What is the significance of neocortical neurons

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Pedregosa, F. Scikit-learn: machine learning in Python. Open Source Softw. Article Google Scholar. Seabold, S. In Proc. Supek, F. PLoS One 6 , e Download references. We thank A. Wanner for providing reconstruction services through A. Szeto and R. Szeto, and Z. Popovic for facilitating the reconstruction work contributed by Mozak. We also thank the Mozak citizen scientists for their valuable contribution. The content is solely the responsibility of the authors and does not necessarily represent the official views of NIH and its subsidiary institutes.

This work was funded by the Allen Institute for Brain Science. We dedicate this paper to the vision, encouragement, and long-term support of our founder, Paul G.

These authors contributed equally: Jim Berg, Staci A. Sorensen, Jonathan T. Ting, Jeremy A. Jim Berg, Staci A. Gouwens, Rebecca D. Levi, Katherine E. Sunkin, Aaron Szafer, Elliot R. Hawrylycz, Allan R. Jones, Gabe J. Murphy, Lydia Ng, John W. Jonathan T. Dirk Keene. Anna A. Galakhova, Natalia A. Goriounova, Tim S. Heistek, Djai B. Heyer, Eline J. Richard G. Ellenbogen, Manuel Ferreira, Andrew L.

Ko, Jeffrey G. However, a systematic analysis of synapse density in the neocortex from a diversity of species is lacking, limiting what can be understood about the evolution of this fundamental aspect of brain structure. To address this, we quantified synapse density in supragranular layers II—III and infragranular layers V—VI from primary visual cortex and inferior temporal cortex in a sample of 25 species of primates, including humans.

We found that synapse densities were relatively constant across these levels of the cortical visual processing hierarchy and did not significantly differ with brain mass, varying by only 1.

We also found that neuron densities decreased in relation to brain enlargement. Consequently, these data show that the number of synapses per neuron significantly rises as a function of brain expansion in these neocortical areas of primates. Humans displayed the highest number of synapses per neuron, but these values were generally within expectations based on brain size. The metabolic and biophysical constraints that regulate uniformity of synapse density, therefore, likely underlie a key principle of neuronal connectivity scaling in primate neocortical evolution.

Synapses are the site of interneuronal communication and consume the majority of metabolic energy in the brain Karbowski ; Magistretti and Allaman The density of synapses in a region of the brain, therefore, may be functionally significant and reflect the integrative capacity of local neurons.

In primates, cortical pyramidal neurons generally harbor a greater density of dendritic spines, the sites of excitatory synaptic contacts, in higher-order association areas than in primary sensory and motor regions Elston et al. In addition, pyramidal neurons in prefrontal and temporal cortices of primates have been shown to display increased dendritic branching and greater synaptic spine numbers in correlation with brain enlargement Elston et al.

Although such comparative data on pyramidal neuron dendritic morphology and spine numbers provide important insight into regional specializations of cortical processing, synapse density itself has not yet been systematically evaluated in the cerebral cortex. Although some authors have claimed that there is relative invariance of synapse density per unit tissue volume in the adult mammalian neocortex e. Here we examined synapse and neuron density in primates in relation to brain size to provide a more complete understanding of connectivity scaling in neocortical evolution.

We quantified synapse and neuron densities in supragranular layers II—III and infragranular layers V—VI of primary visual cortex V1 and inferior temporal cortex IT across 25 phylogenetically diverse species of primates. Synapses were labeled using immunohistochemical staining against synaptophysin SYP , a protein that is ubiquitously present in vesicles of presynaptic terminals Calhoun et al.

Area V1 and IT cortex represent two distinct hierarchical levels of functional processing within the ventral visual stream. Supragranular and infragranular cortical layers contain neurons that project predominantly to other cortical regions and to non-cortical brain structures, respectively Gilbert and Kelly ; Barbas ; Nudo and Masterton Accordingly, the present study allows for a comprehensive investigation of synapse distributions in primates across variation in phylogeny, brain size, levels of cortical processing, and connectivity profile.

All brains were from adults above the age of species-typical sexual maturity. Reference data on age of sexual maturity and maximum longevity for each species were taken from the Human Aging Genomic Resources AnAge database Tacutu et al. Only two individuals in the sample were from the upper quartile of their species-specific adult lifespan Ateles belzebuth and Tarsius bancanus.

Nonhuman primate specimens came from individuals that lived in zoos and research centers. Neither of the human subjects had a reported history of neurological or psychiatric disorders.

Although human prefrontal cortex neurons undergo prolonged synaptic overproduction in development and are not pruned to adult-like levels until the third decade of life Petanjek et al. Therefore, we considered the year-old male to be generally representative of a typical adult for the regions we analyzed here. Postmortem brains appeared normal upon routine neuropathology evaluation. All experimental procedures with postmortem tissue were carried out according to the National Institutes of Health guidelines for animal research and were approved by the Institutional Animal Care and Use Committee at the George Washington University.

After fixation, brains were then transferred to 0. The ranges of sections containing area V1 and IT cortex were identified by comparing the Nissl-stained sections to publications that illustrate the location of the relevant cortical areas in primates Figure 2A Preuss and Goldman-Rakic ; Fang et al. Area V1 and IT cortex are both considered to be homologous across primate phylogeny Rosa and Tweedale ; Kaas Three equidistantly spaced sections from freezer storage were selected from each cortical region of interest for synapse labeling.

A The locations of primary visual cortex V1 and inferior temporal IT cortex in three representative primate species of different brain sizes. We counted all SYP-immunoreactive puncta that had a spherical appearance with clear boundaries. Examples of stained puncta are indicated with arrowheads. Free-floating sections of the regions of interest were stained with rabbit polyclonal IgG 1 antibodies against synaptophysin SYP , which is an acidic, homo-oligomeric integral membrane glycoprotein localized in presynaptic vesicles dilution, A, DakoCytomation, Glostrup, Denmark.

SYP concentrations in human and rat cortex have been shown to be unaffected by postmortem intervals up to 72 h Siew et al. Prior to immunostaining, sections were rinsed thoroughly in PBS and pretreated for antigen retrieval by incubation in 10 mM sodium citrate buffer pH 3. Sections were rinsed and immersed in a solution of 0. Sections were rinsed again in PBS, followed by a rinse in sodium acetate buffer. After SYP immunostaining of sections, we reviewed slides for quality control before inclusion in our study.

To be used in further quantitative analyses, the sections needed to show a punctate distribution of immunostaining surrounding unstained ovoid and pyramidal shapes putatively corresponding to cell somata, which is consistent with the localization of presynaptic boutons Figure 2.

Employing these strict quality control criteria meant that several brain specimens that were initially processed and stained had to be excluded from further analysis. Three equidistantly spaced sections were chosen for stereologic analysis. Adjacent Nissl-stained sections of regions of interest were used to confirm the cytoarchitecture, to outline layer boundaries and to obtain counts of neurons. Because precise boundaries of layer IV may be difficult to discern, it was not included as a separate region of interest in the analysis.

These sampling parameters were chosen because SYP immunostaining does not penetrate the entire section. Measurement of mounted section thickness was collected at every fifth sampling site. Synapse counting was performed blind to species identity of the specimen. We counted all puncta that had a spherical appearance with clear boundaries irrespective of staining intensity, following the methods of previous studies Calhoun et al. Across all individuals and regions of interest in the study, this sampling design yielded on average Synapse density counts from the two older individuals in the sample Ateles belzebuth and Tarsius bancanus were not outliers.

Inter-rater reliability was determined by recounting SYP-immunoreactive puncta in 14 different regions of interest, which yielded an acceptable level of agreement with an intraclass correlation coefficient of 0. Neurons including large pyramidal cells and smaller interneurons were identified as distinct from glia by the presence of a visible cytoplasm surrounding a round or ovoid lightly stained nucleus and the frequent appearance of lightly stained proximal segments of dendritic processes.

Often a distinct nucleolus was evident, although small neurons may have small nucleoli surrounded by thick perinucleolar heterochromatin clumps. Neuronal densities were derived from these stereological counts as described above. Across all individuals in the study, this sampling design yielded All samples came from the right hemisphere, with the exception of Pan troglodytes , which came from the left hemisphere.

After embedding in Epon, nm ultrathin sections were collected on silicon wafers. Quantification of synapse density was then measured on digital images obtained from a Helios FIBSEM FEI with a concentric back scatter detector, at a working distance of approximately 4 mm.

Sampling fields covering the entire cortical width were chosen by using a systematic-random sampling method. Three montage images of the cortical width were quantified per individual. Criteria for identification of synapses included the presence of a synaptic junction and the appearance of at least two synaptic vesicles in the presynaptic component.

Symmetric and asymmetric synapses were pooled in this analysis. All species mean data used in analyses are presented in Supplementary Table 2. To account for the expected error structure due to the relatedness among species in this comparative sample, we employed phylogenetic generalized least-squares procedures pGLS.

The pGLS procedures allow performing all tests of standard least-squares analysis but additionally account for phylogenetic relatedness by including a variance-covariance matrix of shared ancestry in the error term of the standard GLS equation Rohlf The variance-covariance matrix of phylogenetic relatedness is further adjusted for the extent to which the data adhere to a pure gradual model of evolution using a likelihood-fitted lambda transformation Pagel Lambda varies between 0 and 1, where 0 indicates that traits covary independently of their degree of shared ancestry and 1 indicates that traits covary in a manner accurately described by their degree of shared ancestry.

We obtained a phylogeny of the primate species in the sample from the 10 k Trees website Arnold et al. To determine the scaling relationships in our dataset, we employed pGLS regression analysis on log-transformed data. In these scaling analyses, both dependent and independent variables contain similar error from any shrinkage fixation artifact that might be present in the sample. As a result, individual data points might shift along the major axis of the regression, but slope and intercept calculations are not significantly altered.

To test for differences in slope and intercept among regions of interest, and to test for differences in intercepts of human data points for particular regions of interest, standard extensions of pGLS procedures were employed Smaers and Rohlf Within the pGLS framework, the strength of fit across different regressions was calculated using the Brownian motion rate parameter sigma2 of the residuals. This rate parameter calculates accumulation of variance over time. Given that variables are measured in the same sample with a common phylogenetic tree, differences in this rate parameter indicate differences among measures in the accumulation of residual variance and the strength of allometric integration i.

Low sigma2 rates indicate little residual variation high strength of allometric integration , and high rates indicate high residual variation low strength of allometric integration. We used brain mass as an independent scaling variable in our analyses because it was recorded from the same individuals as histological measures of synapse and neuron densities. Notably, interspecific variation in overall brain mass of primates has been shown to be closely associated with neocortical size and neuron number Charvet and Finlay ; Herculano-Houzel et al.

Therefore, the scaling relationships related to brain mass we observe here are likely to reflect scaling to the neocortex more specifically. Figure 3 provides an overview of synapse densities, neuron densities, and numbers of synapses per neuron across the phylogeny of primates in our sample.

Synapse densities in supragranular and infragranular layers of area V1 and IT cortex were not associated with brain size Figure 4A. Furthermore, pGLS analyses showed that slopes and intercepts did not significantly differ among cortical regions Supplementary Table 3. The range of synapse density observed across the total sample was 1. On average, supragranular layers in both cortical areas have approximately Overview of synapse densities, neuron densities, and numbers of synapses per neuron across the phylogeny of primates in our sample.

C The density of synapses as measured from electron microscopy in V1 from selected primate species, with their respective brain masses arranged in increasing size order. Electron microscopy evaluation of synapses directly from ultrastructure showed agreement with SYP immunostaining in finding invariant synapse density across species, although the densities observed from electron microscopy were higher overall, which is consistent with other studies DeFelipe et al.

By contrast, neuron densities displayed a significant negative relationship with brain mass Figure 4B. In each cortical area and layer, neuron densities decreased as a function of increasing brain mass Table 1. Area V1 tended to have higher neuron density than IT cortex in this sample of primate species. We tested whether synapse densities within each cortical area and layer were associated with neuron densities and found that they were independent of each other Table 1 ; Figure 6.

This range represents a 7. We found that synapse density is relatively uniform in the primate neocortex, as observed across variation in brain size and levels of the processing hierarchy in supragranular and infragranular layers of primary visual cortex V1 and inferior temporal association cortex IT. These results provide a more comprehensive context to understand the scaling of synaptic integration by cortical neurons and energetic constraints in primate brain evolution.

Invariance of synapse density is congruent with data indicating that other aspects of synapse biology are highly conserved in neocortical evolution. The length of the postsynaptic density and overall size of synapses vary minimally with developmental stage, aging, and brain size among mammals reviewed in Karbowski , This likely impacts aspects of cellular and systems function, such as discharge properties and memory storage capacity Ashford and Fuster ; Murayama et al.

Theoretically, neocortical pyramidal neurons with expansive dendritic trees and thousands of synapses are modeled to be capable of recognizing hundreds of independent patterns of cellar activity, even in the presence of large amount of noise and signal variability Hawkins and Ahmad Increased complexity of dendritic structure and greater numbers of synapses determines the biophysical properties of neurons and the potential for plasticity Chklovskii et al.

Differences in the number of synapses incorporated by neurons may influence local summation, the degree of dendritic compartmentalization of processing, and the inhibitory control of inputs White ; Koch Smaller neurons with fewer synapses have a higher input resistance and greater evoked action potential firing rate as compared to neurons with more synapses Amatrudo et al.

Area V1 neurons, accordingly, have physiological properties of being highly excitable, which is optimal for signal transformations with high fidelity Olshausen and Field This contrasts with higher-order association cortex, such as IT cortex, which contains neurons with many synapses that integrate a greater diversity of inputs along more complex dendritic arbors Elston et al. This neuronal morphology is consistent with excitatory events of larger amplitude and longer decay time, making them better suited for facilitating sustained activation, coincidence detection, and spike-timing dependent plasticity for a wider dynamic range of information integration Constantinidis and Wang The functional relationship between synapses and neurons in the neocortex is limited by energy availability.

The consistency of synapse structure and distributions may be associated with constant glial density, which has also been reported in adult mammalian neocortex Herculano-Houzel , Glucose taken up by astrocytes is coupled to neuronal energetics through glutamate-mediated synaptic transmission Magistretti and Allaman , suggesting that synapses and glia are anatomically and functionally interrelated in a manner that is governed by energetic constraints per unit cortical tissue volume.

Synapse distribution differences across cortical layers are likely to also be functionally significant. Neurons in supragranular layers generally furnish corticocortical projections, whereas infragranular layer neurons tend to form connections between cortex and other brain areas Gilbert and Kelly ; Barbas ; Nudo and Masterton Neocortical histological organization develops in a sequence with pyramidal neurons of the deepest layers generated first and neurons exiting the stem cell pool later migrating to the more superficial layers of the cortical plate McConnell Furthermore, in humans and macaques, there is evidence that there is a higher degree of synaptic overproduction prior to the pruning phase in supragranular layers versus infragranular layers in postnatal development, with especially pronounced dendritic spine overproduction of pyramidal neurons in cortical association areas compared to primary sensory regions Bourgeois et al.

Thus, extended synaptic formation in supragranular layers may lend a further channel for the development of complex corticocortical networks that are shaped by experience and learning in primate brain evolution. These comparative data from 25 primate species allows us to view human neocortical synapse distributions in a phylogenetic context. Consistent with this finding, compared to other primates, pyramidal neurons of the human neocortex, especially prefrontal association cortex, have been demonstrated to display more complex dendritic branching, greater neuropil fraction, and wider spacing between minicolumns Elston et al.

Furthermore, since the last common ancestor shared by humans-chimpanzees-bonobos, the gene SRGAP2 underwent a series of duplications in the human lineage Dennis et al.

The human-specific paralog interferes with the ancestral copy of SRGAP2 and regulates synapse development, resulting in protracted synapse maturation and increased dendritic spine density of neocortical pyramidal neurons Charrier et al.

Additionally, comparative gene expression profiling from human prefrontal cortex has revealed developmental delays in synapse-associated transcripts, which may prolong the period of plasticity of higher-order cortical networks Liu et al. Molecular modifications of synaptic strength, which occurs during the period of developmental overproduction and elimination of synapses, are thought to be important for incorporating environmental influences in circuit reorganization because they occur when the magnitude of plasticity of dendritic spines is greatest Rakic et al.