Perceptual expertise enhances the resolution but not the number of representations in working memory

Despite its central role in cognition, capacity in visual working memory is restricted to about three or four items. Curby and Gauthier (2007) examined whether perceptual expertise can help to overcome this limit by enabling more efficient coding of visual information. In line with this, they observed higher capacity estimates for upright than for inverted faces, suggesting that perceptual expertise enhances visual working memory. In the present work, we examined whether the improved capacity estimates for upright faces indicates an increased number of "slots" in working memory, or improved resolution within the existing slots. Our results suggest that perceptual expertise enhances the resolution but not the number of representations that can be held in working memory. These results clarify the effects of perceptual expertise in working memory and support recent suggestions that number and resolution represent distinct facets of working memory ability.     

Perceptual‐cognitive expertise in sport and its acquisition: Implications for applied cognitive psychology

We review contemporary research on perceptual‐cognitive expertise in sport and consider implications for those working in the field of applied cognitive psychology. We identify the important perceptual‐cognitive skills that facilitate anticipation in sport and illustrate how these skills interact in a dynamic manner during performance. We also highlight our current understanding of how these skills are acquired and consider the extent to which the underlying processes are specific to a particular domain and role within that domain. Next, we briefly review recent attempts to facilitate the acquisition of perceptual‐cognitive expertise using simulation training coupled with instruction and feedback on task performance. Finally, we discuss how research on elite athletes can help inform applied cognitive psychologists who are interested in capturing and enhancing perceptual‐cognitive expertise across various domains. Copyright © 2010 John Wiley & Sons, Ltd.     

The Epistemological Status of Vision and its Implications for Design

Computational theories of vision typically rely on the analysis of two aspects of human visual function: (1) object and shape recognition (2) co-calibration of sensory measurements. Both these approaches are usually based on an inverse-optics model, where visual perception is viewed as a process of inference from a 2D retinal projection to a 3D percept within a Euclidean space schema. This paradigm has had great success in certain areas of vision science, but has been relatively less successful in understanding perceptual representation, namely, the nature of the perceptual encoding. One of the drawbacks of inverse-optics approaches has been the difficulty in defining the constraints needed to make the inference computationally tractable (e.g. regularity assumptions, Bayesian priors, etc.). These constraints, thought to be learned assumptions about the nature of the physical and optical structures of the external world, have to be incorporated into any workable computational model in the inverse-optics paradigm. But inference models that employ an inverse optics plus structural assumptions approach inevitably result in a naïve realist theory of perceptual representation. Another drawback of inference models for theories of perceptual representation is their inability to explain central features of the visual experience. The one most evident in the process and visual understanding of design is the fact that some visual configurations appear, often spontaneously, as perceptually more coherent than others. The epistemological consequences of inferential approaches to vision indicate that they fail to capture enduring aspects of our visual experience. Therefore they may not be suited to a theory of perceptual representation, or useful for an understanding of the role of perception in the design process and product.     

The functional form of performance improvements in perceptual learning: learning rates and transfer

The functional form of performance improvements has been extensively studied in speeded cognitive and motor tasks; in such tasks, reductions in response times have been characterized by the ubiquitous power law of learning or by a simpler exponential form. Performance improvements in perceptual capacities are also important in expertise, but their functional form is unknown. This study investigated the functional form of perceptual learning. For individual observers, reductions in thresholds were best described by an exponential function, rather than a power or compound exponential and power (apex) function. Learning was specific to orientation, a result that supports the perceptual locus of the learning, and was decoupled in high and low external noise, a result that reflects separable learning mechanisms in the two conditions. The simple exponential form of learning implies a constant relative rate of learning throughout practice; there was no evidence supporting multilevel hypotheses, such as serial reverse hierarchical and parallel-learning models, that posit multiple processes of learning characterized by different rates.     

Preparing for the 21st Century: Some Goals and Challenges for Studies of Infant Sensory and Perceptual Development

While acknowledging that there has been enormous progress in our understanding of sensory and perceptual development in human infancy over the past three decades, this paper looks toward future directions in preparation for the 21st century. It is argued that investigators should move away from the categorical thinking that dominates the field and focus more on developmental process in studying the acquisition of perceptual skills. Also, more attention should be paid to the functional role of perceptual skills and less to demonstrations of discrimination. In addition, researchers should attempt to bring their work and conceptualizations more in line with that on adults and older children. Future work on sensory and perceptual development in infancy will be heavily influenced by our understanding of how the brain works, especially with refinements in brain imaging and neurophysiology and with developments in computational modeling of perceptual processes. Finally, it is likely that there will be increased application of research findings to such problems as identification of infants at risk.     

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.     

Curiosity‐based learning in infants: a neurocomputational approach

Infants are curious learners who drive their own cognitive development by imposing structure on their learning environment as they explore. Understanding the mechanisms by which infants structure their own learning is therefore critical to our understanding of development. Here we propose an explicit mechanism for intrinsically motivated information selection that maximizes learning. We first present a neurocomputational model of infant visual category learning, capturing existing empirical data on the role of environmental complexity on learning. Next we “set the model free”, allowing it to select its own stimuli based on a formalization of curiosity and three alternative selection mechanisms. We demonstrate that maximal learning emerges when the model is able to maximize stimulus novelty relative to its internal states, depending on the interaction across learning between the structure of the environment and the plasticity in the learner itself. We discuss the implications of this new curiosity mechanism for both existing computational models of reinforcement learning and for our understanding of this fundamental mechanism in early development.     

Forming stable partnerships

Autonomous agents interacting in an open world can be considered to be primarily driven by self interests. In this paper, we evaluate the hypotheses that self-interested agents with complementary expertise can learn to recognize cooperation possibilities and develop stable, mutually beneficial partnerships that is resistant to exploitation by malevolent agents. Previous work in this area has prescribed a strategy of reciprocal behavior for promoting and sustaining cooperation among such cognitive learning agents. We develop on that work by expanding the task cost metric to include both time of completion and quality of performance. Different task types are assumed and, in contrast to previous work, we use heterogeneous agents with varying expertise for different task types. This necessitates the incorporation of cognitive abilities, including an understanding of one’s own capabilities and learning about other’s capabilities within the reciprocity framework.     

Coming together and remaining a part: Development of a group-as-a-whole compass. Part II

Group-as-a-whole theory is an attempt to explain the collaboration and synergy that results when patients share their care. The art and science of treating individuals within psychotherapy groups is enriched by an understanding of the unique mediums ³ through which a group comes into being and the more general domains within which it comes to be known. This paper continues the development of a group-as-a-whole compass, as an integration of extant models and theories (Ettin, 1996). The focus shifts from conceptual and spatial models to an exploration of the cultural and relational processes that make up whole-group functioning. The paper comes full circle with hypotheses drawn about how a psychotherapy group, as a holistic phenomenon, is composed and maintained.Private practice, East Brunswick, New Jersey.     

Individual differences in echocardiography: Visual object recognition ability predicts cue utilization

Echocardiographers are highly specialised, skilled practitioners who play a critical role in medical imaging diagnostics. Yet, little is known about the cognitive and perceptual attributes of experts within this domain. This study was designed to examine the role of individual differences in expertise. Specifically, the contribution of a domain general visual expertise and pattern recognition, or cue utilization. Data were collected from 42 echocardiographers and 43 naïve participants. All of the participants competed the Novel Object Memory Test (NOMT). When compared, the echocardiographers were more accurate than the naïve participants. The echocardiographers also completed an echocardiography edition of the Expert Intensive Skills Evaluation 2.0, to establish behavioral indicators of context-related cue utilization. Those with relatively higher cue utilization performed more accurately on the NOMT, controlling for exposure. These results suggest that a general perceptual ability contributes to echocardiography potential and a sensitivity to cue-based learning may contribute to expertise.     

The training and transfer of real-world perceptual expertise

A hallmark of perceptual expertise is that experts classify objects at a more specific, subordinate level of abstraction than novices. To what extent does subordinate-level learning contribute to the transfer of perceptual expertise to novel exemplars and novel categories? In this study, participants learned to classify 10 varieties of wading birds and 10 varieties of owls at either the subordinate, species (e.g., "great blue crown heron,"eastern screech owl") or the family ("wading bird,"owl") level of abstraction. During training, the amount of visual exposure was equated such that participants received an equal number of learning trials for wading birds and owls. Pre- and posttraining performance was measured in a same/different discrimination task in which participants judged whether pairs of bird stimuli belonged to the same or different species. Participants trained in species-level discrimination demonstrated greater transfer to novel exemplars and novel species categories than participants trained in family-level discrimination. These findings suggest that perceptual categorization, not perceptual exposure per se, is important for the development and generalization of visual expertise.     

Identifying stimuli of different perceptual categories in mixed blocks of trials: evidence for cost in switching between computational processes

Responding to stimuli of different perceptual categories is usually faster when the categories are presented isolated from each other, in pure blocks, than when they are presented intermixed, in mixed blocks. According to criterion models, these perceptual mixing costs result from the use of a less conservative response criterion in pure than in mixed blocks. According to alternate processing models, mixing costs result from time-consuming switching in mixed blocks between different computational processes called on by the different perceptual categories. In 5 experiments, participants had to identify number stimuli of different categories. The results showed clear mixing costs whenever these categories differed in their assumed computational processing requirements but not when they differed on features that seemed trivial from a computational viewpoint. The results favor the alternate processing conception.     

Perceptual mechanisms that characterize gender differences in decoding women's sexual intent

Men and women often disagree about the meaning of women's nonverbal cues, particularly those conveying dating-relevant information. Men perceive more sexual intent in women's behavior than women perceive or report intending to convey. Although this finding has been attributed to gender differences in the threshold for labeling ambiguous cues as sexual in nature, little research has been conducted to determine etiology. Using a model that differentiates perceptual sensitivity from decisional bias, we found no evidence that men have lenient thresholds for perceiving women's nonverbal behavior as indicating sexual interest. Rather, gender differences were captured by a relative perceptual insensitivity among men. Just as in previous studies, men were more likely than women to misperceive friendliness as sexual interest, but they also were quite likely to misperceive sexual interest as friendliness. The results point to the promise of computational models of perception in increasing the understanding of clinically relevant social processes.     

Does task-set reconfiguration create cognitive slack?

C. Oriet and P. Jolicoeur (2003) reported 2 experiments in which the perceptual contrast of stimuli was manipulated in a task-switching paradigm. They failed to observe an interaction in the reaction time data between task switching, perceptual contrast, and response-stimulus interval. Using the locus of slack logic, they concluded from these results that early perceptual processing of stimuli awaits the completion of a task-set reconfiguration stage, rather than proceeding in parallel with it. Here, an assumption necessary for this argument is questioned, and it is shown that an existing computational model of task switching, without successive stages for task-set reconfiguration and perceptual processing, produces a similar pattern of data. Thus, C. Oriet and P. Jolicoeur's data are compatible with models in which early perceptual processing and task-set reconfiguration take place in parallel.     

Perceptual organization in schizophrenia spectrum disorders: empirical research and theoretical implications

The research into perceptual organization in schizophrenia spectrum disorders has found evidence for and against a perceptual organization deficit and has interpreted the data from within several different theoretical frameworks. A synthesis of this evidence, however, reveals that this body of work has produced reliable evidence for deficits in schizophrenia, as well as for the clinical, stimulus, and task parameters associated with normal and abnormal performance. Recent models of cognition have also advanced understanding of the underlying pathophysiological processes of perceptual organization dysfunction in schizophrenia spectrum disorders. These suggest that deficits in perceptual organization may be one manifestation of a wider disturbance in the integration of contextually related information across space and time.     

Perceptual and conceptual training mediate the verbal overshadowing effect in an unfamiliar domain

Describing memory for a nonverbal perceptual stimulus can impair recognition. This verbal overshadowing effect may occur when perceptual expertise exceeds verbal expertise, but previous evidence for this hypothesis has been strictly correlational. We conducted two experiments, exploring the relation between expertise and verbal overshadowing by manipulating perceptual and conceptual knowledge. Participants received perceptual training (categorizing mushrooms), conceptual training (lecture), or no training, then viewed a mushroom and described it or not. A recognition test followed. In Experiment 1, perceptual training increased susceptibility to verbalization relative to the no training condition. However, conceptual training did not insulate individuals from the verbal overshadowing effect. Experiment 2 was modified to enhance both forms of training. It replicated the finding that perceptual training increases vulnerability to verbal overshadowing, and indicated that, when sufficiently emphasized, verbalization may be useful following conceptual training. The results demonstrate the role that different forms of learning and expertise may play in mediating language influences on recognition memory.     

Object knowledge in infancy: current controversies and approaches

Studies relying on looking-time measures have found evidence of a far more precocious understanding of hidden objects than Piaget originally described. However, there is now a heated controversy surrounding the results from looking-time studies - do they constitute any evidence of a conceptual or explicit understanding of objects? Moreover, even within the looking-time paradigm, young infants show rapid changes in their understanding of what constitutes a legitimate occlusion event, and in their ability to use feature information to individuate or keep track of the number of hidden objects. The picture that emerges from these studies is that young infants have a limited and sometimes fragmented understanding of hidden objects. We suggest that computational modelling could help provide a coherent account of the emergence of object-directed behaviours in infancy, although the fit between current models and existing data remains poor.     

Chunking mechanisms in human learning

Pioneering work in the 1940s and 1950s suggested that the concept of 'chunking' might be important in many processes of perception, learning and cognition in humans and animals. We summarize here the major sources of evidence for chunking mechanisms, and consider how such mechanisms have been implemented in computational models of the learning process. We distinguish two forms of chunking: the first deliberate, under strategic control, and goal-oriented; the second automatic, continuous, and linked to perceptual processes. Recent work with discrimination-network computational models of long- and short-term memory (EPAM/CHREST) has produced a diverse range of applications of perceptual chunking. We focus on recent successes in verbal learning, expert memory, language acquisition and learning multiple representations, to illustrate the implementation and use of chunking mechanisms within contemporary models of human learning.     

Toward computational neuroconstructivism: a framework for developmental systems neuroscience

Brain development is underpinned by complex interactions between neural assemblies, driving structural and functional change. This neuroconstructivism (the notion that neural functions are shaped by these interactions) is core to some developmental theories. However, due to their complexity, understanding underlying developmental mechanisms is challenging. Elsewhere in neurobiology, a computational revolution has shown that mathematical models of hidden biological mechanisms can bridge observations with theory building. Can we build a similar computational framework yielding mechanistic insights for brain development? Here, we outline the conceptual and technical challenges of addressing this theory gap, and demonstrate that there is great potential in specifying brain development as mathematically defined processes operating within physical constraints. We provide examples, alongside broader ingredients needed, as the field explores computational explanations of system-wide development.     

Normative and Substantive Expertise in Multiple Hypotheses Evaluation

We distinguish two criteria for evaluating the judgments of trained professionals. One criterion is conformance with a theoretical model and the other is conformance with known external criteria. Further, we label judgments that depart from a theoretical model as errors and those that depart from known external criteria as mistakes. Following this distinction, we hypothesize that auditors′ multiple hypotheses judgments will be characterized by errors but not mistakes. This hypothesis was tested by asking professional auditors to evaluate multiple hypotheses. The results confirm our expectations. Auditors′ judgments reflected ecological base rate information, and they appropriately ignored nondiagnostic evidence. Moreover, auditors did not exhibit a perseverance bias and 84% of them identified the correct hypothesis. The absence of mistakes reflect substantive expertise. Conversely, auditors′ probabilities were not additive, and, when a hypothesis was eliminated, they did not adjust beliefs for the remaining hypotheses. These errors reflect a lack of normative expertise. A second study employed inexperienced subjects to establish whether the strong substantive performance of the professional auditors was attributed to their expertise or was an artifact of the task. The results from the second study were strongly supportive of the substantive expertise explanation. Taken together, these results suggest that substantive expertise can help contain mistakes but it is not sufficient to mitigate errors. Further, lack of normative expertise can lead to errors but these errors do not translate into mistakes. The paper concludes that the distinction between normative and substantive expertise on one hand and errors and mistakes on the other is crucial to understanding when basic findings will generalize to professional settings.