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{
    "pk": 24392,
    "title": "Modeling infant cortical tracking of statistical learning in simple recurrent networks",
    "subtitle": null,
    "abstract": "Consider a classic statistical learning (SL) paradigm, where participants hear an uninterrupted stream of syllables in seemingly random order. In fact, the sequence is generated by repeating 4 word-like patterns, each comprised of 3 syllables. After brief exposure, adults and infants can discriminate ‘words' from the sequence from other syllable sequences (‘nonwords' that did not occur in exposure). If syllables have a fixed duration (e.g., 333.3 ms), syllable rate is fixed (e.g., 3/s or 3hz) and so is word rate (e.g., 1hz). If EEG is acquired during exposure, neural phase-locking is observed, initially to the syllable rate, and gradually to the word rate. This has been interpreted as a neural index of word learning. We tested whether two models that can simulate human SL behavior could simulate neural entrainment (Simple Recurrent Net- works [SRNs] or multi-layer perceptrons [MLPs, feedforward neural networks]). Both models could, although SRNs provided a better fit to correlations observed between entrainment and behavior. We also discovered that raw input sequences (even for a single syllable) have rhythmic properties that generate apparent ‘entrainment' when treated like EEG signals – without learning. We discuss theoretical implications for SL and challenges for interpreting phase-locked entrainment.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [
        {
            "word": "Cognitive Neuroscience; Language development; Statistical learning; Computational neuroscience; Electroencephalography (EEG)"
        }
    ],
    "section": "Papers with Poster Presentation",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/2fh04209",
    "frozenauthors": [
        {
            "first_name": "Qihui",
            "middle_name": "",
            "last_name": "Xu",
            "name_suffix": "",
            "institution": "Ohio State University",
            "department": ""
        },
        {
            "first_name": "Guro Stensby",
            "middle_name": "",
            "last_name": "Sjuls",
            "name_suffix": "",
            "institution": "Norwegian University of Science and Technology",
            "department": ""
        },
        {
            "first_name": "Marina",
            "middle_name": "",
            "last_name": "Kalashnikova",
            "name_suffix": "",
            "institution": "Basque Center on Cognition, Brain and Language",
            "department": ""
        },
        {
            "first_name": "James",
            "middle_name": "",
            "last_name": "Magnuson",
            "name_suffix": "",
            "institution": "University of Connecticut",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "2024-01-01T18:00:00Z",
    "render_galley": null,
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            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24392/galley/13989/download/"
        },
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24392/galley/21371/download/"
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}