透视图(图形)
感知
认知心理学
选择性
心理学
计算机科学
化学
神经科学
人工智能
生物化学
催化作用
作者
Barry Giesbrecht,Jocelyn L. Sy,Claus Bundesen,Søren Kyllingsbæk
摘要
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.
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