Abstract
There is an ongoing debate about the replicability of neuroimaging research. It was suggested that one of the main reasons for the high rate of false positive results is the many degrees of freedom researchers have during data analysis. In the Neuroimaging Analysis Replication and Prediction Study (NARPS), we aim to provide the first scientific evidence on the variability of results across analysis teams in neuroscience. We collected fMRI data from 108 participants during two versions of the mixed gambles task, which is often used to study decision-making under risk. For each participant, the dataset includes an anatomical (T1 weighted) scan and fMRI as well as behavioral data from four runs of the task. The dataset is shared through OpenNeuro and is formatted according to the Brain Imaging Data Structure (BIDS) standard. Data pre-processed with fMRIprep and quality control reports are also publicly shared. This dataset can be used to study decision-making under risk and to test replicability and interpretability of previous results in the field.
Highlights
Background & SummaryThe recent “replication crisis” in many scientific fields has raised broad concern regarding the reliability of published results[1,2,3]
One main reason for the high rate of false positive results is the large number of “researcher degrees of freedom”, wherein the process of data analysis can be modified towards desired results based on data itself[4,5,6]
In the Neuroimaging Analysis Replication and Prediction Study (NARPS; https://www.narps.info/), we collected fMRI data in order to estimate the variability of neuroimaging results across analysis teams, and measure peer beliefs about the results by running prediction markets[3,9]
Summary
The recent “replication crisis” in many scientific fields has raised broad concern regarding the reliability of published results[1,2,3]. Tom et al.[18] studied the neural basis of loss aversion with the mixed gambles task They found that fMRI activity in many regions (including dopaminergic midbrain regions and their targets) increased as potential gains increased, while activity in most of these regions decreased as potential losses increased. Canessa et al.[20] aimed to resolve the inconsistent previous results by focusing on individual differences in loss aversion They found both bidirectional as well as gain/loss-specific fMRI activity during choices. Anatomical and fMRI data from 108 healthy participants, each performing one version of the mixed gambles task (equal range/equal indifference) This dataset was collected in order to test replicability and resolve inconsistencies of previous results. The two conditions used provide a unique opportunity to compare the interactions between the specific gains/losses matrix used and the elicited behavior and neural fMRI activity
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
