Ultrafast scene detection and recognition with limited visual information

利用有限的视觉信息进行超快速场景检测和识别

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Abstract

Humans can detect target color pictures of scenes depicting concepts like picnic or harbor in sequences of six or twelve pictures presented as briefly as 13 ms, even when the target is named after the sequence (Potter, Wyble, Hagmann, & McCourt, 2014). Such rapid detection suggests that feedforward processing alone enabled detection without recurrent cortical feedback. There is debate about whether coarse, global, low spatial frequencies (LSFs) provide predictive information to high cortical levels through the rapid magnocellular (M) projection of the visual path, enabling top-down prediction of possible object identities. To test the "Fast M" hypothesis, we compared detection of a named target across five stimulus conditions: unaltered color, blurred color, grayscale, thresholded monochrome, and LSF pictures. The pictures were presented for 13-80 ms in six-picture rapid serial visual presentation (RSVP) sequences. Blurred, monochrome, and LSF pictures were detected less accurately than normal color or grayscale pictures. When the target was named before the sequence, all picture types except LSF resulted in above-chance detection at all durations. Crucially, when the name was given only after the sequence, performance dropped and the monochrome and LSF pictures (but not the blurred pictures) were at or near chance. Thus, without advance information, monochrome and LSF pictures were rarely understood. The results offer only limited support for the Fast M hypothesis, suggesting instead that feedforward processing is able to activate conceptual representations without complementary reentrant processing.

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