Attentional propagation of conceptual information in the human brain

The visual environment is complicated, and humans and other animals accordingly prioritise some sources of information over others through the deployment of spatial attention. We presume that attention has the ultimate purpose of guiding the abstraction of information from perceptual experience in the development of concepts and categories. However, neuroscientific investigation has focussed closely on identification of the systems and algorithms that support attentional control, or that instantiate the effect of attention on sensation and perception. Much less is known about how attention impacts the acquisition and activation of high-level information in the brain. Here, we use machine learning of EEG and concurrently-recorded EEG/MRI to temporally and anatomically characterise the neural network that abstracts from attended perceptual information to activate and construct semantic and conceptual representations. We find that the trial-wise amplitude of N2pc - an ERP component closely linked to selective attention - predicts the rapid emergence of information about semantic categories in EEG. Similar analysis of EEG/MRI shows that N2pc predicts MRI-derived category information in a network including VMPFC, posterior parietal cortex, and anterior insula. These brain areas appear critically involved in the attention-mediated translation of perceptual information to concepts, semantics, and action plans.