The relationship between the evoked responses (ERPs/ERFs) and the event-related changes in EEG/MEG power that can be observed during sentence-level language comprehension is as yet unclear. This study addresses a possible relationship between MEG power changes and the N400m component of the event-related field. Whole-head MEG was recorded while subjects listened to spoken sentences with incongruent (IC) or congruent (C) sentence endings. A clear N400m was observed over the left hemisphere, and was larger for the IC sentences than for the C sentences. A time-frequency analysis of power revealed a decrease in alpha and beta power over the left hemisphere in roughly the same time range as the N400m for the IC relative to the C condition. A linear regression analysis revealed a positive linear relationship between N400m and beta power for the IC condition, not for the C condition. No such linear relation was found between N400m and alpha power for either condition. The sources of the beta decrease were estimated in the LIFG, a region known to be involved in semantic unification operations. One source of the N400m was estimated in the left superior temporal region, which has been related to lexical retrieval. We interpret our data within a framework in which beta oscillations are inversely related to the engagement of task-relevant brain networks. The source reconstructions of the beta power suppression and the N400m effect support the notion of a dynamic communication between the LIFG and the left superior temporal region during language comprehension.

Levels of job satisfaction, occupational commitment and intent to stay reported by nurses in this study can be improved. Suggested strategies for improvement are: increasing salaries, decreasing workloads, modifying task structure, cultivating work passion and creating more professional opportunity for nurses' personal growth development and promotion. Enhancing nurses' job satisfaction and occupational commitment are vital to improve nurses' intent to stay and for strategies to address the nursing shortage.

Readers and listeners actively predict upcoming words during language processing. These predictions might serve to support the unification of incoming words into sentence context and thus rely on interactions between areas in the language network. In the current magnetoencephalography study, participants read sentences that varied in contextual constraints so that the predictability of the sentence-final words was either high or low. Before the sentence-final words, we observed stronger alpha power suppression for the highly compared with low constraining sentences in the left inferior frontal cortex, left posterior temporal region, and visual word form area. Importantly, the temporal and visual word form area alpha power correlated negatively with left frontal gamma power for the highly constraining sentences. We suggest that the correlation between alpha power decrease in temporal language areas and left prefrontal gamma power reflects the initiation of an anticipatory unification process in the language network.