Simulation Engine
139,000 neurons on a laptop, from first principles. The simulation engine assembles anatomy (parcellation), connectivity (edge lists), and physiology (cell and synapse models) into a running whole-brain LIF simulation — no Brian2, no NEST, just pure NumPy. Lesson 11 — Whole-Brain LIF Simulation The simulation uses the Shiu et al. formulation: current-based LIF with exponential synaptic conductances, sparse connectivity matrix, and vectorised Euler integration. Key design choices: Pure NumPy — no external simulator dependency; every equation is visible and modifiable Sparse matrices — scipy.sparse CSR format for the 50M-synapse connectivity Stimulus protocols — current injection, optogenetic activation, sensory input patterns Analysis tools — raster plots, firing rate histograms, population synchrony measures Lesson 15 — Brunel Phase Diagram Where does the mushroom body sit in dynamical regime space? The Brunel (2000) framework classifies networks by two axes: synchrony (synchronous vs. asynchronous) and balance (excitation-dominated vs. inhibition-stabilised). By varying external drive and inhibitory gain, we map the MB’s operating point. ...