Connectome datasets.

For each connectome, we list its number of non-isolated nodes, N, its number of directed edges, E, its density ρ = E/[N(N − 1)], the features of the most compressing model for the connectome, its compressibility ΔL*, the difference in codelengths between the best models with and without motifs, ΔLmotifs, and the reference to the original publication of the dataset. The absolute compressibility ΔL* measures the number of bits that the shortest-codelength model compresses compared to a simple Erdős-Rényi model (Eq (15)). The difference in compression with and without motifs, ΔLmotifs, quantifies the significance of the inferred motif sets as the number of bits gained by the motif-based encoding compared to the optimal motif-free, dyadic model. For datasets where no motifs are found, this column is marked as “N/A”. All datasets are available at https://gitlab.pasteur.fr/sincobe/brain-motifs/-/tree/master/data.