Vision Research

Intersaccadic times or eye fixation durations (EFD) are relatively stable at around 250ms, equivalent to 4 saccades by second. However, the mean and standard deviation are not sufficient to describe the frequency histogram distribution of EFD. The exgaussian has been proposed for fitting the EFD histograms. Present report tries to adjust a competition model (C model) between the saccadic and the fixation network to the EFD histograms. This model is at a rather conceptual level (computational level in Marrs classification). Both models were adjusted to EFD from an open database with data of 179473 eye fixations. The C model showed to be able, along with exgaussian model, to be compatible for explaining the EFD distributions. The two parameters of the C model can be ascribed to (i) a refractory period for new saccades modeled by a sigmoid equation (A parameter), while (ii) the ps parameter would be related to the continuous competition between the saccadic network related to the saliency map and the eye fixation network, and would be modeled through a geometric probability density function. The model suggests that competition between neural networks would be an organizational property of brain neural networks to facilitate the decision process for action and perception. In the visual scene scanning the C model dynamic justifies the early post-saccadic stability of the foveated image, and the subsequent exploration of a broad space in the observed image. Code to extract the data and to run the model is added at the supplementary material.

Motion estimation is an essential ability for sighted animals to survive in their natural environment. Many anatomical and electrophysiological studies on low visual levels have been based on the classic pioneering HRC (Hassenstein & Reichaedt Correlator) computational model. The accumulated experimental findings, which have given rise to a debate in the current computational models regarding the interaction between the On and Off pathways. The previous algorithms were challenged to correctly predict physiological experiment results and the two types of motion: a) Phi motion, also termed apparent motion. b) Reverse-phi motion that is perceived when the image contrast flips during the rapid succession. We have developed a computational model supported by simulations, which for the first time leads to correct predictions of the behavioral motions (phi and reverse-phi), while considering separated On and Off pathways and is also in agreement with the relevant electrophysiological findings. This has been achieved through the well-known neuronal response: the rebound response or "Off response". We suggest that the rebound response, which has not been taken into account in the previous models, is a key player in the motion mechanism, and its existence requires separation between the On and the Off pathways for correct motion interpretation. We furthermore suggest that the criterial reverse-phi effect is only an epiphenomenon of the rebound response for the visual system. The theoretical predictions are confirmed by a psychophysical experiment on human subjects. Our findings shed new light on the comprehensive role of the rebound response as a parsimonious spatiotemporal detector for motion and additional memory tasks, such as for stabilization and navigation.

How is curvature coded in the early human visual system? Humans are successful in recognizing objects and by extension, the shape representing the object, under varying scale conditions (Biederman & Cooper, 1992; Lindeberg, 2013). How do we neuro-physiologically code the invariance (or variance) in curvature and does the curvature coding change with scale? The circle-polygon illusion produces polygonal percepts during adaptation when a static dark outline circle is pulsed at 2 Hz alternating with a gradient luminance circle. We use the circle-polygon to study curvature processing with respect to size and scale. Both the radius and eccentricity of the stimulus were varied in a crossed design over 1-8 deg. Observers reported a circle or the polygon order and the strength of the percept. We test a lower level account that argues for curvature opponency between neurons against a higher level account that codes for whole shapes. This higher level account supports scale invariance, a property through which we recognize objects regardless of the objects size on the retina. We show the following: (1) Scale invariance is not obeyed during adaptation. The mean order of the perceived polygon increased with stimulus size and decreased with eccentricity. This also demonstrates that curvature coding occurs in the early visual system. (2) Linear regression analysis reveals that the cortical size of the stimulus is a better predictor of perceived polygon order. We quantify the relationship parametrically between cortical size and polygon order. Using integration and regression, we identify the region of the cortex, V1, where the shape, a regular ordered polygon, is being computationally constructed.

Visual perceptual learning (VPL) is defined as long-term improvement on a visual task as a result of visual experience. In many cases, the improvement is highly specific to the location where the target is presented, which refers to location specificity. In the current study, we investigated the effect of a geometrical relationship between the trained location and an untrained location on transfer of VPL. We found that significant transfer occurs either diagonally or along a line passing the fixation point. This indicates that whether location specificity or location transfer occurs at least partially depends on the geometrical relationship between trained location and an untrained location.

In previous studies with dichoptic center-ring-surround stimuli, we found that two properties of the ring element have a strong influence on the phenomenon of binocular luster. The strength of the lustrous impression in the central target patch varies with increasing ring width, with the direction of this variation (increasing or decreasing) depending on the rings luminance. In this study, we used stimuli in which the ring was split into segments with two different luminances that in uniform rings had opposite effects on perceived luster. The aim was to investigate how the lustrous impression is influenced by combining a weaker and a stronger contrast effect, in particular how they are spatially integrated by the visual system. In a psychophysical matching experiment, subjects had to assess the strength of the lustrous impression in a series of test stimuli with different ring widths, numbers of ring segments, and spatial proportions between the two ring parts. We found that the results of the experiment could neither be explained by a winner-takes-all integration (assuming that the lustrous response is completely determined by the stronger effect) nor by a balanced integration process (assuming equal weights for the two effects). Instead, both effects contribute to the overall lustrous response, with the stronger effect having a greater weight. Interestingly, the magnitude of this weight varied considerably between different groups of subjects. We found two main trends in the data, representing two different types of sensitivity to the phenomenon of binocular luster.

Visual illusions have long been studied because the illusory effect they induce is believed to tell us something important on how the visual system processes visual information. Here, we modified a classic visual illusion, the Delboeuf illusion, so that it resembled a type of stimulus commonly used in experiments investigating surround modulation. We then performed a small set of psychophysical experiments in order to determine if the classical Delboeuf illusion effect, i.e. a change in the perceived size of an object, could be observed in these altered stimuli. In four conditions, we created stimuli that either had a high or low frequency surround in addition to being presented with a proximal thin surround or a distal thick surround. We found a significant difference in perceived object size for all four conditions compared to control indicating the presence of an illusion, and we discuss these findings in relation to existing literature from electrophysiological animal studies.

Previous studies have demonstrated that bias, sensitivity and similarity between letters are causes of errors in letter identification. However, these factors and their relative contribution in letter identification have not been investigated extensively. Our previous model (noisy template model) was devised to calculate the effect of bias and sensitivity in letter identification task. In the current study, we used the method of constant stimuli to measure letter acuity for Sloan letters at an eccentricity of 7 deg from fixation (temporal visual field). Similar to our previous work, we devised an tested a variety of models to estimate the joint role of bias and sensitivity, but extended our model to also incorporate the similarity between letters. Modelling results showed that bias is the major factor in determining the pattern of total, correct and incorrect responses in letter identification. Furthermore, the joint effect of similarity and bias was found to be higher than the joint effect of either bias and sensitivity or similarity and sensitivity in shaping the pattern of overall responses in letter identification. Incorporating the similarity factor to the noisy template model improved our understanding of the simultaneous contribution of the bias, sensitivity and similarity between letters in the letter identification task.

AO_SCPLOWBSTRACTC_SCPLOWThe distribution of retinal ganglion cells in primate visual systems portrays a densely distributed central region, with an incrementally decreasing cell density as the angle of visual eccentricity increases. This results in a non-uniform sampling of the retinal image that resembles a wheelbarrow distortion. We propose that this sampling gives rise to several organizational properties of the primate visual system, including cortical magnification, linear relationship between eccentricity and receptive field sizes, eccentricity-dependent drop-off in spatial-frequency preference, and radial bias. We test this hypothesis by training a convolutional neural network to classify the orientation of sine gratings and Gabor stimuli, resampled according to retinal ganglion cell distributions. Our simulations show that introducing this sampling step gives rise to the aforementioned organizational principles in convolutional layers while only minimally affecting their classification performance. This lends credence to the notion that the retinal ganglion cell distribution is an important factor for the emergence of these organizational principles in visual systems.

Previous studies have demonstrated that density is an important perceptual aspect of textural appearance to which the visual system is highly attuned. Furthermore, it is known that density cues not only influence texture segmentation, but can enable segmentation by themselves, in the absence of other cues. A popular computational model of texture segmentation known as the "Filter-Rectify-Filter" (FRF) model predicts that density should be a second-order cue enabling segmentation. For a compound texture boundary defined by superimposing two single-micropattern density boundaries, a version of the FRF model in which different micropattern-specific channels are analyzed separately by different second-stage filters makes the prediction that segmentation thresholds should be identical in two cases: (1) Compound boundaries with an equal number of micropatterns on each side but different relative proportions of each variety (compound feature boundaries) and (2) Compound boundaries with different numbers of micropatterns on each side, but with each side having an identical number of each variety (compound density boundaries). We directly tested this prediction by comparing segmentation thresholds for second-order compound feature and density boundaries, comprised of two superimposed single-micropattern density boundaries comprised of complementary micropattern pairs differing either in orientation or contrast polarity. In both cases, we observed lower segmentation thresholds for compound density boundaries than compound feature boundaries, with identical results when the compound density boundaries were equated for RMS contrast. In a second experiment, we considered how two varieties of micropatterns summate for compound boundary segmentation. In the case where two single micro-pattern density boundaries are superimposed to form a compound density boundary, we find that the two channels combine via probability summation. By contrast, when they are superimposed to form a compound feature boundary, segmentation performance is worse than for either channel alone. From these findings, we conclude that density segmentation may rely on neural mechanisms different from those which underlie feature segmentation, consistent with recent findings suggesting that density comprises a separate psychophysical channel.

The estimation of spatial distances is one of the most important perceptual outputs of vision and can easily be deduced even with detached objects. However, how the visual system encodes distances between objects and object sizes is unclear. Hisakata, Nishida, and Johnston (2016) reported a new adaptation effect, in which the perceived distance between objects and the size of an object shrink after adaptation to a dense texture. They proposed that the internal representation of density plays a role in a spatial metric system that measures distance and size. According to the theory of magnitude (Walsh, 2003), the estimation of spatial extent (distance and size) shares common metrics with the estimation of temporal length and numerosity magnitudes and is processed at the same stage. Here, we show the existence of temporal enhancement in cross-adaptation between density and size perception. We used the staircase method to measure the temporal property. The test stimuli were two circles, and the adapting stimulus had a dotted texture. The adapting texture refreshed every 100 or 300 ms, or not at all (static), during the adaptation. The results showed that the aftereffects from a refreshing stimulus were larger than those under the static condition. On the other hand, density adaptation lacked such enhancement. This result indicates that repetitive presentation of an adapting texture enhanced the density-size cross-aftereffect. According to the theory of magnitude, a common mechanism encodes spatial and temporal magnitude estimation and the adaptation to temporal density explains this cross-adaptation enhancement.

An objects colour, brightness and pattern are all influenced by its surroundings, and a number of visual phenomena and "illusions" have been discovered that highlight these often dramatic effects. Explanations for these phenomena range from low-level neural mechanisms to high-level processes that incorporate contextual information or prior knowledge. Importantly, few of these phenomena can currently be accounted for when measuring an objects perceived colour. Here we ask to what extent colour appearance is predicted by a model based on the principle of coding efficiency. The model assumes that the image is encoded by noisy spatio-chromatic filters at one octave separations, which are either circularly symmetrical or oriented. Each spatial bands lower threshold is set by the contrast sensitivity function, and the dynamic range of the band is a fixed multiple of this threshold, above which the response saturates. Filter outputs are then reweighted to give equal power in each channel for natural images. We demonstrate that the model fits human behavioural performance in psychophysics experiments, and also primate retinal ganglion responses. Next we systematically test the models ability to qualitatively predict over 35 brightness and colour phenomena, with almost complete success. This implies that contrary to high-level processing explanations, much of colour appearance is potentially attributable to simple mechanisms evolved for efficient coding of natural images, and is a basis for modelling the vision of humans and other animals.

We perform microelectrode array recordings of neonatal chick retina explants and report stimulus-dependent response properties of different retinal ganglion cell (RGC) types to various luminance and contrast adaptation conditions. The isolated single units indicate wavelength-sensitive response properties for all the retinal ganglion cell types recorded from. Responses to different luminance and contrast conditions investigated as a function of wavelength indicates a combination of adaptation and sensitization features in the recorded population of RGCs. We further demonstrate the presence of complementary response properties in most of the RGCs to blue (450 nm) and green (530 nm) light input and infer that luminance, contrast and color information are encoded in a wide variety of metrics such as latency, response event duration and pairwise correlations.

Binocular vision fuses compatible inputs from the two eyes into a single percept, whereas incompatible inputs can produce rivalry, lustre, or diplopia. We measured neural responses to binocular stimuli with different phase relationships to test predictions from contemporary binocular combination models. Steady-State Visually Evoked Potentials (SSVEPs) were recorded from 15 observers in response to monocular and binocular stimulation at 3 Hz, using either On/Off or counterphase flicker with varied spatial and temporal phase relationships. On/Off flicker elicited responses at the fundamental frequency (3 Hz), and its integer harmonics, while counterphase flicker generated responses at the even integer harmonics (6Hz, 12Hz, 18Hz). Manipulating phase relationships modulated these response patterns, including a reduction in the fundamental amplitude for On/Off flicker. The data were modeled with a series of binocular combination algorithms, ranging in complexity from a simple linear sum to a two-stage binocular gain-control model with parallel monocular and binocular phase-selective channels. The model required parallel monocular channels to account for our data, whereas phase selectivity was not essential. Overall, the two-stage contrast gain-control model remains a powerful and flexible framework for describing binocular combinations across various experimental conditions and modalities.

Here we investigate how the extent of spatial attention affects center-surround interaction in visual motion processing. To do so, we measured motion direction discrimination thresholds in humans using drifting gratings and two attention conditions. Under the narrow attention condition, attention was limited to the central part of the visual stimulus, whereas under the wide attention condition, it was directed to both the center and surround of the stimulus. We found stronger surround suppression under the wide attention condition. The magnitude of the attention effect increased with the size of the surround when the stimulus had low contrast, but did not change when it had high contrast. Results also showed that attention had a weaker effect when the center and surround gratings drifted in opposite directions. Next, to establish a link between the behavioral results and the neuronal response characteristics, we performed computer simulations using the divisive normalization model. Our simulations showed that the model can successfully predict the observed behavioral results using parameters derived from the medial temporal (MT) area of the cortex. These findings reveal the critical role of spatial attention on surround suppression and establish a link between neuronal activity and behavior. Further, these results also suggest that the reduced surround suppression found in certain clinical disorders (e.g., schizophrenia and autism spectrum disorder) may be caused by abnormal attention mechanisms.

Does the human visual system sample shapes at discrete points? During adaptation, when the neurons are fatigued, one observes the underlying principles that were once less prominent than the fatigued features. Operating under deficit, these less prominent features expose the original contributions from the fatigued neurons that are now absent. An underlying lower-order neural process is thus, now revealed. In this paper, we conduct experiments using a modified version of the circle-polygon illusion to reveal the brains sampling pattern. The circle-polygon illusion produces polygonal percepts during adaptation when a static dark outline circle is pulsed at 2 Hz alternating with a gradient luminance circle. We define sampling as the edge length of the emergent polygon. We develop a reconstruction function that defines the edge length based on psychophysical responses. We perform two experiments. In the first experiment, we present circles of size [2,4,8,16] deg presented at eccentricity [0,1,2,4,8] deg in a cross design. In the second experiment, we modify the method of Sakurai (2014) and display arc lengths that are 1/8, 1/4, 3/8, 1/2, 5/8, 3/4, 7/8 and 1 (whole) of a circle, of size 4 and 8 deg, presented centrally. The observers report the edge length. We find that the stimulus size and presentation eccentricity, taken together, best explain the edge length reported by the users. The users, as a random effect, do not influence the mean of the edge length reported when considering the best model reported (size and eccentricity together). However, the users do influence edge length reported only when using mean eccentricity or eccentricity as the parameter influencing edge length. Arc lengths of a circle produce the same or similar edge lengths. The length of the curve does not play a significant role signifying that biological neurophysiology at an eccentricity controls the edge length formation. Using the influences on edge length, we define sampling as a sum of qualitative influences and a sampling function derived from Taylors polynomial using sampling values along the eccentricity grid. As we use the sampled values directly to reconstruct the function, we remove the need for recording directly from neurons and instead rely on behavioural responses to build the reconstruction function.

The complexity of human perceptual system has often been investigated through its atypical function; the illusion. Here, I introduce a new visual illusion induced by rotational motion binding, which leads to a gestalt perception of illusory object rhythmically popping out and fading away. In this illusion, observers reported non-existing rhythm out of rotating Gabor patches (e.g., local rotation) that also have orbital trajectory with opposite direction (e.g., global rotation), only under the particular combinations of parameters. This illusory rhythmicity was four times faster than the average of global/local rotational speed. Image reconstruction using the response-triggered average revealed the rhythmicity is explained by the circular alignment of array, demonstrating the effect of repeated contour integration and its perceptual consequences.

Currently, the human myopia epidemic is estimated to affect nearly 3 billion persons, yet experimental refractive error research is still hampered by the lack of a plausible theoretical mechanism explaining how the eye detects defocus and grows to minimise error (emmetropization). Applied lens defocus, either positive or negative, to animals including human, induces rapid changes in both refraction and axial length. Such changes have been linked to the rate of transfer of fluid from the vitreous chamber across the Retinal Pigment Epithelium (RPE). However, the theoretical basis of sensing the sign of defocus still eludes, as does the physiological operationalisation of this defocus signal. We propose that the signal for the sign of defocus is contained within the pattern of temporal modulation of light on the retina during the myriad saccadic eye movements performed every minute. This pattern is generated by a combination of the ocular point spread function for the defocused eye, narrow cone photoreceptor acceptance of light and the modification of photoreceptor directionality by the retinal shear that accompanies saccadic eye movements. Thus, under conditions of defocus, performing a saccade across a simple visual grating produces an out of focus dynamic stimulus pattern on the retina which is sawtooth-like, the profile being dependent on the sign of defocus. Positive lens defocus induces a fast-OFF/slow-ON sawtooth-like luminance modulation transfer function, while negative lens defocus results in a fast-ON/slow-OFF temporal pattern. Such patterns produce relative incremental or decremental changes in the trans-epithelial electrical potential and consequent changes in fluid absorption across the RPE. Thus, rearing with positive lens defocus is associated with an increase in trans-epithelial potential, increasing trans-epithelial absorption and decreasing vitreous chamber size, while rearing with a negative lens decreases the trans-epithelial electrical potential and decreases RPE fluid absorption, increasing eyeball size. In both cases, retinal images become more in-focus, and the refractive error tends to zero. The resultant is emmetropization, modifying eyeball size in response to applied defocus in a stable negative feedback fashion.

Visual perception is profoundly sensitive to context. Surround suppression is a well-known visual context effect in which the firing rate of a neuron is suppressed by stimulation of its extra-classical receptive field. The majority of contrast surround suppression studies exclusively use narrowband, sinusoidal grating stimuli; however, it is unclear whether the results produced by such artificial stimuli generalize to real-world, naturalistic visual experiences. To address this issue, we developed a contrast discrimination paradigm that includes both naturalistic broadband textures and narrowband grating textures. All textures were matched for first order image statistics and overall perceptual salience. We observed surround suppression across broadband textures (F(1,6)=19.01, p=.005); however, effect sizes were largest for narrowband, sinusoidal gratings (Cohens d=1.83). Among the three broadband texture types, we observed strongest suppression for the texture with a clear dominant orientation (stratified: Cohens d=1.29), while the textures with a more even distribution of orientation information produced weaker suppression (fibrous: Cohens d=0.63; braided: Cohens d=0.65). We also observed an effect of texture identity on the slope of psychometric functions (F(1.98,11.9)=7.29, p=0.01), primarily driven by smaller slopes for the texture with the most uniform distribution of orientations. Our results suggest that well-known contextual modulation effects only partially generalize to more ecologically valid stimuli.

BackgroundVisual mental imagery or "seeing with the minds eye" is an everyday phenomenon. Visual mental imagery and visual perception share common neural-networks. Hence deficits that affect the visual perception may also affect visual mental imagery. AimWe aimed to study the effect of refractive blur on the vividness of mental imagery. MethodsSubjects were recruited from volunteers and divided into two groups; individuals with refractive errors-Ametropes(AM), and individuals without refractive errors - Emmetropes(EM). After filling in the Verbalizer-Visualizer-Questionnaire (VVQ), the subjects were asked to perform a mental imagery task with and without refractive blur. The participants were asked to generate a mental image of a specific object initially with eyes closed, eyes open and then with refractive blur in random order, and then judge the vividness of the mental image on a Likert scale ranging from 1 (low vividness) to 5 (good vividness). The EM participants had to wear a + 2D spectacles to produce refractive blur. ResultsA total of 162 participants were recruited to the study. Of these 73 were EM and 89 were AM. Of the AM, 30 had additional astigmatism. The mean VVQ score was 64.9(11.2). The mean refractive error was 1.8(1.3)D. Following the mental imagery task, at baseline with eyes closed, 138 (85.5%)subjects had vivid mental imagery close to visual perception(Likert scale:5). With the opening of the eyes, the vividness dropped by at least 1 point in the Likert scale in 139(85.8%). With the introduction of refractive blur, 153(94.4%) subjects had a drop in the vividness of the image by at least 1 point and 22(13.6%) subjects by at least 2 points. ConclusionIntroduction of refractory blur results in the reduction of the vividness of mental imagery.

In this study, we characterize the spatial summation properties of targeted magnocellular, parvocellular, and koniocellular pathways within the central 20{degrees} of visual field using chromatic transformations in DKL color space. For the magnocellular and koniocellular conditions, critical areas of complete spatial summation were found for all eccentricities. For the parvocellular conditions, complete spatial summation was absent within the stimulus size ranges tested. We also describe an anatomically and physiologically motivated model of receptive field pooling using probability summation. Model simulations suggest that the critical area of summation can be explained by the dendritic field size of underlying retinal ganglion cells, corroborating our psychophysical data.