Research News
Do fish know where they are? Our researchers in the Department of Computational Neuroethology have developed a behavioral experiment to test spatial navigation in the tiny translucent fish species, Danionella cerebrum. They demonstrated that adult D. cerebrum move away from bright light sources, a behavior known as negative phototaxis. Using areas of darkness as a reward, the experimenters trained the fish to use abstract visual cues to find this phototactic reward. The fishes’ ability to solve the task degraded as the experimenters removed visual contextual information, which is evidence for landmark-based navigational strategies and an internal cognitive map. This new study, published in Current Biology, sets the foundation for future experiments where brain-wide neuronal activity can be recorded in D. cerebrum to study general neuronal mechanisms underlying spatial navigation in vertebrates.
We know of the heroic migration of salmon during their annual “salmon run” or of the specificity of the clownfish to its anemone home. But how do the brains of fish tell them where they are? To answer this question, Dr. Timothy Lee, a post-doc in the lab of Dr. Kevin Briggman, developed a vision-based behavioral experiment for the small translucent fish, Danionella cerebrum. Listed among the world’s smallest fish and virtually transparent into adulthood, D. cerebrum offers exciting opportunities for the study of neuronal circuits controlling behavior. So far, the navigational abilities of these fish remain largely unexplored.
Drawing inspiration from the Morris Water Maze — a gold standard behavioral assay used to test navigational abilities in rodents — Lee and Briggman designed their own navigation task, but with a new twist for D. cerebrum. A key feature of the original Morris Water Maze, as the name implies, is that water is used as a negative reinforcing stimulus (rats don’t like to swim if they don’t have to), but this wouldn’t work for fish (for obvious reasons). Instead, Lee and Briggman discovered that bright light could be used as a motivator for D. cerebrum — specifically, they preferred dark areas over bright ones. Using a small region of darkness surrounded by light as a phototactic reward, our researchers trained D. cerebrum to associate abstract visual cues with the reward location. “Over time, the fish would learn the location of the reward and prefer to swim there, even if the dark spot was not shown”, says Dr. Timothy Lee.
A key experiment was testing the ability of D. cerebrum to use the environmental visual context: It is one thing to know where you are based off of what you see (e.g., “my house is the red house”), but another strategy is to deduce where you are based off of the surrounding visual context (e.g., “my house is behind the blue house, even though I can’t see it”). By placing visual blockades in the behavioral arena, Lee and Briggman showed that D. cerebrum are sensitive to use the broader environmental visual context while trying to find the reward location, giving behavioral evidence for spatial memory and an internal cognitive map.
The next steps for the team are to combine these behavioral experiments with two-photon calcium imaging to look into the brain of D. cerebrum while it learns and performs the task. These experiments will be directly followed by nanometer-resolution volume electron microscopy to draw a connection between the fish’s brain activity and nanoscale brain anatomy. “Together, this will allow us to piece together, from both the brain function and neuroanatomy, how navigational circuits in Danionella cerebrum operate”, says Dr. Kevin Briggman. The overarching goal of the team is to understand general mechanisms of how a neuronal circuit enables spatial navigation in an adult vertebrate species and if there are conserved circuit motifs that generalize across species.
Article was published online in Current Biology on December 8th, 2023.
Lee and Briggman, Visually guided and context-dependent spatial navigation in the translucent fish Danionella cerebrum, Current Biology (2023)