bluuebunny/crossref_metadata_2025 huggingface dataset:
Modeling developmental transitions on the balance scale task
Authors: van Rijn Hedderik , van Someren Maarten , van der Maas Han
Published: August 2005

Periods of relatively stable, rule‐like behavior alternated with short transition periods characterize cognitive development on reasoning tasks like the balance scale task. Each transition gives rise to an improvement in behavior, until a phase is reached in which performance is flawless or improvement is not worthwhile given the necessary extra effort. Several computational models have been developed to capture the developmental phenomena associated with the balance scale task. These models, which originate from different computational traditions, explain the main phenomena of development. Recently, empirical phenomena have been reported that these models cannot easily accommodate. We propose a computational model that is implemented in ACT‐R and that is based on the evaluation of success of applied knowledge, combined with a mechanism to construct newknowledge by searching for differences between the left‐ and right‐hand sides of presented balance scale problems. This model accounts for the main empirical phenomena as well as for the recently reported empirical phenomena such as learning without feedback.
Intrinsic cognitive models
Authors: Waskan Jonathan A.
Published: August 2005

Theories concerning the structure, or format, of mental representation should (1) be formulated in mechanistic, rather than metaphorical terms; (2) do justice to several philosophical intuitions about mental representation; and (3) explain the human capacity to predict the consequences of worldly alterations (i.e., to think before we act). The hypothesis that thinking involves the application of syntax‐sensitive inference rules to syntactically structured mental representations has been said to satisfy all three conditions. An alternative hypothesis is that thinking requires the construction and manipulation of the cognitive equivalent of scale models. A reading of this hypothesis is provided that satisfies condition (1) and which, even though it may not fully satisfy condition (2), turns out (in light of the frame problem) to be the only known way to satisfy condition (3).
Lexical effects on compensation for coarticulation: the ghost of Christmash past
Authors: Magnuson James S. , McMurray Bob , Tanenhaus Michael K. , Aslin Richard N.
Published: August 2005

The question of when and how bottom‐up input is integrated with top‐down knowledge has been debated extensively within cognition and perception, and particularly within language processing. A long running debate about the architecture of the spoken‐word recognition system has centered on the locus of lexical effects on phonemic processing: does lexical knowledge influence phoneme perception through feedback, or post‐perceptually in a purely feedforward system? Elman and McClelland (1988) reported that lexically restored ambiguous phonemes influenced the perception of the following phoneme, supporting models with feedback from lexical to phonemic representations. Subsequently, several authors have argued that these results can be fully accounted for by diphone transitional probabilities in a feedforward system (Cairns et al., 1995; Pitt & McQueen, 1998). We report results strongly favoring the original lexical feedback explanation: lexical effects were present even when transitional probability biases were opposite to those of lexical biases.
Area activation: a computational model of saccadic selectivity in visual search
Authors: Pomplun Marc , Reingold Eyal M. , Shen Jiye
Published: August 2005

The Area Activation Model (Pomplun, Reingold, Shen, & Williams, 2000) is a computational model predicting the statistical distribution of saccadic endpoints in visual search tasks. Its basic assumption is that saccades in visual search tend to foveate display areas that provide a maximum amount of task‐relevant information for processing during the subsequent fixation. In the present study, a counterintuitive prediction by the model is empirically tested, namely that saccadic selectivity towards stimulus features depends on the spatial arrangement of search items. We find good correspondence between simulated and empirically observed selectivity patterns, providing strong support for the Area Activation Model.
ERP evidence for task modulations on face perceptual processing at different spatial scales
Authors: Goffaux V. , Jemel B. , Jacques C. , Rossion B. , Schyns P.G.
Published: August 2005

Does the perceptual processing of faces flexibly adapt to the requirements of the categorization task at hand, or does it operate independently of this cognitive context? Behavioral studies have shown that the fine and coarse spatial scales of a face are differentially processed depending on the categorization task performed, thus suggesting that the latter can influence stimulus perception. Here, we investigated the time course of these task influences on perceptual processing by examining the visual N170 face‐sensitive Event‐Related Potential (ERP), while observers categorized faces for their gender and familiarity. Stimuli were full spectrum, or filtered versions that preserved either coarse or fine scale information of the faces. Behavioral results replicated previous findings of a differential processing of coarse and fine spatial scales across tasks. In addition, the N170 amplitude was larger in the Gender task as compared to the Familiarity task for LSF faces exclusively, thus showing that task demands differentially modulated the spatial scale processing on faces. These results suggest that the diagnosticity of scale‐specific cues in categorization tasks can modulate face processing.
Modeling memory and perception
Authors: Shiffrin Richard M.
Published: August 2005

I present a framework for modeling memory, retrieval, perception, and their interactions. Recent versions of the models were inspired by Bayesian induction: We chose models that make optimal decisions conditioned on a memory/perceptual system with inherently noisy storage and retrieval. The resultant models are, fortunately, largely consistent with my models dating back to the 1960s, and are therefore natural successors. My recent articles have presented simplified models in order to focus on particular applications. This article takes a larger perspective and places the individual models in a more global framework. I will discuss (1) the storage of episodic traces, the accumulation of these into knowledge (e.g., lexical/semantic traces in the case of words), and the changes in knowledge caused by learning; (2) the retrieval of information from episodic memory and from general knowledge; (3) decisions concerning storage, retrieval, and responding. Examples of applications include episodic recognition and cued and free recall, perceptual identification (naming, yes–no and forced‐choice), lexical decision, and long‐term and short‐term priming.
A Bayesian approach to the evolution of perceptual and cognitive systems
Authors: Geisler Wilson S. , Diehl Randy L.
Published: August 2005

We describe a formal framework for analyzing how statistical properties of natural environments and the process of natural selection interact to determine the design of perceptual and cognitive systems. The framework consists of two parts: a Bayesian ideal observer with a utility function appropriate for natural selection, and a Bayesian formulation of Darwin's theory of natural selection. Simulations of Bayesian natural selection were found to yield new insights, for example, into the co‐evolution of camouflage, color vision, and decision criteria. The Bayesian framework captures and generalizes, in a formal way, many of the important ideas of other approaches to perception and cognition.
Persistence and accommodation in short‐term priming and other perceptual paradigms: temporal segregation through synaptic depression
Authors: Huber David E. , O'Reilly Randall C.
Published: August 2005

Perceptual input changes constantly in an unpredictable fashion, often changing before our somewhat sluggish perceptual systems have adequately processed this input. This can give rise to source confusion—how do we know whether a given perceptual activation is due to the current input, or a previous input that had yet to be completely processed? We propose that activity‐dependent neural accommodation naturally limits this source confusion by suppressing items once they have been identified. We review behavioral paradigms from different literatures that measure the correlates of persistence and accommodation. Of the various accommodative mechanisms, we focus on synaptic depression, deriving a rate‐coded expression that can be used to produce accommodating dynamics in any neural network with real valued activation. We implement this expression in a hierarchical model of perception termed, “a neural mechanism for responding optimally with unknown sources of evidence” (nROUSE). This model can be viewed as a more detailed version of the more abstract ROUSE model of Huber, Shiffrin, Lyle, and Ruys (2001), which produces accommodated levels of feature evidence through an optimal calculation. We apply nROUSE to three short‐term priming experiments that manipulated prime duration.
Spacing and repetition effects in human memory: application of the SAM model
Authors: Raaijmakers Jeroen G.W.
Published: August 2005

Spacing between study trials of an item increases the probability that item will be recalled. This article presents a new model for spacing based on the SAM theory of memory developed by Raaijmakers and Shiffrin (1980, 1981). The model is a generalization of the SAM model as applied to interference paradigms (Mensink & Raaijmakers, 1988, 1989) and may be viewed as a mathematical version of the Component‐Levels theory proposed by Glenberg (1979). It is assumed that on a second presentation of an item, information is added to an existing trace if the episodic memory image corresponding to that item is retrieved. If it is not retrieved, a new image is stored. It is shown that the model predicts many standard findings including the lack of a spacing effect for the recall of at least one of two items each presented once (Ross & Landauer, 1978).
Inferring causal networks from observations and interventions
Authors: Steyvers Mark , Tenenbaum Joshua B. , Wagenmakers Eric‐Jan , Blum Ben
Published: August 2005

Information about the structure of a causal system can come in the form of observational data—random samples of the system's autonomous behavior—or interventional data—samples conditioned on the particular values of one or more variables that have been experimentally manipulated. Here we study people's ability to infer causal structure from both observation and intervention, and to choose informative interventions on the basis of observational data. In three causal inference tasks, participants were to some degree capable of distinguishing between competing causal hypotheses on the basis of purely observational data. Performance improved substantially when participants were allowed to observe the effects of interventions that they performed on the systems. We develop computational models of how people infer causal structure from data and how they plan intervention experiments, based on the representational framework of causal graphical models and the inferential principles of optimal Bayesian decision‐making and maximizing expected information gain. These analyses suggest that people can make rational causal inferences, subject to psychologically reasonable representational assumptions and computationally reasonable processing constraints.
Data‐driven approaches to information access
Authors: Dumais Susan
Published: August 2005

This paper summarizes three lines of research that are motivated by the practical problem of helping users find information from external data sources, most notably computers. The application areas include information retrieval, text categorization, and question answering. A common theme in these applications is that practical information access problems can be solved by analyzing the statistical properties of words in large volumes of real world texts. The same statistical properties constrain human performance, thus we believe that solutions to practical information access problems can shed light on human knowledge representation and reasoning.
Controlled & automatic processing: behavior, theory, and biological mechanisms
Authors: Schneider Walter , Chein Jason M.
Published: August 2005

This paper provides an overview of developments in a dual processing theory of automatic and controlled processing that began with the empirical and theoretical work described by Schneider and Shiffrin (1977) and Shiffrin and Schneider (1977) over a quarter century ago. A review of relevant empirical findings suggests that there is a set of core behavioral phenomena reflecting differences between controlled and automatic processing that must be addressed by a successful theory. These phenomena relate to: consistency in training, serial versus parallel processing, level of effort, robustness to stressors, degree of control, effects on long‐term memory, and priority encoding. We detail a computational model of controlled processing, CAP2, that accounts for these phenomena as emergent properties of an underlying hybrid computational architecture. The model employs a large network of distributed data modules that can categorize, buffer, associate, and prioritize information. Each module is a connectionist network with input and output layers, and each module communicates with a central Control System by outputting priority and activity report signals, and by receiving control signals. The Control System is composed of five processors including a Goal Processor, an Attention Controller, an Activity Monitor, an Episodic Store, and a Gating & Report Relay. The transition from controlled to automatic processing occurs in this model as the data modules become capable of transmitting their output without mediation by the Control System. We describe recent progress in mapping the components of this model onto specific neuroanatomical substrates, briefly discuss the potential for applying functional neuroimaging techniques to test the model's predictions, and its relation to other models.
Two ways of learning associations
Authors: Boucher Luke , Dienes Zoltán
Published: August 2005

How people learn chunks or associations between adjacent items in sequences was modelled. Two previously successful models of how people learn artificial grammars were contrasted: the CCN, a network version of the competitive chunker of Servan‐Schreiber and Anderson [J. Exp. Psychol.: Learn. Mem. Cogn. 16 (1990) 592], which produces local and compositionally‐structured chunk representations acquired incrementally; and the simple recurrent network (SRN) of Elman [Cogn. Sci. 14 (1990) 179], which acquires distributed representations through error correction. The models' susceptibility to two types of interference was determined: prediction conflicts, in which a given letter can predict two other letters that appear next with an unequal frequency; and retroactive interference, in which the prediction made by a letter changes in the second half of training. The predictions of the models were determined by exploring parameter space and seeing howdensely different regions of the space of possible experimental outcomes were populated by model outcomes. For both types of interference, human data fell squarely in regions characteristic of CCN performance but not characteristic of SRN performance.
A construction based analysis of child directed speech
Authors: Cameron‐Faulkner Thea , Lieven Elena , Tomasello Michael
Published: August 2005

The child directed speech of twelve English‐speaking motherswas analyzed in terms of utterance‐level constructions. First, the mothers' utterances were categorized in terms of general constructional categories such as Wh‐questions, copulas and transitives. Second, mothers' utterances within these categories were further specified in terms of the initial words that framed the utterance, item‐based phrases such as Are you …, I'll …, It's …, Let's …, What did … The findings were: (i) overall, only about 15% of all maternal utterances had SVO form (most were questions, imperatives, copulas, and fragments); (ii) 51% of all maternal utterances began with one of 52 item‐based phrases, mostly consisting of two words or morphemes (45% began with one of just 17 words); and (iii) children used many of these same item‐based phrases, in some cases at a rate that correlated highly with their own mother's frequency of use. We suggest that analyses of adult–child linguistic interaction should take into account not just general constructional categories, but also the item‐based constructions that adults and children use and the frequency with which they use them.
Modeling knowledge‐based inferences in story comprehension
Authors: Frank Stefan L. , Koppen Mathieu , Noordman Leo G.M. , Vonk Wietske
Published: August 2005

A computational model of inference during story comprehension is presented, in which story situations are represented distributively as points in a high‐dimensional “situation‐state space.” This state space organizes itself on the basis of a constructed microworld description. From the same description, causal/temporal world knowledge is extracted. The distributed representation of story situations is more flexible than Golden and Rumelhart's [Discourse Proc 16 (1993) 203] localist representation.

A story taking place in the microworld corresponds to a trajectory through situation‐state space. During the inference process, world knowledge is applied to the story trajectory. This results in an adjusted trajectory, reflecting the inference of propositions that are likely to be the case. Although inferences do not result from a search for coherence, they do cause story coherence to increase. The results of simulations correspond to empirical data concerning inference, reading time, and depth of processing.

An extension of the model for simulating story retention shows how coherence is preserved during retention without controlling the retention process. Simulation results correspond to empirical data concerning story recall and intrusion.
A tale of two similarities: comparison and integration in conceptual combination
Authors: Estes Zachary
Published: August 2005

The perception of semantic similarity derives from distinct processes of comparison and integration. A dual process model of conceptual combination claims that attributive combination (e.g., umbrella tree) entails comparison, while relational combination (e.g., pancake spatula) requires integration. The present research uses similarity as a test of this dual process model. Participants (N = 168) were presented attributive and relational conceptual combinations. Half of the participants interpreted the combinations before rating the similarity of their constituent concepts, while the other half provided similarity ratings without interpreting the concepts together. The experiment revealed that attributive combination decreased the perceived similarity of the constituent concepts, whereas relational combination increased the similarity of the constituents. This result indicates that attributive and relational combination occur via distinct processes. Results of a post‐test (N = 60) suggested that these effects were specific to the particular concepts compared or integrated, and do not generalize to other concepts not compared or integrated. The present research thus supported a dual process model of conceptual combination by demonstrating differential effects of comparison and integration on the perception of semantic similarity.
What goes up may come down: perceptual process and knowledge access in the organization of complex visual patterns by young infants
Authors: Quinn Paul C. , Schyns Philippe G.
Published: August 2005

The relationship between perceptual categorization and organization processes in 3‐ to 4‐month‐old infants was explored. The question was whether an invariant part abstracted during category learning could interfere with Gestalt organizational processes. Experiment 1 showed that the infants could parse a circle in accord with good continuation from visual patterns consisting of a circle and a complex polygon. In Experiments 2 and 3, however, this parsing was interfered with by a prior category familiarization experience in which infants were presented with visual patterns consisting of a pacman shape and a complex polygon. Part 1 of Experiments 2 and 3 showed that the infants recognized the pacman as familiar, and Part 2 demonstrated that the representation of the pacman blocked the subsequent parsing of the circle. The results suggest that a cognitive system of flexible feature creation can override organizational principles with which a perceptual system may come pre‐equipped.
Interpretation‐based processing: a unified theory of semantic sentence comprehension
Authors: Budiu Raluca , Anderson John R.
Published: August 2005

We present interpretation‐based processing—a theory of sentence processing that builds a syntactic and a semantic representation for a sentence and assigns an interpretation to the sentence as soon as possible. That interpretation can further participate in comprehension and in lexical processing and is vital for relating the sentence to the prior discourse. Our theory offers a unified account of the processing of literal sentences, metaphoric sentences, and sentences containing semantic illusions. It also explains how text can prime lexical access. We show that word literality is a matter of degree and that the speed and quality of comprehension depend both on how similar words are to their antecedents in the preceding text and how salient the sentence is with respect to the preceding text. Interpretation‐based processing also reconciles superficially contradictory findings about the difference in processing times for metaphors and literals. The theory has been implemented in ACT‐R [Anderson and Lebiere, The Atomic Components of Thought, Lawrence Erlbaum Associates Publishers, Mahwah, NJ, 1998].
Feature centrality and property induction
Authors: Hadjichristidis Constantinos , Sloman Steven , Stevenson Rosemary , Over David
Published: August 2005

A feature is central to a concept to the extent that other features depend on it. Four studies tested the hypothesis that people will project a feature from a base concept to a target concept to the extent that they believe the feature is central to the two concepts. This centrality hypothesis implies that feature projection is guided by a principle that aims to maximize the structural commonality between base and target concepts. Participants were told that a category has two or three novel features. One feature was the most central in that more properties depended on it. The extent to which the target shared the feature's dependencies was manipulated by varying the similarity of category pairs. Participants' ratings of the likelihood that each feature would hold in the target category support the centrality hypothesis with both natural kind and artifact categories and with both well‐specified and vague dependency structures.
A rhythm recognition computer program to advocate interactivist perception
Authors: Buisson Jean‐Christophe
Published: August 2005

This paper advocates the main ideas of the interactive model of representation of Mark Bickhard and the assimilation/accommodation framework of Jean Piaget, through a rhythm recognition demonstration program. Although completely unsupervised, the program progressively learns to recognize more and more complex rhythms struck on the user's keyboard. It does so without any recording of the input flow, and without any pattern matching in the usual sense. On the contrary, internal processes are dynamically constructed to follow and anticipate the user's actions. We show that these processes are representations of the rhythms in the interactivist sense, and that they emerge from non representational grounds, avoiding the symbol‐grounding problem. They are not copies or transductions of reality, but ideal internal constructions of the agent, avoiding the circularity pointed out by Piaget. In practice, the active nature of this recognition process allows it to work even with noisy and complex input flows.
Modelling the effects of semantic ambiguity in word recognition
Authors: Rodd Jennifer M. , Gaskell M. Gareth , Marslen‐Wilson William D.
Published: August 2005

Most words in English are ambiguous between different interpretations; words can mean different things in different contexts. We investigate the implications of different types of semantic ambiguity for connectionist models of word recognition. We present a model in which there is competition to activate distributed semantic representations. The model performs well on the task of retrieving the different meanings of ambiguous words, and is able to simulate data reported by Rodd, Gaskell, and Marslen‐Wilson [J. Mem. Lang. 46 (2002) 245] on how semantic ambiguity affects lexical decision performance. In particular, the network shows a disadvantage forwords with multiple unrelated meanings (e.g., bark) that coexists with a benefit for words with multiple related word senses (e.g., twist). The ambiguity disadvantage arises because of interference between the different meanings, while the sense benefit arises because of differences in the structure of the attractor basins formed during learning. Words with few senses develop deep, narrow attractor basins, while words with many senses develop shallow, broad basins. We conclude that the mental representations of word meanings can be modelled as stable states within a high‐dimensional semantic space, and that variations in the meanings of words shape the landscape of this space.
Pragmatic effects on reference resolution in a collaborative task: evidence from eye movements
Authors: Hanna Joy E. , Tanenhaus Michael K.
Published: August 2005

In order to investigate whether addressees can make immediate use of speaker‐based constraints during reference resolution, participant addressees' eye movements were monitored as they helped a confederate cook follow a recipe. Objects were located in the helper's area, which the cook could not reach, and the cook's area, which both could reach. Critical referring expressions matched one object (helper's area) or two objects (helper's and cook's areas), and were produced when the cook's hands were empty or full, which defined the cook's reaching ability constraints. Helper's first and total fixations showed that they restricted their domain of interpretation to their own objects when the cook's hands were empty, and widened it to include the cook's objects only when the cook's hands were full. These results demonstrate that addressees can quickly take into account task‐relevant constraints to restrict their referential domain to referents that are plausible given the speaker's goals and constraints.
Children's attributions of beliefs to humans and God: cross‐cultural evidence
Authors: Knight Nicola , Sousa Paulo , Barrett Justin L. , Atran Scott
Published: August 2005

The capacity to attribute beliefs to others in order to understand action is one of the mainstays of human cognition. Yet it is debatable whether children attribute beliefs in the same way to all agents. In this paper, we present the results of a false‐belief task concerning humans and God run with a sample of Maya children aged 4–7, and place them in the context of several psychological theories of cognitive development. Children were found to attribute beliefs in different ways to humans and God. The evidence also speaks to the debate concerning the universality and uniformity of the development of folk‐psychological reasoning.
Comparing expert and novice understanding of a complex system from the perspective of structures, behaviors, and functions
Authors: Hmelo‐Silver Cindy E. , Pfeffer Merav Green
Published: August 2005

Complex systems are pervasive in the world around us. Making sense of a complex system should require that a person construct a network of concepts and principles about some domain that represents key (often dynamic) phenomena and their interrelationships. This raises the question of how expert understanding of complex systems differs from novice understanding. In this study we examined individuals' representations of an aquatic system from the perspective of structural (elements of a system), behavioral (mechanisms), and functional aspects of a system. Structure–Behavior–Function (SBF) theory was used as a framework for analysis. The study included participants from middle school children to preservice teachers to aquarium experts. Individual interviews were conducted to elicit participants' mental models of aquaria. Their verbal responses and pictorial representations were analyzed using an SBF‐based coding scheme. The results indicated that representations ranged from focusing on structures with minimal understanding of behaviors and functions to representations that included behaviors and functions. Novices' representations focused on perceptually available, static components of the system, whereas experts integrated structural, functional, and behavioral elements. This study suggests that the SBF framework can be one useful formalism for understanding complex systems.
Reverse correlation in neurophysiology
Authors: Ringach Dario , Shapley Robert
Published: August 2005

This article presents a review of reverse correlation in neurophysiology. We discuss the basis of reverse correlation in linear transducers and in spiking neurons. The application of reverse correlation to measure the receptive fields of visual neurons using white noise and m‐sequences, and classical findings about spatial and color processing in the cortex resulting from such measurements, are emphasized. Finally, we describe new developments in reverse correlation, including “sub‐space” and categorical reverse‐correlation. Recent results obtained by applying such methods in the orientation, spatial‐frequency and Fourier domains have revealed the importance of cortical inhibition in the establishment of sharp tuning selectivity in single neurons.
Characterizing perceptual learning with external noise
Authors: Gold Jason M. , Sekuler Allison B. , Bennett Partrick J.
Published: August 2005

Performance in perceptual tasks often improves with practice. This effect is known as ‘perceptual learning,’ and it has been the source of a great deal of interest and debate over the course of the last century. Here, we consider the effects of perceptual learning within the context of signal detection theory. According to signal detection theory, the improvements that take place with perceptual learning can be due to increases in internal signal strength or decreases in internal noise. We used a combination of psychophysical techniques (external noise masking and double‐pass response consistency) that involve corrupting stimuli with externally added noise to discriminate between the effects of changes in signal and noise as observers learned to identify sets of unfamiliar visual patterns. Although practice reduced thresholds by as much as a factor of 14, internal noise remained virtually fixed throughout training, indicating learning served to predominantly increase the strength of the internal signal. We further examined the specific nature of the changes that took place in signal strength by correlating the externally added noise with observer's decisions across trials (response classification). This technique allowed us to visualize some of the changes that took place in the linear templates used by the observers as learning occurred, as well as test the predictions of a linear template‐matching model. Taken together, the results of our experiments offer important new theoretical constraints on models of perceptual learning.
Making the ineffable explicit: estimating the information employed for face classifications
Authors: Mangini Michael C. , Biederman Irving
Published: August 2005

When we look at a face, we readily perceive that person's gender, expression, identity, age, and attractiveness. Perceivers as well as scientists have hitherto had little success in articulating just what information we are employing to achieve these subjectively immediate and effortless classifications. We describe here a method that estimates that information. Observers classified faces in high levels of visual noise as male or female (in a gender task), happy/unhappy (in an expression task), or Tom Cruise/John Travolta (in an individuation task). They were unaware that the underlying face (which was midway between each of the classes) was identical throughout a task, with only the noise rendering it more like one category value or the other. The difference between the average of noise patterns for each classification decision provided a linear estimate of the information mediating these classifications. When the noise was combined with the underlying face, the resultant images appeared to be excellent prototypes of their respective classes. Other methods of estimating the information employed in complex classification have relied on judgments of exemplars of a class or tests of experimenter‐defined hypotheses about the class information. Our method allows an estimate, however subtle, of what is in the subject's (rather than the experimenter's) head.
Classification objects, ideal observers & generative models
Authors: Olman Cheryl , Kersten Daniel
Published: August 2005

A successful vision system must solve the problem of deriving geometrical information about three‐dimensional objects from two‐dimensional photometric input. The human visual system solves this problem with remarkable efficiency, and one challenge in vision research is to understand howneural representations of objects are formed and what visual information is used to form these representations. Ideal observer analysis has demonstrated the advantages of studying vision from the perspective of explicit generative models and a specified visual task, which divides the causes of image variations into the separate categories of signal and noise. Classification image techniques estimate the visual information used in a task from the properties of “noise” images that interact most strongly with the task. Both ideal observer analysis and classification image techniques rely on the assumption of a generative model. We show here how the ability of the classification image approach to understand how an observer uses visual information can be improved by matching the type and dimensionality of the model to that of the neural representation or internal template being studied. Because image variation in real world object tasks can arise from both geometrical shape and photometric (illumination or material) changes, a realistic image generation process should model geometry as well as intensity. A simple example is used to demonstrate what we refer to as a “classification object” approach to studying three‐dimensional object representations.
Mapping visual attention with change blindness: new directions for a new method
Authors: Tse Peter U.
Published: August 2005

Change blindness provides a new technique for mapping visual attention with unprecedented spatial and temporal resolution. Change blindness can occur when a brief full‐field blank interferes with the detection of changes in a scene that occur during the blank. This interference can be overcome by attending to the location of a change. Because changes are detected at attended locations, but not at unattended locations, detection accuracy provides an indirect measure of the distribution of visual attention. The likelihood of detecting a new element in a scene provides a measure of the occurrence of attention at that element's location. Potential new directions, advantages, and problems with this method are considered.
Object recognition and Random Image Structure Evolution
Authors: Sadr Javid , Sinha Pawan
Published: August 2005

We present a technique called Random Image Structure Evolution (RISE) for use in experimental investigations of high‐level visual perception. Potential applications of RISE include the quantitative measurement of perceptual hysteresis and priming, the study of the neural substrates of object perception, and the assessment and detection of subtle forms of agnosia. In simple terms, RISE involves the measurement of perceptual and/or neural responses as visual stimuli are systematically transformed—in particular, as recognizable objects evolve from, then dissolve into, randomness. Points along the sequences corresponding to the onset and offset of subjects' percepts serve as markers for quantitatively and objectively characterizing several perceptual phenomena. Notably, these image sequences are created in a manner that strictly controls a number of important low‐level image properties, such as luminance and frequency spectra, thus reducing confounds in the analysis of high‐level visual processes. Here we describe the RISE paradigm, report the results of a few basic RISE experiments, and discuss a number of experimental and clinical applications of this approach.
Spatio‐temporal dynamics of face recognition in a flash: it's in the eyes
Authors: Vinette Céline , Gosselin Frédéric , Schyns Philippe G.
Published: August 2005

We adapted the Bubbles procedure [Vis. Res. 41 (2001) 2261] to examine the effective use of information during the first 282 ms of face identification. Ten participants each viewed a total of 5100 faces sub‐sampled in space–time. We obtained a clear pattern of effective use of information: the eye on the left side of the image became diagnostic between 47 and 94 ms after the onset of the stimulus; after 94 ms, both eyes were used effectively. This preference for the eyes increased with practice, and was not solely due to the informativeness of the eyes for the task at hand. The bias for the eye on the left side of the image is explained in terms of hemispheric specialization. Although there were individual differences, most participants exhibited this pattern of effective use of information. An intriguing finding is that most participants displayed a clear sinusoidal modulation of effective use of attention through time with a frequency of about 10.6 Hz.
Children's causal inferences from indirect evidence: Backwards blocking and Bayesian reasoning in preschoolers
Authors: Sobel David M. , Tenenbaum Joshua B. , Gopnik Alison
Published: August 2005

Previous research suggests that children can infer causal relations from patterns of events. However, what appear to be cases of causal inference may simply reduce to children recognizing relevant associations among events, and responding based on those associations. To examine this claim, in Experiments 1 and 2, children were introduced to a “blicket detector,” a machine that lit up and played music when certain objects were placed upon it. Children observed patterns of contingency between objects and the machine's activation that required them to use indirect evidence to make causal inferences. Critically, associative models either made no predictions, or made incorrect predictions about these inferences. In general, children were able to make these inferences, but some developmental differences between 3‐ and 4‐year‐olds were found. We suggest that children's causal inferences are not based on recognizing associations, but rather that children develop a mechanism for Bayesian structure learning. Experiment 3 explicitly tests a prediction of this account. Children were asked to make an inference about ambiguous data based on the base rate of certain events occurring. Four‐year‐olds, but not 3‐year‐olds were able to make this inference.
Varieties of sameness: the impact of relational complexity on perceptual comparisons*
Authors: Kroger James K. , Holyoak Keith J. , Hummel John E.
Published: August 2005

The fundamental relations that underlie cognitive comparisons—“same” and “different”—can be defined at multiple levels of abstraction, which vary in relational complexity. We compared response times to decide whether or not two sequentially‐presented patterns, each composed of two pairs of colored squares, were the same at three levels of abstraction: perceptual, relational, and system (higher order relations). For both 150 ms and 5 s inter‐stimulus intervals (ISIs), both with and without a masking stimulus, decision time increased with level of abstraction. Sameness at lower complexity levels contributed to decisions based on the higher levels. The pattern of comparison times across levelswas not predictable solely from encoding times. The results indicated that relations at multiple levels of complexity can be abstracted and compared in working memory, with higher complexity levels requiring more processing time. We simulated the impact of relational complexity on response time using Learning and Inference with Schemas and Analogies (LISA), a computational model of relational comparisons based on dynamic binding of elements into roles in a relational working memory.
Soft constraints in interactive behavior: the case of ignoring perfect knowledge in‐the‐world for imperfect knowledge in‐the‐head*,**
Authors: Gray Wayne D. , Fu Wai‐Tat
Published: August 2005

Constraints and dependencies among the elements of embodied cognition form patterns or microstrategies of interactive behavior. Hard constraints determine which microstrategies are possible. Soft constraints determine which of the possible microstrategies are most likely to be selected. When selection is non‐deliberate or automatic the least effort microstrategy is chosen. In calculating the effort required to execute a microstrategy each of the three types of operations, memory retrieval, perception, and action, are given equal weight; that is, perceptual‐motor activity does not have a privileged status with respect to memory. Soft constraints can work contrary to the designer's intentions by making the access of perfect knowledge in‐the‐world more effortful than the access of imperfect knowledge in‐the‐head. These implications of soft constraints are tested in two experiments. In experiment 1 we varied the perceptual‐motor effort of accessing knowledge in‐the‐world as well as the effort of retrieving items from memory. In experiment 2 we replicated one of the experiment 1 conditions to collect eye movement data. The results suggest that milliseconds matter. Soft constraints lead to a reliance on knowledge in‐the‐head even when the absolute difference in perceptual‐motor versus memory retrieval effort is small, and even when relying on memory leads to a higher error rate and lower performance. We discuss the implications of soft constraints for routine interactive behavior, accounts of embodied cognition, and tool and interface design.
Artificial syntactic violations activate Broca's region
Authors: Petersson Karl Magnus , Forkstam Christian , Ingvar Martin
Published: August 2005

In the present study, using event‐related functional magnetic resonance imaging, we investigated a group of participants on a grammaticality classification task after they had been exposed to well‐formed consonant strings generated from an artificial regular grammar. We used an implicit acquisition paradigm in which the participants were exposed to positive examples. The objective of this studywas to investigate whether brain regions related to language processing overlap with the brain regions activated by the grammaticality classification task used in the present study. Recent meta‐analyses of functional neuroimaging studies indicate that syntactic processing is related to the left inferior frontal gyrus (Brodmann's areas 44 and 45) or Broca's region. In the present study, we observed that artificial grammaticality violations activated Broca's region in all participants. This observation lends some support to the suggestions that artificial grammar learning represents a model for investigating aspects of language learning in infants [TICS 4 (2000) 178] and adults [Proceedings of the National Academy of Sciences of United States of America 99 (2002) 529].
Special Sciences: still a flawed argument after all these years
Authors: Jones Todd Edwin
Published: August 2005

Jerry Fodor has argued that the multiple realizability argument, as discussed in his original “Special Sciences” article, “refutes psychophysical reductionism once and for all.” I argue that his argument in “Special Sciences” does no such thing. Furthermore, if one endorses the physicalism that most supporters of the “Special Sciences” view endorse, special science laws must be reducible, in principle. The compatibility of MR with reduction, however, need not threaten the autonomy of the special sciences.
On the spontaneous discovery of a mathematical relation during problem solving
Authors: Dixon James A. , Bangert Ashley S.
Published: August 2005

People spontaneously discover new representations during problem solving. Discovery of a mathematical representation is of special interest, because it shows that the underlying structure of the problem has been extracted. In the current study, participants solved gear‐system problems as part of a game. Although none of the participants initially used a mathematical representation, many discovered a parity‐based, mathematical strategy during problem solving. Two accounts of the spontaneous discovery of mathematical strategies were tested. According to the automatic schema abstraction hypothesis, experience with multiple, unique problem exemplars facilitates extraction of the parity relation. According to the comparison‐based abstraction hypothesis, explicitly comparing gear pathways that have different number, but the same parity, should result in extraction of parity. An event history analysis showed that accumulation of experiences with different‐number, same‐parity comparisons predicted discovery of parity; accumulation of unique exemplars did not. Results suggest that comparison‐based abstraction processes can lead to the discovery of a mathematical relation.
You'll see what you mean: Students encode equations based on their knowledge of arithmetic
Authors: McNeil Nicole M. , Alibali Martha W.
Published: August 2005

This study investigated the roles of problem structure and strategy use in problem encoding. Fourth‐grade students solved and explained a set of typical addition problems (e.g., 5 + 4 + 9 + 5 = _) and mathematical equivalence problems (e.g., 4 + 3 + 6 = 4 + _ or 6 + 4 + 5 = _ + 5). Next, they completed an encoding task in which they reconstructed addition and equivalence problems after viewing each for 5 s. Equivalence problems of the form 4 + 3 + 6 = 4 + _ overlap with a perceptual pattern found in traditional arithmetic problems (i.e., answer blank in final position), and students' encoding was poorest on problems of this type. Individual differences in encoding the equivalence problems were related to variations in strategy use. Some students solved blank‐final equivalence problems using the standard arithmetic strategy of performing all given operations on all given numbers. These students made more errors in encoding problem structure, but fewer errors in encoding the numbers, than did students who solved the problems using correct or other incorrect strategies. Moreover, students who expressed many strategies for solving the blank‐final equivalence problems made fewer errors in encoding problem structure, but more errors in encoding the numbers, than did students who expressed only a single strategy. Results highlight that encoding is intended to guide action and that prior experience can simultaneously facilitate and interfere with accurate encoding.
The conjunction fallacy: a misunderstanding about conjunction?
Authors: Tentori Katya , Bonini Nicolao , Osherson Daniel
Published: August 2005

It is easy to construct pairs of sentences X, Y that lead many people to ascribe higher probability to the conjunction X‐and‐Y than to the conjuncts X, Y. Whether an error is thereby committed depends on reasoners' interpretation of the expressions “probability” and “and.” We report two experiments designed to clarify the normative status of typical responses to conjunction problems.