Sources of information waste in neuroimaging: mishandling structures, thinking dichotomously, and over-reducing data
Neuroimaging relies on separate statistical inferences at tens of thousands of spatial
locations. Such massively univariate analysis typically requires an adjustment for multiple …
locations. Such massively univariate analysis typically requires an adjustment for multiple …
[HTML][HTML] Fighting or embracing multiplicity in neuroimaging? neighborhood leverage versus global calibration
Neuroimaging faces the daunting challenge of multiple testing–an instance of multiplicity–
that is associated with two other issues to some extent: low inference efficiency and poor …
that is associated with two other issues to some extent: low inference efficiency and poor …
Removal of scanner effects in covariance improves multivariate pattern analysis in neuroimaging data
To acquire larger samples for answering complex questions in neuroscience, researchers
have increasingly turned to multi-site neuroimaging studies. However, these studies are …
have increasingly turned to multi-site neuroimaging studies. However, these studies are …
Highlight Results, Don't Hide Them: enhance interpretation, reduce biases and improve reproducibility
Most neuroimaging studies display results that represent only a tiny fraction of the collected
data. While it is conventional to present" only the significant results" to the reader, here we …
data. While it is conventional to present" only the significant results" to the reader, here we …
Mitigating site effects in covariance for machine learning in neuroimaging data
To acquire larger samples for answering complex questions in neuroscience, researchers
have increasingly turned to multi‐site neuroimaging studies. However, these studies are …
have increasingly turned to multi‐site neuroimaging studies. However, these studies are …
Analytical transparency and reproducibility in human neuroimaging studies
M Picciotto - Journal of Neuroscience, 2018 - Soc Neuroscience
The Journal of Neuroscience is committed to editorial transparency and scientific
excellence. Consistent with these goals, this editorial is the first of a series aimed at …
excellence. Consistent with these goals, this editorial is the first of a series aimed at …
Site effects how-to and when: An overview of retrospective techniques to accommodate site effects in multi-site neuroimaging analyses
Site differences, or systematic differences in feature distributions across multiple data-
acquisition sites, are a known source of heterogeneity that may adversely affect large-scale …
acquisition sites, are a known source of heterogeneity that may adversely affect large-scale …
Handling multiplicity in neuroimaging through Bayesian lenses with multilevel modeling
Here we address the current issues of inefficiency and over-penalization in the massively
univariate approach followed by the correction for multiple testing, and propose a more …
univariate approach followed by the correction for multiple testing, and propose a more …
Overfitting the literature to one set of stimuli and data
T Grootswagers, AK Robinson - Frontiers in human neuroscience, 2021 - frontiersin.org
A large number of papers in Computational Cognitive Neuroscience are developing and
testing novel analysis methods using one specific neuroimaging dataset and problematic …
testing novel analysis methods using one specific neuroimaging dataset and problematic …
Moving beyond processing and analysis-related variation in neuroscience
When fields lack consensus standards and ground truths for their analytic methods,
reproducibility can be more of an ideal than a reality. Such has been the case for functional …
reproducibility can be more of an ideal than a reality. Such has been the case for functional …