26 citations · 28 across the 3 of their papers we have counts for
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cs.NE2024★ 1 cited
Spatial embedding promotes a specific form of modularity with low entropy and heterogeneous spectral dynamics
Cornelia Sheeran, Andrew S. Ham, Duncan E. Astle +2
Understanding how biological constraints shape neural computation is a central goal of computational neuroscience. Spatially embedded recurrent neural networks provide a promising…
cs.NE2023★ 1 cited
Building artificial neural circuits for domain-general cognition: a primer on brain-inspired systems-level architecture
Jascha Achterberg, Danyal Akarca, Moataz Assem +3
There is a concerted effort to build domain-general artificial intelligence in the form of universal neural network models with sufficient computational flexibility to solve a wide…