Confidence through consensus: a neural mechanism for uncertainty monitoring

Abstract

Models that integrate sensory evidence to a threshold can explain task accuracy, response times and/nconfidence, yet it is still unclear how confidence is encoded in the brain. Classic models assume that/nconfidence is encoded in some form of balance between the evidence integrated in favor and against/nthe selected option. However, recent experiments that measure the sensory evidence’s influence on/nchoice and confidence contradict these classic models. We propose that the decision is taken by many/nloosely coupled modules each of which represent a stochastic sample of the sensory evidence integral./nConfidence is then encoded in the dispersion between modules. We show that our proposal can account/nfor the well established relations between confidence, and stimuli discriminability and reaction times,/nas well as the fluctuations influence on choice and confidence.