The secret lives of experiments: Methods reporting in the fMRI literature

By Joshua Carp. NeuroImage, 2012

465 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/57dc9829ca370aacc52f2c858eb132134cbb4832

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Citations in the corpus

Cross‐validation failure: Small sample sizes lead to large error bars (2017, background): “However, the success of meta-analysis in fMRI suggests that pooling data can be beneficial, whether it is by assembling a small number of well-matched studies or over a wider coverage of the literature (Laird et al., 2005; Costafreda, 2009).”
The impact of traditional neuroimaging methods on the spatial localization of cortical areas (2018, methodology): “The most common smoothing level in the literature is 8-mm FWHM, the default value in SPM, the most commonly used neuroimaging software package (17).”
Behavior, Sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation (2016, unknown): “Furthermore, the substantial analytic flexibility of neuroimaging pipelines also leads to low reliability and reproducibility of neuroimaging findings (Carp, 2012b; Glatard et al., 2015; Wager et al., 2009).”
The Nuisance of Nuisance Regression: Spectral Misspecification in a Common Approach to Resting-State fMRI Preprocessing Reintroduces Noise and Obscures Functional Connectivity (2013, background): “Moreoever, in many articles, the sequence and details of RS-fcMRI preprocessing, particularly bandpass filtering and nuisance regression, were unclear (cf. Carp, 2012).”
Deriving reproducible biomarkers from multi‐site resting‐state data: An Autism‐based example (2016, background): “Given that processing pipelines differ greatly between studies (Carp, 2012), comparing data-analysis methods is challenging.”
On the Plurality of (Methodological) Worlds: Estimating the Analytic Flexibility of fMRI Experiments (2012, methodology): “A recent survey of methods used in the fMRI literature shows that research strategies are highly flexible across published studies, with nearly as many unique methodological pipelines as studies in the sample (Carp, 2012).”
Best Practices in Data Analysis and Sharing in Neuroimaging using MRI (2016, background): “While the dangers of multiple testing are generally well understood, one review found only 59& of studies used a correction for multiple testing [Carp2012], While there are domains where stringent corrections are not suitable (e.g. presurgical fMRI, where false positive risk has to be balanced…”
Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis (2021, background): “Strikingly, no two individual analysts employed precisely the same specification for either Hypothesis 1 or 2 (see Botvinik-Nezer et al., 2020, and Carp, 2012a; 2012b, for similar findings in neuroimaging studies and Bastiaansen et al., 2020, for a conceptual replication with event sampling data…”
ITK: enabling reproducible research and open science (2014, unknown): “Data and documentation are also required (Carp, 2012; Vines et al., 2013; Glasziou et al., 2014).”
50 Years of Data Science (2017, unknown): “Carp (2012) studied analysis workflows in 241 fMRI studies.”