If the calibration or scaling of an informational variable to a task variable is unique to a particular coupling, transfer of calibration between the two tasks is unlikely.
Previous work has shown that outcome feedback (or knowledge of results) on the magnitude and sign of error aids the learner in enhancing calibration of an informational variable to a task variable (i.e., I t) and T t) in Eq. 1; see, e.g., Cabe & Wagman, 2010; Wagman, McBride & Trefzger, 2008; Withagen & Michaels, 2005).
Some of the z-scores were multiplied by -1, so that the z-scores of all task variables would have the same meaning: A higher z-score was indicative of poor performance or underestimation.
The present findings suggest that such selective gating in the caudate nucleus can occur via a neuronal population code, which allows for independent read-out of all task variables by downstream structures.
Developing new indices that combine different variables is not a trivial task: variables may be qualitative, or measured in different units, and the relationship between primitive components and quality may be ambiguous.
For each genetic marker an association analysis between the task variable and genotype was performed using single-step additive, dominant, and recessive regression models that included age, gender, IQ, and medication status on the day of testing, as covariates.
A genuine demonstration of a rescaling between information and task variables (i.e., presumably, for putting, this task variable is the orientation of the club head at impact) requires that the informational variable is varied (e.g., by manipulating distance between the ball and hole and/or the head position relative to the ball).
Second, the study paralleled tasks to minimize the task variable; however, no evidence of their supposed equivalence was offered.
Significant t-test results, indicating learning effects, emerged for all other fast task variables, except the standard deviation of reaction times in the baseline condition, but for only one go/no-go task variable (commission errors in the slow condition).
For the VR-Colonoscopy task variable Pain again single incidents would lead to very different values, so this variable was left out of the analysis.
The absolute (unstandardised) beta value for the task variable was recorded (these values are hereafter referred to as the unshuffled test statistics).
