structure-activity-nonlinear-spiking-networks

What problem does it solve?

This framework links neural connectivity structure to collective activity in networks of nonlinear spiking neurons, addressing the limitations of linearization by using diagrammatic fluctuation expansion.

Core Features & Use Cases

• Diagrammatic fluctuation expansion to connect connectome structure with population activity.
• Nonlinear spike response modeling to capture realistic neuron behavior beyond linear approximations.
• Structure-driven activity analysis to infer how connectivity shapes pairwise and higher-order correlations.
• Cell-type aware extensions to study inhibitory and excitatory interactions across neuron classes.
• Use cases include predicting population statistics from connectomes, modeling nonlinear network dynamics, and validating against empirical data.

Quick Start

Define your network connectivity and neuron nonlinearities, then apply the diagrammatic fluctuation expansion to predict population correlations.