FLYWATT
Browser MaleCNS subset (38,178 neurons, 5.1M synapses); every spike is converted to power and lights a bulb (~6.5 µW).
Neurons are simulated — leaky integrate-and-fire or better — with documented, tuned parameters.
Dispute this rating →The evidence
No evidence, no level.Every LIF constant is declared and commented in one shared parameter file, including membrane time constant, rest, threshold, reset, refractory and synaptic decay.
https://github.com/flywatt-live/watt-the-fly/blob/924204469581e83d283aeacdbd3a27a25b8e6834/src/sim/params.ts#L11-L26Synapse counts are held in a read-only Int16Array and appear in the step loop only as a right-hand-side term accumulating synaptic input.
https://github.com/flywatt-live/watt-the-fly/blob/924204469581e83d283aeacdbd3a27a25b8e6834/src/sim/core.ts#L118-L126The one adaptive per-neuron variable in the integration loop is a slow running mean of that neuron's own synaptic input, subtracted from its drive - intrinsic adaptation, not a synaptic weight.
https://github.com/flywatt-live/watt-the-fly/blob/924204469581e83d283aeacdbd3a27a25b8e6834/src/sim/core.ts#L143-L162Calibration writes fixed scalar constants (background drive, one global synaptic gain, rate range) into the parameter file offline, with the run's date, seed and build recorded.
https://github.com/flywatt-live/watt-the-fly/blob/924204469581e83d283aeacdbd3a27a25b8e6834/src/sim/params.ts#L102-L117
A 38,178-neuron, 5.1M-synapse visual-to-wing-motor subcircuit of MaleCNS v1.0 is run as current-based leaky integrate-and-fire in a Web Worker with every constant declared and commented in one file (20 ms membrane, -65/-50/-70 mV rest/threshold/reset, 2 ms refractory, 5 ms synaptic decay, seeded 0.5-1.5 ms delays), and the bulb's brightness and the wattage figure are computed from the running spike count, so simulated neural activity genuinely drives the output. This is among the best-documented L1s in the batch - the repo ships a verification script that asserts the claims the site makes and reports the looming causal chain neuron type by neuron type. Not L2: the synapse-count weight array is an Int16Array read only on the right-hand side of the conductance accumulation and is never written; the calibration step does adjust a single global synaptic gain, but that is an offline bisection that bakes a fixed constant into params.ts before any run, not plasticity at run time, and the only state that adapts during a run is a per-neuron running mean of its own input, which is intrinsic adaptation rather than a synaptic change. The ~6.5 uW figure is an energy estimate applied to spike counts, using a mammalian ATP-per-spike number the README flags as such.
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