A Shared, Flexible Neural Map Architecture Reflects Capacity Limits in Both Visual Short-Term Memory and Enumeration
A Shared, Flexible Neural Map Architecture Reflects Capacity Limits in Both Visual Short-Term Memory and Enumeration
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DOI：
10.1523/jneurosci.2758-13.2014
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发表时间：
2014-07-23
影响因子：
5.3
通讯作者：
Melcher, David
中科院分区：
文献类型：
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作者：
Knops, Andre;Piazza, Manuela;Melcher, David
人类认知的特点是严重的能力限制：我们一次只能准确地跟踪、列举或记住少量的项目。跨任务的容量限制是否由一个共同的系统决定仍然存在争议。在这里，我们测量了成人受试者在执行视觉短期记忆（vSTM）任务时的大脑激活情况，该任务包括记住关于可变数量的物品的方向和位置的精确信息，或者在执行枚举任务时包括评估这些集合中的物品数量。我们发现，特定任务的容量限制（列举3到4个项目，vSTM 2到3个项目）在神经上反映在后顶叶皮层（PPC）的活动中：该区域的一组相同的体素，通常在两个任务期间被激活，改变了其整体反应概况，反映了特定任务的容量限制。这些结果在第二个实验中得到了重复，并得到了多元模式分析的进一步支持，在多元模式分析中，我们可以在枚举期间解码比vSTM期间更大范围内呈现的项目数量。最后，我们使用显著性图架构模拟了PPC的计算模型，其中节点之间的相互抑制水平会产生容量限制，并反映了需要编码对象的任务相关精度（vSTM的高精度，枚举的低精度）。总之，我们的工作支持在PPC中存在一个通用的、灵活的系统，该系统可以采用显著性图的形式来支持跨任务的容量限制。
Human cognition is characterized by severe capacity limits: we can accurately track, enumerate, or hold in mind only a small number of items at a time. It remains debated whether capacity limitations across tasks are determined by a common system. Here we measure brain activation of adult subjects performing either a visual short-term memory (vSTM) task consisting of holding in mind precise information about the orientation and position of a variable number of items, or an enumeration task consisting of assessing the number of items in those sets. We show that task-specific capacity limits (three to four items in enumeration and two to three in vSTM) are neurally reflected in the activity of the posterior parietal cortex (PPC): an identical set of voxels in this region, commonly activated during the two tasks, changed its overall response profile reflecting task-specific capacity limitations. These results, replicated in a second experiment, were further supported by multivariate pattern analysis in which we could decode the number of items presented over a larger range during enumeration than during vSTM. Finally, we simulated our results with a computational model of PPC using a saliency map architecture in which the level of mutual inhibition between nodes gives rise to capacity limitations and reflects the task-dependent precision with which objects need to be encoded (high precision for vSTM, lower precision for enumeration). Together, our work supports the existence of a common, flexible system underlying capacity limits across tasks in PPC that may take the form of a saliency map.