Modeling code accompanying the ENeuro paper entitled "Neurodynamic Evidence Supports a Forced-Excursion Model of Decision-Making under Speed/Accuracy Instructions"
Matlab code (developed using 2015-2017 versions) used to fit quantile RT data with several versions of a race (two accumulator) sequential-sampling model, and produce predictions for EEG and TMS MEP signals. This process is fully described in the ENeuro paper entitled "Neurodynamic Evidence Supports a Forced-Excursion Model of Decision-Making under Speed/Accuracy Instructions." Code is being archived for the purpose of improving methodological transparency. It has not been commented or optimized with a view to use by third parties. For TMS/MEP data, the final part of the processing pipeline (re-scaling the predicted signal magnitude to match MEP data) will not run, as full MEP data are not included here. Please contact the authors of the paper for further information.
Funding
Leverhulme Trust Research Project Grant (RPG-2014188)