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Duality of Function: Activation for Meaningless Nonwords and Semantic Codes in the Same Brain Areas

机译:功能的二元性:激活同一大脑区域的无意义的非单词和语义代码

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Studies of the neural substrates of semantic (word meaning) processing have typically focused on semantic manipulations, with less consideration for potential differences in difficulty across conditions. While the idea that particular brain regions can support multiple functions is widely accepted, studies of specific cognitive domains rarely test for co-location with other functions. Here we start with standard univariate analyses comparing words to meaningless nonwords, replicating our recent finding that this contrast can activate task-positive regions for words, and default-mode regions in the putative semantic network for nonwords, pointing to difficulty effects. Critically, this was followed up with a multivariate analysis to test whether the same areas activated for meaningless nonwords contained semantic information sufficient to distinguish high- from low-imageability words. Indeed, this classification was performed reliably better than chance at 75% accuracy. This is compatible with two non-exclusive interpretations. Numerous areas in the default-mode network are task-negative in the sense of activating for less demanding conditions, and the same areas contain information supporting semantic cognition. Therefore, while areas of the default mode network have been hypothesized to support semantic cognition, we offer evidence that these areas can respond to both domain-general difficulty effects, and to specific aspects of semantics.
机译:语义(词含义)处理的神经基材的研究通常集中在语义上,较少考虑跨条件困难的潜在差异。虽然特别是脑区可以支持多种功能的想法被广泛接受,但对特定认知结构域的研究很少测试与其他功能的共同位置。在这里,我们从标准的单变量分析开始将单词与无意义的非单词进行比较,复制我们最近的发现,这对比度可以激活任务正区域的单词,以及指向难以造成的Unword的推定语义网络中的默认模式区域。批判性地,这是随后进行的多变量分析,以测试针对无意义的非字的相同区域是否包含足以区分高低可易成形性词的语义信息。实际上,这种分类比以75%的准确度更好地完成。这与两个非独家解释兼容。默认模式网络中的许多区域是激活苛刻条件的激活感的任务负数,并且相同的区域包含支持语义认知的信息。因此,虽然默认模式网络的区域已经假设支持语义认知,但我们提供了这些领域可以响应域一般难度影响以及语义的具体方面。

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