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Updated: Jun 24, 2026

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Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control
Published on: July 5, 2015
Symbolic control of attention: tracking its temporal dynamics
Bernhard Hommel1, Elkan G Akyürek
1Leiden University, Leiden, The Netherlands. hommel@fsw.leidenuniv.nl
Attention, Perception & Psychophysics
|March 24, 2009
Summary
Task-irrelevant spatial symbols disrupt attentional control, delaying responses and increasing errors. This demonstrates that symbolic meanings can automatically bias attention, challenging current control theories.
Area of Science:
- Cognitive Psychology
- Neuroscience
- Attention Studies
Background:
- Attentional control is crucial for information processing.
- The influence of task-irrelevant stimuli on attention is a key area of research.
- Symbolic stimuli can carry spatial meanings that may interact with attentional processes.
Purpose of the Study:
- To investigate the temporal dynamics of how symbols with irrelevant spatial meanings affect attentional control.
- To determine if task-irrelevant symbolic cues can bias top-down attentional control.
- To challenge existing theories of attentional control.
Main Methods:
- Three experiments were conducted using parallel letter streams.
- Participants identified letters in a target stream, cued by colored arrows indicating either the correct or incorrect stream.
- Response times and error rates were measured to assess attentional control.
Main Results:
- Incompatible arrows (pointing away from the target stream) significantly delayed letter selection.
- Participants made more errors when presented with incompatible symbolic cues.
- Even with advance cueing, incompatible symbols continued to impede target selection.
Conclusions:
- The irrelevant spatial meaning of symbols can penetrate and bias attentional top-down control.
- These findings suggest a more automatic influence of symbolic meaning on attention than previously theorized.
- Existing attentional control theories may need revision to account for these automatic biases.
