How to tell a wife from a hat: Affective feedback in perceptual categorization

How do people understand that their perception is correct? In line with the recurring idea of perception as prediction, the affective feedback account of hypotheses testing suggests that correct perceptual predictions are reinforced with positive affect. In four experiments, we tested whether correct categorization of a degraded image will lead to more positive liking ratings. The obtained findings supported the proposed approach: subjects liked the images they were able to perceive correctly more than others. Importantly, these findings were independent of the initial affective valence of stimuli. A further investigation demonstrated that this effect exists only when answers are at least moderately confident. The obtained findings add to the growing amount of literature on the role of affect in basic cognitive processing.     

Comparison and contrast in perceptual categorization

People categorized pairs of perceptual stimuli that varied in both category membership and pairwise similarity. Experiments 1 and 2 showed categorization of 1 color of a pair to be reliably contrasted from that of the other. This similarity-based contrast effect occurred only when the context stimulus was relevant for the categorization of the target (Experiment 3). The effect was not simply owing to perceptual color contrast (Experiment 4), and it extended to pictures from common semantic categories (Experiment 5). Results were consistent with a sign-and-magnitude version of N. Stewart and G. D. A. Brown's (2005) similarity-dissimilarity generalized context model, in which categorization is affected by both similarity to and difference from target categories. The data are also modeled with criterion setting theory (M. Treisman & T. C. Williams, 1984), in which the decision criterion is systematically shifted toward the mean of the current stimuli.     

Digital embryos: a novel technical approach to investigate perceptual categorization in pigeons (Columba livia) using machine learning

Animal Cognition - Pigeons are classic model animals to study perceptual category learning. To achieve a deeper understanding of the cognitive mechanisms of categorization, a careful consideration...     

Costs and benefits in perceptual categorization

Observers categorized perceptual stimuli when the category costs and benefits were manipulated across conditions, and costs were either zero or nonzero. The cost-benefit structures were selected so that performance across conditions was equivalent with respect to the optimal classifier. Each observer completed several blocks of trials in each of the experimental conditions, and a series of nested models was applied to the individual observer data from all conditions. In general, performance became more nearly optimal as observers gained experience with the cost-benefit structures, but performance reached asymptote at a suboptimal level. Observers behaved differently in the zero- and nonzero-cost conditions, performing consistently worse when costs were nonzero. A test of the hypothesis that observers weight costs more heavily than benefits was inconclusive. Some aspects of the data supported this differential weighting hypothesis, but others did not. Implications for current theories of cost-benefit learning are discussed.     

Category discriminability, base-rate, and payoff effects in perceptual categorization

The optimality of perceptual categorization performance under manipulations of category discriminability (i.e., d' level), base rates, and payoffs was examined. Base-rate and payoff manipulations across two category discriminabilities allowed a test of the hypothesis that the steepness of the objective reward function affects performance (i.e., the flat-maxima hypothesis), as well as the hypothesis that observers combine base-rate and payoff information independently. Performance was (1) closer to optimal for the steeper objective reward function, in line with the flat-maxima hypothesis, (2) closer to optimal in base-rate conditions than in payoff conditions, and (3) in partial support of the hypothesis that base-rate and payoff knowledge is combined independently. Implications for current theories of base-rate and payoff learning are discussed.     

Similarity and dissimilarity as evidence in perceptual categorization

In exemplar models the similarities between a new stimulus and each category exemplar constitute positive evidence for category membership. In contrast, other models assume that, if the new stimulus is sufficiently dissimilar to a category member, then that dissimilarity constitutes evidence against category membership. We propose a new similarity-dissimilarity exemplar model that provides a framework for integrating these two types of accounts. The evidence for a category is assumed to be the summed similarity to members of that category plus the summed dissimilarity to members of competing categories. The similarity-dissimilarity exemplar model is shown to mimic the standard exemplar model very closely in the unidimensional domain.     

A feedback model of perceptual learning and categorization

Top-down, feedback, influences are known to have significant effects on visual information processing. Such influences are also likely to affect perceptual learning. This paper employs a computational model of the cortical region inter-actions underlying visual perception to investigate possible influences of top-down information on learning. The results suggest that feedback could bias the way in which perceptual stimuli are categorized and could also facilitate the learning of subordinate level representations suitable for object identification and perceptual expertise.     

PsychoPro 2.0: Using multidimensional scaling to examine the perceptual categorization of race

Recently, researchers examining cognitive mechanisms involved in the detection of racial markers have been using psychophysics to examine perceptual thresholds delineating race using a program called PsychoPro (MacLin, MacLin, Peterson, Chowdhry, & Joshi, 2009). PsychoPro allows researchers to collect data using facial stimuli morphed along a racial continuum with psychophysical methodology. PsychoPro 2.0 was updated so researchers could collect paired-comparison data that can then be analyzed using multidimensional scaling (MDS). MDS allows researchers to examine the perceptions of racial boundaries along perceptual dimensions not bounded by the stimulus continuum, by having the observer make paired comparisons to racial stimuli based on their perceived similarity. Results indicate that ratings were made on the basis of at least six different racial dimensions that suggest the emergence of a third race not represented by the original morph starting images. Details of the software, the new paired-comparison feature and its relevance in psychophysical studies in general and racial categorization in particular are presented.     

On the relation between decision rules and perceptual representation in multidimensional perceptual categorization

This article examines the relation between changing categorization decision rules and the nature of the underlying perceptual representation. Observers completed a matching task that required them to adjust the length and orientation of a single line stimulus until they perceived it to "match" a second line stimulus (Alfonso-Reese, 1996, 1997). The same observers then completed four categorization tasks with the same stimuli. Data from the matching task were used to estimate a perceptual representation for each stimulus and observer. Three hypotheses regarding potential interactions between categorization decision rules and perceptual representation were examined. One assumed that there was no interaction between decision rules and perceptual representation. The second assumed that linear categorization rules affect the perceptual representation differently from nonlinear categorization rules. The third assumed that dimensional integration rules affected the perceptual representation differently from decision rules that require the observer to set a criterion along one stimulus dimension while ignoring the other; this is referred to as decisional selective attention. The results suggested that (1) the matching task perceptual representation provided a good account of the categorization data, (2) decisional selective attention affected the perceptual representation differently from decisional integration, and (3) decisional selective attention generally decreased the perceptual variability along the attended dimension.     

Central tendencies, extreme points, and prototype enhancement effects in ill-defined perceptual categorization

In three perceptual classification experiments involving ill-defined category structures, extreme prototype enhancement effects were observed in which prototypes were classified more accurately than other category instances. Such empirical findings can prove theoretically challenging to exemplar-based models of categorization if prototypes are psychological central tendencies of category instances. We found instead that category prototypes were sometimes better characterized as psychological extreme points relative to contrast categories. Extending a classic and widely cited study (Posner & Keele, 1968), participants learned categories created from distortions of dot patterns arranged in familiar shapes. Participants then made pairwise similarity judgements of the patterns. Multidimensional scaling (MDS) analyses of the similarity data revealed the prototypes to be psychological extreme points, not central tendencies. Evidence for extreme point representations was also found for novel prototype patterns displaying a symmetry structure and for prototypes of grid patterns used in recent studies by McLaren and colleagues (McLaren, Bennet, Guttman-Nahir, Kim, & M ackintosh, 1995). When used in combination with the derived M DS solutions, an exemplar-based model of categorization, the Generalized Context Model (Nosofsky, 1986), provided good fits to the observed categorization data in all three experiments.     

Toward a unified theory of decision criterion learning in perceptual categorization

Optimal decision criterion placement maximizes expected reward and requires sensitivity to the category base rates (prior probabilities) and payoffs (costs and benefits of incorrect and correct responding). When base rates are unequal, human decision criterion is nearly optimal, but when payoffs are unequal, suboptimal decision criterion placement is observed, even when the optimal decision criterion is identical in both cases. A series of studies are reviewed that examine the generality of this finding, and a unified theory of decision criterion learning is described (Maddox & Dodd, 2001). The theory assumes that two critical mechanisms operate in decision criterion learning. One mechanism involves competition between reward and accuracy maximization: The observer attempts to maximize reward, as instructed, but also places some importance on accuracy maximization. The second mechanism involves a flat-maxima hypothesis that assumes that the observer's estimate of the reward-maximizing decision criterion is determined from the steepness of the objective reward function that relates expected reward to decision criterion placement. Experiments used to develop and test the theory require each observer to complete a large number of trials and to participate in all conditions of the experiment. This provides maximal control over the reinforcement history of the observer and allows a focus on individual behavioral profiles. The theory is applied to decision criterion learning problems that examine category discriminability, payoff matrix multiplication and addition effects, the optimal classifier's independence assumption, and different types of trial-by-trial feedback. In every case the theory provides a good account of the data, and, most important, provides useful insights into the psychological processes involved in decision criterion learning.     

Probability matching, accuracy maximization, and a test of the optimal classifier's independence assumption in perceptual categorization

Observers completed perceptual categorization tasks that included 25 base-rate/payoff conditions constructed from the factorial combination of five base-rate ratios (1:3, 1:2, 1:1, 2:1, and 3:1) with five payoff ratios (1:3, 1:2, 1:1, 2:1, and 3:1). This large database allowed an initial comparison of the competition between reward and accuracy maximization (COBRA) hypothesis with a competition between reward maximization and probability matching (COBRM) hypothesis, and an extensive and critical comparison of the flat-maxima hypothesis with the independence assumption of the optimal classifier. Model-based instantiations of the COBRA and COBRM hypotheses provided good accounts of the data, but there was a consistent advantage for the COBRM instantiation early in learning and for the COBRA instantiation later in learning. This pattern held in the present study and in a reanalysis of Bohil and Maddox (2003). Strong support was obtained for the flat-maxima hypothesis over the independence assumption, especially as the observers gained experience with the task. Model parameters indicated that observers' reward-maximizing decision criterion rapidly approaches the optimal value and that more weight is placed on accuracy maximization in separate base-rate/payoff conditions than in simultaneous base-rate/payoff conditions. The superiority of the flat-maxima hypothesis suggests that violations of the independence assumption are to be expected, and are well captured by the flat-maxima hypothesis, with no need for any additional assumptions.     

A dynamical approach to speech categorization: Two routes to learning

Learning to perceive a non-native speech sound reliably is a specific instance of the more general issue of category learning. Here we take a dynamical approach that provides a theoretically motivated way to understand individual differences in the process of learning to perceive new speech sounds. Fundamental to this approach is the focus on the initial categorization and discrimination abilities of individual perceivers and how these structure the form of learning over time. Two distinct patterns of learning were observed that were predictable based on initial perceptual abilities. In one pattern, subjects became more attuned to small acoustic distinctions between stimuli and could use that sensitivity to label tokens reliably. In the second pattern, subjects became less attuned to within-category acoustic distinctions, suggesting cognitive restructuring. Finally, we present a dynamical model that incorporates both modes of category learning, and also allows for failure to learn.     

Separating perceptual processes from decisional processes in identification and categorization

Four observers completed perceptual matching, identification, and categorization tasks using separable-dimension stimuli. A unified quantitative approach relating perceptual matching, identification, and categorization was proposed and tested. The approach derives from general recognition theory (Ashby & Townsend, 1986) and provides a powerful method for quantifying the separate influences of perceptual processes and decisional processes within and across tasks. Good accounts of the identification data were obtained from an initial perceptual representation derived from perceptual matching. The same perceptual representation provided a good account of the categorization data, except when selective attention to one stimulus dimension was required. Selective attention altered the perceptual representation by decreasing the perceptual variance along the attended dimension. These findings suggest that a complete understanding of identification and categorization performance requires an understanding of perceptual and decisional processes. Implications for other psychological tasks are discussed.     

The topological approach to perceptual organization

To address the fundamental question of “what are the primitives of visual perception”, a theory of topological structure and functional hierarchy in visual perception has been proposed. This holds that the global nature of perceptual organization can be described in terms of topological invariants, global topological perception is prior to the perception of other featural properties, and the primitives of visual form perception are geometric invariants at different levels of structural stability. In Part I of this paper, I will illustrate why and how the topological approach to perceptual organization has been advanced. In Part II, I will provide empirical evidence supporting the early topological perception, while answering some commonly considered counteraccounts. In Part III, to complete the theory, I will apply the mathematics of tolerance spaces to describe global properties in discrete sets. In Part IV, I will further present experimental data to demonstrate the global-to-local functional hierarchy in form perception, which is stratified with respect to structural stability defined by Klein's Erlangen Program. Finally, in Part V, I will discuss relations of the global-to-local topological model to other theories: The topological approach reformulates both classical Gestalt holism and Gibson's direct perception of invariance, while providing a challenge to computational approaches to vision based on the local-to-global assumption.     

Infant perceptual and conceptual categorization: the roles of static and dynamic stimulus attributes

Infants' categorization of animals and vehicles based on static vs. dynamic attributes of stimuli was investigated in five experiments (N=158) using a categorization habituation-of-looking paradigm. In Experiment 1, 6-month-olds categorized static color images of animals and vehicles, and in Experiment 2, 6-month-olds categorized dynamic point-light displays showing only motions of the same animals and vehicles. In Experiments 3, 4, and 5, 6- and 9-month-olds were tested in an habituation-transfer paradigm: half of the infants at each age were habituated to static images and tested with dynamic point-light displays, and the other half were habituated to dynamic point-light displays and tested with static images. Six-month-olds did not transfer. Only 9-month-olds who were habituated to dynamic displays showed evidence of category transfer to static images. Together the findings show that 6-month-olds categorize animals and vehicles based on static and dynamic information, and 9-month-olds can transfer dynamic category information to static images. Transfer, static vs. dynamic information, and age effects in infant categorization are discussed.     

Exogenous attention to angry faces in social anxiety: a perceptual accuracy approach

We investigated the interaction between endogenous and exogenous attention for the processing of emotional stimuli in individuals with high social anxiety using accuracy rates. Following the presentation of an endogenous cue at the centre, exogenous cues (i.e., angry and neutral faces) were presented at peripheral locations. Subsequently, non-emotional masked targets were presented, and the participants were instructed to discriminate between the targets. With respect to exogenous attention, high socially anxious people exhibited higher accuracy when the angry face and target appeared on the same side than when they appeared on different sides, whereas low socially anxious people did not exhibit such effects. On the other hand, different abilities of endogenous attention were not observed between high and low socially anxious people. These results suggest that exogenous attention is biased towards threat in high socially anxious people.     

Separating perceptual processes from decisional processes in identification and categorization.

Four observers completed perceptual matching, identification, and categorization tasks using separable-dimension stimuli. A unified quantitative approach relating perceptual matching, identification, and categorization was proposed and tested. The approach derives from general recognition theory (Ashby & Townsend, 1986) and provides a powerful method for quantifying the separate influences of perceptual processes and decisional processes within and across tasks. Good accounts of the identification data were obtained from an initial perceptual representation derived from perceptual matching. The same perceptual representation provided a good account of the categorization data, except when selective attention to one stimulus dimension was required. Selective attention altered the perceptual representation by decreasing the perceptual variance along the attended dimension. These findings suggest that a complete understanding of identification and categorization performance requires an understanding of perceptual and decisional processes. Implications for other psychological tasks are discussed.     

Identification of gender in domestic-cat faces with and without training: perceptual learning of a natural categorization task

Three experiments were conducted to determine whether human observers could identify the gender of 40 domestic cats (20 female, 20 male) depicted in individual color photographs. In experiment 1a, observers performed at chance for photographs depicting whole cats, cat heads (bodies occluded), and cat bodies (heads occluded). Experiment 1b showed that chance performance was also obtained when the photographs were full-face close-ups of the cats. Experiment 2a revealed that even with gender-identification training on 30 (15 female, 15 male) of the 40 face close-ups, observers were unable to generalize their training to reliably identify the gender of the 10 remaining test faces (5 female, 5 male). However, experiment 2b showed that gender-identification training with the 14 most accurately identified faces from experiment 1b (7 female, 7 male) was successful in raising gender identification of the 10 test faces above chance. Experiments 3a and 3b extended this facilitative effect of gender-identification training to a population of animal-care workers. The findings indicate that, with appropriate training, human observers can identify the gender of cat faces at an above-chance level. A perceptual category learning account emphasizing the on-line formation of differentiated male versus female prototypes during training is offered as an explanation of the findings.