Beyond the word and image: III. Neurodynamic properties of the semantic network

Abstract

Understanding the neural process underlying the comprehension of visual images and sentences remains a major open challenge in cognitive neuroscience. We previously demonstrated with fMRI and DTI that comprehension of visual images and sentences describing human activities recruits a common semantic system. The current research tests the hypothesis that this common semantic system will display similar neural dynamics during processing in these two modalities. To investigate these neural dynamics we recorded EEG from naïve subjects as they saw simple narratives made up of a first visual image depicting a human event, followed by a second that was either a sequentially coherent narrative follow-up, or not, of the first image. In separate blocks of trials the same protocol was presented using sentences. Analysis of the EEG signal revealed common neural dynamics for semantic processing across image and sentence modalities. Late positive ERPs were observed in response to sequential incoherence for sentences and images, consistent with previous studies that examined coherence in these two modalities separately. Analysis of oscillatory power revealed increased gamma-band activity for sequential coherence, again consistent with previous studies showing gamma increases for coherence and matching in sentence and image processing. Multivariate analysis demonstrated that training a classifier on data from one modality (images or sentences) allowed reliable decoding of the sequential coherence of data from trials in the untrained modality, providing further support for a common underlying semantic system for images and sentences. Processing sequential coherence of successive stimuli is associated with neural dynamics that are common to sentence and visual image modalities and that can be decoded across modalities. These results are discussed in the context of EEG signatures of narrative processing and meaning, and more general neural mechanisms for structure processing.