Forsøksdyr: Imaging cortical population codes for self-paced behavior in mice

Godkjenningsdato 20.06.2018

One of the great questions facing neuroscience is how the brain generates goal-directed motor behavior. More than a century of work has shown that purposeful movements of the body result from neural activity spanning several regions of the brain, including the posterior parietal cortex (PPC) and pre-motor cortex. These areas are major components of the cortical motor network, and play central roles in planning targeted actions in space before they are actually made. These regions have been most studied during behaviors in which the subjects are physically constrained (monkeys being head-fixed, or humans laying inside a functional scanner). As a result, there is a gap in our quantitative understanding of how the PPC-premotor pathway formulates self-paced, natural behavior in unrestrained individuals. Therefore, one goal of this project is to gain a deeper understanding of how the cortex generates self-guided movement in different behavioral contexts, and to quantify the neural correlates of behavior at the timescales at which they naturally occur. Another major goal is to better understand the degree to which cortical coding in the mouse reflects the behavior of their cohorts (as this could underlie social learning and action understanding). To accomplish these goals we propose to study cortical population codes during a variety of behaviors in freely moving or head-fixed mice while tracking them in 3D.

This project is an extension of work from the past few years (FOTS application 6833, approved 2014), and we estimate that an upper limit of 100 mice will be used. Any distress to the animals would be in the post-surgical recovery period, during which animal health and welfare are monitored very closely. Beyond the surgery interval, we will cause no harm or further distress, and wish to emphasize that our scientific success requires that the animals are healthy, well-nourished and behaving vigorously. A full description of how our work will comply with the principles of the 3 R's can be found within the application, but briefly, we are using state-of-the-art recording hardware that yields 100's of cells per animal, which reduces the number of subjects need to obtain statistically meaningful data sets and, when possible, animals will be re-used for multiple experiments. We will also aim to ensure that animal housing conditions are the best possible. Animals will be housed in large cages, and will be handled frequently. Funding for the work is provided by the Norwegian Research Council (Centre of Excellence scheme), the Kavli Foundation, and the European Research Council.

Through studying how the brains of these animals represent natural patterns of behavior in 3D, we hope to uncover general neural coding principles of goal-directed motor behavior which could be used, for example, to improve the efficiency of brain-controlled prosthetic devices in patients suffering from paralysis. The data obtained from this work could also be applied in the optimization of generative movement algorithms in robotics-- a field which is intent on producing machines to assist humans in hazardous environments and rescue situations.