A multi-dataset evaluation of frame censoring for motion correction in task-based fMRI

Jones, Michael S.; Zhu, Zhili; Bajracharya, Aahana; Luor, Austin; Peelle, Jonathan E.

doi:10.1101/2021.10.12.464075

Cited by 3 publications

(3 citation statements)

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“…We included nuisance regressors to capture 1) run intercepts and 2) the average timeseries across white matter and CSF (as segmented by fMIRPrep). To reduce the influence of motion artifacts, we used robust weighted least-squares (Diedrichsen and Shadmehr, 2005; Jones et al, 2021), a procedure for optimally down-weighting noisy TRs.…”

Section: Methodsmentioning

confidence: 99%

Orthogonal neural encoding of targets and distractors supports multivariate cognitive control

Ritz

Shenhav

2022

Preprint

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People can overcome a wide array of mental challenges by coordinating their neural information processing to align with their goals. Recent behavioral work has shown that people can independently control their attention across multiple features during perceptual decision-making, but the structure of the neural representations that enables this multivariate control remains mysterious. We hypothesized that the brain solves this complex coordination problem by orthogonalizing feature-specific representations of task demands and attentional priority, allowing the brain to independently monitor and adjust multiple streams of stimulus information. To test this hypothesis, we measured fMRI activity while participants performed a task designed to tag processing and control over feature-specific information that is task-relevant (targets) versus task-irrelevant (distractors). We then characterized the geometry of these neural representations using a novel multivariate analysis (Encoding Geometry Analysis), estimating where the encoding of different task features is correlated versus orthogonal. We identified feature-specific representations of task demands and attentional priority in the dorsal anterior cingulate cortex (dACC) and intraparietal sulcus (IPS), respectively, consistent with differential roles for these regions in monitoring versus directing information processing. Representations of attentional priority in IPS were fully mediated by the control requirements of the task, associated with behavioral performance, and depended on connectivity with nodes in the frontoparietal control network, suggesting that these representations serve a fundamental role in supporting attentional control. Together, these findings provide evidence for a neural geometry that can enable coordinated control over multiple sources of information.

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Section: Methodsmentioning

confidence: 99%

Orthogonal neural encoding of targets and distractors supports multivariate cognitive control

Ritz

Shenhav

2022

Preprint

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“…To reduce the effects of motion on statistical results we calculated framewise displacement (FD) using the six realignment parameters assuming the head as a sphere with a radius of 50 mm (Power et al, 2012). We censored frames exceeding an FD of 0.5, which resulted in ;8% data loss across all participants (Jones et al, 2021). Frames with FD values exceeding this threshold were modeled out by adding in one additional column to the design matrix for each high-motion scan (compare Lemieux et al, 2007).…”

Section: Experimental Design and Statistical Analysismentioning

confidence: 99%

Increased Connectivity among Sensory and Motor Regions during Visual and Audiovisual Speech Perception

et al. 2021

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In everyday conversation, we usually process the talker's face as well as the sound of the talker's voice. Access to visual speech information is particularly useful when the auditory signal is degraded. Here, we used fMRI to monitor brain activity while adult humans (n = 60) were presented with visual-only, auditory-only, and audiovisual words. The audiovisual words were presented in quiet and in several signal-to-noise ratios. As expected, audiovisual speech perception recruited both auditory and visual cortex, with some evidence for increased recruitment of premotor cortex in some conditions (including in substantial background noise). We then investigated neural connectivity using psychophysiological interaction analysis with seed regions in both primary auditory cortex and primary visual cortex. Connectivity between auditory and visual cortices was stronger in audiovisual conditions than in unimodal conditions, including a wide network of regions in posterior temporal cortex and prefrontal cortex. In addition to whole-brain analyses, we also conducted a region-of-interest analysis on the left posterior superior temporal sulcus (pSTS), implicated in many previous studies of audiovisual speech perception. We found evidence for both activity and effective connectivity in pSTS for visual-only and audiovisual speech, although these were not significant in whole-brain analyses. Together, our results suggest a prominent role for cross-region synchronization in understanding both visual-only and audiovisual speech that complements activity in integrative brain regions like pSTS.

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“…Thus, it is important to discuss the impact of modeling motion outliers and interpolation in the data. Modeling motion outliers through scrubbing is a widely used technique to correct sudden movements of the head, however, it creates temporal discontinuities as it involves some effective data loss, in which volumes to be regressed out do not contribute to the task-related parameter estimates, reducing the available degrees of freedom ( Jones et al, 2021 ). Interpolation overcomes this problem and avoids side effects in the high pass filtering step ( Michielsen et al, 2011 ).…”

Section: Discussionmentioning

confidence: 99%

Task-based functional MRI challenges in clinical neuroscience: Choice of the best head motion correction approach in multiple sclerosis

et al. 2022

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IntroductionFunctional MRI (fMRI) is commonly used for understanding brain organization and connectivity abnormalities in neurological conditions, and in particular in multiple sclerosis (MS). However, head motion degrades fMRI data quality and influences all image-derived metrics. Persistent controversies regarding the best correction strategy motivates a systematic comparison, including methods such as scrubbing and volume interpolation, to find optimal correction models, particularly in studies with clinical populations prone to characterize by high motion. Moreover, strategies for correction of motion effects gain more relevance in task-based designs, which are less explored compared to resting-state, have usually lower sample sizes, and may have a crucial role in describing the functioning of the brain and highlighting specific connectivity changes.MethodsWe acquired fMRI data from 17 early MS patients and 14 matched healthy controls (HC) during performance of a visual task, characterized motion in both groups, and quantitatively compared the most used and easy to implement methods for correction of motion effects. We compared task-activation metrics obtained from: (i) models containing 6 or 24 motion parameters (MPs) as nuisance regressors; (ii) models containing nuisance regressors for 6 or 24 MPs and motion outliers (scrubbing) detected with Framewise Displacement or Derivative or root mean square VARiance over voxelS; and (iii) models with 6 or 24 MPs and motion outliers corrected through volume interpolation. To our knowledge, volume interpolation has not been systematically compared with scrubbing, nor investigated in task fMRI clinical studies in MS.ResultsNo differences in motion were found between groups, suggesting that recently diagnosed MS patients may not present problematic motion. In general, models with 6 MPs perform better than models with 24 MPs, suggesting the 6 MPs as the best trade-off between correction of motion effects and preservation of valuable information. Parsimonious models with 6 MPs and volume interpolation were the best combination for correcting motion in both groups, surpassing the scrubbing methods. A joint analysis regardless of the group further highlighted the value of volume interpolation.DiscussionVolume interpolation of motion outliers is an easy to implement technique, which may be an alternative to other methods and may improve the accuracy of fMRI analyses, crucially in clinical studies in MS and other neurological populations.

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A multi-dataset evaluation of frame censoring for motion correction in task-based fMRI

Cited by 3 publications

References 62 publications

Orthogonal neural encoding of targets and distractors supports multivariate cognitive control

Orthogonal neural encoding of targets and distractors supports multivariate cognitive control

Increased Connectivity among Sensory and Motor Regions during Visual and Audiovisual Speech Perception

Task-based functional MRI challenges in clinical neuroscience: Choice of the best head motion correction approach in multiple sclerosis

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