Evidence for a subtractive component in motion adaptation

Information-optimal local features automatically attract covert and overt attention

In fast vision, local spatial properties of the visual scene can automatically capture the observer's attention. We used specific local features, predicted by a constrained maximum-entropy model to be optimal information-carriers, as candidate "salient features''. Previous studies showed that participants choose these optimal features as "more salient" if explicitly asked. Here, we investigated the implicit saliency of these optimal features in two attentional tasks. In a covert-attention experiment, we measured the luminance-contrast threshold for discriminating the orientation of a peripheral gabor. In a gaze-orienting experiment, we analyzed latency and direction of saccades towards a peripheral target. In both tasks, two brief peripheral cues, differing in saliency according to the model, preceded the target, presented on the same (valid trials) or the opposite side (invalid trials) of the optimal cue. Results showed reduced contrast thresholds, saccadic latencies, and direction errors in valid trials, and the opposite in invalid trials, compared to baseline values obtained with equally salient cues. Also, optimal features triggered more anticipatory saccades. Similar effects emerged in a luminance-control condition. Overall, in fast vision, optimal features automatically attract covert and overt attention, suggesting that saliency is determined by information maximization criteria coupled with computational limitations.

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.

Color illusions also deceive CNNs for low-level vision tasks: Analysis and implications

The study of visual illusions has proven to be a very useful approach in vision science. In this work we start by showing that, while convolutional neural networks (CNNs) trained for low-level visual tasks in natural images may be deceived by brightness and color illusions, some network illusions can be inconsistent with the perception of humans. Next, we analyze where these similarities and differences may come from. On one hand, the proposed linear eigenanalysis explains the overall similarities: in simple CNNs trained for tasks like denoising or deblurring, the linear version of the network has center-surround receptive fields, and global transfer functions are very similar to the human achromatic and chromatic contrast sensitivity functions in human-like opponent color spaces. These similarities are consistent with the long-standing hypothesis that considers low-level visual illusions as a by-product of the optimization to natural environments. Specifically, here human-like features emerge from error minimization. On the other hand, the observed differences must be due to the behavior of the human visual system not explained by the linear approximation. However, our study also shows that more 'flexible' network architectures, with more layers and a higher degree of nonlinearity, may actually have a worse capability of reproducing visual illusions. This implies, in line with other works in the vision science literature, a word of caution on using CNNs to study human vision: on top of the intrinsic limitations of the L + NL formulation of artificial networks to model vision, the nonlinear behavior of flexible architectures may easily be markedly different from that of the visual system.

Low-level mediation of directionally specific motion aftereffects: Motion perception is not necessary

Previous psychophysical experiments with normal human observers have shown that adaptation to a moving dot stream causes directionally specific repulsion in the perceived angle of a subsequently viewed moving probe. In this study, we used a two-alternative forced choice task with roving pedestals to determine the conditions that are necessary and sufficient for producing directionally specific repulsion with compound adaptors, each of which contains two oppositely moving, differently colored component streams. Experiment 1 provided a demonstration of repulsion between single-component adaptors and probes moving at approximately 90° or 270°. In Experiment 2, oppositely moving dots in the adaptor were paired to preclude the appearance of motion. Nonetheless, repulsion remained strong when the angle between each probe stream and one component was approximately 30°. In Experiment 3, adapting dot pairs were kept stationary during their limited lifetimes. Their orientation content alone proved insufficient for producing repulsion. In Experiments 4–6, the angle between the probe and both adapting components was approximately 90° or 270°. Directional repulsion was found when observers were asked to visually track one of the adapting components (Exp. 6), but not when they were asked to attentionally track it (Exp. 5), nor while they passively viewed the adaptor (Exp. 4). Our results are consistent with a low-level mechanism for motion adaptation. This mechanism is not selective for stimulus color and is not susceptible to attentional modulation. The most likely cortical locus of adaptation is area V1.

A bias-minimising measure of the influence of head orientation on perceived gaze direction

The orientation of the head is an important cue for gaze direction, and its role has been explained in a dual route model. The model incorporates both an attractive and a repulsive effect of head orientation, which act to support accurate gaze perception across large changes in natural stimuli. However, in all previous studies of which we are aware, measurements of the influence of head orientation on perceived gaze direction were obtained using a single-interval methodology, which may have been affected by response bias. Here we compare the single-interval methodology with a two-interval (bias-minimising) design. We find that although measures obtained using the two-interval design showed a stronger attractive effect of head orientation than previous studies, the influence of head orientation on perceived gaze direction still represents a genuine perceptual effect. Measurements obtained using the two-interval design were also shown to be more stable across sessions one week apart. These findings suggest the two-interval design should be used in future experiments, especially if comparing groups who may systematically differ in their biases, such as patients with schizophrenia or autism.

Sustained attention is not necessary for velocity adaptation

Prolonged adaptation to a stimulus, such as a drifting grating, lowers sensitivity for detecting similar stimuli, and changes their appearance, for example, making gratings of the same orientation appear of lower contrast and move more slowly. It has been suggested that adaptation is increased by sustained attention to the adapting stimulus and is decreased by distracting attention with a competing task. This paper describes a novel 2AFC (spatial) measure of adaptation in which adaptation and bias are carefully distinguished by the random interleaving of different test conditions. The experiment revealed significant adaptation of perceived velocity, but no effect of attentional distraction.

What is the primary cause of individual differences in contrast sensitivity?

One of the primary objectives of early visual processing is the detection of luminance variations, often termed image contrast. Normal observers can differ in this ability by at least a factor of 4, yet this variation is typically overlooked, and has never been convincingly explained. This study uses two techniques to investigate the main source of individual variations in contrast sensitivity. First, a noise masking experiment assessed whether differences were due to the observer's internal noise, or the efficiency with which they extracted information from the stimulus. Second, contrast discrimination functions from 18 previous studies were compared (pairwise, within studies) using a computational model to determine whether differences were due to internal noise or the low level gain properties of contrast transduction. Taken together, the evidence points to differences in contrast gain as being responsible for the majority of individual variation across the normal population. This result is compared with related findings in attention and amblyopia.

Wohlgemuth was right: distracting attention from the adapting stimulus does not decrease the motion after-effect

We determined whether distracting the observer's attention from an adapting stimulus could decrease the motion after-effect. Unlike previous studies we used a relatively bias-free 2AFC procedure to measure the strength of adaptation. The strength of motion adaptation was measured by the effects of a moving grating on the contrast discrimination (T vs. C) function for gratings moving in the same or opposite direction. As in previous reports, the effect of adaptation was to move the T vs. C function upwards and rightwards, consistent with an increase in the C50 (semi-saturation) response in the transduction function of the neural mechanism underlying the discrimination. On the other hand, manipulating the attentional load of a distracting task during adaptation had no consistent effect on contrast discrimination, including the absolute detection threshold. It is suggested that previous reported effects of attentional load on adaptation may have depended on response bias, rather than changes in sensitivity.