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Keith J Holyoak - One of the best experts on this subject based on the ideXlab platform.

  • linking metaphor comprehension with Analogical Reasoning evidence from typical development and autism spectrum disorder
    British Journal of Psychology, 2021
    Co-Authors: Jayne Hamilton, Kinga Morsanyi, Dusan Stamenkovic, Keith J Holyoak
    Abstract:

    We examined the relationship between metaphor comprehension and verbal Analogical Reasoning in young adults who were either typically developing (TD) or diagnosed with Autism Spectrum Disorder (ASD). The ASD sample was highly educated and high in verbal ability, and closely matched to a subset of TD participants on age, gender, educational background, and verbal ability. Additional TD participants with a broader range of abilities were also tested. Each participant solved sets of verbal analogies and metaphors in verification formats, allowing measurement of both accuracy and reaction times. Measures of individual differences in vocabulary, verbal working memory, and autistic traits were also obtained. Accuracy for both the verbal analogy and the metaphor task was very similar across the ASD and matched TD groups. However, reaction times on both tasks were longer for the ASD group. Additionally, stronger correlations between verbal Analogical Reasoning and working memory capacity in the ASD group indicated that processing verbal analogies was more effortful for them. In the case of both groups, accuracy on the metaphor and analogy tasks was correlated. A mediation analysis revealed that after controlling for working memory capacity, the inter-task correlation could be accounted for by the mediating variable of vocabulary knowledge, suggesting that the primary common mechanisms linking the two tasks involve language skills.

  • neural and computational mechanisms of Analogical Reasoning
    bioRxiv, 2019
    Co-Authors: Jeffrey N Chiang, Keith J Holyoak, Yujia Peng, Martin M Monti
    Abstract:

    Summary High-level cognition inevitably involves multiple component processes, which are difficult to distinguish at the neural level. We apply model-guided componential analysis to disaggregate components of verbal Analogical Reasoning, a hallmark of human intelligence. This approach integrates a sequential task design with representational and encoding analyses of fMRI data. The analyses were guided by three computational models of lexical and relation semantics that vary in the specificity of their relation representations. Word2vec-concat is nonrelational (based solely on individual word meanings); Word2vec-diff computes the generic relation between any word pair; and BART derives relational similarity from a set of learned abstract semantic relations (e.g., synonym, antonym, cause-effect). The predictions derived from BART, based on its learned relations, showed the strongest correlation with neural activity in regions including the left posterior parietal cortex (during both relation representation and relation comparison) and rostrolateral prefrontal cortex (during relation comparison). Model-guided componential analysis shows promise as an approach to discovering the neural basis of propositional thought.

  • common and dissociable prefrontal loci associated with component mechanisms of Analogical Reasoning
    Cerebral Cortex, 2010
    Co-Authors: Soohyun Cho, Tyrone D Cannon, Teena D Moody, Leonardo Fernandino, Jeanette A Mumford, Russell A Poldrack, Barbara J Knowlton, Keith J Holyoak
    Abstract:

    The ability to draw analogies requires 2 key cognitive processes, relational integration and resolution of interference. The present study aimed to identify the neural correlates of both component processes of Analogical Reasoning within a single, nonverbal analogy task using event-related functional magnetic resonance imaging. Participants verified whether a visual analogy was true by considering either 1 or 3 relational dimensions. On half of the trials, there was an additional need to resolve interference in order to make a correct judgment. Increase in the number of dimensions to integrate was associated with increased activation in the lateral prefrontal cortex as well as lateral frontal pole in both hemispheres. When there was a need to resolve interference during Reasoning, activation increased in the lateral prefrontal cortex but not in the frontal pole. We identified regions in the middle and inferior frontal gyri which were exclusively sensitive to demands on each component process, in addition to a partial overlap between these neural correlates of each component process. These results indicate that Analogical Reasoning is mediated by the coordination of multiple regions of the prefrontal cortex, of which some are sensitive to demands on only one of these 2 component processes, whereas others are sensitive to both.

  • Analogical Reasoning ability in autistic and typically developing children
    Developmental Science, 2009
    Co-Authors: Kinga Morsanyi, Keith J Holyoak
    Abstract:

    Recent studies (e.g. Dawson et al., 2007) have reported that autistic people perform in the normal range on the Raven Progressive Matrices test, a formal Reasoning test that requires integration of relations as well as the ability to infer rules and form high-level abstractions. Here we compared autistic and typically developing children, matched on age, IQ, and verbal and non-verbal working memory, using both the Raven test and pictorial tests of Analogical Reasoning. Whereas the Raven test requires only formal Analogical Reasoning, the other analogy tests require use of real-world knowledge, as well as inhibition of salient distractors. We found that autistic children performed as well as controls on all these tests of Reasoning with relations. Our findings indicate that the basic ability to reason systematically with relations, for both abstract and thematic materials, is intact in autism.

  • Analogical Reasoning in working memory resources shared among relational integration interference resolution and maintenance
    Memory & Cognition, 2007
    Co-Authors: Keith J Holyoak, Tyrone D Cannon
    Abstract:

    We report a series of experiments using a pictorial analogy task designed to manipulate relational integration, interference resolution, and active maintenance simultaneously. The difficulty of the problems was varied in terms of the number of relations to be integrated, the need for interference resolution, and the duration of maintenance required to correctly solve the analogy. The participants showed decreases in performance when integrating multiple relations, as compared with a single relation, and when interference resolution was required in solving the analogy. When the participants were required to integrate multiple relations while simultaneously engaged in interference resolution, performance was worse, as compared with problems that incorporated either of these features alone. Maintenance of information across delays in the range of 1–4.5 sec led to greater decrements in visual memory, as compared with Analogical Reasoning. Misleading information caused interference when it had been necessarily attended to and maintained in working memory and, hence, had to be actively suppressed. However, sources of conflict within information that had not been attended to or encoded into working memory did not interfere with the ongoing controlled information processing required for relational integration. The findings provide evidence that relational integration and interference resolution depend on shared cognitive resources in working memory during Analogical Reasoning.

Robert G Morrison - One of the best experts on this subject based on the ideXlab platform.

  • a computational account of children s Analogical Reasoning balancing inhibitory control in working memory and relational representation
    Developmental Science, 2011
    Co-Authors: Robert G Morrison, Leonidas A A Doumas, Lindsey E Richland
    Abstract:

    Theories accounting for the development of Analogical Reasoning tend to emphasize either the centrality of relational knowledge accretion or changes in information processing capability. Simulations in LISA (Hummel & Holyoak, 1997, 2003), a neurally inspired computer model of Analogical Reasoning, allow us to explore how these factors may collaboratively contribute to the development of analogy in young children. Simulations explain systematic variations in United States and Hong Kong children’s performance on analogies between familiar scenes (Richland, Morrison & Holyoak, 2006; Richland, Chang, Morrison & Au, 2010). Specifically, changes in inhibition levels in the model’s working-memory system explain the developmental progression in US children’s ability to handle increases in relational complexity and distraction from object similarity during Analogical Reasoning. In contrast, changes in how relations are represented in the model best capture cross-cultural differences in performance between children of the same ages (3‐4 years) in the United States and Hong Kong. We use these results and simulations to argue that the development of Analogical Reasoning in children may best be conceptualized as an equilibrium between knowledge accretion and the maturation of information processing capability.

  • young children s Analogical Reasoning across cultures similarities and differences
    Journal of Experimental Child Psychology, 2010
    Co-Authors: Lindsey E Richland, Tszkit Chan, Robert G Morrison
    Abstract:

    A cross-cultural comparison between U.S. and Hong Kong preschoolers examined factors responsible for young children's Analogical Reasoning errors. On a scene analogy task, both groups had adequate prerequisite knowledge of the key relations, were the same age, and showed similar baseline performance, yet Chinese children outperformed U.S. children on more relationally complex problems. Children from both groups were highly susceptible to choosing a perceptual or semantic distractor during Reasoning when one was present. Taken together, these similarities and differences suggest that (a) cultural differences can facilitate better knowledge representations by allowing more efficient processing of relationally complex problems and (b) inhibitory control is an important factor in explaining the development of children's Analogical Reasoning.

  • children s development of Analogical Reasoning insights from scene analogy problems
    Journal of Experimental Child Psychology, 2006
    Co-Authors: Lindsey E Richland, Robert G Morrison, Keith J Holyoak
    Abstract:

    We explored how relational complexity and featural distraction, as varied in scene analogy problems, affect children's Analogical Reasoning performance. Results with 3- and 4-year-olds, 6- and 7-year-olds, 9- to 11-year-olds, and 13- and 14-year-olds indicate that when children can identify the critical structural relations in a scene analogy problem, development of their ability to reason Analogically interacts with both relational complexity and featural distraction. Error patterns suggest that children are more likely to select a distracting object than to make a relational error for problems that present both possibilities. This tendency decreases with age, and older children make fewer errors overall. The results suggest that changes in Analogical Reasoning with age depend on the interplay among increases in relational knowledge, the capacity to integrate multiple relations, and inhibitory control over featural distraction.

  • relational integration inhibition and Analogical Reasoning in older adults
    Psychology and Aging, 2004
    Co-Authors: Indre V Viskontas, Robert G Morrison, Keith J Holyoak, John E Hummel, Barbara J Knowlton
    Abstract:

    The difficulty of Reasoning tasks depends on their relational complexity, which increases with the number of relations that must be considered simultaneously to make an inference, and on the number of irrelevant items that must be inhibited. The authors examined the ability of younger and older adults to integrate multiple relations and inhibit irrelevant stimuli. Young adults performed well at all but the highest level of relational complexity, whereas older adults performed poorly even at a medium level of relational complexity, especially when irrelevant information was presented. Simulations based on a neurocomputational model of Analogical Reasoning, Learning and Inference with Schemas and Analogies (LISA), suggest that the observed decline in Reasoning performance may be explained by a decline in attention and inhibitory functions in older adults.

  • a neurocomputational model of Analogical Reasoning and its breakdown in frontotemporal lobar degeneration
    Journal of Cognitive Neuroscience, 2004
    Co-Authors: Robert G Morrison, Keith J Holyoak, Daniel C Krawczyk, John E Hummel, Tiffany W Chow, Bruce L Miller, Barbara J Knowlton
    Abstract:

    Analogy is important for learning and discovery and is considered a core component of intelligence. We present a computational account of Analogical Reasoning that is compatible with data we have collected from patients with cortical degeneration of either their frontal or anterior temporal cortices due to frontotemporal lobar degeneration (FTLD). These two patient groups showed different deficits in picture and verbal analogies: frontal lobe FTLD patients tended to make errors due to impairments in working memory and inhibitory abilities, whereas temporal lobe FTLD patients tended to make errors due to semantic memory loss. Using the "Learning and Inference with Schemas and Analogies" model, we provide a specific account of how such deficits may arise within neural networks supporting Analogical problem solving.

Zhe Chen - One of the best experts on this subject based on the ideXlab platform.

  • Analogical Reasoning in children with autism spectrum disorder evidence from an eye tracking approach
    Frontiers in Psychology, 2018
    Co-Authors: Enda Tan, Tracy Nishida, Dan Huang, Zhe Chen
    Abstract:

    The present study examined Analogical Reasoning in children with autism spectrum disorder (ASD) and its relationship with cognitive and executive functioning and processing strategies. Our findings showed that although children with ASD were less competent in solving Analogical problems than typically developing children, this inferior performance was attributable to general cognitive impairments. Eye-movement analyses revealed that children with ASD paid less attention to relational items and showed fewer gaze shifts between relational locations. Nevertheless, these eye-movement patterns did not predict autistic children's behavioral performance. Together, our findings suggest that ASD per se does not entail impairments in Analogical Reasoning. The inferior performance of autistic children on Analogical Reasoning tasks is attributable to deficits in general cognitive and executive functioning.

Kenneth D Forbus - One of the best experts on this subject based on the ideXlab platform.

  • Natural Language Instruction for Analogical Reasoning: An Initial Report
    2020
    Co-Authors: Joseph A Blass, Kenneth D Forbus
    Abstract:

    Abstract. A challenge for any case-based Reasoning system is how to acquire the cases with which to reason. Here we explore acquiring cases via natural language instruction by a person. We show how, using microstories (1-3 sentence stories) expressed in simplified English syntax, small cases -called common sense units -can be incrementally added to improve Analogical Reasoning performance. Keywords: Analogy, Commonsense, Language Understanding, Instruction Introduction A challenge for Analogical Reasoning, or any case-based Reasoning system, is how to acquire the cases with which to reason, a separate challenge from how those cases are reasoned with. Hand-encoding does not scale. Most machine learning systems now focus on feature vectors rather than the relational representations that are the hallmark of analogy. Exceptions, like inductive logic programming [1] and other forms of statistical relational learning [2] themselves require formal representations of examples from an external source. We present a system which acquires cases from a person through natural-language instruction, and show that these cases are useful in a system that reasons by analogy. We accomplish this by expanding our dialogue and natural language understanding (NLU) systems and integrating them with an Analogical Reasoning system. We start by reviewing the Companion cognitive architecture, its language system, and the structure-mapping models and Cyc-derived ontology used. We describe Analogical Chaining (AC), wherein multiple Analogical retrievals elaborate a situation, providing a set of plausible explanations and prediction

  • modeling visual problem solving as Analogical Reasoning
    Psychological Review, 2017
    Co-Authors: Andrew Lovett, Kenneth D Forbus
    Abstract:

    We present a computational model of visual problem solving, designed to solve problems from the Raven's Progressive Matrices intelligence test. The model builds on the claim that Analogical Reasoning lies at the heart of visual problem solving, and intelligence more broadly. Images are compared via structure mapping, aligning the common relational structure in 2 images to identify commonalities and differences. These commonalities or differences can themselves be reified and used as the input for future comparisons. When images fail to align, the model dynamically rerepresents them to facilitate the comparison. In our analysis, we find that the model matches adult human performance on the Standard Progressive Matrices test, and that problems which are difficult for the model are also difficult for people. Furthermore, we show that model operations involving abstraction and rerepresentation are particularly difficult for people, suggesting that these operations may be critical for performing visual problem solving, and Reasoning more generally, at the highest level. (PsycINFO Database Record

  • Analogical Reasoning and conceptual change a case study of johannes kepler
    The Journal of the Learning Sciences, 1997
    Co-Authors: Dedre Gentner, Sarah K Brem, Ronald W Ferguson, Arthur B Markman, Bjorn B Levidow, Phillip Wolff, Kenneth D Forbus
    Abstract:

    The work of Johannes Kepler offers clear examples of conceptual change. In this article, using Kepler's work as a case study, we argue that Analogical Reasoning facilitates change of knowledge in four ways: (a) highlighting, (b) projection, (c) rerepresentation, and (d) restructuring. We present these four mechanisms within the context of structure-mapping theory and its computational implementation, the structure-mapping engine. We exemplify these mechanisms using the extended analogies Kepler used in developing a causal theory of planetary motion.

Christelle Maillart - One of the best experts on this subject based on the ideXlab platform.

  • how language and inhibition influence Analogical Reasoning in children with or without developmental language disorder
    Journal of Clinical and Experimental Neuropsychology, 2020
    Co-Authors: Magali Krzemien, Jeanpierre Thibaut, Christelle Maillart
    Abstract:

    Introduction: Analogical Reasoning is a human ability of crucial importance in several domains of cognition, such as numerical abilities, social cognition, and language, and which is impair...

  • Analogical Reasoning in children with specific language impairment evidence from a scene analogy task
    Clinical Linguistics & Phonetics, 2017
    Co-Authors: Magali Krzemien, Boutheina Jemel, Christelle Maillart
    Abstract:

    Analogical Reasoning is a human ability that maps systems of relations. It develops along with relational knowledge, working memory and executive functions such as inhibition. It also maintains a mutual influence on language development. Some authors have taken a greater interest in the Analogical Reasoning ability of children with language disorders, specifically those with specific language impairment (SLI). These children apparently have weaker Analogical Reasoning abilities than their aged-matched peers without language disorders. Following cognitive theories of language acquisition, this deficit could be one of the causes of language disorders in SLI, especially those concerning productivity. To confirm this deficit and its link to language disorders, we use a scene analogy task to evaluate the Analogical performance of SLI children and compare them to controls of the same age and linguistic abilities. Results show that children with SLI perform worse than age-matched peers, but similar to language-matched peers. They are more influenced by increased task difficulty. The association between language disorders and Analogical Reasoning in SLI can be confirmed. The hypothesis of limited processing capacity in SLI is also being considered.