Processing Mechanism of Chinese Verbal Jokes : Evidence from ERP and Neural Oscillations
Li, X.-Y., Wang, H.-L., Saariluoma, P., Zhang, G.-H., Zhu, Y.-J., Zhang, C., Cong, F.-Y., & Ristaniemi, T. (2019). Processing Mechanism of Chinese Verbal Jokes : Evidence from ERP and Neural Oscillations. Journal of Electronic Science and Technology, 17(3), 260-277. https://doi.org/10.11989/JEST.1674-862X.80520017
Published inJournal of Electronic Science and Technology
© 2019 University of Electronic Science and Technology of China
The cognitive processing mechanism of humor refers to how the system of neural circuitry and pathways in the brain deals with the incongruity in a humorous manner. The past research has revealed different stages and corresponding functional brain activities involved in humor-processing in terms of time and space dimensions, highlighting the effects of the time windows of about 400 ms, 600 ms, and 900 ms. However, much less is known about humor processing in light of the frequency dimension. A total of 36 Chinese participants were recruited in this experiment, with Chinese jokes, nonjokes, and nonsensical sentences used as the stimuli. The experimental results showed that there were significant differences among conditions in the P200 effect, which signified that the incongruity detection had already been integrated and perceived at about 200 ms, prior to the semantic integration at about 400 ms. This pre-processing is specific to Chinese verbal jokes due to the simultaneous involvement of both orthographic and phonologic parts in processing Chinese characters. The analysis on the frequency dimension indicated that beta’s power particularly reflected the characteristics of different stages in Chinese verbal humor processing. Jokes’ and nonsensical sentences’ relative power changes on the beta band ranked significantly higher than that of nonjokes at about 200 ms, which suggested the existence of more difficulties in meaning construction in pre-processing the incongruities. This indicated a continuity between the analysis of event related potential (ERP) components and neural oscillations and revealed the key role of the beta frequency band in Chinese verbal joke processing. ...
PublisherDianzi Keji Daxue, University of Electronic Science and Technology of China
Publication in research information system
MetadataShow full item record
Showing items with similar title or keywords.
Li, Xueyan; Wang, Huili; Saariluoma, Pertti; Wang, Xiaolu (Sciencedomain International, 2018)Aims: To apply the findings of neurolinguistic research to the practical technological artifact design, the cognitive mechanism of verbal humour is comprehensively investigated and designed with EEG-based Brain Computer ...
Neural Mechanisms Underlying Human Auditory Evoked Responses Revealed By Human Neocortical Neurosolver Kohl, Carmen; Parviainen, Tiina; Jones, Stephanie R. (Springer, 2021)Auditory evoked fields (AEFs) are commonly studied, yet their underlying neural mechanisms remain poorly understood. Here, we used the biophysical modelling software Human Neocortical Neurosolver (HNN) whose foundation is ...
Hannonen, Riitta (Jyväskylän yliopisto, 2011)
Neural correlates of morphological processing and its development from pre-school to the first grade in children with and without familial risk for dyslexia Louleli, Natalia; Hämäläinen, Jarmo A.; Nieminen, Lea; Parviainen, Tiina; Leppänen, Paavo H.T. (Elsevier, 2022)Previous studies have shown that the development of morphological awareness and reading skills are interlinked. However, most have focused on phonological awareness as a risk factor for dyslexia, although there is considerable ...
Identifying Oscillatory Hyperconnectivity and Hypoconnectivity Networks in Major Depression Using Coupled Tensor Decomposition Liu, Wenya; Wang, Xiulin; Xu, Jing; Chang, Yi.; Hämäläinen, Timo; Cong, Fengyu (Institute of Electrical and Electronics Engineers (IEEE), 2021)Previous researches demonstrate that major depression disorder (MDD) is associated with widespread network dysconnectivity, and the dynamics of functional connectivity networks are important to delineate the neural mechanisms ...