Results for ' computer modeling'

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  1.  29
    Computer modelling of neural tube defects.David Dunnett, Anthony Goodbody & Martin Stanisstreet - 1991 - Acta Biotheoretica 39 (1):63-79.
    Neurulation, the curling of the neuroepithelium to form the neural tube, is an essential component of the development of animal embryos. Defects of neural tube formation, which occur with an overall frequency of one in 500 human births, are the cause of severe and distressing congenital abnormalities. However, despite the fact that there is increasing information from animal experiments about the mechanisms which effect neural tube formation, much less is known about the fundamental causes of neural tube defects (NTD). The (...)
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  2.  17
    Computer modelling of ion migration in zirconia.Martin Kilo, Robert A. Jackson & Günter Borchardt - 2003 - Philosophical Magazine 83 (29):3309-3325.
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  3.  29
    Cost-benefits of computer modelling.Jaak Panksepp - 1979 - Behavioral and Brain Sciences 2 (1):114-114.
  4.  10
    Musical pragmatics and computer modelling Alan A. Marsden.Alan A. Marsden - 1995 - In Eero Tarasti (ed.), Musical signification: essays in the semiotic theory and analysis of music. New York: Mouton de Gruyter. pp. 121--335.
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  5. Computational Modeling in Cognitive Science: A Manifesto for Change.Caspar Addyman & Robert M. French - 2012 - Topics in Cognitive Science 4 (3):332-341.
    Computational modeling has long been one of the traditional pillars of cognitive science. Unfortunately, the computer models of cognition being developed today have not kept up with the enormous changes that have taken place in computer technology and, especially, in human-computer interfaces. For all intents and purposes, modeling is still done today as it was 25, or even 35, years ago. Everyone still programs in his or her own favorite programming language, source code is rarely (...)
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  6. Tacit knowledg and the problem of computer modelling cognitive processes in science.Stephen P. Turner - 1989 - In Steve Fuller (ed.), The Cognitive turn: sociological and psychological perspectives on science. Boston: Kluwer Academic Publishers.
    In what follows I propose to bring out certain methodological properties of projects of modelling the tacit realm that bear on the kinds of modelling done in connection with scientific cognition by computer as well as by ethnomethodological sociologists, both of whom must make some claims about the tacit in the course of their efforts to model cognition. The same issues, I will suggest, bear on the project of a cognitive psychology of science as well.
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  7.  10
    Computational Modeling of the Segmentation of Sentence Stimuli From an Infant Word‐Finding Study.Daniel Swingley & Robin Algayres - 2024 - Cognitive Science 48 (3):e13427.
    Computational models of infant word‐finding typically operate over transcriptions of infant‐directed speech corpora. It is now possible to test models of word segmentation on speech materials, rather than transcriptions of speech. We propose that such modeling efforts be conducted over the speech of the experimental stimuli used in studies measuring infants' capacity for learning from spoken sentences. Correspondence with infant outcomes in such experiments is an appropriate benchmark for models of infants. We demonstrate such an analysis by applying the (...)
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  8.  7
    Review: Alan Bundy, The Computer Modelling of Mathematical Reasoning. [REVIEW]Vladimir Lifschitz - 1987 - Journal of Symbolic Logic 52 (2):555-557.
  9.  16
    Alan Bundy. The computer modelling of mathematical reasoning. Academic Press, London etc. 1983, xiv + 322 pp. [REVIEW]Vladimir Lifschitz - 1987 - Journal of Symbolic Logic 52 (2):555-557.
  10. Computational modeling in philosophy: introduction to a topical collection.Simon Scheller, Christoph Merdes & Stephan Hartmann - 2022 - Synthese 200 (2):1-10.
    Computational modeling should play a central role in philosophy. In this introduction to our topical collection, we propose a small topology of computational modeling in philosophy in general, and show how the various contributions to our topical collection fit into this overall picture. On this basis, we describe some of the ways in which computational models from other disciplines have found their way into philosophy, and how the principles one found here still underlie current trends in the field. (...)
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  11.  61
    Computational Modeling in Philosophy.Simon Scheller, Merdes Christoph & Stephan Hartmann (eds.) - 2022
    Computational modeling should play a central role in philosophy. In this introduction to our topical collection, we propose a small topology of computational modeling in philosophy in general, and show how the various contributions to our topical collection ft into this overall picture. On this basis, we describe some of the ways in which computational models from other disciplines have found their way into philosophy, and how the principles one found here still underlie current trends in the feld. (...)
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  12. Computational Modeling as a Philosophical Methodology.Patrick Grim - 2003 - In Luciano Floridi (ed.), The Blackwell guide to the philosophy of computing and information. Blackwell. pp. 337–349.
    Since the sixties, computational modeling has become increasingly important in both the physical and the social sciences, particularly in physics, theoretical biology, sociology, and economics. Sine the eighties, philosophers too have begun to apply computational modeling to questions in logic, epistemology, philosophy of science, philosophy of mind, philosophy of language, philosophy of biology, ethics, and social and political philosophy. This chapter analyzes a selection of interesting examples in some of those areas.
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  13. From Computer Metaphor to Computational Modeling: The Evolution of Computationalism.Marcin Miłkowski - 2018 - Minds and Machines 28 (3):515-541.
    In this paper, I argue that computationalism is a progressive research tradition. Its metaphysical assumptions are that nervous systems are computational, and that information processing is necessary for cognition to occur. First, the primary reasons why information processing should explain cognition are reviewed. Then I argue that early formulations of these reasons are outdated. However, by relying on the mechanistic account of physical computation, they can be recast in a compelling way. Next, I contrast two computational models of working memory (...)
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  14.  40
    Computer Modeling in Philosophy of Religion.F. LeRon Shults - 2019 - Open Philosophy 2 (1):108-125.
    How might philosophy of religion be impacted by developments in computational modeling and social simulation? After briefly describing some of the content and context biases that have shaped traditional philosophy of religion, this article provides examples of computational models that illustrate the explanatory power of conceptually clear and empirically validated causal architectures informed by the bio-cultural sciences. It also outlines some of the material implications of these developments for broader metaphysical and metaethical discussions in philosophy. Computer modeling (...)
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  15.  21
    Computational Modeling of Cognition and Behavior.Simon Farrell & Stephan Lewandowsky - 2017 - Cambridge University Press.
    Computational modeling is now ubiquitous in psychology, and researchers who are not modelers may find it increasingly difficult to follow the theoretical developments in their field. This book presents an integrated framework for the development and application of models in psychology and related disciplines. Researchers and students are given the knowledge and tools to interpret models published in their area, as well as to develop, fit, and test their own models. Both the development of models and key features of (...)
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  16. Computational modeling vs. computational explanation: Is everything a Turing machine, and does it matter to the philosophy of mind?Gualtiero Piccinini - 2007 - Australasian Journal of Philosophy 85 (1):93 – 115.
    According to pancomputationalism, everything is a computing system. In this paper, I distinguish between different varieties of pancomputationalism. I find that although some varieties are more plausible than others, only the strongest variety is relevant to the philosophy of mind, but only the most trivial varieties are true. As a side effect of this exercise, I offer a clarified distinction between computational modelling and computational explanation.<br><br>.
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  17. Computer Modeling in Climate Science: Experiment, Explanation, Pluralism.Wendy S. Parker - 2003 - Dissertation, University of Pittsburgh
    Computer simulation modeling is an important part of contemporary scientific practice but has not yet received much attention from philosophers. The present project helps to fill this lacuna in the philosophical literature by addressing three questions that arise in the context of computer simulation of Earth's climate. Computer simulation experimentation commonly is viewed as a suspect methodology, in contrast to the trusted mainstay of material experimentation. Are the results of computer simulation experiments somehow deeply problematic (...)
     
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  18.  20
    Five Ways in Which Computational Modeling Can Help Advance Cognitive Science: Lessons From Artificial Grammar Learning.Willem Zuidema, Robert M. French, Raquel G. Alhama, Kevin Ellis, Timothy J. O'Donnell, Tim Sainburg & Timothy Q. Gentner - 2020 - Topics in Cognitive Science 12 (3):925-941.
    Zuidema et al. illustrate how empirical AGL studies can benefit from computational models and techniques. Computational models can help clarifying theories, and thus in delineating research questions, but also in facilitating experimental design, stimulus generation, and data analysis. The authors show, with a series of examples, how computational modeling can be integrated with empirical AGL approaches, and how model selection techniques can indicate the most likely model to explain experimental outcomes.
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  19.  28
    Computer modeling and simulation: towards epistemic distinction between verification and validation.Vitaly Pronskikh - unknown
    Verification and validation of computer codes and models used in simulation are two aspects of the scientific practice of high importance and have recently been discussed by philosophers of science. While verification is predominantly associated with the correctness of the way a model is represented by a computer code or algorithm, validation more often refers to model’s relation to the real world and its intended use. It has been argued that because complex simulations are generally not transparent to (...)
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  20.  17
    Computer Modeling and Simulation: Increasing Reliability by Disentangling Verification and Validation.Vitaly Pronskikh - 2019 - Minds and Machines 29 (1):169-186.
    Verification and validation of computer codes and models used in simulations are two aspects of the scientific practice of high importance that recently have been discussed widely by philosophers of science. While verification is predominantly associated with the correctness of the way a model is represented by a computer code or algorithm, validation more often refers to the model’s relation to the real world and its intended use. Because complex simulations are generally opaque to a practitioner, the Duhem (...)
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  21.  59
    A Computational Modeling Strategy for Levels.John Symons - 2008 - Philosophy of Science 75 (5):608-620.
    Rather than taking the ontological fundamentality of an ideal microphysics as a starting point, this article sketches an approach to the problem of levels that swaps assumptions about ontology for assumptions about inquiry. These assumptions can be implemented formally via computational modeling techniques that will be described below. It is argued that these models offer a way to save some of our prominent commonsense intuitions concerning levels. This strategy offers a way of exploring the individuation of higher level properties (...)
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  22. A Computational Modeling Approach on Three‐Digit Number Processing.Stefan Huber, Korbinian Moeller, Hans-Christoph Nuerk & Klaus Willmes - 2013 - Topics in Cognitive Science 5 (2):317-334.
    Recent findings indicate that the constituting digits of multi-digit numbers are processed, decomposed into units, tens, and so on, rather than integrated into one entity. This is suggested by interfering effects of unit digit processing on two-digit number comparison. In the present study, we extended the computational model for two-digit number magnitude comparison of Moeller, Huber, Nuerk, and Willmes (2011a) to the case of three-digit number comparison (e.g., 371_826). In a second step, we evaluated how hundred-decade and hundred-unit compatibility effects (...)
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  23.  25
    Computational modeling of interventions for developmental disorders.Michael S. C. Thomas, Anna Fedor, Rachael Davis, Juan Yang, Hala Alireza, Tony Charman, Jackie Masterson & Wendy Best - 2019 - Psychological Review 126 (5):693-726.
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  24. Dynamic mechanistic explanation: computational modeling of circadian rhythms as an exemplar for cognitive science.William Bechtel & Adele Abrahamsen - 2010 - Studies in History and Philosophy of Science Part A 41 (3):321-333.
    Two widely accepted assumptions within cognitive science are that (1) the goal is to understand the mechanisms responsible for cognitive performances and (2) computational modeling is a major tool for understanding these mechanisms. The particular approaches to computational modeling adopted in cognitive science, moreover, have significantly affected the way in which cognitive mechanisms are understood. Unable to employ some of the more common methods for conducting research on mechanisms, cognitive scientists’ guiding ideas about mechanism have developed in conjunction (...)
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  25.  49
    Computationally modeling interpersonal trust.Jin Joo Lee, W. Bradley Knox, Jolie B. Wormwood, Cynthia Breazeal & David DeSteno - 2013 - Frontiers in Psychology 4.
  26. The computational modeling of inferential and referential competence.Fabrizio Calzavarini & Antonio Lieto - 2018 - In Fabrizio Calzavarini & Antonio Lieto (eds.), AISC 2018 Proceedings.
  27.  30
    Computational modeling of reading in semantic dementia: Comment on Woollams, Lambon Ralph, Plaut, and Patterson (2007).Max Coltheart, Jeremy J. Tree & Steven J. Saunders - 2010 - Psychological Review 117 (1):256-271.
  28.  22
    Computational modeling of analogy: Destined ever to only be metaphor?Ann Speed - 2008 - Behavioral and Brain Sciences 31 (4):397-398.
    The target article by Leech et al. presents a compelling computational theory of analogy-making. However, there is a key difficulty that persists in theoretical treatments of analogy-making, computational and otherwise: namely, the lack of a detailed account of the neurophysiological mechanisms that give rise to analogy behavior. My commentary explores this issue.
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  29. Understanding scientists' computational modeling decisions about climate risk management strategies using values-informed mental models.Lauren Mayer, Kathleen Loa, Bryan Cwik, Nancy Tuana, Klaus Keller, Chad Gonnerman, Andrew Parker & Robert Lempert - 2017 - Global Environmental Change 42:107-116.
    When developing computational models to analyze the tradeoffs between climate risk management strategies (i.e., mitigation, adaptation, or geoengineering), scientists make explicit and implicit decisions that are influenced by their beliefs, values and preferences. Model descriptions typically include only the explicit decisions and are silent on value judgments that may explain these decisions. Eliciting scientists’ mental models, a systematic approach to determining how they think about climate risk management, can help to gain a clearer understanding of their modeling decisions. In (...)
     
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  30.  17
    Modeling Misretrieval and Feature Substitution in Agreement Attraction: A Computational Evaluation.Dario Paape, Serine Avetisyan, Sol Lago & Shravan Vasishth - 2021 - Cognitive Science 45 (8):e13019.
    We present computational modeling results based on a self‐paced reading study investigating number attraction effects in Eastern Armenian. We implement three novel computational models of agreement attraction in a Bayesian framework and compare their predictive fit to the data using k‐fold cross‐validation. We find that our data are better accounted for by an encoding‐based model of agreement attraction, compared to a retrieval‐based model. A novel methodological contribution of our study is the use of comprehension questions with open‐ended responses, so (...)
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  31.  11
    Archaeological computer graphic modelling, simulation and spatial interpretation.Graeme Earl - forthcoming - Perspectives on Science.
  32. Computational modeling in cognitive neuroscience.M. J. Farah - 2000 - In Martha J. Farah & Todd E. Feinberg (eds.), Patient-Based Approaches to Cognitive Neuroscience. MIT Press. pp. 53--62.
     
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  33. Computer modeling and the fate of folk psychology.John A. Barker - 2002 - Metaphilosophy 33 (1-2):30-48.
    Although Paul Churchland and Jerry Fodor both subscribe to the so-called theory-theory– the theory that folk psychology (FP) is an empirical theory of behavior – they disagree strongly about FP’s fate. Churchland contends that FP is a fundamentally flawed view analogous to folk biology, and he argues that recent advances in computational neuroscience and connectionist AI point toward development of a scientifically respectable replacement theory that will give rise to a new common-sense psychology. Fodor, however, wagers that FP will be (...)
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  34.  32
    Computer simulation modelling and visualization of 3d architecture of biological tissues.Carole J. Clem & Jean Paul Rigaut - 1995 - Acta Biotheoretica 43 (4):425-442.
    Recent technical improvements, such as 3D microscopy imaging, have shown the necessity of studying 3D biological tissue architecture during carcinogenesis. In the present paper a computer simulation model is developed allowing the visualization of the microscopic biological tissue architecture during the development of metaplastic and dysplastic lesions.The static part of the model allows the simulation of the normal, metaplastic and dysplastic architecture of an external epithelium. This model is associated to a knowledge base which contains only data on the (...)
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  35.  22
    7T MRI and Computational Modeling Supports a Critical Role of Lead Location in Determining Outcomes for Deep Brain Stimulation: A Case Report.Lauren E. Schrock, Remi Patriat, Mojgan Goftari, Jiwon Kim, Matthew D. Johnson, Noam Harel & Jerrold L. Vitek - 2021 - Frontiers in Human Neuroscience 15.
    Subthalamic nucleus deep brain stimulation is an established therapy for Parkinson’s disease motor symptoms. The ideal site for implantation within STN, however, remains controversial. While many argue that placement of a DBS lead within the sensorimotor territory of the STN yields better motor outcomes, others report similar effects with leads placed in the associative or motor territory of the STN, while still others assert that placing a DBS lead “anywhere within a 6-mm-diameter cylinder centered at the presumed middle of the (...)
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  36.  26
    A computational modeling approach to investigating mind wandering-related adjustments to gaze behavior during scene viewing.Kristina Krasich, Kevin O'Neill, Samuel Murray, James R. Brockmole, Felipe De Brigard & Antje Nuthmann - 2024 - Cognition 242 (C):105624.
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  37.  60
    Conjectures and manipulations. Computational modeling and the extra- theoretical dimension of scientific discovery.Lorenzo Magnani - 2004 - Minds and Machines 14 (4):507-538.
    Computational philosophy (CP) aims at investigating many important concepts and problems of the philosophical and epistemological tradition in a new way by taking advantage of information-theoretic, cognitive, and artificial intelligence methodologies. I maintain that the results of computational philosophy meet the classical requirements of some Peircian pragmatic ambitions. Indeed, more than a 100 years ago, the American philosopher C.S. Peirce, when working on logical and philosophical problems, suggested the concept of pragmatism(pragmaticism, in his own words) as a logical criterion to (...)
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  38.  94
    Autonomy and Automation: Computational Modeling, Reduction, and Explanation in Quantum Chemistry.Johannes Lenhard - 2014 - The Monist 97 (3):339-358.
    This paper discusses how computational modeling combines the autonomy of models with the automation of computational procedures. In particular, the case of ab-initio methods in quantum chemistry will be investigated to draw two lessons from the analysis of computational modeling. The first belongs to general philosophy of science: Computational modeling faces a trade-off and enlarges predictive force at the cost of explanatory force. The other lesson is about the philosophy of chemistry: The methodology of computational modeling (...)
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  39. Computer modeling of cognition: Levels of analysis.Michael Rw Dawson - 2002 - In Lynn Nadel (ed.), The Encyclopedia of Cognitive Science. Macmillan.
  40. Computer modeling and the fate of folk psychology.John A. Barker - 2002 - In James Moor & Terrell Ward Bynum (eds.), Cyberphilosophy: the intersection of philosophy and computing. Malden, MA: Blackwell.
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  41.  53
    Reciprocal modelling of active perception of 2-d forms in a simple tactile-vision substitution system.John Stewart & Olivier Gapenne - 2004 - Minds and Machines 14 (3):309-330.
    The strategies of action employed by a human subject in order to perceive simple 2-D forms on the basis of tactile sensory feedback have been modelled by an explicit computer algorithm. The modelling process has been constrained and informed by the capacity of human subjects both to consciously describe their own strategies, and to apply explicit strategies; thus, the strategies effectively employed by the human subject have been influenced by the modelling process itself. On this basis, good qualitative and (...)
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  42.  19
    Guidelines for Computational Modeling of Friendship.William F. Clocksin - 2023 - Zygon 58 (4):1045-1061.
    Humans participate in an immense variety of relationships with other persons and other entities: human and nonhuman, living and nonliving, tangible and intangible, real and imagined. Participation in relationships is considered a key benchmark of personhood. Some of these relationships, particularly friendships, involve close emotional attachments, and some friendships have been described since antiquity as spiritual in nature. Different types of friendship depend upon factors such as proximity, social formality, physical intimacy, information exchanged, and the costs and benefits of maintaining (...)
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  43.  49
    Complexity of a modelling exercise: A discussion of the role of computer simulation in complex system science.Fabio Boschetti, David McDonald & Randall Gray - 2008 - Complexity 13 (6):21-28.
  44.  12
    The Presence of Background Noise Extends the Competitor Space in Native and Non‐Native Spoken‐Word Recognition: Insights from Computational Modeling.Themis Karaminis, Florian Hintz & Odette Scharenborg - 2022 - Cognitive Science 46 (2):e13110.
    Oral communication often takes place in noisy environments, which challenge spoken-word recognition. Previous research has suggested that the presence of background noise extends the number of candidate words competing with the target word for recognition and that this extension affects the time course and accuracy of spoken-word recognition. In this study, we further investigated the temporal dynamics of competition processes in the presence of background noise, and how these vary in listeners with different language proficiency (i.e., native and non-native) using (...)
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  45.  51
    Issues in computer modeling of cognitive phenomena: An artificial intelligence perspective.Jaime G. Carbonell - 1981 - Behavioral and Brain Sciences 4 (4):536-537.
  46.  13
    for learning by imitation Computational modeling.Aude Billard & Michael Arbib - 2002 - In Maxim I. Stamenov & Vittorio Gallese (eds.), Mirror Neurons and the Evolution of Brain and Language. John Benjamins. pp. 42--343.
  47. An evaluation of computational modeling in cognitive science.M. A. Boden - 2008 - In Ron Sun (ed.), The Cambridge handbook of computational psychology. New York: Cambridge University Press. pp. 667--683.
     
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  48.  17
    Bernsteinian physiology and computational modeling: East meets West at the “boundary”.Gary Goldberg & Hon C. Kwan - 1985 - Behavioral and Brain Sciences 8 (1):153-154.
  49.  21
    Two Routes to Face Perception: Evidence From Psychophysics and Computational Modeling.Adrian Schwaninger, Janek S. Lobmaier, Christian Wallraven & Stephan Collishaw - 2009 - Cognitive Science 33 (8):1413-1440.
    The aim of this study was to separately analyze the role of featural and configural face representations. Stimuli containing only featural information were created by cutting the faces into their parts and scrambling them. Stimuli only containing configural information were created by blurring the faces. Employing an old‐new recognition task, the aim of Experiments 1 and 2 was to investigate whether unfamiliar faces (Exp. 1) or familiar faces (Exp. 2) can be recognized if only featural or configural information is provided. (...)
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  50.  13
    Anatomy and computational modeling of networks underlying cognitive-emotional interaction.Yohan J. John, Daniel Bullock, Basilis Zikopoulos & Helen Barbas - 2013 - Frontiers in Human Neuroscience 7.
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