A quantitative analysis of cerebellar anatomy in birds

The cerebellum is largely conserved in its circuitry, but varies greatly in size and shape across species. The extent to which differences in cerebellar morphology is driven by changes in neuron numbers, neuron sizes or both, remains largely unknown. To determine how species variation in cerebellum size and shape is reflective of neuron sizes and numbers requires the development of a suitable comparative data set and one that can effectively separate different neuronal populations. Here, we generated the largest comparative dataset to date on neuron numbers, sizes, and volumes of cortical layers and surface area of the cerebellum across 54 bird species. Across different cerebellar sizes, the cortical layers maintained relatively constant proportions to one another and variation in cerebellum size was largely due to neuron numbers rather than neuron sizes. However, the rate at which neuron numbers increased with cerebellum size varied across Purkinje cells, granule cells, and cerebellar nuclei neurons. We also examined the relationship among neuron numbers, cerebellar surface area and cerebellar folding. Our estimate of cerebellar folding, the midsagittal foliation index, was a poor predictor of surface area and number of Purkinje cells, but surface area was the best predictor of Purkinje cell numbers. Overall, this represents the first comprehensive, quantitative analysis of cerebellar anatomy in a comparative context of any vertebrate. The extent to which these relationships occur in other vertebrates requires a similar approach and would determine whether the same scaling principles apply throughout the evolution of the cerebellum.

Automated summary

The study revealed that the variations in size and shape of the cerebellum are largely influenced by neuron numbers, rather than neuron sizes. The rate of increase in neuron numbers varied across different types of neurons, highlighting the complexity of cerebellar anatomy across species. Additionally, while the folding index was a poor predictor of surface area and Purkinje cell numbers, surface area was found to be the best predictor of Purkinje cell numbers.