{
  "abstract": "Translation of laboratory-derived metrics to quantify learning in naturalistic settings is an important goal in neuroscience. In the current study we tested if a common neural metric of visual attention, alpha-range (8–12 Hz) oscillations, generalizes from laboratory to naturalistic learning. We recorded electroencephalography (EEG) in eighty 6–10-year-old children while they participated in naturalistic learning activities and during a laboratory spatial working memory task ( n = 51 final sample). We found that alpha power during the activities did not correlate with event-related alpha power modulations (ERMs) during stimulus processing in the laboratory task, a common indicator of visual attention. By contrast, multiple control analyses showed the expected relationships among baseline activity, task-related modulation and behavioral performance. These results suggest that alpha ERMs during task processing reflect different neural processes of visual attention than alpha power during learning activities – potentially reflecting additional contributions from arousal, motivation or motor activity in naturalistic environments. These findings suggest that laboratory-derived neural metrics of visual attention may not directly generalize to naturalistic learning, highlighting the need to consider multiple contributing processes when translating laboratory-derived neural metrics to naturalistic learning.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 8,
  "authors": [
    {
      "name": "Fang Yu Chang"
    },
    {
      "name": "Xinyi Zoe Mao"
    },
    {
      "name": "Maya Khalil"
    },
    {
      "name": "Mark D. Rapport"
    },
    {
      "name": "Andrea Dillon"
    },
    {
      "name": "Sandra K. Loo"
    },
    {
      "name": "Jennie K. Grammer"
    },
    {
      "name": "Agatha Lenartowicz",
      "orcid": "0000-0001-8015-8251"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/f9dd26h996smh.bib",
  "cited_by": 0,
  "doi": "10.1038/s41598-026-76587-6",
  "fulltext_url": null,
  "id": "f9dd26h996smh",
  "issns": [
    "2045-2322"
  ],
  "landing_url": "https://www.nature.com/articles/s41598-026-76587-6",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2805|Neural dynamics and brain function"
    ]
  ],
  "openalex": "W7223684810",
  "pdf_url": "https://www.nature.com/articles/s41598-026-76587-6_reference.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-26",
  "publisher": "Springer Science and Business Media LLC",
  "ris": "https://research.draconitic.com/paper/f9dd26h996smh.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:34Z",
      "native_id": "10.1038/s41598-026-76587-6",
      "source": "crossref",
      "url": "https://www.nature.com/articles/s41598-026-76587-6"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "openalex:2805|Neural dynamics and brain function",
      "subfield": "neuroscience"
    }
  ],
  "title": "Mechanisms and measurement of attention in laboratory tasks versus naturalistic learning contexts",
  "title_text": "Mechanisms and measurement of attention in laboratory tasks versus naturalistic learning contexts",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:34Z",
  "url": "https://research.draconitic.com/paper/f9dd26h996smh",
  "venue": "Scientific Reports",
  "versions": []
}