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Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
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Related Experiment Video

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3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol

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Efficient physical embedding of topologically complex information processing networks in brains and computer

Danielle S Bassett¹, Daniel L Greenfield, Andreas Meyer-Lindenberg

¹Department of Physics, University of California Santa Barbara, Santa Barbara, California, United States of America. dbassett@physics.ucsb.edu

Plos Computational Biology

|April 28, 2010

Summary

Biological and artificial information processing systems, like brains and computer circuits, share common design principles. Both exhibit modularity and follow Rent

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Area of Science:

Computational Neuroscience
Network Science
Comparative Biology

Background:

Information processing systems, including nervous systems and very large scale integrated (VLSI) circuits, evolve through different mechanisms (natural selection vs. commercial development).
Shared organizational properties, such as modularity, are hypothesized to confer adaptive function across diverse physical information processing systems.

Purpose of the Study:

To investigate whether biological nervous systems and artificial computer circuits share fundamental organizational principles.
To determine if Rent's rule, observed in VLSI circuits, applies to biological neural networks.
To explore the implications of these shared principles for understanding nervous system evolution and design.

Main Methods:

Analysis of structural network data from human brains (MRI) and the nematode C. elegans nervous system.
Application of Rent's rule to quantify scaling relationships between processing elements and connections.
Comparison of topological dimensionality and wiring costs across different network types.

Main Results:

Both human brain structural networks and the C. elegans nervous system obey Rent's rule, indicating hierarchical modularity.
The Rent exponent derived from human brain networks explains allometric scaling of gray and white matter volumes across mammalian species.
Network interconnect topology dimensionality exceeded embedding Euclidean dimensions, suggesting a trade-off between wiring cost and complexity.

Conclusions:

Nervous systems and artificial circuits exhibit homologous principles of economical, fractal, and modular design.
These findings suggest conserved principles governing the evolution of physical information processing systems.
A balance between physical cost and topological complexity likely drives the design of both biological and artificial networks.