Department of Psychology, National Taiwan University Taipei, Taiwan ; Department of Psychology, Fo Guang University Yilan, Taiwan.
Department of Psychology, National Taiwan University Taipei, Taiwan ; Neurobiology and Cognitive Science Center, National Taiwan University Taipei, Taiwan.
Front Psychol. 2014 May 21;5:456. doi: 10.3389/fpsyg.2014.00456. eCollection 2014.
Visual attention can be allocated to either a location or an object, named location- or object-based attention, respectively. Despite the burgeoning evidence in support of the existence of two kinds of attention, little is known about their underlying mechanisms in terms of whether they are achieved by enhancing signal strength or excluding external noises. We adopted the noise-masking paradigm in conjunction with the double-rectangle method to probe the mechanisms of location-based attention and object-based attention. Two rectangles were shown, and one end of one rectangle was cued, followed by the target appearing at (a) the cued location; (b) the uncued end of the cued rectangle; and (c) the equal-distant end of the uncued rectangle. Observers were required to detect the target that was superimposed at different levels of noise contrast. We explored how attention affects performance by assessing the threshold versus external noise contrast (TvC) functions and fitted them with a divisive inhibition model. Results show that location-based attention - lower threshold at cued location than at uncued location - was observed at all noise levels, a signature of signal enhancement. However, object-based attention - lower threshold at the uncued end of the cued than at the uncued rectangle - was found only in high-noise conditions, a signature of noise exclusion. Findings here shed a new insight into the current theories of object-based attention.
视觉注意力可以分配到一个位置或一个物体,分别称为位置或基于物体的注意力。尽管有越来越多的证据支持这两种注意力的存在,但对于它们是通过增强信号强度还是排除外部噪声来实现的,人们知之甚少。我们采用噪声掩蔽范式结合双矩形方法来探究基于位置的注意力和基于物体的注意力的机制。显示两个矩形,一个矩形的一端被提示,然后目标出现在 (a) 提示位置;(b) 提示矩形的未提示端;和 (c) 未提示矩形的等距端。观察者需要检测叠加在不同噪声对比度水平下的目标。我们通过评估阈值与外部噪声对比度 (TvC) 函数并将其拟合到一个除法抑制模型来探索注意力如何影响性能。结果表明,基于位置的注意力——在提示位置的阈值低于未提示位置——在所有噪声水平下都观察到,这是信号增强的特征。然而,基于物体的注意力——在提示矩形的未提示端的阈值低于未提示矩形的阈值——仅在高噪声条件下发现,这是噪声排除的特征。这一发现为基于物体的注意力的现有理论提供了新的见解。