Theoretical Analysis of Coupled Modified Hindmarsh-rose Model Under Transcranial Magnetic-acoustic Electrical Stimulation

Transcranial magnetic-acoustic electrical stimulation (TMAES) is a new technology with ultrasonic waves and a static magnetic field to generate an electric current in nerve tissues to modulate neuronal firing activities. The existing neuron models only simulate a single neuron, and there are few studies on coupled neurons models about TMAES. Most of the neurons in the cerebral cortex are not isolated but are coupled to each other. It is necessary to study the information transmission of coupled neurons. The types of neuron coupled synapses include electrical synapse and chemical synapse. A neuron model without considering chemical synapses is not comprehensive. Here, we modified the Hindmarsh-Rose (HR) model to simulate the smallest nervous system—two neurons coupled electrical synapses and chemical synapses under TMAES. And the environmental variables describing the synaptic coupling between two neurons and the nonlinearity of the nervous system are also taken into account. The firing behavior of the nervous system can be modulated by changing the intensity or the modulation frequency. The results show that within a certain range of parameters, the discharge frequency of coupled neurons could be increased by altering the modulation frequency, and intensity of stimulation, modulating the excitability of neurons, reducing the response time of chemical postsynaptic neurons, and accelerating the information transferring. Moreover, the discharge frequency of neurons was selective to stimulus parameters. These results demonstrate the possible theoretical regulatory mechanism of the neurons' firing frequency characteristics by TMAES. The study establishes the foundation for large-scale neural network modeling and can be taken as the theoretical basis for TMAES experimental and clinical application.

A New Memristive Neuron Map Model and Its Network’s Dynamics under Electrochemical Coupling

A memristor is a vital circuit element that can mimic biological synapses. This paper proposes the memristive version of a recently proposed map neuron model based on the phase space. The dynamic of the memristive map model is investigated by using bifurcation and Lyapunov exponents’ diagrams. The results prove that the memristive map can present different behaviors such as spiking, periodic bursting, and chaotic bursting. Then, a ring network is constructed by hybrid electrical and chemical synapses, and the memristive neuron models are used to describe the nodes. The collective behavior of the network is studied. It is observed that chemical coupling plays a crucial role in synchronization. Different kinds of synchronization, such as imperfect synchronization, complete synchronization, solitary state, two-cluster synchronization, chimera, and nonstationary chimera, are identified by varying the coupling strengths.

The synaptic organization in the C. elegans neural network suggests significant local compartmentalized computations

Neurons are characterized by elaborate tree-like dendritic structures that support local computations by integrating multiple inputs from upstream presynaptic neurons. It is less clear if simple neurons, consisting of a few or even a single neurite, may perform local computations as well. To address this question, we focused on the compact neural network of C. elegans animals for which the full wiring diagram is available, including the coordinates of individual synapses. We find that the positions of the chemical synapses along the neurites are not randomly distributed, nor can they be explained by anatomical constraints. Instead, synapses tend to form clusters, an organization that supports local compartmentalized computations. In mutually-synapsing neurons, connections of opposite polarity cluster separately, suggesting that positive and negative feedback dynamics may be implemented in discrete compartmentalized regions along neurites. In triple-neuron circuits, the non-random synaptic organization may facilitate local functional roles, such as signal integration and coordinated activation of functionally-related downstream neurons. These clustered synaptic topologies emerge as a guiding principle in the network presumably to facilitate distinct parallel functions along a single neurite, effectively increasing the computational capacity of the neural network.

Control of noise-induced coherent oscillations in three-neuron motifs

The phenomenon of self-induced stochastic resonance (SISR) requires a nontrivial scaling limit between the deterministic and the stochastic timescales of an excitable system, leading to the emergence of coherent oscillations which are absent without noise. In this paper, we numerically investigate SISR and its control in single neurons and three-neuron motifs made up of the Morris–Lecar model. In single neurons, we compare the effects of electrical and chemical autapses on the degree of coherence of the oscillations due to SISR. In the motifs, we compare the effects of altering the synaptic time-delayed couplings and the topologies on the degree of SISR. Finally, we provide two enhancement strategies for a particularly poor degree of SISR in motifs with chemical synapses: (1) we show that a poor SISR can be significantly enhanced by attaching an electrical or an excitatory chemical autapse on one of the neurons, and (2) we show that by multiplexing the motif with a poor SISR to another motif (with a high SISR in isolation), the degree of SISR in the former motif can be significantly enhanced. We show that the efficiency of these enhancement strategies depends on the topology of the motifs and the nature of synaptic time-delayed couplings mediating the multiplexing connections.

Behavioral control by depolarized and hyperpolarized states of an integrating neuron

Coordinated transitions between mutually exclusive motor states are central to behavioral decisions. During locomotion, the nematode Caenorhabditis elegans spontaneously cycles between forward runs, reversals, and turns with complex but predictable dynamics. Here, we provide insight into these dynamics by demonstrating how RIM interneurons, which are active during reversals, act in two modes to stabilize both forward runs and reversals. By systematically quantifying the roles of RIM outputs during spontaneous behavior, we show that RIM lengthens reversals when depolarized through glutamate and tyramine neurotransmitters and lengthens forward runs when hyperpolarized through its gap junctions. RIM is not merely silent upon hyperpolarization: RIM gap junctions actively reinforce a hyperpolarized state of the reversal circuit. Additionally, the combined outputs of chemical synapses and gap junctions from RIM regulate forward-to-reversal transitions. Our results indicate that multiple classes of RIM synapses create behavioral inertia during spontaneous locomotion.

Opponent vesicular transporters regulate the strength of glutamatergic neurotransmission in a C. elegans sensory circuit

At chemical synapses, neurotransmitters are packaged into synaptic vesicles that release their contents in response to depolarization. Despite its central role in synaptic function, regulation of the machinery that loads vesicles with neurotransmitters remains poorly understood. We find that synaptic glutamate signaling in a C. elegans chemosensory circuit is regulated by antagonistic interactions between the canonical vesicular glutamate transporter EAT-4/VGLUT and another vesicular transporter, VST-1. Loss of VST-1 strongly potentiates glutamate release from chemosensory BAG neurons and disrupts chemotaxis behavior. Analysis of the circuitry downstream of BAG neurons shows that excess glutamate release disrupts behavior by inappropriately recruiting RIA interneurons to the BAG-associated chemotaxis circuit. Our data indicate that in vivo the strength of glutamatergic synapses is controlled by regulation of neurotransmitter packaging into synaptic vesicles via functional coupling of VGLUT and VST-1.

Extensive GJD2 Expression in the Song Motor Pathway Reveals the Extent of Electrical Synapses in the Songbird Brain

Birdsong is a precisely timed animal behavior. The connectivity of song premotor neural networks has been proposed to underlie the temporal patterns of neuronal activity that control vo-cal muscle movements during singing. Although the connectivity of premotor nuclei via chemical synapses has been characterized, electrical synapses and their molecular identity remain unex-plored. We show with in situ hybridizations that GJD2 mRNA, coding for the major channel-form-ing electrical synapse protein in mammals, connexin 36, is expressed in the two nuclei that control song production, HVC and RA from canaries and zebra finches. In canaries’ HVC, GJD2 mRNA is extensively expressed in GABAergic and only a fraction of glutamatergic cells. By contrast, in RA, GJD2 mRNA expression is widespread in glutamatergic and GABAergic neurons. Remarkably, GJD2 expression is similar in song nuclei and their respective embedding brain regions, revealing the widespread expression of GJD2 in the avian brain. Inspection of a single-cell sequencing data-base from zebra and Bengalese finches generalizes the distributions of electrical synapses across cell types and song nuclei that we found in HVC and RA from canaries, reveals a differential GJD2 mRNA expression in HVC glutamatergic subtypes and its transient increase along the neurogenic lineage. We propose that songbirds are a suitable model to investigate the contribution of electrical synapses to motor skill learning and production.

Neuroligin-3: A Circuit-Specific Synapse Organizer That Shapes Normal Function and Autism Spectrum Disorder-Associated Dysfunction

Chemical synapses provide a vital foundation for neuron-neuron communication and overall brain function. By tethering closely apposed molecular machinery for presynaptic neurotransmitter release and postsynaptic signal transduction, circuit- and context- specific synaptic properties can drive neuronal computations for animal behavior. Trans-synaptic signaling via synaptic cell adhesion molecules (CAMs) serves as a promising mechanism to generate the molecular diversity of chemical synapses. Neuroligins (Nlgns) were discovered as postsynaptic CAMs that can bind to presynaptic CAMs like Neurexins (Nrxns) at the synaptic cleft. Among the four (Nlgn1-4) or five (Nlgn1-3, Nlgn4X, and Nlgn4Y) isoforms in rodents or humans, respectively, Nlgn3 has a heterogeneous expression and function at particular subsets of chemical synapses and strong association with non-syndromic autism spectrum disorder (ASD). Several lines of evidence have suggested that the unique expression and function of Nlgn3 protein underlie circuit-specific dysfunction characteristic of non-syndromic ASD caused by the disruption of Nlgn3 gene. Furthermore, recent studies have uncovered the molecular mechanism underlying input cell-dependent expression of Nlgn3 protein at hippocampal inhibitory synapses, in which trans-synaptic signaling of specific alternatively spliced isoforms of Nlgn3 and Nrxn plays a critical role. In this review article, we overview the molecular, anatomical, and physiological knowledge about Nlgn3, focusing on the circuit-specific function of mammalian Nlgn3 and its underlying molecular mechanism. This will provide not only new insight into specific Nlgn3-mediated trans-synaptic interactions as molecular codes for synapse specification but also a better understanding of the pathophysiological basis for non-syndromic ASD associated with functional impairment in Nlgn3 gene.

Genetic Transsynaptic Techniques for Mapping Neural Circuits in Drosophila

A neural circuit is composed of a population of neurons that are interconnected by synapses and carry out a specific function when activated. It is the structural framework for all brain functions. Its impairments often cause diseases in the nervous system. To understand computations and functions in a brain circuit, it is of crucial importance to identify how neurons in this circuit are connected. Genetic transsynaptic techniques provide opportunities to efficiently answer this question. These techniques label synapses or across synapses to unbiasedly label synaptic partners. They allow for mapping neural circuits with high reproducibility and throughput, as well as provide genetic access to synaptically connected neurons that enables visualization and manipulation of these neurons simultaneously. This review focuses on three recently developed Drosophila genetic transsynaptic tools for detecting chemical synapses, highlights their advantages and potential pitfalls, and discusses the future development needs of these techniques.

A serotonergic axon-cilium synapse drives nuclear signaling to maintain chromatin accessibility

Chemical synapses between axons and dendrites mediate much of the brain's intercellular communication. Here we describe a new kind of synapse - the axo-ciliary synapse - between axons and primary cilia. By employing enhanced focused ion beam - scanning electron microscopy on samples with optimally preserved ultrastructure, we discovered synapses between the serotonergic axons arising from the brainstem, and the primary cilia of hippocampal CA1 pyramidal neurons. Functionally, these cilia are enriched in a ciliary-restricted serotonin receptor, 5-hydroxytryptamine receptor 6 (HTR6), whose mutation is associated with learning and memory defects. Using a newly developed cilia-targeted serotonin sensor, we show that optogenetic stimulation of serotonergic axons results in serotonin release onto cilia. Ciliary HTR6 stimulation activates a non-canonical GNAQ/11-RhoA pathway. Ablation of this pathway results in nuclear actin and chromatin accessibility changes in CA1 pyramidal neurons. Axo-ciliary synapses serve as a distinct mechanism for neuromodulators to program neuron transcription through privileged access to the nuclear compartment.