ArticleFrontiers in computational neuroscience2022
Mean-field based framework for forward modeling of LFP and MEG signals.
Article in Frontiers in computational neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed.
- A spatially discretized convolutional neural mass model for studying meso-scale spatio-temporal transformations in the rat hippocampus.Research square · 2026Article
- A computational approach to evaluate how molecular mechanisms impact large-scale brain activity.Nature computational science · 2025Article
- On the validity of electric brain signal predictions based on population firing rates.PLoS computational biology · 2025Article
- A multi-scale study of thalamic state-dependent responsiveness.PLoS computational biology · 2024Article
- Break-up and recovery of harmony between direct and indirect pathways in the basal ganglia: Huntington's disease and treatment.Cognitive neurodynamics · 2024Article
- Article
- Multiscale modeling of neuronal dynamics in hippocampus CA1.Frontiers in computational neuroscience · 2024Article
- Modeling the relationship between neuronal activity and the BOLD signal: contributions from astrocyte calcium dynamics.Scientific reports · 2023Article
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5 authors.
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Abstract
The use of mean-field models to describe the activity of large neuronal populations has become a very powerful tool for large-scale or whole brain simulations. However, the calculation of brain signals from mean-field models, such as the electric and magnetic fields, is still under development. Thus, the emergence of new methods for an accurate and efficient calculation of such brain signals is currently of great relevance. In this paper we propose a novel method to calculate the local field potentials (LFP) and magnetic fields from mean-field models. The calculation of LFP is done
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