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Spatially embedded recurrent neural networks reveal widespread links between structural and functional neuroscience findings

Computer Science

Spatially embedded recurrent neural networks reveal widespread links between structural and functional neuroscience findings

J. Achterberg, D. Akarca, et al.

Discover the groundbreaking spatially embedded recurrent neural networks (seRNNs) model that uniquely merges artificial systems with biophysical constraints. This research, conducted by Jascha Achterberg, Danyal Akarca, D. J. Strouse, John Duncan, and Duncan E. Astle, unveils how seRNNs embody features akin to primate cerebral cortices, shedding light on structural and functional neuroscience.

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