Semantic properties of words: Establishing their temporal and spatial correlates in the brain

Recognising written words, an essential part of reading, is subjectively effortless and objectively fast. While it is well-established that readers are highly proficient in the semantic interpretation of written information, debate and enquiry continues to surround the precise time course of word recognition, its neural substrates, and the extent to which semantic factors can modulate these processes. The current proposal investigates the temporal and spatial correlates of processing the semantic features of words, including their emotionality (arousal, valence, dominance), visualisation (concreteness, imageability), salience (semantic size, gendered association), and subjective frequency (familiarity, age
of acquisition). Brain imaging techniques capable of capturing the temporal and spatial contingencies of word recognition processes are utilised across a series of experiments. First, in a large-scale word recognition task using simultaneous electroencephalography (EEG) and magnetoencephalography (MEG) recording, the relative timing and strength of activations associated with different semantic dimensions will be assessed. Second, in two studies using functional magnetic resonance imaging (fMRI), the contribution of brain regions specific to the processing of words' emotionality and semantic size will be evaluated. It is expected that the findings will provide novel insights into the semantic
processing of words and will inform and constrain current models of word recognition in reading.

The research will be the first study of its kind to examine precise temporal and spatial components of processing multiple semantic dimensions of words. The EEG-MEG and fMRI experiments complement each other in identifying components associated with words varying across multiple semantic dimensions. It is expected that the findings will establish the contributions of semantic features to word recognition, and will help delineate the differences between individual features. This will in turn inform models of the neural circuitry associated with automatic recognition of words. Although humans are capable of rapid word recognition with minimal effort, much remains unknown as to how this is achieved. The combined findings from large, multidimensional EEG-MEG and more focussed fMRI studies will allow for identification of both the temporal and spatial properties of components associated with various semantic features of words, establishing the 'when' and 'where' of semantic feature integration during word recognition.