Optimising neonatal fMRI data analysis: Design and validation of an extended dHCP preprocessing pipeline to characterise noxious-evoked brain activity in infants

Luke Baxter,Sean Fitzgibbon,Fiona Moultrie,Sezgi Goksan,Mark Jenkinson,Stephen Smith,Jesper Andersson,Eugene Duff,Rebeccah Slater

doi:10.1016/j.neuroimage.2018.11.006

Luke Baxter, Sean Fitzgibbon + Show 7 more

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https://doi.org/10.1016/j.neuroimage.2018.11.006

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Abstract

The infant brain is unlike the adult brain, with considerable differences in morphological, neurodynamic, and haemodynamic features. As the majority of current MRI analysis tools were designed for use in adults, a primary objective of the Developing Human Connectome Project (dHCP) is to develop optimised methodological pipelines for the analysis of neonatal structural, resting state, and diffusion MRI data. Here, in an independent neonatal dataset we have extended and optimised the dHCP fMRI preprocessing pipeline for the analysis of stimulus-response fMRI data. We describe and validate this extended dHCP fMRI preprocessing pipeline to analyse changes in brain activity evoked following an acute noxious stimulus applied to the infant's foot. We compare the results obtained from this extended dHCP pipeline to results obtained from a typical FSL FEAT-based analysis pipeline, evaluating the pipelines' outputs using a wide range of tests. We demonstrate that a substantial increase in spatial specificity and sensitivity to signal can be attained with a bespoke neonatal preprocessing pipeline through optimised motion and distortion correction, ICA-based denoising, and haemodynamic modelling. The improved sensitivity and specificity, made possible with this extended dHCP pipeline, will be paramount in making further progress in our understanding of the development of sensory processing in the infant brain.

Highlights

The infant brain is not a miniature replica of the adult brain
Semi-automated independent component analysis (ICA)-based denoising (Salimi-Khorshidi et al, 2014) has previously been adapted for neonatal data (Ball et al, 2016); spatial smoothing extents have been scaled based on infant brain size (Gao et al, 2015); and haemodynamic response function (HRF) modelling has been optimised for a range of neonatal ages (Arichi et al, 2012)
We extended the Developing Human Connectome Project (dHCP) fMRI preprocessing pipeline to characterise the noxious-evoked blood oxygen level dependent (BOLD) activity, and compare the results to a typical analysis using FMRIB Software Library (FSL) FMRI Expert Analysis Tool (FEAT) procedures (Jenkinson et al, 2012) that we have previously used to study these responses in infants (Goksan et al, 2015)

Summary

Introduction

The composition, size, and morphology of the human brain changes rapidly (Dubois et al, 2014; Dubois and Dehaene-Lambertz, 2015), and neurodynamic and haemodynamic activity differs dramatically from that observed in adults (Andre et al, 2010; Arichi et al, 2012) Features such as the high water and low myelin content lead to a reduction in contrast and an inversion of MRI signal between tissue types (Paus et al, 2001), and data quality can be highly influenced by infant movement (Power et al, 2012; Reuter et al, 2015; Satterthwaite et al, 2012; Siegel et al, 2017; Yendiki et al, 2014). This is not an exhaustive list, and those interested in the challenges and progress in neonatal fMRI are directed to recent reviews and references therein (Cusack et al, 2017; Mongerson et al, 2017) for further reading

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