Abstract
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.
Highlights
The period of the first thousand days of life – from conception to 2 years of age – is a critical stage in the development of the brain and nervous system (Bornstein, 2014; Cusick and Georgieff, 2012; Mendez and Adair, 1999; Powell et al, 1995)
Using image reconstruction to quantify and isolate the effects of variability in head size and array position, we find that inferences drawn from group-level channel-space Functional near-infrared spectroscopy (fNIRS) analyses are unlikely to be significantly affected by these assumptions given the variability of these parameters in our dataset, though their effect is much more influential at the individuallevel
Using an image reconstruction approach to analyse longitudinallyacquired infant fNIRS data, we have found that inferences drawn from group-level channel-space fNIRS analyses are robust to the implicit assumptions of constant head size and array position
Summary
The period of the first thousand days of life – from conception to 2 years of age – is a critical stage in the development of the brain and nervous system (Bornstein, 2014; Cusick and Georgieff, 2012; Mendez and Adair, 1999; Powell et al, 1995). While longitudinal studies of brain function play an important role in understanding development, less than a third of developmental neuroimaging studies published between 2008 and 2019 employed this design (Azhari et al, 2020). While there has been an overall decreasing trend in published neuroimaging infant studies over the past decade (Azhari et al, 2020), recently and there has been an increase in the number of studies employing functional near-infrared spectroscopy. This technique, abbreviated to fNIRS, is a non-invasive optical neuroimaging technique measuring changes in cortical haemoglobin concentration as a marker of functional activation (Lloyd-Fox et al, 2010; Pinti et al, 2020).
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