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首页> 外文期刊>Neuropsychologia >The steady-state visual evoked potential reveals neural correlates of the items encoded into visual working memory
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The steady-state visual evoked potential reveals neural correlates of the items encoded into visual working memory

机译：稳态视觉诱发电位揭示了编码到视觉工作记忆中的项目的神经相关性

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摘要

Visual working memory (VWM) capacity limitations are estimated to be ~4 items. Yet, it remains unclear why certain items from a given memory array may be successfully retrieved from VWM and others are lost. Existing measures of the neural correlates of VWM cannot address this question because they measure the aggregate processing of the entire stimulus array rather than neural signatures of individual items. Moreover, this cumulative processing is usually measured during the delay period, thereby reflecting the allocation of neural resources during VWM maintenance. Here, we use the steady-state visual evoked potential (SSVEP) to identify the neural correlates of individual stimuli at VWM encoding and test two distinct hypotheses: the focused-resource hypothesis and the diffuse-resource hypothesis, for how the allocation of neural resources during VWM encoding may contribute to VWM capacity limitations. First, we found that SSVEP amplitudes were larger for stimuli that were later remembered than for items that were subsequently forgotten. Second, this pattern generalized so that the SSVEP amplitudes were also larger for the unprobed stimuli in correct compared to incorrect trials. These data are consistent with the diffuse-resource view in which attentional resources are broadly allocated across the whole stimulus array. These results illustrate the important role encoding mechanisms play in limiting the capacity of VWM.
机译：视觉工作记忆（VWM）的容量限制估计约为4个项目。但是，仍不清楚为什么可以从VWM成功检索给定内存阵列中的某些项目而丢失其他项目。 VWM的神经关联的现有度量无法解决此问题，因为它们度量的是整个刺激阵列的总体处理过程，而不是单个项目的神经特征。而且，这种累积处理通常在延迟期间进行测量，从而反映了VWM维护期间神经资源的分配。在这里，我们使用稳态视觉诱发电位（SSVEP）来识别VWM编码下单个刺激的神经相关性，并测试两个不同的假设：聚焦资源假设和分散资源假设，以了解神经资源的分配方式VWM编码过程中可能会造成VWM容量限制。首先，我们发现，对于后来被记忆的刺激，SSVEP振幅要大于后来被遗忘的刺激。其次，这种模式普遍存在，因此与未正确的试验相比，未正确刺激的SSVEP振幅也更大。这些数据与分散资源视图一致，在分散资源视图中，注意力资源广泛分布在整个刺激阵列中。这些结果说明了编码机制在限制VWM容量方面的重要作用。

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