论文标题
在不同的实验条件下，惊喜如何解释N400振幅？
How well does surprisal explain N400 amplitude under different experimental conditions?
论文作者
论文摘要
我们研究了可以使用单词惊奇的单词来预测人类语言处理难度的神经度量-N400。为此，我们使用复发性神经网络来计算先前发表的N400神经语言学研究的刺激的惊喜。我们发现，惊奇可以在各种情况下预测N400振幅，而这种情况无法做到的情况可以为反应背后的神经认知过程提供宝贵的见解。
We investigate the extent to which word surprisal can be used to predict a neural measure of human language processing difficulty - the N400. To do this, we use recurrent neural networks to calculate the surprisal of stimuli from previously published neurolinguistic studies of the N400. We find that surprisal can predict N400 amplitude in a wide range of cases, and the cases where it cannot do so provide valuable insight into the neurocognitive processes underlying the response.
