Garagnani Max, Shtyrov Yury, Pulvermüller Friedemann
Medical Research Council, Cognition and Brain Sciences Unit Cambridge, UK.
Front Hum Neurosci. 2009 Jun 30;3:10. doi: 10.3389/neuro.09.010.2009. eCollection 2009.
Recent results obtained with a neural-network model of the language cortex suggest that the memory circuits developing for words are both distributed and functionally discrete. This model makes testable predictions about brain responses to words and pseudowords under variable availability of attentional resources. In particular, due to their strong internal connections, the action-perception circuits for words that the network spontaneously developed exhibit functionally discrete activation dynamics, which are only marginally affected by attentional variations. At the same time, network responses to unfamiliar items - pseudowords - that have not been previously learned (and, therefore, lack corresponding memory representations) exhibit (and predict) strong attention dependence, explained by the different amounts of attentional resources available and, therefore, different degrees of competition between multiple memory circuits partially activated by items lacking lexical traces. We tested these predictions in a novel magnetoencephalography experiment and presented subjects with familiar words and matched unfamiliar pseudowords during attention demanding tasks and under distraction. The magnetic mismatch negativity (MMN) response to words showed relative immunity to attention variations, whereas the MMN to pseudowords exhibited profound variability: when subjects attended the stimuli, the brain response to pseudowords was larger than that to words (as typically observed in the N400); when attention was withdrawn, the opposite pattern emerged, with the response to pseudowords reduced below the response to words. Main cortical sources of these activations were localized to superior-temporal cortex. These results confirm the model's predictions and provide evidence in support of the hypothesis that words are represented in the brain as action-perception circuits that are both discrete and distributed.
最近利用语言皮层神经网络模型获得的结果表明，为单词形成的记忆回路既是分布式的，又是功能离散的。该模型对在注意力资源可用性变化的情况下大脑对单词和伪词的反应做出了可检验的预测。特别是，由于其强大的内部连接，网络自发形成的单词动作感知回路表现出功能离散的激活动态，这种动态仅受到注意力变化的轻微影响。与此同时，网络对以前未学过的（因此缺乏相应记忆表征的）不熟悉项目——伪词——的反应表现出（并预测）强烈的注意力依赖性，这可以用可用注意力资源的不同数量来解释，因此也可以用缺乏词汇痕迹的项目部分激活的多个记忆回路之间不同程度的竞争来解释。我们在一项新颖的脑磁图实验中测试了这些预测，并在注意力要求较高的任务和分心情况下向受试者呈现熟悉的单词和匹配的不熟悉伪词。对单词的磁失配负波（MMN）反应对注意力变化表现出相对的免疫性，而对伪词的MMN则表现出极大的变异性：当受试者关注刺激时，大脑对伪词的反应比对单词的反应更大（如在N400中通常观察到的那样）；当注意力被撤回时，出现相反的模式，对伪词的反应降低到对单词的反应以下。这些激活的主要皮层源定位在颞上叶皮层。这些结果证实了模型的预测，并为单词在大脑中作为离散且分布式的动作感知回路来表征这一假设提供了支持证据。
