ArticleFrontiers in computational neuroscience2018
Criteria on Balance, Stability, and Excitability in Cortical Networks for Constraining Computational Models.
Article in Frontiers in computational neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Nonlinear Dendritic Integration Supports Up-Down States in Single Neurons.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- A layered microcircuit model of somatosensory cortex with three interneuron types and cell-type-specific short-term plasticity.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
During ongoing and Up state activity, cortical circuits manifest a set of dynamical features that are conserved across these states. The present work systematizes these phenomena by three notions: excitability, the ability to sustain activity without external input; balance, precise coordination of excitatory and inhibitory neuronal inputs; and stability, maintenance of activity at a steady level. Slice preparations exhibiting Up states demonstrate that balanced activity can be maintained by small local circuits. While computational models of cortical circuits have included different combinations of excitability, balance, and stability, they have done so without a systematic quantitative comparison with experimental data. Our study provides quantitative criteria for this purpose, by analyzing
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