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Longitudinal infant fNIRS channel-space analyses are robust to variability parameters at the group-level: an image reconstruction investigation.

Collins-Jones, LH; Cooper, RJ; Bulgarelli, C; Blasi, A; Katus, L; McCann, S; Mason, L; ... BRIGHT Study Team; + view all (2021) Longitudinal infant fNIRS channel-space analyses are robust to variability parameters at the group-level: an image reconstruction investigation. Neuroimage , Article 118068. 10.1016/j.neuroimage.2021.118068. Green open access

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Abstract

The first 1,000 days from conception to two-years of age are a critical period in brain development, and there is an increasing drive for developing technologies to help advance our understanding of neurodevelopmental processes during this time. Functional near-infrared spectroscopy (fNIRS) has enabled longitudinal infant brain function to be studied in a multitude of settings. Conventional fNIRS analyses tend to occur in the channel-space, where data from equivalent channels across individuals are combined, which implicitly assumes that head size and source-detector positions (i.e. array position) on the scalp are constant across individuals. The validity of such assumptions in longitudinal infant fNIRS analyses, where head growth is most rapid, has not previously been investigated. We employed an image reconstruction approach to analyse fNIRS data collected from a longitudinal cohort of infants in The Gambia aged 5- to 12-months. This enabled us to investigate the effect of variability in both head size and array position on the anatomical and statistical inferences drawn from the data at both the group- and the individual-level. We also sought to investigate the impact of group size on inferences drawn from the data. We found that variability in array position was the driving factor between differing inferences drawn from the data at both the individual- and group-level, but its effect was weakened as group size increased towards the full cohort size (N = 53 at 5-months, N = 40 at 8-months and N = 45 at 12-months). We conclude that, at the group sizes in our dataset, group-level channel-space analysis of longitudinal infant fNIRS data is robust to assumptions about head size and array position given the variability in these parameters in our dataset. These findings support a more widespread use of image reconstruction techniques in longitudinal infant fNIRS studies.

Type: Article
Title: Longitudinal infant fNIRS channel-space analyses are robust to variability parameters at the group-level: an image reconstruction investigation.
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.neuroimage.2021.118068
Publisher version: https://doi.org/10.1016/j.neuroimage.2021.118068
Language: English
Additional information: © 2021 The Author(s). Published by Elsevier Inc.This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Keywords: Functional near-infrared spectroscopy, image reconstruction, infant cognitive development, infant functional neuroimaging, longitudinal imaging, neurodevelopment
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10127519
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