Testing two-step models of negative quantification using a novel machine learning analysis of EEG.

The sentences " of the students passed the exam" and " of the students failed the exam" describe the same set of situations, and yet the former results in shorter reaction times in verification tasks. The two-step model explains this result by postulating that negative quantifiers contain hidden negation, which involves an extra processing stage. To test this theory, we applied a novel EEG analysis technique focused on detecting cognitive stages (HsMM-MVPA) to data from a picture-sentence verification task. We estimated the number of processing stages during reading and verification of quantified sentences (e.g. " of the dots are blue") that followed the presentation of pictures containing coloured geometric shapes. We did not find evidence for an extra step during the verification of sentences with . We provide an alternative interpretation of our results in line with an expectation-based pragmatic account.