Heart rate variability covaries with amygdala functional connectivity during voluntary emotion regulation DOI Creative Commons
Emma Tupitsa,

Ifeoma Egbuniwe,

William Lloyd

et al.

NeuroImage, Journal Year: 2023, Volume and Issue: 274, P. 120136 - 120136

Published: April 26, 2023

The Neurovisceral Integration Model posits that shared neural networks support the effective regulation of emotions and heart rate, with rate variability (HRV) serving as an objective, peripheral index prefrontal inhibitory control. Prior neuroimaging studies have predominantly examined both HRV associated functional connectivity at rest, opposed to contexts require active emotion regulation. present study sought extend upon previous resting-state findings, examining task-related corresponding amygdala during a cognitive reappraisal task. Seventy adults (52 older 18 younger adults, 18-84 years, 51% male) received instructions cognitively reappraise negative affective images MRI scanning. measures were derived from finger pulse signal throughout scan. During task, exhibited significant inverse association between amygdala-medial cortex (mPFC) connectivity, in which higher was correlated weaker amygdala-mPFC coupling, whereas displayed slight positive, albeit non-significant correlation. Furthermore, voxelwise whole-brain analyses showed task-based linked right amygdala-posterior cingulate across positively stronger amygdala-right ventrolateral connectivity. Collectively, these findings highlight importance assessing regulatory further identify concomitants adaptive

Language: Английский

Is it time to put rest to rest? DOI
Emily S. Finn

Trends in Cognitive Sciences, Journal Year: 2021, Volume and Issue: 25(12), P. 1021 - 1032

Published: Oct. 6, 2021

Language: Английский

Citations

189
A guide to the measurement and interpretation of fMRI test-retest reliability DOI Creative Commons
Stephanie Noble, Dustin Scheinost, R. Todd Constable

et al.

Current Opinion in Behavioral Sciences, Journal Year: 2021, Volume and Issue: 40, P. 27 - 32

Published: Jan. 20, 2021

The test-retest reliability of functional neuroimaging data has recently been a topic much discussion. Despite early conflicting reports, converging reports now suggest that is poor for standard univariate measures — namely, voxel-based and region-level task-based activation edge-level connectivity. To better understand the implications these recent studies requires understanding nuances as commonly measured by intraclass correlation coefficient (ICC). Here we provide guide to measurement interpretation in review major findings literature. We highlight importance making choices improve so long they do not diminish validity, pointing potential multivariate approaches both. Finally, discuss low context ongoing work field.

Language: Английский

Citations

143
The Burden of Reliability: How Measurement Noise Limits Brain-Behaviour Predictions DOI Creative Commons
Martin Gell, Simon B. Eickhoff, Amir Omidvarnia

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Feb. 10, 2023

Abstract Major efforts in human neuroimaging strive to understand individual differences and find biomarkers for clinical applications by predicting behavioural phenotypes from brain imaging data. An essential prerequisite identifying generalizable replicable brain-behaviour prediction models is sufficient measurement reliability. However, the selection of targets predominantly guided scientific interest or data availability rather than reliability considerations. Here we demonstrate impact low phenotypic on out-of-sample performance. Using simulated empirical Human Connectome Projects, found that levels common across many can markedly limit ability link behaviour. Next, using 5000 subjects UK Biobank, show only highly reliable fully benefit increasing sample sizes hundreds thousands participants. Overall, our findings highlight importance brain–behaviour associations differences.

Language: Английский

Citations

43
Moving beyond processing- and analysis-related variation in resting-state functional brain imaging DOI
Xinhui Li, Nathália Bianchini Esper, Lei Ai

et al.

Nature Human Behaviour, Journal Year: 2024, Volume and Issue: 8(10), P. 2003 - 2017

Published: Aug. 5, 2024

Language: Английский

Citations

20
Striving toward translation: strategies for reliable fMRI measurement DOI Creative Commons
Maxwell L. Elliott, Annchen R. Knodt, Ahmad R. Hariri

et al.

Trends in Cognitive Sciences, Journal Year: 2021, Volume and Issue: 25(9), P. 776 - 787

Published: June 14, 2021

Language: Английский

Citations

75
Suboptimal phenotypic reliability impedes reproducible human neuroscience DOI Creative Commons
Aki Nikolaidis, Andrew A. Chen,

Xiaoning He

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2022, Volume and Issue: unknown

Published: July 23, 2022

Summary Paragraph Biomarkers of behavior and psychiatric illness for cognitive clinical neuroscience remain out reach 1–4 . Suboptimal reliability biological measurements, such as functional magnetic resonance imaging (fMRI), is increasingly cited a primary culprit discouragingly large sample size requirements poor reproducibility brain-based biomarker discovery 1,5–7 In response, steps are being taken towards optimizing MRI increasing sizes 8–11 , though this will not be enough. Optimizing measurement necessary but insufficient discovery; focus has overlooked the ‘other side equation’ - assessments which often suboptimal or unassessed. Through combination simulation analysis empirical studies using neuroimaging data, we demonstrate that joint both clinical/cognitive phenotypic measurements must optimized in order to ensure biomarkers reproducible accurate. Even with best-case scenario high sizes, show data (i.e., diagnosis, behavioral measurements) continue impede meaningful field. Improving through development novel variation needed, it sole solution. We emphasize potential improve established methods aggregation across multiple raters and/or 12–15 becoming feasible recent innovations acquisition (e.g., web- smart-phone-based administration, ecological momentary assessment, burst sampling, wearable devices, multimodal recordings) 16–20 can achieve better fraction cost engendered by large-scale samples. Although current study been motivated ongoing developments neuroimaging, prioritization reliable phenotyping revolutionize neurobiological endeavors focused on brain behavior.

Language: Английский

Citations

52
Toward a functional future for the cognitive neuroscience of human aging DOI Creative Commons

Zoya Mooraj,

Alireza Salami, Karen L. Campbell

et al.

Neuron, Journal Year: 2025, Volume and Issue: 113(1), P. 154 - 183

Published: Jan. 1, 2025

Language: Английский

Citations

1
Moving Beyond Processing and Analysis-Related Variation in Neuroscience DOI Creative Commons
Xinhui Li, Nathália Bianchini Esper, Lei Ai

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2021, Volume and Issue: unknown

Published: Dec. 3, 2021

Abstract When fields lack consensus standard methods and accessible ground truths, reproducibility can be more of an ideal than a reality. Such has been the case for functional neuroimaging, where there exists sprawling space tools processing pipelines. We provide critical evaluation impact differences across five independently developed minimal preprocessing pipelines MRI. show that even when handling identical data, inter-pipeline agreement was only moderate, critically shedding light on factor limits cross-study reproducibility. low mainly becomes appreciable reliability underlying data is high, which increasingly as field progresses. Crucially, we compromised, so too are consistency insights from brainwide association studies. highlight importance comparing analytic configurations, both widely discussed commonly overlooked decisions lead to marked variation.

Language: Английский

Citations

50
ReX: an integrative tool for quantifying and optimizing measurement reliability for the study of individual differences DOI
Ting Xu, Gregory Kiar, Jae Wook Cho

et al.

Nature Methods, Journal Year: 2023, Volume and Issue: 20(7), P. 1025 - 1028

Published: June 1, 2023

Language: Английский

Citations

22
Less is more: balancing noise reduction and data retention in fMRI with data-driven scrubbing DOI Creative Commons
Damon Pham, Daniel J. McDonald, Lei Ding

et al.

NeuroImage, Journal Year: 2023, Volume and Issue: 270, P. 119972 - 119972

Published: Feb. 25, 2023

Artifacts in functional MRI (fMRI) data cause deviations from common distributional assumptions, introduce spatial and temporal outliers, reduce the signal-to-noise ratio of -- all which can have negative consequences for downstream statistical analysis. Scrubbing is a technique excluding fMRI volumes thought to be contaminated by artifacts generally comes two flavors. Motion scrubbing based on subject head motion-derived measures popular but suffers number drawbacks, especially high rates censoring individual entire subjects. Alternatively, data-driven methods like DVARS are observed noise processed timeseries may avoid some these issues. Here we propose "projection scrubbing", novel method outlier detection framework strategic dimension reduction, including independent component analysis (ICA), isolate artifactual variation. We undertake comprehensive comparison motion with projection DVARS. argue that an appropriate metric success maximal retention reasonable performance typical benchmarks connectivity. find stringent yields worsened validity, reliability, produced small improvements fingerprinting. Meanwhile, tend yield greater fingerprinting while not worsening validity or reliability. Importantly, however, excludes fraction sessions compared scrubbing. The ability improve without negatively impacting quality has major implications sample sizes population neuroscience research.

Language: Английский

Citations

17