We will discuss these attentional interpretations in Section Studies on the relation between auditory attention and prediction, where interactions between prediction and attention mechanisms will be considered.
Furthermore, do these areas show a response profile across cue outcome combinations that reflects a match between prediction and outcome or rather a prediction-error response?
These include: (1) a hierarchical organisation with (2) reciprocal connections between areas (conveying predictions and prediction errors) that are (3) divergent (because a cause has multiple consequences) and (4) functionally asymmetrical.
Comparison of the modelling results shows a large scatter and considerable disparity among the predictions, and between predictions and experimental measurements.
The stratification is optimized by a novel method (Ospats), an iterative procedure that re-allocates grid points to strata on the basis of pairwise differences between predictions and covariances of prediction errors.
For those species with sufficient data to assess the fit between predictions and observations, the correspondence between model predictions and observations was extremely close (examples given in Fig. 4).
Our factorial design enabled us 1) to characterize changes in neurophysiological responses due to learned associations that were incidental to behavior, and 2) to investigate whether activity in specific brain areas, and the connection strengths amongst them, reflected a match between predictions and outcome or prediction errors, respectively.
Each partition yields a point estimate of prediction accuracy (e.g., correlation between predictions and phenotypes).
Prediction accuracy in GS usually is assessed using the sample correlation between predictions and phenotypes.
In evaluating predictions, we focused on the association between predictions and TSRs or gene starts.
