Methods to investigate the structure and connectivity of the nervous system

Understanding the computations that take place in neural circuits requires identifying how neurons in those circuits are connected to one another. In addition, recent research indicates that aberrant neuronal wiring may be the cause of several neurodevelopmental disorders, further emphasizing the importance of identifying the wiring diagrams of brain circuits. To address this issue, several new approaches have been recently developed. In this review, we describe several methods that are currently available to investigate the structure and connectivity of the brain, and discuss their strengths and limitations.     

Variability v.s. synchronicity of neuronal activity in local cortical network models with different wiring topologies

Dynamical behavior of a biological neuronal network depends significantly on the spatial pattern of synaptic connections among neurons. While neuronal network dynamics has extensively been studied with simple wiring patterns, such as all-to-all or random synaptic connections, not much is known about the activity of networks with more complicated wiring topologies. Here, we examined how different wiring topologies may influence the response properties of neuronal networks, paying attention to irregular spike firing, which is known as a characteristic of in vivo cortical neurons, and spike synchronicity. We constructed a recurrent network model of realistic neurons and systematically rewired the recurrent synapses to change the network topology, from a localized regular and a “small-world” network topology to a distributed random network topology. Regular and small-world wiring patterns greatly increased the irregularity or the coefficient of variation (Cv) of output spike trains, whereas such an increase was small in random connectivity patterns. For given strength of recurrent synapses, the firing irregularity exhibited monotonous decreases from the regular to the random network topology. By contrast, the spike coherence between an arbitrary neuron pair exhibited a non-monotonous dependence on the topological wiring pattern. More precisely, the wiring pattern to maximize the spike coherence varied with the strength of recurrent synapses. In a certain range of the synaptic strength, the spike coherence was maximal in the small-world network topology, and the long-range connections introduced in this wiring changed the dependence of spike synchrony on the synaptic strength moderately. However, the effects of this network topology were not really special in other properties of network activity. Action Editor: Xiao-Jing Wang     

Multiple forms of activity-dependent competition refine hippocampal circuits in vivo

Efficient memory formation relies on the establishment of functional hippocampal circuits. It has been proposed that synaptic connections are refined by neural activity to form functional brain circuitry. However, it is not known whether and how hippocampal connections are refined by neural activity in vivo. Using a mouse genetic system in which restricted populations of neurons in the hippocampal circuit are inactivated, we show that inactive axons are eliminated after they develop through a competition with active axons. Remarkably, in the dentate gyrus, which undergoes neurogenesis throughout life, axon refinement is achieved by a competition between mature and young neurons. These results demonstrate that activity-dependent competition plays multiple roles in the establishment of functional memory circuits in vivo.     

Local cortical circuit model inferred from power-law distributed neuronal avalanches

How cortical neurons process information crucially depends on how their local circuits are organized. Spontaneous synchronous neuronal activity propagating through neocortical slices displays highly diverse, yet repeatable, activity patterns called “neuronal avalanches”. They obey power-law distributions of the event sizes and lifetimes, presumably reflecting the structure of local circuits developed in slice cultures. However, the explicit network structure underlying the power-law statistics remains unclear. Here, we present a neuronal network model of pyramidal and inhibitory neurons that enables stable propagation of avalanche-like spiking activity. We demonstrate a neuronal wiring rule that governs the formation of mutually overlapping cell assemblies during the development of this network. The resultant network comprises a mixture of feedforward chains and recurrent circuits, in which neuronal avalanches are stable if the former structure is predominant. Interestingly, the recurrent synaptic connections formed by this wiring rule limit the number of cell assemblies embeddable in a neuron pool of given size. We investigate how the resultant power laws depend on the details of the cell-assembly formation as well as on the inhibitory feedback. Our model suggests that local cortical circuits may have a more complex topological design than has previously been thought. Competing financial interests: The authors declare that they have no competing financial interests. Action Editor: Peter Latham     

Computational methods and challenges for large-scale circuit mapping

The connectivity architecture of neuronal circuits is essential to understand how brains work, yet our knowledge about the neuronal wiring diagrams remains limited and partial. Technical breakthroughs in labeling and imaging methods starting more than a century ago have advanced knowledge in the field. However, the volume of data associated with imaging a whole brain or a significant fraction thereof, with electron or light microscopy, has only recently become amenable to digital storage and analysis. A mouse brain imaged at light-microscopic resolution is about a terabyte of data, and 1mm(3) of the brain at EM resolution is about half a petabyte. This has given rise to a new field of research, computational analysis of large-scale neuroanatomical data sets, with goals that include reconstructions of the morphology of individual neurons as well as entire circuits. The problems encountered include large data management, segmentation and 3D reconstruction, computational geometry and workflow management allowing for hybrid approaches combining manual and algorithmic processing. Here we review this growing field of neuronal data analysis with emphasis on reconstructing neurons from EM data cubes.     

A technicolour approach to the connectome

A central aim of neuroscience is to map neural circuits, in order to learn how they account for mental activities and behaviours and how alterations in them lead to neurological and psychiatric disorders. However, the methods that are currently available for visualizing circuits have severe limitations that make it extremely difficult to extract precise wiring diagrams from histological images. Here we review recent advances in this area, along with some of the opportunities that these advances present and the obstacles that remain.     

Specificity of cortical synaptic connectivity: Emphasis on perspectives gained from quantitative electron microscopy

This report traces the historical development of concepts regarding the specificity of synaptic connectivity in the cerebral cortex as viewed primarily from the perspective of electron microscopy. The occurrence of stereotypical patterns of connection (e.g., contrasting synaptic patterns on the surfaces of spiny vs. non-spiny neurons, the general consistency with which axonal pathways impinge on and originate within specific cortical areas and layers, triadic synaptic relationships) implies that cortical connectivity is highly structured. The high degree of order characterizing many aspects of cortical organization is mirrored by an equally ordered arrangement of synaptic connections between specific types of neurons. This observation is based on quantitative electron microscopic studies of synapses between identified neurons and from the results of correlative anatomical/electrophysiological investigations. The recognition of recurring synaptic patterns and responses between specific neurons has generated increased support for the notion of specificity of synaptic connections at the expense of randomness, but the role of specificity in cortical function is an unresolved question. At the core of cortical processing lie myriad possibilities for computation provided by the wealth of synaptic connections involving each cortical neuron. Specificity, by limiting possibilities for connection, can impose an order on synaptic interactions even as processes of dynamic selection or synaptic remodeling ensure the constant formation and dissolution of cortical circuits. These operations make maximal use of the richness of cortical synaptic connections to produce a highly flexible system, irrespective of the degree of randomness or specificity that obtains for cortical wiring at any particular time.     

Genetic Control of Wiring Specificity in the Fly Olfactory System

Precise connections established between pre- and postsynaptic partners during development are essential for the proper function of the nervous system. The olfactory system detects a wide variety of odorants and processes the information in a precisely connected neural circuit. A common feature of the olfactory systems from insects to mammals is that the olfactory receptor neurons (ORNs) expressing the same odorant receptor make one-to-one connections with a single class of second-order olfactory projection neurons (PNs). This represents one of the most striking examples of targeting specificity in developmental neurobiology. Recent studies have uncovered central roles of transmembrane and secreted proteins in organizing this one-to-one connection specificity in the olfactory system. Here, we review recent advances in the understanding of how this wiring specificity is genetically controlled and focus on the mechanisms by which transmembrane and secreted proteins regulate different stages of the Drosophila olfactory circuit assembly in a coordinated manner. We also discuss how combinatorial coding, redundancy, and error-correcting ability could contribute to constructing a complex neural circuit in general.     

The Interscutularis Muscle Connectome

The complete connectional map (connectome) of a neural circuit is essential for understanding its structure and function. Such maps have only been obtained in Caenorhabditis elegans. As an attempt at solving mammalian circuits, we reconstructed the connectomes of six interscutularis muscles from adult transgenic mice expressing fluorescent proteins in all motor axons. The reconstruction revealed several organizational principles of the neuromuscular circuit. First, the connectomes demonstrate the anatomical basis of the graded tensions in the size principle. Second, they reveal a robust quantitative relationship between axonal caliber, length, and synapse number. Third, they permit a direct comparison of the same neuron on the left and right sides of the same vertebrate animal, and reveal significant structural variations among such neurons, which contrast with the stereotypy of identified neurons in invertebrates. Finally, the wiring length of axons is often longer than necessary, contrary to the widely held view that neural wiring length should be minimized. These results show that mammalian muscle function is implemented with a variety of wiring diagrams that share certain global features but differ substantially in anatomical form. This variability may arise from the dominant role of synaptic competition in establishing the final circuit.     

Wiring specificity in the olfactory system

The fruitfly brain learns about the olfactory world by reading the activity of about 50 distinct channels of incoming information. The receptor neurons that compose each channel have their own distinctive odour response profile governed by a specific receptor molecule. These receptor neurons form highly specific connections in the first olfactory relay of the fly brain, each synapsing with specific second order partner neurons. We use this system to discuss the logic of wiring specificity in the brain and to review the cellular and molecular mechanisms that allow such precise wiring to develop.     

Wiring economy and volume exclusion determine neuronal placement in the Drosophila brain

Wiring economy has successfully explained the individual placement of neurons in simple nervous systems like that of Caenorhabditis elegans [1-3] and the locations of coarser structures like cortical areas in complex vertebrate brains [4]. However, it remains unclear whether wiring economy can explain the placement of individual neurons in brains larger than that of C.?elegans. Indeed, given the greater number of neuronal interconnections in larger brains, simply minimizing the length of connections results in unrealistic configurations, with multiple neurons occupying the same position in space. Avoiding such configurations, or volume exclusion, repels neurons from each other, thus counteracting wiring economy. Here we test whether wiring economy together with volume exclusion can explain the placement of neurons in a module of the Drosophila melanogaster brain known as lamina cartridge [5-13]. We used newly developed techniques for semiautomated reconstruction from serial electron microscopy (EM) [14] to obtain the shapes of neurons, the location of synapses, and the resultant synaptic connectivity. We show that wiring length minimization and volume exclusion together can explain the structure of the lamina microcircuit. Therefore, even in brains larger than that of C.?elegans, at least for some circuits, optimization can play an important role in individual neuron placement.     

Targeting of amacrine cell neurites to appropriate synaptic laminae in the developing zebrafish retina

Cellular mechanisms underlying the precision by which neurons target their synaptic partners have largely been determined based on the study of projection neurons. By contrast, little is known about how interneurons establish their local connections in vivo. Here, we investigated how developing amacrine interneurons selectively innervate the appropriate region of the synaptic neuropil in the inner retina, the inner plexiform layer (IPL). Increases (ON) and decreases (OFF) in light intensity are processed by circuits that are structurally confined to separate ON and OFF synaptic sublaminae within the IPL. Using transgenic zebrafish in which the majority of amacrine cells express fluorescent protein, we determined that the earliest amacrine-derived neuritic plexus formed between two cell populations whose somata, at maturity, resided on opposite sides of this plexus. When we followed the behavior of individual amacrine cells over time, we discovered that they exhibited distinct patterns of structural dynamics at different stages of development. During cellular migration, amacrine cells exhibited an exuberant outgrowth of neurites that was undirected. Upon reaching the forming IPL, neurites extending towards the ganglion cell layer were relatively more stable. Importantly, when an arbor first formed, it preferentially ramified in either the inner or outer IPL corresponding to the future ON and OFF sublaminae, and maintained this stratification pattern. The specificity by which ON and OFF amacrine interneurons innervate their respective sublaminae in the IPL contrasts with that observed for projection neurons in the retina and elsewhere in the central nervous system.     

Expression of the Immunoglobulin Superfamily Cell Adhesion Molecules in the Developing Spinal Cord and Dorsal Root Ganglion

Cell adhesion molecules belonging to the immunoglobulin superfamily (IgSF) control synaptic specificity through hetero- or homophilic interactions in different regions of the nervous system. In the developing spinal cord, monosynaptic connections of exquisite specificity form between proprioceptive sensory neurons and motor neurons, however, it is not known whether IgSF molecules participate in regulating this process. To determine whether IgSF molecules influence the establishment of synaptic specificity in sensory-motor circuits, we examined the expression of 157 IgSF genes in the developing dorsal root ganglion (DRG) and spinal cord by in situ hybridization assays. We find that many IgSF genes are expressed by sensory and motor neurons in the mouse developing DRG and spinal cord. For instance, Alcam, Mcam, and Ocam are expressed by a subset of motor neurons in the ventral spinal cord. Further analyses show that Ocam is expressed by obturator but not quadriceps motor neurons, suggesting that Ocam may regulate sensory-motor specificity in these sensory-motor reflex arcs. Electrophysiological analysis shows no obvious defects in synaptic specificity of monosynaptic sensory-motor connections involving obturator and quadriceps motor neurons in Ocam mutant mice. Since a subset of Ocam⁺ motor neurons also express Alcam, Alcam or other functionally redundant IgSF molecules may compensate for Ocam in controlling sensory-motor specificity. Taken together, these results reveal that IgSF molecules are broadly expressed by sensory and motor neurons during development, and that Ocam and other IgSF molecules may have redundant functions in controlling the specificity of sensory-motor circuits.     

Bayesian inference in populations of cortical neurons: a model of motion integration and segmentation in area MT

A major issue in cortical physiology and computational neuroscience is understanding the interaction between extrinsic signals from feedforward connections and intracortical signals from lateral connections. We propose here a computational model for motion perception based on the assumption that the local cortical circuits in the medio-temporal area (area MT) implement a Bayesian inference principle. This approach establishes a functional balance between feedforward and lateral, excitatory and inhibitory, inputs. The model reproduces most of the known properties of the neurons in area MT in response to moving stimuli. It accounts for important motion perception phenomena including motion transparency, spatial and temporal integration/segmentation. While integrating several properties of previously proposed models, it makes specific testable predictions concerning, in particular, temporal properties of neurons and the architecture of lateral connections in area MT. In addition, the proposed mechanism is consistent with the known properties of local cortical circuits in area V1. This suggests that Bayesian inference may be a general feature of information processing in cortical neuron populations. Received: 3 December 1997 / Accepted in revised form: 21 July 1998     

Establishment of high reciprocal connectivity between clonal cortical neurons is regulated by the Dnmt3b DNA methyltransferase and clustered protocadherins

Background

The specificity of synaptic connections is fundamental for proper neural circuit function. Specific neuronal connections that underlie information processing in the sensory cortex are initially established without sensory experiences to a considerable extent, and then the connections are individually refined through sensory experiences. Excitatory neurons arising from the same single progenitor cell are preferentially connected in the postnatal cortex, suggesting that cell lineage contributes to the initial wiring of neurons. However, the postnatal developmental process of lineage-dependent connection specificity is not known, nor how clonal neurons, which are derived from the same neural stem cell, are stamped with the identity of their common neural stem cell and guided to form synaptic connections.

Results

We show that cortical excitatory neurons that arise from the same neural stem cell and reside within the same layer preferentially establish reciprocal synaptic connections in the mouse barrel cortex. We observed a transient increase in synaptic connections between clonal but not nonclonal neuron pairs during postnatal development, followed by selective stabilization of the reciprocal connections between clonal neuron pairs. Furthermore, we demonstrate that selective stabilization of the reciprocal connections between clonal neuron pairs is impaired by the deficiency of DNA methyltransferase 3b (Dnmt3b), which determines DNA-methylation patterns of genes in stem cells during early corticogenesis. Dnmt3b regulates the postnatal expression of clustered protocadherin (cPcdh) isoforms, a family of adhesion molecules. We found that cPcdh deficiency in clonal neuron pairs impairs the whole process of the formation and stabilization of connections to establish lineage-specific connection reciprocity.

Conclusions

Our results demonstrate that local, reciprocal neural connections are selectively formed and retained between clonal neurons in layer 4 of the barrel cortex during postnatal development, and that Dnmt3b and cPcdhs are required for the establishment of lineage-specific reciprocal connections. These findings indicate that lineage-specific connection reciprocity is predetermined by Dnmt3b during embryonic development, and that the cPcdhs contribute to postnatal cortical neuron identification to guide lineage-dependent synaptic connections in the neocortex.

     

Beyond the connectome: how neuromodulators shape neural circuits

Powerful ultrastructural tools are providing new insights into neuronal circuits, revealing a wealth of anatomically-defined synaptic connections. These wiring diagrams are incomplete, however, because functional connectivity is actively shaped by neuromodulators that modify neuronal dynamics, excitability, and synaptic function. Studies of defined neural circuits in crustaceans, C. elegans, Drosophila, and the vertebrate retina have revealed the ability of modulators and sensory context to reconfigure information processing by changing the composition and activity of functional circuits. Each ultrastructural connectivity map encodes multiple circuits, some of which are active and some of which are latent at any given time.     

Architecture of spatial circuits in the hippocampal region

The hippocampal region contains several principal neuron types, some of which show distinct spatial firing patterns. The region is also known for its diversity in neural circuits and many have attempted to causally relate network architecture within and between these unique circuits to functional outcome. Still, much is unknown about the mechanisms or network properties by which the functionally specific spatial firing profiles of neurons are generated, let alone how they are integrated into a coherently functioning meta-network. In this review, we explore the architecture of local networks and address how they may interact within the context of an overarching space circuit, aiming to provide directions for future successful explorations.     

Structural properties of the Caenorhabditis elegans neuronal network

Despite recent interest in reconstructing neuronal networks, complete wiring diagrams on the level of individual synapses remain scarce and the insights into function they can provide remain unclear. Even for Caenorhabditis elegans, whose neuronal network is relatively small and stereotypical from animal to animal, published wiring diagrams are neither accurate nor complete and self-consistent. Using materials from White et al. and new electron micrographs we assemble whole, self-consistent gap junction and chemical synapse networks of hermaphrodite C. elegans. We propose a method to visualize the wiring diagram, which reflects network signal flow. We calculate statistical and topological properties of the network, such as degree distributions, synaptic multiplicities, and small-world properties, that help in understanding network signal propagation. We identify neurons that may play central roles in information processing, and network motifs that could serve as functional modules of the network. We explore propagation of neuronal activity in response to sensory or artificial stimulation using linear systems theory and find several activity patterns that could serve as substrates of previously described behaviors. Finally, we analyze the interaction between the gap junction and the chemical synapse networks. Since several statistical properties of the C. elegans network, such as multiplicity and motif distributions are similar to those found in mammalian neocortex, they likely point to general principles of neuronal networks. The wiring diagram reported here can help in understanding the mechanistic basis of behavior by generating predictions about future experiments involving genetic perturbations, laser ablations, or monitoring propagation of neuronal activity in response to stimulation.