From Ions to Chaos: exploring a whole-brain modelling framework in the mouse

Abstract

Computational neuroscience offers powerful tools for understanding brain function in both healthy and diseased states. However, detailed data on microscale mechanisms--such as those involved in genetics and pharmacology--are often derived from mouse experiments and further lack integration into whole-brain models. In this work, we bridge microscale ion-channel dynamics and macroscale network behavior by employing the Larter-Breakspear neural mass model on The Virtual Brain platform with a mouse brain connectome. Our simulations reproduced key findings from prior computational studies with the Larter-Breakspear model, demonstrating its cross-species translation to the mouse. This included the emergence of chaotic dynamics and network synchrony as a function of coupling and delay parameters. Furthermore, we demonstrate that Calcium, Sodium, and Potassium-related parameters each critically shape the global dynamic regimes and that the response to external stimuli is highly sensitive to calcium concentrations. This work represents the first integration of the Larter-Breakspear model into a mouse-scale connectome, validating previous results in a new context. In addition, it establishes a framework for a detailed exploration of synchrony, ion dependency, and stimulus reactivity. By linking molecular simulations, genetic data, and mouse electrophysiology, this approach holds promise for mechanistic insights into neuropsychiatric disorders, such as schizophrenia and epilepsy.