The cerebellum ranks among the least understood brain structures and for decades was thought to contribute to movement and coordination. But this tiny structure — appropriately nicknamed “the little brain” because it looks like a miniature of the cortex — actually houses about 50% more neurons than the rest of the brain and likely contributes to myriad behaviors.
Neuroscientists are just beginning to challenge the simplistic idea that the cerebellum is only important for coordinated movement. Connections exist between the cerebellum and brain areas involved in higher order cognitive functions like memory, decision-making and goal pursuit. Injury to the cerebellum can lead to deficits in higher order cognition, and in kids, cerebellar injury is associated with a higher risk of autism.
Jessica Verpeut, who will start as an assistant professor of psychology at Arizona State University in January 2021, is one of the neuroscientists working to understand the roles of the cerebellum. She studies brain circuits and mechanisms that contribute to behavior, and wants to know what the cerebellum is doing and why it is so important, especially early in life.
“Usually when studying a neurodevelopmental disorder or a specific behavior, the focus is on a single brain region but often many brain regions or entire circuits contribute to a behavior or are impacted by a disorder. My research looks at whole brain mechanisms, which lets me ask how a brain region like the cerebellum influences other regions to give rise to a behavior or deficit,” Verpeut said.
To study a brain circuit in its entirety, Verpeut uses molecular biology techniques to stain areas of neuronal activity while making the other tissue transparent. In this way, she can visualize the entire brain and map entire neural circuits that were active.
In this 3D image of a brain, light areas identify regions stained with c-Fos, which is a protein that marks neural activity. Image courtesy of Jessica Verpeut.
“Putting our tracer into the cerebellum we can find regions of the neocortex that are active. This type of circuit analysis lets us develop a sense of how the cerebellum sends signals to the rest of the brain,” Verpeut added.
Verpeut also uses machine learning to measure how the cerebellum contributes to brain circuits that are involved in natural behaviors like socializing with others. In these types of experiments, the animal does whatever they want while being filmed. An unsupervised machine learning algorithm identifies movement patterns of the animal and classifies those patterns into distinct behaviors. Verpeut can then use the tracer and imaging techniques to map out brain networks associated with the identified behaviors.
“This technique will let us understand behavior in a whole new way. We do not understand yet how the cerebellum contributes to social behavior, and this method of categorizing behaviors will let us look at group dynamics,” Verpeut said.
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