Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.06.22.163584v1?rss=1 Authors: Quek, G. L., Rossion, B., Liu-Shuang, J. Abstract: Humans rapidly and automatically recognise faces on multiple different levels, yet little is known about how the brain achieves these manifold categorisations concurrently. We bring a new perspective to this emerging issue by probing the relative informational dependencies of two of the most important aspects of human face processing: categorisation of the stimulus as a face (generic face recognition) and categorisation of its familiarity (familiar face recognition). Recording electrophysiological responses to a large set of natural images progressively increasing in image duration (Expt. 1) or spatial frequency content (Expt. 2), we contrasted critical sensory thresholds for these recognition functions as driven by the same face encounters. Across both manipulations, individual observer thresholds were consistently lower for distinguishing faces from other objects than for distinguishing familiar from unfamiliar faces. Moreover, familiar face recognition displayed marked inter-individual variability compared to generic face recognition, with no systematic relationship evident between the two thresholds. Scalp activation was also more strongly right-lateralised at the generic face recognition threshold than at the familiar face recognition threshold. These results suggest that high-level recognition of a face as a face arises based on minimal sensory input (i.e., very brief exposures/coarse resolutions), predominantly in right hemisphere regions. In contrast, the amount of additional sensory evidence required to access face familiarity is highly idiosyncratic and recruits wider neural networks. These findings underscore the neurofunctional distinctions between these two recognition functions, and constitute an important step forward in understanding how the human brain recognises various dimensions of a face in parallel. Copy rights belong to original authors. Visit the link for more info