Tasty non-words and neighbours: The cognitive roots of lexical-gustatory synaesthesia

For lexical-gustatory synaesthetes, words trigger automatic, associated food sensations (e.g., for JB, the word slope tastes of over-ripe melon). Our study tests two claims about this unusual condition: that synaesthetic tastes are associated with abstract levels of word representation (concepts/lemmas), and that the first tastes to crystallise in early development are those triggered by food-names (e.g., apple tastes of apple; Simner & Ward, 2006). This concept/lemma-based proposal is difficult to immediately reconcile with the finding that non-words may also generate tastes (Ward, Simner, & Auyeung, 2005), since non-words have no concept/lemma representations. We manipulated the characteristics of non-words to provide three types of evidence that non-word tastes in fact stem from real word neighbours: Non-words with neighbours (e.g., keach) are more likely to generate tastes than those with no neighbours (e.g., vilps); pseudo-homophone non-words that are orthographically close to real words (e.g., peeple) are more likely to generate tastes than those that are more distant (baybee); and finally, the tastes of non-words are less consistent, and less intense, than those of real words. Additionally, we test the hypothesis that synaesthetic tastes develop initially from food-names by showing that non-words are more intensely flavoured if they are homophonic with food-names (e.g., toffie) versus non-foods (e.g., peeple). From this we conclude that synaesthetic tastes develop from food-names, and that tasty non-words do not challenge a concept/lemma-based account of lexical-gustatory synaesthesia.     

Coloured Letters and Numbers (CLaN): A reliable factor-analysis based synaesthesia questionnaire

Synaesthesia is a heterogeneous phenomenon, even when considering one particular sub-type. The purpose of this study was to design a reliable and valid questionnaire for grapheme-colour synaesthesia that captures this heterogeneity. By the means of a large sample of 628 synaesthetes and a factor analysis, we created the Coloured Letters and Numbers (CLaN) questionnaire with 16 items loading on 4 different factors (i.e., localisation, automaticity/attention, deliberate use, and longitudinal changes). These factors were externally validated with tests which are widely used in the field of synaesthesia research. The questionnaire showed good test–retest reliability and construct validity (i.e., internally and externally). Our findings are discussed in the light of current theories and new ideas in synaesthesia research. More generally, the questionnaire is a useful tool which can be widely used in synaesthesia research to reveal the influence of individual differences on various performance measures and will be useful in generating new hypotheses.     

Varieties of grapheme-colour synaesthesia: a new theory of phenomenological and behavioural differences

Recent research has suggested that not all grapheme-colour synaesthetes are alike. One suggestion is that they can be divided, phenomenologically, in terms of whether the colours are experienced in external or internal space (projector–associator distinction). Another suggestion is that they can be divided according to whether it is the perceptual or conceptual attributes of a stimulus that is critical (higher–lower distinction). This study compares the behavioural performance of 7 projector and 7 associator synaesthetes. We demonstrate that this distinction does not map on to behavioural traits expected from the higher–lower distinction. We replicate previous research showing that projectors are faster at naming their synaesthetic colours than veridical colours, and that associators show the reverse profile. Synaesthetes who project colours into external space but not on to the surface of the grapheme behave like associators on this task. In a second task, graphemes presented briefly in the periphery are more likely to elicit reports of colour in projectors than associators, but the colours only tend to be accurate when the grapheme itself is also accurately identified. We propose an alternative model of individual differences in grapheme-colour synaesthesia that emphasises the role of different spatial reference frames in synaesthetic perception. In doing so, we attempt to bring the synaesthesia literature closer to current models of non-synaesthetic perception, attention and binding.     

An associative account of the development of word learning

Word learning is a notoriously difficult induction problem because meaning is underdetermined by positive examples. How do children solve this problem? Some have argued that word learning is achieved by means of inference: young word learners rely on a number of assumptions that reduce the overall hypothesis space by favoring some meanings over others. However, these approaches have difficulty explaining how words are learned from conversations or text, without pointing or explicit instruction. In this research, we propose an associative mechanism that can account for such learning. In a series of experiments, 4-year-olds and adults were presented with sets of words that included a single nonsense word (e.g. dax). Some lists were taxonomic (i.,e., all items were members of a given category), some were associative (i.e., all items were associates of a given category, but not members), and some were mixed. Participants were asked to indicate whether the nonsense word was an animal or an artifact. Adults exhibited evidence of learning when lists consisted of either associatively or taxonomically related items. In contrast, children exhibited evidence of word learning only when lists consisted of associatively related items. These results present challenges to several extant models of word learning, and a new model based on the distinction between syntagmatic and paradigmatic associations is proposed.     

Familial patterns and the origins of individual differences in synaesthesia

The term synaesthesia has been applied to a range of different sensory-perceptual and cognitive experiences, yet how these experiences are related to each other is not well understood. Not only are there disparate types of synaesthesia, but even within types there are vast individual differences in the way that stimuli induce synaesthesia and in the subjective synaesthetic experience. An investigation of the inheritance patterns of different types of synaesthesia is likely to elucidate whether a single underlying mechanism can explain all types. This study is the first to systematically survey all types of synaesthesia within a familial framework. We recruited 53 synaesthetes and 42% of these probands reported a first-degree relative with synaesthesia. We then directly contacted as many first-degree relatives as possible and collected complete data on synaesthetic status for all family members for 17 families. We found that different types of synaesthesia can occur within the same family and that the qualitative nature of the experience can differ between family members. Our findings strongly indicate that various types of synaesthesia are fundamentally related at the genetic level, but that the explicit associations and the individual differences between synaesthetes are influenced by other factors. Synaesthesia thus provides a good model to explore the interplay of all these factors in the development of cognitive traits in general.     

Evidence against an occasion setting account of avoidance learning

Earlier studies on human avoidance learning showed that an avoidance response reduces the expectancy that a warning stimulus (WS) will be followed by an unconditioned stimulus (US). This modulation can transfer to WSs with which the avoidance response did not occur in the past. Recent studies suggest that transfer of modulation is selective in that it is stronger for WSs that previously went together with other avoidance responses than for WSs that never went together with an avoidance response. This finding has been interpreted as providing unique support for an occasion setting account of avoidance learning. We put forward alternative explanations of selective transfer of modulation in terms of the rate with which a WS was reinforced in the absence an avoidance response. In support of the alternative explanations, we found that transfer of modulation depended not on whether a WS previously went together with another avoidance response but on the rate with which the WS was reinforced in the past. We conclude that selective transfer of modulation in avoidance learning does not provide (unique) support for the occasion setting account. Our findings are in line with a revised expectancy model of avoidance learning.     

Prejudiced learning: A connectionist account

Connectionist simulation was employed to investigate processes that may underlie the relationships between prior expectancies or prejudices and the acquisition of attitudes, under conditions where learners can only discover the valence of attitude objects through directly experiencing them. We compared contexts analogous to learners holding either false negative expectancies (‘prejudices’) about a subclass of objects that were actually good or false positive expectancies about objects that were actually bad. We introduced expectancy‐related bias either by altering the probability of approach, or by varying the rate of learning following experience with good or bad objects. Where feedback was contingent on approach, the false positive expectancies were corrected by experience, but negative prejudices resisted change, since the network avoided objects deemed to be bad, and so received less corrective feedback. These findings are discussed in relation to the effects of intergroup contact and expectancy‐confirmation processes in reducing or sustaining prejudice.     

A dual-process account of digit invariance learning

Performance in the McGeorge and Burton (1990) digit invariance task was originally thought to be mediated by unconscious abstraction of a “rule” that identified the invariant feature across all study items. Subsequent explanations have suggested explicit strategy use or similarity-to-exemplar matching rather than abstraction. This paper presents data that suggest that both similarity and abstraction can be used under different task demands. Delay between study and test afforded abstraction of the invariant knowledge whereas reducing the pool of study exemplars enhanced responding based on specific similarity. These results parallel effects found in the categorization literature. Rule abstraction in this sense may be due to statistical learning of feature frequency rather than abstraction of a central tendency or a complex/conceptual rule. Categorizing responses into subjective memory states (remember/know/guess) demonstrates that neither the similarity matching nor the abstraction mechanism uses information from episodic memory. Confidence measures show that participants are more confident of responses when the prototypical representation is used but not specific similarity. Taken together, these data suggest that abstracted knowledge is not held consciously but that participants have meta-awareness of when they are using the abstracted representation.     

A dual-process account of digit invariance learning

Performance in the McGeorge and Burton (1990) digit invariance task was originally thought to be mediated by unconscious abstraction of a “rule” that identified the invariant feature across all study items. Subsequent explanations have suggested explicit strategy use or similarity-to-exemplar matching rather than abstraction. This paper presents data that suggest that both similarity and abstraction can be used under different task demands. Delay between study and test afforded abstraction of the invariant knowledge whereas reducing the pool of study exemplars enhanced responding based on specific similarity. These results parallel effects found in the categorization literature. Rule abstraction in this sense may be due to statistical learning of feature frequency rather than abstraction of a central tendency or a complex/conceptual rule. Categorizing responses into subjective memory states (remember/know/guess) demonstrates that neither the similarity matching nor the abstraction mechanism uses information from episodic memory. Confidence measures show that participants are more confident of responses when the prototypical representation is used but not specific similarity. Taken together, these data suggest that abstracted knowledge is not held consciously but that participants have meta-awareness of when they are using the abstracted representation.     

Numerical and nonnumerical estimation in children with and without mathematical learning disabilities

There are currently multiple explanations for mathematical learning disabilities (MLD). The present study focused on those assuming that MLD are due to a basic numerical deficit affecting the ability to represent and to manipulate number magnitude (Butterworth, 1999 Butterworth, B. 1999. The mathematical brain, London, , United Kingdom: Macmillan.  [Google Scholar], 2005 Butterworth, B. 2005. “Developmental dyscalculia”. In Handbook of mathematical cognition, Edited by: Campbell, J. I. D. 455–467. New York, NY: Psychology Press.  [Google Scholar]; A. J. Wilson &; Dehaene, 2007 Wilson, A. J. and Dehaene, S. 2007. “Number sense and developmental dyscalculia”. In Human behavior, learning, and the developing brain: Atypical development, 2nd, Edited by: Coch, D., Dawson, G. and Fischer, K. 212–237. New York, NY: Guilford Press.  [Google Scholar]) and/or to access that number magnitude representation from numerical symbols (Rousselle &; Noël, 2007 Rousselle, L. and Noël, M. P. 2007. Basic numerical skills in children with mathematics learning disabilities: A comparison of symbolic vs non-symbolic number magnitude processing. Cognition, 102(3): 361–395. [Crossref], [PubMed], [Web of Science ®] , [Google Scholar]). The present study provides an original contribution to this issue by testing MLD children (carefully selected on the basis of preserved abilities in other domains) on numerical estimation tasks with contrasting symbolic (Arabic numerals) and nonsymbolic (collection of dots) numbers used as input or output. MLD children performed consistently less accurately than control children on all the estimation tasks. However, MLD children were even weaker when the task involved the mapping between symbolic and nonsymbolic numbers than when the task required a mapping between two nonsymbolic numerical formats. Moreover, in the estimation of nonsymbolic numerosities, MLD children relied more than control children on perceptual cues such as the cumulative area of the dots. Finally, the task requiring a mapping from a nonsymbolic format to a symbolic format was the best predictor of MLD. In order to explain these present results, as well as those reported in the literature, we propose that the impoverished number magnitude representation of MLD children may arise from an initial mapping deficit between number symbols and that magnitude representation.     

Implicit learning of tonality: a self-organizing approach

Tonal music is a highly structured system that is ubiquitous in our cultural environment. We demonstrate the acquisition of implicit knowledge of tonal structure through neural self-organization resulting from mere exposure to simultaneous and sequential combinations of tones. In the process of learning, a network with fundamental neural constraints comes to internalize the essential correlational structure of tonal music. After learning, the network was run through a range of experiments from the literature. The model provides a parsimonious account of a variety of empirical findings dealing with the processing of tone, chord, and key relationships, including relatedness judgments, memory judgments, and expectancies. It also illustrates the plausibility of activation being a unifying mechanism underlying a range of cognitive tasks.     

A connectionist account of asymmetric category learning in early infancy

Young infants show unexplained asymmetries in the exclusivity of categories formed on the basis of visually presented stimuli. A connectionist model is described that shows similar exclusivity asymmetries when categorizing the same stimuli presented to infants. The asymmetries can be explained in terms of an associative learning mechanism, distributed internal representations, and the statistics of the feature distributions in the stimuli. The model was used to explore the robustness of this asymmetry. The model predicts that the asymmetry will persist when a category is acquired in the presence of mixed category exemplars. An experiment with 3-4-month-olds showed that asymmetric exclusivity persisted in the presence of mixed-exemplar familiarization, thereby confirming the model's prediction.     

Not all same-different discriminations are created equal: Evidence contrary to a unidimensional account of same-different learning

In Experiment 1, we trained four pigeons to concurrently discriminate displays of 16 same icons (16S) from displays of 16 different icons (16D) as well as between displays of same icons (16S) from displays that contained 15 same icons and one different icon (15S:1D). The birds rapidly learned to discriminate 16S vs. 16D displays, but they failed to learn to discriminate 16S vs. 15S:1D displays. In Experiment 2, the same pigeons acquired the 16S vs. 15S:1D task after being required to locate and peck at the odd-item in the 15S:1D displays. Acquisition of the 16S vs. 15S:1D task had little effect on discriminative performance in the concurrent 16S:16D task, suggesting that a unidimensional entropy explanation for mastery of these two same-different tasks is not viable. During testing, the birds transferred discriminative performance in both tasks to displays composed of different visual stimuli. Such concurrent discrimination learning, performance, and transfer suggest that pigeons are flexible in the way they process the displays seen in these two same-different tasks.     

An account of the relationship between fluid intelligence and complex learning in considering storage capacity and executive attention

Although fluid intelligence and complex learning are conceptualized differently and assessed by apparently different measures, both theoretical accounts and empirical evidence suggest a relationship between the two constructs. In this study, major working memory aspects including the storage capacity and executive attention were proposed to account for the relationship between fluid intelligence and complex learning. A sample of 184 participants completed fluid intelligence and complex learning scales, as well as working memory measures that each included two or three treatment levels differing in the demands on capacity or executive control. The differences among the treatment levels provided a favorable precondition for employing fixed-links models to separate the core processes of storage capacity or executive attention from the auxiliary processes. Results indicated that both storage capacity and executive attention contributed significantly to fluid intelligence and complex learning. A further analysis showed that the two working memory aspects, particularly the storage capacity, accounted for most of the shared variance between fluid intelligence and complex learning.     

A probabilistic computational model of cross-situational word learning

Words are the essence of communication: They are the building blocks of any language. Learning the meaning of words is thus one of the most important aspects of language acquisition: Children must first learn words before they can combine them into complex utterances. Many theories have been developed to explain the impressive efficiency of young children in acquiring the vocabulary of their language, as well as the developmental patterns observed in the course of lexical acquisition. A major source of disagreement among the different theories is whether children are equipped with special mechanisms and biases for word learning, or their general cognitive abilities are adequate for the task. We present a novel computational model of early word learning to shed light on the mechanisms that might be at work in this process. The model learns word meanings as probabilistic associations between words and semantic elements, using an incremental and probabilistic learning mechanism, and drawing only on general cognitive abilities. The results presented here demonstrate that much about word meanings can be learned from naturally occurring child-directed utterances (paired with meaning representations), without using any special biases or constraints, and without any explicit developmental changes in the underlying learning mechanism. Furthermore, our model provides explanations for the occasionally contradictory child experimental data, and offers predictions for the behavior of young word learners in novel situations.     

Conditional discrimination learning: A critique and amplification

Carter and Werner recently reviewed the literature on conditional discrimination learning by pigeons, which consists of studies of matching-to-sample and oddity-from-sample. They also discussed three models of such learning: the “multiple-rule” model (learning of stimulus-specific relations), the “configuration” model, and the “single-rule” model (concept learning). Although their treatment of the multiple-rule model, which seems most applicable to the pigeon data, is generally excellent, their discussion of the other two models is incomplete and sometimes inaccurate. Potential problems of terminology are discussed in the present paper, as are additional lines of research that deserve consideration by those interested in further work in this area. The issue of response versus stimulus selection (configuration versus compound-cue learning) is discussed in connection with the configuration model. Particular attention is given to Carter and Werner's criticism of the application, in studies with other species, of the learning set procedure in testing for single-rule learning. Some of the important related issues are: the bias for improvement on new problems in a series, the adequacy of a multiple-rule model to explain learning set formation, and evidence in favor of the single-rule model, at least in primates. Consideration of these additional contributions to the study of conditional discrimination learning emphasizes the usefulness of this task in the comparative study of cognitive processes.     

A computational account of the development of the generalization of shape information

Abecassis, Sera, Yonas, and Schwade (2001) showed that young children represent shapes more metrically, and perhaps more holistically, than do older children and adults. How does a child transition from representing objects and events as undifferentiated wholes to representing them explicitly in terms of their attributes? According to RBC (Recognition‐by‐Components theory; Biederman, 1987 ), objects are represented as collections of categorical geometric parts (“geons”) in particular categorical spatial relations. We propose that the transition from holistic to more categorical visual shape processing is a function of the development of geon‐like representations via a process of progressive intersection discovery. We present an account of this transition in terms of DORA ( Doumas, Hummel, & Sandhofer, 2008 ), a model of the discovery of relational concepts. We demonstrate that DORA can learn representations of single geons by comparing objects composed of multiple geons. In addition, as DORA is learning it follows the same performance trajectory as children, originally generalizing shape more metrically/holistically and eventually generalizing categorically.     

A model for stochastic drift in memory strength to account for judgments of learning

Previous research has shown that judgments of learning (JOLs) made immediately after encoding have a low correlation with actual cued-recall performance, whereas the correlation is high for delayed judgments. In this article, the authors propose a formal theory describing the stochastic drift of memory strength over the retention interval to account for the delayed-JOL effect. This is done by first decomposing the aggregated memory strength into exponential functions with slow and fast memory traces. The mean aggregated memory strength shows power-function forgetting curves. The drift of the memory strength is large for immediate JOLs (causing a low predictability) and weak for delayed JOLs (causing a high predictability). Consistent with empirical data, the model makes a novel prediction of JOL asymmetry, or that immediate weak JOLs are more predictive of future performance than are immediate strong JOLs. The JOL distributions for immediate and delayed JOLs are also accounted for.