ArticleNeuroImage2012
Dynamic causal modeling with neural fields.
Article in NeuroImage, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
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Who cites it
53 citing papers in PubMed.
- Article
- Ephaptic coupling and power fluctuations in depression.bioRxiv : the preprint server for biology · 2025Article
- SPM-30 years and beyond.Cerebral cortex (New York, N.Y. : 1991) · 2025Review
- Phase slips extracted from derivatives of EEG data provide a deeper insight into the formation of cortical phase transitions.Frontiers in integrative neuroscience · 2025Article
- A cortical field theory - dynamics and symmetries.Journal of computational neuroscience · 2024Article
- Decrease in phase slip rates and phase cone structures during seizure evolution and epileptogenic activities derived from microgrid ECoG data.Current research in neurobiology · 2024Article
- Bayesian inference of frequency-specific functional connectivity in MEG imaging using a spectral graph model.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Bayesian inference of a spectral graph model for brain oscillations.NeuroImage · 2023Article
- A multi-layer mean-field model of the cerebellum embedding microstructure and population-specific dynamics.PLoS computational biology · 2023Article
- In vivo ephaptic coupling allows memory network formation.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Multi-modal and multi-model interrogation of large-scale functional brain networks.NeuroImage · 2023Article
- Uncovering the organization of neural circuits with Generalized Phase Locking Analysis.PLoS computational biology · 2023Article
- Bayesian Inference of a Spectral Graph Model for Brain Oscillations.bioRxiv : the preprint server for biology · 2023Article
- Global nonlinear approach for mapping parameters of neural mass models.PLoS computational biology · 2023Article
- Dynamic interactions between anterior insula and anterior cingulate cortex link perceptual features and heart rate variability during movie viewing.Network neuroscience (Cambridge, Mass.) · 2023Article
- Structure-function models of temporal, spatial, and spectral characteristics of non-invasive whole brain functional imaging.Frontiers in neuroscience · 2022Review
- Toward biophysical markers of depression vulnerability.Frontiers in psychiatry · 2022Article
- Computational Models in Electroencephalography.Brain topography · 2022Review
- Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation states.Communications biology · 2021Article
- Noise induced quiescence of epileptic spike generation in patients with epilepsy.Journal of computational neuroscience · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
The aim of this paper is twofold: first, to introduce a neural field model motivated by a well-known neural mass model; second, to show how one can estimate model parameters pertaining to spatial (anatomical) properties of neuronal sources based on EEG or LFP spectra using Bayesian inference. Specifically, we consider neural field models of cortical activity as generative models in the context of dynamic causal modeling (DCM). This paper considers the simplest case of a single cortical source modeled by the spatiotemporal dynamics of hidden neuronal states on a bounded cortical surface or manifold. We build this model using multiple layers, corresponding to cortical lamina in the real cortical manifold. These layers correspond to the populations considered in classical (Jansen and Rit) neural mass models. This allows us to formulate a neural field model that can be reduced to a neural mass model using appropriate constraints on its spatial parameters. In turn, this enables one to compare and contrast the predicted responses from equivalent neural field and mass models respectively. We pursue this using empirical LFP data from a single electrode to show that the parameters controlling the spatial dynamics of cortical activity can be recovered, using DCM, even in the absence of explicit spatial information in observed data.
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Registered trials
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.