Getting Started with consciousnessModelR

library(consciousnessModelR)

Overview

consciousnessModelR provides simplified simulations for teaching major ideas in consciousness studies.

The package focuses on educational clarity. It does not attempt to measure or produce consciousness.

The central learning question is:

How can different theories of consciousness be represented as simple computational models?

Main ideas

The package includes models inspired by:

Global Workspace Theory
Attention competition
Broadcast dynamics
Information integration
Threshold models of awareness-like processing

A first simulation

sim <- simulate_global_workspace(n_processes = 8, steps = 100, seed = 123)
head(sim)
#>   step process activation winner is_winner broadcast ignited
#> 1    1      P1  0.3920908     P8     FALSE         0    TRUE
#> 2    1      P2  0.7014752     P8     FALSE         0    TRUE
#> 3    1      P3  0.7208877     P8     FALSE         0    TRUE
#> 4    1      P4  0.8383253     P8     FALSE         0    TRUE
#> 5    1      P5  0.9127688     P8     FALSE         0    TRUE
#> 6    1      P6  0.3300235     P8     FALSE         0    TRUE

Plot activation through time

plot_consciousness_sim(sim, x = "step", y = "activation", group = "process")

Apply a threshold

thresholded <- consciousness_threshold(sim, activation_col = "activation", threshold = 0.7)
head(thresholded)
#>   step process activation winner is_winner broadcast ignited threshold
#> 1    1      P1  0.3920908     P8     FALSE         0    TRUE       0.7
#> 2    1      P2  0.7014752     P8     FALSE         0    TRUE       0.7
#> 3    1      P3  0.7208877     P8     FALSE         0    TRUE       0.7
#> 4    1      P4  0.8383253     P8     FALSE         0    TRUE       0.7
#> 5    1      P5  0.9127688     P8     FALSE         0    TRUE       0.7
#> 6    1      P6  0.3300235     P8     FALSE         0    TRUE       0.7
#>   above_threshold threshold_distance
#> 1           FALSE       -0.307909171
#> 2            TRUE        0.001475242
#> 3            TRUE        0.020887668
#> 4            TRUE        0.138325290
#> 5            TRUE        0.212768817
#> 6           FALSE       -0.369976484

Interpretation

In this toy model, several processes compete for access. A process with sufficiently high activation may cross a threshold and become globally broadcast.