Oscillatory Dynamics Supporting Semantic Cognition: MEG Evidence for the Contribution of the Anterior Temporal Lobe Hub and Modality-Specific Spokes.
Oscillatory Dynamics Supporting Semantic Cognition: MEG Evidence for the Contribution of the Anterior Temporal Lobe Hub and Modality-Specific Spokes.
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DOI：
10.1371/journal.pone.0169269
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发表时间：
2017
期刊：
影响因子：
3.7
通讯作者：
Jefferies E
中科院分区：
文献类型：
--
作者：
Mollo G;Cornelissen PL;Millman RE;Ellis AW;Jefferies E
语义表示的“中心和辐条模型”表明，对象的多模态特征由前颞叶（ATL）“中心”汇集在一起，而特定模态的“辐条”捕获感知/动作特征。然而，人们对这些组件如何随着时间的推移而被招募来支持物体识别知之甚少。我们使用脑磁图来测量不同类别（人造与动物）的不同特异性水平（使用上级标签与特定标签）的文字-图片匹配过程中左 ATL、外侧梭状皮层 (FC) 和中央沟 (CS) 内的神经振荡。这使我们能够确定（i）每个站点何时对语义类别敏感，以及（ii）这是否受到任务需求的调节。在 ATL 中，有两个响应阶段：从刺激后约 100 毫秒开始，出现低伽马活性的阶段性爆发，导致振荡功率相对于基线期降低，并受到类别和特异性的调节；随后，从 250 毫秒开始，整个频段的功率持续下降。在辐条中，对于特定识别而言，初始功率增加并不强，而对于动物的 FC 和人造物体的 CS 中的特定级别识别，后来的功率下降更强（分别约为 150 毫秒和 200 毫秒）。这些数据与时间顺序不一致，其中早期感觉运动活动随后是 ATL 中的后期检索。相反，知识是从中心和辐条的快速招募中产生的，在 ATL 中心具有早期的特异性和类别效应。这些组成部分之间的平衡取决于语义类别和任务，视觉皮层在动物的细粒度识别中发挥更大的作用，而运动皮层则有助于工具的识别。
The “hub and spoke model” of semantic representation suggests that the multimodal features of objects are drawn together by an anterior temporal lobe (ATL) “hub”, while modality-specific “spokes” capture perceptual/action features. However, relatively little is known about how these components are recruited through time to support object identification. We used magnetoencephalography to measure neural oscillations within left ATL, lateral fusiform cortex (FC) and central sulcus (CS) during word-picture matching at different levels of specificity (employing superordinate vs. specific labels) for different categories (manmade vs. animal). This allowed us to determine (i) when each site was sensitive to semantic category and (ii) whether this was modulated by task demands. In ATL, there were two phases of response: from around 100 ms post-stimulus there were phasic bursts of low gamma activity resulting in reductions in oscillatory power, relative to a baseline period, that were modulated by both category and specificity; this was followed by more sustained power decreases across frequency bands from 250 ms onwards. In the spokes, initial power increases were not stronger for specific identification, while later power decreases were stronger for specific-level identification in FC for animals and in CS for manmade objects (from around 150 ms and 200 ms, respectively). These data are inconsistent with a temporal sequence in which early sensory-motor activity is followed by later retrieval in ATL. Instead, knowledge emerges from the rapid recruitment of both hub and spokes, with early specificity and category effects in the ATL hub. The balance between these components depends on semantic category and task, with visual cortex playing a greater role in the fine-grained identification of animals and motor cortex contributing to the identification of tools.