Work

Introduction to the special issue on reproducibility in neuroimaging

Year: 2019

Type: editorial

Abstract: The last decade has seen increasing attention to the problem of scientific reproducibility, across a broad range of scientific fields (Camerer et al., 2016;Morrison, 2014;Open Science Collaboration, 2015). Within the field of neuroimaging, there has been a particular focus on issues of analytic variability (Bowring et al., 2019;Carp, 2012) statistical power (Button et al., 2013;Poldrack et al., 2017), and test-retest reliability (Bennett and Miller, 2013), all of which have raised alarms regarding the potential for irreproducible results. In addition, failed replications (Boekel et al., 2015;Dinga et al., 2019) and meta-analytic null results (Müller et al., 2017) have raised particular concern about studies of group and individual differences. This special issue was developed in light of these emerging concerns, with the goal of highlighting and encouraging work that aims to both quantify and improve the reproducibility of neuroimaging research. Here we provide a brief overview of the papers within this special issue.

Source: NeuroImage

DOI: 10.1016/j.neuroimage.2019.116357

Authors: Russell A. Poldrack, Kirstie Whitaker, David Kennedy

Institutions: Stanford University, University of Cambridge, The Alan Turing Institute, University of Massachusetts Chan Medical School, Eunice Kennedy Shriver Center

Language: English

Topic: Functional Brain Connectivity Studies

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $3,250

OpenAlex ID: W2986270241

Cites: 13

Cited by: 15

Related to: 10