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

Auditory Perception / physiology Cerebral Cortex / diagnostic imaging Child Development / physiology Functional Neuroimaging / methods Gambia Humans Image Processing, Computer-Assisted / methods Infant Longitudinal Studies Social Perception Spectroscopy, Near-Infrared / methods Visual Perception / physiology

Functional near-infrared spectroscopy Image reconstruction Infant cognitive development Infant functional neuroimaging Longitudinal imaging Neurodevelopment

Journal

NeuroImage

ISSN: 1095-9572

Titre abrégé: Neuroimage

Pays: United States

ID NLM: 9215515

Informations de publication

Date de publication:
15 08 2021

Historique:

received: 01 12 2020

revised: 12 03 2021

accepted: 08 04 2021

pubmed: 30 4 2021

medline: 29 10 2021

entrez: 29 4 2021

Statut: ppublish

Résumé

The first 1000 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.

Identifiants

DOI: 10.1016/j.neuroimage.2021.118068 PMID: 33915275 PMC: PMC8285580

pubmed: 33915275

pii: S1053-8119(21)00345-1

doi: 10.1016/j.neuroimage.2021.118068

pmc: PMC8285580

pii:

doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng