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  1. Investigating the structure of semantic networks in low and high creative persons.Yoed N. Kenett, David Anaki & Miriam Faust - 2014 - Frontiers in Human Neuroscience 8:89404.
    According to Mednick’s (1962) theory of individual differences in creativity, creative individuals appear to have a richer and more flexible associative network than less creative individuals. Thus, creative individuals are characterized by “flat” (broader associations) instead of “steep” (few, common associations) associational hierarchies. To study these differences, we implement a novel computational approach to the study of semantic networks, through the analysis of free associations. The core notion of our method is that concepts in the network are related to each (...)
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  • How semantic memory structure and intelligence contribute to creative thought: a network science approach.Mathias Benedek, Yoed N. Kenett, Konstantin Umdasch, David Anaki, Miriam Faust & Aljoscha C. Neubauer - 2017 - Thinking and Reasoning 23 (2):158-183.
    The associative theory of creativity states that creativity is associated with differences in the structure of semantic memory, whereas the executive theory of creativity emphasises the role of top-down control for creative thought. For a powerful test of these accounts, individual semantic memory structure was modelled with a novel method based on semantic relatedness judgements and different criteria for network filtering were compared. The executive account was supported by a correlation between creative ability and broad retrieval ability. The associative account (...)
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  • Using Network Science to Understand the Aging Lexicon: Linking Individuals' Experience, Semantic Networks, and Cognitive Performance.Dirk U. Wulff, Simon De Deyne, Samuel Aeschbach & Rui Mata - 2022 - Topics in Cognitive Science 14 (1):93-110.
    People undergo many idiosyncratic experiences throughout their lives that may contribute to individual differences in the size and structure of their knowledge representations. Ultimately, these can have important implications for individuals' cognitive performance. We review evidence that suggests a relationship between individual experiences, the size and structure of semantic representations, as well as individual and age differences in cognitive performance. We conclude that the extent to which experience-dependent changes in semantic representations contribute to individual differences in cognitive aging remains unclear. (...)
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  • The Cognitive Social Network in Dreams: Transitivity, Assortativity, and Giant Component Proportion Are Monotonic.Hye Joo Han, Richard Schweickert, Zhuangzhuang Xi & Charles Viau-Quesnel - 2016 - Cognitive Science 40 (3):671-696.
    For five individuals, a social network was constructed from a series of his or her dreams. Three important network measures were calculated for each network: transitivity, assortativity, and giant component proportion. These were monotonically related; over the five networks as transitivity increased, assortativity increased and giant component proportion decreased. The relations indicate that characters appear in dreams systematically. Systematicity likely arises from the dreamer's memory of people and their relations, which is from the dreamer's cognitive social network. But the dream (...)
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  • Editors' Introduction to Networks of the Mind: How Can Network Science Elucidate Our Understanding of Cognition?Thomas T. Hills & Yoed N. Kenett - 2022 - Topics in Cognitive Science 14 (1):189-208.
    Topics in Cognitive Science, Volume 14, Issue 1, Page 189-208, January 2022.
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  • Methodological Considerations for Incorporating Clinical Data Into a Network Model of Retrieval Failures.Nichol Castro - 2022 - Topics in Cognitive Science 14 (1):111-126.
    Difficulty retrieving information (e.g., words) from memory is prevalent in neurogenic communication disorders (e.g., aphasia and dementia). Theoretical modeling of retrieval failures often relies on clinical data, despite methodological limitations (e.g., locus of retrieval failure, heterogeneity of individuals, and progression of disorder/disease). Techniques from network science are naturally capable of handling these limitations. This paper reviews recent work using a multiplex lexical network to account for word retrieval failures and highlights how network science can address the limitations of clinical data. (...)
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  • Graph‐Theoretic Properties of Networks Based on Word Association Norms: Implications for Models of Lexical Semantic Memory.Thomas M. Gruenenfelder, Gabriel Recchia, Tim Rubin & Michael N. Jones - 2016 - Cognitive Science 40 (6):1460-1495.
    We compared the ability of three different contextual models of lexical semantic memory and of a simple associative model to predict the properties of semantic networks derived from word association norms. None of the semantic models were able to accurately predict all of the network properties. All three contextual models over-predicted clustering in the norms, whereas the associative model under-predicted clustering. Only a hybrid model that assumed that some of the responses were based on a contextual model and others on (...)
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  • The Role of Semantic Clustering in Optimal Memory Foraging.Priscilla Montez, Graham Thompson & Christopher T. Kello - 2015 - Cognitive Science 39 (8):1925-1939.
    Recent studies of semantic memory have investigated two theories of optimal search adopted from the animal foraging literature: Lévy flights and marginal value theorem. Each theory makes different simplifying assumptions and addresses different findings in search behaviors. In this study, an experiment is conducted to test whether clustering in semantic memory may play a role in evidence for both theories. Labeled magnets and a whiteboard were used to elicit spatial representations of semantic knowledge about animals. Category recall sequences from a (...)
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