Neural Correlates of Semantic Prediction and Resolution in Sentence Processing
نویسندگان
چکیده
Most brain-imaging studies of language comprehension focus on activity following meaningful stimuli. Testing adult human participants with high-density EEG, we show that, already before the presentation of a critical word, context-induced semantic predictions are reflected by a neurophysiological index, which we therefore call the semantic readiness potential (SRP). The SRP precedes critical words if a previous sentence context constrains the upcoming semantic content (high-constraint contexts), but not in unpredictable (low-constraint) contexts. Specific semantic predictions were indexed by SRP sources within the motor system-in dorsolateral hand motor areas for expected hand-related words (e.g., "write"), but in ventral motor cortex for face-related words ("talk"). Compared with affirmative sentences, negated ones led to medial prefrontal and more widespread motor source activation, the latter being consistent with predictive semantic computation of alternatives to the negated expected concept. Predictive processing of semantic alternatives in negated sentences is further supported by a negative-going event-related potential at ∼400 ms (N400), which showed the typical enhancement to semantically incongruent sentence endings only in high-constraint affirmative contexts, but not to high-constraint negated ones. These brain dynamics reveal the interplay between semantic prediction and resolution (match vs error) processing in sentence understanding.SIGNIFICANCE STATEMENT Most neuroscientists agree on the eminent importance of predictive mechanisms for understanding basic as well as higher brain functions. This contrasts with a sparseness of brain measures that directly reflects specific aspects of prediction, as they are relevant in the processing of language and thought. Here we show that when critical words are strongly expected in their sentence context, a predictive brain response reflects meaning features of these anticipated symbols already before they appear. The granularity of the semantic predictions was so fine grained that the cortical sources in sensorimotor and medial prefrontal cortex even distinguished between predicted face- or hand-related action words (e.g., the words "lick" or "pick") and between affirmative and negated sentence meanings.
منابع مشابه
Semantic Priming Effect on Relative Clause Attachment Ambiguity Resolution in L2
This study examined whether processing ambiguous sentences containing relative clauses (RCs) following a complex determiner phrase (DP) by Persian-speaking learners of L2 English with different proficiency and working memory capacities (WMCs) is affected by semantic priming. The semantic relationship studied was one between the subject/verb of the main clause and one of the DPs in the complex D...
متن کاملFirst Language Activation during Second Language Lexical Processing in a Sentential Context
Lexicalization-patterns, the way words are mapped onto concepts, differ from one language to another. This study investigated the influence of first language (L1) lexicalization patterns on the processing of second language (L2) words in sentential contexts by both less proficient and more proficient Persian learners of English. The focus was on cases where two different senses of a polys...
متن کاملElectrophysiological correlates of semantic anticipation during speech comprehension.
Words that are more predictable given a previous context show facilitated processing over low predictable ones. Such facilitation has been traditionally viewed as associated with reduced amplitudes in the N400 component. However, this effect is observed during the presentation of the target word, and it does not provide direct information about the prediction processes engaged before. To overco...
متن کاملForm and Content Dissociating Syntax and Semantics in Sentence Comprehension
The distinction between syntax (sentence form) and semantics (sentence meaning) is fundamental to our thinking about language. Whether and where this distinction is represented at the neural level is still a matter of considerable debate. In the present fMRI study, we examined the neural correlates of syntactic and semantic functions using an innovative activation paradigm specifically designed...
متن کاملA combined Wavelet- Artificial Neural Network model and its application to the prediction of groundwater level fluctuations
Accurate groundwater level modeling and forecasting contribute to civil projects, land use, citys planning and water resources management. Combined Wavelet-Artificial Neural Network (WANN) model has been widely used in recent years to forecast hydrological and hydrogeological phenomena. This study investigates the sensitivity of the pre-processing to the wavelet type and decomposition level in ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره 37 شماره
صفحات -
تاریخ انتشار 2017