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rt-me-fMRI: A task and resting state dataset for real-time, multi-echo fMRI methods development and validation
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rt-me-fMRI: A task and resting state dataset for real-time, multi-echo fMRI methods development and validation
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Paper
rt-me-fMRI: A task and resting state dataset for real-time, multi-echo fMRI methods development and validation
2020
Overview
Abstract 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. Competing Interest Statement RL, WH, and MB are, respectively, employees of Philips Research and Philips Healthcare in The Netherlands. The other authors have declared that no further competing interests exist Footnotes * https://dataverse.nl/dataverse/rt-me-fmri * https://rt-me-fmri.herokuapp.com * https://github.com/jsheunis/rt-me-fMRI
Publisher
Cold Spring Harbor Laboratory Press,Cold Spring Harbor Laboratory
