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Neural codes for space in complex multi-scale environments: Insights from the bat (NEUROBAT)
Start date: Nov 1, 2011, End date: Oct 31, 2016 PROJECT  FINISHED 

Studies of spatial navigation and neural codes for space have followed two parallel tracks over the last 100 years: One research approach was to study animal navigation in the wild over large spatial scales (kilometers); this approach focused on non-mammalian species and on behavioral studies, with hardly any research on the underlying brain mechanisms. The other approach was to study the navigation of mammals (mostly rats) in mazes and small arenas; this approach revealed 'place cells' in the hippocampus, neurons that become active at specific locations; and 'grid cells' in entorhinal cortex – neurons that respond when the animal passes through the vertices of a hexagonal grid spanning the entire environment. However, it is unknown whether place- and grid-cells are relevant at all to large-scale navigation over kilometers. Thus, there is a large gap between the two parallel approaches to studying spatial memory and navigation – both a conceptual gap, and a gap in spatial scale. Here, we propose to bridge this gap, by recording from place cells and grid cells in a flying mammal – the bat – while it moves in 4 different environments of varying sizes, from centimeters to kilometers. We will conduct both standard (tethered) and wireless neural recordings, and will also pioneer the development of a novel sonar-based virtual reality system for studying large-scale navigation. The same neurons will be recorded across different spatial scales, which will allow comparing various neural-coding schemes. These new setups will allow the first testing for the existence of kilometer-sized hippocampal place-fields and entorhinal grids, in bats navigating through naturalistic virtual landscapes; they will also provide rich information on neural codes for 2-D and 3-D space in the mammalian brain. Our innovative project is expected to provide – for the first time – a true understanding of the brain mechanisms of large-scale, realistic navigation in complex 3-D environments.

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