Computational and neural mechanisms of divided attention in vision

项目摘要 人类每天多次尝试将注意力分散到多个刺激上，这与我们出色的能力不同 选择性地关注视觉场景中的相关位置，人类在这方面的成功程度要低得多。例如，考虑一下 在更换车内电台的同时检测红绿灯的变化。 在过去的几十年里，选择性注意的研究取得了长足的进步，但对选择性注意的研究却知之甚少。 注意力分散的影响。许多问题仍然存在，例如：你能注意到多少刺激而不损害 表现如何？在什么情况下，你可以并行处理多个刺激？现有的行为证据是 好坏参半。人们普遍认为，对于简单的视觉特征检测，分散注意力的成本很小，甚至没有成本。 然而，随着任务变得更加复杂，例如检测两个显示器之间的变化或某些视觉刺激 例如，去多个相关地点似乎是有成本的。这些任务和刺激的差异 尚未完全确定其特征，其潜在的神经机制尚不清楚。 在这里，我们提出了一系列的心理物理和功能核磁共振研究，以调查分离的空间注意在任务中的作用。 涉及到视觉刺激。通过改变任务需求，我们可以区分多个候选处理阶段 这可能会增加分散注意力的成本(具体目标1和2)。一种可能性是，在某些情况下 条件，加工刺激特征仅限于知觉水平。另一种是持有和比较多个 记忆中的视觉刺激会导致错误。第三种选择是，关注多个刺激会增加决策时的噪音 处理的阶段。一旦我们在行为上隔离了不同处理阶段的影响和组合，我们就会 使用功能磁共振成像定位早期视觉区域的神经机制(特定目标3)。 了解导致注意力分散的行为差异的大脑机制具有临床意义。 当我们考虑到有多少人有注意力差异作为表型时。例如，患有自闭症谱系的人 精神障碍患者在处理不止一种刺激方面有困难，而ADHD患者更有可能遇到困难 保持对多种刺激的注意。潜在机制可能被证明是将这些行为与 潜在的神经生理机制。

Project Summary Humans attempt to divide their attention across multiple stimuli many times a day, and unlike our excellent ability to selectively attend to a relevant location in a visual scene, humans are far less successful at doing so. Consider, for example, detecting a traffic light change while changing the radio station in the car. The study of selective attention has made considerable progress over the last few decades but much less is known about the effects of divided attention. Many questions still exist, such as: How many stimuli can you attend to without impairing performance? Under what circumstances can you process multiple stimuli in parallel? Existing behavioral evidence is mixed. It is generally agreed that for simple detection of visual features there is little to no cost of dividing attention. However, as the task becomes more complex, for example detecting a change between two displays, or certain visual stimuli such as words, there appears to be a cost to attending multiple relevant locations. These task and stimuli differences have not been fully characterized and the underlying neuronal mechanisms are unknown. Here, we propose a series of psychophysical and fMRI studies to investigate the role of divided spatial attention on tasks involving visual stimuli. By varying the task demands we can distinguish between a number of candidate processing stages which may be contributing to the cost of dividing attention (Specific Aim 1 and 2). One possibility is that under certain conditions, processing stimulus features is limited at the perceptual level. Another is that holding and comparing multiple visual stimuli in memory introduces errors. A third alternative is that attending to multiple stimuli adds noise at a decision stage of processing. Once we have behaviorally isolated the effects and combinations of different processing stages we will use fMRI to localize neural mechanisms in the early visual areas (Specific Aim 3). Understanding the brain mechanisms responsible for behavioral differences in dividing attention has clinical importance when we consider how many have attention differences as a phenotype. For example, individuals with autism spectrum disorder have difficulties attending to more than one stimuli, while those with ADHD are more likely to have difficulty maintaining attention on multiple stimuli. The underlying mechanisms may prove critical in linking these behaviors with underlying neurophysiological mechanisms.