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Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
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Incentive value and spatial certainty combine additively to determine visual priorities.

K G Garner1,2, H Bowman3, J E Raymond3

  • 1School of Psychology, University of Birmingham, Birmingham, UK. getkellygarner@gmail.com.

Attention, Perception & Psychophysics
|October 9, 2020
PubMed
Summary
This summary is machine-generated.

The brain combines incentive value and spatial certainty independently, not multiplicatively, to guide visual attention. This supports an additive model over expected value computations for visual selection.

Keywords:
AttentionExpectationIncentivePredictionReward

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Area of Science:

  • Cognitive Neuroscience
  • Neuroeconomics
  • Visual Attention

Background:

  • The brain integrates incentive value and spatial certainty to guide visual selection.
  • Existing theories propose additive or multiplicative integration models.
  • Discrepancies exist between behavioral and neuroeconomic findings.

Purpose of the Study:

  • To determine how the brain combines incentive value and spatial certainty.
  • To adjudicate between additive and multiplicative integration hypotheses.
  • To test whether expected value computations solely drive attention.

Main Methods:

  • Two experiments using visual search tasks with parametrically manipulated spatial cues.
  • Participants viewed placeholders indicating potential task value.
  • Bayesian model selection was used to analyze performance data.

Main Results:

  • Performance improved with higher incentive value and valid spatial cues.
  • Effects of incentive value and spatial certainty did not interact.
  • The additive hypothesis was strongly supported over the multiplicative hypothesis.

Conclusions:

  • Incentive value and spatial certainty independently influence visual selection.
  • Findings refute theories of expected value computations as the sole driver of attention.
  • The brain employs an additive mechanism for integrating these predictive signals.