Mean-field based framework for forward modeling of LFP and MEG signals

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 via a kernel method based on unitary LFP's (the LFP generated by a single axon) that was recently introduced for spiking-networks simulations and that we adapt here for mean-field models. The calculation of the magnetic field is based on current-dipole and volume-conductor models, where the secondary currents (due to the conducting extracellular medium) are estimated using the LFP calculated via the kernel method and the effects of medium-inhomogeneities are incorporated. We provide an example of the application of our method for the calculation of LFP and MEG under slow-waves of neuronal activity generated by a mean-field model of a network of Adaptive-Exponential Integrate-and-Fire (AdEx) neurons. We validate our method via comparison with results obtained from the corresponding spiking neuronal networks. Finally we provide an example of our method for whole brain simulations performed with The Virtual Brain (TVB), a recently developed tool for large scale simulations of the brain. Our method provides an efficient way of calculating electric and magnetic fields from mean-field models. This method exhibits a great potential for its application in large-scale or whole-brain simulations, where calculations via detailed biological models are not feasible.

Modeling the relationship between neuronal activity and the BOLD signal: contributions from astrocyte calcium dynamics

“…The development of realistic models of the neurovascular coupling is currently of great relevance for the analysis of clinical data 14,67 . Furthermore, the mean-field formalism adopted here provides tools to estimate multiple brain signals such as LFP and MEG 68 . This will give the chance to analyze multimodal experiments, where BOLD imaging is combined with electrical measurements, which is a topic of great interest 14 .…”

Experimental and computational analysis of REM sleep distributed cortical activity in mice

“…The estimate of the LFP signal of each node is computed with a Kernel-based method based on previous work (Telenczuk et al, 2020; Tesler et al, 2022). First demonstrated in a neuron network and then extended to mean-field models, it relates the spiking of neurons to the LFP through efferent synaptic connections.…”

“…The estimate of the LFP signal of each node is computed with a Kernel-based method based on previous work (Telenczuk et al, 2020;Tesler et al, 2022).…”

Connectomes, simultaneous EEG-fMRI resting-state data and brain simulation results from 50 healthy subjects

“…In a follow-up study, Goldman et al 19 used the subject sub-36 to test the AdEx mean-field model on its connectome. Tesler et al 20 used the data of the sub-36 to test a newly proposed method of local field potential (LFP) and magnetoencephalography (MEG) signal forward modeling based on mean-field models. They also used the AdEx model as in 19 .…”