Information Theory for Biology and the Brain
Information theory has emerged as a powerful tool to quantify spatio-temporal interdependencies in various biological systems, from flocks of birds to the human brain. In this talk, I will briefly introduce some recent advances in information theory and their applications to biological systems. I will then discuss in detail our recent work on using information decomposition to study self-organised criticality in the brain.
Long-range correlations are a key signature of systems operating near criticality, indicating spatially-extended interactions across large distances. In the brain, along with other signatures of criticality, long-range correlations have been observed across various spatial scales, suggesting that the brain may operate near a critical point to optimise information processing and adaptability. However, the mechanisms underlying these long-range correlations remain poorly understood. We investigate the role of synergistic interactions in mediating long-range correlations in the visual cortex of awake mice. We leverage recent advances in mesoscale two-photon calcium imaging to analyse the activity of thousands of neurons across a wide field of view, allowing us to confirm the presence of long-range correlations at the level of neuronal populations. By applying the Partial Information Decomposition (PID) framework, we decompose the correlations into synergistic and redundant information interactions. Our results reveal that the increase in long-range correlations during visual stimulation is accompanied by a significant increase in synergistic rather than redundant interactions among neurons.