Afrina Asad Meghla: Modeling and Simulation of Dentate Gyrus Granule Cells: Understanding Aging and Neuronal Excitability

Dentate gyrus granule cells are among the most important neurons in the hippocampus, playing a key role in how the brain forms and separates memories. What makes these cells particularly interesting is how sensitive they are to calcium. Calcium is not just another ion here—it links electrical signals to internal cellular processes, shaping how the neuron responds, adapts, and stores information.

As the brain ages, these neurons do not stay the same. Their structure begins to change, dendrites can shrink, synaptic connections may become less dense, and the distribution of ion channels can shift. At the same time, the internal calcium machinery also evolves. Together, these changes alter how the neuron behaves. Instead of a single factor, neuronal excitability emerges from the interaction of those multiple factors—intracellular infrastructure, dendritic shrinkage, synaptic density, and channel distribution.

Understanding how all of these pieces work together is still a challenge, since many existing models focus on only one aspect at a time. More importantly, there is no way of experimentally measuring how these pieces work together. To address this gap, we built a multi-compartment neuron model using a realistic morphology. The model combines voltage dynamics with intracellular calcium processes. It also enables inhomogeneous behavior across the neuron by assigning region-specific properties and synaptic inputs.

The goal is to understand how aging-related changes work together to influence neuronal excitability and how their interactions may lead to hyperexcitability. This model is currently under development and serves as a framework for exploring these complex interactions, with the aim to answer how aging affects calcium signaling and how to possibly predict and address aging-related dysfunction.