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Visual attention models postulate that relevant information is selectively extracted by differentially modulating neural activity in the visual cortex to control the response to target and distractor stimuli. To investigate attention bias mechanisms in the brain, we use general linear modeling of cortically constrained images of oscillatory alpha activity extracted from an MEG study of visual attention. By using a novel ANCOVA design, we create statistics that estimate the temporal evolution of attention effects on several cortical regions. We present evidence that the superior parietal lobe and temporal parietal junction have instrumental roles, respectively, in shifting and sustaining attention.