Serences John T, Boynton Geoffrey M
Department of Cognitive Sciences, University of California, Irvine, Irvine, CA 92697-5100, USA.
Neuron. 2007 Jul 19;55(2):301-12. doi: 10.1016/j.neuron.2007.06.015.
When faced with a crowded visual scene, observers must selectively attend to behaviorally relevant objects to avoid sensory overload. Often this selection process is guided by prior knowledge of a target-defining feature (e.g., the color red when looking for an apple), which enhances the firing rate of visual neurons that are selective for the attended feature. Here, we used functional magnetic resonance imaging and a pattern classification algorithm to predict the attentional state of human observers as they monitored a visual feature (one of two directions of motion). We find that feature-specific attention effects spread across the visual field-even to regions of the scene that do not contain a stimulus. This spread of feature-based attention to empty regions of space may facilitate the perception of behaviorally relevant stimuli by increasing sensitivity to attended features at all locations in the visual field.
当面对拥挤的视觉场景时，观察者必须有选择地关注与行为相关的物体，以避免感官过载。通常，这种选择过程由对目标定义特征的先验知识引导（例如，寻找苹果时的红色），这会提高对所关注特征具有选择性的视觉神经元的 firing 率。在这里，我们使用功能磁共振成像和模式分类算法来预测人类观察者在监测视觉特征（两种运动方向之一）时的注意力状态。我们发现，特定于特征的注意力效应会在整个视野中传播——甚至传播到不包含刺激的场景区域。基于特征的注意力向空间空白区域的这种传播可能通过提高对视野中所有位置的关注特征的敏感性来促进对与行为相关刺激的感知。
