Imagine driving a car in a computer game simulator. As you move the wheel, the image on the screen in front of you changes. How much you turn left or right depends on how much you turned the wheel by. Now imagine the rules change and you need to turn the wheel twice as much to experience the same effect. As your brain adapts you will quickly learn to play by the new rules. How does the brain accomplish this?
We investigate this question using a small transparent vertebrate: the larval zebrafish. Just as we sit in front of a monitor and play computer games, a larval zebrafish can temporarily be embedded in jelly and placed in front of a monitor. The tail of the fish is free, so that the fish can still move it as if swimming or turning. In fact, using self-programmed image analysis software, we can turn the tail of the fish into its joystick. If it moves left we can change the image on the screen as if the fish had actually turned left. We can thus create a virtual reality "swim simulator" for the fish. This allows us to change the rules by which the fish's behavior is translated into changes in the monitor in front of it. Through this, we can investigate how the fish learns to deal with new rules with which it interacts with the environment.
How do we do this? A variety of genetic tools allow us to express fluorescent proteins in the neurons of the fish's brain. Under the microscope, the fluorescent proteins light up whenever a neuron is active. This allows us to see the fish's brain activity as it observes the "world" on the monitor, reacts to what it sees, and learns to deal with the new rules. We can literally see how the fish "thinks" and “learns”.
Although we use the analogy to computer games, learning how to play these games (better) is not the focus of our research. Our body needs to learn almost continuously how to do something different depending on whether a previous attempt was successful or not. For example, during growth we need to get used to our new size and strength, after an injury we need to change the way we move, or we refine our movements when learning how to walk, training in sport or practicing an instrument.
The ultimate research aim of our group is thus to understand how sensory input is taken into account by brain circuits while the brain is trying to do something (sensorimotor integration) and how this information is used to improve behavior and performance (motor learning).