Spiking Network Model Builder

What problem does it solve?

Assists researchers and engineers in constructing and simulating biologically realistic spiking neural networks by guiding neuron model choice, synaptic dynamics, and network architecture.

Core Features & Use Cases

• Neuron model selection (LIF, EIF, AdEx, Izhikevich, HH) with guidance on when to use each.
• Synapse configuration (AMPA/NMDA/GABA, conductance vs current-based, TM plasticity).
• Network connectivity and E/I balance.
• STDP, BCM, and homeostatic plasticity rules.
• Simulation parameters, validation metrics, and recommended toolchains (NEST, Brian2, NEURON, GeNN).
• Use Case: Design cortical microcircuits or AI-regime networks and compare statistics like firing rates, CV, and synchrony.

Quick Start

Prototype a minimal LIF network with 80/20 E/I balance and run a 1-second simulation.