<p>Each bar represents the group-averaged optimality index for a specific session, for each prior (indexed from 1 to 8, see also <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003661#pcbi-1003661-g002" target="_blank">Figure 2</a>) and cue type, low-noise cues (red bars) or high-noise cues (blue bars). The optimality index in each trial is computed as the probability of locating the correct target based on the subjects' responses divided by the probability of locating the target for an optimal responder. The maximal optimality index is 1, for a Bayesian observer with correct internal model of the task and no sensorimotor noise. Error bars are SE across subjects. Priors are arranged in the order of differential e...
Ideal observer analysis is a fundamental tool for analyzing the efficiency with which a cognitive or...
A psychometric function can be described by its shape and four parameters: position or threshold, sl...
<p>Grouped bar-graphs show the mean (plus standard deviation) of the optimal model order, p<sup>o</s...
<p>Each bar represents the group-averaged optimality index for a specific session, for each prior (i...
<p>Each panel shows the pooled subjects' responses as a function of the position of the cue either f...
Sensory weight for each participant is calculated by the slope of the regression between the true ce...
Our brains process sensory information to infer the state of the world. However, the input from our ...
Human performance in sensorimotor estimation tasks typically shows that: ⋄under Gaussian distributio...
The main task of perceptual systems is to make truthful inferences about the environment. The sensor...
Humans typically make near-optimal sensorimotor judgements but show systematic biases when making mo...
<p>Left: group average correlation between participants' Volterra kernels and the "best <i>k-ToM</i>...
Weighted averaging is said to be optimal when the weights assigned to the cues minimize the variance...
Humans have been shown to combine noisy sensory information with previous experience (priors), in qu...
<p>(a) Observational correlation describes the degree to which observations made by different group ...
<p>Comparison of the mean optimality index computed from the data and the simulated optimality index...
Ideal observer analysis is a fundamental tool for analyzing the efficiency with which a cognitive or...
A psychometric function can be described by its shape and four parameters: position or threshold, sl...
<p>Grouped bar-graphs show the mean (plus standard deviation) of the optimal model order, p<sup>o</s...
<p>Each bar represents the group-averaged optimality index for a specific session, for each prior (i...
<p>Each panel shows the pooled subjects' responses as a function of the position of the cue either f...
Sensory weight for each participant is calculated by the slope of the regression between the true ce...
Our brains process sensory information to infer the state of the world. However, the input from our ...
Human performance in sensorimotor estimation tasks typically shows that: ⋄under Gaussian distributio...
The main task of perceptual systems is to make truthful inferences about the environment. The sensor...
Humans typically make near-optimal sensorimotor judgements but show systematic biases when making mo...
<p>Left: group average correlation between participants' Volterra kernels and the "best <i>k-ToM</i>...
Weighted averaging is said to be optimal when the weights assigned to the cues minimize the variance...
Humans have been shown to combine noisy sensory information with previous experience (priors), in qu...
<p>(a) Observational correlation describes the degree to which observations made by different group ...
<p>Comparison of the mean optimality index computed from the data and the simulated optimality index...
Ideal observer analysis is a fundamental tool for analyzing the efficiency with which a cognitive or...
A psychometric function can be described by its shape and four parameters: position or threshold, sl...
<p>Grouped bar-graphs show the mean (plus standard deviation) of the optimal model order, p<sup>o</s...