Technical NoteAn alternative approach towards assessing and accounting for individual motion in fMRI timeseries
Highlights
► Translations and rotations can be combined into a single measure (total displacement). ► More covariates lead to a progressive loss of detection power (first>second level). ► An individually-derived motion fingerprint can be computed from the data. ► Such a “mfp” explains variance to a similar degree as the realignment parameters. ► This individualized approach to explaining motion-related variance may be beneficial.
Introduction
Functional magnetic resonance imaging (fMRI) has become one of the most widely-used research tools in the basic and clinical neurosciences (Detre, 2006, Logothetis, 2008). While offering many advantages, it is very vulnerable to subject motion (Lemieux et al., 2007, Lund et al., 2005, Wu et al., 1997). Therefore, motion is commonly “corrected for” by aligning the successive images in an fMRI timeseries, usually to the first volume (Friston et al., 1996); however, this does not fully remove all motion effects from the data (Andersson et al., 2001, Wu et al., 1997). Consequently, it was recommended to include these realignment parameters into ensuing statistical analyses (Friston et al., 1996, Lemieux et al., 2007, Salek-Haddadi et al., 2003), potentially as a function of the experimental design (Johnstone et al., 2006). The inclusion of derivatives of these parameters (for example, the Voltera expansion; Friston et al., 1996, Lemieux et al., 2007, Salek-Haddadi et al., 2003) has been shown to additionally explain variance in the data that may be attributed to motion.
However, there seem to be two points that are as yet not fully taken into account, namely that, first, the effects of motion depend on the individual geometry of the brain. As rotations around any given point will lead to a larger displacement further away from the center of rotation than closer to it, identical motion will lead to different effects in different brain regions, or across different subjects. Hence, an individualized assessment of these motion effects may be beneficial. A second concern is that including more covariates will lead to a loss of power in the final statistical model, impacting the individual as well as the group level. Hence, using fewer parameters to explain motion-related variance may be helpful, particularly in less-efficient designs with fewer degrees of freedom (Friston et al., 1999, Josephs et al., 1997, Liu et al., 2001). This technical note is aimed at exploring these aspects.
Section snippets
Subjects
Healthy children were recruited from the community by means of advertisements. In addition to standard MR contraindications, children were excluded if there was a personal history of neurological/psychiatric disorders or prematurity. The institutional review board of the University of Tübingen approved this study. Overall, 21 children were included, 14 boys, 7 girls, 12.5 ± 2.2 years. The first dataset consisted of resting-state fMRI data (Biswal et al., 1995), which has the advantage that both
Total displacement
For davg (average cortical distance from individual origin), a median of 72.5 mm (MAD = 1.48, range, 68.1 to 75.9 mm) was determined. At the individual davg, median total displacement over time over subjects was .47 mm (MAD = .25, range, .08 to 8.1 mm) in the resting state dataset, with one subject showing catastrophic motion (maximum total displacement = 31.8 mm, Fig. 1, upper panel, truncated for better accessibility). For the beep story dataset, these values were .35 mm (MAD = .11, range, .09 to 1.06 mm;
Discussion
This manuscript addresses the question of an individualized assessment of and accounting for motion effects in fMRI timeseries.
Acknowledgements
This work has been supported by the Deutsche Forschungsgemeinschaft DFG (WI3630 1-1). I would like to thank Ingeborg Krägeloh-Mann and Ulrike Ernemann for continued support, and Paul Mazaika and Chloe Hutton for helpful discussions. The code to generate the individual motion fingerprint is available from the author.
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