Neural mass models

…of TMS induced electric fields to neural mass models is still largely unexplored, while previously approached as an arbitrary current pulse [1, 2]. Via multi-scale simulations at the subcellular and neural mass level we study the underlying mechanisms of electromagnetic activation of cortical tissue by TMS. Validation of the coupling model is aided by measurements like E

Neural mass models (NMM) seek to unveil the fundamental principles governing macroscopic neural activity, drawing insights from the brain's intricate and multi-scale structure. The advent of an exact mean-field theory for networks of quadratic integrate-and-fire (QIF) neurons represents a significant leap forward in our comprehension of the link between microscale neural mechanisms and mesoscopic brain activity [1]. This model establishes a robust coupling between two biophysically relevant macroscopic quantities: the firing rate and the mean membrane potential, which collectively drive the ev

…Several models exist for alpha-rhythm generation using neural mass models, including the Jansen-Rit, Moran-David-Friston, Robinson-Rennie-Wright, and Liley-Wright models [1]. Fitting these models traditionally relies on manual parameter tuning or computationally expensive parameter searches, and they rarely account for inter-individual variation. However, there is substantial experimental variability in the propensity for robust oscillatory activity in EEG, e.g., influenced by structur

Firing-rate (FR) or neural-mass models are widely used for studying computations performed by neural populations. Despite their success, classical firing-rate models do not capture spike timing effects on the microscopic level such as spike synchronization and are difficult to link to spiking data in experimental recordings. For large neuronal populations, the gap between the spiking neuron dynamics on the microscopic level and coarse-grained FR models on the population level can be bridged by mean-field theory formally valid for infinitely many neurons. It remains however challenging to exten