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Unbelievably honoured to read Tatiana Engel's (@engeltatiana.bsky.social) wonderfully written Preview on our work "Linking neural manifolds to circtuit structure in recurrent networks" (with @lpezon.bsky.social & @gerstnerlab.bsky.social) in this issue of Neuron www.cell.com/neuron/fullt... 🙏
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In this issue of Neuron, Pezon et al. introduce neural circuit models with flexible connectivity structure that can generate low-dimensional population dynamics with different distributions of single-...
Finding clues to circuit structure in population dynamics and single-neuron selectivity
NEW PAPER. Why do larger networks train better? "Because they contain more candidate *sub*networks that can learn the task" → lottery tickets This popular explanation uses an appealing but misleading metaphor🧵 We propose an intuitive alternative grounded in theory: escape dimensions
1d
Valentin Schmutz
Presenting a poster tomorrow at Cosyne 26: [3-033] Compositional computation via shared latent dynamics in low-rank RNNs. With @avm.bsky.social, we explore how RNNs can re-use the same dynamics across different tasks, and what it implies for their connectivity and neural activity.