Multiband acceleration can provide moderate improvements in single-subject voxel-wise statistics in block-design task-based fMRI

Multiband (MB) acceleration of functional magnetic resonance imaging has become more widely available to neuroscientists. Here we compare MB factors of 1, 2 and 4 while participants view complex hand actions vs. simpler hand movements to localize the action observation network. While in a previous study, we show that MB4 shows moderate improvements in the group-level statistics, here we explore the impact it has on single subject statistics. We find that MB4 provides an increase in p values at the first level that is of medium effect size compared to MB1, providing moderate evidence across a number of voxels that MB4 indeed improves single subject statistics. This effect was localized mostly within regions that belong to the action observation network. In parallel, we find that Cohen’s d at the single subject level actually decreases using MB4 compared to MB1. Intriguingly, we find that subsampling MB4 sequences, by only considering every fourth acquired volume, also leads to increased Cohen’s d values, suggesting that the FAST algorithm we used to correct for temporal auto-correlation may over-penalize sequences with higher temporal autocorrelation, thereby underestimating the potential gains in single subject statistics offered by MB acceleration, and alternative methods should be explored. In summary, considering the moderate gains in statistical values observed both at the group level in our previous study and at the single subject level in this study, we believe that MB technology is now ripe for neuroscientists to start using MB4 acceleration for their studies, be it to accurately map activity in single subjects of interest (e.g. for presurgical planning or to explore rare patients) or for the purpose of group studies.

[1]  Steen Moeller,et al.  Multiband multislice GE‐EPI at 7 tesla, with 16‐fold acceleration using partial parallel imaging with application to high spatial and temporal whole‐brain fMRI , 2010, Magnetic resonance in medicine.

[2]  Stephen M Smith,et al.  Correspondence of the brain's functional architecture during activation and rest , 2009, Proceedings of the National Academy of Sciences.

[3]  Z. Vidnyánszky,et al.  Reducing task-based fMRI scanning time using simultaneous multislice echo planar imaging , 2018, Neuroradiology.

[4]  Steen Moeller,et al.  Functional Sensitivity of 2D Simultaneous Multi-Slice Echo-Planar Imaging: Effects of Acceleration on g-factor and Physiological Noise , 2017, Front. Neurosci..

[5]  David W Carmichael,et al.  Optimal repetition time reduction for single subject event‐related functional magnetic resonance imaging , 2018, Magnetic resonance in medicine.

[6]  Markus Barth,et al.  Serial correlations in single-subject fMRI with sub-second TR , 2017, NeuroImage.

[7]  Lorenzo De Angelis,et al.  Does higher sampling rate (multiband + SENSE) improve group statistics - An example from social neuroscience block design at 3T , 2020, NeuroImage.

[8]  Klaus Scheffler,et al.  Effect of temporal resolution and serial autocorrelations in event‐related functional MRI , 2016, Magnetic resonance in medicine.

[9]  C. Keysers,et al.  The Observation and Execution of Actions Share Motor and Somatosensory Voxels in all Tested Subjects: Single-Subject Analyses of Unsmoothed fMRI Data , 2008, Cerebral cortex.

[10]  Peter J. Koopmans,et al.  Improved sensitivity and specificity for resting state and task fMRI with multiband multi-echo EPI compared to multi-echo EPI at 7T , 2015, NeuroImage.

[11]  Steen Moeller,et al.  Evaluation of 2D multiband EPI imaging for high-resolution, whole-brain, task-based fMRI studies at 3T: Sensitivity and slice leakage artifacts , 2016, NeuroImage.

[12]  Klaus Scheffler,et al.  Evaluating the impact of fast-fMRI on dynamic functional connectivity in an event-based paradigm , 2018, PloS one.

[13]  Pre-surgical Language Mapping in Epilepsy: Using fMRI in Chinese-Speaking Patients , 2019, Front. Hum. Neurosci..

[14]  Peter J. Koopmans,et al.  Whole brain, high resolution spin-echo resting state fMRI using PINS multiplexing at 7T , 2012, NeuroImage.

[15]  Stephen M. Smith,et al.  Multiplexed Echo Planar Imaging for Sub-Second Whole Brain FMRI and Fast Diffusion Imaging , 2010, PloS one.

[16]  C. Stippich,et al.  Diagnostic benefits of presurgical fMRI in patients with brain tumours in the primary sensorimotor cortex , 2011, European Radiology.

[17]  Amanda F. Mejia,et al.  Zen and the Art of Multiple Comparisons , 2015, Psychosomatic medicine.

[18]  Klaudius Kalcher,et al.  Scanning fast and slow: current limitations of 3 Tesla functional MRI and future potential , 2014, Front. Physics.

[19]  Steen Moeller,et al.  ICA-based artefact removal and accelerated fMRI acquisition for improved resting state network imaging , 2014, NeuroImage.

[20]  Rexford D. Newbould,et al.  A comprehensive evaluation of increasing temporal resolution with multiband-accelerated protocols and effects on statistical outcome measures in fMRI , 2018, NeuroImage.

[21]  Vivek Prabhakaran,et al.  Usage of fMRI for pre-surgical planning in brain tumor and vascular lesion patients: Task and statistical threshold effects on language lateralization☆☆☆ , 2014, NeuroImage: Clinical.

[22]  Valentin Riedl,et al.  Evaluation of Multiband EPI Acquisitions for Resting State fMRI , 2015, PloS one.

[23]  Steen Moeller,et al.  Evaluation of highly accelerated simultaneous multi-slice EPI for fMRI , 2015, NeuroImage.

[24]  Song Zhi,et al.  Quantum dynamics of tight-binding networks coherently controlled by external fields , 2007 .