Object recognition under challenging real-world conditions, including partial occlusion, remains an enduring focus of investigation in cognitive visual neuroscience. This study addresses the insufficiently elucidated neural mechanisms and temporal dynamics involved in this complex process, concentrating on the persistent challenge of recognizing objects obscured by occlusion. Through the analysis of human EEG data, we decode feedback characteristics within frontotemporal networks, uncovering intricate neural mechanisms during occlusion coding, with a specific emphasis on processing complex stimuli such as occluded faces. Our findings elucidate the critical role of frontal feedback in the late processing stage of occluded face recognition, contributing to enhanced accuracy in identification. Temporal dynamics reveal distinct characteristics in both early and late processing stages, allowing the discernment of two unique types of occlusion processing that go beyond visual features, incorporating higher-order associations. The increased synchronized activity between frontal and temporal areas during the processing of occluded stimuli underscores the importance of frontotemporal coordination in challenging real-world conditions. A comparative analysis with macaque IT cortex recordings validates the contribution of the frontal cortex in the late stage of occluded face processing. Notably, the observed disparity between human EEG and two deep computational models, both with and without the consideration of feedback connection, emphasize the necessity for expanding models to accurately simulate frontal feedback.
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http://dx.doi.org/10.1016/j.neuroimage.2025.121058 | DOI Listing |
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