A null model of the mouse whole-neocortex micro-connectome

Area of Science:

• Neuroscience
• Computational Biology
• Connectomics

Background:

• Connectomics studies neural network structure at macro/meso and micro scales.
• Advances in macro/meso-scale connectomics provide region-to-region connectivity data.
• Micro-scale connectomics focuses on individual neuron connectivity.

Purpose of the Study:

• To build a statistical model of the micro-connectome for an entire mouse neocortex.
• To integrate macro/meso-scale and micro-scale connectomics data.
• To reveal and predict neural targeting principles.

Main Methods:

• Utilized available data on region-to-region connectivity.
• Incorporated individual whole-brain axon reconstructions.
• Developed a statistical modeling approach to combine data scales.

Main Results:

• Generated a first draft statistical model of the mouse neocortex micro-connectome.
• Identified a targeting principle predicting individual axon innervation from meso-scale data.
• Demonstrated that biological targeting trends are recreated across scales.

Conclusions:

• Scale-invariant topological organization of connectivity extends to individual neurons.
• The model serves as a null model for connectomics research.
• The model provides a substrate for whole-brain simulations.