Group-wise alignment of resting fMRI in space and time

Haleh Akrami; Anand A. Joshi; Jian Li; Richard M. Leahy

doi:10.1117/12.2512564

15 March 2019 Group-wise alignment of resting fMRI in space and time

Haleh Akrami, Anand A. Joshi, Jian Li, Richard M. Leahy

Proceedings Volume 10949, Medical Imaging 2019: Image Processing; 109492W (2019) https://doi.org/10.1117/12.2512564
Event: SPIE Medical Imaging, 2019, San Diego, California, United States

Abstract

Spontaneous brain activity is an important biomarker for various neurological and psychological conditions and can be measured using resting functional Magnetic Resonance Imaging (rfMRI). Since brain activity during resting is spontaneous, it is not possible to directly compare rfMRI time-courses across subjects. Moreover, the spatial configuration of functionally specialized brain regions can vary across subjects throughout the cortex limiting our ability to make precise spatial comparisons. We describe a new approach to jointly align and synchronize fMRI data in space and time, across a group of subjects. We build on previously described methods for inter-subject spatial “Hyper-Alignment” and temporal synchronization through the “BrainSync” transform. We first describe BrainSync Alignment (BSA), a group-based extension of the pair-wise BrainSync transform, that jointly synchronizes resting or task fMRI data across time for multiple subjects. We then explore the combination of BSA with Response Hyper-Alignment (RHA) and compare with Connectivity Hyper-Alignment (CHA), an alternative approach to spatial alignment based on resting fMRI. The result of applying RHA and BSA is both to produce improved functional spatial correspondence across a group of subjects, and to align their time-series so that, even for spontaneous resting data, we see highly correlated temporal dynamics at homologous locations across the group. These spatiotemporally aligned data can then be used as an atlas in future applications. We validate these transfer functions by applying them to z-score maps of an independent dataset and calculating inter-subject correlation. The results show that RHA can be calculated from rfMRI and have comparable output with CHA by leveraging BSA. Moreover, through calculation and application to task fMRI-based spatial transformations on an independent dataset, we show that the combination of RHA and BSA produces improved spatial functional alignment significantly relative to either RHA or CHA alone.

Citation Download Citation

Haleh Akrami, Anand A. Joshi, Jian Li, and Richard M. Leahy "Group-wise alignment of resting fMRI in space and time", Proc. SPIE 10949, Medical Imaging 2019: Image Processing, 109492W (15 March 2019); https://doi.org/10.1117/12.2512564

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