eNeuro Promotes Scientific Rigor With Commentary Series
The 黑料社’s open-access journal, eNeuro, recently published a series of commentaries on the issue of scientific rigor, with articles focusing on best practices to enhance research methodologies. The series is the latest in a set of SfN activities to maintain and enhance scientific rigor as part of the field’s collective responsibility to the integrity of the scientific mission.
In an , eNeuro Editor-in-Chief Christophe Bernard introduces the series, which includes commentaries from two experts:
- by Oswald Steward of University of California, Irvine
- by Katherine S. Button of the University of Bath
Bernard also describes the importance of conducting rigorous science by consistently applying the highest standards in research methodologies, including experimental design, statistical analysis and reporting, and scientific communication. “One of the missions of eNeuro is to provide the scientific community with teaching and training elements” related to publishing, he writes, noting recent webinars and online chats about peer review.
“Steadfast in its commitment to scientific rigor, SfN has responded to recent concerns voiced in both the scientific community and the media about the reproducibility of scientific research,” SfN President Hollis Cline said. “SfN is providing the community with new resources that reinforce the importance of scientific rigor, including ongoing training programs and annual meeting events that complement the commentaries in eNeuro.”
In 2015, SfN released to provide a foundational guideline for both trainees and experienced researchers to reference and use as the basis for conversation, training, and practice.
The Society has also partnered with NIH and leading neuroscientists who are experts in the field of scientific rigor to create an ongoing series of intensive training modules open to the entire field. The project, , is funded by a two-year grant from the National Institute on Drug Abuse as a part of NIH’s Training Modules to Enhance Data Reproducibility. These resources are available to all on , SfN’s online home for training, learning, and discussion.
