Retrieving fMRI data in real-time: difficulties and pitfalls

Author:

Lührs MichaelORCID,Poser Benedikt AORCID,Auer TiborORCID,Goebel RainerORCID

Abstract

ABSTRACTOne of the significant challenges in real-time fMRI environments is to ensure that the functional images are exported in real-time. The prerequired ability to reconstruct these images immediately after the acquisition has already been resolved in 2004. Nowadays, more sophisticated sequences allow for higher resolution and faster repetition times and thereby challenging the ability to export this data in real-time. In this article, we tackle the potentially arising problem of sending the reconstructed data from the MRI to an external PC to perform the real-time fMRI analysis. We show that depending on the implementation of the data transfer, long delays can occur that can differ drastically in time and how often they occur. In addition, we propose a solution for SIEMENS MRI devices which was tested and applied already on multiple MRI devices including 3T and 7T machines on different vendor software versions. This new technique can be used as a blueprint that can be directly applied to other manufacturers. We also provide the source code of the described solution and show that the delay in the data transfer can be significantly reduced to a tolerable level using our proposed procedure. Finally, we integrate measurement options for the data transfer times to improve quality measures in real-time fMRI environments (e.g., clinical) that can implement the proposed solution. Efforts should be taken by the real-time community and MRI manufacturers to employ a standardized real-time export e.g., similar to the lab streaming layer which is used as a standard export method in EEG environments.

Publisher

Cold Spring Harbor Laboratory

Reference20 articles.

1. Semantic fMRI neurofeedback: a multi-subject study at 3 tesla;Journal of Neural Engineering,2022

2. Biofeedback of Real-Time Functional Magnetic Resonance Imaging Data from the Supplementary Motor Area Reduces Functional Connectivity to Subcortical Regions;Brain Connectivity,2011

3. Intermittent compared to continuous real-time fMRI neurofeedback boosts control over amygdala activation;NeuroImage,2018

4. Heunis, S. , Hellrung, L. , Van der Meer, J. , Bergert, S. , Sladky, R. , Pamplona, G. S. P. , & Skouras, S. (2019). rtQC: an open-source toolbox for real-time fMRI quality control. Annu. Meet. Organ. Hum. Brain Mapp, 10. https://doi.org/10.5281/ZENODO.3239084

5. Quality and denoising in real-time functional magnetic resonance imaging neurofeedback: A methods review;Human Brain Mapping,2020

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3