The brain is like a lively orchestra, with different regions working together to produce the symphony of our thoughts and experiences. Scientists have developed mean-field models, which are powerful tools for simulating the activity of large groups of neurons. However, calculating brain signals like local field potentials (LFP) and magnetic fields from these models has been challenging. In this study, researchers propose a novel method to accurately calculate LFP and magnetic fields using mean-field models. They use a kernel method based on unitary LFPs, similar to individual instruments in an orchestra, to estimate the LFP generated by a single axon. They also incorporate the effects of the conducting medium on magnetic fields using current-dipole and volume-conductor models. This innovative approach has been validated using spiking neuronal networks and applied to whole-brain simulations. By providing an efficient way to calculate electric and magnetic fields from mean-field models, this method opens up possibilities for large-scale brain simulations that were previously unattainable. To dive deeper into this exciting research, check out the full article!

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.

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