5 research outputs found
Task setup and analysis of walking trajectory.
<p>a) Scheme of the experimental setup with the spatial arrangement of the three operating areas (M: model, W: workspace, R: resource area, S: start and end point of a subjects' trajectory) for the two distance conditions (black boxes: far distance condition, gray boxes: near distance condition). b) Example of a subject's single trial trajectory in the long distance and complex pattern condition. Temporal course is coded with a gray-scale gradient. b) Relevant sub-strategies (together with their names) and their demand on WM from low to high usage. The W-M-W sub-strategy was applied as ‘control’ strategy without any block operation. ‘Other’ denotes all remaining sub-strategies which had individual frequencies of occurrence below 2% (for a detailed explanation see section ‘walking sub-strategies’).</p
Task performance: error rate and overall response time.
<p>a) Box-Whisker plot of proportion of errors made during copying the ten simple patterns (left) and the ten complex patterns (right) for the far and the near distance conditions. Black boxes display the pattern errors: the proportion of false on all patterns (n = 10) averaged over subjects of the respective group. White boxes display the block errors: the proportion of false blocks on all blocks in all ten patterns (n = 6 blocks×10 patterns = 60) averaged over subjects of the respective group. b) Box-Whisker plot of response time to complete a single trial averaged over all subjects of the respective group for the simple (left) and complex (right) pattern situations and for the far (black boxes) and near (gray boxes) distance conditions. Statistical effects (post-hoc analyses) are presented for each pattern complexity/distance combination (<sup>★</sup>p<.05; <sup>★★</sup>p<.01; <sup>★★★</sup> p<.001).</p
Proportion of walking sub-strategies.
<p>Box-Whisker plot of proportion of walking sub-strategies used by subjects during copying the simple patterns (left) and the complex patterns (right) averaged over all subjects of the respective group. Black boxes display the frequencies of walking sub-strategies for the far distance condition and gray boxes these for the near distance condition. Post-hoc analyses are calculated for ‘low-memory’ and ‘high-memory’ referring the proportion of walking sub-strategies between far and near and simple and complex pattern conditions (<sup>★</sup>p<.05; <sup>★★</sup>p<.01; <sup>★★★</sup> p<.001; n.s. not significant). The characteristics of all individual sub-strategies are explained in detail in the results chapter (see section ‘walking sub-strategies’).</p
Sub-strategy characterization.
<p>Characterization of all sub-strategies used by subjects for the purpose of copying a block regarding the involvement of memory (M: model, W: workspace, and R: resource area). Each sub-strategy is given a name which is used throughout the manuscript.</p
Linear cost optimization.
<p>Experimental data for a) costs for memorization (i.e., duration of 1st model visit) with power function fits for simple (dashed line) and complex (dotted line) patterns, b) costs for acquisition (i.e., overall time for transitions) with linear regression lines for near (gray) and far conditions (black), and c) total time costs (i.e., overall response time; regressions indicate quadratic functions). All data are shown as a function of the ratio between ‘high-memory’ and ‘low-memory’ sub-strategies. d) Model: Total costs are divided in costs for memorization (C<b><sub>Me</sub></b>) and acquisition (C<b><sub>Ac</sub></b>). If more information is processed at each model visit (i.e., if the task is solved with fewer visits), memory costs increase while acquisition costs decrease. These individual costs vary also with the experimental conditions for walking distance (near and far) and pattern complexity (simple and complex). Total costs for the complex/far condition are depicted as the sum of the according individual cost curves (blue line), leading to an optimum of processed information per model visit at point <i>b</i>. The location of each optimum for the four experimental groups is indicated with <i>a–d</i>.</p