| Last Updated:
Creating DOI. Please wait...
Visuospatial bootstrapping (VSB) occurs when memory for verbal material is enhanced via association with meaningful visuospatial information. Sequences of digits are visually presented either in the center of the screen or within a keypad layout in which the digits may be arranged identically to familiar pin pad and mobile phone layouts, or randomly. Recall is consistently higher when digits are presented in the familiar layout. This “bootstrapping” could involve primarily long-term memories, primarily spatial memories, or may depend on both. We manipulated the path complexity of sequences to test whether the VSB effect depends on the quality of spatial representations in conjunction with the familiarity of the spatial layout in two experiments. We consistently observed both VSB effects and path complexity effects on verbal serial recall, but never observed any interaction between these factors, even when articulatory suppression was imposed. Analysis of recall by serial position revealed that the VSB effect was focused on the end-of-list items. Our finding of pervasive path complexity effects on verbal serial recall suggests incidental encoding of spatial path occurs during visually-presented verbal tasks regardless of layout familiarity, confirming that spatial factors can affect verbal recall. However, because similar path complexity effects occurred with familiar and random layouts, the VSB effect cannot be attributed to any unique opportunity to encode spatial paths only afforded by presentation within the familiar layout.
The materials folder contains the editable E-Prime file used to run Experiment 2. Experiment 1 was identical, except that 7-digit lists were used and there was no articulatory suppression.
The Data and Analyses folder contains :
1) vsbPathCrossings.R: This script pre-processed the data, combining the trial data recorded by E-Prime with the responses recorded by the researcher, and calculated dependent variables.
2) vsbXCross.Rdata is the data output by the script in step 1, used in all subsequent analyses.
3) vsbPath_summaryCCM.Rmd contains the analyses described in the manuscript and supplemental error analyses. This markdown-file outputs the .html summary file.
4) vsbPath_summaryCCM.html summarizes the analyses. Code is available in the .Rmd file.
5) readMe_vsbXCross.R lists the contents of each column in the cleaned data frame.
The remaining 8 .Rdata files are the output from the Bayes Factor ANOVAs called in the .Rmd file. If run as written, the .Rmd file will call these saved analyses. You may also uncomment the scripts performing the analyses to re-run them.