Hub Neuron Research Articles

Functional analysis of conserved C. elegans bHLH family members uncovers lifespan control by a peptidergic hub neuron.

Throughout the animal kingdom, several members of the basic helix-loop-helix (bHLH) family act as proneural genes during early steps of nervous system development. Roles of bHLH genes in specifying terminal differentiation of postmitotic neurons have been less extensively studied. We analyze here the function of five C. elegans bHLH genes, falling into three phylogenetically conserved subfamilies, which are continuously expressed in a very small number of postmitotic neurons in the central nervous system. We show (a) that two orthologs of the vertebrate bHLHb4/b5 genes, called hlh-17 and hlh-32, function redundantly to specify the identity of a single head interneuron (AUA), as well as an individual motor neuron (VB2), (b) that the PTF1a ortholog hlh-13 acts as a terminal selector to control terminal differentiation and function of the sole octopaminergic neuron class in C. elegans, RIC, and (c) that the NHLH1/2 ortholog hlh-15 controls terminal differentiation and function of the peptidergic AVK head interneuron class, a known neuropeptidergic signaling hub in the animal. Strikingly, through null mutant analysis and cell-specific rescue experiments, we find that loss of hlh-15/NHLH in the peptidergic AVK neurons and the resulting abrogation of neuropeptide secretion causes a substantially expanded lifespan of the animal, revealing an unanticipated impact of a central, peptidergic hub neuron in regulating lifespan, which we propose to be akin to hypothalamic control of lifespan in vertebrates. Taken together, our functional analysis reveals themes of bHLH gene function during terminal differentiation that are complementary to the earlier lineage specification roles of other bHLH family members. However, such late functions are much more sparsely employed by members of the bHLH transcription factor family, compared to the function of the much more broadly employed homeodomain transcription factor family.

Synchronous tonic-to-bursting transitions in a neuronal hub motif.

We study a heterogeneous neuronal network motif where a central node (hub neuron) is connected via electrical synapses to other nodes (peripheral neurons). Our numerical simulations show that the networked neurons synchronize in three different states: (i) robust tonic, (ii) robust bursting, and (iii) tonic initially evolving to bursting through a period-doubling cascade and chaos transition. This third case displays interesting features, including the carrying on of a characteristic firing rate found in the single neuron tonic-to-bursting transition.

Sexually Dimorphic Differentiation of a C. elegans Hub Neuron Is Cell Autonomously Controlled by a Conserved Transcription Factor

Functional and anatomical sexual dimorphisms in the brain are either the result of cells that are generated only in one sex or a manifestation of sex-specific differentiation of neurons present in both sexes. The PHC neuron pair of the nematode C.elegans differentiates in a strikingly sex-specific manner. In hermaphrodites the PHC neurons display a canonical pattern of synaptic connectivity similar to that of other sensory neurons, but in males PHC differentiates into a densely connected hub sensory neuron/interneuron, integrating a large number of male-specific synaptic inputs and conveying them to both male-specific and sex-shared circuitry. We show that the differentiation into such a hub neuron involves thesex-specific scaling of several components of thesynaptic vesicle machinery, including the vesicular glutamate transporter eat-4/VGLUT, induction of neuropeptide expression, changes in axonal projection morphology, and a switch in neuronal function. We demonstrate that these molecular and anatomical remodeling events are controlled cell autonomously by the phylogenetically conserved Doublesex homolog dmd-3, which is both required and sufficient for sex-specific PHC differentiation. Cellular specificity of dmd-3 action is ensured byitscollaboration with non-sex-specific terminal selector-type transcription factors, whereas the sex specificity of dmd-3 action is ensured by the hermaphrodite-specific transcriptional master regulator of hermaphroditic cell identity tra-1, which represses the transcription of dmd-3 in hermaphrodite PHC. Taken together, our studies provide mechanistic insights into how neurons are specified in a sexually dimorphic manner.

Modulation of a Single Neuron Has State-Dependent Actions on Circuit Dynamics,.

When does neuromodulation of a single neuron influence the output of the entire network? We constructed a five-cell circuit in which a neuron is at the center of the circuit and the remaining neurons form two distinct oscillatory subnetworks. All neurons were modeled as modified Morris-Lecar models with a hyperpolarization-activated conductance (ḡh ) in addition to calcium (ḡCa ), potassium (ḡK ), and leak conductances. We determined the effects of varying ḡCa , ḡK , and ḡh on the frequency, amplitude, and duty cycle of a single neuron oscillator. The frequency of the single neuron was highest when the ḡK and ḡh conductances were high and ḡCa was moderate whereas, in the traditional Morris-Lecar model, the highest frequencies occur when both ḡK and ḡCa are high. We randomly sampled parameter space to find 143 hub oscillators with nearly identical frequencies but with disparate maximal conductance, duty cycles, and burst amplitudes, and then embedded each of these hub neurons into networks with different sets of synaptic parameters. For one set of network parameters, circuit behavior was virtually identical regardless of the underlying conductances of the hub neuron. For a different set of network parameters, circuit behavior varied with the maximal conductances of the hub neuron. This demonstrates that neuromodulation of a single target neuron may dramatically alter the performance of an entire network when the network is in one state, but have almost no effect when the circuit is in a different state.

The role of interconnected hub neurons in cortical dynamics

The structure of synaptic connectivity plays an important role in information processing and dynamics of neuronal microcircuits. Previous work has shown that cortical microcircuits contain non-random features of the network structure [1], and that these affect neuronal dynamics [2]. Earlier models of non-random network structure proposed local correlations in synaptic weight or connection number (degree) [3, 4]. In such network models, there are neurons receiving stronger synaptic weights or higher numbers of synapses compared to other neurons. Here, we refer to the former neuron type as hub neuron, or simply hub. In other words, a hub receives strong synapses, but not necessarily a higher number of synapses. Importantly, a hub results from the structure of the network and not from differences in neuron parameters. Here we introduce the network feature of connectedness of hub neurons. We show that an elevated connection probability between hubs affects various aspects of network activity, ranging from spontaneous oscillations to the response of cortical populations to stimulation. A subpopulation of connected hubs can be analyzed using common mean-field methods. This analysis reveals two stable fixed points of the spiking activity, one at a low firing rate and another one at a high firing rate. We first model a single layer of a column of rodent barrel cortex. The subpopulation of connected hubs switches between the two fixed points and generates up-state/down-state oscillations (see Figure 1), and thus acts as the “heart” of the oscillator. Furthermore, we demonstrate that the different characteristics of cortical layer responses in optogenetic stimulation experiments [5] can be explained by the absence or presence of connected hubs. Finally, we extend the system to contain several connected hubs subpopulations. Such multiheart oscillators generate irregular oscillations, reminiscent of spontaneous cortical activity.

Rectifying Electrical Synapses Can Affect the Influence of Synaptic Modulation on Output Pattern Robustness

Rectifying electrical synapses are commonplace, but surprisingly little is known about how rectification alters the dynamics of neuronal networks. In this study, we use computational models to investigate how rectifying electrical synapses change the behavior of a small neuronal network that exhibits complex rhythmic output patterns. We begin with an electrically coupled circuit of three oscillatory neurons with different starting frequencies, and subsequently add two additional neurons and inhibitory chemical synapses. The five-cell model represents a pattern-generating neuronal network with two simultaneous rhythms competing for the recruitment of a hub neuron. We compare four different configurations of rectifying synapse placement and polarity, and we investigate how rectification changes the functional output of this network. Rectification can have a striking effect on the network's sensitivity to alterations of the strengths of the chemical synapses in the network. For some configurations, the rectification makes the circuit dynamics remarkably robust against changes in synaptic strength compared with the nonrectifying case. Based on our findings, we predict that modulation of rectifying electrical synapses could have functional consequences for the neuronal circuits that express them.

A Gap Junction Circuit Enhances Processing of Coincident Mechanosensory Inputs

SummaryElectrical synapses have been shown to be important for enabling and detecting neuronal synchrony in both vertebrates [1–4] and invertebrates [5, 6]. Hub-and-spoke circuits, in which a central hub neuron is electrically coupled to several input neurons, are an overrepresented motif in the C. elegans nervous system [7] and may represent a conserved functional unit. The functional relevance of this configuration has been demonstrated for circuits mediating aggregation behavior [8] and nose touch perception [9]. Modeling approaches have been useful for understanding structurally and dynamically more complex electrical circuits [10, 11]. Therefore, we formulated a simple analytical model with minimal assumptions to obtain insight into the properties of the hub-and-spoke microcircuit motif. A key prediction of the model is that an active input neuron should facilitate activity throughout the network, whereas an inactive input should suppress network activity through shunting; this prediction was supported by cell ablation and in vivo neuroimaging experiments in the C. elegans nose touch circuit. Thus, the hub-and-spoke architecture may implement an analog coincidence detector enabling distinct responses to distributed and localized patterns of sensory input.

Multiple Mechanisms Switch an Electrically Coupled, Synaptically Inhibited Neuron between Competing Rhythmic Oscillators

Rhythmic oscillations are common features of nervous systems. One of the fundamental questions posed by these rhythms is how individual neurons or groups of neurons are recruited into different network oscillations. We modeled competing fast and slow oscillators connected to a hub neuron with electrical and inhibitory synapses. We explore the patterns of coordination shown in the network as a function of the electrical coupling and inhibitory synapse strengths with the help of a novel visualization method that we call the "parameterscape." The hub neuron can be switched between the fast and slow oscillators by multiple network mechanisms, indicating that a given change in network state can be achieved by degenerate cellular mechanisms. These results have importance for interpreting experiments employing optogenetic, genetic, and pharmacological manipulations to understand circuit dynamics.

Bifurcation in neuronal networks with hub structure

We investigate bifurcations in neuronal networks with a hub structure. It is known that hubs play a leading role in characterizing the network dynamical behavior. However, the dynamics of hubs or star-coupled systems is not well understood. Here, we study rather subnetworks with a star-like configuration. This coupled system is an important motif in complex networks. Thus, our study is a basic step for understanding structure formation in large networks. We use the Morris–Lecar neuron with class I and class II excitabilities as a node. Homogeneous (coupling the same class neurons) and heterogeneous (coupling different class neurons) cases are considered for both excitatory and inhibitory coupling. For the homogeneous system class II neurons are suitable for achieving both complete and cluster synchronization in excitatory and inhibitory coupling, respectively. For the heterogeneous system with inhibitory coupling, the class I hub neuron has a wider parameter region of synchronous firings than the class II hub. Moreover, the class I hub neuron with the excitatory synapse gives rise to bifurcations of synchronized states and multi-stability (coexistence of a few different states) is observed.