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Large-scale Three-dimensional Imaging of Cellular Organization in the Mouse Neocortex

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Grades in neural complexity: how large is the span?

Theodore Holmes Bullock¹

¹Neurobiology Unit, Scripps Institution of Oceanography and Department of Neurosciences, University of California San Diego, La Jolla, California 92093-0240.

Integrative and Comparative Biology

|June 29, 2011

Summary

Brain evolution shows repeated increases in complexity across diverse species, not just in mammals. Understanding these distinct grades of brain complexity requires more comparative research.

Area of Science:

Neuroscience
Evolutionary Biology
Comparative Anatomy

Background:

The evolutionary trajectory of brains exhibits vast complexity differences, from simple flatworms to advanced mammals.
Brain evolution has often involved adaptive radiation within similar complexity levels, with distinct grades appearing multiple times, sometimes in reverse.

Purpose of the Study:

To highlight the understudied nature of evolutionary achievements in brain complexity across different taxa.
To advocate for detailed comparative studies on the anatomical and physiological differences between distinct brain complexity grades.

Main Methods:

Comparative analysis of brain structures and functions across diverse animal groups.
Identifying and quantifying differences in anatomical parts, physiological processes, sensory abilities, and behaviors.

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Proposing research avenues for detailed characterization of brain grades.

Main Results:

Evolutionary advancement in brain complexity is not linear or exclusive to vertebrates, occurring independently in invertebrates like cephalopods and insects.
Significant gaps exist in quantitative data regarding neural connectivity, neuronal properties, and emergent phenomena across different brain complexity levels.

Conclusions:

Further research is needed to quantitatively compare brain connectivity and organization across various taxa to understand evolutionary grades.
Characterizing distinct grades of brain complexity requires detailed investigation into neuronal and circuit-level properties.