a b s t r a c tBy means of functional magnetic resonance imaging the present paper analyzes the neural correlates of processing and appreciating incongruity-resolution and nonsense cartoons. Furthermore, the relation between experience seeking and these neural substrates was investigated as this personality characteristic is known to influence humor appreciation. In the processing of incongruity-resolution stimuli the incongruity of the joke is largely resolvable, whereas in nonsense stimuli it is only partially resolvable and more incongruity remains. The anterior medial prefrontal cortex, bilateral superior frontal gyri and temporo-parietal junctions (TPJ) show more activation during processing of incongruity-resolution than of nonsense cartoons. These differences indicate that processing of incongruity-resolution cartoons requires more integration of multi-sensory information and coherence building, as well as more mental manipulation and organization of information. In addition, less self-reference might be established in nonsense cartoons as it is more absurd and more often deals with impossible situations. Higher experience-seeking scores correlate with increased activation in prefrontal, posterior temporal regions and the hippocampus. This might be due to a more intense exploration of the humorous stimuli as experience seekers tend to search novel mental stimulation. Furthermore, experience seeking was positively associated with brain reactivity towards processing nonsense in contrast to incongruity-resolution stimuli, which is in line with behavioral studies that showed a preference for nonsense humor by experience seekers.

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A pun is a form of wordplay in which a word suggests two or more meanings by exploiting polysemy, homonymy, or phonological similarity to another word, for an intended humorous or rhetorical effect. Though a recurrent and expected feature in many discourse types, puns stymie traditional approaches to computational lexical semantics because they violate their one-sense-percontext assumption. This paper describes the first competitive evaluation for the automatic detection, location, and interpretation of puns. We describe the motivation for these tasks, the evaluation methods, and the manually annotated data set. Finally, we present an overview and discussion of the participating systems' methodologies, resources, and results.