https://mayalucia.dev/tags/simulation/ Recent content in Simulation on MayaLucIA Hugo -- 0.156.0 en-us Wed, 25 Feb 2026 12:00:00 +0100 https://mayalucia.dev/domains/bravli/simulation/ Wed, 25 Feb 2026 12:00:00 +0100 https://mayalucia.dev/domains/bravli/simulation/ <p>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 &mdash; no Brian2, no NEST, just pure NumPy.</p> <h2 id="lesson-11--whole-brain-lif-simulation">Lesson 11 &mdash; Whole-Brain LIF Simulation</h2> <p>The simulation uses the Shiu <em>et al.</em> formulation: current-based LIF with exponential synaptic conductances, sparse connectivity matrix, and vectorised Euler integration. Key design choices:</p> <ul> <li><strong>Pure NumPy</strong> &mdash; no external simulator dependency; every equation is visible and modifiable</li> <li><strong>Sparse matrices</strong> &mdash; <code>scipy.sparse</code> CSR format for the 50M-synapse connectivity</li> <li><strong>Stimulus protocols</strong> &mdash; current injection, optogenetic activation, sensory input patterns</li> <li><strong>Analysis tools</strong> &mdash; raster plots, firing rate histograms, population synchrony measures</li> </ul> <h2 id="lesson-15--brunel-phase-diagram">Lesson 15 &mdash; Brunel Phase Diagram</h2> <p>Where does the mushroom body sit in dynamical regime space? The Brunel (2000) framework classifies networks by two axes: <strong>synchrony</strong> (synchronous vs. asynchronous) and <strong>balance</strong> (excitation-dominated vs. inhibition-stabilised). By varying external drive and inhibitory gain, we map the MB&rsquo;s operating point.</p>