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首页> 外文期刊>Journal of vision >Recall of facial expressions and simple orientations reveals competition for resources at multiple levels of the visual hierarchy
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Recall of facial expressions and simple orientations reveals competition for resources at multiple levels of the visual hierarchy

机译:回忆面部表情和简单的方向揭示了视觉层次结构多个级别上对资源的竞争

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Many studies of visual working memory have tested humans' ability to reproduce primary visual features of simple objects, such as the orientation of a grating or the hue of a color patch, following a delay. A consistent finding of such studies is that precision of responses declines as the number of items in memory increases. Here we compared visual working memory for primary features and high-level objects. We presented participants with memory arrays consisting of oriented gratings, facial expressions, or a mixture of both. Precision of reproduction for all facial expressions declined steadily as the memory load was increased from one to five faces. For primary features, this decline and the specific distributions of error observed, have been parsimoniously explained in terms of neural population codes. We adapted the population coding model for circular variables to the non-circular and bounded parameter space used for expression estimation. Total population activity was held constant according to the principle of normalization and the intensity of expression was decoded by drawing samples from the Bayesian posterior distribution. The model fit the data well, showing that principles of population coding can be applied to model memory representations at multiple levels of the visual hierarchy. When both gratings and faces had to be remembered, an asymmetry was observed. Increasing the number of faces decreased precision of orientation recall, but increasing the number of gratings did not affect recall of expression, suggesting that memorizing faces involves the automatic encoding of low-level features, in addition to higher-level expression information.
机译:视觉工作记忆的许多研究已经测试了人类在延迟之后再现简单对象的主要视觉特征的能力,例如光栅的方向或色块的色调。此类研究的一个一致发现是,随着记忆中项目数量的增加,响应的精度会下降。在这里,我们比较了主要功能和高级对象的视觉工作记忆。我们为参与者提供了由定向光栅,面部表情或两者混合构成的存储阵列。随着记忆负荷从一张面孔增加到五张面孔,所有面部表情的再现精度都在稳步下降。对于主要特征,已经用神经人口代码来简化解释了这种下降和观察到的误差的具体分布。我们将用于圆形变量的总体编码模型调整为用于表达式估计的非圆形和有界参数空间。根据归一化原理,总种群活动保持恒定,并且通过从贝叶斯后验分布中抽取样本来解码表达强度。该模型很好地拟合了数据,表明总体编码的原理可以应用于可视层次结构的多个级别的模型内存表示。当必须记住光栅和面时,观察到不对称。面孔数量的增加会降低定向召回的准确性,但增加光栅的数量不会影响表情的召回,这表明记忆面孔不仅会涉及高层表情信息,还会涉及对低层特征的自动编码。

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