Research Project
10376584
Project Summary / Abstract A fundamental goal in neuroscience is understanding how information is processed in neuronal circuits. However, the immense complexity of most brain networks has been a significant barrier to progress. Neurons are a primary computational component of the brain, yet we do not have a comprehensive list of their types for even the simplest mammalian neuronal circuit. Moreover, a neuron?s function is dependent on how it is connected, yet mammalian neuronal networks consist of billions of cells with trillions of connections. How do we approach such a complex computational system? Recent advances in X-ray microscopy, electron microscopy, and molecular genetic tools have allowed us to begin detailed mapping of neural network anatomy and connectivity. The cerebellum is an excellent system to scale and validate a new platform to systematically reverse engineer a functional neural circuit that is involved in motor control and social behavior. Its basic structure is well ordered, relatively simple and sufficiently studied to have inspired computational models that capture aspects of cerebellar function. However, even the most advanced models are limited by an incomplete characterization of the cell types and their connectivity within the cerebellum. Here, we propose to scale and validate our next-generation X-ray holographic nanotomography (XNH) platform and provide a comprehensive characterization of cerebellar circuitry. We will use tools recently established in our labs to disentangle a circuit that offers the advantages of relative simplicity and a strong starting foundation. These studies will allow us to understand principles of cerebellar circuit and cell type organization, and may help us determine the role of specific cell types in neurodegenerative disorders.
