Choose where to go.
Your controls set the drive going to Brian’s left and right legs. The banana is a destination you can see; nothing in the simulation smells it.
Loading his little world…
You chose a direction. A programmed rhythm coordinated Brian’s legs, and his simulated body responded to forces and to contact with the table. The program doing that coordination is called a controller.
Your controls set the drive going to Brian’s left and right legs. The banana is a destination you can see; nothing in the simulation smells it.
Coupled rhythms carry each leg through a stepping pattern. This is a central pattern generator — a controller built from simplified mathematical rules, not a reconstructed circuit.
NeuroMechFly supplies the anatomically grounded body. MuJoCo computes how that body moves and where it makes contact with the table.
Both are simulated fly bodies, both run on MuJoCo, and both need something to drive them. They are different models built by different groups for different questions — and neither one settles how a fly’s nervous system produces behaviour.
Brian is walking on NeuroMechFly’s body under its programmed rhythms. FlyBrian’s DigiFly interactive view uses flybody, so you can feel the difference between the two for yourself.
In a living fly, movement involves the brain, the limb-coordinating circuits of the ventral nerve cord, and sensory feedback from the body. A controller that walks well has reproduced the behaviour — it has not shown that it reproduced the circuitry. That gap is the interesting part.
FlyBrian is a workspace for building and comparing neural simulations on Janelia connectome releases, inspecting the activity they produce, and investigating the mechanisms behind behaviour. Brian’s afternoon is the front door.
See what FlyBrian isBody model and walking controller adapted from NeuroMechFly (NeLy-EPFL, Apache-2.0), simulated with MuJoCo (Google DeepMind). Pinned versions and the exact changes are recorded in the model notice.