One of the grand challenges in the brain sciences is to comprehend the origin of higher-order functions such as thinking, planning, memory, and decision making. Such functions depend strongly on the parts of cortex that have shown the largest expansion and differentiation during mammalian evolution. While many of these functions are still poorly understood, there has been substantial progress in our comprehension of how the brain encodes position. This encoding takes place deep in the cortex - in the hippocampus and the associated entorhinal cortex - far away from sensory inputs and motor outputs. During the past decade we have shown that the entorhinal cortex contains a number of cell types in which position is encoded in various ways. The first cell type to be discovered was the grid cell. Grid cells are cells in the medial entorhinal cortex that are active only when animals are at locations that, for each cell, tile the environment in a periodic hexagonal pattern, like in a Chinese checkerboard. Grid cells express the metric of our internal spatial map and are thus often referred to as the brain's internal GPS. The present project is part of a research program using our discovery of grid cells to unravel the fundamental computations underlying our 'sense' of position. For such computations to be identified, we need access to the simultaneous activity of hundreds of neurons in the local entorhinal network. No one has yet been able to record electric signals from so many cells in parallel but technologies for large-scale population recordings are now coming of age. In the present project, we shall implement and develop two emerging technologies in neural population studies of entorhinal cortex in freely moving rodents: One allows the recording of electrical signals from many hundreds of distributed cells; the other exploits the invention of a two-photon high-resolution microscope so light (2 g) that it can be carried on the animal's head during natural behaviour.
The proposed work is basic science, which is the foundation for all advance of knowledge and technology in our society. A major impact of the development of methods for large-scale population recording is that we have enabled scientific investigation of neural network operations, and computations, anywhere in the cortex of freely-behaving animals. The impact on computational systems neuroscience, and our understanding of neural mechanisms of cognition, will be huge.
Despite its focus on fundamental questions, the work is particularly relevant for fighting Alzheimers disease, which is associated with severe destruction of the entorhinal cortex, the brain area that we use as a starting point for our studies. Through the development of new methods for read-out of electrical impulses from thousands of entorhinal or other cortical neurons at the same time, the present project sets the stage for a comprehensive understanding of normal and abnormal cortical functioning.
One of the grand challenges in neuroscience is to comprehend neural computation in the association cortices, the parts of cortex that have shown the largest expansion and differentiation during mammalian evolution. While we have learnt a lot about neural coding at the bottom of the cortical hierarchy, in sensory systems, we still have only a nascent understanding of coding and computation in higher-order sensory and association cortices. The present project is part of a research programme using our 2005 discovery of grid cells to unravel the fundamental computational algorithms of the association cortices and their contribution to specific functions of the mammalian cortex. Grid cells are cells in the mammalian medial entorhinal cortex that are active only when animals are at locations that, for each cell, tile the environment in a periodic hexagonal pattern, like in a Chinese checkerboard. The aim of the present project is to identify the key computational neural-network algorithms underlying the formation of grid-cell patterns and the use of such patterns to express dynamically information about the animal's location. For such algorithms to be identified, we need access to the simultaneous activity of hundreds of neurons in the local entorhinal network. No one has yet been able to record from so many cells in parallel but technologies for large-scale population recordings are now coming of age. In this project, we shall implement two emerging technologies - very-high-site-count silicon-probe recordings and miniature 2-photon imaging - in neural population studies of entorhinal cortex in freely moving rodents. We shall use these technologies to decipher the intrinsic activity structure of grid-cell networks and determine if grid patterns are present in the absence of external sensory stimulation. We shall also establish how entorhinal networks are organized in anatomical space and how these networks emerge during pre- and postnatal development of entorhinal cortex.