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Didier Le Gall - One of the best experts on this subject based on the ideXlab platform.
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Involvement of Technical Reasoning More Than Functional Knowledge in Development of Tool Use in Childhood.
Frontiers in psychology, 2016Co-Authors: Chrystelle Remigereau, Arnaud Roy, Orianne Costini, François Osiurak, Christophe Jarry, Didier Le GallAbstract:It is well-known that even toddlers are able to manipulate tools in an appropriate manner according to their physical properties. The ability of children to make novel tools in order to solve problems is, however, surprisingly limited. In adults, mechanical problem solving has been proposed to be supported by “technical reasoning skills,” which are thought to be involved in every situation requiring the use of a tool (whether conventional or unusual). The aim of this study was to investigate the typical development of real tool use skills and its link with technical reasoning abilities in healthy children. Three experimental tasks were adapted from those used with adults: mechanical problem solving (three different apparatus), real tool use (10 familiar tool-object pairs), and Functional Knowledge (10 Functional picture matching with familiar tools previously used). The tasks were administered to 85 healthy children divided into six age groups (from 6 to 14 years of age). The results revealed that real tool use (p = .01) and mechanical problem solving skills improve with age, even if this improvement differs according to the apparatus for the latter (p < .01 for the Hook task and p < .05 for the Sloping task). Results also showed that mechanical problem solving is a better predictor of real tool use than Functional Knowledge, with a significant and greater weight (importance weight: 0.65; Estimate±Standard Error: 0.27±0.08). Ours findings suggest that real tool use and technical reasoning develop jointly in children, independently from development of Functional Knowledge. In addition, technical reasoning appears partially operative from the age of 6 onwards, even though the outcome of these skills depends of the context in which they are applied (i.e., the type of apparatus).
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Involvement of Technical Reasoning More Than Functional Knowledge in Development of Tool Use in Childhood
Frontiers in Psychology, 2016Co-Authors: Chrystelle Remigereau, Arnaud Roy, Orianne Costini, François Osiurak, Christophe Jarry, Didier Le GallAbstract:It is well-known that even toddlers are able to manipulate tools in an appropriate manner according to their physical properties. The ability of children to make novel tools in order to solve problems is, however, surprisingly limited. In adults, mechanical problem solving (MPS) has been proposed to be supported by "technical reasoning skills," which are thought to be involved in every situation requiring the use of a tool (whether conventional or unusual). The aim of this study was to investigate the typical development of real tool use (RTU) skills and its link with technical reasoning abilities in healthy children. Three experimental tasks were adapted from those used with adults: MPS (three different apparatus), RTU (10 familiar tool-object pairs), and Functional Knowledge (FK; 10 Functional picture matching with familiar tools previously used). The tasks were administered to 85 healthy children divided into six age groups (from 6 to 14 years of age). The results revealed that RTU ( = 0.01) and MPS skills improve with age, even if this improvement differs according to the apparatus for the latter ( < 0.01 for the Hook task and < 0.05 for the Sloping task). Results also showed that MPS is a better predictor of RTU than FK, with a significant and greater weight (importance weight: 0.65; Estimate ± Standard Error: 0.27 ± 0.08). Ours findings suggest that RTU and technical reasoning develop jointly in children, independently from development of FK. In addition, technical reasoning appears partially operative from the age of six onward, even though the outcome of these skills depends of the context in which they are applied (i.e., the type of apparatus).
Solène Kalénine - One of the best experts on this subject based on the ideXlab platform.
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CogSci - Neurophysiological Correlates of Thematic and Functional Knowledge Activation during Object Conceptual Processing
Cognitive Science, 2014Co-Authors: Yannick Wamain, Ewa Pluciennicka, Solène KalénineAbstract:Neurophysiological Correlates of Thematic and Functional Knowledge Activation during Object Conceptual Processing Yannick Wamain (ywamain@gmail.com) Universite Lille Nord de France, F-59000 Lille, France UDL3, URECA, F-59653 Villeneuve d'Ascq Cedex, France Ewa Pluciennicka (ewa.pluciennicka@univ-lille3.fr) Universite Lille Nord de France, F-59000 Lille, France UDL3, URECA, F-59653 Villeneuve d'Ascq Cedex, France Solene Kalenine (solene.kalenine@univ-lille3.fr) Universite Lille Nord de France, F-59000 Lille, France UDL3, IRHIS, F-59653 Villeneuve d'Ascq Cedex, France CNRS, URM8529, F-59653 Villeneuve d'Ascq Cedex, France Abstract Behavioral studies suggest that manipulable artifact concepts are largely organized around action-based Knowledge with thematic and Functional relations being privileged ways to group objects together. Moreover, recent eye tracking studies have shown that thematic and Functional Knowledge are activated with different temporal dynamics during object conceptual processing. In order to assess the neurophysiological correlates of thematic and Functional Knowledge activation, we used a priming paradigm in which Event-Related Potentials were recorded during object identification. The neural response was analyzed as a function of the type of semantic relation shared by prime and target objects: Thematic [saw-wood], Specific Function [saw-axe] and General Function [saw-knife]. Results revealed graded priming effects on the N400 component that could be related to processing time course differences. Findings support the hypothesis of distinct cognitive and neurophysiological mechanisms underlying thematic and Functional Knowledge. Keywords: EEG, Semantic priming, Thematic Functional Knowledge, Manipulable artifacts. and Introduction Increasing evidence indicates that action-related information is a central part of our Knowledge about manipulable artifacts (i.e., manipulable manmade objects). For example, damage to Functional/motor feature information has been associated with selective deficits in artifact Knowledge (Farah & McClelland, 1991). In property generation tasks, Functional/motor properties are produced relatively more frequently in response to artifact than natural object concepts (Cree & McRae, 2003; Garrard, Lambon Ralph, Hodges, & Patterson, 2001; McRae, Cree, Seidenberg, & McNorgan, 2005). Moreover, object recognition and categorization can be facilitated by the prior presentation of another object that shares action-related features (Helbig, Graf, & Kiefer, 2006; Labeye, Oker, Badard, & Versace, 2008; Myung, Blumstein, & Sedivy, 2006). These behavioral data, in addition to numerous neuroimaging findings showing activation of the visuo-motor system during processing of manipulable artifact concepts (Martin, 2007; Noppeney, 2008), are generally consistent with the proposal that object conceptual Knowledge is grounded in sensory and motor systems (Barsalou, 1999, 2008; Borghi, 2005; Gallese & Lakoff, 2005). The relevance of action-related information for manipulable artifact concepts is also consistent with previous work in the categorization domain. Categorization studies have shown that thematic and Functional relations are particularly relevant for manipulable artifacts. In the case of manipulable artifacts, thematic relations typically correspond to tool-recipient relationships (e.g., screwdriver- screw), and are more quickly processed than categorical relations (e.g., screwdriver-hammer; Kalenine & Bonthoux, 2008). Moreover, recent neuroimaging evidence (Kalenine et al., 2009) indicates that identification of thematic associations selectively activates brain regions associated with the visuo-motor system (temporo-parietal areas), further supporting the close link between thematic relation processing and some aspect of object use experience. In addition, contrary to natural object categories (e.g. animals), manipulable artifacts are largely characterized by Functional attributes associated with object use (Cree & McRae, 2003; Garrard et al., 2001; McRae et al., 2005), suggesting that Functional similarities play an important role in object semantic structure. For example, hammer and screwdriver are assumed to belong to the same category because they are both used to repair things. Taken together, these findings suggest that manipulable artifact concepts are largely organized around action-based Knowledge, with thematic and Functional relations being privileged ways to group objects together. Yet little is known about how these two types of information can be articulated in object semantic structure. Thematic and Functional similarity relation processing has been the focus of a few previous behavioral studies. One of them used an explicit forced-choice task (Kalenine et al., 2009) in order to compare identification speed of thematic and categorical relations. Results showed faster explicit
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Temporal dynamics of activation of thematic and Functional Knowledge during conceptual processing of manipulable artifacts.
Journal of experimental psychology. Learning memory and cognition, 2012Co-Authors: Solène Kalénine, Daniel Mirman, Erica L. Middleton, Laurel J. BuxbaumAbstract:The current research aimed at specifying the activation time course of different types of semantic information during object conceptual processing and the effect of context on this time course. We distinguished between thematic and Functional Knowledge and the specificity of Functional similarity. Two experiments were conducted with healthy older adults using eye tracking in a word-to-picture matching task. The time course of gaze fixations was used to assess activation of distractor objects during the identification of manipulable artifact targets (e.g., broom). Distractors were (a) thematically related (e.g., dustpan), (b) related by a specific function (e.g., vacuum cleaner), or (c) related by a general function (e.g., sponge). Growth curve analyses were used to assess competition effects when target words were presented in isolation (Experiment 1) and embedded in contextual sentences of different generality levels (Experiment 2). In the absence of context, there was earlier and shorter lasting activation of thematically related as compared to Functionally related objects. The time course difference was more pronounced for general functions than specific functions. When contexts were provided, Functional similarities that were congruent with context generality level increased in salience with earlier activation of those objects. Context had little impact on thematic activation time course. These data demonstrate that processing a single manipulable artifact concept implicitly activates thematic and Functional Knowledge with different time courses and that context speeds activation of context-congruent Functional similarity.
René Garcia - One of the best experts on this subject based on the ideXlab platform.
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Incorporating Functional Knowledge in Neural Networks
Journal of Machine Learning Research, 2009Co-Authors: Charles Dugas, Yoshua Bengio, François Bélisle, Claude Nadeau, René GarciaAbstract:Incorporating prior Knowledge of a particular task into the architecture of a learning algorithm can greatly improve generalization performance. We study here a case where we know that the function to be learned is non-decreasing in its two arguments and convex in one of them. For this purpose we propose a class of functions similar to multi-layer neural networks but (1) that has those properties, (2) is a universal approximator of Lipschitz functions with these and other properties. We apply this new class of functions to the task of modelling the price of call options. Experiments show improvements on regressing the price of call options using the new types of function classes that incorporate the a priori constraints.
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incorporating second order Functional Knowledge for better option pricing
Neural Information Processing Systems, 2000Co-Authors: Charles Dugas, Yoshua Bengio, François Bélisle, Claude Nadeau, René GarciaAbstract:Incorporating prior Knowledge of a particular task into the architecture of a learning algorithm can greatly improve generalization performance. We study here a case where we know that the function to be learned is non-decreasing in two of its arguments and convex in one of them. For this purpose we propose a class of functions similar to multi-layer neural networks but (1) that has those properties, (2) is a universal approximator of continuous functions with these and other properties. We apply this new class of functions to the task of modeling the price of call options. Experiments show improvements on regressing the price of call options using the new types of function classes that incorporate the a priori constraints.
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NIPS - Incorporating Second-Order Functional Knowledge for Better Option Pricing
2000Co-Authors: Charles Dugas, Yoshua Bengio, François Bélisle, Claude Nadeau, René GarciaAbstract:Incorporating prior Knowledge of a particular task into the architecture of a learning algorithm can greatly improve generalization performance. We study here a case where we know that the function to be learned is non-decreasing in two of its arguments and convex in one of them. For this purpose we propose a class of functions similar to multi-layer neural networks but (1) that has those properties, (2) is a universal approximator of continuous functions with these and other properties. We apply this new class of functions to the task of modeling the price of call options. Experiments show improvements on regressing the price of call options using the new types of function classes that incorporate the a priori constraints.
Dana Samson - One of the best experts on this subject based on the ideXlab platform.
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On disentangling and weighting kinds of semantic Knowledge
Behavioral and Brain Sciences, 2001Co-Authors: Agnesa Pillon, Dana SamsonAbstract:To account for category-specific semantic deficits, Humphreys and Forde propose to fractionate semantic memory into multiple sensory and Functional Knowledge stores. There axe reasons to doubt the empirical productivity of this proposal, unless theoretically motivated principles of distinguishing and weighting the different kinds of object Knowledge can be spelled out in detail.
Haja N. Kadarmideen - One of the best experts on this subject based on the ideXlab platform.
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FunctSNP: an R package to link SNPs to Functional Knowledge and dbAutoMaker: a suite of Perl scripts to build SNP databases
BMC bioinformatics, 2010Co-Authors: Stephen J. Goodswen, Cedric Gondro, Nathan S. Watson-haigh, Haja N. KadarmideenAbstract:Background: Whole genome association studies using highly dense single nucleotide polymorphisms (SNPs) are a set of methods to identify DNA markers associated with variation in a particular complex trait of interest. One of the main outcomes from these studies is a subset of statistically significant SNPs. Finding the potential biological functions of such SNPs can be an important step towards further use in human and agricultural populations (e.g., for identifying genes related to susceptibility to complex diseases or genes playing key roles in development or performance). The current challenge is that the information holding the clues to SNP functions is distributed across many different databases. Efficient bioinformatics tools are therefore needed to seamlessly integrate up-to-date Functional information on SNPs. Many web services have arisen to meet the challenge but most work only within the framework of human medical research. Although we acKnowledge the importance of human research, we identify there is a need for SNP annotation tools for other organisms. Description: We introduce an R package called FunctSNP, which is the user interface to custom built species-specific databases. The local relational databases contain SNP data together with Functional annotations extracted from online resources. FunctSNP provides a unified bioinformatics resource to link SNPs with Functional Knowledge (e.g., genes, pathways, ontologies). We also introduce dbAutoMaker, a suite of Perl scripts, which can be scheduled to run periodically to automatically create/update the customised SNP databases. We illustrate the use of FunctSNP with a livestock example, but the approach and software tools presented here can be applied also to human and other organisms. Conclusions: Finding the potential Functional significance of SNPs is important when further using the outcomes from whole genome association studies. FunctSNP is unique in that it is the only R package that links SNPs to Functional annotation. FunctSNP interfaces to local SNP customised databases which can be built for any species contained in the National Center for Biotechnology Information dbSNP database.
