While storing information in LTM is the basic step of learning, Paas et al. suggested two other critical mechanisms: schemata acquisition and the transfer of learned procedures from controlled to automatic processing [ 37].
Among the reasons suggested for this gap in theoretical knowledge and skills are inadequate training methods, insufficient practice of learned procedures due to lack of equipment [ 35], inability to delegate tasks [ 29, 34, 45, 49], and large variations in clinical protocols [ 45].
To enable a fair comparison, the data samples are sparse-coded using OMP under the learned dictionary for both algorithms after the learning procedure, these implementations lead to approximate patches with reduced noise { b ̃ 1, b ̃ 2, ⋯, b ̃ 6 2 0 0 1 }.
Single pulse-induced motor evoked potentials (MEPs) obtained by stimulation above the left hemisphere were recorded from the first dorsal interosseus muscle of the right hand prior to and after the learning procedure while subjects listened passively to the learned melodies, unknown melodies, and to white noise.
This function is in many respects the reverse of the learning procedure shown in Fig. 10: a population-coded object identity (see Fig. 3), the search cue, is specified and activation is propagated backwards through the system-level network using Eq. 4, the search cue and the learned reverse weight matrices.
This is not to deny that some secondary processes (e.g., awareness of feelings in the generation of behavioral choices) cannot be evaluated in animals with sufficiently clever behavioral learning procedures, as with place-preference procedures and the analysis of changes in learned behaviors after one has induced re-valuation of incentives.
To quantify the variability of the learned metrics, this procedure was repeated 30 times for each of the 18 groups by using different random training samples.
Communication tends to be envisaged as a series of learned prototypical 'skills' or procedures for accomplishing clinical tasks rather than as a dynamic interaction that emerges moment-by-moment, shaped by every interactional nuance along the way.
Simulation results show that the set of learned actions may efficiently perform the construction procedures without resulting in conditions which prevent the fulfillment of the assembly procedures.
However, unlike some learning techniques, such as Artificial Neural Networks (ANNs), GP does not have a principled procedure for changing parts of a learned structure based on that structure's performance on the training data.
