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News/Random matrix theory of sparse neuronal networks with heterogeneous timescales
arxiv
PublishedSeptember 15, 2026 at 4:00 AM

Random matrix theory of sparse neuronal networks with heterogeneous timescales

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arXiv:2512.12767v2 Announce Type: replace-cross Abstract: Training recurrent neuronal networks consisting of excitatory (E) and inhibitory (I) units with additive noise for working memory computation slows and diversifies inhibitory timescales, leading to improved task performance that is attributed

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