Conical expansion of the outer subventricular zone and the role of neocortical folding in evolution and development

Abstract

as it expands, so does it fold. The degree to which it folds, however, cannot strictly be attributed to its expansion. Across species, cortical volume does not keep pace with cortical surface area, but rather folds appear more rapidly than expected. As a result, larger brains quickly become disproportionately more convoluted than smaller brains. Both the absence (lissencephaly) and presence (gyrencephaly) of cortical folds is observed in all mammalian orders and, while there is likely some phylogenetic signature to the evolutionary appearance of gyri and sulci, there are undoubtedly universal trends to the acquisition of folds in an expanding neocortex. Whether these trends are governed by conical expansion of neocortical germinal zones, the distribution of cortical connectivity, or a combination of growth- and connectivity-driven forces remains an open question. But the importance of cortical folding for evolution of the uniquely mammalian neocortex, as well as for the incidence of neuropathologies in humans, is undisputed. In this hypothesis and theory article, we will summarize the development of cortical folds in the neocortex, consider the relative influence of growth- vs. connectivity-driven forces for the acquisition of cortical folds between and within species, assess the genetic, cell-biological, and mechanistic implications for neocortical expansion, and discuss the significance of these implications for human evolution, development, and disease. We will argue that evolutionary increases in the density of neuron production, achieved via maintenance of a basal proliferative niche in the neocortical germinal zones, drive the conical migration of neurons toward the cortical surface and ultimately lead to the establishment of cortical folds in large-brained mammal species.

Keywords: extracellular matrix; gyrencephaly; mammals; neocortex; neural progenitors; phylogenetics; subventricular zone.

Figure 1

Timeline of gyrification in human. Stages 1 and 2 are delineated by GW 31-32. There is a progressive lack of conservation in cortical folding patterns toward the final stages of gyrification, as minor developmental changes in gyri and sulci become increasingly specialized to species and, ultimately, susceptible to local environmental and experiential variations. 3D reconstructions of fetal human brains from Barnette et al. (2009). Figure follows Sawada et al. (2012b).

Figure 2

Schematic of neural progenitors in the developing neocortex in mouse (left) and human (right). Polarized progenitors (bRG and aRG) are depicted with processes extending to the apical (bottom) and/or basal (top) surface. Non-polarized cells (IPCs and TAPs) divide exclusively in the SVZ in both mouse and human. The human SVZ is relatively expanded compared to the mouse and divided into an outer (OSVZ) and inner (ISVZ) region. CP, cortical plate; IZ, intermediate zone; MZ, marginal zone; SP, subplate.

Figure 3

Observed axonal tension across neocortical gyri. Axonal tension (arrows) is distributed circumferentially across the subcortical white matter (dashed arrows), but radially in the subplate and gyral folds (filled arrows). Contrary to the connectivty-driven hypothesis (see section 4), circumferential tension is not observed across neocortical gray matter (Xu et al., 2010).

Figure 4

Basal fibers extending to the cortex during development. The density of progenitors in the proliferative basal compartment is increased and the angle of migration of their fibers more oblique at sites of developing gyri compared to sulci. In lissencephalic species, the basal compartment is scarcely populated by proliferating progenitors and fibers migrate in parallel to the developing cortex.

Figure 5

Gray matter cortical thickness varies with brain regions and phylogeny. (A) Twelve brain region volumes and GM thickness presented in a pie-chart matrix of positive (blue gradient) and negative (red gradient) correlations. Note that all brain region volumes - except BBO, which is a developmentally and functionally separate region - show very high (R² > 0.8) positive correlations, whereas cortical thickness is lowly (R² < 0.4) correlated with all brain region volumes. BBO, olfactory bulb; CRB, cerebellum; CT, cortical thickness; DCP, diencephalon; HPC, hippocampus; LBP, piriform lobe; MCP, mesencephalon; MDO, medulla oblongata; NHP, neurohypophysis; NPL, neopallial; SPM, septum; STM, striatum; TCP, telencephalon. Volumetric data from Stephan et al. (1981). (B) GM thickness is measured as the average distance between layers I and VI (yellow bars) in a systematic random sample of the neocortex. (C) A phylogenetic tree of 40 mammal species (Bininda-Emonds et al. 2007) showing the distribution of brain weight (log10 + 1) and GM thickness (log10 + 1) across species. GM thickness in all species was measured with Fiji (Schindelin et al., 2012) on slides from brainmuseum.org. See Lewitus et al. (2013) and Table A1 for neuroanatomical data in (C).

Figure 6

Gray matter (GM) thickness is a function of brain weight and neuron density. (A) Variation in GM thickness can be significantly explained by brain weight [F_{(2, 37)} = 22.58, P = 3.9 × 10⁻⁷] and neuron density [F_{(2, 20)} = 7.96, P = 0.003], but not by either GI [F_{(2, 38)} = 0.066, P = 0.936] or astrocyte density [F_{(2, 20)} = 2.37, P = 0.119]. The insets suggest a strong phylogenetic signal (Pagel, 1999), tantamount to a random walk, in the scaling of GM thickness as a function of brain weight (lambda = 0.89^(+0.07)_(−0.09)) and neuron density (lambda = 0.88^(+0.12)_(−0.17)). (B,C) Ln-transformed phylogenetically independent contrasts with regression through the origin for GM thickness as a function of (B) brain weight and (C) neuron density. GM thickness scales positively as a function of brain weight (e^{0.136 ± 0.027}) and negatively as a function of neuron density (e^{−0.276 ± 0.098}). Cell densities pertain to gray matter counts in the visual cortex from Lewitus et al. (2012). See (Lewitus et al., 2013) and Table A1 for neuroanatomical data.