Francesco Poli

This paper benchmarks 16 brain network similarity measures, finding DeltaCon is most accurate for parameter recovery but no measure excels across all criteria.

The paper shows that curiosity and brain-like constraints can generate complex neural architectures and cognitive abilities in artificial networks.

This study introduces a heterochronous generative network model to better capture the spatial and temporal aspects of brain network development, improving model fit and identification of individual differences.