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Comprehending conditional statements is fundamental for hypothetical reasoning about situations. However, the online comprehension of conditional statements containing different conditional connectives is still debated. We report two self-paced reading experiments on German conditionals presenting the conditional connectives wenn (‘if’) and nur wenn (‘only if’) in identical discourse contexts. In Experiment 1, participants read a conditional sentence followed by the confirmed antecedent p and the confirmed or negated consequent q. The final, critical sentence was presented word by word and contained a positive or negative quantifier (ein/kein ‘one/no’). Reading times of the two quantifiers did not differ between the two conditional connectives. In Experiment 2, presenting a negated antecedent, reading times for the critical positive quantifier (ein) did not differ between conditional connectives, while reading times for the negative quantifier (kein) were shorter for nur wenn than for wenn. The results show that comprehenders form distinct predictions about discourse continuations due to differences in the lexical semantics of the tested conditional connectives, shedding light on the role of conditional connectives in the online interpretation of conditionals in general.
Although the N400 was originally discovered in a paradigm designed to elicit a P300 (Kutas and Hillyard, 1980), its relationship with the P300 and how both overlapping event-related potentials (ERPs) determine behavioral profiles is still elusive. Here we conducted an ERP (N = 20) and a multiple-response speed-accuracy tradeoff (SAT) experiment (N = 16) on distinct participant samples using an antonym paradigm (The opposite of black is white/nice/yellow with acceptability judgment). We hypothesized that SAT profiles incorporate processes of task-related decision-making (P300) and stimulus-related expectation violation (N400). We replicated previous ERP results (Roehm et al., 2007): in the correct condition (white), the expected target elicits a P300, while both expectation violations engender an N400 [reduced for related (yellow) vs. unrelated targets (nice)]. Using multivariate Bayesian mixed-effects models, we modeled the P300 and N400 responses simultaneously and found that correlation between residuals and subject-level random effects of each response window was minimal, suggesting that the components are largely independent. For the SAT data, we found that antonyms and unrelated targets had a similar slope (rate of increase in accuracy over time) and an asymptote at ceiling, while related targets showed both a lower slope and a lower asymptote, reaching only approximately 80% accuracy. Using a GLMM-based approach (Davidson and Martin, 2013), we modeled these dynamics using response time and condition as predictors. Replacing the predictor for condition with the averaged P300 and N400 amplitudes from the ERP experiment, we achieved identical model performance. We then examined the piecewise contribution of the P300 and N400 amplitudes with partial effects (see Hohenstein and Kliegl, 2015). Unsurprisingly, the P300 amplitude was the strongest contributor to the SAT-curve in the antonym condition and the N400 was the strongest contributor in the unrelated condition. In brief, this is the first demonstration of how overlapping ERP responses in one sample of participants predict behavioral SAT profiles of another sample. The P300 and N400 reflect two independent but interacting processes and the competition between these processes is reflected differently in behavioral parameters of speed and accuracy.