首页> 外文会议>Proceedings of 2011 3rd International Conference on Awareness Science and Technology >Uncovering perceptual awareness of visual stimulus with adaptive multiscale entropy
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Uncovering perceptual awareness of visual stimulus with adaptive multiscale entropy

机译:通过自适应多尺度熵发现视觉刺激的知觉意识

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To probe the perceptual awareness of a visual stimulus, we use the paradigm of generalized flash suppression (GFS) to dissociate physical stimulation from perceptual experience. This perceptual suppression approach has previously been used to investigate perceptual visibility correlates in visual cortex, mainly with linear methods, such as spectral analysis. While meaningful, the linear method alone may be insufficient for the full assessment of neural dynamics due to the fundamentally nonlinear nature of neural signal. In this contribution, we set forth to analyze local field potential (LFP) data collected from the multiple visual areas in V1, V2 and V4 of a macaque monkey while performing the GFS task using nonlinear method - adaptive multiscale entropy (AME) - to study the neural dynamics of perceptual suppression. We also propose a new cross-entropy measure at multiple scales, namely adaptive multiscale cross-entropy (AMCE), to assess the nonlinear interdependency between cortical areas. We show that: (1) multiscale entropy exhibits perception-related changes in all three areas, with higher entropy (i.e. higher complexity) observed during perceptual suppression; (2) the magnitude of the perception-related entropy changes increases systematically over successive hierarchical stages (i.e. from lower areas V1 to V2, up to higher area V4); and (3) cross-entropy between any two cortical areas reveals higher degree of asynchrony or dissimilarity during perceptual suppression, indicating decreased neuronal interdependency between areas. Our findings demonstrate that the adaptive multiscale entropy is a sensitive measure of perceptual visibility, and thus can be used to uncover perceptual awareness of a stimulus.
机译:为了探究视觉刺激的感知意识,我们使用广义闪光抑制(GFS)范例将物理刺激与感知经验分离。这种知觉抑制方法先前已用于研究视觉皮层中的知觉可见性相关性,主要是通过线性方法(例如光谱分析)进行的。尽管有意义,但由于神经信号的根本非线性特性,仅线性方法可能不足以全面评估神经动力学。在这项贡献中,我们着手分析从猕猴V1,V2和V4的多个视觉区域收集的局部场电势(LFP)数据,同时使用非线性方法-自适应多尺度熵(AME)-执行GFS任务,以进行研究知觉抑制的神经动力学。我们还提出了一种新的多尺度交叉熵度量,即自适应多尺度交叉熵(AMCE),以评估皮质区域之间的非线性相互依赖性。我们证明:(1)多尺度熵在所有三个区域均表现出与感知有关的变化,在知觉抑制过程中观察到较高的熵(即较高的复杂性); (2)与感知有关的熵变化的幅度在连续的分级阶段(即从较低的区域V1到V2,直到较高的区域V4)有系统地增加; (3)在认知抑制期间,任意两个皮质区域之间的交叉熵显示出较高程度的异步性或不相似性,表明区域之间的神经元相互依赖性降低。我们的发现表明,自适应多尺度熵是感知可见性的敏感度量,因此可用于揭示刺激的感知意识。

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