Markov blankets in the brain

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.

Automated summary

Recent studies have found that the characteristics of self-organising systems are related to the presence of a "Markov blanket", a statistical boundary that mediates interactions between the inside and outside of a system. Utilizing this concept allows for the analysis of partitions in neuronal systems, applicable at multiple scales of brain architecture, enabling the division into individual neurons, brain regions, and brain-wide networks. The partitioning of neural systems in this manner highlights certain limitations of modular perspectives of brain function that only consider a single level of description.