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要旨:
Introduction:
During language comprehension, word-level information has to be integrated (unified) into an overall message-level representation. Theoretical accounts (e.g. Jackendoff, 2007; see also Hagoort, 2005) propose that unification operations occur in parallel at the phonological, syntactic and semantic levels. Meta-analysis of fMRI studies (Bookheimer, 2002) shows that largely overlapping areas in left inferior frontal gyrus (LIFG) are activated during the different types of unification operations. This raises the question of how the brain functionally segregates these different unification operations.
Previously, we have established that semantic unification modulates oscillatory EEG activity in the gamma frequency range (Hagoort, Hald, Bastiaansen, & Petersson, 2004; Hald, Bastiaansen, & Hagoort, 2005). More recently, we have shown that syntactic unification modulates MEG activity in the lower beta frequencies (13-18 Hz). Here we report a fully within-subjects replication of these findings.
Methods:
We recorded the EEG (64 channels, filtered from 0.1 - 100 Hz) of 30 subjects while they read sentences presented in serial visual presentation mode. Sentences were either correct (COR), contained a semantic violation (SEM), or a syntactic (grammatical gender agreement) violation (SYN). Two additional conditions were constructed on the basis of COR sentences by (1) replacing all the nouns, verbs and adjectves with semantically unrelated ones that were matched for length and frequency, making the sentences semantically ininterpretable (global semantic violation, GSEM, and (2) randomly re-assigning word order of the COR sentences, so as to remove overall syntactic structure from the sentences (global syntactic violation, GSYN). Here we only report the results of analyses on the COR, GSEM and GSYN conditions.
EEG epochs from 1s preceding sentence onset to 6s after sentence onset (corresponding to the first 10 words in each sentence) were extracted from the EEG recordings, and epochs with artifacts were removed. A multitaper-based time-frequency (TF) analysis of power changes (Mitra & Pesaran, 1999) was performed, separately for a low-frequency window (1-30 Hz) and high-frequency window (25-100 Hz). Significant differences in the TF representations between any two conditions were established unsing non-parametric random permutation analysis (Maris & Oostenveld, 2007).
Results:
Semantic unification: gamma
Figure 1 presents the comparison between the TF responses of the semantically intact condition (COR) and those of the semantically incorrect ones (GSEM, but also GSYN, since the absence of syntactic structure makes the sentence semantically uninterpretable as well). Both the COR-GSEM and the COR-GSYN contrasts show significantly larger power for the semantically correct sentences in a frequency range around 40 Hz (as well as some less consistent differences in higher frequencies). No differences were observed between GSEM and GSYN in the frequency range 25-100 Hz.
Syntactic unification: beta
Figure 2 presents the conparison between the TF responses of the syntactically correct conditions (COR and GSEM) and the incorrect one (GSYN). Both the COR-GSYN and the GSEM-GSYN contrasts show larger power in the 13-18 Hz frequency range for the syntactically correct sentences. No significant differences were observed between COR and GSEM in the frequency range 1-30 Hz.
Conclusions:
During the comprehension of correct sentences, both low beta power (13-18 Hz) and gamma power (here around 40 Hz) slowly increase as the sentence unfolds. When a sentence is devoid of syntactic structure, the beta increase is absent. When a sentence is devoid of semantically co=herent structure, the gamma increase is absent. Together the data show a fully within-subjects confirmation of previously obtained results in separate experiments (for review, see Bastiaansen & Hagoort, 2006). This suggests that neuronal synchronization in LIFG at gamma frequencies is related to semantic unification, whereas synchronization at beta frequencies is related to syntactic unification. Thus, our data are consistent with the notion of functional segregation through frequency-coding during unification operations in language comprehension.
References:
Bastiaansen, M. (2006), 'Oscillatory neuronal dynamics during language comprehension.', Prog Brain Res, vol. 159, pp. 179-196.
Bookheimer, S. (2002), 'Functional MRI of language: new approaches to understanding the cortical organization of semantic processing', Annu Rev Neurosci, vol. 25, pp. 151-188.
Hagoort, P. (2005), 'On Broca, brain, and binding: a new framework.', Trends Cogn Sci,, vol. 9, no. 9, pp. 416-423.
Hagoort, p. (2004), 'Integration of word meaning and world knowledge in language comprehension', Science, vol. 304, no. 5669, pp. 438-441.
Hald, L. (2005), 'EEG theta and gamma responses to semantic violations in online sentence processing', Brain & Language, vol. 96, no. 1, pp. 90-105..
Jackendoff, R. (2007), 'A Parallel Architecture perspective on language processing', Brain research, vol. 1146, pp. 2-22.
Maris, E. (2007), 'Nonparametric statistical testing of EEG- and MEG-data', J Neurosci Methods, vol. 164, no. 1, pp. 177-190.
Mitra, P. (1999), 'Analysis of dynamic brain imaging data.', Biophys. J., vol. 76, no. 2, pp. 691-708.
