In this work, we illustrate how new tools in information theory can be applied to certain encoding questions in neuroscience. Grid cells provide a suitable, intuitive neural context for testing such tools. Using Partial Information Decomposition, we analyzed simulated and real grid cell data to explore possible insights the tool may give for understanding neural encoding schemes.
This work was elevated to a podium talk at the Rice Neuroengineering Initiative Conference in 2022, and was presented as a poster at Society for Neuroscience in the same year. The paper describing this work has been accepted for publication in the Journal on Selected Areas in Information Theory.