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Neural Discriminability of Object Features Predicts Perceptual Organization

机译:对象特征的神经可分辨性预测感知组织

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How does the neural representation of simple visual features affect perceptual operations, such as perceptual grouping? If the strength of feature representations in the brain is indicative of how the perceptual system partitions information into visual elements, then identifying the underlying neural representation may determine why things look the way they do. During functional MRI, participants viewed objects that varied along three feature dimensions: shape, color, and orientation. Afterward, participants performed an independent perceptual-grouping task outside the scanner to measure the strength of feature grouping. In lateral occipital cortex, neural feature discriminability, characterized using functional MRI multivariate pattern classification, positively predicted feature grouping strength: The more distinct the neural representations of a particular feature, the stronger the grouping was for that feature outside the scanner. Thus, variation in neural feature representation can be quantified to predict perceptual organization.
机译:简单视觉特征的神经表示如何影响诸如感知分组的感知操作?如果大脑中特征表示的强度指示了感知系统如何将信息划分为视觉元素,那么识别潜在的神经表示可以确定事物为何以它们的方式运行。在功能性MRI期间,参与者查看了沿三个特征维度变化的对象:形状,颜色和方向。之后,参与者在扫描仪外部执行了独立的感知分组任务,以测量特征分组的强度。在枕外侧叶中,使用功能性MRI多元模式分类进行表征的神经特征可辨别性,正向预测特征分组强度:特定特征的神经表示越清晰,在扫描仪外部对该特征的分组就越强。因此,可以量化神经特征表示的变化以预测知觉组织。

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