ADAM is a whole-brain neural mass modeling framework that aims to represent the effects of aging via dopaminergic modulation, using the power of JAX for efficient computation.
ADAM builds on the work of Gast et al. and Depannemaecker et al., extending neural mass models to incorporate:
- D1 dopaminergic modulation of excitatory AMPA currents
- Dose-dependent dopamine effects across whole-brain networks
- Anatomically-informed connectivity via tractography
The dopamine implementation in ADAM is originally forked from giapre/dopamine_model and adapted for efficient & scalable simulations, bypassing the need for multiprocessing.
- Whole-brain simulation with dopaminergic modulation
- Efficient and scalable integration via JAX
- jax
- numpy
- matplotlib
- pandas
- xarray