Markov blankets in the brain. (June 2021) - Hipólito, Inês; Ramstead, Maxwell J.D.; Convertino, Laura; Bhat, Anjali; Friston, Karl; Parr, Thomas
Highlights: We leverage the idea of 'Markov blanket' as a statistical boundary to provide an analysis of partitions in neuronal systems. We show this partition is applicable to multiple scales, from single neurons, brain regions, and brain-wide networks. Based on the canonical micro-circuitry, our treatment has practical applications for effective connectivity. Our proposed partition highlights the limitations of 'modular' proposals considering a single level of description. Abstract: Recent characterisations of self-organising systems depend upon the presence of a 'Markov blanket': a statistical boundary that mediates the interactions between the inside and outside of a system. We leverage this idea to provide an analysis of partitions in neuronal systems. This is applicable to brain architectures at multiple scales, enabling partitions into single neurons, brain regions, and brain-wide networks. This treatment is based upon the canonical micro-circuitry used in empirical studies of effective connectivity, so as to speak directly to practical applications. The notion of effective connectivity depends upon the dynamic coupling between functional units, whose form recapitulates that of a Markov blanket at each level of analysis. The nuance afforded by partitioning neural systems in this way highlights certain limitations of 'modular' perspectives of brain function that only consider a single level of description.