Citation

Sy JL, Guerin SA, Stegman A, Giesbrecht B. Front. Hum. Neurosci. 2014; 8: 334.

Affiliation

Department of Psychological and Brain Sciences, University of California Santa Barbara, Santa Barbara, CA, USA ; Institute for Collaborative Biotechnologies, University of California Santa Barbara, Santa Barbara, CA, USA.

Copyright

(Copyright © 2014, Frontiers Research Foundation)

DOI

10.3389/fnhum.2014.00334

PMID

24904374

PMCID

PMC4034704

Abstract

The load theory of visual attention proposes that efficient selective perceptual processing of task-relevant information during search is determined automatically by the perceptual demands of the display. If the perceptual demands required to process task-relevant information are not enough to consume all available capacity, then the remaining capacity automatically and exhaustively "spills-over" to task-irrelevant information. The spill-over of perceptual processing capacity increases the likelihood that task-irrelevant information will impair performance. In two visual search experiments, we tested the automaticity of the allocation of perceptual processing resources by measuring the extent to which the processing of task-irrelevant distracting stimuli was modulated by both perceptual load and top-down expectations using behavior, functional magnetic resonance imaging, and electrophysiology. Expectations were generated using a trial-by-trial cue that provided information about the likely load of the upcoming visual search task. When the cues were valid, behavioral interference was eliminated and the influence of load on frontoparietal and visual cortical responses was attenuated relative to when the cues were invalid. In conditions in which task-irrelevant information interfered with performance and modulated visual activity, individual differences in mean blood oxygenation level dependent responses measured from the left intraparietal sulcus were negatively correlated with individual differences in the severity of distraction. These results are consistent with the interpretation that a top-down biasing mechanism interacts with perceptual load to support filtering of task-irrelevant information.


Keywords: Driver distraction;

Language: en