论文标题
人类语言处理的脑电图签名的统一信息理论模型
A unified information-theoretic model of EEG signatures of human language processing
论文作者
论文摘要
我们推进了大脑中人类语言处理的信息理论模型，在该模型中，就启发式解释和误差校正而言，传入的语言输入在两个层面上进行了处理。我们建议这两种信息处理具有不同的脑电图签名，对应于有据可查的N400和P600与语言相关事件相关电位（ERP）的组件。正式地，我们表明，上下文中单词的信息内容（惊人）可以分解为两个数量：（a）启发式惊喜，启发式惊喜，鉴于其推断的上下文，它信号处理难度，并且与N400信号相对应； （b）差异信号，它反映了真实上下文和推断上下文之间的差异，并且对应于p600信号。这两种数量都可以使用现代NLP技术估算。我们通过成功模拟Ryskin等人先前报告的实验数据中的各种语言操作引起的ERP模式来验证我们的理论。 （2021）。我们的理论原则上与传统的认知理论兼容，假设“良好”的启发式解释阶段，但具有精确的信息理论表述。
We advance an information-theoretic model of human language processing in the brain, in which incoming linguistic input is processed at two levels, in terms of a heuristic interpretation and in terms of error correction. We propose that these two kinds of information processing have distinct electroencephalographic signatures, corresponding to the well-documented N400 and P600 components of language-related event-related potentials (ERPs). Formally, we show that the information content (surprisal) of a word in context can be decomposed into two quantities: (A) heuristic surprise, which signals processing difficulty of word given its inferred context, and corresponds with the N400 signal; and (B) discrepancy signal, which reflects divergence between the true context and the inferred context, and corresponds to the P600 signal. Both of these quantities can be estimated using modern NLP techniques. We validate our theory by successfully simulating ERP patterns elicited by a variety of linguistic manipulations in previously-reported experimental data from Ryskin et al. (2021). Our theory is in principle compatible with traditional cognitive theories assuming a `good-enough' heuristic interpretation stage, but with precise information-theoretic formulation.
