Spatial frequency supports the emergence of categorical representations in visual cortex during natural scene perception

Diana C. Dima, Gavin Perry, Krish D. Singh
2018 NeuroImage  
A R T I C L E I N F O Keywords: Multivariate pattern analysis (MVPA) Representational similarity analysis (RSA) Magnetoencephalography (MEG) Convolutional neural network (CNN) Scene categorization A B S T R A C T In navigating our environment, we rapidly process and extract meaning from visual cues. However, the relationship between visual features and categorical representations in natural scene perception is still not well understood. Here, we used natural scene stimuli from different
more » ... es and filtered at different spatial frequencies to address this question in a passive viewing paradigm. Using representational similarity analysis (RSA) and crossdecoding of magnetoencephalography (MEG) data, we show that categorical representations emerge in human visual cortex at~180 ms and are linked to spatial frequency processing. Furthermore, dorsal and ventral stream areas reveal temporally and spatially overlapping representations of low and high-level layer activations extracted from a feedforward neural network. Our results suggest that neural patterns from extrastriate visual cortex switch from low-level to categorical representations within 200 ms, highlighting the rapid cascade of processing stages essential in human visual perception.
doi:10.1016/j.neuroimage.2018.06.033 pmid:29902586 pmcid:PMC6057270 fatcat:b7loogks5nefjdojo3qcz2jqyy