Suppr超能文献

利用脑磁图检测视听整合过程中的功能连接:连接性指标比较

Detecting Functional Connectivity During Audiovisual Integration with MEG: A Comparison of Connectivity Metrics.

作者信息

Ard Tyler, Carver Frederick W, Holroyd Tom, Horwitz Barry, Coppola Richard

机构信息

1 Magnetoencephalography Core Facility, National Institute of Mental Health (NIMH) , National Institutes of Health, Bethesda, Maryland.

2 Neuroscience Graduate Program, Brown University , Providence, Rhode Island.

出版信息

Brain Connect. 2015 Aug;5(6):336-48. doi: 10.1089/brain.2014.0296. Epub 2015 Feb 26.

Abstract

In typical magnetoencephalography and/or electroencephalography functional connectivity analysis, researchers select one of several methods that measure a relationship between regions to determine connectivity, such as coherence, power correlations, and others. However, it is largely unknown if some are more suited than others for various types of investigations. In this study, the authors investigate seven connectivity metrics to evaluate which, if any, are sensitive to audiovisual integration by contrasting connectivity when tracking an audiovisual object versus connectivity when tracking a visual object uncorrelated with the auditory stimulus. The authors are able to assess the metrics' performances at detecting audiovisual integration by investigating connectivity between auditory and visual areas. Critically, the authors perform their investigation on a whole-cortex all-to-all mapping, avoiding confounds introduced in seed selection. The authors find that amplitude-based connectivity measures in the beta band detect strong connections between visual and auditory areas during audiovisual integration, specifically between V4/V5 and auditory cortices in the right hemisphere. Conversely, phase-based connectivity measures in the beta band as well as phase and power measures in alpha, gamma, and theta do not show connectivity between audiovisual areas. The authors postulate that while beta power correlations detect audiovisual integration in the current experimental context, it may not always be the best measure to detect connectivity. Instead, it is likely that the brain utilizes a variety of mechanisms in neuronal communication that may produce differential types of temporal relationships.

摘要

在典型的脑磁图和/或脑电图功能连接性分析中,研究人员会从几种测量区域之间关系以确定连接性的方法中选择一种,比如相干性、功率相关性等。然而,对于各种类型的研究而言,某些方法是否比其他方法更适用,在很大程度上尚不清楚。在本研究中,作者调查了七种连接性指标,通过对比跟踪视听对象时的连接性与跟踪与听觉刺激不相关的视觉对象时的连接性,来评估哪些指标(如果有的话)对视听整合敏感。作者能够通过研究听觉和视觉区域之间的连接性来评估这些指标在检测视听整合方面的表现。至关重要的是,作者在全脑所有区域之间的映射上进行研究,避免了种子选择中引入的混淆因素。作者发现,在视听整合过程中,β波段基于振幅的连接性测量方法能检测到视觉和听觉区域之间的强连接,特别是在右半球的V4/V5和听觉皮层之间。相反,β波段基于相位的连接性测量方法以及α、γ和θ波段的相位和功率测量方法均未显示出视听区域之间的连接性。作者推测,虽然β功率相关性在当前实验环境中能检测到视听整合,但它可能并不总是检测连接性的最佳方法。相反,大脑很可能在神经元通信中利用了多种机制,这些机制可能会产生不同类型的时间关系。

相似文献

9
Decreased BOLD responses in audiovisual processing.视听处理中血氧水平依赖(BOLD)反应降低。
Neuroreport. 2010 Dec 29;21(18):1146-51. doi: 10.1097/WNR.0b013e328340cc47.

本文引用的文献

1
Good practice for conducting and reporting MEG research.脑磁图(MEG)研究的良好实践。
Neuroimage. 2013 Jan 15;65:349-63. doi: 10.1016/j.neuroimage.2012.10.001. Epub 2012 Oct 6.
8
Network-based statistic: identifying differences in brain networks.基于网络的统计方法:识别脑网络的差异。
Neuroimage. 2010 Dec;53(4):1197-207. doi: 10.1016/j.neuroimage.2010.06.041. Epub 2010 Jun 25.
9

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验