In the brain, neurons express information electrically, as series of action potentials. These in turn influence other neurons via divergent synaptic connections. Although we feel we know quite a lot about neurons, action potentials and synapses, this knowledge gives us surprisingly little insight into brain function. It is certainly not possible to recreate sophisticated brain functions by randomly connecting model neurons with realistic synapses and action potentials. We believe that a key piece of missing information is the specific properties of the neural networks supporting this activity. Our group aims to understand the operation and function of one particular brain region, the cerebellum, basing our research upon a multidisciplinary characterization of the neural networks it contains. The cerebellum is involved in the learning and execution of coordinated movements. As a brain structure in which to study the representation and transformation of information, it offers several significant advantages: it has a simple and well-described cellular architecture, we know something about both its (sensory) inputs and (motor) outputs, and several well-understood model behaviors are very strongly linked to the cerebellum. We study cerebellar function using three principal approaches:
- The in vitro characterization of the network, neurons and synapses of the cerebellum, using patch-clamp recording and imaging in slices.
- In vivo recordings of cerebellar activity during behavior, using tetrodes to monitor the behavior of multiple neurons simultaneously.
- Theoretical analysis and numerical modeling (often in collaboration with theoretical physicists).
We believe that the combination of these techniques will lead us to a deeper understanding of cerebellar function and offer insight into the operation of neural circuitry in general.
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