The brain's code and its canonical computational motifs. From sensory cortex to the default mode network: A multi-scale model of brain function in health and disease

The brain appears to use repeated computational building blocks—canonical computational motifs—that are similar across species, brain areas, and sensory modalities. These motifs, grounded in stereotyped neuronal circuits and inhibitory interneurons, operate at micro-, meso-, and macro-scales to form a multiplexing information system capable of encoding and transmitting increasingly complex information. Similar activation patterns are observed in primary sensory cortices via electrophysiology and in large-scale networks measured with fMRI. The authors apply this canonical model to unify evidence on the pathophysiology of schizophrenia and suggest it may extend to other brain disorders involving GABA interneuron dysfunction.

Study at a glance

Abstract

A variety of anatomical and physiological evidence suggests that the brain performs computations using motifs that are repeated across species, brain areas, and modalities. The computational architecture of cortex, for example, is very similar from one area to another and the types, arrangements, and connections of cortical neurons are highly stereotyped. This supports the idea that each cortical area conducts calculations using similarly structured neuronal modules: what we term canonical computational motifs. In addition, the remarkable self-similarity of the brain observables at the micro-, meso- and macro-scale further suggests that these motifs are repeated at increasing spatial and temporal scales supporting brain activity from primary motor and sensory processing to higher-level behaviour and cognition. Here, we briefly review the biological bases of canonical brain circuits and the role of inhibitory interneurons in these computational elements. We then elucidate how canonical computational motifs can be repeated across spatial and temporal scales to build a multiplexing information system able to encode and transmit information of increasing complexity. We point to the similarities between the patterns of activation observed in primary sensory cortices by use of electrophysiology and those observed in large scale networks measured with fMRI. We then employ the canonical model of brain function to unify seemingly disparate evidence on the pathophysiology of schizophrenia in a single explanatory framework. We hypothesise that such a framework may also be extended to cover multiple brain disorders which are grounded in dysfunction of GABA interneurons and/or these computational motifs.