ArticleCerebral cortex (New York, N.Y. : 1991)2014
The cell-type specific cortical microcircuit: relating structure and activity in a full-scale spiking network model.
Article in Cerebral cortex (New York, N.Y. : 1991), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 203 papers.
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203 citing papers in PubMed.
- Synaptic-state-dependent plasticity routes learning signals in recurrent circuits.bioRxiv : the preprint server for biology · 2026Article
- Predictive acoustical processing in human cortical layers.Nature communications · 2026Article
- Deep-learning-assisted simulation of a cortical circuit: integrating anatomy, physiology and function.bioRxiv : the preprint server for biology · 2026Article
- Visualization and simulation of full-scale point-neuron circuits via the Neural Circuit Visualizer web platform.Scientific reports · 2026Article
- High-frequency bursts facilitate fast communication for human spatial attention.Nature neuroscience · 2026Article
- Iso-orientation bias of layer 2/3 connections unifies spontaneous, visually and optogenetically driven V1 dynamics.Nature communications · 2026Article
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- Container-based framework for large-scale spiking network simulation.Frontiers in neuroscience · 2026Article
- Building on models-a perspective for computational neuroscience.Cerebral cortex (New York, N.Y. : 1991) · 2025Article
- Layered structure of cortex explains reversal dynamics in bistable perception.Scientific reports · 2025Article
- Biologically grounded neocortex computational primitives implemented on neuromorphic hardware improve vision transformer performance.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Global and local nature of cortical slow waves.iScience · 2025Article
- Simulation of evoked responses to transcranial magnetic stimulation using a multiscale cortical circuit model.bioRxiv : the preprint server for biology · 2025Article
- Cortical networks with multiple interneuron types generate oscillatory patterns during predictive coding.PLoS computational biology · 2025Article
- A simplified model of NMDA-receptor-mediated dynamics in leaky integrate-and-fire neurons.Journal of computational neuroscience · 2025Article
- Excitatory/inhibitory ratio disruption modulates neural synchrony and flow directions in a cortical microcircuit.PLoS computational biology · 2025Article
- State modulation in spatial networks with three interneuron subtypes.Science advances · 2025Article
- Metadata practices for simulation workflows.Scientific data · 2025Article
- A Python toolbox for neural circuit parameter inference.NPJ systems biology and applications · 2025Article
- On the validity of electric brain signal predictions based on population firing rates.PLoS computational biology · 2025Article
143 more citing papers are in PubMed but not listed here.
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2 authors.
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Abstract
In the past decade, the cell-type specific connectivity and activity of local cortical networks have been characterized experimentally to some detail. In parallel, modeling has been established as a tool to relate network structure to activity dynamics. While available comprehensive connectivity maps ( Thomson, West, et al. 2002; Binzegger et al. 2004) have been used in various computational studies, prominent features of the simulated activity such as the spontaneous firing rates do not match the experimental findings. Here, we analyze the properties of these maps to compile an integrated connectivity map, which additionally incorporates insights on the specific selection of target types. Based on this integrated map, we build a full-scale spiking network model of the local cortical microcircuit. The simulated spontaneous activity is asynchronous irregular and cell-type specific firing rates are in agreement with in vivo recordings in awake animals, including the low rate of layer 2/3 excitatory cells. The interplay of excitation and inhibition captures the flow of activity through cortical layers after transient thalamic stimulation. In conclusion, the integration of a large body of the available connectivity data enables us to expose the dynamical consequences of the cortical microcircuitry.
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