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Spatiotemporal mechanisms for detecting and identifying image features in human vision

Abstract

Our visual system constantly selects salient features in the environment, so that only those features are attended and targeted by further processing efforts to identify them. Models of feature detection hypothesize that salient features are localized based on contrast energy (local variance in intensity) in the visual stimulus. This hypothesis, however, has not been tested directly. We used psychophysical reverse correlation to study how humans detect and identify basic image features (bars and short line segments). Subjects detected a briefly flashed 'target bar' that was embedded in 'noise bars' that randomly changed in intensity over space and time. By studying how the intensity of the noise bars affected performance, we were able to dissociate two processing stages: an early 'detection' stage, whereby only locations of high-contrast energy in the image are selected, followed (after 100 ms) by an 'identification' stage, whereby image intensity at selected locations is used to determine the identity (whether bright or dark) of the target.

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Figure 1: Stimuli and reverse-correlation technique.
Figure 2: Mean and variance kernels for two subjects.
Figure 3: Experiment 2.
Figure 4: Mean and variance images for false alarm trials only, from experiment 1, bright bar target.

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Acknowledgements

We thank H. Barlow, C. Blakemore, B. Cumming, A. Parker, D. Ringach and B. Zenger-Landolt for useful discussions. P.N. was supported by the McDonnell-Pew Program in Cognitive Neuroscience (while at Oxford) and the Wellcome Trust (while at Stanford). D.J.H. was supported by a National Eye Institute grant.

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Correspondence to Peter Neri.

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Neri, P., Heeger, D. Spatiotemporal mechanisms for detecting and identifying image features in human vision. Nat Neurosci 5, 812–816 (2002). https://doi.org/10.1038/nn886

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