brain

A whole connectome running as a leaky integrate-and-fire network on the GPU. Brain.load binds any connectome asset to the package's four lif_* kernels and returns a network; the FruitFlyBrain component is the usual owner, and anything holding the network can step, drive, cut, read out and draw it.

Exports

• M.load(connectomeRef, params?) -> Brain — allocate the network at rest. params overrides any of dtMs, vRest, vThresh, vReset, tauM, tauSyn, refracMs, delayMs, weightMv, gain, minSynapses, traceMs, maxSpikes, seed.
• brain:update(dt) — once a frame: queue the steps dt covers, issue and drain the counter readback.
• brain:step(n) — queue n steps outright.
• brain:select(sel) -> { index } — the neurons a selection names.
• brain:stimulate(sel, hz) / brain:clearStimulation() — Poisson drive.
• brain:silence(sel, on) — ablate or restore.
• brain:watch(name, sel) / brain:unwatch(name) / brain:rates() — read groups out as Hz per neuron.
• brain:activity() — network mean rate, total spikes, dropped spikes, simulated time.
• brain:info(i) — what one neuron is.
• brain:showCloud(opts) / brain:hideCloud() / brain:worldPosition(i) — the instanced neuron cloud.
• brain:setParams(patch), brain:setRunning(on), brain:setTimeScale(x), brain:reset(), brain:ready(), brain:destroy(), brain:describe().

Usage

local Brain = require("~.brain")   -- from inside the package
local brain = Brain.load(asset.resolve("fruitFly.maleCNS", "connectome"), { gain = 0.6 })
brain:watch("MN9", { types = { "MN9" } })
brain:stimulate({ types = { "claw_tpGRN" } }, 100)
-- every frame:
brain:update(dt)
print(brain:rates().MN9)

A selection is { types?, typePrefix?, pattern?, classes?, superclasses?, sides?, excitatory?, indices?, limit? }; every given key must hold.

Notes

• The network is silent until something is driven; a spike always traces back to a stimulus.
• Every GPU buffer is named brain.<id>.<name>; compute.observe() lists them. destroy releases them all.
• The kernels' params are per shader, so two networks on one engine share the model constants the last applyParams wrote.