ArticleJournal of mathematical neuroscience2017
Symmetries Constrain Dynamics in a Family of Balanced Neural Networks.
Article in Journal of mathematical neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Balancing Stability and Flow in Hippocampal Networks via Inductive Bias and Learned Symmetry Breaking.bioRxiv : the preprint server for biology · 2026Article
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3 authors.
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Abstract
We examine a family of random firing-rate neural networks in which we enforce the neurobiological constraint of Dale's Law-each neuron makes either excitatory or inhibitory connections onto its post-synaptic targets. We find that this constrained system may be described as a perturbation from a system with nontrivial symmetries. We analyze the symmetric system using the tools of equivariant bifurcation theory and demonstrate that the symmetry-implied structures remain evident in the perturbed system. In comparison, spectral characteristics of the network coupling matrix are relatively uninformative about the behavior of the constrained system.
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