In the present study, participants trained the NRT before sleep in order to create implicit neural representations of task material and performed a retest session after sleep, as reported in previous sleep studies with the NRT [26], [28].
The novel feature of our experimental design allowed us to isolate the different schema components that consisted of rule-based associations and low-level visual features of the task material, while controlling for various, potentially confounding factors (such as complexity and attentional demands; see Guerin et al., 2012).
Therefore, the schema components consisted of (1) rule-based associations, and (2) low-level visual features of the task material.
Features (i.e., voxels) were transformed into a pattern vector and a linear SVM classifier with a fixed regularization parameter C = 1 was trained to discriminate between schema components that consisted of (1) rule-based associations, and (2) low-level visual features of the task material.
Low-level visual features of the task material were represented in occipital regions, AG, and fusiform gyrus.
We defined the low-level visual features of the task material as a schema component since the visual features are connected to higher-order information (see also our reply to Point 6).
Second, we repeated this procedure and trained a classifier for the low-level visual features of the task material (circle pairs 1 and 2 vs. circle pairs 3 and 4).
Thus, we reasoned that discrimination of low-level visual features should be possible across days and repeated the above analysis using a classifier that discriminated between the low-level visual features of the task material (Materials and methods, Multi-voxel pattern analysis).
Additionally, we discriminated the low-level features (circle pairs 1 and 2 vs. circle pairs 3 and 4) of the task material and showed that also during the transfer test, multi-voxel patterns were mainly represented within occipital regions (Author response image 4).
Other indicators, such as cost per case-mix, highlight the issue of productivity and the imperative of maximizing the outputs produced from a given set of inputs or, alternatively, minimizing the inputs of nursing tasks, materials, and equipment to produce nursing services.
