BIROn - Birkbeck Institutional Research Online

    Using multiple short epochs optimises the stability of infant EEG connectivity parameters

    Haartsen, R. and van der Velde, B. and Jones, Emily J.H. and Johnson, Mark H. and Kemner, C. (2020) Using multiple short epochs optimises the stability of infant EEG connectivity parameters. Scientific Reports 10 (12703), ISSN 2045-2322.

    [img] Text
    TRT_EEGfc10mo_MM_forBiron.pdf - Author's Accepted Manuscript
    Restricted to Repository staff only

    Download (1MB)
    [img]
    Preview
    Text
    32408.pdf - Published Version of Record
    Available under License Creative Commons Attribution.

    Download (2MB) | Preview

    Abstract

    Atypicalities in connectivity between brain regions have been implicated in a range of neurocognitive disorders. We require metrics to assess stable individual differences in connectivity in the developing brain, while facing the challenge of limited data quality and quantity. Here, we examine how varying core processing parameters can optimise the test-retest reliability of EEG connectivity measures in infants. EEG was recorded twice with a 1-week interval between sessions in 10- month-olds. EEG alpha connectivity was measured across different epoch lengths and numbers, with the phase lag index (PLI) and debiased weighted PLI (dbWPLI), for both whole-head connectivity and graph theory metrics. We calculated intra-class correlations between sessions for infants with sufficient data for both sessions (N’s = 19 – 41, depending on the segmentation method). Reliability for the whole brain dbWPLI was higher across many short epochs, whereas reliability for the whole brain PLI was higher across fewer long epochs. However, the PLI is confounded by the number of available segments. Reliability was higher for whole brain connectivity than graph theory metrics. Thus, segmenting available data into a high number of short epochs and calculating the dbWPLI is most appropriate for characterising connectivity in populations with limited availability of EEG data.

    Metadata

    Item Type: Article
    School: School of Science > Psychological Sciences
    Research Centres and Institutes: Brain and Cognitive Development, Centre for (CBCD)
    Depositing User: Emily Jones
    Date Deposited: 02 Dec 2020 17:43
    Last Modified: 07 Jul 2021 10:49
    URI: https://eprints.bbk.ac.uk/id/eprint/32408

    Statistics

    Downloads
    Activity Overview
    7Downloads
    19Hits

    Additional statistics are available via IRStats2.

    Archive Staff Only (login required)

    Edit/View Item Edit/View Item