Identifying Objective EEG Based Markers of Linear Vection in Depth.
Identifying Objective EEG Based Markers of Linear Vection in Depth.
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DOI：
10.3389/fpsyg.2016.01205
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发表时间：
2016
影响因子：
3.8
通讯作者：
Fogarty JS
中科院分区：
文献类型：
--
作者：
Palmisano S;Barry RJ;De Blasio FM;Fogarty JS
该概念验证研究调查了时间-频率EEG方法是否可用于检查向量（即，自我运动的错觉）。在主要实验中，我们比较了10名观察者在重复暴露于两种不同类型的光流显示（每种显示宽35°，高29°，提供20 s的运动刺激）期间和之后的事件相关光谱扰动（ERSP）数据。显示器由矢量显示器（其模拟在深度上的恒定速度向前自运动）或控制显示器（矢量显示器的空间扰乱版本）组成。采用时频主成分分析（t-fPCA）对ERSP数据进行分解。我们发现10 Hz α活动增加，在显示器运动开始后约14秒达到峰值，这与更强的矢量评级呈正相关。这是继β活动减少，也是继δ活动减少;这些减少脑电图振幅呈负相关的强度的vection的经验。显示运动停止后，α波段的一系列增加也与vection强度相关，似乎反映了vection和/或运动后效应，以及后来的认知准备报告的vection经验的强度。总的来说，这些发现为EEG可用于提供两种向量状态（即，“转染/无转染”）和转染强度。
This proof-of-concept study investigated whether a time-frequency EEG approach could be used to examine vection (i.e., illusions of self-motion). In the main experiment, we compared the event-related spectral perturbation (ERSP) data of 10 observers during and directly after repeated exposures to two different types of optic flow display (each was 35° wide by 29° high and provided 20 s of motion stimulation). Displays consisted of either a vection display (which simulated constant velocity forward self-motion in depth) or a control display (a spatially scrambled version of the vection display). ERSP data were decomposed using time-frequency Principal Components Analysis (t–f PCA). We found an increase in 10 Hz alpha activity, peaking some 14 s after display motion commenced, which was positively associated with stronger vection ratings. This followed decreases in beta activity, and was also followed by a decrease in delta activity; these decreases in EEG amplitudes were negatively related to the intensity of the vection experience. After display motion ceased, a series of increases in the alpha band also correlated with vection intensity, and appear to reflect vection- and/or motion-aftereffects, as well as later cognitive preparation for reporting the strength of the vection experience. Overall, these findings provide support for the notion that EEG can be used to provide objective markers of changes in both vection status (i.e., “vection/no vection”) and vection strength.