Tom Putzeys

A new perceptual bias reveals suboptimal population decoding of sensory responses.

Several studies have reported optimal population decoding of sensory responses in two-alternative visual discrimination tasks. Such decoding involves integrating noisy neural responses into a more reliable representation of the likelihood that the stimuli under consideration evoked the observed responses. Importantly, an ideal observer must be able to evaluate likelihood with high precision and only consider the likelihood of the two relevant stimuli involved in the discrimination task. We report a new perceptual bias suggesting that observers read out the likelihood representation with remarkably low precision when discriminating grating spatial frequencies. Using spectrally filtered noise, we induced an asymmetry in the likelihood function of spatial frequency. This manipulation mainly affects the likelihood of spatial frequencies that are irrelevant to the task at hand. Nevertheless, we find a significant shift in perceived grating frequency, indicating that observers evaluate likelihoods of a broad range of irrelevant frequencies and discard prior knowledge of stimulus alternatives when performing two-alternative discrimination.

Predictive Coding and the Neural Response to Predictable Stimuli

Many studies have characterized the brain as an efficient coding system ([Olshausen and Field, 1996][1]). A common claim in this “efficient coding” approach is that the brain has evolved to code sensory information in an efficient way by using information-processing strategies optimized to the

A neural population model for visual pattern detection.

Pattern detection is the bedrock of modern vision science. Nearly half a century ago, psychophysicists advocated a quantitative theoretical framework that connected visual pattern detection with its neurophysiological underpinnings. In this theory, neurons in primary visual cortex constitute linear and independent visual channels whose output is linked to choice behavior in detection tasks via simple read-out mechanisms. This model has proven remarkably successful in accounting for threshold vision. It is fundamentally at odds, however, with current knowledge about the neurophysiological underpinnings of pattern vision. In addition, the principles put forward in the model fail to generalize to suprathreshold vision or perceptual tasks other than detection. We propose an alternative theory of detection in which perceptual decisions develop from maximum-likelihood decoding of a neurophysiologically inspired model of population activity in primary visual cortex. We demonstrate that this theory explains a broad range of classic detection results. With a single set of parameters, our model can account for several summation, adaptation, and uncertainty effects, thereby offering a new theoretical interpretation for the vast psychophysical literature on pattern detection.

Spatial Arrangement in Texture Discrimination and Texture Segregation

We investigated the role of spatial arrangement of texture elements in three psychophysical experiments on texture discrimination and texture segregation. In our stimuli, oriented Gabor elements formed an iso-oriented and a randomly oriented texture region. We manipulated (1) the orientation similarity in the iso-oriented region by adding orientation jitter to the orientation of each Gabor; (2) the spatial arrangement of the Gabors: quasi-random or regular; and (3) the shape of the edge between the two texture regions: straight or curved. In Experiment 1, participants discriminated an iso-oriented stimulus from a stimulus with only randomly oriented elements. Experiment 2 required texture segregation to judge the shape of the texture edge. Experiment 3 replicated Experiment 2 with Gabors of a smaller spatial extent in a denser arrangement. We found comparable performance levels with regular and quasi-random Gabor positions in the discrimination task but not in the segregation tasks. We conclude that spatial arrangement plays a role in a texture segregation task requiring shape discrimination of the texture edge but not in a texture discrimination task in which it is sufficient to discriminate an iso-oriented region from a completely random region.

Both predictability and familiarity facilitate contour integration

Research has shown that contour detection is impaired in the visual periphery for snake-shaped Gabor contours but not for circular and elliptical contours. This discrepancy in findings could be due to differences in intrinsic shape properties, including shape closure and curvature variation, as well as to differences in stimulus predictability and familiarity. In a detection task using only circular contours, the target shape is both more familiar and more predictable to the observer compared with a detection task in which a different snake-shaped contour is presented on each trial. In this study, we investigated the effects of stimulus familiarity and predictability on contour integration by manipulating and disentangling the familiarity and predictability of snakelike stimuli. We manipulated stimulus familiarity by extensively training observers with one particular snake shape. Predictability was varied by alternating trial blocks with only a single target shape and trial blocks with multiple target shapes. Our results show that both predictability and familiarity facilitated contour integration, which constitutes novel behavioral evidence for the adaptivity of the contour integration mechanism in humans. If familiarity or predictability facilitated contour integration in the periphery specifically, this could explain the discrepant findings obtained with snake contours as compared with circles or ellipses. However, we found that their facilitatory effects did not differ between central and peripheral vision and thus cannot explain that particular discrepancy in the literature.

Apparent Motion Suppresses Responses in Early Visual Cortex: A Population Code Model

Two stimuli alternately presented at different locations can evoke a percept of a stimulus continuously moving between the two locations. The neural mechanism underlying this apparent motion (AM) is thought to be increased activation of primary visual cortex (V1) neurons tuned to locations along the AM path, although evidence remains inconclusive. AM masking, which refers to the reduced detectability of stimuli along the AM path, has been taken as evidence for AM-related V1 activation. AM-induced neural responses are thought to interfere with responses to physical stimuli along the path and as such impair the perception of these stimuli. However, AM masking can also be explained by predictive coding models, predicting that responses to stimuli presented on the AM path are suppressed when they match the spatio-temporal prediction of a stimulus moving along the path. In the present study, we find that AM has a distinct effect on the detection of target gratings, limiting the maximum performance at high contrast levels. This masking is strongest when the target orientation is identical to the orientation of the inducers. We developed a V1-like population code model of early visual processing, based on a standard contrast normalization model. We find that AM-related activation in early visual cortex is too small to either cause masking or to be perceived as motion. Our model instead predicts strong suppression of early sensory responses during AM, consistent with the theoretical framework of predictive coding.

Region-based texture segregation and orientation-similarity grouping

Experiment 2 Yes/No task: straight or curved borderline?  edge information necessary, region grouping not sufficient Stimulus presentation 500 ms 2. Repeated measures ANOVA on group level AV CB EG FH JW KV LP MS TP 0 20 40 60 1. Individual psychometric functions and non-parametric test on thresholds and slopes  no consistent differences, except for a trend for higher threshold in regular positioned elements in Experiment 2.