Department of Linguistics
Title: An fMRI study of the neural networks of semantic categorisation and semantic association
Speaker: LIU Chun Yin
Time: 3.30pm, Monday 25th April
via Zoom
https://hku.zoom.us/j/91560333381?pwd=TCtTS1hhaHBQWU4rTlo2ZTUxQXVBUT09
Meeting ID: 915 6033 3381
Password: 334702
Abstract:
Semantic categorisation and semantic association constitute two different kinds of processing. The former relies on grouping concepts which share a linguistic label (e.g. animals, food, vehicles) but are not necessarily similar perceptually, while the latter depends on the spatial, temporal or logical co-occurrence of the two concepts (e.g. cloud and sky, door and lock). The present study investigates the neural mechanisms of processing these two semantic relationships. The semantic network is known to be divided into at least two components in the cerebral cortex, namely a semantic representation network and a semantic control network. The semantic representation network is further divided into modality-specific regions and heteromodal regions for the integration of modality-specific concepts. The goal of this study is to examine the relative contributions of these networks to semantic categorisation and association. An fMRI study was conducted in which twenty-three participants were scanned while performing semantic categorisation and semantic association tasks. A synonym judgement task was included as a reference for the basic semantic retrieval processing. We identified a distributed semantic network shared among the three tasks, including bilateral inferior and superior frontal gyri, the left middle frontal gyrus, fusiform gyrus, middle and interior temporal gyrus, superior parietal lobule and angular gyrus. Comparison between tasks revealed that semantic association recruited bilateral frontal regions and the left posterior temporal region more strongly, while the activation of the bilateral precuneus was stronger during semantic categorisation. We discuss the implications of the results to the semantic representation and control networks, and the neurocognitive models of semantic categorisation and association.
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