Positive and negative moods tend to have differential effects on lexico-semantic processing in the native language (L1). Though accumulating evidence points to dampened sensitivity to affective stimuli in the non-native language (L2), little is known about the effects of positive and negative moods on L2 processing. Here, we show that lexico-semantic processing is differently affected by positive and negative moods only in L1. Unbalanced Polish–English bilinguals made meaningfulness judgments on L1 and L2 sentences during two EEG recording sessions featuring either positive- or negative-mood-inducing films. We observed a reduced N1 (lexical processing) for negative compared to positive mood in L2 only, a reduced N2 (lexico-semantic processing) in negative compared to positive mood in L1 only, a reduced N400 (lexico-semantic processing) for meaningless compared to meaningful L1 sentences in positive mood only, and an enhanced late positive complex (semantic integration and re-analysis) for L2 compared to L1 meaningful sentence in negative mood only. Altogether, these results suggest that positive and negative moods affect lexical, lexico-semantic, and semantic processing differently in L1 and L2. Our observations are consistent with previous accounts of mood-dependent processing and emotion down-regulation observed in bilinguals.

This study presents a Polish semantic priming dataset and semantic similarity ratings for word pairs obtained with native Polish speakers, as well as a range of semantic spaces. The word pairs include strongly related, weakly related, and semantically unrelated word pairs. The rating study (Experiment 1) confirmed that the three conditions differed in semantic relatedness. The semantic priming lexical decision study with a carefully matched subset of the stimuli (Experiment 2), revealed strong semantic priming effects for strongly related word pairs, whereas weakly related word pairs showed a smaller but still significant priming effect relative to semantically unrelated word pairs. The datasets of both experiments and those of SimLex-999 for Polish were then used in a robust semantic model selection from existing and newly trained semantic spaces. This database of semantic vectors, semantic relatedness ratings, and behavioral data collected for all word pairs enable future researchers to benchmark new vectors against this dataset. Furthermore, the new vectors are made freely available for researchers. Although similar semantically strongly and weakly related word pairs are available in other languages, this is the first freely available database for Polish, that combines measures of semantic distance and human data.