NNMT

NNMT implements mean-field analyses for large-scale neuronal network models, focusing on the leaky integrate-and-fire neuron model to estimate firing rates, power spectra, and dynamical stability.

Key Features:

• Analytical Estimation: Estimates firing rates, power spectra, and dynamical stability using mean-field theory and linear response approximations.
• Extensibility: Provides an architecture for integrating additional analytical methods beyond the leaky integrate-and-fire neuron model.
• Implementation: Implemented in Python and released as open-source software.

Scientific Applications:

• Reproducing Previous Studies: Enables replication of results from earlier research for validation and comparison.
• Parameter Space Exploration: Supports systematic exploration of parameter spaces to study how parameters influence network behavior.
• Model Mapping: Facilitates mapping and comparison between different neuronal network models and theoretical frameworks.

Methodology:

Applies mean-field theory and linear response approximations to derive analytical estimates of firing rates, power spectra, and dynamical stability.