Article Instance

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{
    "pk": 32754,
    "title": "A Computational Model of Number Comparison",
    "subtitle": null,
    "abstract": "Number comparison is a task that has been widely used to investigate the mental representation of number magnitudes. It is frequently assumed that the mapping from numerals to a \"mental number line\" is compressive (i.e., logarithmic) or that magnitude representations have the property of scalar variability. In this study, w e simulate the process of selecting the larger of two numbers in a neural network model. We show that it is possible to account for the main experimental effects (e.g., the distance effect and the number size effect) with a simple architecture using a linear representation of numerical magnitudes. The compressive effects that are found in the reaction times emerge from the non-linear interactions that are intrinsic to the decision process.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [],
    "section": "Long Papers",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/00q3v9j1",
    "frozenauthors": [
        {
            "first_name": "Marco",
            "middle_name": "",
            "last_name": "Zorzi",
            "name_suffix": "",
            "institution": "Dipartimento di Psicologia Generale, Universita di Padova",
            "department": ""
        },
        {
            "first_name": "Brian",
            "middle_name": "",
            "last_name": "Butterworth",
            "name_suffix": "",
            "institution": "Institute of Cognitive Neuroscience, University College London",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "1999-01-01T21:00:00+03:00",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/32754/galley/23815/download/"
        }
    ]
}