Effective connectivity predicts distributed neural coding of perceptual decision confidence, uncertainty and speed

Abdoreza Asadpour, KongFatt Wong-Lin

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Abstract

Decision-making is often accompanied by a level of confidence regarding the accuracy of one's decision. Previous studies have indicated neural activity associated with perceptual decision confidence during sensory stimulus presentation. Choice-based reaction time (RT) has been suggested as an indirect but more objective measure of decision confidence – generally faster RT for higher confidence. However, it is unclear whether choice confidence and RT are mediated by distinct neural pathways, and whether their neural correlates are encoded nonlinearly. Within a perceptual decision-making task, we applied fMRI-informed EEG-based effective connectivity analysis via dynamic causal modelling (DCM) on event-related potentials and found the frontoparietal network for fast-vs-slow RT condition to be different from that of high-vs-low confidence rating condition. Furthermore, trial-by-trial DCM analysis predicted cortical layer-based, distributed and nonlinear coding of RT, confidence or uncertainty. Collectively, our study suggests that decision confidence and speed are instantiated by different dynamical networks distributed across cortical layers.
Original languageEnglish
JournalImaging Neuroscience
Early online date2 Jan 2025
DOIs
Publication statusPublished online - 2 Jan 2025

Data Access Statement

Source codes on subset of processed data (for demonstrative purposes) used in our analysis are available at https://github.com/asadpouretal/DCM-confidence. Original data are available in the open dataset (Gherman & Philiastides, 2020).

Keywords

  • perceptual decision confidence
  • reaction time
  • dynamic causal modelling DCM
  • Bayesian model selection
  • event-related potentials ERP

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