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{
    "pk": 49403,
    "title": "Symbolic numerical generalization through representational alignment",
    "subtitle": null,
    "abstract": "The mapping between nonsymbolic quantities and symbolic\nnumbers lays the foundation for mathematical development\nin children. However, the neural mechanisms underlying\nthis crucial cognitive bridge remain unclear. Here, we in-\nvestigate the computational principles governing symbolic-\nnonsymbolic integration using a biologically inspired neural\nnetwork trained through developmentally inspired stages. Our\ninvestigation reveals that generalization from nonsymbolic to\nsymbolic numerical processing emerges specifically when rep-\nresentational alignment forms between these numerical for-\nmats. Notably, this alignment appears to be stronger in cross-\nformat comparison-based mapping compared to direct-label-\nbased mapping. Furthermore, we demonstrate that subsequent\nsymbolic specialization creates a representational divergence\nthat impairs nonsymbolic performance while maintaining the\nordinal structure of the mapping. These findings highlight rep-\nresentational alignment as a fundamental mechanism in nu-\nmerical cognition and suggest that targeted cross-format com-\nparison tasks may be particularly effective in improving math-\nematical learning in children with numerical processing diffi-\nculties.\nKeywords: Emergence of number semantics, Representa-\ntional alignment, Artificial neural network",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [
        {
            "word": "Artificial Intelligence; Cognitive Neuroscience; Representation; Semantic memory; Computational Modeling; Computational neuroscience; Neural Networks"
        }
    ],
    "section": "Papers with Poster Presentation",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/2zz1n5nx",
    "frozenauthors": [
        {
            "first_name": "Anthony",
            "middle_name": "",
            "last_name": "Strock",
            "name_suffix": "",
            "institution": "Stanford University",
            "department": ""
        },
        {
            "first_name": "Ruizhe",
            "middle_name": "",
            "last_name": "Liu",
            "name_suffix": "",
            "institution": "Stanford University",
            "department": ""
        },
        {
            "first_name": "Rishab",
            "middle_name": "S",
            "last_name": "Iyer",
            "name_suffix": "",
            "institution": "Princeton University",
            "department": ""
        },
        {
            "first_name": "Percy",
            "middle_name": "",
            "last_name": "Mistry",
            "name_suffix": "",
            "institution": "Stanford Unversity",
            "department": ""
        },
        {
            "first_name": "Vinod",
            "middle_name": "",
            "last_name": "Menon",
            "name_suffix": "",
            "institution": "Stanford University",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "2025-01-01T18:00:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49403/galley/37365/download/"
        }
    ]
}