Our research focuses on the cerebellum, a brain structure that is critical for the control of movements. We are using behavioral, electrophysiological, and computational approaches in combination with the latest molecular-genetic techniques to analyze how the cerebellar circuit is specialized to support motor learning, the process by which movements become smooth and accurate with practice.
Previous, long-standing theories had assumed there that there was a single, common mechanism for all cerebellum-dependent learning. In contrast, we have identified multiple, molecularly distinct components of cerebellum-dependent learning that may be recruited in a combinatorial fashion to support specific learning events. Our dissection of cerebellum-dependent learning into its elemental components will help to elucidate the general principles governing the function of the cerebellum across different behaviors. Moreover, the conceptual and technical groundwork we have laid has positioned us to conduct a systematic and in-depth analysis of how specific molecules, synapses, and neurons influence the computations performed by the cerebellum.
Many diseases of the brain begin at the genetic level, and the available therapies are mainly pharmacological manipulations of molecular signaling pathways. Our progress in understanding how molecular-genetic events influence computation in the brain should lead to the development of more rational therapies. Moreover, a better understanding of how the biological hardware of the brain computes will inform efforts by engineers and computer scientists to improve our quality of life by building computers and robots that better mimic the brain’s abilities.
Christine Guo’s project focuses on the algorithms that our brain circuits utilize for learning and memory. The basic experimental approach is in vivo recording from cerebellar neurons during motor learning in the vestibulo-ocular reflex (VOR). She wants to understand how the error signals that guide learning are encoded in the cerebellum and used to guide the induction of plasticity in the neural circuit controlling this movement
Grace Zhao’s research interest is to determine the computational properties of the neural circuits that allow us to adapt our movements to external or internal changes. Essentially she wants to find the neuronal basis of: “practice makes perfect”. She is combining systems neuroscience approaches to analyze neural circuits with molecular-genetic tools for precisely manipulating specific circuit elements. To this end, she has generated a number of transgenic mouse lines which will enable her to investigate the functional roles of particular cell types in the cerebellum.
The cerebellum is known to play a key role in controlling the timing of movements. Akira Katoh studies the mechanisms for adaptively modifying the timing of the VOR, by using detailed behavioral analysis, genetically-manipulated mice, pharmacological manipulation, and in vivo recording from single neurons in alert mice undergoing learning. His recent findings include the identification of specific molecular signaling pathways that play important roles in timing.
The mechanisms by which synapses alter their strength have been studied mainly in brain slice preparations. Barbara Nguyen’s research interest is to understand how such synaptic plasticity mechanisms are implemented in an intact neural circuit to achieve the behaviorally-relevant experience of learning and memory. To this end, her work includes behavioral analysis of genetically, pharmacologically, and optogenetically-manipulated mice through the course of motor learning.
To maintain their accuracy, movements must be recalibrated whenever sensory or motor processing is altered (for example, by aging or injury). Soon-Lim Shin is using a behavioral approach to analyze which sensory or motor cues guide the calibration of the vestibulo-ocular reflex (VOR). She is also using mice with cell type-specific genetic manipulations to study the role of presynaptic plasticity in motor learning in the VOR.
The dominant hypothesis in the cerebellar field has been that the climbing fiber input to the cerebellar cortex provides the key instructive signal controlling motor learning. However, our recent results suggest that different components of VOR motor learning are mediated by distinct neural processes (see, for example, Kimpo et al, 2005 and 2007). Rhea Kimpo is working to determine: “Which components of learning are controlled by instructive signals carried by the climbing fibers?” To address this question, Rhea uses electrophysiological recordings of single neurons in behaving mice, as well as electrical microstimulation and optogenetic techniques to manipulate the activity of the climbing fiber input to the VOR circuit.