Categorical encoding of decision variables in orbitofrontal cortex
Fig 4
Silhouette comparison of clustering algorithms on synthetic categorical data.
Synthetic data consist of firing rates from a total of 400 simulated cells representing the variables chosen value, offer value A, offer value B and chosen juice (100 cells each). Independent Gaussian noise with a standard deviation of 0.25 and a mean given by the variable rates was used to simulate the activity of a cell. Each color corresponds to one cluster. Clustering algorithms were Mini-Batch k-means (A), Spectral Clustering (B), Ward (C), Agglomerative Clustering (D), Birch (E) and Spherical k-means (F).The number of clusters was fixed to 4.