Mapping WordNet onto human brain connectome in emotion processing and semantic similarity recognition

In this article we extend a WordNet structure with relations linking synsets to Desikan?s brain regions. Based on lexicographer files and WordNet Domains the mapping goes from synset semantic categories to behavioural and cognitive functions and then directly to brain lobes. A human brain connectome (HBC) adjacency matrix was utilised to capture transition probabilities between brain regions. We evaluated the new structure in several tasks related to semantic similarity and emotion processing using brain-expanded Princeton WordNet (207k LUs) and Polish WordNet (285k LUs, 30k annotated with valence, arousal and 8 basic emotions). A novel HBC vector representation turned out to be significantly better than proposed baselines.

Automated summary

In this study, a WordNet structure was expanded to link synsets to Desikan's brain regions, mapping from synset semantic categories to behavioral and cognitive functions to brain lobes. Transition probabilities between brain regions were captured using a human brain connectome (HBC) adjacency matrix. The new structure was evaluated in tasks related to semantic similarity and emotion processing, showing that the novel HBC vector representation outperformed proposed baselines.