Types Of Synapses Research Articles

A Practical Guide to Using CV Analysis for Determining the Locus of Synaptic Plasticity.

Long-term synaptic plasticity is widely believed to underlie learning and memory in the brain. Whether plasticity is primarily expressed pre- or postsynaptically has been the subject of considerable debate for many decades. More recently, it is generally agreed that the locus of plasticity depends on a number of factors, such as developmental stage, induction protocol, and synapse type. Since presynaptic expression alters not just the gain but also the short-term dynamics of a synapse, whereas postsynaptic expression only modifies the gain, the locus has fundamental implications for circuits dynamics and computations in the brain. It therefore remains crucial for our understanding of neuronal circuits to know the locus of expression of long-term plasticity. One classical method for elucidating whether plasticity is pre- or postsynaptically expressed is based on analysis of the coefficient of variation (CV), which serves as a measure of noise levels of synaptic neurotransmission. Here, we provide a practical guide to using CV analysis for the purposes of exploring the locus of expression of long-term plasticity, primarily aimed at beginners in the field. We provide relatively simple intuitive background to an otherwise theoretically complex approach as well as simple mathematical derivations for key parametric relationships. We list important pitfalls of the method, accompanied by accessible computer simulations to better illustrate the problems (downloadable from GitHub), and we provide straightforward solutions for these issues.

The Y172 Monoclonal Antibody Against p-c-Jun (Ser63) Is a Marker of the Postsynaptic Compartment of C-Type Cholinergic Afferent Synapses on Motoneurons.

C-bouton-type cholinergic afferents exert an important function in controlling motoneuron (MN) excitability. During the immunocytochemical analysis of the role of c-Jun in MNs with a monoclonal (clone Y172) antibody against phospho (p)-c-Jun (serine [Ser]63), unexpected labeling was identified in the cell body cytoplasm. As predicted for c-Jun in adult spinal cord, very few, if any MNs exhibited nuclear immunoreactivity with the Y172 antibody; conversely, virtually all MNs displayed strong Y172 immunostaining in cytoplasmic structures scattered throughout the soma and proximal dendrites. The majority of these cytoplasmic Y172-positive profiles was closely associated with VAChT-positive C-boutons, but not with other types of nerve afferents contacting MNs. Ultrastructural analysis revealed that cytoplasmic Y172 immunostaining was selectively located at the subsurface cistern (SSC) of C-boutons and also in the inner areas of the endoplasmic reticulum (ER). We also described changes in cytoplasmic Y172 immunoreactivity in injured and degenerating MNs. Moreover, we noticed that MNs from NRG1 type III-overexpressing transgenic mice, which show abnormally expanded SSCs, exhibited an increase in the density and size of peripherally located Y172-positive profiles. A similar immunocytochemical pattern to that of the Y172 antibody in MNs was found with a polyclonal antibody against p-c-Jun (Ser63) but not with another polyclonal antibody that recognizes c-Jun phosphorylated at a different site. No differential band patterns were found by western blotting with any of the antibodies against c-Jun or p-c-Jun used in our study. In cultured MNs, Y172-positive oval profiles were distributed in the cell body and proximal dendrites. The in vitro lentiviral-based knockdown of c-Jun resulted in a dramatic decrease in nuclear Y172 immunostaining in MNs without any reduction in the density of cytoplasmic Y172-positive profiles, suggesting that the synaptic antigen recognized by the antibody corresponds to a C-bouton-specific protein other than p-c-Jun. Our results lay the foundation for further studies aimed at identifying this protein and determining its role in this particular type of synapse.

An Artificial Optoelectronic Synapse Based on a Photoelectric Memcapacitor

AbstractThe rapid development of artificial intelligence technology has led to the urge for artificial optoelectronic synapses with visual perception and memory capabilities. A new type of artificial optoelectronic synapse, namely a photoelectric memcapacitor, is proposed and demonstrated. This photoelectric memcapacitor, with a planar Au/La1.875Sr0.125NiO4/Au metal–semiconductor–metal structure, displays a complementary optical and electrical modulation of capacitance, which can be attributed to the charge trapping/detrapping‐induced Schottky barrier variation. It further exhibits versatile synaptic functions, such as photonic potentiation/electric depression, paired‐pulse facilitation, short‐/long‐term memory, and “learning‐experience” behavior. Moreover, the photoplasticity of the memcapacitor can be modulated by varying the frequency of applied AC voltage, thus enabling self‐adaptive optical signal detection and mimicry of interest‐modulated human visual memory. Therefore, it represents a new paradigm for artificial optoelectronic synapses and opens up opportunities for developing low‐power humanoid optoelectronic devices.

Target-wide Induction and Synapse Type-Specific Robustness of Presynaptic Homeostasis.

Presynaptic homeostatic plasticity (PHP) is an evolutionarily conserved form of adaptive neuromodulation and is observed at both central and peripheral synapses. In this work, we make several fundamental advances by interrogating the synapse specificity of PHP. We define how PHP remains robust to acute versus long-term neurotransmitter receptor perturbation. We describe a general PHP property that includes global induction and synapse-specific expression mechanisms. Finally, we detail a novel synapse-specific PHP expression mechanism that enables the conversion from short- to long-term PHP expression. If our data can be extended to other systems, including the mammalian central nervous system, they suggest that PHP can be broadly induced and expressed to sustain the function of complex neural circuitry.

Reinforcement Learning in Spiking Neural Networks with Stochastic and Deterministic Synapses.

Though succeeding in solving various learning tasks, most existing reinforcement learning (RL) models have failed to take into account the complexity of synaptic plasticity in the neural system. Models implementing reinforcement learning with spiking neurons involve only a single plasticity mechanism. Here, we propose a neural realistic reinforcement learning model that coordinates the plasticities of two types of synapses: stochastic and deterministic. The plasticity of the stochastic synapse is achieved by the hedonistic rule through modulating the release probability of synaptic neurotransmitter, while the plasticity of the deterministic synapse is achieved by a variant of a reward-modulated spike-timing-dependent plasticity rule through modulating the synaptic strengths. We evaluate the proposed learning model on two benchmark tasks: learning a logic gate function and the 19-state random walk problem. Experimental results show that the coordination of diverse synaptic plasticities can make the RL model learn in a rapid and stable form.

Neurons with Multiplicative Interactions of Nonlinear Synapses.

Neurons are the fundamental units of the brain and nervous system. Developing a good modeling of human neurons is very important not only to neurobiology but also to computer science and many other fields. The McCulloch and Pitts neuron model is the most widely used neuron model, but has long been criticized as being oversimplified in view of properties of real neuron and the computations they perform. On the other hand, it has become widely accepted that dendrites play a key role in the overall computation performed by a neuron. However, the modeling of the dendritic computations and the assignment of the right synapses to the right dendrite remain open problems in the field. Here, we propose a novel dendritic neural model (DNM) that mimics the essence of known nonlinear interaction among inputs to the dendrites. In the model, each input is connected to branches through a distance-dependent nonlinear synapse, and each branch performs a simple multiplication on the inputs. The soma then sums the weighted products from all branches and produces the neuron's output signal. We show that the rich nonlinear dendritic response and the powerful nonlinear neural computational capability, as well as many known neurobiological phenomena of neurons and dendrites, may be understood and explained by the DNM. Furthermore, we show that the model is capable of learning and developing an internal structure, such as the location of synapses in the dendritic branch and the type of synapses, that is appropriate for a particular task- for example, the linearly nonseparable problem, a real-world benchmark problem- Glass classification and the directional selectivity problem.

Multifaceted Changes in Synaptic Composition and Astrocytic Involvement in a Mouse Model of Fragile X Syndrome

Fragile X Syndrome (FXS), a common inheritable form of intellectual disability, is known to alter neocortical circuits. However, its impact on the diverse synapse types comprising these circuits, or on the involvement of astrocytes, is not well known. We used immunofluorescent array tomography to quantify different synaptic populations and their association with astrocytes in layers 1 through 4 of the adult somatosensory cortex of a FXS mouse model, the FMR1 knockout mouse. The collected multi-channel data contained approximately 1.6 million synapses which were analyzed using a probabilistic synapse detector. Our study reveals complex, synapse-type and layer specific changes in the neocortical circuitry of FMR1 knockout mice. We report an increase of small glutamatergic VGluT1 synapses in layer 4 accompanied by a decrease in large VGluT1 synapses in layers 1 and 4. VGluT2 synapses show a rather consistent decrease in density in layers 1 and 2/3. In all layers, we observe the loss of large inhibitory synapses. Lastly, astrocytic association of excitatory synapses decreases. The ability to dissect the circuit deficits by synapse type and astrocytic involvement will be crucial for understanding how these changes affect circuit function, and ultimately defining targets for therapeutic intervention.

RIM-BP2 primes synaptic vesicles via recruitment of Munc13-1 at hippocampal mossy fiber synapses.

All synapses require fusion-competent vesicles and coordinated Ca2+-secretion coupling for neurotransmission, yet functional and anatomical properties are diverse across different synapse types. We show that the presynaptic protein RIM-BP2 has diversified functions in neurotransmitter release at different central murine synapses and thus contributes to synaptic diversity. At hippocampal pyramidal CA3-CA1 synapses, RIM-BP2 loss has a mild effect on neurotransmitter release, by only regulating Ca2+-secretion coupling. However, at hippocampal mossy fiber synapses, RIM-BP2 has a substantial impact on neurotransmitter release by promoting vesicle docking/priming and vesicular release probability via stabilization of Munc13-1 at the active zone. We suggest that differences in the active zone organization may dictate the role a protein plays in synaptic transmission and that differences in active zone architecture is a major determinant factor in the functional diversity of synapses.

Emerging Roles of Synapse Organizers in the Regulation of Critical Periods.

Experience remodels cortical connectivity during developmental windows called critical periods. Experience-dependent regulation of synaptic strength during these periods establishes circuit functions that are stabilized as critical period plasticity wanes. These processes have been extensively studied in the developing visual cortex, where critical period opening and closure are orchestrated by the assembly, maturation, and strengthening of distinct synapse types. The synaptic specificity of these processes points towards the involvement of distinct molecular pathways. Attractive candidates are pre- and postsynaptic transmembrane proteins that form adhesive complexes across the synaptic cleft. These synapse-organizing proteins control synapse development and maintenance and modulate structural and functional properties of synapses. Recent evidence suggests that they have pivotal roles in the onset and closure of the critical period for vision. In this review, we describe roles of synapse-organizing adhesion molecules in the regulation of visual critical period plasticity and we discuss the potential they offer to restore circuit functions in amblyopia and other neurodevelopmental disorders.

Firing dynamics in hybrid coupled populations of bistable neurons

We study the firing behavior of bistable neurons that are coupled by both electrical and chemical synapses, constituting a hybrid coupled population. We use stochastic Hodgkin–Huxley model neurons for the dynamics of individual bistable units within the population and the connectivity is implemented with a scale-free network topology which is a widely used network paradigm in theoretical studies of neural circuits. By analyzing the electrical activity of both whole population and individual neurons, it is shown that population mean firing rate exhibits a non-monotonic behavior in the space of electrical and chemical coupling strengths. We identify dynamical mechanisms that shape such non-monotonic spiking behavior and show that different types of population spiking patterns can emerge by fine-tuning the coupling strengths of electrical and chemical synapses. Furthermore, we map the transitions between observed dynamical states in the parameter space of interest depending on the level of individual neuron bistability, existence probability of a synapse type and intrinsic ion channel noise.

Early functional alterations in membrane properties and neuronal degeneration are hallmarks of progressive hearing loss in NOD mice

Presbycusis or age-related hearing loss (ARHL) is the most common sensory deficit in the human population. A substantial component of the etiology stems from pathological changes in sensory and non-sensory cells in the cochlea. Using a non-obese diabetic (NOD) mouse model, we have characterized changes in both hair cells and spiral ganglion neurons that may be relevant for early signs of age-related hearing loss (ARHL). We demonstrate that hair cell loss is preceded by, or in parallel with altered primary auditory neuron functions, and latent neurite retraction at the hair cell-auditory neuron synapse. The results were observed first in afferent inner hair cell synapse of type I neurites, followed by type II neuronal cell-body degeneration. Reduced membrane excitability and loss of postsynaptic densities were some of the inaugural events before any outward manifestation of hair bundle disarray and hair cell loss. We have identified profound alterations in type I neuronal membrane properties, including a reduction in membrane input resistance, prolonged action potential latency, and a decrease in membrane excitability. The resting membrane potential of aging type I neurons in the NOD, ARHL model, was significantly hyperpolarized, and analyses of the underlying membrane conductance showed a significant increase in K+ currents. We propose that attempts to alleviate some forms of ARHL should include early targeted primary latent neural degeneration for effective positive outcomes.

Efficient gene transfers into neocortical neurons connected by NMDA NR1-containing synapses

BackgroundWithin a circuit, specific neurons and synapses are hypothesized to have essential roles in circuit physiology and learning, and dysfunction in these neurons and synapses causes specific disorders. These critical neurons and synapses are embedded in complex circuits containing many neuron and synapse types. New methodWe established technology that can deliver different genes into pre- and post-synaptic neurons connected by a specific synapse type. The first, presynaptic gene transfer employs standard gene transfer technology to express a synthetic peptide neurotransmitter which has three domains, a dense core vesicle sorting domain for processing the protein as a peptide neurotransmitter, a receptor-binding domain, here a small peptide that binds to NMDA NR1 subunits, and the His tag. Upon release, this peptide neurotransmitter binds to its cognate receptor on postsynaptic neurons. Gene transfer selectively into these postsynaptic neurons employs antibody-mediated, targeted gene transfer and anti-His tag antibodies, which recognize the His tag domain in the synthetic peptide neurotransmitter. ResultsFor the model system, we studied the connection from projection neurons in postrhinal cortex to specific neurons in perirhinal cortex. In our initial report, gene transfer to connected neurons was 20+1% specific. Here, we optimized the technology; we improved the transfection for packaging by using a modern using a modern lipid, Lipofectamine 3000, and used a modern confocal microscope to collect data. We now report 80+2% specific gene transfer to connected neurons. Comparison with existing methodsThere is no existing method with this capability. ConclusionsThis technology may enable studies on the roles of specific neurons and synapses in circuit physiology and learning, and support gene therapy treatments for specific disorders.

Synapse diversity and synaptome architecture in human genetic disorders.

Over 130 brain diseases are caused by mutations that disrupt genes encoding the proteome of excitatory synapses. These include neurological and psychiatric disorders with early and late onset such as autism, schizophrenia and depression and many other rarer conditions. The proteome of synapses is highly complex with over 1000 conserved proteins which are differentially expressed generating a vast, potentially unlimited, number of synapse types. The diversity of synapses and their location in the brain are described by the synaptome. A recent study has mapped the synaptome across the mouse brain, revealing that synapse diversity is distributed into an anatomical architecture observed at scales from individual dendrites to the whole systems level. The synaptome architecture is built from the hierarchical expression and assembly of proteins into complexes and supercomplexes which are distributed into different synapses. Mutations in synapse proteins change the synaptome architecture leading to behavioral phenotypes. Mutations in the mechanisms regulating the hierarchical assembly of the synaptome, including transcription and proteostasis, may also change synapse diversity and synaptome architecture. The logic of synaptome hierarchical assembly provides a mechanistic framework that explains how diverse genetic disorders can converge on synapses in different brain circuits to produce behavioral phenotypes.

Theoretical principles of deep brain stimulation induced synaptic suppression

BackgroundDeep brain stimulation (DBS) is a successful clinical therapy for a wide range of neurological disorders; however, the physiological mechanisms of DBS remain unresolved. While many different hypotheses currently exist, our analyses suggest that high frequency (∼100 Hz) stimulation-induced synaptic suppression represents the most basic concept that can be directly reconciled with experimental recordings of spiking activity in neurons that are being driven by DBS inputs. ObjectiveThe goal of this project was to develop a simple model system to characterize the excitatory post-synaptic currents (EPSCs) and action potential signaling generated in a neuron that is strongly connected to pre-synaptic glutamatergic inputs that are being directly activated by DBS. MethodsWe used the Tsodyks-Markram (TM) phenomenological synapse model to represent depressing, facilitating, and pseudo-linear synapses driven by DBS over a wide range of stimulation frequencies. The EPSCs were then used as inputs to a leaky integrate-and-fire neuron model and we measured the DBS-triggered post-synaptic spiking activity. ResultsSynaptic suppression was a robust feature of high frequency stimulation, independent of the synapse type. As such, the TM equations were used to define alternative DBS pulsing strategies that maximized synaptic suppression with the minimum number of stimuli. ConclusionsSynaptic suppression provides a biophysical explanation to the intermittent, but still time-locked, post-synaptic firing characteristics commonly seen in DBS experimental recordings. Therefore, network models attempting to analyze or predict the effects of DBS on neural activity patterns should integrate synaptic suppression into their simulations.

Latrophilins: A Neuro-Centric View of an Evolutionary Conserved Adhesion G Protein-Coupled Receptor Subfamily.

The adhesion G protein-coupled receptors latrophilins have been in the limelight for more than 20 years since their discovery as calcium-independent receptors for α-latrotoxin, a spider venom toxin with potent activity directed at neurotransmitter release from a variety of synapse types. Latrophilins are highly expressed in the nervous system. Although a substantial amount of studies has been conducted to describe the role of latrophilins in the toxin-mediated action, the recent identification of endogenous ligands for these receptors helped confirm their function as mediators of adhesion events. Here we hypothesize a role for latrophilins in inter-neuronal contacts and the formation of neuronal networks and we review the most recent information on their role in neurons. We explore molecular, cellular and behavioral aspects related to latrophilin adhesion function in mice, zebrafish, Drosophila melanogaster and Caenorhabditis elegans, in physiological and pathophysiological conditions, including autism spectrum, bipolar, attention deficit and hyperactivity and substance use disorders.

Automatic Classification for the Type of Multiple Synapse Based on Deep Learning.

Recent studies have shown that the synaptic plasticity induced by development and learning can promote the formation of multiple synapse. With the rapid development of electron microscopy (EM) technology, we can closely observe the multiple synapse structure with high resolution. Although the multiple synapse has been widely researched by recent researchers, the classification accuracy for the type of multiple synapse has not been documented. In this paper, we propose an effective automatic classification method for the type of multiple synapse. The main steps are summarized as three parts: synaptic cleft segmentation, vesicle band segmentation, multiple synapse classification. The experiments on four datasets demonstrate that the proposed method can reach an average accuracy about 97%.

Presynaptic Endosomal Cathepsin D Regulates the Biogenesis of GABAergic Synaptic Vesicles

Presynaptic endosomes reportedly participate in synaptic vesicle (SV) recycling. However, it remains unclear whether they differentially regulate SV biogenesis and synaptic transmission in different types ofsynapses and how they are implicated in diseases. Using cryo-electron tomography and endocytic tracing, we uncover different endocytic modes and dynamics associated with distinct SV morphology between glutamatergic and GABAergic synapses. We further find that cathepsin D (CatD), a lysosomal storage disease (LSD) protein, is selectively located in GABAergic presynaptic endosomes. Inactivation of CatD results in enlarged presynaptic endosomes, reduces the readily releasable pool, and impairs synaptic transmission in GABAergic, but not glutamatergic, synapses. Moreover, CatD-deficient mice exhibit hyperactivity and increased sensitivity to seizure, mimicking epileptic behavior in CatD-related LSD patients. These data reveal an important role for presynaptic endosomal CatD in regulating GABAergic SV biogenesis and provide mechanistic insights for understanding the synaptic pathology and behavioral defects in CatD-associated LSD.

Synchronization between neural circuits connected by hybrid synapse

Reliable neural circuits provide feasible ways to estimate the information encoding and signal exchange between neurons so that more physical effects can be considered and explained. Electrical synapse benefits signal propagation and neurons can give rapid response selection under an external stimulus. Chemical synapse plays a standing biological function by the continuous release of neurotransmitter. Gap junction coupling can estimate the effect of electrical synapse coupling as resistor-based voltage coupling while chemical synapse coupling shows a complex form in synapse currents. In this paper, two FitzHugh–Nagumo neuron circuits are connected by resistor and induction coil, and thus field coupling is activated to realize synchronization. It gives possible guidance to explain the synapse function from physical view. These circuit equations are obtained and scale transformation is applied to get the dimensionless dynamical systems. Furthermore, the same scheme is used to discuss synchronization realization between Hindmarsh–Rose neuron models. It is found that synchronization can be suppressed when the coupling resistor is in series with the induction coil in which only one coupling channel is open. However, complete synchronization can be enhanced when the coupling resistor is paralleled with the induction coil because two coupling channels are activated simultaneously. As a result, appropriate adjustment and selection for the coupling electric devices can induce transition from synchronization to desynchronization between neural circuits, which indicates the self-adaption of synapse when two types of synapse are activated together.

Delivery of different genes into pre- and post-synaptic neocortical interneurons connected by GABAergic synapses.

Local neocortical circuits play critical roles in information processing, including synaptic plasticity, circuit physiology, and learning, and GABAergic inhibitory interneurons have key roles in these circuits. Moreover, specific neurological disorders, including schizophrenia and autism, are associated with deficits in GABAergic transmission in these circuits. GABAergic synapses represent a small fraction of neocortical synapses, and are embedded in complex local circuits that contain many neuron and synapse types. Thus, it is challenging to study the physiological roles of GABAergic inhibitory interneurons and their synapses, and to develop treatments for the specific disorders caused by dysfunction at these GABAergic synapses. To these ends, we report a novel technology that can deliver different genes into pre- and post-synaptic neocortical interneurons connected by a GABAergic synapse: First, standard gene transfer into the presynaptic neurons delivers a synthetic peptide neurotransmitter, containing three domains, a dense core vesicle sorting domain, a GABAA receptor-binding domain, a single-chain variable fragment anti-GABAA ß2 or ß3, and the His tag. Second, upon release, this synthetic peptide neurotransmitter binds to GABAA receptors on the postsynaptic neurons. Third, as the synthetic peptide neurotransmitter contains the His tag, antibody-mediated, targeted gene transfer using anti-His tag antibodies is selective for these neurons. We established this technology by expressing the synthetic peptide neurotransmitter in GABAergic neurons in the middle layers of postrhinal cortex, and the delivering the postsynaptic vector into connected GABAergic neurons in the upper neocortical layers. Targeted gene transfer was 61% specific for the connected neurons, but untargeted gene transfer was only 21% specific for these neurons. This technology may support studies on the roles of GABAergic inhibitory interneurons in circuit physiology and learning, and support gene therapy treatments for specific disorders associated with deficits at GABAergic synapses.

Elevated synaptic vesicle release probability in synaptophysin/gyrin family quadruple knockouts.

This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).