Neuroimaging of valence decisions in children and adults

Neural correlates of understanding emotional words in late childhood

Prior studies involving adults have shown that words can elicit emotional processing, with emotion-label (e.g., happiness) and emotion-laden words (e.g., gift) having distinct processes. However, limited studies have explored the developmental changes in these processes in relation to emotional valence. To address this question, this exploratory study measured event-related potentials (ERPs) in 11-14-year-old children/adolescents (N = 25) and adults (N = 23) while performing an emotional categorization task. The stimuli used were two-character Chinese words, with factors for word type (emotion-label versus emotion-laden) and valence (positive versus negative). To confirm word emotionality, neutral words were also included and compared with all emotional words. The results showed that adults exhibited reduced N400 amplitudes to emotion-label words compared to emotion-laden ones in both positive and negative valence contexts. The differentiation was only sustained for negative valence in the late positive component (LPC). Similar scalp distributions of the effects of word type were found in children/adolescents; however, they exhibited a more prolonged processing of all emotional words than adults. These results suggest that the processing of emotion-label and emotion-laden words are distinct in late childhood, and this discrepancy varies with emotional valence and increasing age.

Computational Models of Readers' Apperceptive Mass

Recent progress in machine-learning-based distributed semantic models (DSMs) offers new ways to simulate the apperceptive mass (AM; Kintsch, 1980) of reader groups or individual readers and to predict their performance in reading-related tasks. The AM integrates the mental lexicon with world knowledge, as for example, acquired via reading books. Following pioneering work by Denhière and Lemaire (2004), here, we computed DSMs based on a representative corpus of German children and youth literature (Jacobs et al., 2020) as null models of the part of the AM that represents distributional semantic input, for readers of different reading ages (grades 1–2, 3–4, and 5–6). After a series of DSM quality tests, we evaluated the performance of these models quantitatively in various tasks to simulate the different reader groups' hypothetical semantic and syntactic skills. In a final study, we compared the models' performance with that of human adult and children readers in two rating tasks. Overall, the results show that with increasing reading age performance in practically all tasks becomes better. The approach taken in these studies reveals the limits of DSMs for simulating human AM and their potential for applications in scientific studies of literature, research in education, or developmental science.