Guidance of spatial attention during associative learning: Contributions of predictability and intention to learn.

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  • Additional Information
    • Source:
      Publisher: Blackwell Country of Publication: United States NLM ID: 0142657 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1540-5958 (Electronic) Linking ISSN: 00485772 NLM ISO Abbreviation: Psychophysiology Subsets: MEDLINE
    • Publication Information:
      Publication: Malden, MA : Blackwell
      Original Publication: Baltimore, Williams & Wilkins.
    • Subject Terms:
      Cues*; Association Learning/*physiology ; Attention/*physiology ; Brain/*physiology ; Space Perception/*physiology ; Visual Perception/*physiology; Adolescent ; Adult ; Electroencephalography ; Evoked Potentials ; Female ; Humans ; Male ; Photic Stimulation ; Reaction Time ; Young Adult
    • Abstract:
      Expectations of an event can facilitate its neural processing. One of the ways we build expectations is through associative learning. Interestingly, the learning of contingencies between events can also occur without intention. Here, we study feature-based attention during associative learning, by asking how a learned association between a cue and a target outcome impacts the attention allocated to this outcome. Moreover, we investigate attention in learning depending on the intention to learn the association. We used an associative learning paradigm where we manipulated outcome predictability and intention to learn an association within streams of cue-target outcome visual stimuli, while stimulus characteristics and probability were held constant. In order to measure the event-related component N2pc, widely recognized to reflect allocation of spatial attention, every outcome was embedded among distractors. Importantly, the location of the target outcome could not be anticipated. We found that predictable target outcomes showed an increased spatial attention as indexed by a greater N2pc component. A later component, the P300, was sensitive to the intention to learn the association between the cue and the target outcome. The current study confirms the remarkable ability of the brain to extract and update predictive information, in accordance with a predictive-coding model of brain function. Associative learning can guide a visual search and shape covert attentional selection in our rich environments.
      (© 2018 Society for Psychophysiological Research.)
    • Contributed Indexing:
      Keywords: N2pc; associative learning; incidental learning; predictive coding; selective attention
    • Publication Date:
      Date Created: 20180325 Date Completed: 20190506 Latest Revision: 20190506
    • Publication Date:
      20231215
    • Accession Number:
      10.1111/psyp.13077
    • Accession Number:
      29572912