Department of Psychological and Brain Sciences and The Institute for Collaborative Biotechnologies, University of California, Santa Barbara, Santa Barbara, California.
Ann N Y Acad Sci. 2014 May;1316:71-86. doi: 10.1111/nyas.12404. Epub 2014 Apr 9.
The human attention system helps us cope with a complex environment by supporting the selective processing of information relevant to our current goals. Understanding the perceptual, cognitive, and neural mechanisms that mediate selective attention is a core issue in cognitive neuroscience. One prominent model of selective attention, known as load theory, offers an account of how task demands determine when information is selected and an account of the efficiency of the selection process. However, load theory has several critical weaknesses that suggest that it is time for a new perspective. Here we review the strengths and weaknesses of load theory and offer an alternative biologically plausible computational account that is based on the neural theory of visual attention. We argue that this new perspective provides a detailed computational account of how bottom-up and top-down information is integrated to provide efficient attentional selection and allocation of perceptual processing resources.
人类注意系统通过支持对与当前目标相关的信息进行选择性处理，帮助我们应对复杂的环境。理解介导选择性注意的感知、认知和神经机制是认知神经科学的核心问题。选择性注意的一个突出模型，即负荷理论，提供了一种关于任务需求如何决定信息何时被选择的解释，以及关于选择过程效率的解释。然而，负荷理论有几个关键的弱点，这表明它是时候采用一种新的视角了。在这里，我们回顾了负荷理论的优缺点，并提供了一个基于视觉注意的神经理论的替代的、具有生物学意义的计算解释。我们认为，这种新视角提供了一个详细的计算解释，说明如何整合自上而下和自下而上的信息，以提供有效的注意力选择和感知处理资源的分配。
