Abstract
The amplitudes of spontaneous fluctuations in brain activity may be a significant source of within-subject and between-subject variability, and this variability is likely to be carried through into functional connectivity (FC) estimates (whether directly or indirectly). Therefore, improving our understanding of amplitude fluctuations over the course of a resting state scan and variation in amplitude across individuals is of great relevance to the interpretation of FC findings. We investigate resting state amplitudes in two large-scale studies (HCP and UK Biobank), with the aim of determining between-subject and within-subject variability. Between-subject clustering distinguished between two groups of brain networks whose amplitude variation across subjects were highly correlated with each other, revealing a clear distinction between primary sensory and motor regions (‘primary sensory/motor cluster’) and cognitive networks. Within subjects, all networks in the primary sensory/motor cluster showed a consistent increase in amplitudes from the start to the end of the scan. In addition to the strong increases in primary sensory/motor amplitude, a large number of changes in FC were found when comparing the two scans acquired on the same day (HCP data). Additive signal change analysis confirmed that all of the observed FC changes could be fully explained by changes in amplitude. Between-subject correlations in UK Biobank data showed a negative correlation between primary sensory/motor amplitude and average sleep duration, suggesting a role of arousal. Our findings additionally reveal complex relationships between amplitude and head motion. These results suggest that network amplitude is a source of significant variability both across subjects, and within subjects on a within-session timescale. Future rfMRI studies may benefit from obtaining arousal-related (self report) measures, and may wish to consider the influence of amplitude changes on measures of (dynamic) functional connectivity.
Highlights
The Human Connectome Project (HCP) is a unique neuroimaging research resource, consisting of an extensive set of high quality imaging data from a large number of healthy subjects (Van Essen et al, 2013)
The amplitudes of spontaneous fluctuations in brain activity may be a significant source of variability which is commonly overlooked, despite its direct relevance to measures of functional connectivity
Our findings showed a between-subject clustering that separated resting state networks into two clusters based on their amplitudes
Summary
The Human Connectome Project (HCP) is a unique neuroimaging research resource, consisting of an extensive set of high quality imaging data from a large number of healthy subjects (Van Essen et al, 2013). Several studies have been published that use the wealth of betweensubject information available in the HCP data These studies have, for example, identified brain correlates of a positive-negative behavioural mode of population variation (Smith et al, 2015), and have showed that connectivity profiles can be used to predict fluid intelligence (Finn et al, 2015). A recent study has revealed that the withinsubject patterns of associations between functional connectivity and motion are very similar to the between-subject patterns of associations between functional connectivity and motion (Siegel et al, 2016). This suggests that subject head motion forms an important potential confound for correlational studies
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