Can two dots form a Gestalt? Measuring emergent features with the capacity coefficient

Gestalts at threshold could reveal Gestalts as predictions

We review and revisit the predictive processing inspired “Gestalts as predictions” hypothesis. The study of Gestalt phenomena at and below threshold can help clarify the role of higher-order object selective areas and feedback connections in mid-level vision. In two psychophysical experiments assessing manipulations of contrast and configurality we showed that: (1) Gestalt phenomena are robust against saliency manipulations across the psychometric function even below threshold (with the accuracy gains and higher saliency associated with Gestalts being present even around chance performance); and (2) peak differences between Gestalt and control conditions happened around the time where responses to Gestalts are starting to saturate (mimicking the differential contrast response profile of striate vs. extra-striate visual neurons). In addition, Gestalts are associated with steeper psychometric functions in all experiments. We propose that these results reflect the differential engagement of object-selective areas in Gestalt phenomena and of information- or percept-based processing, as opposed to energy- or stimulus-based processing, more generally. In addition, the presence of nonlinearities in the psychometric functions suggest differential top-down modulation of the early visual cortex. We treat this as a proof of principle study, illustrating that classic psychophysics can help assess possible involvement of hierarchical predictive processing in Gestalt phenomena.

Individual differences in processing orientation and proximity as emergent features

Numerous examples of meaningful inter-individual differences in visual processing have been documented in low- and high-level vision. For mid-level vision or perceptual organization, vision scientists have only recently started to study the inter-individual differences structure. In this study, we focus on orientation and proximity as emergent features and combine a quantitative information processing approach with an individual differences approach. We first replicated the results reported in Hawkins, Houpt, Eidels, and Townsend (2016) in a set of 52 observers. That is, observers showed higher processing capacity for detecting a change in a stimulus configuration when the emergent features orientation or proximity were changed. Next, we asked whether individual differences processing capacities were similar across emergent features. The capacity to detect any type of change correlated moderately across individuals, whereas the capacity to detect changes in either emergent feature alone was not strongly correlated. This indicates that there is no general sensitivity to emergent features and that observers can be good at detecting orientation changes whilst being poor at detecting proximity changes (and vice versa). An additional exploratory multivariate analysis of the data revealed that response times and accuracies correlated strongly within each emergent feature. Moreover, specific factors related to change detection and inward displacements were observed, revealing consistent individual differences in our data. We discuss the results in the context of the literature on individual differences in vision where both specific, fragmented factors as well as broad, general factors have been reported.

Can we perceive two colors at the same time? A direct test of Huang and Pashler's (2007) Boolean map theory of visual attention

Can observers access two spatially separated color targets (e.g., red and green) at the same time (i.e., in parallel)? According to the Boolean map theory of visual attention (Huang & Pashler, Psychological Review, 114(3), 599-631, 2007), access to two different features that belong to the same dimension (e.g., red and green targets) is limited and therefore can be held only in a serial fashion. The current study proposes a strong test of the Boolean map theory of attention through the application of two of the most rigorous stochastic approaches to response times modeling-the system factorial technology (Townsend & Nozawa, 1995) and the logical rule models (Fifić, Little, & Nosofsky, Psychological Review, 117, 309-348, 2010). These approaches allowed identification of serial, parallel, and coactive architectures in the processing of multicolor targets. The results showed that multiple-color targets are processed serially when observers are required to process all the targets in the display (i.e., an exhaustive stopping rule), and in parallel or coactively when observers can terminate the search when one of the targets is found (i.e., self-terminating stopping rule). These results are generally inconsistent with predictions of the Boolean map theory. They highlight the role of stopping rules in multicolor visual search, as well as the flexibility of the attentional system in shifting between processing architectures.

Neural Signatures of the Configural Superiority Effect and Fundamental Emergent Features in Human Vision

The concepts of grouping, emergence, and superadditivity (when a whole is qualitatively different from the sum of its parts) are critical in Gestalt psychology and essential to properly understand the information processing mechanisms underlying visual perception. However, very little is known about the neural processes behind these phenomena (particularly in terms of their generality vs. specificity and their time-course). Here, we used the configural superiority effect as a way to define "emergence" and "emergent features" operationally, employing an approach that can isolate different emergent features and compare them on a common scale. By assessing well-established event related potentials in a HD-EEG system, we found that the critical processes behind configural superiority and superadditive Gestalt phenomena are present in the window between 100 and 200 ms after stimulus onset and that these effects seem to be driven by specific attentional selection mechanisms. Also, some emergent features seem to be differentially processed in different brain hemispheres. These results shed new light on the issues of the generality vs. specificity of the neural correlates of different Gestalt principles, the hemispheric asymmetries in the processing of hierarchical image structure and the role of the N1 ERP component in reflecting feature selective mechanisms.

Effects of Task Difficulty and Display Format on Automation Usage Strategy: A Workload Capacity Analysis

Objective An experiment used workload capacity analysis to quantify automation usage strategy across different task difficulty and display format types in a speeded task. Background Workload capacity measures the efficiency of concurrent information processing and can serve as a gauge of automation usage strategy in speeded decision tasks. The present study used workload capacity analysis to investigate automation usage strategy while information display format and task difficulty were manipulated. Method Subjects performed a speeded judgment task assisted by an automated aid that issued decision cues at varying onset times. Response time distributions were converted to measures of workload capacity. Results Two variants of a workload capacity measure, C_zOR and C_zAND, gave evidence that operators moderated their own decision times both in anticipation of and following the arrival of the aid's diagnosis under difficult task conditions regardless of display format. Conclusion Assistance from an automated decision aid may cause operators to delay their own responses in a speeded decision task, producing joint response time distributions that are slower than optimal. Application Even when it renders its own judgments quickly and with high accuracy, an automated decision aid may slow responses from a user. Automation designers should consider the relative costs and benefits of response accuracy and time when choosing whether and how to implement an automated decision aid.

An overview of quantitative approaches in Gestalt perception

Gestalt psychology is often criticized as lacking quantitative measurements and precise mathematical models. While this is true of the early Gestalt school, today there are many quantitative approaches in Gestalt perception and the special issue of Vision Research "Quantitative Approaches in Gestalt Perception" showcases the current state-of-the-art. In this article we give an overview of these current approaches. For example, ideal observer models are one of the standard quantitative tools in vision research and there is a clear trend to try and apply this tool to Gestalt perception and thereby integrate Gestalt perception into mainstream vision research. More generally, Bayesian models, long popular in other areas of vision research, are increasingly being employed to model perceptual grouping as well. Thus, although experimental and theoretical approaches to Gestalt perception remain quite diverse, we are hopeful that these quantitative trends will pave the way for a unified theory.