Confidence through consensus: a neural mechanism for uncertainty monitoring

Models that integrate sensory evidence to a threshold can explain task accuracy, response times and confidence, yet it is still unclear how confidence is encoded in the brain. Classic models assume that confidence is encoded in some form of balance between the evidence integrated in favor and agains...

Full description

Saved in:
Bibliographic Details
Published in:Scientific reports 2016-02, Vol.6 (1), p.21830, Article 21830
Main Authors: Paz, Luciano, Insabato, Andrea, Zylberberg, Ariel, Deco, Gustavo, Sigman, Mariano
Format: Article
Language:English
Subjects:
631/378/116
631/378/2649/1398
631/378/2649/1409
631/378/3920
Algorithms
Computer Simulation
Consensus
Decision Making
Decision theory
Humanities and Social Sciences
Humans
Models, Neurological
multidisciplinary
Neurosciences
Noise
Perception
Probability distribution
Reaction Time
Science
Uncertainty
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Models that integrate sensory evidence to a threshold can explain task accuracy, response times and confidence, yet it is still unclear how confidence is encoded in the brain. Classic models assume that confidence is encoded in some form of balance between the evidence integrated in favor and against the selected option. However, recent experiments that measure the sensory evidence’s influence on choice and confidence contradict these classic models. We propose that the decision is taken by many loosely coupled modules each of which represent a stochastic sample of the sensory evidence integral. Confidence is then encoded in the dispersion between modules. We show that our proposal can account for the well established relations between confidence and stimuli discriminability and reaction times, as well as the fluctuations influence on choice and confidence.
ISSN:2045-2322
2045-2322
DOI:10.1038/srep21830