Topics in Cognitive Science

Publisher: Blackwell Publishing

Description

  • Impact factor
    2.88
  • 5-year impact
    2.88
  • Cited half-life
    2.20
  • Immediacy index
    0.45
  • Eigenfactor
    0.00
  • Article influence
    1.18
  • ISSN
    1756-8765
  • OCLC
    320882278
  • Material type
    Series, Periodical
  • Document type
    Journal / Magazine / Newspaper

Publisher details

Blackwell Publishing

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    • See Wiley-Blackwell entry for articles after February 2007
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    • Publisher copyright and source must be acknowledged with set statement ("The definitive version is available at www.blackwell-synergy.com ")
    • Articles in some journals can be made Open Access on payment of additional charge
    • 'Blackwell Publishing' is an imprint of 'Wiley-Blackwell'
  • Classification
    ​ yellow

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: In philosophy, “singular thought” refers to our capacity to represent entities as individuals, rather than as possessors of properties. Philosophers who defend singularism argue that perception allows us to mentally latch onto objects and persons directly, without conceptualizing them as being of a certain sort. Singularists assume that singular thought forms a unified psychological kind, regardless of the nature of the individuals represented. Empirical findings on the special psychological role of persons as opposed to inanimates threaten singularism. They raise the possibility that tracking individuals specifically as persons might require conceptualizing them in certain ways, for example, as persons. In this paper, we take such a possibility seriously but ultimately reject it. Instead, we propose to revise a prominent singularist theory, the theory of mental files, in order to accommodate data on the psychological distinctiveness of persons: We advocate the postulation of perceptual person-files. Perceptual tracking via person-files is different from object-tracking but also from descriptive classification under the sortal concept PERSON.
    Topics in Cognitive Science 08/2014;
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    ABSTRACT: Tracking persons, that is, determining that a person now is or is not a specific earlier person, is extremely common and widespread in our way of life and extremely important. If so, figuring out what we are tracking, what it is to persist as a person over a period of time, is also important. Trying to figure this out will be the main focus of this chapter.
    Topics in Cognitive Science 08/2014;
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    ABSTRACT: We propose that there is a powerful human disposition to track the actions and possessions of agents. In two experiments, 3-year-olds and adults viewed sets of objects, learned a new fact about one of the objects in each set (either that it belonged to the participant, or that it possessed a particular label), and were queried about either the taught fact or an unrelated dimension (preference) immediately after a spatiotemporal transformation, and after a delay. Adults uniformly tracked object identity under all conditions, whereas children tracked identity more when taught ownership versus labeling information, and only regarding the taught fact (not the unrelated dimension). These findings suggest that the special attention that children and adults pay to agents readily extends to include inanimate objects. That young children track an object's history, despite their reliance on surface features on many cognitive tasks, suggests that unobservable historical features are foundational in human cognition.
    Topics in Cognitive Science 08/2014;
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    ABSTRACT: According to embodied theories of language (ETLs), word meaning relies on sensorimotor brain areas, generally dedicated to acting and perceiving in the real world. More specifically, words denoting actions are postulated to make use of neural motor areas, while words denoting visual properties draw on the resources of visual brain areas. Therefore, there is a direct correspondence between word meaning and the experience a listener has had with a word's referent on the brain level. Behavioral and neuroimaging studies have provided evidence in favor of ETLs; however, recent studies have also shown that sensorimotor information is recruited in a flexible manner during language comprehension (e.g., Raposo et al. 2009; Van Dam et al., 2012), leaving open the question as to what level of language processing sensorimotor activations contribute. In this study, we investigated the time course of modality-specific contributions (i.e., the contribution of action information) as to word processing by manipulating both (a) the linguistic and (b) the action context in which target words were presented. Our results demonstrate that processes reflecting sensorimotor information play a role early in word processing (i.e., within 200 ms of word presentation), but that they are sensitive to the linguistic context in which a word is presented. In other words, when sensorimotor information is activated, it is activated quickly; however, specific words do not reliably activate a consistent sensorimotor pattern.
    Topics in Cognitive Science 07/2014; 6(3).
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    ABSTRACT: The recent trend in cognitive robotics experiments on language learning, symbol grounding, and related issues necessarily entails a reduction of sensorimotor aspects from those provided by a human body to those that can be realized in machines, limiting robotic models of symbol grounding in this respect. Here, we argue that there is a need for modeling work in this domain to explicitly take into account the richer human embodiment even for concrete concepts that prima facie relate merely to simple actions, and illustrate this using distributional methods from computational linguistics which allow us to investigate grounding of concepts based on their actual usage. We also argue that these techniques have applications in theories and models of grounding, particularly in machine implementations thereof. Similarly, considering the grounding of concepts in human terms may be of benefit to future work in computational linguistics, in particular in going beyond "grounding" concepts in the textual modality alone. Overall, we highlight the overall potential for a mutually beneficial relationship between the two fields.
    Topics in Cognitive Science 06/2014;
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    ABSTRACT: This contribution presents a corpus of spatial descriptions and describes the development of a human-driven spatial language robot system for their comprehension. The domain of application is an eldercare setting in which an assistive robot is asked to "fetch" an object for an elderly resident based on a natural language spatial description given by the resident. In Part One, we describe a corpus of naturally occurring descriptions elicited from a group of older adults within a virtual 3D home that simulates the eldercare setting. We contrast descriptions elicited when participants offered descriptions to a human versus robot avatar, and under instructions to tell the addressee how to find the target versus where the target is. We summarize the key features of the spatial descriptions, including their dynamic versus static nature and the perspective adopted by the speaker. In Part Two, we discuss critical cognitive and perceptual processing capabilities necessary for the robot to establish a common ground with the human user and perform the "fetch" task. Based on the collected corpus, we focus here on resolving the perspective ambiguity and recognizing furniture items used as landmarks in the descriptions. Taken together, the work presented here offers the key building blocks of a robust system that takes as input natural spatial language descriptions and produces commands that drive the robot to successfully fetch objects within our eldercare scenario.
    Topics in Cognitive Science 06/2014;
  • [Show abstract] [Hide abstract]
    ABSTRACT: Recently, there has been a great deal of interest in the idea that natural language enhances and extends our cognitive capabilities. Supporters of embodied cognition have been particularly interested in the way in which language may provide a solution to the problem of abstract concepts. Toward this end, some have emphasized the way in which language may act as form of cognitive scaffolding and others have emphasized the potential importance of language-based distributional information. This essay defends a version of the cognitive enhancement thesis that integrates and builds on both of these proposals. I argue that the embodied representations associated with language processing serve as a supplementary medium for conceptual processing. The acquisition of a natural language provides a means of extending our cognitive reach by giving us access to an internalized combinatorial symbol system that augments and supports the context-sensitive embodied representational systems that exist independently of language.
    Topics in Cognitive Science 06/2014;
  • [Show abstract] [Hide abstract]
    ABSTRACT: The topic is characterized by a highly interdisciplinary approach to the issue of action and language integration. Such an approach, combining computational models and cognitive robotics experiments with neuroscience, psychology, philosophy, and linguistic approaches, can be a powerful means that can help researchers disentangle ambiguous issues, provide better and clearer definitions, and formulate clearer predictions on the links between action and language. In the introduction we briefly describe the papers and discuss the challenges they pose to future research. We identify four important phenomena the papers address and discuss in light of empirical and computational evidence: (a) the role played not only by sensorimotor and emotional information but also of natural language in conceptual representation; (b) the contextual dependency and high flexibility of the interaction between action, concepts, and language; (c) the involvement of the mirror neuron system in action and language processing; (d) the way in which the integration between action and language can be addressed by developmental robotics and Human-Robot Interaction.
    Topics in Cognitive Science 06/2014;
  • [Show abstract] [Hide abstract]
    ABSTRACT: Over the past 15 years, there have been two increasingly popular approaches to the study of meaning in cognitive science. One, based on theories of embodied cognition, treats meaning as a simulation of perceptual and motor states. An alternative approach treats meaning as a consequence of the statistical distribution of words across spoken and written language. On the surface, these appear to be opposing scientific paradigms. In this review, we aim to show how recent cross-disciplinary developments have done much to reconcile these two approaches. The foundation to these developments has been the recognition that intralinguistic distributional and sensory-motor data are interdependent. We describe recent work in philosophy, psychology, cognitive neuroscience, and computational modeling that are all based on or consistent with this conclusion. We conclude by considering some possible directions for future research that arise as a consequence of these developments.
    Topics in Cognitive Science 06/2014;
  • [Show abstract] [Hide abstract]
    ABSTRACT: A growing body of evidence in cognitive psychology and neuroscience suggests a deep interconnection between sensory-motor and language systems in the brain. Based on recent neurophysiological findings on the anatomo-functional organization of the fronto-parietal network, we present a computational model showing that language processing may have reused or co-developed organizing principles, functionality, and learning mechanisms typical of premotor circuit. The proposed model combines principles of Hebbian topological self-organization and prediction learning. Trained on sequences of either motor or linguistic units, the network develops independent neuronal chains, formed by dedicated nodes encoding only context-specific stimuli. Moreover, neurons responding to the same stimulus or class of stimuli tend to cluster together to form topologically connected areas similar to those observed in the brain cortex. Simulations support a unitary explanatory framework reconciling neurophysiological motor data with established behavioral evidence on lexical acquisition, access, and recall.
    Topics in Cognitive Science 06/2014;
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    ABSTRACT: This article presents results from a multidisciplinary research project on the integration and transfer of language knowledge into robots as an empirical paradigm for the study of language development in both humans and humanoid robots. Within the framework of human linguistic and cognitive development, we focus on how three central types of learning interact and co-develop: individual learning about one's own embodiment and the environment, social learning (learning from others), and learning of linguistic capability. Our primary concern is how these capabilities can scaffold each other's development in a continuous feedback cycle as their interactions yield increasingly sophisticated competencies in the agent's capacity to interact with others and manipulate its world. Experimental results are summarized in relation to milestones in human linguistic and cognitive development and show that the mutual scaffolding of social learning, individual learning, and linguistic capabilities creates the context, conditions, and requisites for learning in each domain. Challenges and insights identified as a result of this research program are discussed with regard to possible and actual contributions to cognitive science and language ontogeny. In conclusion, directions for future work are suggested that continue to develop this approach toward an integrated framework for understanding these mutually scaffolding processes as a basis for language development in humans and robots.
    Topics in Cognitive Science 06/2014;
  • [Show abstract] [Hide abstract]
    ABSTRACT: As embodied theories of cognition are increasingly formalized and tested, care must be taken to make informed assumptions regarding the nature of concepts and representations. In this study, we outline three reasons why one cannot, in effect, represent the same concept twice. First, online perception affects offline representation: Current representational content depends on how ongoing demands direct attention to modality-specific systems. Second, language is a fundamental facilitator of offline representation: Bootstrapping and shortcuts within the computationally cheaper linguistic system continuously modify representational content. Third, time itself is a source of representational change: As the content of underlying concepts shifts with the accumulation of direct and vicarious experience, so too does the content of representations that draw upon these concepts. We discuss the ramifications of these principles for research into both human and synthetic cognitive systems.
    Topics in Cognitive Science 06/2014;
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    ABSTRACT: There have been two major lines of research aimed at capturing resource-bounded players in game theory. The first, initiated by Rubinstein (), charges an agent for doing costly computation; the second, initiated by Neyman (), does not charge for computation, but limits the computation that agents can do, typically by modeling agents as finite automata. We review recent work on applying both approaches in the context of decision theory. For the first approach, we take the objects of choice in a decision problem to be Turing machines, and charge players for the “complexity” of the Turing machine chosen (e.g., its running time). This approach can be used to explain well-known phenomena like first-impression-matters biases (i.e., people tend to put more weight on evidence they hear early on) and belief polarization (two people with different prior beliefs, hearing the same evidence, can end up with diametrically opposed conclusions) as the outcomes of quite rational decisions. For the second approach, we model people as finite automata, and provide a simple algorithm that, on a problem that captures a number of settings of interest, provably performs optimally as the number of states in the automaton increases.
    Topics in Cognitive Science 04/2014; 6(2).
  • Topics in Cognitive Science 04/2014; 6(2).
  • [Show abstract] [Hide abstract]
    ABSTRACT: Cognitive science views thought as computation; and computation, by its very nature, can be understood in both rational and mechanistic terms. In rational terms, a computation solves some information processing problem (e.g., mapping sensory information into a description of the external world; parsing a sentence; selecting among a set of possible actions). In mechanistic terms, a computation corresponds to causal chain of events in a physical device (in engineering context, a silicon chip; in biological context, the nervous system). The discipline is thus at the interface between two very different styles of explanation-as the papers in the current special issue well illustrate, it explores the interplay of rational and mechanistic forces.
    Topics in Cognitive Science 03/2014;
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    ABSTRACT: Although seemingly irrational choice abounds, the rules governing these mis-steps that might provide hints about the factors limiting normative behavior are unclear. We consider three experimental tasks, which probe different aspects of non-normative choice under uncertainty. We argue for systematic statistical, algorithmic, and implementational sources of irrationality, including incomplete evaluation of long-run future utilities, Pavlovian actions, and habits, together with computational and statistical noise and uncertainty. We suggest structural and functional adaptations that minimize their maladaptive effects.
    Topics in Cognitive Science 03/2014;

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