Decoding the internal focus of attention.
Decoding the internal focus of attention.
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DOI：
10.1016/j.neuropsychologia.2011.11.006
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发表时间：
2012-03
期刊：
影响因子：
2.6
通讯作者：
Postle BR
中科院分区：
文献类型：
--
作者：
Lewis-Peacock JA;Postle BR
最近引入认知神经科学的多变量模式分析（MVPA）的意义在于，与单变量方法不同，单变量方法仅限于识别大脑局部区域的活动幅度，它提供了对分布在多个大脑区域内和跨多个大脑区域的活动模式的检测和表征。这种技术支持更强的推理，因为它捕获的神经表征具有明显高于单变量激活峰的选择性。最近，我们使用MVPA来评估从短期记忆（STM）中分离注意力的内部焦点的神经后果，发现延迟期活动中表示的信息仅对应于前者。在这里，我们报告了这些数据的几个额外分析，其中我们直接比较了MVPA产生的结果与单变量分析产生的结果。MVPA对分布式大脑活动模式的微妙变化的敏感性揭示了一个新的见解：尽管与无人看管的STM项目相对应的类别选择性大脑区域的总体活动仍然升高，但这些区域内的多变量活动模式反映了不同类别的代表性，即，目前正在接受治疗此外，MVPA是能够解离出席从无人值守的STM项目在大脑区域的单变量活动似乎并不敏感的任务。这些研究结果突出的谬误假设的同质性的代表在假定的类别选择区域。他们肯定了STM中的神经表征是高度分布和重叠的观点，并证明了多变量分析分离这种表征的必要性。
The significance of the recent introduction to cognitive neuroscience of multivariate pattern analysis (MVPA) is that, unlike univariate approaches which are limited to identifying magnitudes of activity in localized parts of the brain, it affords the detection and characterization of patterns of activity distributed within and across multiple brain regions. This technique supports stronger inferences because it captures neural representations that have markedly higher selectivity than do univariate activation peaks. Recently, we used MVPA to assess the neural consequences of dissociating the internal focus of attention from short-term memory (STM), finding that the information represented in delay-period activity corresponds only to the former. Here we report several additional analyses of these data in which we directly compared the results generated by MVPA vs. those generated by univariate analyses. The sensitivity of MVPA to subtle variations in patterns of distributed brain activity revealed a novel insight: Although overall activity remains elevated in category-selective brain regions corresponding to unattended STM items, the multivariate patterns of activity within these regions reflect the representation of a different category, i.e., the one that is currently being attended to. In addition, MVPA was able to dissociate attended from unattended STM items in brain regions whose univariate activity did not appear to be sensitive to the task. These findings highlight the fallacy of the assumption of homogeneity of representation within putative category-selective regions. They affirm the view that neural representations in STM are highly distributed and overlapping, and they demonstrate the necessity of multivariate analysis for dissociating such representations.
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