All brains are made of this: a fundamental building block of brain matter with matching neuronal and glial masses

Enabling Electric Field Modeling of Microscopically Realistic Brain

Across all domains of brain stimulation (neuromodulation), conventional analysis of neuron activation involves two discrete steps: i) prediction of macroscopic electric field, ignoring presence of cells and; ii) prediction of cell activation from tissue electric fields. The first step assumes that current flow is not distorted by the dense tortuous network of cell structures. The deficiencies of this assumption have long been recognized, but - except for trivial geometries - ignored, because it presented intractable computation hurdles. This study introduces a novel approach for analyzing electric fields within a microscopically realistic brain volume. Our pipeline overcomes the technical intractability that prevented such analysis while also showing significant implications for brain stimulation. Contrary to the standard finite element method (FEM), we suggest using a nested iterative boundary element method (BEM) coupled with the fast multipole method (FMM). This approach allows for solving problems with multiple length scales more efficiently. A target application is a subvolume of the L2/3 P36 mouse primary visual cortex containing approximately 400 detailed densely packed neuronal cells at a resolution of 100 nm, which is obtained from scanning electron microscopy data. Our immediate result is a reduction of the stimulation field strength necessary for neuron activation by a factor of 0.85-0.55 (by 15%-45%) as compared to macroscopic predictions. This is in line with modern experimental data stating that existing macroscopic theories substantially overestimate electric field levels necessary for brain stimulation.

A 3D atlas of functional human brain energetic connectome based on neuropil distribution

The human brain is energetically expensive, yet the key factors governing its heterogeneous energy distributions across cortical regions to support its diversity of functions remain unexplored. Here, we built up a 3D digital cortical energy atlas based on the energetic costs of all neuropil activities into a high-resolution stereological map of the human cortex with cellular and synaptic densities derived, respectively, from ex vivo histological staining and in vivo PET imaging. The atlas was validated with PET-measured glucose oxidation at the voxel level. A 3D cortical activity map was calculated to predict the heterogeneous activity rates across all cortical regions, which revealed that resting brain is indeed active with heterogeneous neuronal activity rates averaging around 1.2 Hz, comprising around 70% of the glucose oxidation of the cortex. Additionally, synaptic density dominates spatial patterns of energetics, suggesting that the cortical energetics rely heavily on the distribution of synaptic connections. Recent evidence from functional imaging studies suggests that some cortical areas act as hubs (i.e., interconnecting distinct and functionally active regions). An inverse allometric relationship was observed between hub metabolic rates versus hub volumes. Hubs with smaller volumes have higher synapse density, metabolic rate, and activity rates compared to nonhubs. The open-source BrainEnergyAtlas provides a granular framework for exploring revealing design principles in energy-constrained human cortical circuits across multiple spatial scales.

Regressive changes in sizes of somatosensory cuneate nucleus after sensory loss in primates

Neurons in the early stages of processing sensory information suffer transneuronal atrophy when deprived of their activating inputs. For over 40 y, members of our laboratory have studied the reorganization of the somatosensory cortex during and after recovering from different types of sensory loss. Here, we took advantage of the preserved histological material from these studies of the cortical effects of sensory loss to evaluate the histological consequences in the cuneate nucleus of the lower brainstem and the adjoining spinal cord. The neurons in the cuneate nucleus are activated by touch on the hand and arm, and relay this activation to the contralateral thalamus, and from the thalamus to the primary somatosensory cortex. Neurons deprived of activating inputs tend to shrink and sometimes die. We considered the effects of differences in species, type and extent of sensory loss, recovery time after injury, and age at the time of injury on the histology of the cuneate nucleus. The results indicate that all injuries that deprived part or all of the cuneate nucleus of sensory activation result in some atrophy of neurons as reflected by a decrease in nucleus size. The extent of the atrophy is greater with greater sensory loss and with longer recovery times. Based on supporting research, atrophy appears to involve a reduction in neuron size and neuropil, with little or no neuron loss. Thus, the potential exists for restoring the hand to cortex pathway with brain-machine interfaces, for bionic prosthetics, or biologically with hand replacement surgery.

Neuronal and non-neuronal scaling across brain regions within an intercross of domestic and wild chickens

The allometric scaling of the brain size and neuron number across species has been extensively studied in recent years. With the exception of primates, parrots, and songbirds, larger brains have more neurons but relatively lower neuronal densities than smaller brains. Conversely, when considering within-population variability, it has been shown that mice with larger brains do not necessarily have more neurons but rather more neurons in the brain reflect higher neuronal density. To what extent this intraspecific allometric scaling pattern of the brain applies to individuals from other species remains to be explored. Here, we investigate the allometric relationships among the sizes of the body, brain, telencephalon, cerebellum, and optic tectum, and the numbers of neurons and non-neuronal cells of the telencephalon, cerebellum, and optic tectum across 66 individuals originated from an intercross between wild and domestic chickens. Our intercross of chickens generates a population with high variation in brain size, making it an excellent model to determine the allometric scaling of the brain within population. Our results show that larger chickens have larger brains with moderately more neurons and non-neuronal cells. Yet, absolute number of neurons and non-neuronal cells correlated strongly and positively with the density of neurons and non-neuronal cells, respectively. As previously shown in mice, this scaling pattern is in stark contrast with what has been found across different species. Our findings suggest that neuronal scaling rules across species are not a simple extension of the neuronal scaling rules that apply within a species, with important implications for the evolutionary developmental origins of brain diversity.

Avian neurons consume three times less glucose than mammalian neurons

Brains are among the most energetically costly tissues in the mammalian body.¹ This is predominantly caused by expensive neurons with high glucose demands.² Across mammals, the neuronal energy budget appears to be fixed, possibly posing an evolutionary constraint on brain growth.^3-6 Compared to similarly sized mammals, birds have higher numbers of neurons, and this advantage conceivably contributes to their cognitive prowess.⁷ We set out to determine the neuronal energy budget of birds to elucidate how they can metabolically support such high numbers of neurons. We estimated glucose metabolism using positron emission tomography (PET) and 2-[¹⁸F]fluoro-2-deoxyglucose ([¹⁸F]FDG) as the radiotracer in awake and anesthetized pigeons. Combined with kinetic modeling, this is the gold standard to quantify cerebral metabolic rate of glucose consumption (CMR_glc).⁸ We found that neural tissue in the pigeon consumes 27.29 ± 1.57 μmol glucose per 100 g per min in an awake state, which translates into a surprisingly low neuronal energy budget of 1.86 × 10^-9 ± 0.2 × 10^-9 μmol glucose per neuron per minute. This is approximately 3 times lower than the rate in the average mammalian neuron.³ The remarkably low neuronal energy budget explains how pigeons, and possibly other avian species, can support such high numbers of neurons without associated metabolic costs or compromising neuronal signaling. The advantage in neuronal processing of information at a higher efficiency possibly emerged during the distinct evolution of the avian brain.

Energy supply per neuron is constrained by capillary density in the mouse brain

Neuronal densities vary enormously across sites within a brain. Does the density of the capillary bed vary accompanying the presumably larger energy requirement of sites with more neurons, or with larger neurons, or is energy supply constrained by a mostly homogeneous capillary bed? Here we find evidence for the latter, with a capillary bed that represents typically between 0.7 and 1.5% of the volume of the parenchyma across various sites in the mouse brain, whereas neuronal densities vary by at least 100-fold. As a result, the ratio of capillary cells per neuron decreases uniformly with increasing neuronal density and therefore with smaller average neuronal size across sites. Thus, given the relatively constant capillary density compared to neuronal density in the brain, blood and energy availability per neuron is presumably dependent on how many neurons compete for the limited supply provided by a mostly homogeneous capillary bed. Additionally, we find that local capillary density is not correlated with local synapse densities, although there is a small but significant correlation between lower neuronal density (and therefore larger neuronal size) and more synapses per neuron within the restricted range of 6,500–9,500 across cortical sites. Further, local variations in the glial/neuron ratio are not correlated with local variations in the number of synapses per neuron or local synaptic densities. These findings suggest that it is not that larger neurons, neurons with more synapses, or even sites with more synapses demand more energy, but simply that larger neurons (in low density sites) have more energy available per cell and for the totality of its synapses than smaller neurons (in high density sites) due to competition for limited resources supplied by a capillary bed of fairly homogeneous density throughout the brain.

Resting Rates of Blood Flow and Glucose Use per Neuron Are Proportional to Number of Endothelial Cells Available per Neuron Across Sites in the Rat Brain

We report in a companion paper that in the mouse brain, in contrast to the 1,000-fold variation in local neuronal densities across sites, capillary density (measured both as capillary volume fraction and as density of endothelial cells) show very little variation, of the order of only fourfold. Here we confirm that finding in the rat brain and, using published rates of local blood flow and glucose use at rest, proceed to show that what small variation exists in capillary density across sites in the rat brain is strongly and linearly correlated to variations in local rates of brain metabolism at rest. Crucially, we show that such variations in local capillary density and brain metabolism are not correlated with local variations in neuronal density, which contradicts expectations that use-dependent self-organization would cause brain sites with more neurons to have higher capillary densities due to higher energetic demands. In fact, we show that the ratio of endothelial cells per neuron serves as a linear indicator of average blood flow and glucose use per neuron at rest, and both increase as neuronal density decreases across sites. In other words, because of the relatively tiny variation in capillary densities compared to the large variation in neuronal densities, the anatomical infrastructure of the brain is such that those sites with fewer neurons have more energy supplied per neuron, which matches a higher average rate of energy use per neuron, compared to sites with more neurons. Taken together, our data support the interpretation that resting brain metabolism is not demand-based, but rather limited by its capillary supply, and raise multiple implications for the differential vulnerability of diverse brain areas to disease and aging.

Brain region specificity in reactive oxygen species production and maintenance of redox balance

The brain produces various reactive oxygen species in enzymatic and non-enzymatic reactions as a by-product of metabolism and/or for redox signaling. Effective antioxidant system in the brain cells maintains redox balance. However, neurons and glia from some brain regions are more vulnerable to oxidative stress in ischemia/reperfusion, epilepsy, and neurodegenerative disorders than the rest of the brain. Using fluorescent indicators in live cell imaging and confocal microscopy, we have measured the rate of cytosolic and mitochondrial reactive oxygen species production, lipid peroxidation, and glutathione levels in cortex, hippocampus, midbrain, brain stem and cerebellum in acute slices of rat brain. We have found that the basal rate of ROS production is at its highest in brain stem and cerebellum, and that it is mainly generated by glial cells. Activation of neurons and glia by glutamate and ATP led to maximal rates of ROS production in the midbrain compared to the rest of the brain. Mitochondrial ROS had only minor implication to the total ROS production with maximal values in the cortex and minimal in the midbrain. The basal rate of lipid peroxidation was higher in the midbrain and hippocampus, while the GSH level was similar in most brain regions with the lowest level in the midbrain. Thus, the rate of ROS production, lipid peroxidation and the level of GSH vary across brain regions.

Structural changes in brains of patients with disorders of consciousness treated with deep brain stimulation

Disorders of consciousness (DOC) are one of the major consequences after anoxic or traumatic brain injury. So far, several studies have described the regaining of consciousness in DOC patients using deep brain stimulation (DBS). However, these studies often lack detailed data on the structural and functional cerebral changes after such treatment. The aim of this study was to conduct a volumetric analysis of specific cortical and subcortical structures to determine the impact of DBS after functional recovery of DOC patients. Five DOC patients underwent unilateral DBS electrode implantation into the centromedian parafascicular complex of the thalamic intralaminar nuclei. Consciousness recovery was confirmed using the Rappaport Disability Rating and the Coma/Near Coma scale. Brain MRI volumetric measurements were done prior to the procedure, then approximately a year after, and finally 7 years after the implementation of the electrode. The volumetric analysis included changes in regional cortical volumes and thickness, as well as in subcortical structures. Limbic cortices (parahippocampal and cingulate gyrus) and paralimbic cortices (insula) regions showed a significant volume increase and presented a trend of regional cortical thickness increase 1 and 7 years after DBS. The volumes of related subcortical structures, namely the caudate, the hippocampus as well as the amygdala, were significantly increased 1 and 7 years after DBS, while the putamen and nucleus accumbens presented with volume increase. Volume increase after DBS could be a result of direct DBS effects, or a result of functional recovery. Our findings are in accordance with the results of very few human studies connecting DBS and brain volume increase. Which mechanisms are behind the observed brain changes and whether structural changes are caused by consciousness recovery or DBS in patients with DOC is still a matter of debate.

Microglial Density Alters Measures of Axonal Integrity and Structural Connectivity

Diffusion tensor imaging (DTI) has fundamentally transformed how we interrogate diseases and disorders of the brain in neuropsychiatric illness. DTI and recently developed multicompartment diffusion-weighted imaging (MC-DWI) techniques, such as NODDI (neurite orientation dispersion and density imaging), measure diffusion anisotropy presuming a static neuroglial environment; however, microglial morphology and density are highly dynamic in psychiatric illness, and how alterations in microglial density might influence intracellular measures of diffusion anisotropy in DTI and MC-DWI brain microstructure is unknown. To address this question, DTI and MC-DWI studies of murine brains depleted of microglia were performed, revealing significant alterations in axonal integrity and fiber tractography in DTI and in commonly used MC-DWI models. With accumulating evidence of the role of microglia in neuropsychiatric illness, our findings uncover the unexpected contribution of microglia to measures of axonal integrity and structural connectivity and provide unanticipated insights into the potential influence of microglia in diffusion imaging studies of neuropsychiatric disease.

Cholinergic Modulation of Glial Function During Aging and Chronic Neuroinflammation

Aging is a complex biological process that increases the risk of age-related cognitive degenerative diseases such as dementia, including Alzheimer’s disease (AD), Lewy Body Dementia (LBD), and mild cognitive impairment (MCI). Even non-pathological aging of the brain can involve chronic oxidative and inflammatory stress, which disrupts the communication and balance between the brain and the immune system. There has been an increasingly strong connection found between chronic neuroinflammation and impaired memory, especially in AD. While microglia and astrocytes, the resident immune cells of the central nervous system (CNS), exerting beneficial effects during the acute inflammatory phase, during chronic neuroinflammation they can become more detrimental. Central cholinergic circuits are involved in maintaining normal cognitive function and regulating signaling within the entire cerebral cortex. While neuronal-glial cholinergic signaling is anti-inflammatory and anti-oxidative, central cholinergic neuronal degeneration is implicated in impaired learning, memory sleep regulation, and attention. Although there is evidence of cholinergic involvement in memory, fewer studies have linked the cholinergic anti-inflammatory and anti-oxidant pathways to memory processes during development, normal aging, and disease states. This review will summarize the current knowledge of cholinergic effects on microglia and astroglia, and their role in both anti-inflammatory and anti-oxidant mechanisms, concerning normal aging and chronic neuroinflammation. We provided details on how stimulation of α7 nicotinic acetylcholine (α7nACh) receptors can be neuroprotective by increasing amyloid-β phagocytosis, decreasing inflammation and reducing oxidative stress by promoting the nuclear factor erythroid 2-related factor 2 (Nrf2) pathways and decreasing the release of pro-inflammatory cytokines. There is also evidence for astroglial α7nACh receptor stimulation mediating anti-inflammatory and antioxidant effects by inhibiting the nuclear factor-κB (NF-κB) pathway and activating the Nrf2 pathway respectively. We conclude that targeting cholinergic glial interactions between neurons and glial cells via α7nACh receptors could regulate neuroinflammation and oxidative stress, relevant to the treatment of several neurodegenerative diseases.

Electrochemical detection of neuronal extracellular phosphorylation by PKA, PKC and Src

The focus of this work described here is to establish a method for monitoring and quantifying the extracellular phosphorylation of Human SHSY5Y undifferentiated neuronal cells by three ectokinases PKA, PKC and Src; these are kinases that are known to be present in the extracellular matrix. Here is demonstrated that a combination of different experimental techniques, including microscopy and electrochemistry, can be used to detect extracellular phosphorylations. Phosphorylation profiles of the three ectokinases, PKA, PKC and Src, were investigated using fluorescence microscopy and the number of phosphorylation sites per kinase was estimated using QCM. Finally, the phosphorylation of the extracellular membrane was determined using electrochemistry. Our results clearly demonstrate the extracellular phosphorylation of neuronal cells and the strength of surface electrochemical techniques in the investigation of cellular phosphorylation.

Similar Microglial Cell Densities across Brain Structures and Mammalian Species: Implications for Brain Tissue Function

Microglial cells play essential volume-related actions in the brain that contribute to the maturation and plasticity of neural circuits that ultimately shape behavior. Microglia can thus be expected to have similar cell sizes and even distribution both across brain structures and across species with different brain sizes. To test this hypothesis, we determined microglial cell densities (the inverse of cell size) using immunocytochemistry to Iba1 in samples of free cell nuclei prepared with the isotropic fractionator from brain structures of 33 mammalian species belonging to males and females of five different clades. We found that microglial cells constitute ∼7% of non-neuronal cells in different brain structures as well as in the whole brain of all mammalian species examined. Further, they vary little in cell density compared with neuronal cell densities within the cerebral cortex, across brain structures, across species within the same clade, and across mammalian clades. As a consequence, we find that one microglial cell services as few as one and as many as 100 neurons in different brain regions and species, depending on the local neuronal density. We thus conclude that the addition of microglial cells to mammalian brains is governed by mechanisms that constrain the size of these cells and have remained conserved over 200 million years of mammalian evolution. We discuss the probable consequences of such constrained size for brain function in health and disease.SIGNIFICANCE STATEMENT Microglial cells are resident macrophages of the CNS, with key functions in recycling synapses and maintaining the local environment in health and disease. We find that microglial cells occur in similar densities in the brains of different species and in the different structures of each individual brain, which indicates that these cells maintain a similar average size in mammalian evolution, suggesting in turn that the volume monitored by each microglial cell remains constant across mammals. Because the density of neurons is highly variable across the same brain structures and species, our finding implies that microglia-dependent functional recovery may be particularly difficult in those brain structures and species with high neuronal densities and therefore fewer microglial cells per neuron.

Proteomic examination of the neuroglial secretome: lessons for the clinic

Introduction: Glial cells are closely associated with neurons located throughout the nervous system and regulate neuronal activity and function through various mechanisms including the secretion of proteins and other signaling molecules. Glia-secreted proteins play crucial roles in modulating neuronal function in physiological and pathological conditions. Aberrant activation of glial cells leading to neuroinflammation is a common phenomenon observed in various neurological disorders. Aberrantly activated glial cells secrete proteins in disease-specific manner and can be exploited as a repository for novel biomarker discovery.Areas covered: In this review, we describe the recent advances in proteomic techniques, highlighting the need for their application to the secretomic field. Studies regarding the secretome profile of glial cells published within the last 5 years are discussed in detail. The use of glia-based biomarkers in various neuroinflammatory and neurodegenerative diseases is also discussed.Expert opinion: Precise diagnosis and timely treatment of neurological disorders remains a challenge and glia-focused research to identify specific biomarkers appears to be a promising approach to combat these disorders. Recent technological advancement in proteomic research would open new frontiers for more rigorous analysis of glial secretome variations over time and the discovery/development of novel biomarkers for neurological disorders.

A Model of Brain Folding Based on Strong Local and Weak Long-Range Connectivity Requirements

Throughout the animal kingdom, the structure of the central nervous system varies widely from distributed ganglia in worms to compact brains with varying degrees of folding in mammals. The differences in structure may indicate a fundamentally different circuit organization. However, the folded brain most likely is a direct result of mechanical forces when considering that a larger surface area of cortex packs into the restricted volume provided by the skull. Here, we introduce a computational model that instead of modeling mechanical forces relies on dimension reduction methods to place neurons according to specific connectivity requirements. For a simplified connectivity with strong local and weak long-range connections, our model predicts a transition from separate ganglia through smooth brain structures to heavily folded brains as the number of cortical columns increases. The model reproduces experimentally determined relationships between metrics of cortical folding and its pathological phenotypes in lissencephaly, polymicrogyria, microcephaly, autism, and schizophrenia. This suggests that mechanical forces that are known to lead to cortical folding may synergistically contribute to arrangements that reduce wiring. Our model provides a unified conceptual understanding of gyrification linking cellular connectivity and macroscopic structures in large-scale neural network models of the brain.

Co-evolution of cerebral and cerebellar expansion in cetaceans

Cetaceans possess brains that rank among the largest to have ever evolved, either in terms of absolute mass or relative to body size. Cetaceans have evolved these huge brains under relatively unique environmental conditions, making them a fascinating case study to investigate the constraints and selection pressures that shape how brains evolve. Indeed, cetaceans have some unusual neuroanatomical features, including a thin but highly folded cerebrum with low cortical neuron density, as well as many structural adaptations associated with acoustic communication. Previous reports also suggest that at least some cetaceans have an expanded cerebellum, a brain structure with wide‐ranging functions in adaptive filtering of sensory information, the control of motor actions, and cognition. Here, we report that, relative to the size of the rest of the brain, both the cerebrum and cerebellum are dramatically enlarged in cetaceans and show evidence of co‐evolution, a pattern of brain evolution that is convergent with primates. However, we also highlight several branches where cortico‐cerebellar co‐evolution may be partially decoupled, suggesting these structures can respond to independent selection pressures. Across cetaceans, we find no evidence of a simple linear relationship between either cerebrum and cerebellum size and the complexity of social ecology or acoustic communication, but do find evidence that their expansion may be associated with dietary breadth. In addition, our results suggest that major increases in both cerebrum and cerebellum size occurred early in cetacean evolution, prior to the origin of the major extant clades, and predate the evolution of echolocation.

Life history changes accompany increased numbers of cortical neurons: A new framework for understanding human brain evolution

Narratives of human evolution have focused on cortical expansion and increases in brain size relative to body size, but considered that changes in life history, such as in age at sexual maturity and thus the extent of childhood and maternal dependence, or maximal longevity, are evolved features that appeared as consequences of selection for increased brain size, or increased cognitive abilities that decrease mortality rates, or due to selection for grandmotherly contribution to feeding the young. Here I build on my recent finding that slower life histories universally accompany increased numbers of cortical neurons across warm-blooded species to propose a simpler framework for human evolution: that slower development to sexual maturity and increased post-maturity longevity are features that do not require selection, but rather inevitably and immediately accompany evolutionary increases in numbers of cortical neurons, thus fostering human social interactions and cultural and technological evolution as generational overlap increases.

White matter volume and white/gray matter ratio in mammalian species as a consequence of the universal scaling of cortical folding

Because the white matter of the cerebral cortex contains axons that connect distant neurons in the cortical gray matter, the relationship between the volumes of the 2 cortical compartments is key for information transmission in the brain. It has been suggested that the volume of the white matter scales universally as a function of the volume of the gray matter across mammalian species, as would be expected if a global principle of wiring minimization applied. Using a systematic analysis across several mammalian clades, here we show that the volume of the white matter does not scale universally with the volume of the gray matter across mammals and is not optimized for wiring minimization. Instead, the ratio between volumes of gray and white matter is universally predicted by the same equation that predicts the degree of folding of the cerebral cortex, given the clade-specific scaling of cortical thickness, such that the volume of the gray matter (or the ratio of gray to total cortical volumes) divided by the square root of cortical thickness is a universal function of total cortical volume, regardless of the number of cortical neurons. Thus, the very mechanism that we propose to generate cortical folding also results in compactness of the white matter to a predictable degree across a wide variety of mammalian species.

Detecting Microglial Density With Quantitative Multi-Compartment Diffusion MRI

Neuroinflammation plays a central role in the neuropathogenesis of a wide-spectrum of neurologic and psychiatric disease, but current neuroimaging methods to detect and characterize neuroinflammation are limited. We explored the sensitivity of quantitative multi-compartment diffusion MRI, and specifically neurite orientation dispersion and density imaging (NODDI), to detect changes in microglial density in the brain. Monte Carlo simulations of water diffusion using a NODDI acquisition scheme were performed to measure changes in a virtual MRI signal following modeled cellular changes within the extra-neurite space. 12-week-old C57BL/6J male mice (n = 48; 24 control, 24 treated with colony stimulating factor 1 receptor (CSF1R) inhibitor, PLX5622) were sacrificed at 0, 1, 3, and 7 days following withdrawal of CSF1R inhibition and were imaged ex-vivo to obtain measures of the orientation dispersion index (ODI). Following imaging, all brains were immunostained with Iba-1, NeuN, and GFAP for quantitative fluorescence microscopy. Cell populations were calculated with the ImageJ particle analyzer tool; correlation between microglial density and mean ODI values were calculated with Kendall's tau. Monte Carlo simulations demonstrate the sensitivity and positive correlation of ODI to increased occupancy in the extra-neurite space. Commensurate with our simulation data, ex-vivo NODDI imaging demonstrates an increase in ODI as microglia repopulate the brain following the withdrawal of CSF1R inhibition. Quantitative immunofluorescence of microglial density reveals that microglial density is positively correlated with ODI and greater hindered diffusion in the extra-neurite space (τ = 0.386, p < 0.05). Our results demonstrate that clinically feasible multi-compartment diffusion weighted imaging techniques such as NODDI are sensitive to microglial density and the cellular changes associated with microglial activation and highlights its potential to improve clinical diagnostic accuracy, patient risk stratification, and therapeutic monitoring of neuroinflammation in neurologic and psychiatric disease.

Evaluating the gray and white matter energy budgets of human brain function

The insatiable appetite for energy to support human brain function is mainly supplied by glucose oxidation (CMR_glc(ox)). But how much energy is consumed for signaling and nonsignaling processes in gray/white matter is highly debated. We examined this issue by combining metabolic measurements of gray/white matter and a theoretical calculation of bottom-up energy budget using biophysical properties of neuronal/glial cells in conjunction with species-exclusive electrophysiological and morphological data. We calculated a CMR_glc(ox)-derived budget and confirmed it with experimental results measured by PET, autoradiography, ¹³C-MRS, and electrophysiology. Several conserved principles were observed regarding the energy costs for brain's signaling and nonsignaling components in both human and rat. The awake resting cortical signaling processes and mass-dependent nonsignaling processes, respectively, demand ∼70% and ∼30% of CMR_glc(ox). Inhibitory neurons and glia need 15-20% of CMR_glc(ox), with the rest demanded by excitatory neurons. Nonsignaling demands dominate in white matter, in near opposite contrast to gray matter demands. Comparison between ¹³C-MRS data and calculations suggests ∼1.2 Hz glutamatergic signaling rate in the awake human cortex, which is ∼4 times lower than signaling in the rat cortex. Top-down validated bottom-up budgets could allow computation of anatomy-based CMR_glc(ox) maps and accurate cellular level interpretation of brain metabolic imaging.

New Insights into Microglia-Neuron Interactions: A Neuron's Perspective

Microglia are the primary immune cells of the central nervous system. However, recent data indicate that microglia also contribute to diverse physiological and pathophysiological processes that extend beyond immune-related functions and there is a growing interest to understand the mechanisms through which microglia interact with other cells in the brain. In particular, the molecular processes that contribute to microglia-neuron communication in the healthy brain and their role in common brain diseases have been intensively studied during the last decade. In line with this, fate-mapping studies, genetic models and novel pharmacological approaches have revealed the origin of microglial progenitors, demonstrated the role of self-maintaining microglial populations during brain development or in adulthood, and identified the unexpectedly long lifespan of microglia that may profoundly change our view about senescence and age-related human diseases. Despite the exponentially increasing knowledge about microglia, the role of these cells in health and disease is still extremely controversial and the precise molecular targets for intervention are not well defined. This is in part due to the lack of microglia-specific manipulation approaches until very recently and to the high level of complexity of the interactions between microglia and other cells in the brain that occur at different temporal and spatial scales. In this review, we briefly summarize the known physiological roles of microglia-neuron interactions in brain homeostasis and attempt to outline some major directions and challenges of future microglia research.

Distribution of brain sodium long and short relaxation times and concentrations: a multi-echo ultra-high field 23Na MRI study

Sodium (²³Na) MRI proffers the possibility of novel information for neurological research but also particular challenges. Uncertainty can arise in in vivo ²³Na estimates from signal losses given the rapidity of T2* decay due to biexponential relaxation with both short (T₂*_short) and long (T₂*_long) components. We build on previous work by characterising the decay curve directly via multi-echo imaging at 7 T in 13 controls with the requisite number, distribution and range to assess the distribution of both in vivo T₂*_short and T₂*_long and in variation between grey and white matter, and subregions. By modelling the relationship between signal and reference concentration and applying it to in vivo ²³Na-MRI signal, ²³Na concentrations and apparent transverse relaxation times of different brain regions were measured for the first time. Relaxation components and concentrations differed substantially between regions of differing tissue composition, suggesting sensitivity of multi-echo ²³Na-MRI toward features of tissue composition. As such, these results raise the prospect of multi-echo ²³Na-MRI as an adjunct source of information on biochemical mechanisms in both physiological and pathophysiological states.

Quantitative sodium MR imaging: A review of its evolving role in medicine

Sodium magnetic resonance (MR) imaging in humans has promised metabolic information that can improve medical management in important diseases. This technology has yet to find a role in clinical practice, lagging proton MR imaging by decades. This review covers the literature that demonstrates that this delay is explained by initial challenges of low sensitivity at low magnetic fields and the limited performance of gradients and electronics available in the 1980s. These constraints were removed by the introduction of 3T and now ultrahigh (≥7T) magnetic field scanners with superior gradients and electronics for proton MR imaging. New projection pulse sequence designs have greatly improved sodium acquisition efficiency. The increased field strength has provided the expected increased sensitivity to achieve resolutions acceptable for metabolic interpretation even in small target tissues. Consistency of quantification of the sodium MR image to provide metabolic parametric maps has been demonstrated by several different pulse sequences and calibration procedures. The vital roles of sodium ion in membrane transport and the extracellular matrix will be reviewed to indicate the broad opportunities that now exist for clinical sodium MR imaging. The final challenge is for the technology to be supplied on clinical ≥3T scanners.

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

Carnivorans are a diverse group of mammals that includes carnivorous, omnivorous and herbivorous, domesticated and wild species, with a large range of brain sizes. Carnivory is one of several factors expected to be cognitively demanding for carnivorans due to a requirement to outsmart larger prey. On the other hand, large carnivoran species have high hunting costs and unreliable feeding patterns, which, given the high metabolic cost of brain neurons, might put them at risk of metabolic constraints regarding how many brain neurons they can afford, especially in the cerebral cortex. For a given cortical size, do carnivoran species have more cortical neurons than the herbivorous species they prey upon? We find they do not; carnivorans (cat, mongoose, dog, hyena, lion) share with non-primates, including artiodactyls (the typical prey of large carnivorans), roughly the same relationship between cortical mass and number of neurons, which suggests that carnivorans are subject to the same evolutionary scaling rules as other non-primate clades. However, there are a few important exceptions. Carnivorans stand out in that the usual relationship between larger body, larger cortical mass and larger number of cortical neurons only applies to small and medium-sized species, and not beyond dogs: we find that the golden retriever dog has more cortical neurons than the striped hyena, African lion and even brown bear, even though the latter species have up to three times larger cortices than dogs. Remarkably, the brown bear cerebral cortex, the largest examined, only has as many neurons as the ten times smaller cat cerebral cortex, although it does have the expected ten times as many non-neuronal cells in the cerebral cortex compared to the cat. We also find that raccoons have dog-like numbers of neurons in their cat-sized brain, which makes them comparable to primates in neuronal density. Comparison of domestic and wild species suggests that the neuronal composition of carnivoran brains is not affected by domestication. Instead, large carnivorans appear to be particularly vulnerable to metabolic constraints that impose a trade-off between body size and number of cortical neurons.

Cellular Scaling Rules for the Brains of Marsupials: Not as "Primitive" as Expected

In the effort to understand the evolution of mammalian brains, we have found that common relationships between brain structure mass and numbers of nonneuronal (glial and vascular) cells apply across eutherian mammals, but brain structure mass scales differently with numbers of neurons across structures and across primate and nonprimate clades. This suggests that the ancestral scaling rules for mammalian brains are those shared by extant nonprimate eutherians - but do these scaling relationships apply to marsupials, a sister group to eutherians that diverged early in mammalian evolution? Here we examine the cellular composition of the brains of 10 species of marsupials. We show that brain structure mass scales with numbers of nonneuronal cells, and numbers of cerebellar neurons scale with numbers of cerebral cortical neurons, comparable to what we have found in eutherians. These shared scaling relationships are therefore indicative of mechanisms that have been conserved since the first therians. In contrast, while marsupials share with nonprimate eutherians the scaling of cerebral cortex mass with number of neurons, their cerebella have more neurons than nonprimate eutherian cerebella of a similar mass, and their rest of brain has fewer neurons than eutherian structures of a similar mass. Moreover, Australasian marsupials exhibit ratios of neurons in the cerebral cortex and cerebellum over the rest of the brain, comparable to artiodactyls and primates. Our results suggest that Australasian marsupials have diverged from the ancestral Theria neuronal scaling rules, and support the suggestion that the scaling of average neuronal cell size with increasing numbers of neurons varies in evolution independently of the allocation of neurons across structures.

The search for true numbers of neurons and glial cells in the human brain: A review of 150 years of cell counting

For half a century, the human brain was believed to contain about 100 billion neurons and one trillion glial cells, with a glia:neuron ratio of 10:1. A new counting method, the isotropic fractionator, has challenged the notion that glia outnumber neurons and revived a question that was widely thought to have been resolved. The recently validated isotropic fractionator demonstrates a glia:neuron ratio of less than 1:1 and a total number of less than 100 billion glial cells in the human brain. A survey of original evidence shows that histological data always supported a 1:1 ratio of glia to neurons in the entire human brain, and a range of 40-130 billion glial cells. We review how the claim of one trillion glial cells originated, was perpetuated, and eventually refuted. We compile how numbers of neurons and glial cells in the adult human brain were reported and we examine the reasons for an erroneous consensus about the relative abundance of glial cells in human brains that persisted for half a century. Our review includes a brief history of cell counting in human brains, types of counting methods that were and are employed, ranges of previous estimates, and the current status of knowledge about the number of cells. We also discuss implications and consequences of the new insights into true numbers of glial cells in the human brain, and the promise and potential impact of the newly validated isotropic fractionator for reliable quantification of glia and neurons in neurological and psychiatric diseases. J. Comp. Neurol. 524:3865-3895, 2016. © 2016 Wiley Periodicals, Inc.

The search for true numbers of neurons and glial cells in the human brain: A review of 150 years of cell counting

For half a century, the human brain was believed to contain about 100 billion neurons and one trillion glial cells, with a glia:neuron ratio of 10:1. A new counting method, the isotropic fractionator, has challenged the notion that glia outnumber neurons and revived a question that was widely thought to have been resolved. The recently validated isotropic fractionator demonstrates a glia:neuron ratio of less than 1:1 and a total number of less than 100 billion glial cells in the human brain. A survey of original evidence shows that histological data always supported a 1:1 ratio of glia to neurons in the entire human brain, and a range of 40-130 billion glial cells. We review how the claim of one trillion glial cells originated, was perpetuated, and eventually refuted. We compile how numbers of neurons and glial cells in the adult human brain were reported and we examine the reasons for an erroneous consensus about the relative abundance of glial cells in human brains that persisted for half a century. Our review includes a brief history of cell counting in human brains, types of counting methods that were and are employed, ranges of previous estimates, and the current status of knowledge about the number of cells. We also discuss implications and consequences of the new insights into true numbers of glial cells in the human brain, and the promise and potential impact of the newly validated isotropic fractionator for reliable quantification of glia and neurons in neurological and psychiatric diseases. J. Comp. Neurol. 524:3865-3895, 2016. © 2016 Wiley Periodicals, Inc.

Quantitative sodium MRI of the human brain at 9.4 T provides assessment of tissue sodium concentration and cell volume fraction during normal aging

Sodium ion homeostasis is a fundamental property of viable tissue, allowing the tissue sodium concentration to be modeled as the tissue cell volume fraction. The modern neuropathology literature using ex vivo tissue from selected brain regions indicates that human brain cell density remains constant during normal aging and attributes the volume loss that occurs with advancing age to changes in neuronal size and dendritic arborization. Quantitative sodium MRI performed with the enhanced sensitivity of ultrahigh-field 9.4 T has been used to investigate tissue cell volume fraction during normal aging. This cross-sectional study (n = 49; 21-80 years) finds that the in vivo tissue cell volume fraction remains constant in all regions of the brain with advancing age in individuals who remain cognitively normal, extending the ex vivo literature reporting constant neuronal cell density across the normal adult age range. Cell volume fraction, as measured by quantitative sodium MRI, is decreased in diseases of cell loss, such as stroke, on a time scale of minutes to hours, and in response to treatment of brain tumors on a time scale of days to weeks. Neurodegenerative diseases often have prodromal periods of decades in which regional neuronal cell loss occurs prior to clinical presentation. If tissue cell volume fraction can detect such early pathology, this quantitative parameter may permit the objective measurement of preclinical disease progression. This current study in cognitively normal aging individuals provides the basis for the pursuance of investigations directed towards such neurodegenerative diseases.

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

Comparative studies amongst extant species are one of the pillars of evolutionary neurobiology. In the 20th century, most comparative studies remained restricted to analyses of brain structure volume and surface areas, besides estimates of neuronal density largely limited to the cerebral cortex. Over the last 10 years, we have amassed data on the numbers of neurons and other cells that compose the entirety of the brain (subdivided into cerebral cortex, cerebellum, and rest of brain) of 39 mammalian species spread over 6 clades, as well as their densities. Here we provide that entire dataset in a format that is readily useful to researchers of any area of interest in the hope that it will foster the advancement of evolutionary and comparative studies well beyond the scope of neuroscience itself. We also reexamine the relationship between numbers of neurons, neuronal densities and body mass, and find that in the rest of brain, but not in the cerebral cortex or cerebellum, there is a single scaling rule that applies to average neuronal cell size, which increases with the linear dimension of the body, even though there is no single scaling rule that relates the number of neurons in the rest of brain to body mass. Thus, larger bodies do not uniformly come with more neurons - but they do fairly uniformly come with larger neurons in the rest of brain, which contains a number of structures directly connected to sources or targets in the body.

Framing Neuro-Glia Coupling in Antiepileptic Drug Design

We delineate perspectives for the design and discovery of antiepileptic drugs (AEDs) with fewer side effects by focusing on astroglial modulation of spatiotemporal seizure dynamics. It is now recognized that the major inhibitory neurotransmitter of the brain, γ-aminobutyric acid (GABA), can be released through the reversal of astroglial GABA transporters. Synaptic spillover and subsequent glutamate (Glu) uptake in neighboring astrocytes evoke replacement of extracellular Glu for GABA, driving neurons away from the seizure threshold. Attenuation of synaptic signaling by this negative feedback through the interplay of Glu and GABA transporters of adjacent astroglia can result in shortened seizures. By contrast, long-range activation of astroglia through gap junctions may promote recurrent seizures on the model of pharmacoresistant temporal lobe epilepsy. From their first detection to our current understanding, we identify various targets that shape both short- and long-range neuro-astroglia coupling, as these are manifest in epilepsy phenomena and in the associated research promotions of AED.

When larger brains do not have more neurons: increased numbers of cells are compensated by decreased average cell size across mouse individuals

There is a strong trend toward increased brain size in mammalian evolution, with larger brains composed of more and larger neurons than smaller brains across species within each mammalian order. Does the evolution of increased numbers of brain neurons, and thus larger brain size, occur simply through the selection of individuals with more and larger neurons, and thus larger brains, within a population? That is, do individuals with larger brains also have more, and larger, neurons than individuals with smaller brains, such that allometric relationships across species are simply an extension of intraspecific scaling? Here we show that this is not the case across adult male mice of a similar age. Rather, increased numbers of neurons across individuals are accompanied by increased numbers of other cells and smaller average cell size of both types, in a trade-off that explains how increased brain mass does not necessarily ensue. Fundamental regulatory mechanisms thus must exist that tie numbers of neurons to numbers of other cells and to average cell size within individual brains. Finally, our results indicate that changes in brain size in evolution are not an extension of individual variation in numbers of neurons, but rather occur through step changes that must simultaneously increase numbers of neurons and cause cell size to increase, rather than decrease.

Cellular scaling rules for the brain of Artiodactyla include a highly folded cortex with few neurons

Quantitative analysis of the cellular composition of rodent, primate, insectivore, and afrotherian brains has shown that non-neuronal scaling rules are similar across these mammalian orders that diverged about 95 million years ago, and therefore appear to be conserved in evolution, while neuronal scaling rules appear to be free to vary in a clade-specific manner. Here we analyze the cellular scaling rules that apply to the brain of artiodactyls, a group within the order Cetartiodactyla, believed to be a relatively recent radiation from the common Eutherian ancestor. We find that artiodactyls share non-neuronal scaling rules with all groups analyzed previously. Artiodactyls share with afrotherians and rodents, but not with primates, the neuronal scaling rules that apply to the cerebral cortex and cerebellum. The neuronal scaling rules that apply to the remaining brain areas are, however, distinct in artiodactyls. Importantly, we show that the folding index of the cerebral cortex scales with the number of neurons in the cerebral cortex in distinct fashions across artiodactyls, afrotherians, rodents, and primates, such that the artiodactyl cerebral cortex is more convoluted than primate cortices of similar numbers of neurons. Our findings suggest that the scaling rules found to be shared across modern afrotherians, glires, and artiodactyls applied to the common Eutherian ancestor, such as the relationship between the mass of the cerebral cortex as a whole and its number of neurons. In turn, the distribution of neurons along the surface of the cerebral cortex, which is related to its degree of gyrification, appears to be a clade-specific characteristic. If the neuronal scaling rules for artiodactyls extend to all cetartiodactyls, we predict that the large cerebral cortex of cetaceans will still have fewer neurons than the human cerebral cortex.