Variability in neuron densities across the cortical sheet in primates

A complementary approach for neocortical cytoarchitecture inspection with cellular resolution imaging at whole brain scale

Cytoarchitecture, the organization of cells within organs and tissues, serves as a crucial anatomical foundation for the delineation of various regions. It enables the segmentation of the cortex into distinct areas with unique structural and functional characteristics. While traditional 2D atlases have focused on cytoarchitectonic mapping of cortical regions through individual sections, the intricate cortical gyri and sulci demands a 3D perspective for unambiguous interpretation. In this study, we employed fluorescent micro-optical sectioning tomography to acquire architectural datasets of the entire macaque brain at a resolution of 0.65 μm × 0.65 μm × 3 μm. With these volumetric data, the cortical laminar textures were remarkably presented in appropriate view planes. Additionally, we established a stereo coordinate system to represent the cytoarchitectonic information as surface-based tomograms. Utilizing these cytoarchitectonic features, we were able to three-dimensionally parcel the macaque cortex into multiple regions exhibiting contrasting architectural patterns. The whole-brain analysis was also conducted on mice that clearly revealed the presence of barrel cortex and reflected biological reasonability of this method. Leveraging these high-resolution continuous datasets, our method offers a robust tool for exploring the organizational logic and pathological mechanisms of the brain's 3D anatomical structure.

Common Microscale and Macroscale Principles of Connectivity in the Human Brain

The brain requires efficient information transfer between neurons and large-scale brain regions. Brain connectivity follows predictable organizational principles. At the cellular level, larger supragranular pyramidal neurons have larger, more branched dendritic trees, more synapses, and perform more complex computations; at the macroscale, region-to-region connections display a diverse architecture with highly connected hub areas facilitating complex information integration and computation. Here, we explore the hypothesis that the branching structure of large-scale region-to-region connectivity follows similar organizational principles as the neuronal scale. We examine microscale connectivity of basal dendritic trees of supragranular pyramidal neurons (300+) across 10 cortical areas in five human donor brains (1 male, 4 female). Dendritic complexity was quantified as the number of branch points, tree length, spine count, spine density, and overall branching complexity. High-resolution diffusion-weighted MRI was used to construct white matter trees of corticocortical wiring. Examining complexity of the resulting white matter trees using the same measures as for dendritic trees shows heteromodal association areas to have larger, more complex white matter trees than primary areas (p < 0.0001) and macroscale complexity to run in parallel with microscale measures, in terms of number of inputs (r = 0.677, p = 0.032), branch points (r = 0.797, p = 0.006), tree length (r = 0.664, p = 0.036), and branching complexity (r = 0.724, p = 0.018). Our findings support the integrative theory that brain connectivity follows similar principles of connectivity at neuronal and macroscale levels and provide a framework to study connectivity changes in brain conditions at multiple levels of organization.SIGNIFICANCE STATEMENT Within the human brain, cortical areas are involved in a wide range of processes, requiring different levels of information integration and local computation. At the cellular level, these regional differences reflect a predictable organizational principle with larger, more complexly branched supragranular pyramidal neurons in higher order regions. We hypothesized that the 3D branching structure of macroscale corticocortical connections follows the same organizational principles as the cellular scale. Comparing branching complexity of dendritic trees of supragranular pyramidal neurons and of MRI-based regional white matter trees of macroscale connectivity, we show that macroscale branching complexity is larger in higher order areas and that microscale and macroscale complexity go hand in hand. Our findings contribute to a multiscale integrative theory of brain connectivity.

Ultrasound stimulation of the motor cortex during tonic muscle contraction

Transcranial ultrasound stimulation (tUS) shows potential as a noninvasive brain stimulation (NIBS) technique, offering increased spatial precision compared to other NIBS techniques. However, its reported effects on primary motor cortex (M1) are limited. We aimed to better understand tUS effects in human M1 by performing tUS of the hand area of M1 (M1hand) during tonic muscle contraction of the index finger. Stimulation during muscle contraction was chosen because of the transcranial magnetic stimulation-induced phenomenon known as cortical silent period (cSP), in which transcranial magnetic stimulation (TMS) of M1hand involuntarily suppresses voluntary motor activity. Since cSP is widely considered an inhibitory phenomenon, it presents an ideal parallel for tUS, which has often been proposed to preferentially influence inhibitory interneurons. Recording electromyography (EMG) of the first dorsal interosseous (FDI) muscle, we investigated effects on muscle activity both during and after tUS. We found no change in FDI EMG activity concurrent with tUS stimulation. Using single-pulse TMS, we found no difference in M1 excitability before versus after sparsely repetitive tUS exposure. Using acoustic simulations in models made from structural MRI of the participants that matched the experimental setups, we estimated in-brain pressures and generated an estimate of cumulative tUS exposure experienced by M1hand for each subject. We were unable to find any correlation between cumulative M1hand exposure and M1 excitability change. We also present data that suggest a TMS-induced MEP always preceded a near-threshold cSP.

Creative Destruction: A Basic Computational Model of Cortical Layer Formation

One of the most characteristic properties of many vertebrate neural systems is the layered organization of different cell types. This cytoarchitecture exists in the cortex, the retina, the hippocampus, and many other parts of the central nervous system. The developmental mechanisms of neural layer formation have been subject to substantial experimental efforts. Here, we provide a general computational model for cortical layer formation in 3D physical space. We show that this multiscale, agent-based model, comprising two distinct stages of apoptosis, can account for the wide range of neuronal numbers encountered in different cortical areas and species. Our results demonstrate the phenotypic richness of a basic state diagram structure. Importantly, apoptosis allows for changing the thickness of one layer without automatically affecting other layers. Therefore, apoptosis increases the flexibility for evolutionary change in layer architecture. Notably, slightly changed gene regulatory dynamics recapitulate the characteristic properties observed in neurodevelopmental diseases. Overall, we propose a novel computational model using gene-type rules, exhibiting many characteristics of normal and pathological cortical development.

Length of the Neurogenic Period-A Key Determinant for the Generation of Upper-Layer Neurons During Neocortex Development and Evolution

The neocortex, a six-layer neuronal brain structure that arose during the evolution of, and is unique to, mammals, is the seat of higher order brain functions responsible for human cognitive abilities. Despite its recent evolutionary origin, it shows a striking variability in size and folding complexity even among closely related mammalian species. In most mammals, cortical neurogenesis occurs prenatally, and its length correlates with the length of gestation. The evolutionary expansion of the neocortex, notably in human, is associated with an increase in the number of neurons, particularly within its upper layers. Various mechanisms have been proposed and investigated to explain the evolutionary enlargement of the human neocortex, focussing in particular on changes pertaining to neural progenitor types and their division modes, driven in part by the emergence of human-specific genes with novel functions. These led to an amplification of the progenitor pool size, which affects the rate and timing of neuron production. In addition, in early theoretical studies, another mechanism of neocortex expansion was proposed—the lengthening of the neurogenic period. A critical role of neurogenic period length in determining neocortical neuron number was subsequently supported by mathematical modeling studies. Recently, we have provided experimental evidence in rodents directly supporting the mechanism of extending neurogenesis to specifically increase the number of upper-layer cortical neurons. Moreover, our study examined the relationship between cortical neurogenesis and gestation, linking the extension of the neurogenic period to the maternal environment. As the exact nature of factors promoting neurogenic period prolongation, as well as the generalization of this mechanism for evolutionary distinct lineages, remain elusive, the directions for future studies are outlined and discussed.

Anatomy and Physiology of Macaque Visual Cortical Areas V1, V2, and V5/MT: Bases for Biologically Realistic Models

The cerebral cortex of primates encompasses multiple anatomically and physiologically distinct areas processing visual information. Areas V1, V2, and V5/MT are conserved across mammals and are central for visual behavior. To facilitate the generation of biologically accurate computational models of primate early visual processing, here we provide an overview of over 350 published studies of these three areas in the genus Macaca, whose visual system provides the closest model for human vision. The literature reports 14 anatomical connection types from the lateral geniculate nucleus of the thalamus to V1 having distinct layers of origin or termination, and 194 connection types between V1, V2, and V5, forming multiple parallel and interacting visual processing streams. Moreover, within V1, there are reports of 286 and 120 types of intrinsic excitatory and inhibitory connections, respectively. Physiologically, tuning of neuronal responses to 11 types of visual stimulus parameters has been consistently reported. Overall, the optimal spatial frequency (SF) of constituent neurons decreases with cortical hierarchy. Moreover, V5 neurons are distinct from neurons in other areas for their higher direction selectivity, higher contrast sensitivity, higher temporal frequency tuning, and wider SF bandwidth. We also discuss currently unavailable data that could be useful for biologically accurate models.

GABAergic and non-GABAergic subpopulations of Kv3.1b-expressing neurons in macaque V2 and MT: laminar distributions and proportion of total neuronal population

The Kv3.1b potassium channel subunit, which facilitates the fast-spiking phenotype characteristic of parvalbumin (PV)-expressing inhibitory interneurons, is also expressed by subpopulations of excitatory neurons in macaque cortex. We have previously shown that V1 neurons expressing Kv3.1b but not PV or GABA were largely concentrated within layers 4Cα and 4B of V1, suggesting laminar or pathway specificity. In the current study, the distribution and pattern of co-immunoreactivity of GABA, PV, and Kv3.1b across layers in extrastriate cortical areas V2 and MT of the macaque monkey were measured using the same triple immunofluorescence labeling, confocal microscopy, and partially automated cell-counting strategies used in V1. For comparison, densities of the overall cell and neuronal populations were also measured for each layer of V2 and MT using tissue sections immunofluorescence labeled for the pan-neuronal marker NeuN. GABAergic neurons accounted for 14% of the total neuronal population in V2 and 25% in MT. Neurons expressing Kv3.1b but neither GABA nor PV were present in both areas. This subpopulation was most prevalent in the lowest subcompartment of layer 3, comprising 5% of the total neuronal population in layer 3C of both areas, and 41% and 36% of all Kv3.1b+ neurons in this layer in V2 and MT, respectively. The prevalence and laminar distribution of this subpopulation were remarkably consistent between V2 and MT and showed a striking similarity to the patterns observed previously in V1, suggesting a common contribution to the cortical circuit across areas.

Large-scale acoustic-driven neuronal patterning and directed outgrowth

Acoustic manipulation is an emerging non-invasive method enabling precise spatial control of cells in their native environment. Applying this method for organizing neurons is invaluable for neural tissue engineering applications. Here, we used surface and bulk standing acoustic waves for large-scale patterning of Dorsal Root Ganglia neurons and PC12 cells forming neuronal cluster networks, organized biomimetically. We showed that by changing parameters such as voltage intensity or cell concentration we were able to affect cluster properties. We examined the effects of acoustic arrangement on cells atop 3D hydrogels for up to 6 days and showed that assembled cells spontaneously grew branches in a directed manner towards adjacent clusters, infiltrating the matrix. These findings have great relevance for tissue engineering applications as well as for mimicking architectures and properties of native tissues.

Inversion of a large-scale circuit model reveals a cortical hierarchy in the dynamic resting human brain

We considered a large-scale dynamical circuit model of human cerebral cortex with region-specific microscale properties. The model was inverted using a stochastic optimization approach, yielding markedly better fit to new, out-of-sample resting functional magnetic resonance imaging (fMRI) data. Without assuming the existence of a hierarchy, the estimated model parameters revealed a large-scale cortical gradient. At one end, sensorimotor regions had strong recurrent connections and excitatory subcortical inputs, consistent with localized processing of external stimuli. At the opposing end, default network regions had weak recurrent connections and excitatory subcortical inputs, consistent with their role in internal thought. Furthermore, recurrent connection strength and subcortical inputs provided complementary information for differentiating the levels of the hierarchy, with only the former showing strong associations with other macroscale and microscale proxies of cortical hierarchies (meta-analysis of cognitive functions, principal resting fMRI gradient, myelin, and laminar-specific neuronal density). Overall, this study provides microscale insights into a macroscale cortical hierarchy in the dynamic resting brain.

Neuronal Distribution Across the Cerebral Cortex of the Marmoset Monkey (Callithrix jacchus)

Using stereological analysis of NeuN-stained sections, we investigated neuronal density and number of neurons per column throughout the marmoset cortex. Estimates of mean neuronal density encompassed a greater than 3-fold range, from >150 000 neurons/mm3 in the primary visual cortex to ~50 000 neurons/mm3 in the piriform complex. There was a trend for density to decrease from posterior to anterior cortex, but also local gradients, which resulted in a complex pattern; for example, in frontal, auditory, and somatosensory cortex neuronal density tended to increase towards anterior areas. Anterior cingulate, motor, premotor, insular, and ventral temporal areas were characterized by relatively low neuronal densities. Analysis across the depth of the cortex revealed greater laminar variation of neuronal density in occipital, parietal, and inferior temporal areas, in comparison with other regions. Moreover, differences between areas were more pronounced in the supragranular layers than in infragranular layers. Calculations of the number of neurons per unit column revealed a pattern that was distinct from that of neuronal density, including local peaks in the posterior parietal, superior temporal, precuneate, frontopolar, and temporopolar regions. These results suggest that neuronal distribution in adult cortex result from a complex interaction of developmental/ evolutionary determinants and functional requirements.

Confirmation of a gyral bias in diffusion MRI fiber tractography

Diffusion MRI fiber tractography has been increasingly used to map the structural connectivity of the human brain. However, this technique is not without limitations; for example, there is a growing concern over anatomically correlated bias in tractography findings. In this study, we demonstrate that there is a bias for fiber tracking algorithms to terminate preferentially on gyral crowns, rather than the banks of sulci. We investigate this issue by comparing diffusion MRI (dMRI) tractography with equivalent measures made on myelin-stained histological sections. We begin by investigating the orientation and trajectories of axons near the white matter/gray matter boundary, and the density of axons entering the cortex at different locations along gyral blades. These results are compared with dMRI orientations and tract densities at the same locations, where we find a significant gyral bias in many gyral blades across the brain. This effect is shown for a range of tracking algorithms, both deterministic and probabilistic, and multiple diffusion models, including the diffusion tensor and a high angular resolution diffusion imaging technique. Additionally, the gyral bias occurs for a range of diffusion weightings, and even for very high-resolution datasets. The bias could significantly affect connectivity results using the current generation of tracking algorithms.

Distributions of Cells and Neurons across the Cortical Sheet in Old World Macaques

According to previous research, cell and neuron densities vary across neocortex in a similar manner across primate taxa. Here, we provide a more extensive examination of this effect in macaque monkeys. We separated neocortex from the underlying white matter in 4 macaque monkey hemispheres (1 Macaca nemestrina, 2 Macaca radiata, and 1 Macaca mulatta), manually flattened the neocortex, and divided it into smaller tissue pieces for analysis. The number of cells and neurons were determined for each piece across the cortical sheet using flow cytometry. Primary visual cortex had the most densely packed neurons and primary motor cortex had the least densely packed neurons. With respect to differences in brain size between cases, there was little variability in the total cell and neuron numbers within specific areas, and overall trends were similar to what has been previously described in Old World baboons and other primates. The average hemispheric total cell number per hemisphere ranged from 2.9 to 3.7 billion, while the average total neuron number ranged from 1.3 to 1.7 billion neurons. The visual cortex neuron densities were predictably higher, ranging from 18.2 to 34.7 million neurons/cm2 in macaques, in comparison to a range of 9.3-17.7 million neurons/cm2 across cortex as a whole. The results support other evidence that neuron surface densities vary across the cortical sheet in a predictable pattern within and across primate taxa.

Cortical cell and neuron density estimates in one chimpanzee hemisphere

The density of cells and neurons in the neocortex of many mammals varies across cortical areas and regions. This variability is, perhaps, most pronounced in primates. Nonuniformity in the composition of cortex suggests regions of the cortex have different specializations. Specifically, regions with densely packed neurons contain smaller neurons that are activated by relatively few inputs, thereby preserving information, whereas regions that are less densely packed have larger neurons that have more integrative functions. Here we present the numbers of cells and neurons for 742 discrete locations across the neocortex in a chimpanzee. Using isotropic fractionation and flow fractionation methods for cell and neuron counts, we estimate that neocortex of one hemisphere contains 9.5 billion cells and 3.7 billion neurons. Primary visual cortex occupies 35 cm(2) of surface, 10% of the total, and contains 737 million densely packed neurons, 20% of the total neurons contained within the hemisphere. Other areas of high neuron packing include secondary visual areas, somatosensory cortex, and prefrontal granular cortex. Areas of low levels of neuron packing density include motor and premotor cortex. These values reflect those obtained from more limited samples of cortex in humans and other primates.

The cellular composition of the marsupial neocortex

In the current investigation we examined the number and proportion of neuronal and non-neuronal cells in the primary sensory areas of the neocortex of a South American marsupial, the short-tailed opossum (Monodelphis domestica). The primary somatosensory (S1), auditory (A1), and visual (V1) areas were dissected from the cortical sheet and compared with each other and the remaining neocortex using the isotropic fractionator technique. We found that although the overall sizes of V1, S1, A1, and the remaining cortical regions differed from each other, these divisions of the neocortex contained the same number of neurons, but the remaining cortex contained significantly more non-neurons than the primary sensory regions. In addition, the percent of neurons was higher in A1 than in the remaining cortex and the cortex as a whole. These results are similar to those seen in non-human primates. Furthermore, these results indicate that in some respects, such as number of neurons, the neocortex is homogenous across its extent, whereas in other aspects of organization, such as non-neuronal number and percentage of neurons, there is non-uniformity. Whereas the overall pattern of neuronal distribution is similar between short-tailed opossums and eutherian mammals, short-tailed opossum have a much lower cellular and neuronal density than other eutherian mammals. This suggests that the high neuronal density cortices of mammals such as rodents and primates may be a more recently evolved characteristic that is restricted to eutherians, and likely contributes to the complex behaviors we see in modern mammals.

Cortical high-density counterstream architectures

Small-world networks provide an appealing description of cortical architecture owing to their capacity for integration and segregation combined with an economy of connectivity. Previous reports of low-density interareal graphs and apparent small-world properties are challenged by data that reveal high-density cortical graphs in which economy of connections is achieved by weight heterogeneity and distance-weight correlations. These properties define a model that predicts many binary and weighted features of the cortical network including a core-periphery, a typical feature of self-organizing information processing systems. Feedback and feedforward pathways between areas exhibit a dual counterstream organization, and their integration into local circuits constrains cortical computation. Here, we propose a bow-tie representation of interareal architecture derived from the hierarchical laminar weights of pathways between the high-efficiency dense core and periphery.

Systematic, cross-cortex variation in neuron numbers in rodents and primates

Uniformity, local variability, and systematic variation in neuron numbers per unit of cortical surface area across species and cortical areas have been claimed to characterize the isocortex. Resolving these claims has been difficult, because species, techniques, and cortical areas vary across studies. We present a stereological assessment of neuron numbers in layers II-IV and V-VI per unit of cortical surface area across the isocortex in rodents (hamster, Mesocricetus auratus; agouti, Dasyprocta azarae; paca, Cuniculus paca) and primates (owl monkey, Aotus trivigratus; tamarin, Saguinus midas; capuchin, Cebus apella); these chosen to vary systematically in cortical size. The contributions of species, cortical areas, and techniques (stereology, "isotropic fractionator") to neuron estimates were assessed. Neurons per unit of cortical surface area increase across the rostro-caudal (RC) axis in primates (varying by a factor of 1.64-2.13 across the rostral and caudal poles) but less in rodents (varying by a factor of 1.15-1.54). Layer II-IV neurons account for most of this variation. When integrated into the context of species variation, and this RC gradient in neuron numbers, conflicts between studies can be accounted for. The RC variation in isocortical neurons in adulthood mirrors the gradients in neurogenesis duration in development.

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

THERE IS A BASIC RULE TO MAMMALIAN NEOCORTICAL EXPANSION

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.

Systematic, balancing gradients in neuron density and number across the primate isocortex

The cellular and areal organization of the cerebral cortex impacts how it processes and integrates information. How that organization emerges and how best to characterize it has been debated for over a century. Here we demonstrate and describe in the isocortices of seven primate species a pronounced anterior-to-posterior gradient in the density of neurons and in the number of neurons under a unit area of the cortical surface. Our findings assert that the cellular architecture of the primate isocortex is neither arranged uniformly nor into discrete patches with an arbitrary spatial arrangement. Rather, it exhibits striking systematic variation. We conjecture that these gradients, which establish the basic landscape that richer areal and cellular structure is built upon, result from developmental patterns of cortical neurogenesis which are conserved across species. Moreover, we propose a functional consequence: that the gradient in neurons per unit of cortical area fosters the integration and dimensional reduction of information along its ascent through sensory areas and toward frontal cortex.

Use of flow cytometry for high-throughput cell population estimates in brain tissue

The large size of primate brains is an impediment to obtaining high-resolution cell number maps of the cortex in humans and non-human primates. We present a rapid, flow cytometry-based cell counting method that can be used to estimate cell numbers from homogenized brain tissue samples comprising the entire cortical sheet. The new method, called the flow fractionator, is based on the isotropic fractionator (IF) method (Herculano-Houzel and Lent, 2005), but substitutes flow cytometry analysis for manual, microscope analysis using a Neubauer counting chamber. We show that our flow cytometry-based method for total cell estimation in homogenized brain tissue provides comparable data to that obtained using a counting chamber on a microscope. The advantages of the flow fractionator over existing methods are improved precision of cell number estimates and improved speed of analysis.