bluuebunny/crossref_metadata_2025_split huggingface dataset:
Representation of Principled Connections: A Window Onto the Formal Aspect of Common Sense Conception
Authors: Prasada Sandeep , Dillingham Elaine M. 
Published: February 2010

AbstractNominal concepts represent things as tokens of types. Recent research suggests that we represent principled connections between the type of thing something is (e.g., DOG) and some of its properties (k‐properties; e.g., having four legs for dogs) but not other properties (t‐properties; e.g., being brown for dogs). Principled connections differ from logical, statistical, and causal connections. Principled connections license (i) the expectation that tokens of the type will generally possess their k‐properties, (ii) formal explanations (i.e., explanation of the presence of k‐properties in tokens of a type by reference to the type of thing it is), and (iii) normative expectations concerning the presence of k‐properties in tokens of the type. The present paper investigates the hypothesis that representing principled connections requires representing properties as aspects of being the relevant kind of thing (Aspect Hypothesis). Experiment 1 provides a direct test of the Aspect Hypothesis. Experiments 2 and 3 provide indirect tests of the Aspect Hypothesis. All three experiments provide support for the Aspect Hypothesis. Experiment 4 investigates a prediction of the Aspect Hypothesis concerning the manner in which formal explanations are licensed by principled connections. Finally, Experiment 5 investigates a prediction of the Aspect Hypothesis concerning the nature of the normative expectations licensed by principled connections. Together these results provide strong evidence for the idea that representing principled connections involves representing a property as being an aspect of being a given kind of thing. The results also help clarify the manner in which formal explanation differs from other modes of explanation. Finally, the results of the experiments are used to motivate a proposal concerning the formal structure of the conceptual representations implicated by principled connections. This structure provides a domain‐general way of structuring our concepts and embodies the perspective we take when we think and talk of things as being instances of a kind.
Incrementality and Prediction in Human Sentence Processing
Authors: Altmann Gerry T. M. , Mirković Jelena 
Published: February 2010

AbstractWe identify a number of principles with respect to prediction that, we argue, underpin adult language comprehension: (a) comprehension consists in realizing a mapping between the unfolding sentence and the event representation corresponding to the real‐world event being described; (b) the realization of this mapping manifests as the ability to predict both how the language will unfold, and how the real‐world event would unfold if it were being experienced directly; (c) concurrent linguistic and nonlinguistic inputs, and the prior internal states of the system, each drive the predictive process; (d) the representation of prior internal states across a representational substrate common to the linguistic and nonlinguistic domains enables the predictive process to operate over variable time frames and variable levels of representational abstraction. We review empirical data exemplifying the operation of these principles and discuss the relationship between prediction, event structure, thematic role assignment, and incrementality.
On the Meaning of Words and Dinosaur Bones: Lexical Knowledge Without a Lexicon
Authors: Elman Jeffrey L. 
Published: February 2010

AbstractAlthough for many years a sharp distinction has been made in language research between rules and words—with primary interest on rules—this distinction is now blurred in many theories. If anything, the focus of attention has shifted in recent years in favor of words. Results from many different areas of language research suggest that the lexicon is representationally rich, that it is the source of much productive behavior, and that lexically specific information plays a critical and early role in the interpretation of grammatical structure. But how much information can or should be placed in the lexicon? This is the question I address here. I review a set of studies whose results indicate that event knowledge plays a significant role in early stages of sentence processing and structural analysis. This poses a conundrum for traditional views of the lexicon. Either the lexicon must be expanded to include factors that do not plausibly seem to belong there; or else virtually all information about word meaning is removed, leaving the lexicon impoverished. I suggest a third alternative, which provides a way to account for lexical knowledge without a mental lexicon.
Lexical Organization and Competition in First and Second Languages: Computational and Neural Mechanisms
Authors: Li Ping 
Published: February 2010

AbstractHow does a child rapidly acquire and develop a structured mental organization for the vast number of words in the first years of life? How does a bilingual individual deal with the even more complicated task of learning and organizing two lexicons? It is only until recently have we started to examine the lexicon as a dynamical system with regard to its acquisition, representation, and organization. In this article, I outline a proposal based on our research that takes the dynamical approach to the lexicon, and I discuss how this proposal can be applied to account for lexical organization, structural representation, and competition within and between languages. In particular, I provide computational evidence based on the DevLex model, a self‐organizing neural network model, and neuroimaging evidence based on functional magnetic resonance imaging (fMRI) studies, to illustrate how children and adults learn and represent the lexicon in their first and second languages. In the computational research, our goal has been to identify, through linguistically and developmentally realistic models, detailed cognitive mechanisms underlying the dynamic self‐organizing processes in monolingual and bilingual lexical development; in the neuroimaging research, our goal has been to identify the neural substrates that subserve lexical organization and competition in the monolingual and the bilingual brain. In both cases, our findings lead to a better understanding of the interactive dynamics involved in the acquisition and representation of one or multiple languages.
A Probabilistic Model of Semantic Plausibility in Sentence Processing
Authors: Padó Ulrike , Crocker Matthew W. , Keller Frank 
Published: February 2010

AbstractExperimental research shows that human sentence processing uses information from different levels of linguistic analysis, for example, lexical and syntactic preferences as well as semantic plausibility. Existing computational models of human sentence processing, however, have focused primarily on lexico‐syntactic factors. Those models that do account for semantic plausibility effects lack a general model of human plausibility intuitions at the sentence level. Within a probabilistic framework, we propose a wide‐coverage model that both assigns thematic roles to verb–argument pairs and determines a preferred interpretation by evaluating the plausibility of the resulting (verb,role,argument) triples. The model is trained on a corpus of role‐annotated language data. We also present a transparent integration of the semantic model with an incremental probabilistic parser. We demonstrate that both the semantic plausibility model and the combined syntax/semantics model predict judgment and reading time data from the experimental literature.
Cognitive Models of Choice: Comparing Decision Field Theory to the Proportional Difference Model
Authors: Scheibehenne Benjamin , Rieskamp Jörg , González‐Vallejo Claudia 
Published: February 2010

AbstractPeople often face preferential decisions under risk. To further our understanding of the cognitive processes underlying these preferential choices, two prominent cognitive models, decision field theory (DFT;Busemeyer & Townsend, 1993) and the proportional difference model (PD;González‐Vallejo, 2002), were rigorously tested against each other. In two consecutive experiments, the participants repeatedly had to choose between monetary gambles. The first experiment provided the reference to estimate the models’ free parameters. From these estimations, new gamble pairs were generated for the second experiment such that the two models made maximally divergent predictions. In the first experiment, both models explained the data equally well. However, in the second generalization experiment, the participants’ choices were much closer to the predictions of DFT. The results indicate that the stochastic process assumed by DFT, in which evidence in favor of or against each option accumulates over time, described people’s choice behavior better than the trade‐offs between proportional differences assumed by PD.
Multitimescale Dynamical Interactions Between Speech Rhythm and Gesture
Authors: Tilsen Sam 
Published: February 2010

AbstractTemporal patterns in human movement, and in speech in particular, occur on multiple timescales. Regularities in such patterns have been observed between speech gestures, which are relatively quick movements of articulators (e.g., tongue fronting and lip protrusion), and also between rhythmic units (e.g., syllables and metrical feet), which occur more slowly. Previous work has shown that patterns in both domains can be usefully modeled with oscillatory dynamical systems. To investigate how rhythmic and gestural domains interact, an experiment was conducted in which speakers performed a phrase repetition task, and gestural kinematics were recorded using electromagnetic articulometry. Variance in relative timing of gestural movements was correlated with variance in rhythmic timing, indicating that gestural and rhythmic systems interact in the process of planning and producing speech. A model of rhythmic and gestural planning oscillators with multifrequency coupling is presented, which can simulate the observed covariability between rhythmic and gestural timing.
Do the Weak Stand a Chance? Distribution of Resources in a Competitive Environment
Authors: Avrahami Judith , Kareev Yaakov 
Published: February 2010

AbstractWhen two agents of unequal strength compete, the stronger one is expected to always win the competition. This expectation is based on the assumption that evaluation of performance is complete, hence flawless. If, however, the agents are evaluated on the basis of only a small sample of their performance, the weaker agent still stands a chance of winning occasionally. A theoretical analysis indicates that, to increase the chance of this happening the weaker agent ought to give up on enough occasions so that he or she can match the stronger agent on the remaining ones. We model such a competition in a game, present its game‐theoretic solution, and report an experiment, involving 144 individuals, in which we tested whether players (both weak and strong) are actually sensitive to their relative strengths and know how to allocate their resources accordingly. Our results indicate that they do.
Changing Structures in Midstream: Learning Along the Statistical Garden Path
Authors: Gebhart Andrea L. , Aslin Richard N. , Newport Elissa L. 
Published: February 2010

AbstractPrevious studies of auditory statistical learning have typically presented learners with sequential structural information that is uniformly distributed across the entire exposure corpus. Here we present learners with nonuniform distributions of structural information by altering the organization of trisyllabic nonsense words at midstream. When this structural change was unmarked by low‐level acoustic cues, or even when cued by a pitch change, only the first of the two structures was learned. However, both structures were learned when there was an explicit cue to the midstream change or when exposure to the second structure was tripled in duration. These results demonstrate that successful extraction of the structure in an auditory statistical learning task reduces the ability to learn subsequent structures, unless the presence of two structures is marked explicitly or the exposure to the second is quite lengthy. The mechanisms by which learners detect and use changes in distributional information to maintain sensitivity to multiple structures are discussed from both behavioral and computational perspectives.
How Can Experts See the Invisible? Reply to Bilalić and Gobet
Authors: Linhares Alexandre , Brum Paulo 
Published: February 2010

AbstractExperts in all fields are able to see what is invisible to others. Experts are also able to see what is visible to all—and this is explored by Bilalić and Gobet. We question the method of normalizing all subjects in an experimental condition, and asking experts to behave as if they were novices. We claim that method leads Bilalić and Gobet to a nonsequitur.
They Do What They Are Told to Do: The Influence of Instruction on (Chess) Expert Perception—Commentary on Linhares and Brum (2007)
Authors: Bilalić Merim , Gobet Fernand 
Published: February 2010

AbstractLinhares and Brum (2007) argue that they provide evidence for analogy as the main principle behind experts’ acquisition of perceptual knowledge. However, the methodology they used—asking players to pair positions using abstract similarity—raises the possibility that the task reflects more the effect of directional instructions than the principles underlying the acquisition of knowledge. Here we replicate and extend Linhares and Brum’s experiment and show that the matching task they used is inadequate for drawing any conclusions about the nature of experts’ perception. When expert chess players were instructed to match problems based on similarities at the abstract level (analogy), they produced more abstract pairs than pairs based on concrete similarity. However, the same experts produced more concrete pairs than abstract ones when instructed to match the problems based on concrete similarity. Asking experts to match problems using explicit instructions is not an appropriate way to show the importance of either analogy or similarity in the acquisition of expert knowledge. Experts simply do what they are told to do.
Building to Discover: A Common Coding Model
Authors: Chandrasekharan Sanjay 
Published: February 2010

AbstractI present a case study of scientific discovery, where building two functional and behavioral approximations of neurons, one physical and the other computational, led to conceptual and implementation breakthroughs in a neural engineering laboratory. Such building of external systems that mimic target phenomena, and the use of these external systems to generate novel concepts and control structures, is a standard strategy in the new engineering sciences. I develop a model of the cognitive mechanism that connects such built external systems with internal models, and I examine how new discoveries, and consensus on discoveries, could arise from this external‐internal coupling and the building process. The model is based on the emerging framework of common coding, which proposes a shared representation in the brain between the execution, perception, and imagination of movement.
Occlusion Is Hard: Comparing Predictive Reaching for Visible and Hidden Objects in Infants and Adults
Authors: Hespos Susan , Gredebäck Gustaf , Von Hofsten Claes , Spelke Elizabeth S. 
Published: February 2010

AbstractInfants can anticipate the future location of a moving object and execute a predictive reach to intercept the object. When a moving object is temporarily hidden by darkness or occlusion, 6‐month‐old infants’ reaching is perturbed, but performance on darkness trials is significantly better than occlusion trials. How does this reaching behavior change over development? Experiment 1 tested predictive reaching of 6‐ and 9‐month‐old infants. While there was an increase in the overall number of reaches with increasing age, there were significantly fewer predictive reaches during the occlusion compared to visible trials and no age‐related changes in this pattern. The decrease in performance found in Experiment 1 is likely to apply not only to the object representations formed by infants but also those formed by adults. In Experiment 2 we tested adults with a similar reaching task. Like infants, the adults were most accurate when the target was continuously visible and performance in darkness trials was significantly better than occlusion trials, providing evidence that there is something specific about occlusion that makes it more difficult than merely lack of visibility. Together, these findings suggest that infants’ and adults’ capacities to represent objects have similar signatures throughout development.
Relationships Between Language Structure and Language Learning: The Suffixing Preference and Grammatical Categorization
Authors: St. Clair Michelle C. , Monaghan Padraic , Ramscar Michael 
Published: February 2010

AbstractIt is a reasonable assumption that universal properties of natural languages are not accidental. They occur either because they are underwritten by genetic code, because they assist in language processing or language learning, or due to some combination of the two. In this paper we investigate one such language universal: the suffixing preference across the world’s languages, whereby inflections tend to be added to the end of words. A corpus analysis of child‐directed speech in English found that suffixes were more accurate at cuing the grammatical category of the root word than were prefixes. An artificial language experiment found that there was a learning advantage for suffixes over prefixes in terms of grammatical categorization within an artificial language. The results are consistent with an account of language universals that originate in general purpose learning mechanisms.
Representation Recovers Information
Authors: Thornton Chris 
Published: February 2010

AbstractEarly agreement within cognitive science on the topic of representation has now given way to a combination of positions. Some question the significance of representation in cognition. Others continue to argue in favor, but the case has not been demonstrated in any formal way. The present paper sets out a framework in which the value of representation use can be mathematically measured, albeit in a broadly sensory context rather than a specifically cognitive one. Key to the approach is the use of Bayesian networks for modeling the distal dimension of sensory processes. More relevant to cognitive science is the theoretical result obtained, which is that a certain type of representational architecture isnecessaryfor achievement of sensory efficiency. While exhibiting few of the characteristics of traditional, symbolic encoding, this architecture corresponds quite closely to the forms of embedded representation now being explored in some embedded/embodied approaches. It becomes meaningful to view that type of representation use as a form of information recovery. A formal basis then exists for viewing representation not so much as the substrate of reasoning and thought, but rather as a general medium for efficient, interpretive processing.
Reviving Inert Knowledge: Analogical Abstraction Supports Relational Retrieval of Past Events
Authors: Gentner Dedre , Loewenstein Jeffrey , Thompson Leigh , Forbus Kenneth D. 
Published: February 2010

AbstractWe present five experiments and simulation studies to establishlate analogical abstractionas a new psychological phenomenon: Schema abstraction from analogical examples can revive otherwise inert knowledge. We find that comparing two analogous examples of negotiations at recall time promotes retrieving analogical matches stored in memory—a notoriously elusive effect. Another innovation in this research is that we show parallel effects for real‐life autobiographical memory (Experiments 1–3) and for a controlled memory set (Experiments 4 and 5). Simulation studies show that a unified model based on schema abstraction can capture backward (retrieval) effects as well as forward (transfer) effects.
Exploiting Multiple Sources of Information in Learning an Artificial Language: Human Data and Modeling
Authors: Perruchet Pierre , Tillmann Barbara 
Published: February 2010

AbstractThis study investigates the joint influences of three factors on the discovery of new word‐like units in a continuous artificial speech stream: the statistical structure of the ongoing input, the initial word‐likeness of parts of the speech flow, and the contextual information provided by the earlier emergence of other word‐like units. Results of an experiment conducted with adult participants show that these sources of information have strong and interactive influences on word discovery. The authors then examine the ability of different models of word segmentation to account for these results. PARSER (Perruchet & Vinter, 1998) is compared to the view that word segmentation relies on the exploitation of transitional probabilities between successive syllables, and with the models based on the Minimum Description Length principle, such as INCDROP. The authors submit arguments suggesting that PARSER has the advantage of accounting for the whole pattern of data without ad‐hoc modifications, while relying exclusively on general‐purpose learning principles. This study strengthens the growing notion that nonspecific cognitive processes, mainly based on associative learning and memory principles, are able to account for a larger part of early language acquisition than previously assumed.
Learnability of Embedded Syntactic Structures Depends on Prosodic Cues
Authors: Mueller Jutta L. , Bahlmann Jörg , Friederici Angela D. 
Published: February 2010

AbstractThe ability to process center‐embedded structures has been claimed to represent a core function of the language faculty. Recently, several studies have investigated the learning of center‐embedded dependencies in artificial grammar settings. Yet some of the results seem to question the learnability of these structures in artificial grammar tasks. Here, we tested under which exposure conditions learning of center‐embedded structures in an artificial grammar is possible. We used naturally spoken syllable sequences and varied the presence of prosodic cues. The results suggest that mere distributional information does not suffice for successful learning. Prosodic cues marking the boundaries of the major relevant units, however, can lead to learning success. Thus, our data are consistent with the hypothesis that center‐embedded syntactic structures can be learned in artificial grammar tasks if language‐like acoustic cues are provided.