Topics in Cognitive Science

Publisher: Wiley

Journal description

Current impact factor: 2.88

Impact Factor Rankings

Additional details

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


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    • Must link to publisher version with set statement (see policy)
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    • Reviewed 18/03/14
    • Please see former John Wiley & Sons and Blackwell Publishing policies for articles published prior to February 2007
  • Classification
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Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: Psychologists have used experimental methods to study language for more than a century. However, only with the recent availability of large-scale linguistic databases has a more complete picture begun to emerge of how language is actually used, and what information is available as input to language acquisition. Analyses of such "big data" have resulted in reappraisals of key assumptions about the nature of language. As an example, we focus on corpus-based research that has shed new light on the arbitrariness of the sign: the longstanding assumption that the relationship between the sound of a word and its meaning is arbitrary. The results reveal a systematic relationship between the sound of a word and its meaning, which is stronger for early acquired words. Moreover, the analyses further uncover a systematic relationship between words and their lexical categories-nouns and verbs sound differently from each other-affecting how we learn new words and use them in sentences. Together, these results point to a division of labor between arbitrariness and systematicity in sound-meaning mappings. We conclude by arguing in favor of including "big data" analyses into the language scientist's methodological toolbox.
    Topics in Cognitive Science 09/2015; DOI:10.1111/tops.12164
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    ABSTRACT: This article draws on the ethnography of Aboriginal Australia to argue that perceptual openness, extending from waking life into dreaming experience, provides an important cognitive framework for the apprehension of dreamt experience in these contexts. I argue that this perceptual openness is analogous to the "openness to experience" described as a personality trait that had been linked with dream recall frequency (among other things). An implication of identifying perceptual openness at a cultural rather than at an individual level is two-fold. It provides an example of the ways in which cultural differences affect perception, indicative of cognitive diversity; and, given the relationship between dreams and creativity suggested anecdotally and through research, a cultural orientation toward perceptual openness is also likely to have implications for the realization of creativity that occurs through dreams. Such creativity though cannot be separated from the relational context in which such dreamt material is elaborated and understood.
    Topics in Cognitive Science 09/2015; 7. DOI:10.1111/tops.12157
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    ABSTRACT: We begin our commentary by summarizing the commonalities and differences in cognitive phenomena across cultures, as found by the seven papers of this topic. We then assess the commonalities and differences in how our various authors have approached the study of cognitive diversity, and speculate on the need for, and potential of, cross-disciplinary collaboration.
    Topics in Cognitive Science 09/2015; DOI:10.1111/tops.12161
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    ABSTRACT: Anthropology and the other cognitive sciences currently maintain a troubled relationship (Beller, Bender, & Medin, ). What could rapprochement look like, and how could it be achieved? The seven main articles of this topic present anthropological or anthropologically inspired cross-cultural research on a diverse set of cognitive domains. They serve as an existence proof that not only do synergies abound across anthropology and the other cognitive sciences, but that they are worth achieving.
    Topics in Cognitive Science 09/2015; DOI:10.1111/tops.12160
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    ABSTRACT: The domain of numbers provides a paradigmatic case for investigating interactions of culture, language, and cognition: Numerical competencies are considered a core domain of knowledge, and yet the development of specifically human abilities presupposes cultural and linguistic input by way of counting sequences. These sequences constitute systems with distinct structural properties, the cross-linguistic variability of which has implications for number representation and processing. Such representational effects are scrutinized for two types of verbal numeration systems—general and object-specific ones—that were in parallel use in several Oceanic languages (English with its general system is included for comparison). The analysis indicates that the object-specific systems outperform the general systems with respect to counting and mental arithmetic, largely due to their regular and more compact representation. What these findings reveal on cognitive diversity, how the conjectures involved speak to more general issues in cognitive science, and how the approach taken here might help to bridge the gap between anthropology and other cognitive sciences is discussed in the conclusion.
    Topics in Cognitive Science 09/2015; 7. DOI:10.1111/tops.12165
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    ABSTRACT: We consider a situation in which individuals search for accurate decisions without direct feedback on their accuracy, but with information about the decisions made by peers in their group. The "wisdom of crowds" hypothesis states that the average judgment of many individuals can give a good estimate of, for example, the outcomes of sporting events and the answers to trivia questions. Two conditions for the application of wisdom of crowds are that estimates should be independent and unbiased. Here, we study how individuals integrate social information when answering trivia questions with answers that range between 0% and 100% (e.g., "What percentage of Americans are left-handed?"). We find that, consistent with the wisdom of crowds hypothesis, average performance improves with group size. However, individuals show a consistent bias to produce estimates that are insufficiently extreme. We find that social information provides significant, albeit small, improvement to group performance. Outliers with answers far from the correct answer move toward the position of the group mean. Given that these outliers also tend to be nearer to 50% than do the answers of other group members, this move creates group polarization away from 50%. By looking at individual performance over different questions we find that some people are more likely to be affected by social influence than others. There is also evidence that people differ in their competence in answering questions, but lack of competence is not significantly correlated with willingness to change guesses. We develop a mathematical model based on these results that postulates a cognitive process in which people first decide whether to take into account peer guesses, and if so, to move in the direction of these guesses. The size of the move is proportional to the distance between their own guess and the average guess of the group. This model closely approximates the distribution of guess movements and shows how outlying incorrect opinions can be systematically removed from a group resulting, in some situations, in improved group performance. However, improvement is only predicted for cases in which the initial guesses of individuals in the group are biased. © 2015 Cognitive Science Society, Inc.
    Topics in Cognitive Science 07/2015; 7(3). DOI:10.1111/tops.12150
  • Topics in Cognitive Science 06/2015; 7(3). DOI:10.1111/tops.12152
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    ABSTRACT: Searching through semantic memory may involve the use of several retrieval cues. In a verbal fluency task, the set of available cues is limited and every candidate word is a target. Individuals exhibit clustering behavior as predicted by optimal foraging theory. In another semantic search task, the remote associates task (RAT), three cues are presented and a single target word has to be found. Whereas the task has been widely studied as a task of creativity or insight problem solving, in this article, the RAT is treated as a semantic retrieval task and assessed from the perspective of information foraging theory. Experiments are presented that address the superadditive combination of cues and the anti-clustering behavior in the recall sequence. A new type of search behavior in the RAT is put forward that involves maximizing the difference in activation between target and distractors. This type of search is advantageous when the target is weak and cue patches are contaminated with strong competitors. © 2015 Cognitive Science Society, Inc.
    Topics in Cognitive Science 05/2015; 7(3). DOI:10.1111/tops.12146
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    ABSTRACT: Mata and von Helversen's integrative review of adult age differences in search performance makes a good case that cognitive control may impact certain aspects of self-regulation of search. However, information foraging as a framework also offers an avenue to consider how adults of different ages adapt to age-related changes in cognition, such as in cognitive control. Copyright © 2015 Cognitive Science Society, Inc.
    Topics in Cognitive Science 05/2015; 7(3). DOI:10.1111/tops.12149
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    ABSTRACT: Numerous studies have documented individual differences in exploratory tendencies and other phenomena related to search, and these differences have been linked to fitness. Here, I discuss the origins of these differences, focusing on how experience shapes animal search and exploration. The origin of individual differences will also depend upon the alternatives to exploration that are available. Given that search and exploration frequently carry significant costs, we might expect individuals to utilize cues indicating the potential net payoffs of exploration versus the exploitation of known acts. Informative cues could arise from both recent and early-life experiences, from both the social and physical environment. Open questions are the extent to which an individual's exploratory tendencies are fixed throughout life versus being flexibly adjusted according to prevailing conditions and the actions of other individuals, and the extent to which individual differences in exploration extend across domains and are independent of other processes. Copyright © 2015 Cognitive Science Society, Inc.
    Topics in Cognitive Science 05/2015; 7(3). DOI:10.1111/tops.12148
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    ABSTRACT: While the research programs in early cognitive science and artificial intelligence aimed to articulate what cognition was in ideal terms, much research in contemporary computational neuroscience looks at how and why brains fail to function as they should ideally. This focus on impairment affects how we understand David Marr's hypothesized three levels of understanding. In this essay, we suggest some refinements to Marr's distinctions using a population activity model of cortico-striatal circuitry exploring impulsivity and behavioral inhibition as a case study. In particular, we urge that Marr's computational level should be redefined to include a description of how systems break down. We also underscore that feed-forward processing, cognition disconnected from behavioral context, and representations do not always drive cognition in the way that Marr originally assumed. Copyright © 2015 Cognitive Science Society, Inc.
    Topics in Cognitive Science 04/2015; 7(2). DOI:10.1111/tops.12130
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    ABSTRACT: Are all three of Marr's levels needed? Should they be kept distinct? We argue for the distinct contributions and methodologies of each level of analysis. It is important to maintain them because they provide three different perspectives required to understand mechanisms, especially information-processing mechanisms. The computational perspective provides an understanding of how a mechanism functions in broader environments that determines the computations it needs to perform (and may fail to perform). The representation and algorithmic perspective offers an understanding of how information about the environment is encoded within the mechanism and what are the patterns of organization that enable the parts of the mechanism to produce the phenomenon. The implementation perspective yields an understanding of the neural details of the mechanism and how they constrain function and algorithms. Once we adequately characterize the distinct role of each level of analysis, it is fairly straightforward to see how they relate. Copyright © 2015 Cognitive Science Society, Inc.
    Topics in Cognitive Science 04/2015; 7(2). DOI:10.1111/tops.12141
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    ABSTRACT: We combine two recent probabilistic approaches to natural language understanding, exploring the formal pragmatics of communication on a noisy channel. We first extend a model of rational communication between a speaker and listener, to allow for the possibility that messages are corrupted by noise. In this model, common knowledge of a noisy channel leads to the use and correct understanding of sentence fragments. A further extension of the model, which allows the speaker to intentionally reduce the noise rate on a word, is used to model prosodic emphasis. We show that the model derives several well-known changes in meaning associated with prosodic emphasis. Our results show that nominal amounts of actual noise can be leveraged for communicative purposes. Copyright © 2015 Cognitive Science Society, Inc.
    Topics in Cognitive Science 04/2015; 7(2). DOI:10.1111/tops.12144
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    ABSTRACT: Animals routinely adapt to changes in the environment in order to survive. Though reinforcement learning may play a role in such adaptation, it is not clear that it is the only mechanism involved, as it is not well suited to producing rapid, relatively immediate changes in strategies in response to environmental changes. This research proposes that counterfactual reasoning might be an additional mechanism that facilitates change detection. An experiment is conducted in which a task state changes over time and the participants had to detect the changes in order to perform well and gain monetary rewards. A cognitive model is constructed that incorporates reinforcement learning with counterfactual reasoning to help quickly adjust the utility of task strategies in response to changes. The results show that the model can accurately explain human data and that counterfactual reasoning is key to reproducing the various effects observed in this change detection paradigm. Copyright © 2015 Cognitive Science Society, Inc.
    Topics in Cognitive Science 04/2015; 7(2). DOI:10.1111/tops.12143