TY - JOUR
T1 - Confidence estimation as a stochastic process in a neurodynamical system of decision making
AU - Wei, Ziqiang
AU - Wang, Xiao Jing
N1 - Publisher Copyright:
© 2015 the American Physiological Society.
PY - 2015/5/6
Y1 - 2015/5/6
N2 - Evaluation of confidence about one’s knowledge is key to the brain’s ability to monitor cognition. To investigate the neural mechanism of confidence assessment, we examined a biologically realistic spiking network model and found that it reproduced salient behavioral observations and single-neuron activity data from a monkey experiment designed to study confidence about a decision under uncertainty. Interestingly, the model predicts that changes of mind can occur in a mnemonic delay when confidence is low; the probability of changes of mind increases (decreases) with task difficulty in correct (error) trials. Furthermore, a so-called “hard-easy effect” observed in humans naturally emerges, i.e., behavior shows underconfidence (underestimation of correct rate) for easy or moderately difficult tasks and overconfidence (overestimation of correct rate) for very difficult tasks. Importantly, in the model, confidence is computed using a simple neural signal in individual trials, without explicit representation of probability functions. Therefore, even a concept of metacognition can be explained by sampling a stochastic neural activity pattern.
AB - Evaluation of confidence about one’s knowledge is key to the brain’s ability to monitor cognition. To investigate the neural mechanism of confidence assessment, we examined a biologically realistic spiking network model and found that it reproduced salient behavioral observations and single-neuron activity data from a monkey experiment designed to study confidence about a decision under uncertainty. Interestingly, the model predicts that changes of mind can occur in a mnemonic delay when confidence is low; the probability of changes of mind increases (decreases) with task difficulty in correct (error) trials. Furthermore, a so-called “hard-easy effect” observed in humans naturally emerges, i.e., behavior shows underconfidence (underestimation of correct rate) for easy or moderately difficult tasks and overconfidence (overestimation of correct rate) for very difficult tasks. Importantly, in the model, confidence is computed using a simple neural signal in individual trials, without explicit representation of probability functions. Therefore, even a concept of metacognition can be explained by sampling a stochastic neural activity pattern.
KW - Decision confidence
KW - Lateral intraparietal cortex
KW - Line-attractor neural model
UR - http://www.scopus.com/inward/record.url?scp=84939794227&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84939794227&partnerID=8YFLogxK
U2 - 10.1152/jn.00793.2014
DO - 10.1152/jn.00793.2014
M3 - Article
C2 - 25948870
AN - SCOPUS:84939794227
SN - 0022-3077
VL - 114
SP - 99
EP - 113
JO - Journal of Neurophysiology
JF - Journal of Neurophysiology
IS - 1
ER -