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Mid-level feature differences underlie early animacy and object size distinctions: Evidence from EEG decoding
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Responses to visually-presented objects along the cortical surface of the human brain have a large-scale organization reflecting the broad categorical divisions of animacy and object size. Mounting evidence indicates that this topographical organization is driven by differences between objects in mid-level perceptual features. With regard to the timing of neural responses, images of objects quickly evoke neural responses with decodable information about animacy and object size, but are mid-level features sufficient to evoke these rapid neural responses? Or is slower iterative neural processing required to untangle information about animacy and object size from mid-level features? To answer this question, we used electroencephalography (EEG) to measure human neural responses to images of objects and their texform counterparts – unrecognizable images which preserve some mid-level feature information about texture and coarse form. We found that texform images evoked neural responses with early decodable information about both animacy and real-world size, as early as responses evoked by original images. Further, successful cross-decoding indicates that both texform and original images evoke information about animacy and size through a common underlying neural basis. Broadly, these results indicate that the visual system contains a mid-level feature bank carrying linearly decodable information on animacy and size, which can be rapidly activated without requiring explicit recognition or protracted temporal processing.
Title: Mid-level feature differences underlie early animacy and object size distinctions: Evidence from EEG decoding
Description:
Responses to visually-presented objects along the cortical surface of the human brain have a large-scale organization reflecting the broad categorical divisions of animacy and object size.
Mounting evidence indicates that this topographical organization is driven by differences between objects in mid-level perceptual features.
With regard to the timing of neural responses, images of objects quickly evoke neural responses with decodable information about animacy and object size, but are mid-level features sufficient to evoke these rapid neural responses? Or is slower iterative neural processing required to untangle information about animacy and object size from mid-level features? To answer this question, we used electroencephalography (EEG) to measure human neural responses to images of objects and their texform counterparts – unrecognizable images which preserve some mid-level feature information about texture and coarse form.
We found that texform images evoked neural responses with early decodable information about both animacy and real-world size, as early as responses evoked by original images.
Further, successful cross-decoding indicates that both texform and original images evoke information about animacy and size through a common underlying neural basis.
Broadly, these results indicate that the visual system contains a mid-level feature bank carrying linearly decodable information on animacy and size, which can be rapidly activated without requiring explicit recognition or protracted temporal processing.
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