This is the data and code repository associated with the paper: **Vo, V.A., Sutterer, D.W., Foster, J.J., Sprague, T.C., Awh, E., Serences, J.T. (2021). Shared representational formats for information maintained in working memory and information retrieved from long-term memory. *Cerebral Cortex*, https://doi.org/10.1093/cercor/bhab267**. The paper PDF is available [here](https://academic.oup.com/cercor/advance-article/doi/10.1093/cercor/bhab267/6357181?guestAccessKey=269856a0-0066-4190-9621-c05c93623f54). ### Details about data We are only providing the pre-processed fMRI data here. For access to the raw data or for any other questions, please contact Vy Vo (vy.vo [at] intel [dot] com) or John Serences (jserences [at] ucsd [dot] edu). The data are shared under the CC BY-SA 4.0 license. ### Details about code / analyses The main script here is `wmLTM_allAnalyses.m`. It contains details about all the analyses, in rough order of how they are reported in the manuscript. The one exception is the Bayesian t-tests, which were done in R. The original code in this repository is shared under the GNU Public General License. The majority of the analyses were done in MATLAB 2016b (see `mFiles`). The Bayesian t-tests are performed in R 3.5.3 (see `RFiles`). #### Required MATLAB toolboxes These toolboxes are optionally installed with MATLAB. - System Identification Toolbox - Image Processing Toolbox - Statistics and Machine Learning Toolbox - Wavelet Toolbox - Bioinformatics Toolbox These analysis toolboxes are written by others. Some are included in this repository to ensure reproducibility. - [Circular Statistics Toolbox](https://www.mathworks.com/matlabcentral/fileexchange/10676-circular-statistics-toolbox-directional-statistics) by Philipp Berens. See more in the paper *Berens, P. (2009). CircStat: A Matlab Toolbox for Circular Statistics, Journal of Statistical Software, 31(10)*. - CO16 by Paul Bays (the version I used is included in `dependencies.zip`). Written for the paper: *Bays PM, Catalao RFG & Husain M. (2009). The precision of visual working memory is set by allocation of a shared resource. Journal of Vision 9(10): 7, 1-11*. - [BCa_bootstrap](https://www.mathworks.com/matlabcentral/fileexchange/69119-bca_bootstrap/) by Jared Van Snellenberg. Also included in `dependencies.zip`. These plotting toolboxes are written by others. `export_fig` and `matlab-epsclean` are solely used to make it easier to edit the `.eps` figures, and are not necessary to generate figure views. However, the versions I used are included in `dependencies.zip`. - [export_fig](https://www.mathworks.com/matlabcentral/fileexchange/23629-export_fig/) [[github](https://github.com/altmany/export_fig)] by Yair Altman - [matlab-epsclean](https://github.com/Conclusio/matlab-epsclean), see github authors at link. - [shadedErrorBar](https://www.mathworks.com/matlabcentral/fileexchange/26311-raacampbell-shadederrorbar) by Rob Campbell #### Required R toolboxes The R code relies on the following toolboxes. - tidyverse - BayesFactor