The second contribution U2 was the estimated rate of prediction error: U 2 = 1 2 p j - m j τ j - τ j - 1 + p j - 1 - m j - 1 τ j - 1 - τ j - 2 (1).
We hypothesize that prefrontal cortex accomplishes this task by continually engaging corrective mechanisms that restore optimal baseline firing rates after prediction error signals are generated.
With the development of HRA, many methodologies are established to analyze human errors, such technique for human error rate prediction (THERP) [12], cognitive reliability and error analysis method (CREAM) [13], human error assessment and reduction technique (HEART) [14], a technique for human error analysis (ATHEANA) [15].
In these models, the update of the probability estimate (in our case, the probability that the target will appear in the cued hemifield) is the product of a fixed learning rate and a prediction error (i.e., the difference between observed and predicted outcome).
From Figure 6, it is clear that using a filter order above 10 does not significantly decrease the coding rate for the prediction error over what is possible with a 10th order filter.
The best mutation rates (the rate at which the prediction error is smallest), the corresponding GC contents, the predicted intron phase distributions, the prediction errors, and the standard deviations for all species are provided in Table 2.
Among these 66 functional modules, the lowest error rate was 32.12%, and the average prediction error rate from 66 functional modules was 36.98%.
We then searched for the best mutation rate (i.e., the rate at which the prediction error is smallest) in the range (-1, +1) using the Brent search algorithm [ 40].
Larger link prediction error rate is modeled through larger false negative rate.
The error rate of the second stage predictor was 2.3 fold lower than the error rate of random predictions (error rate = 0.35, p < 0.001).
