Graphical User Interface

The BCI Toolbox GUI provides a complete no-code workflow for model fitting, simulation, visualization, and export. It is useful for rapid model checking, batch fitting across participant files, and communicating results with publication-ready figures.

Launch

import bcitoolbox as btb
btb.gui()

Main Workflows

Model fitting

Import one or more CSV files, choose the fitting objective, select one or more decision strategies, estimate parameters, inspect plots, and export results.

Model simulation

Enter parameter values and stimulus conditions to generate model-predicted response distributions. The simulation tools are useful for understanding how priors, likelihood variance, and causal-prior assumptions shape behavior.

Typical Analysis Workflow

  1. Prepare a CSV file with one row per trial.

  2. Open the GUI and select the relevant fitting module.

  3. Import one or more datasets.

  4. Set the simulation count. Use a smaller value, such as 1000, for a quick pilot run and a larger value, such as 10000, for final fitting.

  5. Choose the objective function and decision strategies.

  6. Select free parameters and review bounds.

  7. Run fitting and inspect the output log.

  8. Plot the fitted model against behavioral data.

  9. Save figures, RDMs, predictions, or parameter summaries as needed.

Decision Strategies

ave

Model averaging. The observer weights causal-structure-specific estimates by the posterior probability of a common cause.

sel

Model selection. The observer uses the estimate from the most likely causal structure.

mat

Probability matching. The observer samples a causal structure according to the posterior probability and responds from that structure.

Fitting Objectives

mll

Minus log likelihood. Recommended for discrete response distributions when likelihood-based model comparison is desired.

mr2 or minusr2

Negative squared correlation between model and behavioral response proportions.

sse

Sum of squared errors between model and behavioral response proportions.

emd

Earth mover’s distance, available for selected continuous workflows.

When to Use the 2D GUI

Use 2D GUI Tutorial when each trial contains two stimulus dimensions. For example, a flash-beep experiment may require both numerosity values and temporal offsets. The 2D GUI keeps these dimensions in one model instead of fitting separate one-dimensional analyses.