SIMULATED NEURONS
—Actual generated populationLIVE / REFERENCE RECORDING
Where the worm
is right now
Market gradients enter named sensory neurons. The c302 network integrates. Forward and reverse command circuits produce an intent. Every value below comes from the recording now in view.
Loading reference recording…c302 C1 → jNeuroML → NEURON
WORMBRAIN TOKEN / LIVE OBSERVER
Real transactions.
One persistent worm.
The observer follows the WORMBRAIN token on Robinhood Chain. New buys, sells, and price changes become calibrated sensory currents for the persistent c302 model. Command voltages become paper order intent, then the independent risk cage records fill or veto feedback. It has no wallet and cannot place real orders.
Connecting to the WORMBRAIN public token feed. The optional Python worker runs the neural observer.
PUBLISHED OBSERVER TIMELINE
FRAME —T + 00:00— / —
Loading the recorded market and neural state.
RECENT INDEXED TRADES—
RECENT BUYS / SELLS—
PRICE IN GOOGL—
Source: Pons public indexer. Receipt verification and complete transaction coverage are not available.
DECODER STATE—
FORWARD / REVERSE— / —
RIM / RIB—
ASE PATH GAIN—
NEXT PVC / DVA—
RISK / PAPER FILL—
RISK REASONS—
BRAIN TIME—
AVB + PVCAVA + AVD + AVE
Waiting for model identity.
Synthetic markets. Paper fills. Real c302 simulation output. This is not a live animal or a profitable strategy.
COMMAND STATE
—Forward / reverse / pause vectorPAPER EQUITY
—Initial balance: $1,000 fictional USDWORM INTENT
—Awaiting reference dataENVIRONMENT
SYNTH / USD
—Synthetic token · 15-second observations
T + 00:0002:15
LIQUIDITY—
BUY / SELL IMBALANCE—
PRICE IMPACT—
COMMAND CIRCUIT
Forward / reverse / pause
AVB + PVCAVA + AVD + AVE
FORWARD · AVB/PVC—
REVERSE · AVA/AVD/AVE—
RIML / RIMR—
RIBL / RIBR—
ENGINEERED INPUT
Sensory stimulation
ASEL and ASER use published, per-cell synthetic salt-gradient transfer curves. Odor and avoidance inputs use bilateral pairs. These financial mappings remain experimental choices.
INDEPENDENT SAFETY
Risk cage
No live transaction path exists in this build.
HASH-LINKED DECISION CHAIN
Who made the decision?
| TIME | BY WORM | BY RISK CAGE | BY PAPER EXECUTOR | EVENT HASH |
|---|
WHAT IT IS
A real model,
not a metaphor
This laboratory keeps c302’s C1 equations and uses the pinned Cook 2019 hermaphrodite reader from CECT. Calibrated sensory currents enter named cells; the generated network propagates them; a state machine decodes forward, reverse, and pause from public command-cell voltages.
The live worker applies one bounded ASE-to-AIA/AIY plastic gain between episodes and feeds paper fill or veto outcomes back through PVC/DVA-style currents. These are engineered experimental rules, not claims about a living worm’s financial intent.
Inspect upstream c302 ↗WHAT IS NOT REAL, STATED PLAINLY
The parts that
aren’t the worm
- The market senses are designed.Price gradients, flow, liquidity, and impact become bounded currents chosen for this experiment.
- The worm does not understand finance.It has no language, goals, wallet, or concept of a token. The readout is an imposed interpretation of command-neuron activity.
- The browser replays recordings.Bundled files contain model traces already calculated through c302, jNeuroML, and NEURON. Playback is not a browser simulation.
- The executor is paper-only.No order-signing method exists. Fills, fees, slippage, impact, balances, and P&L are fictional and fully auditable.
OPTIONAL / REAL RECOMPUTATION
Connect a reference worker
Local Python + Java runs the actual model. The public site works immediately with recordings; new simulations require a separately hosted worker. No wallet or signing key is used.