Topic: Q-MIMI

Real-world complex systems can often be described by changes in a much smaller set of variables; the space they parameterise is called the system’s manifold. Shifting from single-cell to population-level analysis, we see this phenomenon in neuroscience, with recent evidence for “neural manifolds”: low-dimensional, functionally-relevant descriptions of population activity. The most general way to discover manifolds is to find the simplest transform of activity that maximises the mutual information (MI) between the transformation and the relevant task variables, since MI is the most general meas