Functional MRI Can Be Highly Reliable, but It Depends on What You Measure: A Commentary on Elliott et al. (2020)

Kragel, Philip A.; Han, Xiaochun; Kraynak, Thomas E.; Gianaros, Peter J.; Wager, Tor D.

doi:10.1177/0956797621989730

Cited by 88 publications

(44 citation statements)

References 31 publications

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“…While the current review found generally consistent findings concerning the amygdala, this warrants attention for future task-based fMRI investigations, as the issue of reliability becomes exacerbated by small sample sizes [88]. Possible approaches to circumvent this issue include ensuring external factors that affect BOLD signals are accounted for as much as possible as well as analyzing multivariate activity patterns in addition to traditional regional activity changes [89].…”

Section: Factors Contributing To the Mixed Findings In Task-based Fmri Studies Of Gadmentioning

confidence: 58%

Altered Task-Evoked Corticolimbic Responsivity in Generalized Anxiety Disorder

Kim

2021

IJMS

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Generalized anxiety disorder (GAD) is marked by uncontrollable, persistent worry and exaggerated response to uncertainty. Here, we review and summarize the findings from the GAD literature that employs functional neuroimaging methods. In particular, the present review focuses on task-based blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) studies. We find that select brain regions often regarded as a part of a corticolimbic circuit (e.g., amygdala, anterior cingulate cortex, prefrontal cortex) are consistently targeted for a priori hypothesis-driven analyses, which, in turn, shows varying degrees of abnormal BOLD responsivity in GAD. Data-driven whole-brain analyses show the insula and the hippocampus, among other regions, to be affected by GAD, depending on the task used in each individual study. Overall, while the heterogeneity of the tasks and sample size limits the generalizability of the findings thus far, some promising convergence can be observed in the form of the altered BOLD responsivity of the corticolimbic circuitry in GAD.

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Section: Factors Contributing To the Mixed Findings In Task-based Fmri Studies Of Gadmentioning

confidence: 58%

Altered Task-Evoked Corticolimbic Responsivity in Generalized Anxiety Disorder

Kim

2021

IJMS

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“…Similarly, reports show that reproducibility is poor for many task-based fMRI experiments ( Elliott et al, 2020 ). However, this may reflect limitations in the kind of experiments tested, as some studies show higher reproducibility than others ( Kragel et al, 2021 ), and differences in analysis, as surface-based cognitive neuroscience studies of cerebral cortex (such as the current study) perform well with regards to reproducibility ( Assem et al, 2021 ).…”

Section: Discussionmentioning

confidence: 79%

Cross-dataset reproducibility of human retinotopic maps

et al. 2021

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Population receptive field (pRF) models fit to fMRI data are used to non-invasively measure retinotopic maps in human visual cortex, and these maps are a fundamental component of visual neuroscience experiments. Here, we examined the reproducibility of retinotopic maps across two datasets: a newly acquired retinotopy dataset from New York University (NYU) ( n = 44) and a public dataset from the Human Connectome Project (HCP) ( n = 181). Our goal was to assess the degree to which pRF properties are similar across datasets, despite substantial differences in their experimental protocols. The two datasets simultaneously differ in their stimulus apertures, participant pool, fMRI protocol, MRI field strength, and preprocessing pipeline. We assessed the cross-dataset reproducibility of the two datasets in terms of the similarity of vertex-wise pRF estimates and in terms of large-scale polar angle asymmetries in cortical magnification. Within V1, V2, V3, and hV4, the group-median NYU and HCP vertex-wise polar angle estimates were nearly identical. Both eccentricity and pRF size estimates were also strongly correlated between the two datasets, but with a slope different from 1; the eccentricity and pRF size estimates were systematically greater in the NYU data. Next, to compare large-scale map properties, we quantified two polar angle asymmetries in V1 cortical magnification previously identified in the HCP data. The NYU dataset confirms earlier reports that more cortical surface area represents horizontal than vertical visual field meridian, and lower than upper vertical visual field meridian. Together, our findings show that the retinotopic properties of V1, V2, V3, and hV4 can be reliably measured across two datasets, despite numerous differences in their experimental design. fMRI-derived retinotopic maps are reproducible because they rely on an explicit computational model of the fMRI response. In the case of pRF mapping, the model is grounded in physiological evidence of how visual receptive fields are organized, allowing one to quantitatively characterize the BOLD signal in terms of stimulus properties (i.e., location and size). The new NYU Retinotopy Dataset will serve as a useful benchmark for testing hypotheses about the organization of visual areas and for comparison to the HCP 7T Retinotopy Dataset.

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“…Recent publications suggest that the reliability of task‐fMRI paradigms may be inadequate, resulting in an inaccurate estimation of task‐evoked brain activations (Elliott et al, 2020 ; Zuo, Xu, & Milham, 2019 ). The method described here could be used to train prediction models on task‐fMRI data that was collected following rigorous reliability standards (Elliott, Knodt, Caspi, Moffitt, & Hariri, 2021 ; Kragel, Han, Kraynak, Gianaros, & Wager, 2021 ; Zuo et al, 2019 ), and then utilize these models to predict task‐evoked brain activity in other datasets. Therefore, we may provide the opportunity to produce reliable predictions of task‐evoked brain activity at the level of the single participant, without any task actually being performed.…”

Section: Discussionmentioning

confidence: 99%

Predicting individual variability in task‐evoked brain activity in schizophrenia

Tik

Livny

Gal

et al. 2021

Human Brain Mapping

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What goes wrong in a schizophrenia patient's brain that makes it so different from a healthy brain? In this study, we tested the hypothesis that the abnormal brain activity in schizophrenia is tightly related to alterations in brain connectivity. Using functional magnetic resonance imaging (fMRI), we demonstrated that both resting-state functional connectivity and brain activity during the well-validated N-back task differed significantly between schizophrenia patients and healthy controls. Nevertheless, using a machine-learning approach we were able to use resting-state functional connectivity measures extracted from healthy controls to accurately predict individual variability in the task-evoked brain activation in the schizophrenia patients. The predictions were highly accurate, sensitive, and specific, offering novel insights regarding the strong coupling between brain connectivity and activity in schizophrenia. On a practical perspective, these findings may allow to generate task activity maps for clinical populations without the need to actually perform any tasks, thereby reducing patients inconvenience while saving time and money.

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Functional MRI Can Be Highly Reliable, but It Depends on What You Measure: A Commentary on Elliott et al. (2020)

Cited by 88 publications

References 31 publications

Altered Task-Evoked Corticolimbic Responsivity in Generalized Anxiety Disorder

Altered Task-Evoked Corticolimbic Responsivity in Generalized Anxiety Disorder

Cross-dataset reproducibility of human retinotopic maps

Predicting individual variability in task‐evoked brain activity in schizophrenia

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