A microscale mouse-brain model

In the brain, the network of neuron-to-neuron connections somehow converts myriad signals into thoughts, memories, and actions. Connectomics, the study of that network, is a huge, active undertaking (see Physics Today, May 2018, page 26 , and December 2013, page 20 ). Before tackling the human connectome, which comprises more than 86 billion neurons and 100 trillion synapses, several research groups worldwide have set their sights on a smaller target, the mouse brain. Even so, combining the microscale perspective of individual neuron-to-neuron connections with meso- and macroscale pictures of the links between the brain’s different regions remains formidable.

At École Polytechnique Fédérale de Lausanne in Switzerland, researchers with the Blue Brain Project have bridged that gap with a new method to generate a statistical model of the complete micro-connectome of the mouse neocortex, containing 10 million neurons and 88 billion synaptic connections. The method incorporates the current knowledge of region-to-region connections, the neocortex’s laminar patterns, the structure of topological mapping between regions, data from 100 reconstructions of individual neurons that span multiple regions, and a comprehensive mesoscale model of connections between regions. The resulting constraints and organizing principles yielded a highly nonrandom, scale-invariant connectivity structure down to the subcellular level of individual synapses. Shown in detail here, the result is a base model that can be refined as future experiments yield additional constraints on neural connectivity. (M. W. Reimann et al., Nat. Comm. 10, 3903, 2019, doi:10.1038/s41467-019-11630-x . Image courtesy of Blue Brain Project/EPFL.)