ArticlePLoS computational biology2018
Imbalanced amplification: A mechanism of amplification and suppression from local imbalance of excitation and inhibition in cortical circuits.
Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 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
- Gain control of sensory input across polysynaptic circuitries in mouse visual cortex by a single G protein-coupled receptor type (5-HTNature communications · 2024Article
- Plasticity manifolds and degeneracy govern circadian oscillations of neuronal intrinsic properties in the suprachiasmatic nucleus.iScience · 2023Article
- State-Dependent Regulation of Cortical Processing Speed via Gain Modulation.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Article
- Balanced networks under spike-time dependent plasticity.PLoS computational biology · 2021Article
- Nonlinear stimulus representations in neural circuits with approximate excitatory-inhibitory balance.PLoS computational biology · 2020Article
- Spatially extended balanced networks without translationally invariant connectivity.Journal of mathematical neuroscience · 2020Article
- Inference of synaptic connectivity and external variability in neural microcircuits.Journal of computational neuroscience · 2020Article
- Reaction Time Improvements by Neural Bistability.Behavioral sciences (Basel, Switzerland) · 2019Article
- Dynamical modeling of multi-scale variability in neuronal competition.Communications biology · 2019Article
- Emergence of Irregular Activity in Networks of Strongly Coupled Conductance-Based Neurons.Physical review. XArticle
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2 authors.
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Abstract
Understanding the relationship between external stimuli and the spiking activity of cortical populations is a central problem in neuroscience. Dense recurrent connectivity in local cortical circuits can lead to counterintuitive response properties, raising the question of whether there are simple arithmetical rules for relating circuits' connectivity structure to their response properties. One such arithmetic is provided by the mean field theory of balanced networks, which is derived in a limit where excitatory and inhibitory synaptic currents precisely balance on average. However, balanced network theory is not applicable to some biologically relevant connectivity structures. We show that cortical circuits with such structure are susceptible to an amplification mechanism arising when excitatory-inhibitory balance is broken at the level of local subpopulations, but maintained at a global level. This amplification, which can be quantified by a linear correction to the classical mean field theory of balanced networks, explains several response properties observed in cortical recordings and provides fundamental insights into the relationship between connectivity structure and neural responses in cortical circuits.
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