Respiration recording for fMRI: breathing belt versus spine coil sensor

Author:

Wilding Marilena12,Ischebeck Anja12,Zaretskaya Natalia12

Affiliation:

1. Department of Psychology, University of Graz, Graz, Austria

2. BioTechMed-Graz, Graz, Austria

Abstract

Abstract Physiological signals such as pulse and respiration strongly contribute to non-neuronal signal change of the blood oxygenation level-dependent (BOLD) contrast in functional magnetic resonance imaging (fMRI). This has been observed not only during task-based but also during resting-state fMRI measurements, where the confounding influence of physiological signals is most pronounced. Over the last decades, a variety of techniques evolved, aiming at detecting and removing physiological artifacts in fMRI time series. These follow either a solely data-driven approach or rely on externally recorded physiological data. To record cardiac and respiratory signals, typically pulse oximetry or electrocardiography (ECG) and a respiration belt are used, respectively. New technologies allow to capture respiratory signal directly with a sensor placed within the spine coil in the patient table, eliminating the need of a respiration belt, which considerably increases participants’ comfort. However, little is known about the effectiveness of these new technologies and how they compare to the standard respiration belt recording. In the current study, we compared the two devices, respiration belt and spine coil sensor, in their suitability for physiological noise removal during a visual perception task and during rest. We did not find any differences in resting-state functional connectivity (RSFC), stimulus-related activity, or residual noise between data corrected with the two recording devices. Our results show that spine coil-derived respiration recordings are as good as belt respiration recordings for physiological noise removal in task-induced activity, with spine coil recordings having an additional advantage in terms of participants’ comfort and artifact susceptibility.

Publisher

MIT Press

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