Abstract:
:When faced with a crowded visual scene, observers must selectively attend to behaviorally relevant objects to avoid sensory overload. Often this selection process is guided by prior knowledge of a target-defining feature (e.g., the color red when looking for an apple), which enhances the firing rate of visual neurons that are selective for the attended feature. Here, we used functional magnetic resonance imaging and a pattern classification algorithm to predict the attentional state of human observers as they monitored a visual feature (one of two directions of motion). We find that feature-specific attention effects spread across the visual field-even to regions of the scene that do not contain a stimulus. This spread of feature-based attention to empty regions of space may facilitate the perception of behaviorally relevant stimuli by increasing sensitivity to attended features at all locations in the visual field.
journal_name
Neuronjournal_title
Neuronauthors
Serences JT,Boynton GMdoi
10.1016/j.neuron.2007.06.015subject
Has Abstractpub_date
2007-07-19 00:00:00pages
301-12issue
2eissn
0896-6273issn
1097-4199pii
S0896-6273(07)00445-Xjournal_volume
55pub_type
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