studies represent group data and visual motion studies represent single subject data. STM, short-term memory task.

The direction-reversal visual evoked potential (DR-VEP) latency is a key measure of the development of motion processing in infancy. However, the latency of this response has not been previously investigated. For other stimuli, both the latency of an initial peak and a latency measure calculated from steady-state phase as a function of frequency have been shown to be important and distinctive indicators of development. The latter measure is hypothesized to reflect the time course of cortical processing beyond the initial response that generates the first positive peak. DR-VEP was tested in 61 adults at 1-16 reversals per second (r/s) and 76 infants (age 7.7-79.0 weeks) at 2-8 r/s. In addition to measuring the transient peak latency at 1-3 r/s, latencies from the gradient of phase against reversal rates were also calculated from steady-state recordings at 1-16 r/s. For both adults and infants, peak latencies were similar for 1-3 r/s, while the calculated latency was substantially longer. Thirty-nine percent of adults and 17% of infants showed additional early transient peaks. We suggest that this early peak may reflect activation of extrastriate areas by motion, by a route that bypasses V1. While both transient latencies were similar to adult values around the onset of DR responses at 10 weeks of age, the latency calculated from phase values did not asymptote to the adult value of 207 ms until around 30 weeks. The overall time course of the response to direction reversal is prolonged compared with the transmission delay that generates the initial transient peak, presumably reflecting feed-forward, lateral, and recurrent connections that refine and elaborate the directional response of cortical neurons. While the peak latencies stay relatively unchanged throughout development, the dynamics of further motion processing are not mature until after 8 months of age. These measures may prove important indicators of motion development in future clinical evaluations.

Motion is perhaps the most fundamental visual dimension. It provides one of the richest and least ambiguous sources of information about the contents and layout of the environment, and about the observer's own movement within it. Hence it is not surprising that, unlike other visual dimensions such as colour and stereopsis, motion sensitivity is apparently present in all visual systems, from the most primitive to the most advanced. From an evolutionary point of view, detection of relative motion is the primary method of segmenting the visual scene, and that object vision emerges in higher animals as an elaboration of this basic mechanism. This suggests that motion might play a fundamental role in the development of vision, and that motion sensitivity might be one of the first visual functions to appear. Full use of motion information requires sensitivity to speed and direction, and is it generally thought that the first stage of motion analysis consists of more-or-less local estimates of these basic quantities by directionally selective mechanisms. These low-level mechanisms provide the foundation for more global perceptual processes, and insight into their development provides an important first step towards a full understanding of the development of visual motion processing.

Attentive Visual Motion Processing: Computations in the Log-Polar Plane. Attentive vision is characterized by selective sensing in space and time as well as selective processing with respect to a specific task. Selection in space involves the splitting of the visual field in a high resolution area—the fovea—and a space-variant resolution area—the periphery. Both in neurobiology and in robot vision, models of the resolution decrease towards the image boundaries have been established. The most convincing model is the theory of log-polar mapping where very high data compression rates are achieved. In combination with the complexity reduction we believe that the log-polar mapping has further computational advantages which we elaborate in this study. Based on the optical flow we study the computation of 3D motion and structure globally and locally. We present a global method to compute the Focus of Expansion in the case of pure translation. By fixating on an object we show how to estimate ego motion in the presence of translation and rotation of the observer from the flow in the log-polar periphery. Then, we turn to local differential computations and we establish both approximate and exact expressions for the time to collision.

We have addressed the question of whether adaptively modifying the oculomotor response to a visual pursuit stimulus has an influence on a related manual tracking response. Subjects used their unseen right hand to track targets moving at constant velocities while visually fixating a stationary LED. Manual tracking performance was compared before and after a 20 min period during which smooth pursuit eye movements alone were adaptively enhanced by adding 50% of the instantaneous eye position signal to target position. Compared with the preadaptation trials, hand gain was markedly increased during the postadaptation period. These results imply that the adaptation occurred at a level common to both motor systems, probably in CNS structures concerned with visual motion processing.