Cognitive Psychology

How does the existence of case systems, and strict word order patterns affect the learnability of a given language? We present a series of connectionist simulations, suggesting that both case and strict word order may facilitate syntactic acquisition by a sequential learning device. Our results are consistent with typological data concerning the frequencies with which different type of word order patterns occur across the languages of the world. Our model also accommodates patterns of syntactic development across several different languages. We conclude that non-linguistic constraints on general sequential-learning devices may help explain the relationship between case, word order, and learnability of individual languages.

Psycholinguistics refers to the empirical study of the human language processing system, typically using behavioral experiments. This chapter considers attempts to capture psycholinguistic data using connectionist models . We primarily focus on relatively 'early' aspects of speech processing--speech segmentation and word recognition.

Because I don't know what a cultural imaginary is, nor how to put (or find) something in one, I propose instead to provide a brief, general account of what, when we think and write about, and thereby determine, the characteristics of mindedness, the members of my tribe imagine themselves to be doing.

A s y m bol is a pattern (of physical marks, electromagnetic energy, e t c . ) which denotes, designates, or otherwise has meaning. The notion that intelligence requires the use and manipulation of symbols, and that humans are therefore symbol systems, has been extremely in uential in arti cial intelligence.

For the least the last 10 years, there has been growing interest in, and growing evidence for, the intimate relations between more abstract or higher order cognition-such as reasoning, planning, and language use-and the more concrete, immediate, or lower order operations of the perceptual and motor systems that support seeing, feeling, moving, and manipulating. A sub-fi eld of the larger research program in embodied cognition

This article presents a model of long term forgetting based on 3 ideas: (a) Memory for a stimulus can be described by a population of accessible traces; (b) probability of retrieval after a delay is predicted by the proportion of traces in this population that will be defined as correct if sampled; and (c) this population is diluted over time by null traces that, if accessed, block retrieval. Dilution is modeled as a linear function of time and outcome of accessing memories by their temporal organization. The model is applied to 5 published experiments studying forgetting in cued recall, 4 recognition experiments, and 1 using savings methods. The model specifies the different form of the retention function in each case well and provides a principled explanation for some puzzling characteristics of forgetting without recourse to mechanisms such as decay or consolidation.

In 4 experiments, rats were given intermixed or blocked preexposure to an array of landmarks that subsequently defined the location of a hidden goal in a Morris pool task. Previous research has shown that intermixed preexposure to pairs of adjacent landmarks retards learning whereas preexposure to individual landmarks facilitates subsequent learning (J. Prados, V. D. Chamizo, & N. J. . Accordingly, in Experiment 1, intermixed and blocked preexposure to pairs of adjacent landmarks was found to retard learning. In Experiment 2, however, a scheduling effect was found: Rats given intermixed preexposure to the individual landmarks learned faster than rats given blocked or no preexposure. Experiment 3 showed that intermixed (but not blocked) preexposure to pairs of landmarks resulted in a facilitatory effect when preexposure and test were carried out in different contexts. Experiment 4 replicated within a single experiment the main results observed in Experiments 1 and 3. This pattern of results suggests that intermixed preexposure engages learning processes other than latent inhibition that facilitate subsequent learning of the navigation task.

Contrast coding has been reported to differ between dyslexic and normal readers. Dyslexic readers require higher levels of contrast to detect sinewave gratings for certain spatiotemporal conditions, and dyslexic readers show faster visual search at low contrast. We investigated whether these differences in early contrast coding generalize to reading performance by measuring reading speed as a function of text contrast for dyslexic children and adults and for age-matched controls. Contrast affected reading performance of dyslexic and normal readers similarly. For both groups, reading speed was relatively constant between 100 and 2% contrast, and decreased rapidly below 2% contrast. This pattern of results held true for both children and adults, for text with and without sentence context, across a range of character sizes, and for reading aloud and reading silently. We conclude that earlier findings of group differences in contrast effects on grating detection or visual search tasks do not generalize to reading.

This article details a study which predicted that across a wide range of print sizes dyslexic reading would follow the same curve shape as skilled reading, with constant reading rates across large print sizes and a sharp decline in reading rates below a critical print size. It also predicted that dyslexic readers would require larger critical print sizes to attain their maximum reading speeds, following the letter position coding deficit hypothesis. Reading speed was measured across twelve print sizes ranging from Snellen equivalents of 20/12 to 20/200 letter sizes for a group of dyslexic readers in Grades 2 to 4 (aged 7 to 10 years), and for non-dyslexic readers in Grades 1 to 3 (aged 6 to 8 years). The groups were equated for word reading ability. Results confirmed that reading rate-by-print size curves followed the same two-limbed shape for dyslexic and non-dyslexic readers. Dyslexic reading curves showed higher critical print sizes and shallower reading rate-by-print size slopes below the critical print size, consistent with the hypothesis of a letter-position coding deficit. Non-dyslexic reading curves also showed a decrease of critical print size with age. A developmental lag model of dyslexic reading does not account for the results, since the regression of critical print size on maximum reading rate differed between groups.

Previous studies have shown that change detection performance is improved when the visual display holds features (e.g., a colour and an orientation) that are grouped into different parts of the same object compared to when they are all spatially separated (Xu, 2002a, 2002b). These findings indicate that visual short-term memory (VSTM) encoding can be “object-based”. Recently, however, it has been demonstrated that changing the orientation of an item could affect the spatial configuration of the display (Jiang, Chun, & Olson, 2004), which may have an important influence on change detection. The perceptual grouping of features into an object obviously reduces the amount of distinct spatial relations in a display, and hence the complexity of the spatial configuration. In the present study, we ask whether the object-based encoding benefit observed in previous studies may reflect the use of configural coding rather than the outcome of a true object-based effect. The results show that when configural cues are removed, the object-based encoding benefit remains for features (i.e., colour and orientation) from different parts of an object, but is significantly reduced. These findings support the view that memory for features from different parts of an object can benefit from object-based encoding, but the use of configural coding significantly helps enlarge this effect.

In this article, we propose that adolescents' online interactions are both a literal and a metaphoric screen for representing major adolescent developmental issues, such as sexuality and identity. Because of the public nature of Internet chat rooms, they provide an open window into the expression of adolescent concerns. Our study utilizes this window to explore how issues of sexuality and identity are constructed in a teen chat room. We adapt qualitative discourse methodology to microanalyze a half-hour transcript from a monitored teen chat room, comparing it, where relevant, to a second transcript, used in a prior study [Greenfield, P.M., Subrahmanyam, K., 2003. Online discourse in a teen chat room: New codes and new modes of coherence in a visual medium. Journal of Applied Developmental Psychology 24, 713-738.]. Our microanalysis reveals that participants use the online space of teen chat to air adolescent concerns about sexuality and to develop creative strategies to exchange identity information with their peers. This exchange is critical to the activity of bpairing offQ, an important teenage expression of emerging sexuality. Developmental issues from adolescents' offline lives are reconstructed online with some important differences. The virtual world of teen chat may offer a safer environment for exploring emerging sexuality than the real world. Through the verbally explicit exchange of identity information, participants are able to bpair offQ with partners of their choice, despite the disembodied nature of chat participants. D

Because causal relations are neither observable nor deducible, they must be induced from observable events. The 2 dominant approaches to the psychology of causal induction-the covariation approach and the causal power approach-are each crippled by fundamental problems. This article proposes an integration of these approaches thai overcomes these problems. The proposal is that reasoners innately treat the relation between covariation (a function denned in terms of observable events) and causal power (an unobservable entity) as that between scientists' law or model and their theory explaining the model. This solution is formalized in the power PC theory, a causal power theory of the probabilistic contrast model (P. W. Cheng & L. R. . The article reviews diverse old and new empirical tests discriminating this theory from previous models, none of which is justified by a theory. The results uniquely support the power PC theory.

In this chapter, we describe four psychological phenomena that offer clues to how untutored people infer causal relations. We contrast the predictions for these phenomena, all involving asymmetries in causal inferences, according to two psychological approaches-an associationist approach (e.analysis reveals that each phenomenon is inexplicable by associationist models but follows coherently from a causal theory. What distinguishes these approaches is that the causal theory has the goal of explaining the occurrence of a target event by the potentially independent influences of candidate causes and other (background) causes. This goal has no analogue in associationist models. To arrive at a coherent explanation, the causal account creates a theoretical construct of causal power (Cartwright 1989)the probability with which a cause influences an effect. According to this account, reasoners search for, or define, candidate causes with the goal of arriving at causes that influence a target effect independently of the background causes. In other words, they seek causes whose powers are (ideally) invariant regardless of how frequently the background causes occur (see Woodward 2003, for a discussion of the degree of invariance and depth of explanation; also see Haavelmo 1944, for a discussion of causes varying on degree of autonomy).

Five experiments investigated transfer from multiple analogs to a superficially dissimilar target problem. When subjects explicitly compared the analogs and then immediately attempted to solve the target problem in the context of a single experiment, transfer was obtained with significant frequency even without a hint that the analogs and target were related. Prehint transfer was sharply reduced or eliminated when the source analogs and the target were presented in different contexts, even when the transfer test was immediate. However, prehint transfer was enhanced, even after a context shift and a week-long delay between reading the source analogs and solving the problem, when the following conditions were met: The target problem was reworded slightly to emphasize a structural feature that it shared with the analogs; three rather than two source analogs were provided; and detailed, schema-oriented questions were used to help subjects focus on the problem-relevant aspects of the stories. Although spontaneous transfer between small numbers of dissimilar analogs is difficult to obtain, it can be achieved by manipulations that foster abstraction of a problem schema from the training examples.

This article proposes that learning of categories based on cause-effect relations is guided by causal models. In addition to incorporating domain-specific knowledge, causal models can be based on knowledge of such general structural properties as the direction of the causal arrow and the variability of causal variables. Five experiments tested the influence of commoncause models and common-effect models on the ease of learning linearly separable and nonlinearly separable categories. The results show that causal models guide the interpretation of otherwise identical learning inputs, and that learning difficulty is determined by the fit between the structural implications of the causal models and the structure of the learning domain. These influences of the general properties of causal models were obtained across several different content domains, including domains for which subjects lacked prior knowledge.

Theories of analogical reasoning differ in the roles they ascribe to pragmatic factors as a source of constraints on analogical mappings. The multiconstraint theory as instantiated in the ACME model claims that pragmatic constraints interact with structural and semantic constraints within the mapping stage itself, in addition to influencing pre-mapping and post-mapping stages. Participants in three experiments were asked to generate mappings between non-isomorphic analogs for which mappings for some elements were ambiguous on structural grounds. In all experiments, manipulations of participants' processing goals influenced their preferred mappings. At the same time, goal-irrelevant information contributed to many-to-one mappings (Experiments 1 and 2) and to the resolution of mappings that were ambiguous on the basis of goal-relevant information alone (Experiment 3). The qualitative pattern of results was successfully simulated using the ACME model, implementing the impact of processing goals as an inhibitory process of selective attention. ᭧ 1996 Academic Press, Inc.

The use of analogy in human thinking is examined from the perspective of a multiconstraint theory, which postulates 3 basic types of constraints: similarity, structure, and purpose. The operation of these constraints is apparent in laboratory experiments on analogy and in naturalistic settings, including politics, psychotherapy, and scientific research. The multiconstraint theory has been implemented in detailed computational simulations of the analogical human mind.

Theories of analogical reasoning have assumed that a 1-to-1 constraint discourages reasoners from mapping a single element in 1 analog to multiple elements in another. Empirical evidence suggests that reasoners sometimes appear to violate the 1-to-1 constraint when asked to generate mappings, yet virtually never violate it when asked to generate analogical inferences. However, few studies have examined analogical inferences based on nonisomorphic analogs, and their conclusions are suspect due to methodological problems. We sought to elicit mixed inferences that could result from combining information from 2 possible mappings. Participants generated 2-to-1 correspondences when asked for explicit mappings, but did not produce mixed inferences. Multiple correspondences appear to arise from multiple isomorphic mappings, rather than from a single homomorphic mapping.

We present a Bayesian model of causal learning that incorporates generic priors on distributions of weights representing potential powers to either produce or prevent an effect. These generic priors favor necessary and sufficient causes. Across three experiments, the model explains the systematic pattern of human judgments observed for questions regarding support for a causal link, for both generative and preventive causes.

The lateral posterior nucleus and pulvinar (LP-pulvinar complex) are the principal thalamic nuclei associated with the elaborate development of the dorsal and ventral streams of the parietal cortex in primates. In humans, a novel site of origin for a subpopulation of pulvinar neurons has been observed, the ganglionic eminence of the telencephalon. This additional site of neuron origin has been proposed to contribute to the pulvinar's evolutionary expansion Nat Neurosci 4:930 -936). Studies of neuron number in the LP-pulvinar complex in gibbon, chimpanzee, and gorilla compared to humans, however, did not show that the human LPpulvinar was unexpectedly large (Armstrong [1981] Am J Phys Anthropol 55:369 -383). Here we enlarge the allometric basis for comparison by determining neuron number in the LP-pulvinar complex of six New World primates (Cebus apella, Saimiri ustius, Saguinus midas niger, Alouatta caraya, Aotus azarae, and Callicebus moloch) as well as measuring LP-pulvinar volume in a further set of 24 species including additional primates, carnivores, and rodents. The volume of the LP-pulvinar complex scaled with positive allometry with respect to brain volume across all species examined. The scaling of the number of neurons in the LP-pulvinar complex was extremely similar in New World primates and anthropoid apes, with the human LP-pulvinar value close to the regression line. Comparison of the relative volumes of the LP-pulvinar in the larger sample confirmed this observation, and further demonstrated that both primates and carnivores showed a "grade shift" in its size compared to rodents, with the pulvinar comprising a greater proportion of total brain volume across the board. Diurnal, nocturnal, or crepuscular niche did not discriminate LP-pulvinar size across taxa.

Designing auditory displays requires understanding how different attributes of sound are processed. Operators must often listen to a particular stimulus dimension and make control actions contingent on the auditory information. Three experiments used a selective-listening paradigm to examine interactions between auditory dimensions. Participants were instructed to attend to either relative pitch or direction of pitch change of dynamic stimuli. With vertically arranged keypress responses, reactions to both dimensions showed stimulus-response compatibility effects, indicating that pitch is treated spatially. Direction of pitch change affected responses to pitch; level of pitch more strongly affected responses to pitch change. To reduce deleterious effects of irrelevant pitch information, auditory display designers can restrict the pitch range used to display dynamic data.

Research on auditory graphs has investigated mappings, scalings, and polarities , as well as the addition of some contextual design features , in order to improve performance. However, little has been done to quantify the performance effects of such features, or to investigate effects of training in specific sonification tasks such as point estimation. Smith and Walker took a step towards quantifying and comparing the effects of adding several contextual design features. Presented here are selected results from a comprehensive follow-on study comparing effects of adding auditory context, either with or without training. The overall results indicate that some kinds of auditory context improved performance, while others did not. Training improved performance, and an interaction was discovered between type of auditory context and type of training . Implications are discussed.

Two eye-movement experiments examined the processing of sentences containing reduced relative constructions. In the first experiment, animacy of the sentential subject, structural ambiguity, and parafoveal preview of syntactically disambiguating material were manipulated. Evidence of disruption was found in temporarily ambiguous sentences, regardless of animacy or preview. In the second experiment, readers with high versus low verbal working memory capacity read the sentences from Experiment 1. High and low-span readers exhibited very similar patterns of processing. As in the first experiment, evidence for disruption was found in temporarily ambiguous sentences whether the sentential subject was animate or inanimate. Sentences with animate subjects were hard to interpret, and relatively late measures of processing indicated that an animate subject made ambiguity especially hard to overcome. We interpret the findings as being consistent with serial, depth-first models of parsing.

The techniques of computer vision have reached excellent results when applied in the different areas. These methods are used in the discovery of knowledge from images of the real world. This project aims to apply these techniques in morphometric analysis of biological species, trying to classify them. The morphometric analysis makes the extraction of measures in the most diverse structures, such as animals living organs, fruits, leaves, etc.. The development of the project was divided into three parts: (i) study and implementation of the techniques of computer vision (signatures, Fourier transform and curvature), (ii) analysis and extraction of characteristics of the biological images, (iii) classification of species through the techniques of pattern recognition (classification by minimum distance method). The results showed that the techniques of computer vision can be satisfactorily applied in the classification of biological species, which were able to classify correctly 81.82% of the species.

Why do we remember some events and not others, and how does this change in old age? Although there are a variety of ways to address this question, the present perspective emphasizes how value can have a profound eVect on how we use our memory to remember certain information. The ability to select and prioritize what information is important to remember, relative to less salient or peripheral information, is an essential skill for the eYcient use of memory. For example, university students seek to memorize information they think is important for a later test, while grandparents may focus on being able to remember information about children and grandchildren, as well as important life events. In both cases, value is used to direct resources toward information that is deemed to be important to remember. The role that value plays in memory performance is critical to develop a comprehensive understanding of how memory is used across the adult life span.

Observers were presented with pairs of objects varying along binary-valued attributes and learned to predict which member of each pair had a greater value on a continuously varying criterion variable. The predictions from exemplar models of categorization were contrasted with classic alternative models, including generalized versions of a "take-the-best" model and a weighted-additive model, by testing structures in which interactions between attributes predicted the magnitude of the criterion variable. Under typical training conditions, observers showed little sensitivity to the attribute interactions, thereby challenging the predictions from the exemplar models. In a condition involving highly extended training, observers eventually learned the relations between the attribute interactions and the criterion variable. However, an analysis of the observers' response times for making their paired-comparison decisions also challenged the exemplar model predictions. Instead, it appeared that most observers recoded the interacting attributes into emergent configural cues. They then applied a set of hierarchically organized rules based on the priority of the cues to make their decisions.

The authors develop and test generalized versions of take-the-best (TTB) and rational (RAT) models of multiattribute paired-comparison inference. The generalized models make allowances for subjective attribute weighting, probabilistic orders of attribute inspection, and noisy decision making. A key new test involves a response-time (RT) approach. TTB predicts that RT is determined solely by the expected time required to locate the 1st discriminating attribute, whereas RAT predicts that RT is determined by the difference in summed evidence between the 2 alternatives. Critical test pairs are used that partially decouple these 2 factors. Under conditions in which ideal observer TTB and RAT strategies yield equivalent decisions, both the RT results and the estimated attribute weights suggest that the vast majority of subjects adopted the generalized TTB strategy. The RT approach is also validated in an experimental condition in which use of a RAT strategy is essentially forced upon subjects.

Speeded perceptual classification experiments were conducted to distinguish among the predictions of exemplar-retrieval, decision-boundary, and prototype models. The key manipulation was that across conditions, individual stimuli received either probabilistic or deterministic category feedback. Regardless of the probabilistic feedback, however, an ideal observer would always classify the stimuli by using an identical linear decision boundary. Subjects classified the probabilistic stimuli with lower accuracy and longer response times than they classified the deterministic stimuli. These results are in accord with the predictions of the exemplar model and challenge the predictions of the prototype and decision-boundary models.

Multidimensional scaling (MDS) techniques provide a promising measurement strategy for characterizing individual differences in cognitive processing, which many clinical theories associate with the development, maintenance, and treatment of psychopathology. The authors describe the use of deterministic and probabilistic MDS techniques for investigating numerous aspects of perceptual organization, such as dimensional attention, perceptual correlation, within-attribute organization, and perceptual variability. Additionally, they discuss how formal quantitative models can be used, in conjunction with MDS-derived representations of individual differences in perceptual organization, to test theories about the role of cognitive processing in clinically relevant phenomena. They include applied examples from their work in the areas of eating disorders and sexual coercion.

Experiments were conducted in which observers learned to classify simple perceptual stimuli into low-variability and high-variability categories. Similarities between objects were measured in independent psychological-scaling tasks. The results showed that observers classified transfer stimuli into the high-variability categories with greater probability than was predicted by a baseline version of an exemplar-similarity model. Qualitative evidence for the role of category variability on perceptual classification, which could not be explained in terms of the baseline exemplar-similarity model, was obtained as well. Possible accounts of the effects of category variability are considered in the General Discussion section.

R. M. Nosofsky and T. J. Palmeri's (1997) exemplar-based random-walk (EBRW) model of speeded classification is extended to account for speeded same-different judgments among integral-dimension stimuli. According to the model, an important component process of same-different judgments is that people store individual examples of experienced same and different pairs of objects in memory. These exemplar pairs are retrieved from memory on the basis of how similar they are to a currendy presented pair of objects. The retrieved pairs drive a random-walk process for making same-different decisions. The EBRW predicts correctly that same responses are faster for objects lying in isolated than in dense regions of similarity space. The model also predicts correctly effects of same-identity versus samecategory instructions and is sensitive to observers' past experiences with specific same and different pairs of objects.

The authors propose and test an exemplar-based random walk model for predicting response times in tasks of speeded, multidimensional perceptual classification. The model combines elements of R.M. Nosofsky's (1986) generalized context model of categorization and G. D. instance-based model of automaticity. In the model, exemplars race among one another to be retrieved from memory, with rates determined by their similarity to test items. The retrieved exemplars provide incremental information that enters into a random walk process for making classification decisions. The model predicts correctly effects of within-and between-categories similarity, individual-object familiarity, and extended practice on classification response times. It also builds bridges between the domains of categorization and automaticity.

The authors compared the exemplar-based random-walk (EBRW) model of and the decision-bound model (DBM) of on their ability to predict performance in Garner's (1974) speeded classification tasks. A key question was the extent to which the models could predict facilitation in the correlated task and interference in the filtering task, in situations involving integral-dimension stimuli. To obtain rigorous constraints for model evaluation, the goal was to fit the detailed structure of the response time (RT) distribution data associated with each individual stimulus in each task. Both models yielded reasonably good global quantitative fits to the RT distribution and accuracy data. However, the DBM failed to properly characterize the interference effects in the filtering task. Apparently, a fundamental limitation of the DBM is that it predicts that the fastest RTs in the filtering task should be faster than the fastest RTs in the control task, whereas the opposite pattern was observed in our data.

A formal proof is pnnided that Anderson's {1990) rational model of categorization generalizes the Medin and Schaffer {1978) context model. According to the context model, people represent categ<>ries by storing individual exemplars in memoiy. According to the rational mode!, people represent categories in terms of midtiple exemplarclusters or prototypes. In both models, a multiplicative rule is used to compute the similarity of an item to the underlying category representations. In certain special cases, each multiple prototype in the rational model corresponds to an individual exemplar, and in these cases the rational model reduces to the context model. Preliminary quantitative comparisons between the models are illustrated to test whether the multiple-prototype view adds significant explanatory power over the pure exemplar view.

A rule-instantiation model and a similarity-to-exemplars model were contrasted in terms of their predictions of typicality judgments and speeded classificalions-for-members-oflogically defined categories. In Experiment 1, subjects learned a unidimensional rule based on the size of objects. It was assumed that items that maximally instantiated the rule were those farthest from the category boundary that separated small and large stimuli. In Experiment 2, subjects learned a disjunctive rule ofthe form "x or y or both." It was assumed that items that maximally instantiated the rule were those with both positive values (x and y). In both experiments, the frequency with which different exemplars were presented during classification learning was manipulated across conditions. These frequency manipulations exerted a major impact on subjects' postacquisition goodness-of-example judgments, and they also influenced reaction times in a speeded classification task. The results could not be predicted solely on the basis of the degree to which the rules were instantiated. The goodnessjudgments were predicted fairly well by a mixed-exemplar model involving both relative-similarity and absolute-similarity components. It was concluded that even for logically defined concepts, stored exemplars may form a major component of the category representation.

Subjects learned to classify perceptual stimuli varying along continuous, separable dimensions into rule-described categories. The categories were designed to contrast the predictions of a selective-attention exemplar model and a simple rule-based model formalizing an economy-ofdescription view. Converging evidence about categorization strategies was obtained by also collecting identification and recognition data and by manipulating strategies via instructions. In free-strategy conditions, the exemplar model generally provided an accurate quantitative account of identification, categorization, and recognition performance, and it allowed for the interrelationship of these paradigms within a unified framework. Analyses of individual subject data also provided some evidence for the use of rules, but in general, the rules seemed to have a great deal in common with exemplar storage processes. Classification and recognition performance for subjects given explicit instructions to use specific rules contrasted dramatically with performance in the free-strategy conditions and could not be predicted by the exemplar model.

Previously published sets of classification and old-new recognition memory data are reanalyzed within the framework of an exemplar-based generalization model. The key assumption in the model is that, whereas classification decisions are based on the similarity of a probe to exemplars of a target category relative to exemplars of contrast categories, recognition decisions are based on overall summed similarity of a probe to all exemplars. The summed-similarity decision rule is shown to be consistent with a wide variety of recognition memory data obtained in classification learning situations and may provide a unified approach to understanding relations between categorization and recognition.

The bow and sequential effects in absolute identification are investigated in this paper by following two strategies: (1)Experiments are performed in which sequential dependencies in signal presentations are manipulated, and (2)analyses are conducted (some of which are largely free of model-specific assumptions) which bear directly on the question of the origin of the sequential effects. The main result of the study is that absolute identification performance is greatly improved in a design in which each signal lies close to the preceding signal presented, even though the entire range of signals used is the same as in a random presentation design. This finding is consistent with the attention-band model of and rejects hypotheses that suggest that the variability in the signal representation in absolute identification is a function solely of the range of signals being used. However, nonparametric analyses of sequential response errors show that a plausible assumption concerning the trial. by-trial movement of the attention band provides an incomplete explanation of sequential effects in absolute identification. These results are far better explained in terms of systematic shifts of category boundaries in a Thurstonian model, as suggested by Purks, Callahan, Braida, and Durlach (1980). Experiments are also performed which suggest that memory decay is not the major factor accounting for the bow effect in absolute identification.

In this chapter, I consider how objects might phenomenally look to beings with more coarse-grained visual systems than us. Many hold that to such beings, objects may phenomenally look red, without phenomenally looking a particular shade of red. David Armstrong expresses this intuition as follows: ‘It is perfectly possible… to have a mental image of a piece of crimson cloth of no particular shade of crimson.’ In this chapter I try to make intuitions of the kind that Armstrong has precise, and I try to make some progress towards evaluating them.