Microglia in development: linking brain wiring to brain environment

Microglia are enigmatic non-neuronal cells that infiltrate and take up residence in the brain during development and are thought to perform a surveillance function. An established literature has documented how microglia are activated by pathogenic stimuli and how they contribute to and resolve injuries to the brain. However, much less work has been aimed at understanding their function in the uninjured brain. A series of recent in vivo imaging studies shows that microglia in their resting state are highly motile and actively survey their neuronal surroundings. Furthermore, new data suggest that microglia in their resting state are able to phagocytose unwanted synapses and in this way contribute to synaptic pruning and maturation during development. Coupled with their exquisite sensitivity to pathogenic stimuli, these data suggest that microglia form a link that couples changes in brain environment to changes in brain wiring. Here we discuss this hypothesis and propose a model for the role of microglia during development in sculpting brain connectivity.     

Brain organization: wiring economy works for the large and small

The highest-resolution test to date of the wire minimization hypothesis has found that this principle works well for brain regions with a volume just over 400 μm(3). What is the wire minimization hypothesis, and why should anyone care about it?     

The connectivity of the brain: multi-level quantitative analysis

 We develop a mathematical formalism or calculating connectivity volumes generated by specific topologies with various physical packing strategies. We consider four topologies (full, random, nearest-neighbor, and modular connectivity) and three physical models: (i) interior packing, where neurons and connection fibers are intermixed, (ii) sheeted packing where neurons are located on a sheet with fibers running underneath, and (iii) exterior packing where the neurons are located at the surfaces of a cube or sphere with fibers taking up the internal volume. By extensive cross-referencing of available human neuroanatomical data we produce a consistent set of parameters for the whole brain, the cerebral cortex, and the cerebellar cortex. By comparing these inferred values with those predicted by the expressions, we draw the following general conclusions for the human brain, cortex, and cerebellum: (i) Interior packing is less efficient than exterior packing (in a sphere). (ii) Fully and randomly connected topologies are extremely inefficient. More specifically we find evidence that different topologies and physical packing strategies might be used at different scales. (iii) For the human brain at a macrostructural level, modular topologies on an exterior sphere approach the data most closely. (iv) On a mesostructural level, laminarization and columnarization are evidence of the superior efficiency of organizing the wiring as sheets. (v) Within sheets, microstructures emerge in which interior models are shown to be the most efficient. With regard to interspecies similarities and differences we conjecture (vi) that the remarkable constancy of number of neurons per underlying square millimeter of cortex may be the result of evolution minimizing interneuron distance in grey matter, and (vii) that the topologies that best fit the human brain data should not be assumed to apply to other mammals, such as the mouse for which we show that a random topology may be feasible for the cortex. Received: 14 December 1994/Accepted in revised form: 23 May 1995     

Electrical wiring of the oscillating brain

In this issue of Neuron, two laboratories (Deans et al. and Hormuzdi et al.) find that cortical gamma oscillation in vitro is impaired in the Cx36 knockout mouse. What are the implications?     

Intrinsic connectivity reveals functionally distinct cortico-hippocampal networks in the human brain

Episodic memory depends on interactions between the hippocampus and interconnected neocortical regions. Here, using data-driven analyses of resting-state functional magnetic resonance imaging (fMRI) data, we identified the networks that interact with the hippocampus—the default mode network (DMN) and a “medial temporal network” (MTN) that included regions in the medial temporal lobe (MTL) and precuneus. We observed that the MTN plays a critical role in connecting the visual network to the DMN and hippocampus. The DMN could be further divided into 3 subnetworks: a “posterior medial” (PM) subnetwork comprised of posterior cingulate and lateral parietal cortices; an “anterior temporal” (AT) subnetwork comprised of regions in the temporopolar and dorsomedial prefrontal cortex; and a “medial prefrontal” (MP) subnetwork comprised of regions primarily in the medial prefrontal cortex (mPFC). These networks vary in their functional connectivity (FC) along the hippocampal long axis and represent different kinds of information during memory-guided decision-making. Finally, a Neurosynth meta-analysis of fMRI studies suggests new hypotheses regarding the functions of the MTN and DMN subnetworks, providing a framework to guide future research on the neural architecture of episodic memory.

Episodic memory depends on interactions between the hippocampus and interconnected neocortical regions. This study uses network analyses of intrinsic brain networks at rest to identify and characterize brain networks that interact with the hippocampus and have distinct functions during memory-guided decision making.     

Neuronal branching patterns and the economy of cortical wiring.

Keeping the volume of connections in the cortex as low as possible may be an important evolutionary constraint on the design of the brain. Much as an engineer tries to arrange the components of a computer in such a way as to give efficient wiring, so the brain may have evolved a layout of neuronal types which gives an economical use of axonal 'wiring'. One key difference between computer and brain is that connections in the brain take the form of elaborate branching structures. It is argued here that certain features of cortical mapping, such as the stripes and patches seen within cortical areas, may be adaptations which allow efficient wiring by such structures. Some simple calculations are given to support this, using as models for axonal arbors certain branching patterns which give a low volume of wiring. In particular, it is shown that a pattern of stripes can give economical wiring when axon diameters follow a law dp = dp1 + dp2 with p greater than 4, where d1 and d2 are the diameters of the daughter branches and d that of the parent.     

The trappist's approach to pathfinding: elucidating brain wiring using secretory-trap mutagenesis

A key problem in using genetics to dissect the wiring of the mammalian brain lies in discovering which of the billions of neural connections have been disrupted by a particular mutation. A novel gene-trap approach targets the genes involved in brain wiring and labels the axons of neurons expressing those genes, enabling the effects of mutations to be observed directly.     

Relationships between gene expression and brain wiring in the adult rodent brain

We studied the global relationship between gene expression and neuroanatomical connectivity in the adult rodent brain. We utilized a large data set of the rat brain "connectome" from the Brain Architecture Management System (942 brain regions and over 5000 connections) and used statistical approaches to relate the data to the gene expression signatures of 17,530 genes in 142 anatomical regions from the Allen Brain Atlas. Our analysis shows that adult gene expression signatures have a statistically significant relationship to connectivity. In particular, brain regions that have similar expression profiles tend to have similar connectivity profiles, and this effect is not entirely attributable to spatial correlations. In addition, brain regions which are connected have more similar expression patterns. Using a simple optimization approach, we identified a set of genes most correlated with neuroanatomical connectivity, and find that this set is enriched for genes involved in neuronal development and axon guidance. A number of the genes have been implicated in neurodevelopmental disorders such as autistic spectrum disorder. Our results have the potential to shed light on the role of gene expression patterns in influencing neuronal activity and connectivity, with potential applications to our understanding of brain disorders. Supplementary data are available at http://www.chibi.ubc.ca/ABAMS.     

Predator dispersal determines the effect of connectivity on prey diversity

Linking local communities to a metacommunity can positively affect diversity by enabling immigration of dispersal-limited species and maintenance of sink populations. However, connectivity can also negatively affect diversity by allowing the spread of strong competitors or predators. In a microcosm experiment with five ciliate species as prey and a copepod as an efficient generalist predator, we analysed the effect of connectivity on prey species richness in metacommunities that were either unconnected, connected for the prey, or connected for both prey and predator. Presence and absence of predator dispersal was cross-classified with low and high connectivity. The effect of connectivity on local and regional richness strongly depended on whether corridors were open for the predator. Local richness was initially positively affected by connectivity through rescue of species from stochastic extinctions. With predator dispersal, however, this positive effect soon turned negative as the predator spread over the metacommunity. Regional richness was unaffected by connectivity when local communities were connected only for the prey, while predator dispersal resulted in a pronounced decrease of regional richness. The level of connectivity influenced the speed of richness decline, with regional species extinctions being delayed for one week in weakly connected metacommunities. While connectivity enabled rescue of prey species from stochastic extinctions, deterministic extinctions due to predation were not overcome through reimmigration from predator-free refuges. Prey reimmigrating into these sink habitats appeared to be directly converted into increased predator abundance. Connectivity thus had a positive effect on the predator, even when the predator was not dispersing itself. Our study illustrates that dispersal of a species with strong negative effects on other community members shapes the dispersal-diversity relationship. When connections enable the spread of a generalist predator, positive effects of connectivity on prey species richness are outweighed by regional extinctions through predation.     

A wiring of the human nucleolus

Recent proteomic efforts have created an extensive inventory of the human nucleolar proteome. However, approximately 30% of the identified proteins lack functional annotation. We present an approach of assigning function to uncharacterized nucleolar proteins by data integration coupled to a machine-learning method. By assembling protein complexes, we present a first draft of the human ribosome biogenesis pathway encompassing 74 proteins and hereby assign function to 49 previously uncharacterized proteins. Moreover, the functional diversity of the nucleolus is underlined by the identification of a number of protein complexes with functions beyond ribosome biogenesis. Finally, we were able to obtain experimental evidence of nucleolar localization of 11 proteins, which were predicted by our platform to be associates of nucleolar complexes. We believe other biological organelles or systems could be "wired" in a similar fashion, integrating different types of data with high-throughput proteomics, followed by a detailed biological analysis and experimental validation.     

Decoding lifespan changes of the human brain using resting-state functional connectivity MRI

The development of large-scale functional brain networks is a complex, lifelong process that can be investigated using resting-state functional connectivity MRI (rs-fcMRI). In this study, we aimed to decode the developmental dynamics of the whole-brain functional network in seven decades (8-79 years) of the human lifespan. We first used parametric curve fitting to examine linear and nonlinear age effect on the resting human brain, and then combined manifold learning and support vector machine methods to predict individuals' "brain ages" from rs-fcMRI data. We found that age-related changes in interregional functional connectivity exhibited spatially and temporally specific patterns. During brain development from childhood to senescence, functional connections tended to linearly increase in the emotion system and decrease in the sensorimotor system; while quadratic trajectories were observed in functional connections related to higher-order cognitive functions. The complex patterns of age effect on the whole-brain functional network could be effectively represented by a low-dimensional, nonlinear manifold embedded in the functional connectivity space, which uncovered the inherent structure of brain maturation and aging. Regression of manifold coordinates with age further showed that the manifold representation extracted sufficient information from rs-fcMRI data to make prediction about individual brains' functional development levels. Our study not only gives insights into the neural substrates that underlie behavioral and cognitive changes over age, but also provides a possible way to quantitatively describe the typical and atypical developmental progression of human brain function using rs-fcMRI.     

Characterisation of the potamal Danube River and the Delta: connectivity determines indicative macrophyte assemblages

The complexity of water bodies in the eu-potamal river corridor and the main delta channels of the Romanian Danube is exemplified by the macrophyte vegetation. Two hypotheses provided the background for our study: (a) is the macrophyte vegetation of large, permanently connected branches significantly separated from that of the main river channel; (b) is the macrophyte composition of the Danube main stem significantly altered when the river divides into the three large navigable Delta channels. Water bodies considered were two contiguous sections of the main river channel, two large branches remaining from the historical floodplain, and the three main Delta channels. We quantified macrophyte diversity and floristic variation. Our data set was prepared from the MIDCC-project data base, in which macrophyte occurrence, abundance and habitat parameters are stored for contiguous survey units of the whole Danube river corridor. Field survey method followed that of Kohler and the European Standard EN14184. Results confirmed our first hypothesis: permanently connected side branches still support significantly different macrophyte assemblages, making them important indicators of floodplain connectivity. The diversion of the Danube into its three large navigable delta channels significantly alters the macrophyte vegetation from the c. 300 km of main stem up-river, substantially supporting our second hypothesis. Our results largely enhance the knowledge on aquatic plant biodiversity in the eu-potamal Danube, forming a solid base for long-term studies. We also discuss the relevance of our results regarding the ecological, as well as the conservational, quality of rivers and their floodplains.     

Erratum to: The trappist's approach to pathfinding: elucidating brain wiring using secretory-trap mutagenesis

An erratum to The trappist's approach to pathfinding: elucidating brain wiring using secretory-trap mutagenesis by AJ Furley. Genome Biology 2001, 2:reviews1026.1-1026.5     

Functional connectivity fMRI of the rodent brain: comparison of functional connectivity networks in rat and mouse

At present, resting state functional MRI (rsfMRI) is increasingly used in human neuropathological research. The present study aims at implementing rsfMRI in mice, a species that holds the widest variety of neurological disease models. Moreover, by acquiring rsfMRI data with a comparable protocol for anesthesia, scanning and analysis, in both rats and mice we were able to compare findings obtained in both species. The outcome of rsfMRI is different for rats and mice and depends strongly on the applied number of components in the Independent Component Analysis (ICA). The most important difference was the appearance of unilateral cortical components for the mouse resting state data compared to bilateral rat cortical networks. Furthermore, a higher number of components was needed for the ICA analysis to separate different cortical regions in mice as compared to rats.     

Imaging of functional connectivity in the mouse brain

Functional neuroimaging (e.g., with fMRI) has been difficult to perform in mice, making it challenging to translate between human fMRI studies and molecular and genetic mechanisms. A method to easily perform large-scale functional neuroimaging in mice would enable the discovery of functional correlates of genetic manipulations and bridge with mouse models of disease. To satisfy this need, we combined resting-state functional connectivity mapping with optical intrinsic signal imaging (fcOIS). We demonstrate functional connectivity in mice through highly detailed fcOIS mapping of resting-state networks across most of the cerebral cortex. Synthesis of multiple network connectivity patterns through iterative parcellation and clustering provides a comprehensive map of the functional neuroarchitecture and demonstrates identification of the major functional regions of the mouse cerebral cortex. The method relies on simple and relatively inexpensive camera-based equipment, does not require exogenous contrast agents and involves only reflection of the scalp (the skull remains intact) making it minimally invasive. In principle, fcOIS allows new paradigms linking human neuroscience with the power of molecular/genetic manipulations in mouse models.