Simulated zebrafish and a vision-equipped robotic fish reveal how the body shapes brain circuits
figure — image Most fish use vision to register the world sliding past, detect optic flow speed and direction, and their brains turn these signals into compensatory swimming. Neuroscientists call this stabilizing reflex the optomotor response (OMR), from neural activity imaging.
The retina captures signals of optic-flow direction, central pretectal neurons interpret direction, and spinal nerves drive muscle contractions. The catch is that one cannot easily change the living brain to test how these circuits work. Although advances in imaging now allow detailed recording, and even manipulation, of neurons alongside behavior, rewiring connections to ask what a particular link actually does remains almost impossible in the living, complex animal. A joint team from EPFL (Switzerland), Duke University (USA), and the Instituto Superior Técnico (Portugal) took on this challenge by creating a realistic larval zebrafish simulation and a biomimetic robot, published in Science Robotics. The team found a way to replicate the body and known neural circuit architectures of live zebrafish, first as a physics-based simulation, then as a free-swimming robot that autonomously navigates upstream using vision and these bio-inspired neural circuits. The results revealed the minimal set of neural components needed for the OMR and, more interestingly, showed that this balanced neural circuit allows autonomous upstream navigation even in poor visibility. It also highlighted that the fish’s body and eyes are part of the neural computation. A blueprint from the living fish brain The starting point was work in the Naumann Lab at Duke, where detailed behavioral studies and whole-brain calcium imaging of larval zebrafish exposed to visual stimuli that mimicked riverbed optic flow, paired with circuit modeling, yielded a best-fit wiring diagram of the brain-scale OMR pathways. Drawing on other insights about neural processing in the vertebrate retina and spinal cord, Dr. Xiangxiao Liu and Luca Zunino from the EPFL team used this neural circuit model to develop a neuromechanical simulation, simZFish, that not only recreates the larval fish body, complete with eyes and fins, but also takes this experimentally derived brain blueprint to be the simulation’s brain, opening new paths for neuroscience and brain-inspired robotics. simZFish: a brain you can take apart Built in the physics-based Webots simulator, simZFish reproduces a six-day-old larva at 1:1 scale: a tiny 4 mm body, weighing only 0.3 mg with seven segments, driven by six simulated motors, a head with two sideways-facing cameras for eyes, and realistic water fluid dynamics. With just the right head-to-tail weight balance, the simulated simZFish moves just like real larval zebrafish. Its artificial brain replicates the entire neural circuit found in fish, from light-changing pixels to muscle activation. The pretectum is a visual brain region that contains neurons that receive direct input from the retina, computing motion directions. The artificial retina detects motion and feeds four types of direction-selective ganglion cells, which drive pretectal neurons that integrate and process visual information from both eyes, and downstream hindbrain motor command neurons that set how often the fish swims and which way it turns.
