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A quantitative analysis of cerebellar anatomy in birds

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Abstract

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.

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All data generated and analysed in this study are included in the article.

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References

  • Andersen BB, Korbo L, Pakkenberg B (1992) A quantitative study of the human cerebellum with unbiased stereological techniques. J Comparative Neurol 326(4):549–560

    Article  CAS  Google Scholar 

  • Apps R, Hawkes R (2009) Cerebellar cortical organization: a one-map hypothesis. Nat Rev Neurosci 10(9):670–681

    Article  CAS  PubMed  Google Scholar 

  • Apps R, Hawkes R, Aoki S, Bengtsson F, Brown AM, Chen G, Ebner TJ, Isope P, Jörntell H, Lackey EP (2018) Cerebellar modules and their role as operational cerebellar processing units. Cerebellum 17(5):654–682

    Article  PubMed  PubMed Central  Google Scholar 

  • Arends J, Zeigler HP (1991) Organization of the cerebellum in the pigeon (Columba livia): II. Projections of the cerebellar nuclei. J Comparative Neurol 306(2):245–272

    Article  CAS  Google Scholar 

  • Boire D, Baron G (1994) Allometric comparison of brain and main brain subdivisions in birds. J Brain Res 35(1):49–66

    CAS  Google Scholar 

  • Burnham KP, Anderson DR (2002) Model selection and multimodel inference. A practical information-theoretic approach, 2nd edn. Springer, New York. https://doi.org/10.1007/b97636

  • Burnham KP, Anderson DR (2004) Multimodel inference: understanding AIC and BIC in model selection. Sociol Methods Res 33(2):261–304

    Article  Google Scholar 

  • Chang W, Pedroni A, Hohendorf V, Giacomello S, Hibi M, Köster RW, Ampatzis K (2020) Functionally distinct Purkinje cell types show temporal precision in encoding locomotion. Proc Natl Acad Sci 117(29):17330–17337

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Cooper A, Stanford I (2000) Electrophysiological and morphological characteristics of three subtypes of rat globus pallidus neurone in vitro. J Physiol 527(2):291–304

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Corfield JR, Birkhead TR, Spottiswoode CN, Iwaniuk AN, Boogert NJ, Gutiérrez-Ibáñez C, Overington SE, Wylie DR, Lefebvre L (2013) Brain size and morphology of the brood-parasitic and cerophagous honeyguides (Aves: Piciformes). Brain Behav Evol 81(3):170–186

    Article  PubMed  Google Scholar 

  • Corfield JR, Price K, Iwaniuk AN, Gutiérrez-Ibáñez C, Birkhead T, Wylie DR (2015) Diversity in olfactory bulb size in birds reflects allometry, ecology, and phylogeny. Front Neuroanat 9:102

    Article  PubMed  PubMed Central  Google Scholar 

  • Craciun I, Gutierrez-Ibanez C, Chan AS, Luksch H, Wylie DR (2019) Secretagogin immunoreactivity reveals lugaro cells in the pigeon cerebellum. Cerebellum 18(3):544–555

    Article  CAS  PubMed  Google Scholar 

  • Cunha F, Racicot K, Nahirney J, Heuston C, Wylie DR, Iwaniuk AN (2020) Allometric scaling rules of the cerebellum in Galliform birds. Brain Behav Evol 95(2):78–92

    Article  PubMed  Google Scholar 

  • de Sousa AA, Proulx MJ (2014) What can volumes reveal about human brain evolution? A framework for bridging behavioral, histometric, and volumetric perspectives. Front Neuroanat 8:51

    Article  PubMed  PubMed Central  Google Scholar 

  • Dieudonné S (1998) Submillisecond kinetics and low efficacy of parallel fibre-Golgi cell synaptic currents in the rat cerebellum. J Physiol 510(3):845–866

    Article  PubMed  PubMed Central  Google Scholar 

  • El-Andari R, Cunha F, Tschirren B, Iwaniuk AN (2020) Selection for divergent reproductive investment affects neuron size and foliation in the cerebellum. Brain Behav Evol 95(2):69–77

    Article  PubMed  Google Scholar 

  • Ericson PG, Anderson CL, Britton T, Elzanowski A, Johansson US, Källersjö M, Ohlson JI, Parsons TJ, Zuccon D, Mayr G (2006) Diversification of neoaves: integration of molecular sequence data and fossils. Biol Let 2(4):543–547

    Article  Google Scholar 

  • Escalona P, McDonald W, Doraiswamy P, Boyko O, Husain M, Figiel G, Laskowitz D, Ellinwood E, Krishnan K (1991) In vivo stereological assessment of human cerebellar volume: effects of gender and age. Am J Neuroradiol 12(5):927–929

    CAS  PubMed  PubMed Central  Google Scholar 

  • Fox CA (1959) The intermediate cells of Lugaro in the cerebellar cortex of the monkey. J Comparative Neurol 112(1):39–53

    Article  CAS  Google Scholar 

  • Garamszegi LZ (2014) Modern phylogenetic comparative methods and their application in evolutionary biology: concepts and practice. Springer, Heidelberg

    Book  Google Scholar 

  • Gardella D, Hatton WJ, Rind HB, Rosen GD, von Bartheld CS (2003) Differential tissue shrinkage and compression in the z-axis: implications for optical disector counting in vibratome-, plastic-and cryosections. J Neurosci Methods 124(1):45–59

    Article  PubMed  Google Scholar 

  • Gundersen H, Jensen E, Kiêu K, Nielsen J (1999) The efficiency of systematic sampling in stereology—reconsidered. J Microsc 193(3):199–211

    Article  CAS  PubMed  Google Scholar 

  • Gutiérrez-Ibáñez C, Iwaniuk AN, Wylie DR (2011) Relative size of auditory pathways in symmetrically and asymmetrically eared owls. Brain Behav Evol 78(4):286–301

    Article  PubMed  Google Scholar 

  • Gutiérrez-Ibáñez C, Iwaniuk AN, Lisney TJ, Wylie DR (2013) Comparative study of visual pathways in owls (Aves: Strigiformes). Brain Behav Evol 81(1):27–39

    Article  PubMed  Google Scholar 

  • Hackett SJ, Kimball RT, Reddy S, Bowie RC, Braun EL, Braun MJ, Chojnowski JL, Cox WA, Han K-L, Harshman J (2008) A phylogenomic study of birds reveals their evolutionary history. Science 320(5884):1763–1768

    Article  CAS  PubMed  Google Scholar 

  • Hall ZJ, Street SE, Healy SD (2013) The evolution of cerebellum structure correlates with nest complexity. Biol Let 9(6):20130687

    Article  Google Scholar 

  • Haug H (1987) Brain sizes, surfaces, and neuronal sizes of the cortex cerebri: a stereological investigation of man and his variability and a comparison with some mammals (primates, whales, marsupials, insectivores, and one elephant). Am J Anat 180(2):126–142

    Article  CAS  PubMed  Google Scholar 

  • Herculano-Houzel S, Lent R (2005) Isotropic fractionator: a simple, rapid method for the quantification of total cell and neuron numbers in the brain. J Neurosci 25(10):2518–2521

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Herculano-Houzel S, Manger PR, Kaas JH (2014) Brain scaling in mammalian evolution as a consequence of concerted and mosaic changes in numbers of neurons and average neuronal cell size. Front Neuroanat 8:77

    Article  PubMed  PubMed Central  Google Scholar 

  • Herculano-Houzel S, Catania K, Manger PR, Kaas JH (2015a) Mammalian brains are made of these: a dataset of the numbers and densities of neuronal and nonneuronal cells in the brain of glires, primates, scandentia, eulipotyphlans, afrotherians and artiodactyls, and their relationship with body mass. Brain Behav Evol 86(3–4):145–163

    Article  PubMed  Google Scholar 

  • Herculano-Houzel S, Messeder DJ, Fonseca-Azevedo K, Pantoja NA (2015b) When larger brains do not have more neurons: increased numbers of cells are compensated by decreased average cell size across mouse individuals. Front Neuroanat 9:64

    Article  PubMed  PubMed Central  Google Scholar 

  • Herculano-Houzel S, von Bartheld CS, Miller DJ, Kaas JH (2015c) How to count cells: the advantages and disadvantages of the isotropic fractionator compared with stereology. Cell Tissue Res 360(1):29–42

    Article  PubMed  PubMed Central  Google Scholar 

  • Hofman MA (1985) Size and shape of the cerebral cortex in mammals (part 1 of 2). Brain Behav Evol 27(1):28–40

    Article  CAS  PubMed  Google Scholar 

  • Inouye M, Oda SI (1980) Strain-specific variations in the folial pattern of the mouse cerebellum. J Comparative Neurol 190(2):357–362

    Article  CAS  Google Scholar 

  • Iwaniuk AN, Dean KM, Nelson JE (2005) Interspecific allometry of the brain and brain regions in parrots (Psittaciformes): comparisons with other birds and primates. Brain Behav Evol 65(1):40–59

    Article  PubMed  Google Scholar 

  • Iwaniuk AN, Lefebvre L, Wylie DR (2009) The comparative approach and brain–behaviour relationships: a tool for understanding tool use. Can J Exp Psychol/revue Canadienne De Psychologie Expérimentale 63(2):150

    Article  PubMed  Google Scholar 

  • Iwaniuk AN, Hurd PL, Wylie DR (2006) Comparative morphology of the avian cerebellum: I. Degree of foliation. Brain Behav Evol 68(1):45–62

    Article  PubMed  Google Scholar 

  • Iwaniuk AN, Hurd PL, Wylie DR (2007) Comparative morphology of the avian cerebellum: II. Size of folia. Brain Behav Evol 69(3):196–219

    Article  PubMed  Google Scholar 

  • Jardim-Messeder D, Lambert K, Noctor S, Pestana FM, de Castro Leal ME, Bertelsen MF, Alagaili AN, Mohammad OB, Manger PR, Herculano-Houzel S (2017) Dogs have the most neurons, though not the largest brain: trade-off between body mass and number of neurons in the cerebral cortex of large carnivoran species. Front Neuroanat 11:118

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Jarvis ED, Mirarab S, Aberer AJ, Li B, Houde P, Li C, Ho SY, Faircloth BC, Nabholz B, Howard JT (2014) Whole-genome analyses resolve early branches in the tree of life of modern birds. Science 346(6215):1320–1331

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Jetz W, Thomas GH, Joy JB, Hartmann K, Mooers AO (2012) The global diversity of birds in space and time. Nature 491(7424):444–448

    Article  CAS  PubMed  Google Scholar 

  • Lange W (1975) Cell number and cell density in the cerebellar cortex of man and some other mammals. Cell Tissue Res 157(1):115–124

    Article  CAS  PubMed  Google Scholar 

  • Lange W (1982) Regional differences in the cytoarchitecture of the cerebellar cortex. In: Palay SL, Chan-Palay V (eds) The cerebellum. New vistas. Exp Brain Res Suppl 6. Springer, Berlin, Heidelberg, pp 93–107

  • Larsell O (1967) The cerebellum: from myxinoids through birds. University of Minnesota Press, Minneapolis

    Google Scholar 

  • MacLeod CE, Zilles K, Schleicher A, Rilling JK, Gibson KR (2003) Expansion of the neocerebellum in Hominoidea. J Hum Evol 44(4):401–429

    Article  PubMed  Google Scholar 

  • Macrì S, Savriama Y, Khan I, Di-Poï N (2019) Comparative analysis of squamate brains unveils multi-level variation in cerebellar architecture associated with locomotor specialization. Nat Commun 10(1):1–16

    Article  CAS  Google Scholar 

  • Marshall WF (2015) How cells measure length on subcellular scales. Trends Cell Biol 25(12):760–768

    Article  PubMed  PubMed Central  Google Scholar 

  • Meitzen J, Thompson CK (2008) Seasonal-like growth and regression of the avian song control system: neural and behavioral plasticity in adult male Gambel’s white-crowned sparrows. Gen Comp Endocrinol 157(3):259–265

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Moore JM, DeVoogd TJ (2017) Concerted and mosaic evolution of functional modules in songbird brains. Proc R Soc B 284(1854):20170469

    Article  PubMed  PubMed Central  Google Scholar 

  • Mugnaini E, Floris A (1994) The unipolar brush cell: a neglected neuron of the mammalian cerebellar cortex. J Comparative Neurol 339(2):174–180

    Article  CAS  Google Scholar 

  • Mullen RJ, Buck CR, Smith AM (1992) NeuN, a neuronal specific nuclear protein in vertebrates. Development 116(1):201–211

    Article  CAS  PubMed  Google Scholar 

  • Ngwenya A, Nahirney J, Brinkman B, Williams L, Iwaniuk AN (2017) Comparison of estimates of neuronal number obtained using the isotropic fractionator method and unbiased stereology in day old chicks (Gallus domesticus). J Neurosci Methods 287:39–46

    Article  PubMed  Google Scholar 

  • Olkowicz S, Kocourek M, Lučan RK, Porteš M, Fitch WT, Herculano-Houzel S, Němec P (2016) Birds have primate-like numbers of neurons in the forebrain. Proc Natl Acad Sci 113(26):7255–7260

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Orme D, Freckleton R, Thomas G, Petzoldt T, Fritz S, Isaac N, Pearse W (2013) The caper package: comparative analysis of phylogenetics and evolution in R. R Package Vers 5(2):1–36

    Google Scholar 

  • Pagel M (1999) The maximum likelihood approach to reconstructing ancestral character states of discrete characters on phylogenies. Syst Biol 48(3):612–622

    Article  Google Scholar 

  • Pillay P, Manger PR (2007) Order-specific quantitative patterns of cortical gyrification. Eur J Neurosci 25(9):2705–2712

    Article  PubMed  Google Scholar 

  • Pinheiro J, Bates D, DebRoy S, Sarkar D, Team RC (2006) nlme: linear and nonlinear mixed effects models. R Package Vers 3(4):109

    Google Scholar 

  • Prum RO, Berv JS, Dornburg A, Field DJ, Townsend JP, Lemmon EM, Lemmon AR (2015) A comprehensive phylogeny of birds (Aves) using targeted next-generation DNA sequencing. Nature 526(7574):569–573

    Article  CAS  PubMed  Google Scholar 

  • Puzdrowski RL, Leonard RB (1992) Variations in cerebellar morphology of the Atlantic stingray. Dasyatis Sabina Neurosci Lett 135(2):196–200

    Article  CAS  PubMed  Google Scholar 

  • R Core Team (2020) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria

  • Reber S, Goehring NW (2015) Intracellular scaling mechanisms. Cold Spring Harb Perspect Biol 7(12):a019067

    Article  PubMed  PubMed Central  Google Scholar 

  • Schliep KP (2011) Phangorn: phylogenetic analysis in R. Bioinformatics 27(4):592–593

    Article  CAS  PubMed  Google Scholar 

  • Sherwood CC, Miller SB, Karl M, Stimpson CD, Phillips KA, Jacobs B, Hof PR, Raghanti MA, Smaers JB (2020) Invariant synapse density and neuronal connectivity scaling in primate neocortical evolution. Cereb Cortex 30(10):5604–5615

    Article  PubMed  PubMed Central  Google Scholar 

  • Smaers JB, Turner AH, Gómez-Robles A, Sherwood CC (2018) A cerebellar substrate for cognition evolved multiple times independently in mammals. Elife 7:e35696

    Article  PubMed  PubMed Central  Google Scholar 

  • Smaers JB, Vanier DR (2019) Brain size expansion in primates and humans is explained by a selective modular expansion of the cortico-cerebellar system. Cortex 118:292–305

    Article  PubMed  Google Scholar 

  • Smith GT, Brenowitz EA, Beecher MD, Wingfield JC (1997) Seasonal changes in testosterone, neural attributes of song control nuclei, and song structure in wild songbirds. J Neurosci 17(15):6001–6010

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Stevens C (1969) Structure of cat frontal olfactory cortex. J Neurophysiol 32(2):184–192

    Article  CAS  PubMed  Google Scholar 

  • Sultan F, Glickstein M (2007) The cerebellum: comparative and animal studies. Cerebellum 6(3):168–176

    Article  PubMed  Google Scholar 

  • Teeter CM, Stevens CF (2011) A general principle of neural arbor branch density. Curr Biol 21(24):2105–2108

    Article  CAS  PubMed  Google Scholar 

  • Vanier DR, Sherwood CC, Smaers JB (2019) Distinct patterns of hippocampal and neocortical evolution in primates. Brain Behav Evol 93(4):171–181

    Article  PubMed  Google Scholar 

  • Voogd J, Glickstein M (1998) The anatomy of the cerebellum. Trends Cogn Sci 2(9):307–313

    Article  CAS  PubMed  Google Scholar 

  • Yopak KE, Lisney TJ, Collin SP, Montgomery JC (2007) Variation in brain organization and cerebellar foliation in chondrichthyans: sharks and holocephalans. Brain Behav Evol 69(4):280–300

    Article  PubMed  Google Scholar 

  • Yopak KE, Pakan J, Wylie D (2017) The cerebellum of nonmammalian vertebrates. In: Kaas JH (ed) Evolution of nervous systems, 2nd edn. Academic Press, Oxford, pp 373–386

  • Zilles K, Armstrong E, Moser KH, Schleicher A, Stephan H (1989) Gyrification in the cerebral cortex of primates. Brain Behav Evol 34(3):143–150

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We wish to thank Maurice Needham and Ben Brinkman for assistance with microscopy.

Funding

Funding to support this study was provided by scholarships to FC from the University of Lethbridge, NSERC Discovery grants to DRW and ANI and the Canada Foundation for Innovation and Canada Research Chairs Program to ANI.

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All authors had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. FC, DW, and ANI: study concept and design. FC, and KR: acquisition of the data. FC, CGI, DR, and ANI: analysis and interpretation of the data. FC, CGI, DR, and ANI: drafting of the manuscript. FC, KR, CGI, DR, and ANI: critical revision of the manuscript for important intellectual content, administrative, technical, and material support.

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Correspondence to Felipe Cunha.

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429_2021_2352_MOESM1_ESM.jpg

Supplementary file1 (JPG 922 kb) Fig. S1 A comparison of the sizes of Purkinje cells, granule cells, and cerebellar nuclei neurons in two species, ac the brown thornbill (Acanthiza pusilla), and df the little penguin (Eudyptula minor). For each species, Purkinje cells are shown in a and d (scale-bar = 50 μm); granule cells in b and e (scale-bar = 10 μm), and cerebellar nuclei neuron in c and f (scale-bar = 30 μm)

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Cunha, F., Gutiérrez-Ibáñez, C., Racicot, K. et al. A quantitative analysis of cerebellar anatomy in birds. Brain Struct Funct 226, 2561–2583 (2021). https://doi.org/10.1007/s00429-021-02352-2

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