Impact of social knowledge about the speaker on irony understanding: Evidence from neural oscillations

ABSTRACT

The aim of the present study was to explore neuronal oscillatory activity during a task of irony understanding. In this task, we manipulated implicit information about the speaker such as occupation stereotypes (i.e., sarcastic versus non-sarcastic). These stereotypes are social knowledge that influence the extent to which the speaker’s ironic intent is understood. Time-frequency analyses revealed an early effect of speaker occupation stereotypes, as evidenced by greater synchronization in the upper gamma band (in the 150–250 ms time window) when the speaker had a sarcastic occupation, by a greater desynchronization for ironic context compared to literal context in the alpha1 band and by a greater synchronization in the theta band when the speaker had a non-sarcastic occupation. When the speaker occupation did not constrain the ironic interpretation, the interpretation of the sentence as ironic was revealed as resource-demanding and requiring pragmatic reanalysis, as shown mainly by the synchronization in the theta band and the desynchronization in the alpha1 band (in the 500–800 ms time window). These results support predictions of the constraint satisfaction model suggesting that during irony understanding, extra-linguistic information such as information on the speaker is used as soon as it is available, in the early stage of processing.

KEYWORDS:

• irony
• social knowledge
• stereotypes
• constraint satisfaction model
• time-frequency analyses

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/17470919.2023.2203948

Notes

¹ “There are four defining characteristic of constraint-based approaches. First, as an utterance unfolds, listeners rapidly integrate multiple probabilistic sources of information in a weighted manner. Second, listeners generate expectations of multiple types about the future, including the acoustic/phonetic properties of utterances, syntactic structures, referential domains, and possible speaker meanings. Third, speakers and listeners can rapidly adjust expectations to different speakers and different situations, etc. Fourth, explanations that depend upon architectural constraints (e.g., information-encapsulated modules, discrete sequential processing stages) are only considered as a last resort.” (Degen & Tanenhaus, 2019, p. 22).

Additional information

Funding

This work was supported by the Agence Nationale de la Recherche under grant ANR-11-BSH2006-01 to Maud Champagne-Lavau, grants ANR-11-LABX-0036, ANR-16-CONV-0002 and the Excellence Initiative of Aix-Marseille University (A*MIDEX).