Prediction Signatures in the Brain: Semantic Pre-Activation during Language Comprehension

Abstract

There is broad agreement that context-based predictions facilitate lexical-semantic processing. A robust index of semantic prediction during language comprehension is an evoked response, known as the N400, whose amplitude is modulated as a function of semantic context. However, the underlying neural mechanisms that utilize relations of the prior context and the embedded word within it are largely unknown. We measured magnetoencephalography (MEG) data while participants were listening to simple German sentences in which the verbs were either highly predictive for the occurrence of a particular noun (i.e., provided context) or not. The identical set of nouns was presented in both conditions. Hence, differences for the evoked responses of the nouns can only be due to differences in the earlier context. We observed a reduction of the N400 response for highly predicted nouns. Interestingly, the opposite pattern was observed for the preceding verbs: highly predictive (that is more informative) verbs yielded stronger neural magnitude compared to less predictive verbs. A negative correlation between the N400 effect of the verb and that of the noun was found in a distributed brain network, indicating an integral relation between the predictive power of the verb and the processing of the subsequent noun. This network consisted of left hemispheric superior and middle temporal areas and a subcortical area; the parahippocampus. Enhanced activity for highly predictive relative to less predictive verbs, likely reflects establishing semantic features associated with the expected nouns, that is a pre-activation of the expected nouns.

The costs of being certain: Brain potential evidence for linguistic preactivation in sentence processing

“…We therefore argued that this preactivation should modulate the N400 component—the ERP component typically associated with the activation of semantic information (see Kutas & Federmeier, , for a review). The distribution (though more widely distributed; see Figure ) and the time course of the waveform that was modulated by adverb impact strongly suggest that this is indeed an N400 modulation (see Maess, Mamashli, Obleser, Helle, & Friederici, , for a recent comparable magnetoencephalography finding).…”

“…When readers in the present experiment arrived at the adverb, the event conveyed by the sentence was already largely expressed, and this circumstance might have contributed to the observed pattern. And even though results from Maess et al (2016) demonstrate that a minimal context suffices to elicit N400 effects between verbs that are more as compared to less informative about future input 7. Mean (cloze value * frequency * ONS)ˆ2 1 (1 1 (cloze value * frequency * ONS)ˆ2 j participant) 1 (1 j item).…”

“…When readers in the present experiment arrived at the adverb, the event conveyed by the sentence was already largely expressed, and this circumstance might have contributed to the observed pattern. And even though results from Maess et al () demonstrate that a minimal context suffices to elicit N400 effects between verbs that are more as compared to less informative about future input (informative, “He drives ” versus less informative, “He gets ”), it is questionable whether, for instance, in semantic priming studies (where no event information is available), primes that are more informative about the target also engender larger N400s than primes that are less informative.…”

Contributions of left frontal and temporal cortex to sentence comprehension: Evidence from simultaneous TMS-EEG

“…a recent MEG-study found effects of semantic predictability at the main verb of the 114 sentence (Maess et al, 2016). Specifically, a reversed N400m effect, the magnetic 115 pendant of the N400, was reported for the verb, with highly predictive verbs eliciting a 116 stronger N400m relative to verbs with a lower predictability.…”

“…To 157 capture a potential behavioral impact of the TMS induced perturbation that is usually 158 quantified in terms of decreased response accuracy or increased response speed 159 (Hartwigsen, 2015), a lexical decision task was included. Motivated by a previous 160 study that used similar sentences and found effects already at the mid-sentence verb 161 position in addition to the sentence-final noun position (Maess et al, 2016), the 162 present study applied TMS over pIFG and pSTG/STS at verb onset. This allowed for 163 testing whether the perturbation effect would only impact processing during the 164 stimulated period (i.e., processing of the verb) or outlast verb presentation and also 165 impact integration of the final noun into a sentence.…”