Chapter 4 - Allometry, evolution and development of neocortex size in mammals

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Abstract

Variation in neocortex size is one of the defining features of mammalian brain evolution. The paramount assumption has been that neocortex size indicates a monotonic allometric relationship with brain size. This assumption holds the concomitant neurodevelopmental assumption that the ontogenetic trajectory of neocortex size is so stable across species that it restrains changes in the direction of evolution. Here we test this fundamental assumption. Whereas previous research has focused exclusively on changes in mean size among groups (i.e., intercept), we additionally investigate changes in covariation (i.e., slope) and strength of allometric integration (i.e., residual variation). We further increase data resolution by investigating 350 species representing 11 mammalian orders.

Results identify nine shifts in covariation between neocortex and brainstem in different mammalian groups, indicate that these shifts occur independently of shifts in size, and demonstrate that the strength of allometric integration across different neocortical regions in primates is inversely related to the neurodevelopmental gradient such that later developing regions underwent more evolutionary change.

Although our results confirm that variation in brain organization is structured along a neurodevelopmental gradient, our results suggest two additional principles of size reorganization in brain evolution: (1) repatterning of growth allocation among brain regions may occur independently of size and (2) later developing regions indicate faster evolution, not necessarily directional evolution toward larger size. We conclude that the evolution of neocortex size in mammals is far more variable than previously assumed, in turn suggesting a higher degree of evolutionary flexibility in neurodevelopmental patterning than commonly suggested.

Introduction

One of the defining features of mammalian evolution is the extraordinary variation in overall brain size. Explaining the patterns and processes that characterize this variation has been a major driving force of brain evolutionary studies. Whereas the study of pattern is concerned with how variation is ordered across species, the study of process investigates the mechanisms that generate and maintain this order.

One of the central questions in the study of the pattern of mammalian brain evolution is whether certain brain regions can be identified that vary in size more than others (Passingham, 1975), and whether such highly variable regions explain variation in overall brain size (Smaers and Soligo, 2013, Smaers and Vanier, 2019). The neocortex has received particular attention in this regard (Barton and Harvey, 2000). Mammals have evolved a unique set of neocortical features, including six lamina, radial patterning of axonal connections across the lamina, and a clear differentiation between cortical gray matter and axonal white matter (Striedter, 2005). These features are thought to have allowed the so-called scaling up of the mammalian brain. Indeed, when considering the amount of change that has occurred among gross-anatomical brain regions, the neocortex does vary in size more than other regions (Finlay and Darlington, 1995).

However, fundamental questions as to which processes underpin the observed patterns of neocortical evolution remain. The main discussion here mirrors a longstanding discussion in evolutionary biology about the relative influence of selective pressure and biological constraints on evolutionary change. Whereas those emphasizing adaptation in response to directional selective pressures propose that traits are primarily determined by natural selection (Beldade et al., 2002a, Beldade et al., 2002b; Frankino et al., 2005, Frankino et al., 2007), those that emphasize the importance of biological constraints propose that the type and amount of trait change that can be accomplished over evolutionary time is largely determined by genetic and developmental mechanisms (Alberch, 1982; Brakefield, 2006; Jernvall, 2002; Maynard Smith et al., 1985; Schluter, 1996; Stern, 2000). In the context of brain evolution these assumptions translate into suggestions that variation in brain organization either changes flexibly according to behavioral selective pressures (Barton and Harvey, 2000; termed the “mosaic” hypothesis of brain evolution), or that variation in brain organization is restricted to what is possible given a conserved neurogenetic schedule (Yopak et al., 2010 Finlay and Darlington, 1995; termed the “concerted” hypothesis of brain evolution).

Here, we aim to contribute to this discussion by better describing patterns of neocortex size evolution and exploring whether these patterns may have resulted from comparative shifts in the neurodevelopmental schedule. In doing so, we increase both the analytical and empirical resolution compared to previous research. Whereas previous research has focused exclusively on variation in relative neocortex size (differences in intercept) (Barton and Harvey, 2000) or the interpretation of monotonic allometric differences among brain regions (Clancy et al., 2001), we extend our analysis to investigate shifts in covariation (differences in slope) and strength of allometric integration (differences in residual variation). We further increase comparative data resolution compared to previous research by investigating 350 species representing 11 mammalian orders.

Section snippets

Allometric patterning in brain region evolution

A standard approach to quantifying evolution of brain region sizes has been the use of the allometric framework (Passingham, 1973). Allometry is the study of how biological characteristics change with size (Shingleton, 2010). Applied to the study of brain region evolution, allometric analyses quantify how the size of individual brain regions change relative to changes in overall brain size or relative to the size of another brain region. In general, allometric analysis quantifies three aspects

Relating allometric patterning to developmental processes

Huxley (1932) demonstrated that if two traits grow at different rates under a common growth parameter, phenotypic changes in the two traits follow a power law. Allometric relationships often fit very precisely and vary little among closely related species (Gould, 1966), leading to the notion that allometry may be largely monotonic and indicative of a constraint imposed by the developmental architecture in the production of phenotypes (Alberch, 1982; Brakefield, 2006; Maynard Smith et al., 1985

Investigating allometry with increased analytical resolution

To investigate all aspects of the evolutionary allometric pattern of neocortex size, we collated data from the literature on neocortex size and brainstem size for 350 mammalian species (Baron et al., 1996; Frahm et al., 1982; Pirlot, 1981; Pirlot and Desperoni, 1987; Reep et al., 2007; Stephan et al., 1981). As phylogenetic tree we use the consensus tree derived by Smaers et al. (2018) from the mammalian supertree compiled by Faurby and Svenning (2015). Because we are primarily interested in

The allometric pattern of neocortical region size evolution

Although a comprehensive investigation of the allometric patterns that characterize neocortex evolution in mammals is essential to understanding mammalian brain evolution, such analysis inevitably masks patterns of evolution of neocortical regions. The mammalian neocortex consists of a plethora of distinct regions that are associated with different functions and are underpinned by different developmental trajectories (Giedd et al., 1999; Kaas, 2006). Although correlating neocortex size to

Conclusion: Implications for the principles of brain evolution

The evolution of the neocortex is the hallmark of mammalian brain evolution and is commonly understood to be the primary factor in explaining comparative variation in mammalian brain size. Previous studies on neocortex size evolution have, however, erred by not considering putative changes among groups of species in the covariation between neocortex size and other brain regions. The putative occurrence of such shifts would have fundamental implications for explaining comparative variation in

References (88)

  • J. Lázaro et al.

    Profound reversible seasonal changes of individual skull size in a mammal

    Curr. Biol.

    (2017)
  • J.B. Smaers et al.

    Exceptional evolutionary expansion of prefrontal cortex in great apes and humans

    Curr. Biol.

    (2017)
  • H. Tiemeier et al.

    Cerebellum development during childhood and adolescence: a longitudinal morphometric MRI study

    NeuroImage

    (2010)
  • D.C. Adams

    Quantifying and comparing phylogenetic evolutionary rates for shape and other high-dimensional phenotypic data

    Syst. Biol.

    (2014)
  • D.C. Adams et al.

    geomorph: an R package for the collection and analysis of geometric morphometric shape data

    Methods Ecol. Evol.

    (2013)
  • P. Alberch

    Developmental constraints in evolutionary processes

  • W.S. Armbruster et al.

    Covariance and decoupling of floral and vegetative traits in nine neotropical plants: a re-evaluation of Berg's correlation-pleiades concept

    Am. J. Bot.

    (1999)
  • W.S. Armbruster et al.

    Integrated phenotypes: understanding trait covariation in plants and animals

    Philos. Trans. R. Soc., B

    (2014)
  • G. Baron et al.

    Comparative Neurobiology in Chiroptera: Macromorphology, Brain Structures, Tables and Atlases

    (1996)
  • R.A. Barton et al.

    Mosaic evolution of brain structure in mammals

    Nature

    (2000)
  • P. Beldade et al.

    Developmental constraints versus flexibility in morphological evolution

    Nature

    (2002)
  • P. Beldade et al.

    Modularity, individuality, and evo-devo in butterfly wings

    Proc. Natl. Acad. Sci. U. S. A.

    (2002)
  • P.L. Croxson et al.

    Structural variability across the primate brain: a cross-species comparison

    Cereb. Cortex

    (2017)
  • R.B. Darlington et al.

    Neural development in metatherian and eutherian mammals: variation and constraint

    J. Comp. Neurol.

    (1999)
  • A.A. de Sousa et al.

    Comparative cytoarchitectural analyses of striate and extrastriate areas in hominoids

    Cereb. Cortex

    (2010)
  • D.K.N. Dechmann et al.

    Comparative studies of brain evolution: a critical insight from the Chiroptera

    Biol. Rev.

    (2009)
  • R. Desimone et al.

    Visual properties of neurons in area V4 of the macaque: sensitivity to stimulus form

    J. Neurophysiol.

    (1987)
  • C.J. Donahue et al.

    Quantitative assessment of prefrontal cortex in humans relative to nonhuman primates

    Proc. Natl. Acad. Sci. U. S. A.

    (2018)
  • R.I.M. Dunbar et al.

    Understanding primate brain evolution

    Philos. Trans. R. Soc., B

    (2007)
  • R.N. Felice et al.

    A fly in a tube: macroevolutionary expectations for integrated phenotypes

    Evolution

    (2018)
  • B.L. Finlay et al.

    Linked regularities in the development and evolution of mammalian brains

    Science

    (1995)
  • B.L. Finlay et al.

    Developmental structure in brain evolution

    Behav. Brain Sci.

    (2001)
  • B.L. Finlay et al.

    Late still equals large

    Brain Behav. Evol.

    (2010)
  • H.D. Frahm et al.

    Comparison of brain structure volumes in insectivora and primates. 1. Neocortex

    J. Hirnforsch.

    (1982)
  • W.A. Frankino et al.

    Natural selection and developmental constraints in the evolution of allometries

    Science

    (2005)
  • W.A. Frankino et al.

    Internal and external constraints in the evolution of morphological allometries in a butterfly

    Evolution

    (2007)
  • J.A. Fuentes-G et al.

    Phylogenetic ANCOVA: estimating changes in evolutionary rates as well as relationships between traits

    Am. Nat.

    (2016)
  • J.N. Giedd et al.

    Brain development during childhood and adolescence: a longitudinal MRI study

    Nat. Neurosci.

    (1999)
  • J. Gliwicz et al.

    Comparing life histories of shrews and rodents

    Acta Theriol.

    (2002)
  • N. Gogtay et al.

    Dynamic mapping of human cortical development during childhood through early adulthood

    Proc. Natl. Acad. Sci. U. S. A.

    (2004)
  • A. Gómez-Robles et al.

    Relaxed genetic control of cortical organization in human brains compared with chimpanzees

    Proc. Natl. Acad. Sci. U. S. A.

    (2015)
  • A. Goswami et al.

    Developmental modularity and the marsupial–placental dichotomy

    J. Exp. Zool. B Mol. Dev. Evol.

    (2009)
  • A. Goswami et al.

    The macroevolutionary consequences of phenotypic integration: from development to deep time

    Philos. Trans. R. Soc., B

    (2014)
  • S.J. Gould

    Allometry and size in ontogeny and phylogeny

    Biol. Rev.

    (1966)
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