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The dynamics of visual pattern masking in natural scene processing: A magnetoencephalography study

MPG-Autoren
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Rieger,  J
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Bülthoff,  HH
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Gegenfurtner,  K
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Rieger, J., Braun, C., Bülthoff, H., & Gegenfurtner, K. (2005). The dynamics of visual pattern masking in natural scene processing: A magnetoencephalography study. Journal of Vision, 5(3): 10, pp. 275-286. doi:10.1167/5.3.10.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0013-D5F1-B
Zusammenfassung
We investigated the dynamics of natural scene processing and mechanisms of pattern masking in a scene-recognition task. Psychophysical recognition performance and the magnetoencephalogram (MEG) were recorded simultaneously. Photographs of natural scenes were briefly displayed and in the masked condition immediately followed by a pattern mask. Viewing the scenes without masking elicited a transient occipital activation that started approximately 70 ms after the pattern onset, peaked at 110 ms, and ended after 170 ms. When a mask followed the target an additional transient could be reliably identified in the MEG traces. We assessed psychophysical performance levels at different latencies of this transient. Recognition rates were reduced only when the additional activation produced by the pattern mask overlapped with the initial 170 ms of occipital activation from the target. Our results are commensurate with an early cortical locus of pattern masking and indicate that 90 ms of undistorted cortical processing is necessary to reliably recognize a scene. Our data also indicate that as little as 20 ms of undistorted processing is sufficient for above-chance discrimination of a scene from a distracter.