We used natural reading of sentences to study how semantic control and representation mechanisms interact for the successful comprehension of sentences, by manipulating sentence context and single-word meaning. Specifically, we examined whether a word’s semantic characteristic (concreteness) affects first fixation and gaze durations (FFDs and GDs), and whether it interacts with the predictability of a word. We used a linear mixed effects model including several possible psycholinguistic covariates. We found main effects of concreteness and predictability on FFDs, but no interaction between the two. The results parallel previous findings of additive effects of predictability (context) and frequency (lexical-level) in fixation times. Our findings indicate that the semantics of a word and the context created by the preceding words additively influence early stages of word processing in natural sentence reading.

The temporal dynamics within the semantic brain network and its dependence on stimulus and task parameters are still not well understood. Here, we addressed this by decoding task as well as stimulus information from source-estimated EEG/MEG data. We presented the same visual word stimuli in a lexical decision (LD) and three semantic decision (SD) tasks. The meanings of the presented words varied across five semantic categories. Source space decoding was applied over time in five ROIs in the left hemisphere (Anterior and Posterior Temporal Lobe, Inferior Frontal Gyrus, Primary Visual Areas, and Angular Gyrus) and one in the right hemisphere (Anterior Temporal Lobe). Task decoding produced sustained significant effects in all ROIs from 50-100 ms, both when categorising tasks with different semantic demands (LD-SD) as well as for similar semantic tasks (SD-SD). In contrast, semantic word category could only be decoded in lATL, rATL, PTC and IFG, between 250-500 ms. Furthermore, we compared two approaches to source space decoding: Conventional ROI-by-ROI decoding and combined-ROI decoding with back-projected activation patterns. The former produced more reliable results for word-category decoding while the latter was more informative for task-decoding. This indicates that task effects are distributed across the whole semantic network while stimulus effects are more focal. Our results demonstrate that the semantic network is widely distributed but that bilateral anterior temporal lobes together with control regions are particularly relevant for the processing of semantic information.