Axon and dendrite geography predict the specificity of synaptic connections in a functioning spinal cord network

Synaptic promiscuity in brain development

Precise synaptic connectivity is a prerequisite for the function of neural circuits, yet individual neurons, taken out of their developmental context, readily form unspecific synapses. How does the genome encode brain wiring in light of this apparent contradiction? Synaptic specificity is the outcome of a long series of developmental processes and mechanisms before, during and after synapse formation. How much promiscuity is permissible or necessary at the moment of synaptic partner choice depends on the extent to which prior development restricts available partners or subsequent development corrects initially made synapses. Synaptic promiscuity at the moment of choice can thereby play important roles in the development of precise connectivity, but also facilitate developmental flexibility and robustness. In this review, we assess the experimental evidence for the prevalence and roles of promiscuous synapse formation during brain development. Many well-established experimental approaches are based on developmental genetic perturbation and an assessment of synaptic connectivity only in the adult; this can make it difficult to pinpoint when a given defect or mechanism occurred. In many cases, such studies reveal mechanisms that restrict partner availability already prior to synapse formation. Subsequently, at the moment of choice, factors including synaptic competency, interaction dynamics and molecular recognition further restrict synaptic partners. The discussion of the development of synaptic specificity through the lens of synaptic promiscuity suggests an algorithmic process based on neurons capable of promiscuous synapse formation that are continuously prevented from making the wrong choices, with no single mechanism or developmental time point sufficient to explain the outcome.

From decision to action: Detailed modelling of frog tadpoles reveals neuronal mechanisms of decision-making and reproduces unpredictable swimming movements in response to sensory signals

How does the brain process sensory stimuli, and decide whether to initiate locomotor behaviour? To investigate this question we develop two whole body computer models of a tadpole. The "Central Nervous System" (CNS) model uses evidence from whole-cell recording to define 2300 neurons in 12 classes to study how sensory signals from the skin initiate and stop swimming. In response to skin stimulation, it generates realistic sensory pathway spiking and shows how hindbrain sensory memory populations on each side can compete to initiate reticulospinal neuron firing and start swimming. The 3-D "Virtual Tadpole" (VT) biomechanical model with realistic muscle innervation, body flexion, body-water interaction, and movement is then used to evaluate if motor nerve outputs from the CNS model can produce swimming-like movements in a volume of "water". We find that the whole tadpole VT model generates reliable and realistic swimming. Combining these two models opens new perspectives for experiments.

Functional Diversity of Glycinergic Commissural Inhibitory Neurons in Larval Zebrafish

Commissural inhibitory neurons in the spinal cord of aquatic vertebrates coordinate left-right body alternation during swimming. Their developmental origin, however, has been elusive. We investigate this by comparing the anatomy and function of two commissural inhibitory neuron types, dI6dmrt3a and V0d, derived from the pd6 and p0 progenitor domains, respectively. We find that both of these commissural neuron types have monosynaptic, inhibitory connections to neuronal populations active during fictive swimming, supporting their role in providing inhibition to the contralateral side. V0d neurons tend to fire during faster and stronger movements, while dI6dmrt3a neurons tend to fire more consistently during normal fictive swimming. Ablation of dI6dmrt3a neurons leads to an impairment of left-right alternating activity through abnormal co-activation of ventral root neurons on both sides of the spinal cord. Our results suggest that dI6dmrt3a and V0d commissural inhibitory neurons synergistically provide inhibition to the opposite side across different swimming behaviors.

A simple method defines 3D morphology and axon projections of filled neurons in a small CNS volume: Steps toward understanding functional network circuitry

BACKGROUND

Fundamental to understanding neuronal network function is defining neuron morphology, location, properties, and synaptic connectivity in the nervous system. A significant challenge is to reconstruct individual neuron morphology and connections at a whole CNS scale and bring together functional and anatomical data to understand the whole network.

NEW METHOD

We used a PC controlled micropositioner to hold a fixed whole mount of Xenopus tadpole CNS and replace the stage on a standard microscope. This allowed direct recording in 3D coordinates of features and axon projections of one or two neurons dye-filled during whole-cell recording to study synaptic connections. Neuron reconstructions were normalised relative to the ventral longitudinal axis of the nervous system. Coordinate data were stored as simple text files.

RESULTS

Reconstructions were at 1 μm resolution, capturing axon lengths in mm. The output files were converted to SWC format and visualised in 3D reconstruction software NeuRomantic. Coordinate data are tractable, allowing correction for histological artefacts. Through normalisation across multiple specimens we could infer features of network connectivity of mapped neurons of different types.

COMPARISON WITH EXISTING METHODS

Unlike other methods using fluorescent markers and utilising large-scale imaging, our method allows direct acquisition of 3D data on neurons whose properties and synaptic connections have been studied using whole-cell recording.

CONCLUSIONS

This method can be used to reconstruct neuron 3D morphology and follow axon projections in the CNS. After normalisation to a common CNS framework, inferences on network connectivity at a whole nervous system scale contribute to network modelling to understand CNS function.

Orderly compartmental mapping of premotor inhibition in the developing zebrafish spinal cord

In vertebrates, faster movements involve the orderly recruitment of different types of spinal motor neurons. However, it is not known how premotor inhibitory circuits are organized to ensure alternating motor output at different movement speeds. We found that different types of commissural inhibitory interneurons in zebrafish form compartmental microcircuits during development that align inhibitory strength and recruitment order. Axonal microcircuits develop first and provide the most potent premotor inhibition during the fastest movements, followed by perisomatic microcircuits, and then dendritic microcircuits that provide the weakest inhibition during the slowest movements. The conversion of a temporal sequence of neuronal development into a spatial pattern of inhibitory connections provides an "ontogenotopic" solution to the problem of shaping spinal motor output at different speeds of movement.

Excess Neuronal Branching Allows for Local Innervation of Specific Dendritic Compartments in Mature Cortex

The connectivity of cortical microcircuits is a major determinant of brain function; defining how activity propagates between different cell types is key to scaling our understanding of individual neuronal behavior to encompass functional networks. Furthermore, the integration of synaptic currents within a dendrite depends on the spatial organization of inputs, both excitatory and inhibitory. We identify a simple equation to estimate the number of potential anatomical contacts between neurons; finding a linear increase in potential connectivity with cable length and maximum spine length, and a decrease with overlapping volume. This enables us to predict the mean number of candidate synapses for reconstructed cells, including those realistically arranged. We identify an excess of potential local connections in mature cortical data, with densities of neurite higher than is necessary to reliably ensure the possible implementation of any given axo-dendritic connection. We show that the number of local potential contacts allows specific innervation of distinct dendritic compartments.

Positional Strategies for Connection Specificity and Synaptic Organization in Spinal Sensory-Motor Circuits

Proprioceptive sensory axons in the spinal cord form selective connections with motor neuron partners, but the strategies that confer such selectivity remain uncertain. We show that muscle-specific sensory axons project to motor neurons along topographically organized angular trajectories and that motor pools exhibit diverse dendritic arbors. On the basis of spatial constraints on axo-dendritic interactions, we propose positional strategies that can account for sensory-motor connectivity and synaptic organization. These strategies rely on two patterning principles. First, the degree of axo-dendritic overlap reduces the number of potential post-synaptic partners. Second, a close correlation between the small angle of axo-dendritic approach and the formation of synaptic clusters imposes specificity of connections when sensory axons intersect multiple motor pools with overlapping dendritic arbors. Our study identifies positional strategies with prominent roles in the organization of spinal sensory-motor circuits.

A simple decision to move in response to touch reveals basic sensory memory and mechanisms for variable response times

KEY POINTS

Short-term working memory and decision-making are usually studied in the cerebral cortex; in many models of simple decision making, sensory signals build slowly and noisily to threshold to initiate a motor response after long, variable delays. When touched, hatchling frog tadpoles decide whether to swim; we define the long and variable delays to swimming and use whole-cell recordings to uncover the neurons and processes responsible. Firing in sensory and sensory pathway neurons is short latency, and too brief and invariant to explain these delays, while recordings from hindbrain reticulospinal neurons controlling swimming reveal a prolonged and variable build-up of synaptic excitation which can reach firing threshold and initiate swimming. We propose this excitation provides a sensory memory of the stimulus and may be generated by small reverberatory hindbrain networks. Our results uncover fundamental network mechanisms that allow animals to remember brief sensory stimuli and delay simple motor decisions.

ABSTRACT

Many motor responses to sensory input, like locomotion or eye movements, are much slower than reflexes. Can simpler animals provide fundamental answers about the cellular mechanisms for motor decisions? Can we observe the 'accumulation' of excitation to threshold proposed to underlie decision making elsewhere? We explore how somatosensory touch stimulation leads to the decision to swim in hatchling Xenopus tadpoles. Delays measured to swimming in behaving and immobilised tadpoles are long and variable. Activity in their extensively studied sensory and sensory pathway neurons is too short-lived to explain these response delays. Instead, whole-cell recordings from the hindbrain reticulospinal neurons that drive swimming show that these receive prolonged, variable synaptic excitation lasting for nearly a second following a brief stimulus. They fire and initiate swimming when this excitation reaches threshold. Analysis of the summation of excitation requires us to propose extended firing in currently undefined presynaptic hindbrain neurons. Simple models show that a small excitatory recurrent-network inserted in the sensory pathway can mimic this process. We suggest that such a network may generate slow, variable summation of excitation to threshold. This excitation provides a simple memory of the sensory stimulus. It allows temporal and spatial integration of sensory inputs and explains the long, variable delays to swimming. The process resembles the 'accumulation' of excitation proposed for cortical circuits in mammals. We conclude that fundamental elements of sensory memory and decision making are present in the brainstem at a surprisingly early stage in development.

Bifurcations of Limit Cycles in a Reduced Model of the Xenopus Tadpole Central Pattern Generator

We present the study of a minimal microcircuit controlling locomotion in two-day-old Xenopus tadpoles. During swimming, neurons in the spinal central pattern generator (CPG) generate anti-phase oscillations between left and right half-centres. Experimental recordings show that the same CPG neurons can also generate transient bouts of long-lasting in-phase oscillations between left-right centres. These synchronous episodes are rarely recorded and have no identified behavioural purpose. However, metamorphosing tadpoles require both anti-phase and in-phase oscillations for swimming locomotion. Previous models have shown the ability to generate biologically realistic patterns of synchrony and swimming oscillations in tadpoles, but a mathematical description of how these oscillations appear is still missing. We define a simplified model that incorporates the key operating principles of tadpole locomotion. The model generates the various outputs seen in experimental recordings, including swimming and synchrony. To study the model, we perform detailed one- and two-parameter bifurcation analysis. This reveals the critical boundaries that separate different dynamical regimes and demonstrates the existence of parameter regions of bi-stable swimming and synchrony. We show that swimming is stable in a significantly larger range of parameters, and can be initiated more robustly, than synchrony. Our results can explain the appearance of long-lasting synchrony bouts seen in experiments at the start of a swimming episode.

Structural and functional properties of a probabilistic model of neuronal connectivity in a simple locomotor network

Although, in most animals, brain connectivity varies between individuals, behaviour is often similar across a species. What fundamental structural properties are shared across individual networks that define this behaviour? We describe a probabilistic model of connectivity in the hatchling Xenopus tadpole spinal cord which, when combined with a spiking model, reliably produces rhythmic activity corresponding to swimming. The probabilistic model allows calculation of structural characteristics that reflect common network properties, independent of individual network realisations. We use the structural characteristics to study examples of neuronal dynamics, in the complete network and various sub-networks, and this allows us to explain the basis for key experimental findings, and make predictions for experiments. We also study how structural and functional features differ between detailed anatomical connectomes and those generated by our new, simpler, model (meta-model).

And yet it moves: Recovery of volitional control after spinal cord injury

Preclinical and clinical neurophysiological and neurorehabilitation research has generated rather surprising levels of recovery of volitional sensory-motor function in persons with chronic motor paralysis following a spinal cord injury. The key factor in this recovery is largely activity-dependent plasticity of spinal and supraspinal networks. This key factor can be triggered by neuromodulation of these networks with electrical and pharmacological interventions. This review addresses some of the systems-level physiological mechanisms that might explain the effects of electrical modulation and how repetitive training facilitates the recovery of volitional motor control. In particular, we substantiate the hypotheses that: (1) in the majority of spinal lesions, a critical number and type of neurons in the region of the injury survive, but cannot conduct action potentials, and thus are electrically non-responsive; (2) these neuronal networks within the lesioned area can be neuromodulated to a transformed state of electrical competency; (3) these two factors enable the potential for extensive activity-dependent reorganization of neuronal networks in the spinal cord and brain, and (4) propriospinal networks play a critical role in driving this activity-dependent reorganization after injury. Real-time proprioceptive input to spinal networks provides the template for reorganization of spinal networks that play a leading role in the level of coordination of motor pools required to perform a given functional task. Repetitive exposure of multi-segmental sensory-motor networks to the dynamics of task-specific sensory input as occurs with repetitive training can functionally reshape spinal and supraspinal connectivity thus re-enabling one to perform complex motor tasks, even years post injury.

Generative models for network neuroscience: prospects and promise

Network neuroscience is the emerging discipline concerned with investigating the complex patterns of interconnections found in neural systems, and identifying principles with which to understand them. Within this discipline, one particularly powerful approach is network generative modelling, in which wiring rules are algorithmically implemented to produce synthetic network architectures with the same properties as observed in empirical network data. Successful models can highlight the principles by which a network is organized and potentially uncover the mechanisms by which it grows and develops. Here, we review the prospects and promise of generative models for network neuroscience. We begin with a primer on network generative models, with a discussion of compressibility and predictability, and utility in intuiting mechanisms, followed by a short history on their use in network science, broadly. We then discuss generative models in practice and application, paying particular attention to the critical need for cross-validation. Next, we review generative models of biological neural networks, both at the cellular and large-scale level, and across a variety of species including Caenorhabditis elegans, Drosophila, mouse, rat, cat, macaque and human. We offer a careful treatment of a few relevant distinctions, including differences between generative models and null models, sufficiency and redundancy, inferring and claiming mechanism, and functional and structural connectivity. We close with a discussion of future directions, outlining exciting frontiers both in empirical data collection efforts as well as in method and theory development that, together, further the utility of the generative network modelling approach for network neuroscience.

Studying the role of axon fasciculation during development in a computational model of the Xenopus tadpole spinal cord

During nervous system development growing axons can interact with each other, for example by adhering together in order to produce bundles (fasciculation). How does such axon-axon interaction affect the resulting axonal trajectories, and what are the possible benefits of this process in terms of network function? In this paper we study these questions by adapting an existing computational model of the development of neurons in the Xenopus tadpole spinal cord to include interactions between axons. We demonstrate that even relatively weak attraction causes bundles to appear, while if axons weakly repulse each other their trajectories diverge such that they fill the available space. We show how fasciculation can help to ensure axons grow in the correct location for proper network formation when normal growth barriers contain gaps, and use a functional spiking model to show that fasciculation allows the network to generate reliable swimming behaviour even when overall synapse counts are artificially lowered. Although we study fasciculation in one particular organism, our approach to modelling axon growth is general and can be widely applied to study other nervous systems.

The modulation of two motor behaviors by persistent sodium currents in Xenopus laevis tadpoles

We have characterized persistent sodium currents in three groups of spinal neurons and their role in shaping spiking activity in the Xenopus tadpole. We then attempted to evaluate the role of persistent sodium currents in regulating tadpole swimming and struggling motor outputs by using low concentrations of the persistent sodium current antagonist riluzole.

Persistent sodium currents (I_NaP) are common in neuronal circuitries and have been implicated in several diseases, such as amyotrophic lateral sclerosis (ALS) and epilepsy. However, the role of I_NaP in the regulation of specific behaviors is still poorly understood. In this study we have characterized I_NaP and investigated its role in the swimming and struggling behavior of Xenopus tadpoles. I_NaP was identified in three groups of neurons, namely, sensory Rohon-Beard neurons (RB neurons), descending interneurons (dINs), and non-dINs (neurons rhythmically active in swimming). All groups of neurons expressed I_NaP, but the currents differed in decay time constants, amplitudes, and the membrane potential at which I_NaP peaked. Low concentrations (1 µM) of the I_NaP blocker riluzole blocked I_NaP ~30% and decreased the excitability of the three neuron groups without affecting spike amplitudes or cellular input resistances. Riluzole reduced the number of rebound spikes in dINs and depressed repetitive firing in RB neurons and non-dINs. At the behavior level, riluzole at 1 µM shortened fictive swimming episodes. It also reduced the number of action potentials neurons fired on each struggling cycle. The results show that I_NaP may play important modulatory roles in motor behaviors.

NEW & NOTEWORTHY We have characterized persistent sodium currents in three groups of spinal neurons and their role in shaping spiking activity in the Xenopus tadpole. We then attempted to evaluate the role of persistent sodium currents in regulating tadpole swimming and struggling motor outputs by using low concentrations of the persistent sodium current antagonist riluzole.

Mechanosensory neurons control the timing of spinal microcircuit selection during locomotion

Despite numerous physiological studies about reflexes in the spinal cord, the contribution of mechanosensory feedback to active locomotion and the nature of underlying spinal circuits remains elusive. Here we investigate how mechanosensory feedback shapes active locomotion in a genetic model organism exhibiting simple locomotion-the zebrafish larva. We show that mechanosensory feedback enhances the recruitment of motor pools during active locomotion. Furthermore, we demonstrate that inputs from mechanosensory neurons increase locomotor speed by prolonging fast swimming at the expense of slow swimming during stereotyped acoustic escape responses. This effect could be mediated by distinct mechanosensory neurons. In the spinal cord, we show that connections compatible with monosynaptic inputs from mechanosensory Rohon-Beard neurons onto ipsilateral V2a interneurons selectively recruited at high speed can contribute to the observed enhancement of speed. Altogether, our study reveals the basic principles and a circuit diagram enabling speed modulation by mechanosensory feedback in the vertebrate spinal cord.

Mechanisms of Connectome Development

At the centenary of D'Arcy Thompson's seminal work 'On Growth and Form', pioneering the description of principles of morphological changes during development and evolution, recent experimental advances allow us to study change in anatomical brain networks. Here, we outline potential principles for connectome development. We will describe recent results on how spatial and temporal factors shape connectome development in health and disease. Understanding the developmental origins of brain diseases in individuals will be crucial for deciding on personalized treatment options. We argue that longitudinal studies, experimentally derived parameters for connection formation, and biologically realistic computational models are needed to better understand the link between brain network development, network structure, and network function.

Zebrafish transgenic constructs label specific neurons in Xenopus laevis spinal cord and identify frog V0v spinal neurons

A correctly functioning spinal cord is crucial for locomotion and communication between body and brain but there are fundamental gaps in our knowledge of how spinal neuronal circuitry is established and functions. To understand the genetic program that regulates specification and functions of this circuitry, we need to connect neuronal molecular phenotypes with physiological analyses. Studies using Xenopus laevis tadpoles have increased our understanding of spinal cord neuronal physiology and function, particularly in locomotor circuitry. However, the X. laevis tetraploid genome and long generation time make it difficult to investigate how neurons are specified. The opacity of X. laevis embryos also makes it hard to connect functional classes of neurons and the genes that they express. We demonstrate here that Tol2 transgenic constructs using zebrafish enhancers that drive expression in specific zebrafish spinal neurons label equivalent neurons in X. laevis and that the incorporation of a Gal4:UAS amplification cassette enables cells to be observed in live X. laevis tadpoles. This technique should enable the molecular phenotypes, morphologies and physiologies of distinct X. laevis spinal neurons to be examined together in vivo. We have used an islet1 enhancer to label Rohon-Beard sensory neurons and evx enhancers to identify V0v neurons, for the first time, in X. laevis spinal cord. Our work demonstrates the homology of spinal cord circuitry in zebrafish and X. laevis, suggesting that future work could combine their relative strengths to elucidate a more complete picture of how vertebrate spinal cord neurons are specified, and function to generate behavior. © 2017 Wiley Periodicals, Inc. Develop Neurobiol 77: 1007-1020, 2017.

Weighing the Evidence in Peters' Rule: Does Neuronal Morphology Predict Connectivity?

Although the importance of network connectivity is increasingly recognized, identifying synapses remains challenging relative to the routine characterization of neuronal morphology. Thus, researchers frequently employ axon-dendrite colocations as proxies of potential connections. This putative equivalence, commonly referred to as Peters' rule, has been recently studied at multiple levels and scales, fueling passionate debates regarding its validity. Our critical literature review identifies three conceptually distinct but often confused applications: inferring neuron type circuitry, predicting synaptic contacts among individual cells, and estimating synapse numbers within neuron pairs. Paradoxically, at the originally proposed cell-type level, Peters' rule remains largely untested. Leveraging Hippocampome.org, we validate and refine the relationship between axonal-dendritic colocations and synaptic circuits, clarifying the interpretation of existing and forthcoming data.

Dual Function of NRP1 in Axon Guidance and Subcellular Target Recognition in Cerebellum

Subcellular target recognition in the CNS is the culmination of a multiple-step program including axon guidance, target recognition, and synaptogenesis. In cerebellum, basket cells (BCs) innervate the soma and axon initial segment (AIS) of Purkinje cells (PCs) to form the pinceau synapse, but the underlying mechanisms remain incompletely understood. Here, we demonstrate that neuropilin-1 (NRP1), a Semaphorin receptor expressed in BCs, controls both axonal guidance and subcellular target recognition. We show that loss of Semaphorin 3A function or specific deletion of NRP1 in BCs alters the stereotyped organization of BC axon and impairs pinceau synapse formation. Further, we identified NRP1 as a trans-synaptic binding partner of the cell adhesion molecule neurofascin-186 (NF186) expressed in the PC AIS during pinceau synapse formation. These findings identify a dual function of NRP1 in both axon guidance and subcellular target recognition in the construction of GABAergic circuitry.

Homeostatic Activity-Dependent Tuning of Recurrent Networks for Robust Propagation of Activity

Developing neuronal networks display spontaneous bursts of action potentials that are necessary for circuit organization and tuning. While spontaneous activity has been shown to instruct map formation in sensory circuits, it is unknown whether it plays a role in the organization of motor networks that produce rhythmic output. Using computational modeling, we investigate how recurrent networks of excitatory and inhibitory neuronal populations assemble to produce robust patterns of unidirectional and precisely timed propagating activity during organism locomotion. One example is provided by the motor network inDrosophilalarvae, which generates propagating peristaltic waves of muscle contractions during crawling. We examine two activity-dependent models, which tune weak network connectivity based on spontaneous activity patterns: a Hebbian model, where coincident activity in neighboring populations strengthens connections between them; and a homeostatic model, where connections are homeostatically regulated to maintain a constant level of excitatory activity based on spontaneous input. The homeostatic model successfully tunes network connectivity to generate robust activity patterns with appropriate timing relationships between neighboring populations. These timing relationships can be modulated by the properties of spontaneous activity, suggesting its instructive role for generating functional variability in network output. In contrast, the Hebbian model fails to produce the tight timing relationships between neighboring populations required for unidirectional activity propagation, even when additional assumptions are imposed to constrain synaptic growth. These results argue that homeostatic mechanisms are more likely than Hebbian mechanisms to tune weak connectivity based on spontaneous input in a recurrent network for rhythm generation and robust activity propagation.

SIGNIFICANCE STATEMENT

How are neural circuits organized and tuned to maintain stable function and produce robust output? This task is especially difficult during development, when circuit properties change in response to variable environments and internal states. Many developing circuits exhibit spontaneous activity, but its role in the synaptic organization of motor networks that produce rhythmic output is unknown. We studied a model motor network, that when appropriately tuned, generates propagating activity as during crawling inDrosophilalarvae. Based on experimental evidence of activity-dependent tuning of connectivity, we examined plausible mechanisms by which appropriate connectivity emerges. Our results suggest that activity-dependent homeostatic mechanisms are better suited than Hebbian mechanisms for organizing motor network connectivity, and highlight an important difference from sensory areas.

Developmental time windows for axon growth influence neuronal network topology

Early brain connectivity development consists of multiple stages: birth of neurons, their migration and the subsequent growth of axons and dendrites. Each stage occurs within a certain period of time depending on types of neurons and cortical layers. Forming synapses between neurons either by growing axons starting at similar times for all neurons (much-overlapped time windows) or at different time points (less-overlapped) may affect the topological and spatial properties of neuronal networks. Here, we explore the extreme cases of axon formation during early development, either starting at the same time for all neurons (parallel, i.e., maximally overlapped time windows) or occurring for each neuron separately one neuron after another (serial, i.e., no overlaps in time windows). For both cases, the number of potential and established synapses remained comparable. Topological and spatial properties, however, differed: Neurons that started axon growth early on in serial growth achieved higher out-degrees, higher local efficiency and longer axon lengths while neurons demonstrated more homogeneous connectivity patterns for parallel growth. Second, connection probability decreased more rapidly with distance between neurons for parallel growth than for serial growth. Third, bidirectional connections were more numerous for parallel growth. Finally, we tested our predictions with C. elegans data. Together, this indicates that time windows for axon growth influence the topological and spatial properties of neuronal networks opening up the possibility to a posteriori estimate developmental mechanisms based on network properties of a developed network.

Neuronal wiring: linking dendrite placement to synapse formation

Understanding the processes that drive the formation of synapses between specific neurons within a circuit is critical to understanding how neural networks develop. A new study of synapse formation between motor neurons and pre-synaptic partners highlights the importance of dendrite placement.

Development of connectivity in a motoneuronal network in Drosophila larvae

Background

Much of our understanding of how neural networks develop is based on studies of sensory systems, revealing often highly stereotyped patterns of connections, particularly as these diverge from the presynaptic terminals of sensory neurons. We know considerably less about the wiring strategies of motor networks, where connections converge onto the dendrites of motoneurons. Here, we investigated patterns of synaptic connections between identified motoneurons with sensory neurons and interneurons in the motor network of the Drosophila larva and how these change as it develops.

Results

We find that as animals grow, motoneurons increase the number of synapses with existing presynaptic partners. Different motoneurons form characteristic cell-type-specific patterns of connections. At the same time, there is considerable variability in the number of synapses formed on motoneuron dendrites, which contrasts with the stereotypy reported for presynaptic terminals of sensory neurons. Where two motoneurons of the same cell type contact a common interneuron partner, each postsynaptic cell can arrive at a different connectivity outcome. Experimentally changing the positioning of motoneuron dendrites shows that the geography of dendritic arbors in relation to presynaptic partner terminals is an important determinant in shaping patterns of connectivity.

Conclusions

In the Drosophila larval motor network, the sets of connections that form between identified neurons manifest an unexpected level of variability. Synapse number and the likelihood of forming connections appear to be regulated on a cell-by-cell basis, determined primarily by the postsynaptic dendrites of motoneuron terminals.

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Growing motoneurons consolidate synapses with existing presynaptic partners

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Motoneuron dendritic arbors are active parties in setting connectivity patterns

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Cell-type-specific features coexist with variations at the individual cell level

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Motoneuron wiring strategies may contrast with those of sensory neurons

A synaptic mechanism for network synchrony

Within neural networks, synchronization of activity is dependent upon the synaptic connectivity of embedded microcircuits and the intrinsic membrane properties of their constituent neurons. Synaptic integration, dendritic Ca²⁺ signaling, and non-linear interactions are crucial cellular attributes that dictate single neuron computation, but their roles promoting synchrony and the generation of network oscillations are not well understood, especially within the context of a defined behavior. In this regard, the lamprey spinal central pattern generator (CPG) stands out as a well-characterized, conserved vertebrate model of a neural network (Smith et al., 2013a), which produces synchronized oscillations in which neural elements from the systems to cellular level that control rhythmic locomotion have been determined. We review the current evidence for the synaptic basis of oscillation generation with a particular emphasis on the linkage between synaptic communication and its cellular coupling to membrane processes that control oscillatory behavior of neurons within the locomotor network. We seek to relate dendritic function found in many vertebrate systems to the accessible lamprey central nervous system in which the relationship between neural network activity and behavior is well understood. This enables us to address how Ca²⁺ signaling in spinal neuron dendrites orchestrate oscillations that drive network behavior.

Can simple rules control development of a pioneer vertebrate neuronal network generating behavior?

How do the pioneer networks in the axial core of the vertebrate nervous system first develop? Fundamental to understanding any full-scale neuronal network is knowledge of the constituent neurons, their properties, synaptic interconnections, and normal activity. Our novel strategy uses basic developmental rules to generate model networks that retain individual neuron and synapse resolution and are capable of reproducing correct, whole animal responses. We apply our developmental strategy to young Xenopus tadpoles, whose brainstem and spinal cord share a core vertebrate plan, but at a tractable complexity. Following detailed anatomical and physiological measurements to complete a descriptive library of each type of spinal neuron, we build models of their axon growth controlled by simple chemical gradients and physical barriers. By adding dendrites and allowing probabilistic formation of synaptic connections, we reconstruct network connectivity among up to 2000 neurons. When the resulting "network" is populated by model neurons and synapses, with properties based on physiology, it can respond to sensory stimulation by mimicking tadpole swimming behavior. This functioning model represents the most complete reconstruction of a vertebrate neuronal network that can reproduce the complex, rhythmic behavior of a whole animal. The findings validate our novel developmental strategy for generating realistic networks with individual neuron- and synapse-level resolution. We use it to demonstrate how early functional neuronal connectivity and behavior may in life result from simple developmental "rules," which lay out a scaffold for the vertebrate CNS without specific neuron-to-neuron recognition.

A developmental approach to predicting neuronal connectivity from small biological datasets: a gradient-based neuron growth model

Relating structure and function of neuronal circuits is a challenging problem. It requires demonstrating how dynamical patterns of spiking activity lead to functions like cognitive behaviour and identifying the neurons and connections that lead to appropriate activity of a circuit. We apply a “developmental approach” to define the connectome of a simple nervous system, where connections between neurons are not prescribed but appear as a result of neuron growth. A gradient based mathematical model of two-dimensional axon growth from rows of undifferentiated neurons is derived for the different types of neurons in the brainstem and spinal cord of young tadpoles of the frog Xenopus. Model parameters define a two-dimensional CNS growth environment with three gradient cues and the specific responsiveness of the axons of each neuron type to these cues. The model is described by a nonlinear system of three difference equations; it includes a random variable, and takes specific neuron characteristics into account. Anatomical measurements are first used to position cell bodies in rows and define axon origins. Then a generalization procedure allows information on the axons of individual neurons from small anatomical datasets to be used to generate larger artificial datasets. To specify parameters in the axon growth model we use a stochastic optimization procedure, derive a cost function and find the optimal parameters for each type of neuron. Our biologically realistic model of axon growth starts from axon outgrowth from the cell body and generates multiple axons for each different neuron type with statistical properties matching those of real axons. We illustrate how the axon growth model works for neurons with axons which grow to the same and the opposite side of the CNS. We then show how, by adding a simple specification for dendrite morphology, our model “developmental approach” allows us to generate biologically-realistic connectomes.

Principles of interneuron development learned from Renshaw cells and the motoneuron recurrent inhibitory circuit

Renshaw cells provide a convenient model to study spinal circuit development during the emergence of motor behaviors with the goal of capturing principles of interneuron specification and circuit construction. This work is facilitated by a long history of research that generated essential knowledge about the characteristics that define Renshaw cells and the recurrent inhibitory circuit they form with motoneurons. In this review, we summarize recent data on the specification of Renshaw cells and their connections. A major insight from these studies is that the basic Renshaw cell phenotype is specified before circuit assembly, a result of their early neurogenesis and migration. Connectivity is later added, constrained by their placement in the spinal cord. Finally, different rates of synapse proliferation alter the relative weights of different inputs on postnatal Renshaw cells. Based on this work some general principles on the integration of spinal interneurons in developing motor circuits are derived.

A functional scaffold of CNS neurons for the vertebrates: the developing Xenopus laevis spinal cord

In young and developing amphibians and fish the spinal cord is functional but remarkably simple compared with the adult. Is the pattern of neurons and their connections common across at least these lower vertebrates? Does this basic pattern extend into the brainstem? Could the development of simple functioning neuronal networks depend on very basic rules of connectivity and act as pioneer networks providing a substrate for the development of more complex and subtle networks. In this review of the functional neuron classes in the Xenopus laevis tadpole spinal cord up to hatching, we will consider progress and difficulties in using anatomy, transcription factor expression, physiology, and activity to define spinal neuron types. Even here it is not straightforward and is rarely possible to bring all the different strands of evidence together. But, we think we have a rather complete picture of the hatchling tadpole spinal neuron types and can define clear roles for most of them in behavior. Our present knowledge about the hatchling Xenopus spinal cord should set up many of the problems to be unraveled in the future by more developmentally oriented research.

Modeling the connectome of a simple spinal cord

In this paper we develop a computational model of the anatomy of a spinal cord. We address a long-standing ambition of neuroscience to understand the structure–function problem by modeling the complete spinal cord connectome map in the 2-day old hatchling Xenopus tadpole. Our approach to modeling neuronal connectivity is based on developmental processes of axon growth. A simple mathematical model of axon growth allows us to reconstruct a biologically realistic connectome of the tadpole spinal cord based on neurobiological data. In our model we distribute neuron cell bodies and dendrites on both sides of the body based on experimental measurements. If growing axons cross the dendrite of another neuron, they make a synaptic contact with a defined probability. The total neuronal network contains ∼1,500 neurons of six cell-types with a total of ∼120,000 connections. The anatomical model contains random components so each repetition of the connectome reconstruction procedure generates a different neuronal network, though all share consistent features such as distributions of cell bodies, dendrites, and axon lengths. Our study reveals a complex structure for the connectome with many interesting specific features including contrasting distributions of connection length distributions. The connectome also shows some similarities to connectivity graphs for other animals such as the global neuronal network of C. elegans. In addition to the interesting intrinsic properties of the connectome, we expect the ability to grow and analyze a biologically realistic spinal cord connectome will provide valuable insights into the properties of the real neuronal networks underlying simple behavior.

Semaphorin 3A induces CaV2.3 channel-dependent conversion of axons to dendrites

Polarized neurites (axons and dendrites) form the functional circuitry of the nervous system. Secreted guidance cues often control the polarity of neuron migration and neurite outgrowth by regulating ion channels. Here, we show that secreted semaphorin 3A (Sema3A) induces the neurite identity of Xenopus spinal commissural interneurons (xSCINs) by activating Ca(V)2.3 channels (Ca(V)2.3). Sema3A treatment converted the identity of axons of cultured xSCINs to that of dendrites by recruiting functional Ca(V)2.3. Inhibition of Sema3A signalling prevented both the expression of Ca(V)2.3 and acquisition of the dendrite identity, and inhibition of Ca(V)2.3 function resulted in multiple axon-like neurites of xSCINs in the spinal cord. Furthermore, Sema3A-triggered cGMP production and PKG activity induced, respectively, the expression of functional Ca(V)2.3 and the dendrite identity. These results reveal a mechanism by which a guidance cue controls the identity of neurites during nervous system development.

Spinal interneurons differentiate sequentially from those driving the fastest swimming movements in larval zebrafish to those driving the slowest ones

Studies of neuronal networks have revealed few general principles that link patterns of development with later functional roles. While investigating the neural control of movements, we recently discovered a topographic map in the spinal cord of larval zebrafish that relates the position of motoneurons and interneurons to their order of recruitment during swimming. Here, we show that the map reflects an orderly pattern of differentiation of neurons driving different movements. First, we use high-speed filming to show that large-amplitude swimming movements with bending along much of the body appear first, with smaller, regional swimming movements emerging later. Next, using whole-cell patch recordings, we demonstrate that the excitatory circuits that drive large-amplitude, fast swimming movements at larval stages are present and functional early on in embryos. Finally, we systematically assess the orderly emergence of spinal circuits according to swimming speed using transgenic fish expressing the photoconvertible protein Kaede to track neuronal differentiation in vivo. We conclude that a simple principle governs the development of spinal networks in which the neurons driving the fastest, most powerful swimming in larvae develop first with ones that drive increasingly weaker and slower larval movements layered on over time. Because the neurons are arranged by time of differentiation in the spinal cord, the result is a topographic map that represents the speed/strength of movements at which neurons are recruited and the temporal emergence of networks. This pattern may represent a general feature of neuronal network development throughout the brain and spinal cord.

Stringent specificity in the construction of a GABAergic presynaptic inhibitory circuit

GABAergic interneurons are key elements in neural coding, but the mechanisms that assemble inhibitory circuits remain unclear. In the spinal cord, the transfer of sensory signals to motor neurons is filtered by GABAergic interneurons that act presynaptically to inhibit sensory transmitter release and postsynaptically to inhibit motor neuron excitability. We show here that the connectivity and synaptic differentiation of GABAergic interneurons that mediate presynaptic inhibition is directed by their sensory targets. In the absence of sensory terminals these GABAergic neurons shun other available targets, fail to undergo presynaptic differentiation, and withdraw axons from the ventral spinal cord. A sensory-specific source of brain derived neurotrophic factor induces synaptic expression of the GABA synthetic enzyme GAD65--a defining biochemical feature of this set of interneurons. The organization of a GABAergic circuit that mediates presynaptic inhibition in the mammalian CNS is therefore controlled by a stringent program of sensory recognition and signaling.

Dendritic targeting in the leg neuropil of Drosophila: the role of midline signalling molecules in generating a myotopic map

Neural maps are emergent, highly ordered structures that are essential for organizing and presenting synaptic information. Within the embryonic nervous system of Drosophila motoneuron dendrites are organized topographically as a myotopic map that reflects their pattern of innervation in the muscle field. Here we reveal that this fundamental organizational principle exists in adult Drosophila, where the dendrites of leg motoneurons also generate a myotopic map. A single postembryonic neuroblast sequentially generates different leg motoneuron subtypes, starting with those innervating proximal targets and medial neuropil regions and producing progeny that innervate distal muscle targets and lateral neuropil later in the lineage. Thus the cellular distinctions in peripheral targets and central dendritic domains, which make up the myotopic map, are linked to the birth-order of these motoneurons. Our developmental analysis of dendrite growth reveals that this myotopic map is generated by targeting. We demonstrate that the medio-lateral positioning of motoneuron dendrites in the leg neuropil is controlled by the midline signalling systems Slit-Robo and Netrin-Fra. These results reveal that dendritic targeting plays a major role in the formation of myotopic maps and suggests that the coordinate spatial control of both pre- and postsynaptic elements by global neuropilar signals may be an important mechanism for establishing the specificity of synaptic connections.

Midline signalling systems direct the formation of a neural map by dendritic targeting in the Drosophila motor system

A fundamental strategy for organising connections in the nervous system is the formation of neural maps. Map formation has been most intensively studied in sensory systems where the central arrangement of axon terminals reflects the distribution of sensory neuron cell bodies in the periphery or the sensory modality. This straightforward link between anatomy and function has facilitated tremendous progress in identifying cellular and molecular mechanisms that underpin map development. Much less is known about the way in which networks that underlie locomotion are organised. We recently showed that in the Drosophila embryo, dendrites of motorneurons form a neural map, being arranged topographically in the antero-posterior axis to represent the distribution of their target muscles in the periphery. However, the way in which a dendritic myotopic map forms has not been resolved and whether postsynaptic dendrites are involved in establishing sets of connections has been relatively little explored. In this study, we show that motorneurons also form a myotopic map in a second neuropile axis, with respect to the ventral midline, and they achieve this by targeting their dendrites to distinct medio-lateral territories. We demonstrate that this map is "hard-wired"; that is, it forms in the absence of excitatory synaptic inputs or when presynaptic terminals have been displaced. We show that the midline signalling systems Slit/Robo and Netrin/Frazzled are the main molecular mechanisms that underlie dendritic targeting with respect to the midline. Robo and Frazzled are required cell-autonomously in motorneurons and the balance of their opposite actions determines the dendritic target territory. A quantitative analysis shows that dendritic morphology emerges as guidance cue receptors determine the distribution of the available dendrites, whose total length and branching frequency are specified by other cell intrinsic programmes. Our results suggest that the formation of dendritic myotopic maps in response to midline guidance cues may be a conserved strategy for organising connections in motor systems. We further propose that sets of connections may be specified, at least to a degree, by global patterning systems that deliver pre- and postsynaptic partner terminals to common "meeting regions."

Longitudinal neuronal organization and coordination in a simple vertebrate: a continuous, semi-quantitative computer model of the central pattern generator for swimming in young frog tadpoles

When frog tadpoles hatch their swimming requires co-ordinated contractions of trunk muscles, driven by motoneurons and controlled by a Central Pattern Generator (CPG). To study this co-ordination we used a 3.5 mm long population model of the young tadpole CPG with continuous distributions of neurons and axon lengths as estimated anatomically. We found that: (1) alternating swimming-type activity fails to self-sustain unless some excitatory interneurons have ascending axons, (2) a rostro-caudal (R-C) gradient in the distribution of excitatory premotor interneurons with short axons is required to obtain the R-C gradient in excitation and resulting progression of motoneuron firing necessary for forward swimming, (3) R-C delays in motoneuron firing decrease if excitatory motoneuron to premotor interneuron synapses are present, (4) these feedback connections and the electrical synapses between motoneurons synchronise motoneuron discharges locally, (5) the above findings are independent of the detailed membrane properties of neurons.

Excitatory and inhibitory intermediate zone interneurons in pathways from feline group I and II afferents: differences in axonal projections and input

The aim of the present study was to compare properties of excitatory and inhibitory spinal intermediate zone interneurons in pathways from group I and II muscle afferents in the cat. Interneurons were labelled intracellularly and their transmitter phenotypes were defined by using immunocytochemistry. In total 14 glutamatergic, 22 glycinergic and 2 GABAergic/glycinergic interneurons were retrieved. All interneurons were located in laminae V-VII of the L3-L7 segments. No consistent differences were found in the location, the soma sizes or the extent of the dendritic trees of excitatory and inhibitory interneurons. However, major differences were found in their axonal projections; excitatory interneurons projected either ipsilaterally, bilaterally or contralaterally, while inhibitory interneurons projected exclusively ipsilaterally. Terminal projections of glycinergic and glutamatergic cells were found within motor nuclei as well as other regions of the grey matter which include the intermediate region, laminae VII and VIII. Cells containing GABA/glycine had more restricted projections, principally within the intermediate zone where they formed appositions with glutamatergic axon terminals and unidentified cells and therefore are likely to be involved in presynaptic as well as postsynaptic inhibition. The majority of excitatory and inhibitory interneurons were found to be coexcited by group I and II afferents (monosynaptically) and by reticulospinal neurons (mono- or disynaptically) and to integrate information from several muscles. Taken together the morphological and electrophysiological data show that individual excitatory and inhibitory intermediate zone interneurons may operate in a highly differentiated way and thereby contribute to a variety of motor synergies.

The development of motor coordination in Drosophila embryos

We used non-invasive muscle imaging to study the onset of motor activity and emergence of coordinated movement in Drosophila embryos. Earliest movements are myogenic, and neurally controlled muscle contractions first appear with the onset of bursting activity 17 hours after egg laying. Initial episodes of activity are poorly organised and coordinated crawling sequences only begin to appear after a further hour of bursting. Thus, network performance improves during this first period of activity. The embryo continues to exhibit bursts of crawling-like sequences until shortly before hatching, while other reflexes also mature. Bursting does not begin as a reflex response to sensory input but appears to reflect the onset of spontaneous activity in the motor network. It does not require GABA-mediated transmission, and, by using a light-activated channel to excite the network, we demonstrate activity-dependent depression that may cause burst termination.