The evolution of brain structure captured in stereotyped cell count and cell type distributions
Introduction
The ultimate goal of neuroscience is to understand the structure and function of the human brain. However, much of neuroscience research is done on nonhuman model species that are amenable to experiments and genetic manipulations, with an increasing focus on the laboratory mouse in addition to a few other traditional animal models, such as the rat, prairie vole, rhesus macaque, marmoset, and zebra finch. Here we make a case for the importance of comparative studies across a much broader range of mammalian and vertebrate species, applying modern but versatile anatomical methods to disentangle which neural features are shared across distantly related species and which are species-specific or clade-specific. We review how recently acquired estimates of neuron numbers advanced our understanding of the evolution of vertebrate intelligence and highlight the potential of newly developed microscopy and brain clearing and labeling techniques for quantitative assessment of neural cell type-based correlates of cognitive and behavioral capabilities. Finally, we postulate that while the primary focus of contemporary evolutionary neuroscience has been on the identification of homologies at various levels of nervous system organization [1, 2, 3, 4, 5], detailed analyses of both shared and divergent features of brain anatomy can bring new information on the evolution of brain complexity and information-processing capacity.
Section snippets
From brain size to neuron numbers
Brain size is the predominant surrogate measure of brain functional capacity in comparative and cognitive neuroscience. However, it is neurons and their connections that provide the substrate for cognition and behavior. The total number of neurons, the basic computational units of the brain, is therefore a much better approximation of the brain's computational capacity than brain size alone.
Historically, unbiased stereological techniques such as the optical fractionator have been the methods of
From neuron numbers to neural circuits
The simple IF method described above has enabled the use of neuron cell counts in place of brain size in comparative studies, demonstrating, for example, the cognitive relevance of neuronal numbers in the vertebrate pallial telencephalon. Yet the separation between neuronal and non-neuronal cells does not capture the astounding diversity of neuronal cell types known to neuroscientists since the first visualization of brain cytoarchitecture by Camillo Golgi and Santiago Ramón y Cajal more than
Conclusion
We propose that a broad utilization of the IF in synergy with a more selective use of the newly available methods for quantitative whole-brain atlasing of cell type distributions can revolutionize comparative and cognitive neuroscience. The IF is a highly versatile tool that can be employed to estimate neuronal numbers across hundreds of species, generating an unprecedented wealth of comparative data on the evolution of brain complexity in vertebrates, ultimately identifying independent
Conflict of interest statement
Nothing declared.
References and recommended reading
Papers of particular interest, published within the period of review, have been highlighted as:
• of special interest
•• of outstanding interest
Acknowledgements
We thank Kristina Kverková for reading of the manuscript and discussions and Martin Kocourek for his assistance with preparation of Figure 1. This study was supported by Czech Science Foundation (18-15020S to PN and by N.I.H. (U01 MH105971 and U01 MH114824 to PO).
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