When functional magnetic resonance imaging (fMRI) was introduced in the late 1990s, it drew raves for its ability to show brain activity—and concerns that it might be the modern equivalent of phrenology. Now, that debate could spring to life again with revelations that the popular imaging technology could have been flawed for years. As Kate Lunau writes for Motherboard, new research suggests that software used to analyze fMRI results could invalidate up to 40,000 brain activity studies.
Data from RNA-seq experiments provide us with many new possibilities to gain insights into biological and disease mechanisms of cellular functioning. However, the reproducibility and robustness of RNA-seq data analysis results is often unclear. This is in part attributed to the two counter acting goals of (a) a cost efficient and (b) an optimal experimental design leading to a compromise, e.g., in the sequencing depth of experiments.
Reproducibility of data from experimental investigations using animal models is increasingly under scrutiny because of the potentially negative impact of poor reproducibility on the translation of basic research. Histopathology is a key tool in biomedical research, in particular for the phenotyping of animal models to provide insights into the pathobiology of diseases. Failure to disclose and share crucial histopathological experimental details compromises the validity of the review process and reliability of the conclusions. We discuss factors that affect the interpretation and validation of histopathology data in publications and the importance of making these data accessible to promote replicability in research.
We want to enable our authors to publish the best research and maximize the benefit of research funding, which includes achieving good practice in the sharing and archiving of research data. We also aim to facilitate authors’ compliance with institution and research funder requirements to share data. Encourage publication of more open and reproducible research.
A whole pile of "this is how your brain looks like" MRI-based science has been invalidated because someone finally got around to checking the data. The problem is simple: to get from a high-resolution magnetic resonance imaging scan of the brain to a scientific conclusion, the brain is divided into tiny "voxels." Software, rather than humans, then scans the voxels looking for clusters. In this paper at PNAS, they write: "the most common software packages for fMRI analysis (SPM, FSL, AFNI) can result in false-positive rates of up to 70%. These results question the validity of some 40,000 fMRI studies and may have a large impact on the interpretation of neuroimaging results."
To evaluate the reproducibility of indices of lung microstructure and function derived from 129 Xe chemical shift saturation recovery (CSSR) spectroscopy in healthy volunteers and patients with chronic obstructive pulmonary disease (COPD), and to study the sensitivity of CSSR-derived parameters to pulse sequence design and lung inflation level.