Electroencephalogram oscillations differentiate semantic and prosodic processes during sentence reading

Y. Luo, Y. Zhang, X. Feng, X. Zhou*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

41 Citations (Scopus)


How prosodic information is processed at the neural level during silent sentence reading is an unsolved issue. In this study, we investigate whether and how the processing of prosodic constraints can be distinguished from the processing of semantic constraints by measuring changes in event-related electroencephalogram (EEG) power. We visually presented Chinese sentences containing verb-noun combinations that were semantically congruent or incongruent and that had normal or abnormal rhythmic patterns and asked participants to judge whether the sentences were semantically and rhythmically acceptable. In Chinese, the rhythmic pattern refers to the combination of words with different syllable lengths. While the [1+1] pattern is normal for a verb-noun combination, the [2+1] pattern is abnormal. With the critical nouns, we found that the violation of semantic constraints was associated with the low beta (16-20 Hz) decrease in the early window (0-200 ms post onset) and the alpha (10-15 Hz) and low beta decrease in the later window (400-657 ms) while the processing of the abnormal rhythmic pattern was associated with the theta (4-6 Hz) and the alpha increase in the early window and the alpha and upper beta (20-24 Hz) decrease in the later window. These findings suggest that although the processing of semantic constraints and the processing of rhythmic pattern may partially share neuro-cognitive processes, as reflected by the similar decreases in alpha band power, they can nevertheless be differentiated in EEG responses during sentence reading.

Original languageEnglish
Pages (from-to)654-664
Number of pages11
Issue number2
Publication statusPublished - 2010 Aug
Externally publishedYes


  • Prosody
  • Rhythmic pattern
  • Semantic congruency
  • Sentence processing
  • Time-frequency analysis

ASJC Scopus subject areas

  • General Neuroscience


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