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Code conflict in an event file task is reflected by aperiodic neural activity.

Jimin Yan1, Lorenza Colzato, Bernhard Hommel

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Aperiodic electroencephalography (EEG) activity, specifically the aperiodic exponent, may indicate code conflict. Lower exponents suggest increased neural noise and impaired decision-making during conflicting stimuli.

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Area of Science:

  • Cognitive Neuroscience
  • Computational Neuroscience

Background:

  • Code conflict arises from overlapping stimulus and response features.
  • Event file theory suggests combined features are stored and retrieved.
  • Aperiodic electroencephalography (EEG) reflects neural activity dynamics.

Purpose of the Study:

  • To investigate the relationship between aperiodic EEG activity and code conflict.
  • To determine if aperiodic EEG can serve as a neural marker for code conflict.

Main Methods:

  • Analysis of EEG and behavioral data during an event file task.
  • Quantification of aperiodic activity using the fitting oscillations & one-over-f algorithm.
  • Examination of the aperiodic exponent and its correlation with behavioral outcomes.

Main Results:

  • A partial-repetition cost effect was observed behaviorally.
  • The aperiodic exponent was lower for partial repetitions, indicating increased cortical noise.
  • This effect showed a sensorimotor scalp distribution.

Conclusions:

  • The aperiodic exponent shows potential as a neural marker for code conflict.
  • Findings suggest a link between neural noise, excitatory/inhibitory balance, and decision-making under conflict.