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Evidence and Urgency Related EEG Signals during Dynamic Decision-Making in Humans.

Yvonne Yau1, Thomas Hinault2, Madeline Taylor3

  • 1McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montréal, Québec H3A 2B4, Canada.

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
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Summary
This summary is machine-generated.

Urgency signals accelerate decisions by influencing how the brain processes sensory evidence. This study used EEG to show neural signals reflect the combined impact of evidence and urgency, potentially aiding in understanding disorders like addiction.

Keywords:
EEGcentroparietal positivitydecision-makingdrift diffusion modelurgency gating model

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Area of Science:

  • Cognitive Neuroscience
  • Computational Neuroscience
  • Neuroimaging

Background:

  • Decision-making models often assume gradual evidence accumulation to a threshold.
  • An urgency signal, independent of evidence, has been proposed to speed up decisions.
  • Existing human fMRI/EEG studies struggle to separate evidence accumulation from urgency.

Purpose of the Study:

  • To identify neural signals for sensory evidence and decision variables.
  • To test the urgency-gating model of decision-making.
  • To differentiate neural correlates of evidence accumulation and urgency using EEG.

Main Methods:

  • A face-morphing perceptual decision-making task.
  • Electroencephalography (EEG) recordings.
  • Hierarchical Bayesian modeling to analyze neural data.

Main Results:

  • The centroparietal positivity (evoked potential) reflects the computational decision variable.
  • Neural decision signals represent the product of sensory evidence and urgency.
  • Urgency varied across participants, suggesting it may be an individual trait.

Conclusions:

  • EEG can distinguish neural signals for evidence accumulation, decision variables, and urgency.
  • Decision-making is influenced by both sensory evidence and an internal urgency signal.
  • Findings may inform studies of impulse control and addictive disorders.