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Multimodal mossy fiber input and its role in infor.. (MULTIMOSSY)
Multimodal mossy fiber input and its role in information processing in the cerebellar granule cell layer
(MULTIMOSSY)
Date du début: 1 sept. 2013,
Date de fin: 31 août 2015
PROJET
TERMINÉ
Synaptic connectivity within and between neurons in brain networks determines the flow of information, how signals are combined and how they are transformed. However, our understanding of information processing in brain networks remains poor. The cerebellar cortex is an attractive model to study network processing because it consist of relatively few, well defined cell types and a relatively simple structure. The cerebellum is involved in motor coordination, and the maintenance of balance. It receives both sensory and motor inputs and integrates this information to perform its function. However, at the cellular level, the specific connectivity of mossy fibres (Mfs; the major input to the cerebellar cortex) and their integration is uncertain. This proposal focuses on Mfs arising from different precerebellar nuclei conveying both sensory information and motor command signals. Mfs contact Golgi cells (GoCs) and granule cells (GCs) in the cerebellar granule cell layer (GCL). However, the connectivity rules, and thus the integration of different Mf inputs onto these cells remain poorly understood. To tackle this question, I propose a multidisciplinary approach based on electrophysiology, optogenetics, 2-photon microscopy and network modelling. I will describe the functional connectivity between Mfs and GoCs and GCs by infecting distinct precerebellar nuclei with Channelrhodopsin (ChR)-expressing adeno-associated viruses to label and activate Mfs. I will measure the synaptic weight and plasticity of these connections. Using variants of ChR activated by distinct wavelengths, I will examine whether individual GoCs and GCs receive multimodal information from distinct nuclei. The results will be included in a detailed 3D network of the GCL and spatio-temporal dynamics and processing by the network will be investigated. This work will provide an important conceptual advance in our understanding of information processing in a major cortical structure in the mammalian brain.
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