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Is Attentional Resource Allocation Across Sensory Modalities Task-Dependent?

期刊

ADVANCES IN COGNITIVE PSYCHOLOGY
卷 13, 期 1, 页码 83-96

出版社

UNIV ECONOMICS & HUMAN SCIENCES WARSAW
DOI: 10.5709/acp-0209-2

关键词

attentional resources; load theory; multiple object tracking; attentional blink; multisensory

资金

  1. ERC-AdG [269716 - MULTISENSE]
  2. [H2020 - H2020-FETPROACT-2014 611321 - socSMCs]

向作者/读者索取更多资源

Human information processing is limited by attentional resources. That is, via attentional mechanisms, humans select a limited amount of sensory input to process while other sensory input is neglected. In multisensory research, a matter of ongoing debate is whether there are distinct pools of attentional resources for each sensory modality or whether attentional resources are shared across sensory modalities. Recent studies have suggested that attentional resource allocation across sensory modalities is in part task-dependent. That is, the recruitment of attentional resources across the sensory modalities depends on whether processing involves object-based attention (e.g., the discrimination of stimulus attributes) or spatial attention (e.g., the localization of stimuli). In the present paper, we review findings in multisensory research related to this view. For the visual and auditory sensory modalities, findings suggest that distinct resources are recruited when humans perform object-based attention tasks, whereas for the visual and tactile sensory modalities, partially shared resources are recruited. If object-based attention tasks are time-critical, shared resources are recruited across the sensory modalities. When humans perform an object-based attention task in combination with a spatial attention task, partly shared resources are recruited across the sensory modalities as well. Conversely, for spatial attention tasks, attentional processing does consistently involve shared attentional resources for the sensory modalities. Generally, findings suggest that the attentional system flexibly allocates attentional resources depending on task demands. We propose that such flexibility reflects a large-scale optimization strategy that minimizes the brain's costly resource expenditures and simultaneously maximizes capability to process currently relevant information.

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