Table 2. Parameters used for embedding optimization.

Symbol	Value	Settings variable name	Description
Δt	0.005	embedding_step_size	Time step (in seconds) for the discretization of neural spiking activity.
d	1, 2, …, dmax	embedding_number_of_bins_set	Set of embedding dimensions.
Nκ	10	number_of_scalings	Number of linearly spaced values of the exponential scaling κ.
τ1,min	0.005	min_first_bin_size	Minimum bin size (in seconds) of the first past bin.
Δκmin	0.01	min_step_for_scaling	Minimum required difference between two values of κ.
p	0.05	bbc_tolerance	Tolerance for the acceptance of estimates for BBC.
-	False	cross_validated_optimization	Is cross-validation used for optimization or not.
-	250	number_of_bootstraps_R_max	Number of bootstrap samples used to estimate ${\sigma }_{{\widehat{R}}_{\text{max}}}$.
l	1/rΔt	block_length_l	Block length used for blocks-of-blocks bootstrapping.
-	all	estimation_method	Estimators for which embeddings are optimized (BBC, Shuffling)

To facilitate reproduction, we added the settings variable names of the parameters as they are used in the toolbox [37].