rt-me-fMRI: a task and resting state dataset for real-time, multi-echo fMRI methods development and validation
Fecha
2021Autor
Heunis, Stephan
Breeuwer, Marcel
Caballero-Gaudes, César
Hellrung, Lydia
Huijbers, Willem
Jansen, Jacobus F.A.
Lamerichs, Rolf
Zinger, Svitlana
Aldenkamp, Albert P.
Metadatos
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Heunis S, Breeuwer M, Caballero-Gaudes C et al. rt-me-fMRI: a task and resting state dataset for real-time, multi-echo fMRI methods development and validation [version 1; peer review: 1 approved, 1 approved with reservations]. F1000Research 2021, 10:70 (https://doi.org/10.12688/f1000research.29988.1)
Resumen
A multi-echo fMRI dataset (N=28 healthy participants) with four task-based and two resting state runs was collected, curated and made available to the community. Its main purpose is to advance the development of methods for real-time multi-echo functional magnetic resonance imaging (rt-me-fMRI) analysis with applications in neurofeedback, real-time quality control, and adaptive paradigms, although the variety of experimental task paradigms supports a multitude of use cases. Tasks include finger tapping, emotional face and shape matching, imagined finger tapping and imagined emotion processing. This work provides a detailed description of the full dataset; methods to collect, prepare, standardize and preprocess it; quality control measures; and data validation measures. A web-based application is provided as a supplementary tool with which to interactively explore, visualize and understand the data and its derivative measures: https://rt-me-fmri.herokuapp.com/. The dataset itself can be accessed via a data use agreement on DataverseNL at https://dataverse.nl/dataverse/rt-me-fmri. Supporting information and code for reproducibility can be accessed at https://github.com/jsheunis/rt-me-fMRI