title: Evaluation of multi-echo ICA denoising for task based fMRI studies: Block designs, rapid event-related designs, and cardiac-gated fMRI.
abstract: Multi-echo fMRI, particularly the multi-echo independent component analysis (ME-ICA) algorithm, has previously proven useful for increasing the sensitivity and reducing false positives for functional MRI (fMRI) based resting state connectivity studies. Less is known about its efficacy for task-based fMRI, especially at the single subject level. This work, which focuses exclusively on individual subject results, compares ME-ICA to single-echo fMRI and a voxel-wise T2(⁎) weighted combination of multi-echo data for task-based fMRI under the following scenarios: cardiac-gated block designs, constant repetition time (TR) block designs, and constant TR rapid event-related designs. Performance is evaluated primarily in terms of sensitivity (i.e., activation extent, activation magnitude, percent detected trials and effect size estimates) using five different tasks expected to evoke neuronal activity in a distributed set of regions. The ME-ICA algorithm significantly outperformed all other evaluated processing alternatives in all scenarios. Largest improvements were observed for the cardiac-gated dataset, where ME-ICA was able to reliably detect and remove non-neural T1 signal fluctuations caused by non-constant repetition times. Although ME-ICA also outperformed the other options in terms of percent detection of individual trials for rapid event-related experiments, only 46% of all events were detected after ME-ICA; suggesting additional improvements in sensitivity are required to reliably detect individual short event occurrences. We conclude the manuscript with a detailed evaluation of ME-ICA outcomes and a discussion of how the ME-ICA algorithm could be further improved. Overall, our results suggest that ME-ICA constitutes a versatile, powerful approach for advanced denoising of task-based fMRI, not just resting-state data.
authors.affiliation: Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States. Electronic address: javier.gonzalez-castillo@nih.gov.
authors.forename: Javier
authors.initials: J
authors.lastname: Gonzalez-Castillo
authors.affiliation: Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States.
authors.forename: Puja
authors.initials: P
authors.lastname: Panwar
authors.affiliation: Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States.
authors.forename: Laura C
authors.initials: LC
authors.lastname: Buchanan
authors.affiliation: Basque Center on Cognition, Brain and Language, San Sebastian, Spain.
authors.forename: Cesar
authors.initials: C
authors.lastname: Caballero-Gaudes
authors.affiliation: Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States.
authors.forename: Daniel A
authors.initials: DA
authors.lastname: Handwerker
authors.affiliation: Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States.
authors.forename: David C
authors.initials: DC
authors.lastname: Jangraw
authors.affiliation: Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States.
authors.forename: Valentinos
authors.initials: V
authors.lastname: Zachariou
authors.affiliation: Functional MRI Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States.
authors.forename: Souheil
authors.initials: S
authors.lastname: Inati
authors.affiliation: Functional MRI Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States.
authors.forename: Vinai
authors.initials: V
authors.lastname: Roopchansingh
authors.affiliation: Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States.
authors.forename: John A
authors.initials: JA
authors.lastname: Derbyshire
authors.affiliation: Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States; Functional MRI Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States.
authors.forename: Peter A
authors.initials: PA
authors.lastname: Bandettini
mesh_terms: D000328:Adult; D000465:Algorithms; D016477:Artifacts; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods; D055424:Cardiac-Gated Imaging Techniques / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D025341:Principal Component Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D059629:Signal-To-Noise Ratio; D013647:Task Performance and Analysis
keywords: Block design; ME-ICA; Multi-echo fMRI; Rapid event related; Sensitivity