Start here
BrainlessLab is an experimental Python and Quadrants platform for studying neural reservoirs in declared tasks. Begin with one complete record before designing a study.
Run and inspect one simulation
Run your first simulation walks through installation, a small delayed-cue run and inspection of its saved result. You should finish with a complete record, verified checksums and a task outcome in its native units.
That confirms software execution. It does not establish cognition, learning or biological fidelity.
Choose your next question
- Create a reproducible profile to measure one design across independent trials.
- Compare conditions to test a declared change using matched worlds.
Read the system map when you want to understand how a plan becomes a simulation and a saved result.
Check platform limits for supported models, tasks and backends.
What do the tasks look like?
Task illustration · Scripted diagram, not a recorded simulation.
Does the observer align with a moving stimulus? Outcome: mean cosine of angular error.
Does the paddle intercept approaching balls? Outcome: hit fraction.
How long does the pole remain within bounds? Outcome: world steps survived.
Is one cue retained until go? Outcome: response accuracy.
These four illustrations introduce the physical tasks and delayed cue. Use Choose a task for all ten supported families and the model guide for Falandays and SORN.