Graspability in disguise: The cognitive and neural differences in processing words representing small and big objects

Size is a fundamental visual-spatial characteristic of the physical world. Previous studies have revealed distinct brain responses to small and big objects represented by pictures, implying that object size is a key dimension in organizing concrete concepts. However, it remains unknown whether the brain responses reflecting size-based categorization extend to symbolic input like words. Furthermore, several behavioral studies have indicated faster lexical decisions for words representing big objects (big words) than those representing small objects (small words). However, how this behavioral finding relates to potential neural differences in processing small and big words, as well as the underlying cognitive processes, remains unclear. Therefore, the present study investigates the cognitive and neural differences in processing small and big words. We compared the behavioral and neural responses (EEG) to small and big words using a lexical decision task (LDT) and a semantic decision task (SDT). Our results showed that in the LDT, reaction times to big words were significantly shorter than those to small words in the by-participant but not by-item analysis, suggesting a potential rather than robust processing advantage for big words. By contrast, no behavioral differences were observed in the SDT. Our EEG decoding results revealed distinct brain responses to small and big words at 190–250 msec in both tasks, with additional distinct neural responses at 390–520 msec only in the SDT. Importantly, the regression representational similarity analysis (RSA) suggested that these distinct brain responses could be explained by object graspability represented by small and big words, rather than object size. These findings illustrate the cognitive and neural differences in processing small and big words, identify graspability as the key influencing dimension, and demonstrate flexible, two-stage processing of semantic concepts. Moreover, we propose a novel hypothesis to explain the potential processing advantage for big words over small words.