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Topics in Cognitive Science Apr 2023Despite its many twists and turns, the arc of cognitive science generally bends toward progress, thanks to its interdisciplinary nature. By glancing at the last few...
Despite its many twists and turns, the arc of cognitive science generally bends toward progress, thanks to its interdisciplinary nature. By glancing at the last few decades of experimental and computational advances, it can be argued that-far from failing to converge on a shared set of conceptual assumptions-the field is indeed making steady consensual progress toward what can broadly be referred to as interactive frameworks. This inclination is apparent in the subfields of psycholinguistics, visual perception, embodied cognition, extended cognition, neural networks, dynamical systems theory, and more. This pictorial essay briefly documents this steady progress both from a bird's eye view and from the trenches. The conclusion is one of optimism that cognitive science is getting there, albeit slowly and arduously, like any good science should.
Topics: Humans; Cognition; Visual Perception; Psycholinguistics; Neural Networks, Computer; Cognitive Science
PubMed: 36949655
DOI: 10.1111/tops.12645 -
Topics in Cognitive Science Apr 2011We argue that word meanings are not stored in a mental lexicon but are generated in the context of working memory from long-term memory traces that record our experience... (Review)
Review
We argue that word meanings are not stored in a mental lexicon but are generated in the context of working memory from long-term memory traces that record our experience with words. Current statistical models of semantics, such as latent semantic analysis and the Topic model, describe what is stored in long-term memory. The CI-2 model describes how this information is used to construct sentence meanings. This model is a dual-memory model, in that it distinguishes between a gist level and an explicit level. It also incorporates syntactic information about how words are used, derived from dependency grammar. The construction of meaning is conceptualized as feature sampling from the explicit memory traces, with the constraint that the sampling must be contextually relevant both semantically and syntactically. Semantic relevance is achieved by sampling topically relevant features; local syntactic constraints as expressed by dependency relations ensure syntactic relevance.
Topics: Comprehension; Concept Formation; Humans; Language; Memory, Short-Term; Psycholinguistics; Semantics
PubMed: 25164299
DOI: 10.1111/j.1756-8765.2010.01107.x -
Editors' Introduction and Review: Visual Narrative Research: An Emerging Field in Cognitive Science.Topics in Cognitive Science Jan 2020Drawn sequences of images are among our oldest records of human intelligence, appearing on cave paintings, wall carvings, and ancient pottery, and they pervade across...
Drawn sequences of images are among our oldest records of human intelligence, appearing on cave paintings, wall carvings, and ancient pottery, and they pervade across cultures from instruction manuals to comics. They also appear prevalently as stimuli across Cognitive Science, for studies of temporal cognition, event structure, social cognition, discourse, and basic intelligence. Yet, despite this fundamental place in human expression and research on cognition, the study of visual narratives themselves has only recently gained traction in Cognitive Science. This work has suggested that visual narrative comprehension requires cultural exposure across a developmental trajectory and engages with domain-general processing mechanisms shared by visual perception, attention, event cognition, and language, among others. Here, we review the relevance of such research for the broader Cognitive Science community, and make the case for why researchers should join the scholarship of this ubiquitous but understudied aspect of human expression.
Topics: Cognitive Science; Humans; Narration; Pattern Recognition, Visual; Psycholinguistics
PubMed: 31865641
DOI: 10.1111/tops.12473 -
Behavior Research Methods Sep 2023The number of databases that provide various measurements of lexical properties for psycholinguistic research has increased rapidly in recent years. The proliferation of...
The number of databases that provide various measurements of lexical properties for psycholinguistic research has increased rapidly in recent years. The proliferation of lexical variables, and the multitude of associated databases, makes the choice, comparison, and standardization of these variables in psycholinguistic research increasingly difficult. Here, we introduce The South Carolina Psycholinguistic Metabase (SCOPE), which is a metabase (or a meta-database) containing an extensive, curated collection of psycholinguistic variable values from major databases. The metabase currently contains 245 lexical variables, organized into seven major categories: General (e.g., frequency), Orthographic (e.g., bigram frequency), Phonological (e.g., phonological uniqueness point), Orth-Phon (e.g., consistency), Semantic (e.g., concreteness), Morphological (e.g., number of morphemes), and Response variables (e.g., lexical decision latency). We hope that SCOPE will become a valuable resource for researchers in psycholinguistics and affiliated disciplines such as cognitive neuroscience of language, computational linguistics, and communication disorders. The availability and ease of use of the metabase with comprehensive set of variables can facilitate the understanding of the unique contribution of each of the variables to word processing, and that of interactions between variables, as well as new insights and development of improved models and theories of word processing. It can also help standardize practice in psycholinguistics. We demonstrate use of the metabase by measuring relationships between variables in multiple ways and testing their individual contribution towards a number of dependent measures, in the most comprehensive analysis of this kind to date. The metabase is freely available at go.sc.edu/scope.
Topics: Humans; South Carolina; Psycholinguistics; Language; Linguistics; Semantics
PubMed: 35971041
DOI: 10.3758/s13428-022-01934-0 -
PloS One 2019Temperament and Psychological Types can be defined as innate psychological characteristics associated with how we relate with the world, and often influence our study... (Review)
Review
Temperament and Psychological Types can be defined as innate psychological characteristics associated with how we relate with the world, and often influence our study and career choices. Furthermore, understanding these features help us manage conflicts, develop leadership, improve teaching and many other skills. Assigning temperament and psychological types is usually made by filling specific questionnaires. However, it is possible to identify temperamental characteristics from a linguistic and behavioral analysis of social media data from a user. Thus, machine-learning algorithms can be used to learn from a user's social media data and infer his/her behavioral type. This paper initially provides a brief historical review of theories on temperament and then brings a survey of research aimed at predicting temperament and psychological types from social media data. It follows with the proposal of a framework to predict temperament and psychological types from a linguistic and behavioral analysis of Twitter data. The proposed framework infers temperament types following the David Keirsey's model, and psychological types based on the MBTI model. Various data modelling and classifiers are used. The results showed that Random Forests with the LIWC technique can predict with 96.46% of accuracy the Artisan temperament, 92.19% the Guardian temperament, 78.68% the Idealist, and 83.82% the Rational temperament. The MBTI results also showed that Random Forests achieved a better performance with an accuracy of 82.05% for the E/I pair, 88.38% for the S/N pair, 80.57% for the T/F pair, and 78.26% for the J/P pair.
Topics: Behavioral Research; Female; History, 21st Century; Humans; Machine Learning; Male; Models, Psychological; Psycholinguistics; Social Behavior; Social Media; Temperament
PubMed: 30861015
DOI: 10.1371/journal.pone.0212844 -
Evolutionary Psychology : An... May 2015Recently, researchers have begun to investigate the function of memory in our evolutionary history. According to Nairne and colleagues (e.g., Nairne, Pandeirada, and... (Review)
Review
Recently, researchers have begun to investigate the function of memory in our evolutionary history. According to Nairne and colleagues (e.g., Nairne, Pandeirada, and Thompson, 2008; Nairne, Thompson, and Pandeirada, 2007), the best mnemonic strategy for learning lists of unrelated words may be one that addresses the same problems that our Pleistocene ancestors faced: fitness-relevant problems including securing food and water, as well as protecting themselves from predators. Survival processing has been shown to promote better recall and recognition memory than many well-known mnemonic strategies (e.g., pleasantness ratings, imagery, generation, etc.). However, the survival advantage does not extend to all types of stimuli and tasks. The current review presents research that has replicated Nairne et al.'s (2007) original findings, in addition to the research designs that fail to replicate the survival advantage. In other words, there are specific manipulations in which survival processing does not appear to benefit memory any more than other strategies. Potential mechanisms for the survival advantage are described, with an emphasis on those that are the most plausible. These proximate mechanisms outline the memory processes that may contribute to the advantage, although the ultimate mechanism may be the congruity between the survival scenario and Pleistocene problem-solving.
Topics: Humans; Learning; Mental Recall; Problem Solving; Psycholinguistics; Set, Psychology; Survival
PubMed: 25947360
DOI: 10.1177/147470491501300204 -
Topics in Cognitive Science Jul 2019A long-standing question in child language research concerns how children achieve mature syntactic knowledge in the face of a complex linguistic environment. A widely... (Review)
Review
A long-standing question in child language research concerns how children achieve mature syntactic knowledge in the face of a complex linguistic environment. A widely accepted view is that this process involves extracting distributional regularities from the environment in a manner that is incidental and happens, for the most part, without the learner's awareness. In this way, the debate speaks to two associated but separate literatures in language acquisition: statistical learning and implicit learning. Both fields have explored this issue in some depth but, at present, neither the results from the infant studies used by the statistical learning literature nor the artificial grammar learning tasks studies from the implicit learning literature can be used to fully explain how children's syntax becomes adult-like. In this work, we consider an alternative explanation-that children use error-based learning to become mature syntax users. We discuss this proposal in the light of the behavioral findings from structural priming studies and the computational findings from Chang, Dell, and Bock's (2006) dual-path model, which incorporates properties from both statistical and implicit learning, and offers an explanation for syntax learning and structural priming using a common error-based learning mechanism. We then turn our attention to future directions for the field, here suggesting how structural priming might inform the statistical learning and implicit learning literature on the nature of the learning mechanism.
Topics: Child; Child Development; Humans; Learning; Models, Theoretical; Psycholinguistics
PubMed: 30414244
DOI: 10.1111/tops.12396 -
International Journal of... Feb 2015A number of variables—word frequency, word length—have long been known to influence language processing. This study briefly reviews the effects in speech perception... (Review)
Review
A number of variables—word frequency, word length—have long been known to influence language processing. This study briefly reviews the effects in speech perception and production of two more recently examined variables: phonotactic probability and neighbourhood density. It then describes a new approach to study language, network science, which is an interdisciplinary field drawing from mathematics, computer science, physics and other disciplines. In this approach, nodes represent individual entities in a system (i.e. phonological word-forms in the lexicon), links between nodes represent relationships between nodes (i.e. phonological neighbours) and various measures enable researchers to assess the micro-level (i.e. the individual word), the macro-level (i.e. characteristics about the whole system) and the meso-level (i.e. how an individual fits into smaller sub-groups in the larger system). Although research on individual lexical characteristics such as word-frequency has increased understanding of language processing, these measures only assess the "micro-level". Using network science, researchers can examine words at various levels in the system and how each word relates to the many other words stored in the lexicon. Several new findings using the network science approach are summarized to illustrate how this approach can be used to advance basic research as well as clinical practice.
Topics: Adult; Age Factors; Auditory Pathways; Child; Humans; Language Development; Language Disorders; Neural Networks, Computer; Phonetics; Psycholinguistics; Speech; Speech Acoustics; Speech Disorders; Speech Perception; Systems Integration; Systems Theory
PubMed: 25539473
DOI: 10.3109/17549507.2014.987819 -
Psychonomic Bulletin & Review Dec 2019The status of thematic roles such as Agent and Patient in cognitive science is highly controversial: To some they are universal components of core knowledge, to others... (Review)
Review
The status of thematic roles such as Agent and Patient in cognitive science is highly controversial: To some they are universal components of core knowledge, to others they are scholarly fictions without psychological reality. We address this debate by posing two critical questions: to what extent do humans represent events in terms of abstract role categories, and to what extent are these categories shaped by universal cognitive biases? We review a range of literature that contributes answers to these questions: psycholinguistic and event cognition experiments with adults, children, and infants; typological studies grounded in cross-linguistic data; and studies of emerging sign languages. We pose these questions for a variety of roles and find that the answers depend on the role. For Agents and Patients, there is strong evidence for abstract role categories and a universal bias to distinguish the two roles. For Goals and Recipients, we find clear evidence for abstraction but mixed evidence as to whether there is a bias to encode Goals and Recipients as part of one or two distinct categories. Finally, we discuss the Instrumental role and do not find clear evidence for either abstraction or universal biases to structure instrumental categories.
Topics: Concept Formation; Humans; Psycholinguistics; Role
PubMed: 31290008
DOI: 10.3758/s13423-019-01634-5 -
Topics in Cognitive Science Oct 2018Sociolinguists study the interaction between language and society. Variationist sociolinguistics - the subfield of sociolinguistics which is the focus of this issue -... (Review)
Review
Sociolinguists study the interaction between language and society. Variationist sociolinguistics - the subfield of sociolinguistics which is the focus of this issue - uses empirical and quantitative methods to study the production and perception of linguistic variation. Linguistic variation refers to how speakers choose between linguistic forms that say the same thing in different ways, with the variants differing in their social meaning. For example, how frequently someone says fishin' or fishing depends on a number of factors, such as the speaker's regional and social background and the formality of the speech event. Likewise, if listeners are asked to use a rating scale make judgements about speakers who say fishin' or fishing, their ratings depend on what other social characteristics are attributed to the speaker. This issue aims to reflect the growing number of interactions that bring variationist sociolinguistics into contact of different branches of cognitive science. After presenting current trends in sociolinguistics, we identify five areas of contact between the two fields: cognitive sociolinguistics, sociolinguistic cognition, acquisition of variation, computational modeling, and a comparative approach of variation in animal communication. We then explain the benefits of interdisciplinary work: fostering the study of variability and cultural diversity in cognition; bringing together data and modeling; understanding the cognitive mechanisms through which sociolinguistic variation is processed; examining indexical meaning; exploring links between different levels of grammar; and improving methods of data collection and analysis. Finally we explain how the articles in this issue contribute to each of these benefits. We conclude by suggesting that sociolinguistics holds a strategic position for facing the challenge of building theories of language through integrating its linguistic, cognitive, and social aspects at the collective and individual levels.
Topics: Cognitive Science; Humans; Psycholinguistics; Social Sciences
PubMed: 30294877
DOI: 10.1111/tops.12384