Chang Li: Computation by cerebellar cortex astrocytes during reward learning

The basic computational unit of the brain has long been defined as the neuron. However, mounting evidence suggests that other cells, especially astrocytes, also perform computations. Here, we demonstrate that cerebellar astrocytes decompose norepinephrine input into slow and fast Ca²⁺ activities through differential adrenergic receptor engagement. During reward learning in mice, these slow and fast activities selectively target and modulate distinct synaptic pathways. Causal manipulations reveal that fast α2-adrenergic signals govern event-triggered responses and reinforcement learning, whereas slow α1-adrenergic signals maintain behavioral states and coordinate transitions. Remarkably, an actor-critic neural network trained on a similar sequence task spontaneously recapitulates these multitemporal dynamics, suggesting that astrocytes implement critic-like computations that evaluate states and modulate neuronal learning. Chang Li earned his bachelor's in chemistry with a minor in biology from Truman State University. As an undergraduate, he joined Dr. Brett Berke's lab, using Drosophila as a model to study the role of Cyclophilin in larval crawling behavior. In 2021, he joined Dr. Wei Li and Dr. Lucas Pozzo-Miller's lab at the University of Alabama at Birmingham to pursue his PhD in neuroscience. Building on the finding that cerebellar astrocyte activities are strongly correlated with reward behaviors, his thesis research explores the computational roles of astrocytes.