Search Results (73)

Neuronal synapses are the functional units of communication in the central nervous system. This review describes the molecular mechanisms regulating synaptic transmission, plasticity, and circuit refinement. At the presynaptic active zone, scaffolding proteins including bassoon, piccolo, RIMs, and munc13 organize vesicle priming and the localization of voltage-gated calcium channels. Neurotransmitter release is mediated by the SNARE complex, comprising syntaxin-1, SNAP25, and synaptobrevin, and triggered by the calcium sensor synaptotagmin-1. Following exocytosis, synaptic vesicles are recovered through clathrin-mediated, ultrafast, bulk, or kiss-and-run endocytic pathways. Postsynaptically, the postsynaptic density (PSD) serves as a protein hub where scaffolds such as PSD-95, shank, homer, and gephyrin anchor excitatory (AMPA, NMDA) and inhibitory (GABA-A, Glycine) receptors are observed. Synaptic strength is modified during long-term potentiation (LTP) and depression (LTD) through signaling cascades involving kinases like CaMKII, PKA, and PKC, or phosphatases such as PP1 and calcineurin. These pathways regulate receptor trafficking, Arc-mediated endocytosis, and actin-dependent remodeling of dendritic spines. Additionally, synapse formation and elimination are guided by cell adhesion molecules, including neurexins and neuroligins, and by microglial pruning via the complement cascade (C1q, C3) and “don’t eat me” signals like CD47. Molecular diversity is further expanded by alternative splicing and post-translational modifications. A unified model of synaptic homeostasis is required to understand the basis of neuropsychiatric and neurological disorders. Full article

Gliomas are the most common malignant primary brain tumors in adults. The treatment of high-grade gliomas is very limited due to their diffuse infiltration, high plasticity, and resistance to conventional therapies. Although they were long considered passive massive lesions, they are now regarded as functionally integrated components of neural circuits, as they form authentic electrochemical synapses with neurons. This allows them to mimic neuronal activity to drive tumor growth and invasion. Ultrastructural studies show presynaptic vesicles in neurons and postsynaptic densities in glioma cell membranes, while electrophysiological recordings detect postsynaptic currents in tumor cells. Tumor microtubules (TMs), dynamic cytoplasmic protrusions enriched in AMPA receptors, are the structures responsible for glioma–glioma and glioma–neuron connectivity, also contributing to treatment resistance and tumor network integration. In these connections, neurons release glutamate that mainly activates their AMPA receptors in glioma cells, while gliomas release excess glutamate, causing excitotoxicity, altering the local excitatory-inhibitory balance, and promoting a hyperexcitable and pro-tumorigenic microenvironment. In addition, certain gliomas, such as diffuse midline gliomas, have altered chloride homeostasis, which makes GABAergic signaling depolarizing and growth promoting. Synaptogenic factors, such as neuroligin-3 and BDNF, further enhance glioma proliferation and synapse formation. These synaptic and paracrine interactions contribute to cognitive impairment, epileptogenesis, and resistance to surgical and pharmacological interventions. High functional connectivity within gliomas correlates with shorter patient survival. Therapies such as AMPA receptor antagonists (perampanel), glutamate release modulators (riluzole or sulfasalazine), and chloride cotransporter inhibitors (NKCC1 blockers) aim to improve outcomes for patients. Full article

The optimal computing ability of spiking neural networks (SNNs) mainly depends on the connection weights of their synapses and the thresholds that control the spiking. In order to realize the optimization calculation of different objective functions, it is necessary to modify the connection weights adaptively and make the thresholds dynamically self-learning. However, it is very difficult to construct an adaptive learning algorithm for spiking neural networks due to the discontinuity of neuron spike sending process, which is also a fatal problem in this field. In this paper, an efficient adaptive learning algorithm for spiking neural networks is proposed, which adjusts the weights of synaptic connections by a learning factor adaptively and adjusts the probability of spike sending by the self-organizing learning method of the dynamic threshold, so as to achieve the goal of automatic global search optimization. The algorithm is applied to the learning task of global optimization, and the experimental results show that this algorithm has good stability and learning ability, and is effective in dealing with complex multi-objective optimization problems of spatiotemporal spike mode. Moreover, the proposed framework explicitly leverages problem and model symmetries. In Traveling Salesman Problems, distance symmetry (d(i, j) = d(j, i)) and tour permutation symmetry are preserved by our spike-train-based similarity and energy updates, which do not depend on node labels. Together with the homogeneous neuron dynamics and balanced excitatory–inhibitory populations, these symmetry-aware properties reduce the effective search space and enhance the convergence stability. Full article

Background: Fragile X Syndrome (FXS) is the most common monogenic cause of autism spectrum disorders, and is characterized by the excessive immature excitatory synapses in cortical neurons, leading to excitatory/inhibitory imbalance and core autistic behaviors. This synaptic pathology has been attributed to dysregulated levels of synaptic proteins, including CYFIP2: a key regulator of synaptic structure and plasticity. However, the mechanism underlying the increased CYFIP2 protein level in FXS neurons remains unclear. Neurons abundantly secrete extracellular vesicles (EVs) enriched with bioactive cargos (proteins and miRNAs). Objectives: the goal of this research is to identify whether EV-dependent secretion plays important roles in regulating the intracellular CYFIP2 protein level in WT and FXS neurons. Methods and Results: our proteomic analysis reveals that CYFIP2 protein is packaged in EVs released by mouse cortical neurons. Pharmacological and genetic blockades of neuronal EV release significantly elevated intracellular CYFIP2 levels by 78 ± 14% and 168 ± 39%, respectively. Glutamate-evoked EV release significantly reduced the CYFIP2 level by 24 ± 2%. Neurons from Fmr1 KO mice, an FXS model, secreted significantly less EVs (46 ± 5%) than the wild type, and showed significantly elevated CYFIP2 (by 155 ± 31%). Evoking EV release in FXS neurons significantly lowered the intracellular CYFIP2 (by 53 ± 6%). Conclusions: these findings identify an EV-secretion-dependent mechanism that controls neuronal CYFIP2 level, implicating EV-mediated export in the regulation of synaptic protein homeostasis, synaptic remodeling, and FXS-associated synaptic deficits. Full article

Depression is one of the most disabling of all disorders across the community, yet many aspects of the disorder remain contentious. Psychosocial and biological perspectives are often placed in opposition to one another, which in part reflects a failure of our explanatory frameworks. The active inference account of brain function breaks down this dualism, demonstrating that bodily processes are deeply integrated with the social world. It shows us that there is no contradiction in understanding depression as a product of the social environment at the same time as having a brain basis and manifesting in biological symptoms. From an active inference perspective, depression can be thought of as a synaptopathy: a disorder that arises from alterations to the excitatory-inhibitory balance enacted at the synapse, reflecting the interoceptive precision-weightings that have changed in the context of psychosocial instability. Therapies that alleviate depressive symptoms act at different levels of the active inference framework to re-weight precision estimates and the confidence we have in our predictions: this is true for psychotherapies, lifestyle interventions and antidepressant medications. Their effectiveness is often only partial, and while different treatment modalities can complement one another, there is a need for continued development of new and better treatment options. Full article

One major challenge in cellular neuroscience is to elucidate how the accurate alignment of presynaptic release sites with postsynaptic densely clustered ligand-gated ion channels at chemical synapses is achieved upon synapse assembly. The clustering of neurotransmitter receptors at postsynaptic sites is a key moment of synaptogenesis and determinant for effective synaptic transmission. The number of the ionotropic neurotransmitter receptors at these postsynaptic sites of both excitatory and inhibitory synapses is variable and is regulated by different mechanisms, thus allowing the modulation of synaptic strength, which is essential to tune neuronal network activity. Several well-regulated processes seem to be involved, including lateral diffusion within the plasma membrane and local anchoring as well as receptor endocytosis and recycling. The molecular mechanisms implicated are numerous and were reviewed recently in great detail. The role of pre-synaptically released neurotransmitters within the complex regulatory apparatus organizing the postsynaptic site underneath presynaptic terminals is not completely understood, even less for inhibitory synapses. In this mini review article, we focus on this aspect of synapse formation, summarizing and contrasting findings on the functional role of the neurotransmitters glycine and γ-aminobutyric acid (GABA) for initiation of postsynaptic receptor clustering and regulation of Cl⁻ channel receptor numbers at inhibitory synapses gathered over the last two decades. Full article

Botulinum neurotoxins (BoNTs) are known to inhibit synaptic transmission by targeting SNARE proteins, but their selectivity toward central excitatory and inhibitory pathways is not yet fully understood. In this study, the interaction of serotypes A (BoNT/A) and B (BoNT/B) with the glutamatergic and GABAergic systems has been investigated using a pharmacological approach in an animal model of inflammatory pain, i.e., the formalin test in mice. BoNTs were administered intracerebroventricularly, three days before testing, followed 15 min before testing by systemic administration of sub-analgesic doses of MK801, an NMDA receptor antagonist, or muscimol, a GABA_A receptor agonist. BoNT/A reduced the second phase of the formalin test without affecting both the first phase and the interphase, suggesting a selective action on excitatory glutamatergic circuits while sparing GABAergic inhibition. Co-administration of MK801 with BoNT/A did not enhance analgesia, and muscimol did not further reduce interphase, confirming preserved GABAergic transmission. In contrast, BoNT/B abolished the interphase, consistent with impaired GABA release. Co-administration of MK801 or muscimol with BoNT/B restored the interphase, indicating compensatory rebalancing of excitatory-inhibitory networks. These results demonstrate that BoNT/A and BoNT/B exert distinct effects on central neurotransmission and support the hypothesis that BoNT/A preferentially targets excitatory synapses, while BoNT/B targets inhibitory synapses. This work contributes to a deeper understanding of anti-inflammatory mechanisms of BoNTs and their selective interaction with central pain pathways. Full article

Synaptic plasticity is the key mechanism underlying learning and memory. Neurexins are pre-synaptic molecules that play a pivotal role in synaptic plasticity, interacting with many different post-synaptic molecules in the formation of neural circuits. Neurexins are alternatively spliced at different splice sites, yielding thousands of isoforms with different properties of interaction with post-synaptic molecules for a quick adaptation to internal and external inputs. The endocannabinoid system also plays a central role in synaptic plasticity, regulating key retrograde signaling at both excitatory and inhibitory synapses. This study aims at elucidating the crosstalk between alternative splicing of neurexin and the endocannabinoid system in the hippocampus. By employing an ex vivo hippocampal system, we found that pharmacological activation of cannabinoid receptor 1 (CB1) with the specific agonist ACEA led to reduced neurotransmission, associated with increased expression of the Nrxn1–3 spliced isoforms excluding the exon at splice site 4 (SS4−). In contrast, treatment with the CB1 antagonist AM251 increased glutamatergic activity and promoted the expression of the Nrxn variants including the exon (SS4+) Knockout of the involved splicing factor SLM2 determined the suppression of the exon splicing at SS4 and the expression only of the SS4+ variants of Nrxns1–3 transcripts. Interestingly, in SLM2 ko hippocampus, modulation of neurotransmission by AM251 or ACEA was abolished. These findings suggest a direct crosstalk between CB1-dependent signaling, neurotransmission and expression of specific Nrxns splice variants in the hippocampus. We propose that the fine-tuned regulation of Nrxn1–3 genes alternative splicing may play an important role in the feedback control of neurotransmission by the endocannabinoid system. Full article

Background and Objectives: Docosahexaenoic acid (DHA) has been shown to modulate various voltage-gated ion channels and both excitatory and inhibitory synapses. Nonetheless, its exact effect on nociceptive signaling in the trigeminal system has yet to be elucidated. The purpose of the current investigation was to assess if acute DHA given intravenously to rats diminished the excitability of wide dynamic range spinal trigeminal nucleus caudalis (SpVc) neurons in response to mechanical stimulation in vivo. Methods: Single-unit extracellular activity was recorded from SpVc neurons in response to mechanical stimulation of the whisker pad in anesthetized rats. Responses to both non-noxious and noxious mechanical stimuli were analyzed in the present study. Results: The mean firing frequency of SpVc wide dynamic range neurons in response to both non-noxious and noxious mechanical stimuli was significantly dose-dependently inhibited by DHA, and the effect was seen within 5 min. After approximately 20 min, the inhibiting effects dissipated. Conclusions: These results suggest that, in the absence of inflammatory or neuropathic pain, the acute intravenous administration of DHA reduces the activity of trigeminal sensory neurons, including those responsible for pain, indicating that DHA could be utilized as an adjunct and alternative therapeutic agent for managing trigeminal nociceptive pain, including hyperalgesia. Full article

Chimera states and bump states are collective synchronization phenomena observed independently (in different parameter regions) in networks of coupled nonlinear oscillators. And while chimera states are characterized by coexistence of coherent and incoherent domains, bump states consist of alternating active and inactive domains. The idea of multistable plasticity in the network connections originates from brain dynamics where the strength of the synapses (axons) connecting the network nodes (neurons) may change dynamically in time; when reaching the steady state the network connections may be found in one of many possible values depending on various factors, such as local connectivity, influence of neighboring cells etc. The sign of the link weights is also a significant factor in the network dynamics: positive weights are characterized as excitatory connections and negative ones as inhibitory. In the present study we consider the simplest case of bistable plasticity, where the link dynamics has only two fixed points. During the system/network integration, the link weights change and as a consequence the network organizes in excitatory or inhibitory domains characterized by different synaptic strengths. We specifically explore the influence of bistable plasticity on collective synchronization states and we numerically demonstrate that the dynamics of the linking may, under special conditions, give rise to co-existence of bump-like and chimera-like states simultaneously in the network. In the case of bump and chimera co-existence, confinement effects appear: the different domains stay localized and do not travel around the network. Memory effects are also reported in the sense that the final spatial arrangement of the coupling strengths reflects some of the local properties of the initial link distribution. For the quantification of the system’s spatial and temporal features, the global and local entropy functions are employed as measures of the network organization, while the average firing rates account for the network evolution and dynamics. In particular, the spatial minima of the local entropy designate the transition points between domains of different synaptic weights in the hybrid states, while the number of minima corresponds to the number of different domains. In addition, the entropy deviations signify the presence of chimera-like or bump-like states in the network. Full article

Background: Brain-inspired models are commonly employed for artificial intelligence. However, the complex environment can hinder the performance of electronic equipment. Therefore, enhancing the injury resistance of brain-inspired models is a crucial issue. Human brains have self-adaptive abilities under injury, so drawing on the advantages of the human brain to construct a brain-inspired model is intended to enhance its injury resistance. But current brain-inspired models still lack bio-plausibility, meaning they do not sufficiently draw on real neural systems’ structure or function. Methods: To address this challenge, this paper proposes the complex spiking neural network (Com-SNN) as a brain-inspired model, in which the topology is inspired by the topological characteristics of biological functional brain networks, the nodes are Izhikevich neuron models, and the edges are synaptic plasticity models with time delay co-regulated by excitatory synapses and inhibitory synapses. To evaluate the injury resistance of the Com-SNN, two injury-resistance metrics are investigated and compared with SNNs with alternative topologies under the stochastic removal of neuron models to simulate the consequence of stochastic attacks. In addition, the injury-resistance mechanism of brain-inspired models remains unclear, and revealing the mechanism is crucial for understanding the development of SNNs with injury resistance. To address this challenge, this paper analyzes the synaptic plasticity dynamic regulation and dynamic topological characteristics of the Com-SNN under stochastic attacks. Results: The experimental results indicate that the injury resistance of the Com-SNN is superior to that of other SNNs, demonstrating that our results can help improve the injury resistance of SNNs. Conclusions: Our results imply that synaptic plasticity is an intrinsic element impacting injury resistance, and that network topology is another element that impacts injury resistance. Full article

Down syndrome (DS) is characterized by severe neurodevelopmental alterations that ultimately lead to the typical hallmark of DS: intellectual disability. In the DS brain, since the prenatal life stages, the number of astrocytes is disproportional compared to the healthy brain. This increase is due to a shift from neuron to astrocyte differentiation during brain development. Astrocytes are involved in numerous functions during brain development, including balancing pro-neurogenic and pro-gliogenic stimuli, sustaining synapse formation, regulating excitatory/inhibitory signal equilibrium, and supporting the maintenance and integration of functional neural circuits. The enhanced number of astrocytes in the brain of DS individuals leads to detrimental consequences for brain development. This review summarizes the mechanisms underlying astrocytic dysfunction in DS, and particularly the dysregulation of key signaling pathways, which promote astrogliogenesis at the expense of neurogenesis. It further examines the implications of astrocytic alterations on dendritic branching, spinogenesis and synaptogenesis, and the impact of the abnormal astrocytic number in neural excitability and in the maintenance of the inhibitory/excitatory balance. Identifying deregulated pathways and the consequences of astrocytic alterations in early DS brain development may help in identifying new therapeutic targets, with the ultimate aim of ameliorating the cognitive disability that affects individuals with DS. Full article

The maintenance of proper brain function relies heavily on the balance of excitatory and inhibitory neural circuits, governed in part by synaptic adhesion molecules. Among these, MDGA1 (MAM domain-containing glycosylphosphatidylinositol anchor 1) acts as a suppressor of synapse formation by interfering with Neuroligin-mediated interactions, crucial for maintaining the excitatory–inhibitory (E/I) balance. Mdga1^−/− mice exhibit selectively enhanced inhibitory synapse formation in their hippocampal pyramidal neurons, leading to impaired hippocampal long-term potentiation (LTP) and hippocampus-dependent learning and memory function; however, it has not been fully investigated yet if the reduction in MDGA1 protein levels would alter brain function. Here, we examined the behavioral and synaptic consequences of reduced MDGA1 protein levels in Mdga1^+/− mice. As observed in Mdga1^−/− mice, Mdga1^+/− mice exhibited significant deficits in hippocampus-dependent learning and memory tasks, such as the Morris water maze and contextual fear-conditioning tests, along with a significant deficit in the long-term potentiation (LTP) in hippocampal Schaffer collateral CA1 synapses. The acute administration of D-cycloserine, a co-agonist of NMDAR (N-methyl-d-aspartate receptor), significantly ameliorated memory impairments and restored LTP deficits specifically in Mdga1^+/− mice, while having no such effect on Mdga1^−/− mice. These results highlight the critical role of MDGA1 in regulating inhibitory synapse formation and maintaining the E/I balance for proper cognitive function. These findings may also suggest potential therapeutic strategies targeting the E/I imbalance to alleviate cognitive deficits associated with neuropsychiatric disorders. Full article

This paper proposes a novel, five-dimensional memristor synapse-coupled Izhikevich neuron model under electromagnetic induction. Firstly, we analyze the global exponential stability of the presented system by constructing an appropriate Lyapunov function. Furthermore, the Hamilton energy functions of the model and its corresponding error system are derived by using Helmholtz’s theorem. In addition, the influence of external current and system parameters on the dynamical behavior are investigated. The numerical simulation results indicate that the discharge pattern of excitatory and inhibitory neurons changes significantly when the amplitude and frequency of the external stimulus current are applied at different degrees. And the crucial dynamical behavior of the neuronal system is determined by the intensity of modulation of the induced current and the gain in the electromagnetic induction. Moreover, the amount of Hamilton energy released by the model could be evaluated during the conversion between the distinct dynamical behaviors. Full article

We present a novel set of quantitative measures for “likeness” (error function) designed to alleviate the time-consuming and subjective nature of manually comparing biological recordings from electrophysiological experiments with the outcomes of their mathematical models. Our innovative “blended” system approach offers an objective, high-throughput, and computationally efficient method for comparing biological and mathematical models. This approach involves using voltage recordings of biological neurons to drive and train mathematical models, facilitating the derivation of the error function for further parameter optimization. Our calibration process incorporates measurements such as action potential (AP) frequency, voltage moving average, voltage envelopes, and the probability of post-synaptic channels. To assess the effectiveness of our method, we utilized the sea slug Melibe leonina swim central pattern generator (CPG) as our model circuit and conducted electrophysiological experiments with TTX to isolate CPG interneurons. During the comparison of biological recordings and mathematically simulated neurons, we performed a grid search of inhibitory and excitatory synapse conductance. Our findings indicate that a weighted sum of simple functions is essential for comprehensively capturing a neuron’s rhythmic activity. Overall, our study suggests that our blended system approach holds promise for enabling objective and high-throughput comparisons between biological and mathematical models, offering significant potential for advancing research in neural circuitry and related fields. Full article