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Updated: Apr 16, 2026

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control
Published on: July 5, 2015
Neural mechanisms of human perceptual choice under focused and divided attention
Valentin Wyart1, Nicholas E Myers2, Christopher Summerfield3
1Laboratoire de Neurosciences Cognitives, INSERM Unit 960, Département d'Etudes Cognitives, Ecole Normale Supérieure, PSL Research University, 75005 Paris, France, valentin.wyart@ens.fr christopher.summerfield@psy.ox.ac.uk.
Abstract:
Perceptual decisions occur after the evaluation and integration of momentary sensory inputs, and dividing attention between spatially disparate sources of information impairs decision performance. However, it remains unknown whether dividing attention degrades the precision of sensory signals, precludes their conversion into decision signals, or dampens the integration of decision information toward an appropriate response. Here we recorded human electroencephalographic (EEG) activity while participants categorized one of two simultaneous and independent streams of visual gratings according to their average tilt. By analyzing trial-by-trial correlations between EEG activity and the information offered by each sample, we obtained converging behavioral and neural evidence that dividing attention between left and right visual fields does not dampen the encoding of sensory or decision information. Under divided attention, momentary decision information from both visual streams was encoded in slow parietal signals without interference but was lost downstream during their integration as reflected in motor mu- and beta-band (10-30 Hz) signals, resulting in a "leaky" accumulation process that conferred greater behavioral influence to more recent samples. By contrast, sensory inputs that were explicitly cued as irrelevant were not converted into decision signals. These findings reveal that a late cognitive bottleneck on information integration limits decision performance under divided attention, and places new capacity constraints on decision-theoretic models of information integration under cognitive load.
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