Neuromodulatory system in network science. Comment on "Structure and function in artificial, zebrafish and human neural networks" by Peng Ji et al.

The integration of network science methods with neuroscience research has provided valuable insights into the complex relationship between static network architecture and dynamic behavior. The review article by Ji et al. titled "Structure and Function in Artificial, Zebrafish, and Human Neural Networks" sheds light on the integration of network science and neuroscience research, showcasing the application of network science and artificial intelligence techniques in the analysis of neural data [1]. The study emphasizes the significance of understanding the interplay between network structure and functional dynamics in the human and zebrafish brain through the examination of functional connections and dynamic modeling using topological features. This integration not only equips neuroscientists with valuable tools but also opens up new opportunities for network scientists to contribute to the field of neuroscience.