Towards a Distributed-Delay Paradigm in Neural Mass Modeling for High-Dimensional Brain Dynamics

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Neural Mass Models (NMMs) are essential tools for exploring the complex interactions among neuronal populations. However, classical models such as the Jansen and Rit NMM (JR-NMM) are constrained by oversimplified modularization and fixed conduction delays. These limitations hinder their ability to accurately represent brain dynamics, simulate neurological disorders (e.g., epilepsy), and model large-scale network interactions. Building on our previous work on Distributed-Delay NMMs (DD-NMMs) (Fig. 1), we now enhance this framework with biologically plausible distributed delays informed by axonal properties. Furthermore, we extend its utility to include sensitivity analyses and integration of realistic physiological mechanisms, such as electrophysiology, neurotransmitters, and chemoreceptor dynamics, enabling multi-modal studies of brain activity (e.g., EEG/MEG and fMRI).