Spatial learning, a sculptor of networks
Neurocentre Magendie (Bordeaux, France)
During embryonic development, neuronal activity sculpts neuronal networks. Indeed, after an initial overproduction of neurons and contacts, regressive events will stabilize a particular set of contacts among many, thereby sculpting the precise circuits that are crucial for a given function. We will show that similarly to this selective stabilization process, neuronal networks are sculpted during learning. Indeed, the adult dentate gyrus has the peculiarity to produce new neurones throughout the life of an individual. This region is crucially involved in memory and increasing evidence suggests that the addition of adult-born neurons contribute to memory processes. We will show that spatial learning regulates homeostatically the number of new neurons and shapes the dendritic arbor of the set of new neurons stabilized by learning. This "epigenetic" specification of neo-neonetworks are long lasting, depend upon the level of cognitive demand and NMDA receptors. Altogether, these results showed that in addition to remodelling pre-exiting networks, learning sculpts novel networks. In the search for the structural changes underlying long-term memory, these findings highlight that shaping neo-networks is important in forming spatial memories.