English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Gamma oscillatory activity related to language prediction

MPS-Authors
/persons/resource/persons1202

Wang,  Lin
Neurobiology of Language Department, MPI for Psycholinguistics, Max Planck Society;
Donders Institute for Brain, Cognition and Behaviour, External Organizations;
Harvard Medical School;

/persons/resource/persons69

Hagoort,  Peter
Neurobiology of Language Department, MPI for Psycholinguistics, Max Planck Society;
Donders Institute for Brain, Cognition and Behaviour, External Organizations;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)

Wang_Hagoort_Jensen_2018.pdf
(Publisher version), 2MB

Supplementary Material (public)
There is no public supplementary material available
Citation

Wang, L., Hagoort, P., & Jensen, O. (2018). Gamma oscillatory activity related to language prediction. Journal of Cognitive Neuroscience, 30(8), 1075-1085. doi:10.1162/jocn_a_01275.


Cite as: https://hdl.handle.net/21.11116/0000-0001-97F7-E
Abstract
Using magnetoencephalography, the current study examined gamma activity associated with language prediction. Participants read high- and low-constraining sentences in which the final word of the sentence was either expected or unexpected. Although no consistent gamma power difference induced by the sentence-final words was found between the expected and unexpected conditions, the correlation of gamma power during the prediction and activation intervals of the sentence-final words was larger when the presented words matched with the prediction compared with when the prediction was violated or when no prediction was available. This suggests that gamma magnitude relates to the match between predicted and perceived words. Moreover, the expected words induced activity with a slower gamma frequency compared with that induced by unexpected words. Overall, the current study establishes that prediction is related to gamma power correlations and a slowing of the gamma frequency.