The study of the functional connectome, which maps the functional connections between different brain regions, has provided valuable insights through various advanced analysis techniques developed over the years.
Neural networks, inspired by the brain's architecture, have achieved notable success in diverse applications but are often noted for their lack of interpretability.
A novel approach is proposed in this paper to bridge neural networks and human brain functions by leveraging brain-inspired techniques.
The approach enhances the interpretability of neural networks, providing a deeper understanding of their underlying mechanisms.