Reporting of Resting-State Functional Magnetic Resonance Imaging Preprocessing Methodologies

Waheed, Syed Hamza; Mirbagheri, Saeedeh; Agarwal, Shruti; Kamali, Arash; Yahyavi-Firouz-Abadi, Noushin; Chaudhry, Ammar; DiGianvittorio, Michael; Gujar, Sachin K.; Pillai, Jay J.; Sair, Haris I.

doi:10.1089/brain.2016.0446

Cited by 26 publications

(20 citation statements)

References 33 publications

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“…For inclusion in this set of analyses, participants needed to have usable data from encoding and retrieval fMRI scans, including above-chance recognition memory performance, as well as at least 5 min of usable RSFC data from pre-encoding and post-encoding (Waheed et al, 2016). (Although additional measures were gathered as part of the larger study, they were not examined for this analysis and therefore were not required for data inclusion.)…”

Section: Participantsmentioning

confidence: 99%

Post-Encoding Amygdala-Visuosensory Coupling Is Associated with Negative Memory Bias in Healthy Young Adults

Kark

Kensinger

2019

J. Neurosci.

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The amygdala is well documented as the critical nexus of emotionally enhanced memory, yet its role in the creation of negative memory biases, better memory for negative compared with positive stimuli, has not been clarified. Although prior work suggests valence-specific effects at the moment of "online" encoding and retrieval, with enhanced visuosensory processes supporting negative memories in particular, here we tested the novel hypothesis that the amygdala engages with distant cortical regions after encoding in a manner that predicts inter-individual differences in negative memory biases in humans. Twenty-nine young adults (males and females) were scanned while they incidentally encoded negative, neutral, and positive scenes, each preceded by a line-drawing sketch of the scene. Twenty-four hours later, participants were scanned during an Old/New recognition memory task with only the line-drawings presented as retrieval cues. We replicated and extended our prior work, showing that enhanced online visuosensory recapitulation supports negative memory. Critically, resting-state scans flanked the encoding task, allowing us to show for the first time that individual differences in "off-line" increases in amygdala resting-state functional connectivity (RSFC) immediately following encoding relate to negative and positive memory bias at test. Specifically, post-encoding increases in amygdala RSFC with visuosensory and frontal regions were associated with the degree of negative and positive memory bias, respectively. These findings provide new evidence that valence-specific negative memory biases can be linked to the way that sensory processes are integrated into amygdala-centered emotional memory networks. for assistance with participant recruitment and data collection and processing; Ehri Rhyu for helpful discussions of the mediation analysis; and Jaclyn Ford for her thoughtful comments and helpful discussions of this work. Further details of the recapitulation replication results and exploratory moderated mediation analysis can be obtained by contacting the corresponding author directly. This work was included in the dissertation of S.M.K.Decades of research has placed the amygdala at the center of the emotional memory network. Despite the clinical importance of disproportionate memory for negative compared with positive events, it is not known whether post-encoding increases in amygdala-cortical coupling, possibly reflective of early consolidation processes, bear any influence on the degree or direction of such emotional memory biases. We demonstrate that, across participants, increases in post-encoding amygdala coupling with visuosensory and frontal regions are associated with more pronounced negative and positive memory biases, respectively. These findings provide the first evidence linking post-encoding amygdala modulation to the degree of negative or positive memory bias, emphasizing the need for valence-based accounts of the amygdala's role in emotional memory.

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Section: Participantsmentioning

confidence: 99%

Post-Encoding Amygdala-Visuosensory Coupling Is Associated with Negative Memory Bias in Healthy Young Adults

Kark

Kensinger

2019

J. Neurosci.

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“…FD is the most popular metric among motion statistics. It was reported in 24 % of recent fMRI studies compared to similar root mean square (RMS) metric which was reported only in 10 % of recent fMRI studies (Waheed et al, 2016).…”

Section: Framewise Displacement (Fd)mentioning

confidence: 98%

“…It can be influenced by blurring kernel size, frequency filter characteristics, sequence characteristics, etc. DVARS was reported only in 8 % of the recent fMRI studies (Waheed et al, 2016).…”

Section: Derivative Of Root Mean Square Variance Over Voxels (Dvars)mentioning

confidence: 99%

“…Reporting motion statistics should be fundamental for any fMRI study but Waheed et al (2016) analyzed 100 most recent fMRI studies and only 10 % provided a table of motion metrics. Two of the most used motion metrics are framewise displacement (FD) and derivative of root mean square variance over voxels (DVARS).…”

Section: Quantifying Motionmentioning

confidence: 99%

“…The question arises as to which motion metric is optimal. Currently, the most used motion parameters across studies are DVARS and FD (Waheed et al, 2016). As Power et al (2012) pointed out it is difficult to quantify the effect of motion with only one parameter.…”

Section: Limitations and Future Directionsmentioning

confidence: 99%

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Typicality of Functional Connectivity robustly captures motion artifacts in rs-fMRI across datasets, atlases and preprocessing pipelines

Kopál

Pidnebesna

Tomeček

et al. 2020

Preprint

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Functional connectivity analysis of resting state fMRI data has recently become one of the most common approaches to characterizing individual brain function. It has been widely suggested that the functional connectivity matrix, calculated by correlating signals from regions of interest, is a useful approximate representation of the brain's connectivity, potentially providing behaviorally or clinically relevant markers. However, functional connectivity estimates are known to be detrimentally affected by various artifacts, including those due to in-scanner head motion. Treatment of such artifacts poses a standing challenge because of their high variability. Moreover, as individual functional connections generally covary only very weakly with head motion estimates, motion influence is difficult to quantify robustly, and prone to be neglected in practice. Although the use of individual estimates of head motion, or group-level correlation of motion and functional connectivity has been suggested, a sufficiently sensitive measure of individual functional connectivity quality has not yet been established. We propose a new intuitive summary index, the Typicality of Functional Connectivity, to capture deviations from normal brain functional connectivity pattern. Based on results of resting state fMRI for 245 healthy subjects we show that this measure is significantly correlated with individual head motion metrics. The results were further robustly reproduced across atlas granularity and preprocessing options, as well as other datasets including 1081 subjects from the Human Connectome Project. The Typicality of Functional Connectivity provides individual proxy measure of motion effect on functional connectivity and is more sensitive to inter-individual variation of motion than individual functional connections. In principle it should be sensitive also to other types of artifacts, processing errors and possibly also brain pathology, allowing wide use in data quality screening and quantification in functional connectivity studies as well as methodological investigations.

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Reproducibility of graph measures at the subject level using resting‐state fMRI

et al. 2020

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Reporting of Resting-State Functional Magnetic Resonance Imaging Preprocessing Methodologies

Cited by 26 publications

References 33 publications

Post-Encoding Amygdala-Visuosensory Coupling Is Associated with Negative Memory Bias in Healthy Young Adults

Post-Encoding Amygdala-Visuosensory Coupling Is Associated with Negative Memory Bias in Healthy Young Adults

Typicality of Functional Connectivity robustly captures motion artifacts in rs-fMRI across datasets, atlases and preprocessing pipelines

Reproducibility of graph measures at the subject level using resting‐state fMRI

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