2021
DOI: 10.1101/2021.08.22.451834
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Getting the gist faster: Blurry images enhance the early temporal similarity between neural signals and convolutional neural networks

Abstract: Humans are able to recognize objects under a variety of noisy conditions, so models of the human visual system must account for how this feat is accomplished. In this study, we investigated how image perturbations, specifically reducing images to their low spatial frequency (LSF) components, affected correspondence between convolutional neural networks (CNNs) and brain signals recorded using magnetoencephalography (MEG). Using the high temporal resolution of MEG, we found that CNN-Brain correspondence for deep… Show more

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