ArticlePLoS computational biology2016
Identifying Anatomical Origins of Coexisting Oscillations in the Cortical Microcircuit.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Article
- Building on models-a perspective for computational neuroscience.Cerebral cortex (New York, N.Y. : 1991) · 2025Article
- State modulation in spatial networks with three interneuron subtypes.Science advances · 2025Article
- Untangling stability and gain modulation in cortical circuits with multiple interneuron classes.eLife · 2025Article
- Reconciliation of weak pairwise spike-train correlations and highly coherent local field potentials across space.Cerebral cortex (New York, N.Y. : 1991) · 2024Article
- Model-agnostic neural mean field with a data-driven transfer function.Neuromorphic computing and engineering · 2024Article
- Model-Agnostic Neural Mean Field With The Refractory SoftPlus Transfer Function.bioRxiv : the preprint server for biology · 2024Article
- Metamodelling of a two-population spiking neural network.PLoS computational biology · 2023Article
- NNMT: Mean-Field Based Analysis Tools for Neuronal Network Models.Frontiers in neuroinformatics · 2022Article
- Comprehensive characterization of oscillatory signatures in a model circuit with PV- and SOM-expressing interneurons.Biological cybernetics · 2021Article
- NetPyNE Implementation and Scaling of the Potjans-Diesmann Cortical Microcircuit Model.Neural computation · 2021Article
- Correlation Transfer by Layer 5 Cortical Neurons Under Recreated Synaptic InputsThe Journal of neuroscience : the official journal of the Society for Neuroscience · 2019Article
- Macroscopic phase resetting-curves determine oscillatory coherence and signal transfer in inter-coupled neural circuits.PLoS computational biology · 2019Article
- Article
- Visual physiology of the layer 4 cortical circuit in silico.PLoS computational biology · 2018Article
- A multi-scale layer-resolved spiking network model of resting-state dynamics in macaque visual cortical areas.PLoS computational biology · 2018Article
- Computational Neuroscience: Mathematical and Statistical Perspectives.Annual review of statistics and its application · 2018Article
- Reproducible Neural Network Simulations: Statistical Methods for Model Validation on the Level of Network Activity Data.Frontiers in neuroinformatics · 2018Article
- Toward Rigorous Parameterization of Underconstrained Neural Network Models Through Interactive Visualization and Steering of Connectivity Generation.Frontiers in neuroinformatics · 2018Article
- Bistability and up/down state alternations in inhibition-dominated randomly connected networks of LIF neurons.Scientific reports · 2017Article
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3 authors.
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Abstract
Oscillations are omnipresent in neural population signals, like multi-unit recordings, EEG/MEG, and the local field potential. They have been linked to the population firing rate of neurons, with individual neurons firing in a close-to-irregular fashion at low rates. Using a combination of mean-field and linear response theory we predict the spectra generated in a layered microcircuit model of V1, composed of leaky integrate-and-fire neurons and based on connectivity compiled from anatomical and electrophysiological studies. The model exhibits low- and high-γ oscillations visible in all populations. Since locally generated frequencies are imposed onto other populations, the origin of the oscillations cannot be deduced from the spectra. We develop an universally applicable systematic approach that identifies the anatomical circuits underlying the generation of oscillations in a given network. Based on a theoretical reduction of the dynamics, we derive a sensitivity measure resulting in a frequency-dependent connectivity map that reveals connections crucial for the peak amplitude and frequency of the observed oscillations and identifies the minimal circuit generating a given frequency. The low-γ peak turns out to be generated in a sub-circuit located in layer 2/3 and 4, while the high-γ peak emerges from the inter-neurons in layer 4. Connections within and onto layer 5 are found to regulate slow rate fluctuations. We further demonstrate how small perturbations of the crucial connections have significant impact on the population spectra, while the impairment of other connections leaves the dynamics on the population level unaltered. The study uncovers connections where mechanisms controlling the spectra of the cortical microcircuit are most effective.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.