The Neural Dynamics of Attentional Selection in Natural Scenes

Daniel Kaiser, Nikolaas N. Oosterhof, and Marius V. Peelen Center for Mind/Brain Sciences, University of Trento, 38068 Rovereto, Italy Author contributions: D.K. and M.V.P. designed research; D.K. performed research; N.N.O. contributed unpublished reagents/analytic tools; D.K. and N.N.O. analyzed data; D.K. and M.V.P. wrote the paper. Abstract The human visual system can only represent a small subset of the many objects present in cluttered scenes at any given time, such that objects compete for representation. Despite these processing limitations, the detection of object categories in cluttered natural scenes is remarkably rapid. How does the brain efficiently select goal-relevant objects from cluttered scenes? In the present study, we used multivariate decoding of magneto-encephalography (MEG) data to track the neural representation of within-scene objects as a function of top-down attentional set. Participants detected…

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