Neural correlates of face perception modeled with a convolutional recurrent neural network

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dc.contributor.authorJamie A. O’Reilly
dc.contributor.authorJordan Wehrman
dc.contributor.authorAaron Carey
dc.contributor.authorJennifer Bedwin
dc.contributor.authorThomas Hourn
dc.contributor.authorFawad Asadi
dc.contributor.authorPaul F. Sowman
dc.date.accessioned2026-05-08T19:19:43Z
dc.date.issued2023-3-10
dc.description.abstractThe approach developed in this work is potentially of significant value for visual neuroscience research, where it may be adapted for multiple contexts to study computational relationships between visual stimuli and evoked neural activity.
dc.identifier.doi10.1088/1741-2552/acc35b
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/17171
dc.publisherJournal of Neural Engineering
dc.subjectFace Recognition and Perception
dc.subjectNeural dynamics and brain function
dc.subjectVisual Attention and Saliency Detection
dc.titleNeural correlates of face perception modeled with a convolutional recurrent neural network
dc.typeArticle

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