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The computational limitations of balanced networks

The computational limitations of balanced networks

This video was recorded at 5th European Conference on Complex Systems . Computation in neural networks relies crucially on non-linearity. In neural networks in the balanced state the non-linearity of the neuronal transfer function becomes functionally unimportant. The disappearance of this non- linearity strongly limits the computational power of balanced networks. I will show in examples of balanced networks for associative memory how one can try to circumvent this limitation of balanced networks and discuss the problems with these solutions.


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