The Dynamic Synapse

Hydrodynamics of a disk in a thin film of weakly nematic fluid subject to linear friction

To make progress towards the development of a theory on the motion of inclusions in thin structured films and membranes, we here consider as an initial step a circular disk in a two-dimensional, uniaxially anisotropic fluid layer. We assume overdamped dynamics, incompressibility of the fluid, and global alignment of the axis of anisotropy. Motion within this layer is affected by additional linear friction with the environment, for instance, a supporting substrate. We investigate the induced flows in the fluid when the disk is translated parallel or perpendicular to the direction of anisotropy. Moreover, expressions for corresponding mobilities and resistance coefficients of the disk are derived. Our results are obtained within the framework of a perturbative expansion in the parameters that quantify the anisotropy of the fluid. Good agreement is found for moderate anisotropy when compared to associated results from finite-element simulations. At pronounced anisotropy, the induced flow fields are still predicted qualitatively correctly by the perturbative theory, although quantitative deviations arise. We hope to stimulate with our investigations corresponding experimental analyses, for example, concerning fluid flows in anisotropic thin films on uniaxially rubbed supporting substrates.

Unraveling the complexity of human brain: Structure, function in healthy and disease states

The human brain stands as an intricate organ, embodying a nexus of structure, function, development, and diversity. This review delves into the multifaceted landscape of the brain, spanning its anatomical intricacies, diverse functional capacities, dynamic developmental trajectories, and inherent variability across individuals. The dynamic process of brain development, from early embryonic stages to adulthood, highlights the nuanced changes that occur throughout the lifespan. The brain, a remarkably complex organ, is composed of various anatomical regions, each contributing uniquely to its overall functionality. Through an exploration of neuroanatomy, neurophysiology, and electrophysiology, this review elucidates how different brain structures interact to support a wide array of cognitive processes, sensory perception, motor control, and emotional regulation. Moreover, it addresses the impact of age, sex, and ethnic background on brain structure and function, and gender differences profoundly influence the onset, progression, and manifestation of brain disorders shaped by genetic, hormonal, environmental, and social factors. Delving into the complexities of the human brain, it investigates how variations in anatomical configuration correspond to diverse functional capacities across individuals. Furthermore, it examines the impact of neurodegenerative diseases on the structural and functional integrity of the brain. Specifically, our article explores the pathological processes underlying neurodegenerative diseases, such as Alzheimer's, Parkinson's, and Huntington's diseases, shedding light on the structural alterations and functional impairments that accompany these conditions. We will also explore the current research trends in neurodegenerative diseases and identify the existing gaps in the literature. Overall, this article deepens our understanding of the fundamental principles governing brain structure and function and paves the way for a deeper understanding of individual differences and tailored approaches in neuroscience and clinical practice-additionally, a comprehensive understanding of structural and functional changes that manifest in neurodegenerative diseases.

Saponin components in Polygala tenuifolia as potential candidate drugs for treating dementia

Objective

This study aims to elucidate the intervention effects of saponin components from Polygala tenuifolia Willd (Polygalaceae) on dementia, providing experimental evidence and new insights for the research and application of saponins in the field of dementia.

Materials and Methods

This review is based on a search of the PubMed, NCBI, and Google Scholar databases from their inception to 13 May 2024, using terms such as "P. tenuifolia," "P. tenuifolia and saponins," "toxicity," "dementia," "Alzheimer's disease," "Parkinson's disease dementia," and "vascular dementia." The article summarizes the saponin components of P. tenuifolia, including tenuigenin, tenuifolin, polygalasaponins XXXII, and onjisaponin B, as well as the pathophysiological mechanisms of dementia. Importantly, it highlights the potential mechanisms by which the active components of P. tenuifolia prevent and treat diseases and relevant clinical studies.

Results

The saponin components of P. tenuifolia can reduce β-amyloid accumulation, exhibit antioxidant effects, regulate neurotransmitters, improve synaptic function, possess anti-inflammatory properties, inhibit neuronal apoptosis, and modulate autophagy. Therefore, P. tenuifolia may play a role in the prevention and treatment of dementia.

Conclusion

The saponin components of P. tenuifolia have shown certain therapeutic effects on dementia. They can prevent and treat dementia through various mechanisms.

A novel multivariate time series forecasting dendritic neuron model for COVID-19 pandemic transmission tendency

A novel coronavirus discovered in late 2019 (COVID-19) quickly spread into a global epidemic and, thankfully, was brought under control by 2022. Because of the virus's unknown mutations and the vaccine's waning potency, forecasting is still essential for resurgence prevention and medical resource management. Computational efficiency and long-term accuracy are two bottlenecks for national-level forecasting. This study develops a novel multivariate time series forecasting model, the densely connected highly flexible dendritic neuron model (DFDNM) to predict daily and weekly positive COVID-19 cases. DFDNM's high flexibility mechanism improves its capacity to deal with nonlinear challenges. The dense introduction of shortcut connections alleviates the vanishing and exploding gradient problems, encourages feature reuse, and improves feature extraction. To deal with the rapidly growing parameters, an improved variation of the adaptive moment estimation (AdamW) algorithm is employed as the learning algorithm for the DFDNM because of its strong optimization ability. The experimental results and statistical analysis conducted across three Japanese prefectures confirm the efficacy and feasibility of the DFDNM while outperforming various state-of-the-art machine learning models. To the best of our knowledge, the proposed DFDNM is the first to restructure the dendritic neuron model's neural architecture, demonstrating promising use in multivariate time series prediction. Because of its optimal performance, the DFDNM may serve as an important reference for national and regional government decision-makers aiming to optimize pandemic prevention and medical resource management. We also verify that DFDMN is efficiently applicable not only to COVID-19 transmission prediction, but also to more general multivariate prediction tasks. It leads us to believe that it might be applied as a promising prediction model in other fields.

Tuning synaptic strength by regulation of AMPA glutamate receptor localization

Long-term potentiation (LTP) of excitatory synapses is a leading model to explain the concept of information storage in the brain. Multiple mechanisms contribute to LTP, but central amongst them is an increased sensitivity of the postsynaptic membrane to neurotransmitter release. This sensitivity is predominantly determined by the abundance and localization of AMPA-type glutamate receptors (AMPARs). A combination of AMPAR structural data, super-resolution imaging of excitatory synapses, and an abundance of electrophysiological studies are providing an ever-clearer picture of how AMPARs are recruited and organized at synaptic junctions. Here, we review the latest insights into this process, and discuss how both cytoplasmic and extracellular receptor elements cooperate to tune the AMPAR response at the hippocampal CA1 synapse.

Sustained Depolarization Induces Gene Expression Pattern Changes Related to Synaptic Plasticity in a Human Cholinergic Cellular Model

Neuronal gene expression in the brain dynamically responds to synaptic activity. The interplay among synaptic activity, gene expression, and synaptic plasticity has crucial implications for understanding the pathophysiology of diseases such as Alzheimer's disease and epilepsy. These diseases are marked by synaptic dysfunction that affects the expression patterns of neuroprotective genes that are incompletely understood. In our study, we developed a cellular model of synaptic activity using human cholinergic neurons derived from SH-SY5Y cell differentiation. Depolarization induction modulates the expression of neurotrophic genes and synaptic markers, indicating a potential role in synaptic plasticity regulation. This hypothesis is further supported by the induction kinetics of various long non-coding RNAs, including primate-specific ones. Our experimental model showcases the utility of SH-SY5Y cells in elucidating the molecular mechanisms underlying synaptic plasticity in human cellular systems.

Demixing is a default process for biological condensates formed via phase separation

Excitatory and inhibitory synapses do not overlap even when formed on one submicron-sized dendritic protrusion. How excitatory and inhibitory postsynaptic cytomatrices or densities (e/iPSDs) are segregated is not understood. Broadly, why membraneless organelles are naturally segregated in cellular subcompartments is unclear. Using biochemical reconstitutions in vitro and in cells, we demonstrate that ePSDs and iPSDs spontaneously segregate into distinct condensed molecular assemblies through phase separation. Tagging iPSD scaffold gephyrin with a PSD-95 intrabody (dissociation constant ~4 nM) leads to mistargeting of gephyrin to ePSD condensates. Unexpectedly, formation of iPSD condensates forces the intrabody-tagged gephyrin out of ePSD condensates. Thus, instead of diffusion-governed spontaneous mixing, demixing is a default process for biomolecules in condensates. Phase separation can generate biomolecular compartmentalization specificities that cannot occur in dilute solutions.

Asymptotic analysis of particle cluster formation in the presence of anchoring sites

The aggregation or clustering of proteins and other macromolecules plays an important role in the formation of large-scale molecular assemblies within cell membranes. Examples of such assemblies include lipid rafts, and postsynaptic domains (PSDs) at excitatory and inhibitory synapses in neurons. PSDs are rich in scaffolding proteins that can transiently trap transmembrane neurotransmitter receptors, thus localizing them at specific spatial positions. Hence, PSDs play a key role in determining the strength of synaptic connections and their regulation during learning and memory. Recently, a two-dimensional (2D) diffusion-mediated aggregation model of PSD formation has been developed in which the spatial locations of the clusters are determined by a set of fixed anchoring sites. The system is kept out of equilibrium by the recycling of particles between the cell membrane and interior. This results in a stationary distribution consisting of multiple clusters, whose average size can be determined using an effective mean-field description of the particle concentration around each anchored cluster. In this paper, we derive corrections to the mean-field approximation by applying the theory of diffusion in singularly perturbed domains. The latter is a powerful analytical method for solving two-dimensional (2D) and three-dimensional (3D) diffusion problems in domains where small holes or perforations have been removed from the interior. Applications range from modeling intracellular diffusion, where interior holes could represent subcellular structures such as organelles or biological condensates, to tracking the spread of chemical pollutants or heat from localized sources. In this paper, we take the bounded domain to be the cell membrane and the holes to represent anchored clusters. The analysis proceeds by partitioning the membrane into a set of inner regions around each cluster, and an outer region where mean-field interactions occur. Asymptotically matching the inner and outer stationary solutions generates an asymptotic expansion of the particle concentration, which includes higher-order corrections to mean-field theory that depend on the positions of the clusters and the boundary of the domain. Motivated by a recent study of light-activated protein oligomerization in cells, we also develop the analogous theory for cluster formation in a three-dimensional (3D) domain. The details of the asymptotic analysis differ from the 2D case due to the contrasting singularity structure of 2D and 3D Green's functions.

SRC family kinase inhibition rescues molecular and behavioral phenotypes, but not protein interaction network dynamics, in a mouse model of Fragile X syndrome

Glutamatergic synapses encode information from extracellular inputs using dynamic protein interaction networks (PINs) that undergo widespread reorganization following synaptic activity, allowing cells to distinguish between signaling inputs and generate coordinated cellular responses. Here, we investigate how Fragile X Messenger Ribonucleoprotein (FMRP) deficiency disrupts signal transduction through a glutamatergic synapse PIN downstream of NMDA receptor or metabotropic glutamate receptor (mGluR) stimulation. In cultured cortical neurons or acute cortical slices from P7, P17 and P60 FMR1-/y mice, the unstimulated protein interaction network state resembled that of wildtype littermates stimulated with mGluR agonists, demonstrating resting state pre-activation of mGluR signaling networks. In contrast, interactions downstream of NMDAR stimulation were similar to WT. We identified the Src family kinase (SFK) Fyn as a network hub, because many interactions involving Fyn were pre-activated in FMR1-/y animals. We tested whether targeting SFKs in FMR1-/y mice could modify disease phenotypes, and found that Saracatinib (SCB), an SFK inhibitor, normalized elevated basal protein synthesis, novel object recognition memory and social behavior in FMR1-/y mice. However, SCB treatment did not normalize the PIN to a wild-type-like state in vitro or in vivo, but rather induced extensive changes to protein complexes containing Shank3, NMDARs and Fyn. We conclude that targeting abnormal nodes of a PIN can identify potential disease-modifying drugs, but behavioral rescue does not correlate with PIN normalization.

Darwin3: a large-scale neuromorphic chip with a novel ISA and on-chip learning

Spiking neural networks (SNNs) are gaining increasing attention for their biological plausibility and potential for improved computational efficiency. To match the high spatial-temporal dynamics in SNNs, neuromorphic chips are highly desired to execute SNNs in hardware-based neuron and synapse circuits directly. This paper presents a large-scale neuromorphic chip named Darwin3 with a novel instruction set architecture, which comprises 10 primary instructions and a few extended instructions. It supports flexible neuron model programming and local learning rule designs. The Darwin3 chip architecture is designed in a mesh of computing nodes with an innovative routing algorithm. We used a compression mechanism to represent synaptic connections, significantly reducing memory usage. The Darwin3 chip supports up to 2.35 million neurons, making it the largest of its kind on the neuron scale. The experimental results showed that the code density was improved by up to 28.3× in Darwin3, and that the neuron core fan-in and fan-out were improved by up to 4096× and 3072× by connection compression compared to the physical memory depth. Our Darwin3 chip also provided memory saving between 6.8× and 200.8× when mapping convolutional spiking neural networks onto the chip, demonstrating state-of-the-art performance in accuracy and latency compared to other neuromorphic chips.

CSF1R-mediated myeloid cell depletion shifts the ratio of motor cortical excitatory to inhibitory neurons in a multiple system atrophy model

Motor cortical circuit functions depend on the coordinated fine-tuning of two functionally diverse neuronal populations: glutamatergic pyramidal neurons providing synaptic excitation and GABAergic interneurons adjusting the response of pyramidal neurons through synaptic inhibition. Microglia are brain resident macrophages which dynamically refine cortical circuits by monitoring perineuronal extracellular matrix and remodelling synapses. Previously, we showed that colony-stimulating factor 1 receptor (CSF1R)-mediated myeloid cell depletion extended the lifespan, but impaired motor functions of MBP29 mice, a mouse model for multiple system atrophy. In order to better understand the mechanisms underlying these motor deficits we characterized the microglial involvement in the cortical balance of GABAergic interneurons and glutamatergic pyramidal neurons in 4-months-old MBP29 mice following CSF1R inhibition for 12 weeks. Lack of myeloid cells resulted in a decreased number of COUP TF1 interacting protein 2-positive (CTIP2+) layer V pyramidal neurons, however in a proportional increase of calretinin-positive GABAergic interneurons in MBP29 mice. While myeloid cell depletion did not alter the expression of important presynaptic and postsynaptic proteins, the loss of cortical perineuronal net area was attenuated by CSF1R inhibition in MBP29 mice. These cortical changes may restrict synaptic plasticity and potentially modify parvalbumin-positive perisomatic input. Collectively, this study suggests, that the lack of myeloid cells shifts the neuronal balance toward an increased inhibitory connectivity in the motor cortex of MBP29 mice thereby potentially deteriorating motor functions.

Role of GLR-1 in Age-Dependent Short-Term Memory Decline

As the global elderly population grows, age-related cognitive decline is becoming an increasingly significant healthcare issue, often leading to various neuropsychiatric disorders. Among the many molecular players involved in memory, AMPA-type glutamate receptors are known to regulate learning and memory, but how their dynamics change with age and affect memory decline is not well understood. Here, we examined the in vivo properties of the AMPA-type glutamate receptor GLR-1 in the AVA interneuron of the Caenorhabditis elegans nervous system during physiological aging. We found that both total and membrane-bound GLR-1 receptor levels decrease with age in wild-type worms, regardless of their location along the axon. Using fluorescence recovery after photobleaching, we also demonstrated that a reduction in GLR-1 abundance correlates with decreased local, synaptic GLR-1 receptor dynamics. Importantly, we found that reduced GLR-1 levels strongly correlate with the age-related decline in short-term associative memory. Genetic manipulation of GLR-1 stability, by either deleting msi-1 or expressing a ubiquitination-defective GLR-1 (4KR) variant, prevented this age-related reduction in receptor abundance and improved the short-term memory performance in older animals, which reached performance levels similar to those of young animals. Overall, our data indicate that AMPA-type glutamate receptor abundance and dynamics are key factors in maintaining memory function and that changes in these parameters are linked to age-dependent short-term memory decline.

Activity-dependent mitochondrial ROS signaling regulates recruitment of glutamate receptors to synapses

Our understanding of mitochondrial signaling in the nervous system has been limited by the technical challenge of analyzing mitochondrial function in vivo. In the transparent genetic model Caenorhabditis elegans, we were able to manipulate and measure mitochondrial reactive oxygen species (mitoROS) signaling of individual mitochondria as well as neuronal activity of single neurons in vivo. Using this approach, we provide evidence supporting a novel role for mitoROS signaling in dendrites of excitatory glutamatergic C. elegans interneurons. Specifically, we show that following neuronal activity, dendritic mitochondria take up calcium (Ca2+) via the mitochondrial Ca2+ uniporter (MCU-1) that results in an upregulation of mitoROS production. We also observed that mitochondria are positioned in close proximity to synaptic clusters of GLR-1, the C. elegans ortholog of the AMPA subtype of glutamate receptors that mediate neuronal excitation. We show that synaptic recruitment of GLR-1 is upregulated when MCU-1 function is pharmacologically or genetically impaired but is downregulated by mitoROS signaling. Thus, signaling from postsynaptic mitochondria may regulate excitatory synapse function to maintain neuronal homeostasis by preventing excitotoxicity and energy depletion.

A Necessary Role for PKC-2 and TPA-1 in Olfactory Memory and Synaptic AMPAR Trafficking in Caenorhabditis elegans

Protein kinase C (PKC) functions are essential for synaptic plasticity, learning, and memory. However, the roles of specific members of the PKC family in synaptic function, learning, and memory are poorly understood. Here, we investigated the role of individual PKC homologs for synaptic plasticity in Caenorhabditis elegans and found a differential role for pkc-2 and tpa-1, but not pkc-1 and pkc-3 in associative olfactory learning and memory. More specifically we show that PKC-2 is essential for associative learning and TPA-1 for short-term associative memory (STAM). Using endogenous labeling and cell-specific rescues, we show that TPA-1 and PKC-2 are required in AVA for their functions. Previous studies demonstrated that olfactory learning and memory in C. elegans are tied to proper synaptic content and trafficking of AMPA-type ionotropic glutamate receptor homolog GLR-1 in the AVA command interneurons. Therefore, we quantified synaptic content, transport, and delivery of GLR-1 in AVA and showed that loss of pkc-2 and tpa-1 leads to decreased transport and delivery but only a subtle decrease in GLR-1 levels at synapses. AVA-specific expression of both PKC-2 and TPA-1 rescued these defects. Finally, genetic epistasis showed that PKC-2 and TPA-1 likely act in the same pathway to control GLR-1 transport and delivery, while regulating different aspects of olfactory learning and STAM. Thus, our data tie together cell-specific functions of 2 PKCs to neuronal and behavioral outcomes in C. elegans, enabling comparative approaches to understand the evolutionarily conserved role of PKC in synaptic plasticity, learning, and memory.

The gephyrin scaffold modulates cortical layer 2/3 pyramidal neuron responsiveness to single whisker stimulation

Gephyrin is the main scaffolding protein at inhibitory postsynaptic sites, and its clusters are the signaling hubs where several molecular pathways converge. Post-translational modifications (PTMs) of gephyrin alter GABAA receptor clustering at the synapse, but it is unclear how this affects neuronal activity at the circuit level. We assessed the contribution of gephyrin PTMs to microcircuit activity in the mouse barrel cortex by slice electrophysiology and in vivo two-photon calcium imaging of layer 2/3 (L2/3) pyramidal cells during single-whisker stimulation. Our results suggest that, depending on the type of gephyrin PTM, the neuronal activities of L2/3 pyramidal neurons can be differentially modulated, leading to changes in the size of the neuronal population responding to the single-whisker stimulation. Furthermore, we show that gephyrin PTMs have their preference for selecting synaptic GABAA receptor subunits. Our results identify an important role of gephyrin and GABAergic postsynaptic sites for cortical microcircuit function during sensory stimulation.

Operation-robust SiO2-based memristive application in air

In recent years, neuromorphic computing is recognized as a promising path to further improve the efficiency of integrated computing system in the post-Moore era, relying on its high parallelism. As a key fundamental element in hardware-implementing neuromorphic system, the synaptic device has made substantial research progress. Among these, SiO2 trapping-based memristive devices generally have systematically integrated merits, such as ease of fabrication and high CMOS process compatibility, but electrochemical activity to oxygen makes them unreliable for operating in air. Here, by using ultrathin Si3N4 as a physical isolation layer, we have obtained a robust memristive device based on SiO2 trapping although operating in air. Further study of Si3N4 thickness dependence has demonstrated that 7 nm is suggested as the most favorable thickness for reliable and flexible programming, and that an inherent isolating mechanism is 'switching-on' for an electron but 'switching-off' for large-sized oxygen molecules. Based on a device with 7 nm Si3N4, we have mimicked various modes of synaptic plasticities. These results could thus not only increase the prospects of using SiO2 trapping in memristive applications but also provide an effective path to improve the robustness of these SiO2-based applications against ambient air.

Disease Mechanisms of Multiple System Atrophy: What a Parallel Between the Form of Pasta and the Alpha-Synuclein Assemblies Involved in MSA and PD Tells Us

Intracellular deposits rich in aggregated alpha-synuclein that appear within the central nervous system are intimately associated to Parkinson's disease and multiple system atrophy. While it is understandable that the aggregation of proteins, which share no primary structure identity, such as alpha-synuclein and tau protein, leads to different diseases, that of a given protein yielding distinct pathologies is counterintuitive. This short review relates molecular and mechanistic processes to the observed pathological diversity associated to alpha-synuclein aggregation.

Cooperativity, Information Gain, and Energy Cost During Early LTP in Dendritic Spines

We investigate a mutual relationship between information and energy during the early phase of LTP induction and maintenance in a large-scale system of mutually coupled dendritic spines, with discrete internal states and probabilistic dynamics, within the framework of nonequilibrium stochastic thermodynamics. In order to analyze this computationally intractable stochastic multidimensional system, we introduce a pair approximation, which allows us to reduce the spine dynamics into a lower-dimensional manageable system of closed equations. We found that the rates of information gain and energy attain their maximal values during an initial period of LTP (i.e., during stimulation), and after that, they recover to their baseline low values, as opposed to a memory trace that lasts much longer. This suggests that the learning phase is much more energy demanding than the memory phase. We show that positive correlations between neighboring spines increase both a duration of memory trace and energy cost during LTP, but the memory time per invested energy increases dramatically for very strong, positive synaptic cooperativity, suggesting a beneficial role of synaptic clustering on memory duration. In contrast, information gain after LTP is the largest for negative correlations, and energy efficiency of that information generally declines with increasing synaptic cooperativity. We also find that dendritic spines can use sparse representations for encoding long-term information, as both energetic and structural efficiencies of retained information and its lifetime exhibit maxima for low fractions of stimulated synapses during LTP. Moreover, we find that such efficiencies drop significantly with increasing the number of spines. In general, our stochastic thermodynamics approach provides a unifying framework for studying, from first principles, information encoding, and its energy cost during learning and memory in stochastic systems of interacting synapses.

Single-cell expression predicts neuron-specific protein homeostasis networks

The protein homeostasis network keeps proteins in their correct shapes and avoids unwanted aggregation. In turn, the accumulation of aberrantly misfolded proteins has been directly associated with the onset of ageing-associated neurodegenerative diseases such as Alzheimer's and Parkinson's. However, a detailed and rational understanding of how protein homeostasis is achieved in health, and how it can be targeted for therapeutic intervention in diseases remains missing. Here, large-scale single-cell expression data from the Allen Brain Map are analysed to investigate the transcription regulation of the core protein homeostasis network across the human brain. Remarkably, distinct expression profiles suggest specialized protein homeostasis networks with systematic adaptations in excitatory neurons, inhibitory neurons and non-neuronal cells. Moreover, several chaperones and Ubiquitin ligases are found transcriptionally coregulated with genes important for synapse formation and maintenance, thus linking protein homeostasis to the regulation of neuronal function. Finally, evolutionary analyses highlight the conservation of an elevated interaction density in the chaperone network, suggesting that one of the most exciting aspects of chaperone action may yet be discovered in their collective action at the systems level. More generally, our work highlights the power of computational analyses for breaking down complexity and gaining complementary insights into fundamental biological problems.

High-Performance Neuromorphic Computing and Logic Operation Based on a Self-Assembled Vertically Aligned Nanocomposite SrTiO3:MgO Film Memristor

Neuromorphic computing based on memristors capable of in-memory computing is promising to break the energy and efficiency bottleneck of well-known von Neumann architectures. However, unstable and nonlinear conductance updates compromise the recognition accuracy and block the integration of neural network hardware. To this end, we present a highly stable memristor with self-assembled vertically aligned nanocomposite (VAN) SrTiO3:MgO films that achieve excellent resistive switching with low set/reset voltage variability (4.7%/-5.6%) and highly linear conductivity variation (nonlinearity = 0.34) by spatially limiting the conductive channels at the vertical interfaces. Various synaptic behaviors are simulated by continuously modulating the conductance. Especially, convolutional image processing using diverse crossbar kernels is demonstrated, and the artificial neural network achieves an overwhelming recognition accuracy of up to 97.50% for handwritten digits. Even under the perturbation of Poisson noise (λ = 10), 6% Salt and Pepper noise, and 5% Gaussian noise, the high recognition accuracies are retained at 95.43%, 94.56%, and 95.97%, respectively. Importantly, the logic memory function is proven experimentally based on the nonvolatile properties. This work provides a material system and design idea to achieve high-performance neuromorphic computing and logic operation.

Hybrid neuromorphic hardware with sparing 2D synapse and CMOS neuron for character recognition

Neuromorphic computing enables efficient processing of data-intensive tasks, but requires numerous artificial synapses and neurons for certain functions, which leads to bulky systems and energy challenges. Achieving functionality with fewer synapses and neurons will facilitate integration density and computility. Two-dimensional (2D) materials exhibit potential for artificial synapses, including diverse biomimetic plasticity and efficient computing. Considering the complexity of neuron circuits and the maturity of complementary metal-oxide-semiconductor (CMOS), hybrid integration is attractive. Here, we demonstrate a hybrid neuromorphic hardware with 2D MoS2 synaptic arrays and CMOS neural circuitry integrated on board. With the joint benefit of hybrid integration, frequency coding and feature extraction, a total cost of twelve MoS2 synapses, three CMOS neurons, combined with digital/analogue converter enables alphabetic and numeric recognition. MoS2 synapses exhibit progressively tunable weight plasticity, CMOS neurons integrate and fire frequency-encoded spikes to display the target characters. The synapse- and neuron-saving hybrid hardware exhibits a competitive accuracy of 98.8% and single recognition energy consumption of 11.4 μW. This work provides a viable solution for building neuromorphic hardware with high compactness and computility.

Emerging Opportunities for 2D Materials in Neuromorphic Computing

Recently, two-dimensional (2D) materials and their heterostructures have been recognized as the foundation for future brain-like neuromorphic computing devices. Two-dimensional materials possess unique characteristics such as near-atomic thickness, dangling-bond-free surfaces, and excellent mechanical properties. These features, which traditional electronic materials cannot achieve, hold great promise for high-performance neuromorphic computing devices with the advantages of high energy efficiency and integration density. This article provides a comprehensive overview of various 2D materials, including graphene, transition metal dichalcogenides (TMDs), hexagonal boron nitride (h-BN), and black phosphorus (BP), for neuromorphic computing applications. The potential of these materials in neuromorphic computing is discussed from the perspectives of material properties, growth methods, and device operation principles.

NKCC1 and KCC2 Chloride Transporters Have Different Membrane Dynamics on the Surface of Hippocampal Neurons

Na-K-2Cl cotransporter 1 (NKCC1) regulates chloride influx in neurons and thereby GABAA receptor activity in normal and pathological conditions. Here, we characterized in hippocampal neurons the membrane expression, distribution and dynamics of exogenous NKCC1a and NKCC1b isoforms and compared them to those of the chloride extruder K-Cl cotransporter 2 (KCC2). We found that NKCC1a and NKCC1b behave quite similarly. NKCC1a/1b but not KCC2 are present along the axon initial segment where they are confined. Moreover, NKCC1a/1b are detected in the somato-dendritic compartment at a lower level than KCC2, where they form fewer, smaller and less compact clusters at perisynaptic and extrasynaptic sites. Interestingly, ~60% of dendritic clusters of NKCC1a/1b are colocalized with KCC2. They are larger and brighter than those devoid of KCC2, suggesting a particular NKCC1a/1b-KCC2 relationship. In agreement with the reduced dendritic clustering of NKCC1a/1b compared with that of KCC2, NKCC1a/1b are more mobile on the dendrite than KCC2, suggesting weaker cytoskeletal interaction. NKCC1a/b are confined to endocytic zones, where they spend more time than KCC2. However, they spend less time in these compartments than at the synapses, suggesting that they can rapidly leave endocytic zones to increase the membrane pool, which can happen in pathological conditions. Thus, NKCC1a/b have different membrane dynamics and clustering from KCC2, which helps to explain their low level in the neuronal membrane, while allowing a rapid increase in the membrane pool under pathological conditions.

Linking spontaneous and stimulated spine dynamics

Our brains continuously acquire and store memories through synaptic plasticity. However, spontaneous synaptic changes can also occur and pose a challenge for maintaining stable memories. Despite fluctuations in synapse size, recent studies have shown that key population-level synaptic properties remain stable over time. This raises the question of how local synaptic plasticity affects the global population-level synaptic size distribution and whether individual synapses undergoing plasticity escape the stable distribution to encode specific memories. To address this question, we (i) studied spontaneously evolving spines and (ii) induced synaptic potentiation at selected sites while observing the spine distribution pre- and post-stimulation. We designed a stochastic model to describe how the current size of a synapse affects its future size under baseline and stimulation conditions and how these local effects give rise to population-level synaptic shifts. Our study offers insights into how seemingly spontaneous synaptic fluctuations and local plasticity both contribute to population-level synaptic dynamics.

Neurexin-3 subsynaptic densities are spatially distinct from Neurexin-1 and essential for excitatory synapse nanoscale organization in the hippocampus

Proteins critical for synaptic transmission are non-uniformly distributed and assembled into regions of high density called subsynaptic densities (SSDs) that transsynaptically align in nanocolumns. Neurexin-1 and neurexin-3 are essential presynaptic adhesion molecules that non-redundantly control NMDAR- and AMPAR-mediated synaptic transmission, respectively, via transsynaptic interactions with distinct postsynaptic ligands. Despite their functional relevance, fundamental questions regarding the nanoscale properties of individual neurexins, their influence on the subsynaptic organization of excitatory synapses and the mechanisms controlling how individual neurexins engage in precise transsynaptic interactions are unknown. Using Double Helix 3D dSTORM and neurexin mouse models, we identify neurexin-3 as a critical presynaptic adhesion molecule that regulates excitatory synapse nano-organization in hippocampus. Furthermore, endogenous neurexin-1 and neurexin-3 form discrete and non-overlapping SSDs that are enriched opposite their postsynaptic ligands. Thus, the nanoscale organization of neurexin-1 and neurexin-3 may explain how individual neurexins signal in parallel to govern different synaptic properties.

Unveiling the Neural Environment in Cancer: Exploring the Role of Neural Circuit Players and Potential Therapeutic Strategies

The regulation of the immune environment within the tumor microenvironment has provided new opportunities for cancer treatment. However, an important microenvironment surrounding cancer that is often overlooked despite its significance in cancer progression is the neural environment surrounding the tumor. The release of neurotrophic factors from cancer cells is implicated in cancer growth and metastasis by facilitating the infiltration of nerve cells into the tumor microenvironment. This nerve-tumor interplay can elicit cancer cell proliferation, migration, and invasion in response to neurotransmitters. Moreover, it is possible that cancer cells could establish a network resembling that of neurons, allowing them to communicate with one another through neurotransmitters. The expression levels of players in the neural circuits of cancers could serve as potential biomarkers for cancer aggressiveness. Notably, the upregulation of certain players in the neural circuit has been linked to poor prognosis in specific cancer types such as breast cancer, pancreatic cancer, basal cell carcinoma, and stomach cancer. Targeting these players with inhibitors holds great potential for reducing the morbidity and mortality of these carcinomas. However, the efficacy of anti-neurogenic agents in cancer therapy remains underexplored, and further research is necessary to evaluate their effectiveness as a novel approach for cancer treatment. This review summarizes the current knowledge on the role of players in the neural circuits of cancers and the potential of anti-neurogenic agents for cancer therapy.

Mimicking biological synapses with a-HfSiOx-based memristor: implications for artificial intelligence and memory applications

Memristors, owing to their uncomplicated structure and resemblance to biological synapses, are predicted to see increased usage in the domain of artificial intelligence. Additionally, to augment the capacity for multilayer data storage in high-density memory applications, meticulous regulation of quantized conduction with an extremely low transition energy is required. In this work, an a-HfSiO_x-based memristor was grown through atomic layer deposition (ALD) and investigated for its electrical and biological properties for use in multilevel switching memory and neuromorphic computing systems. The crystal structure and chemical distribution of the HfSiOx/TaN layers were analyzed using X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS), respectively. The Pt/a-HfSiO_x/TaN memristor was confirmed by transmission electron microscopy (TEM) and showed analog bipolar switching behavior with high endurance stability (1000 cycles), long data retention performance (10⁴ s), and uniform voltage distribution. Its multilevel capability was demonstrated by restricting current compliance (CC) and stopping the reset voltage. The memristor exhibited synaptic properties, such as short-term plasticity, excitatory postsynaptic current (EPSC), spiking-rate-dependent plasticity (SRDP), post-tetanic potentiation (PTP), and paired-pulse facilitation (PPF). Furthermore, it demonstrated 94.6% pattern accuracy in neural network simulations. Thus, a-HfSiO_x-based memristors have great potential for use in multilevel memory and neuromorphic computing systems.

The kinesin Kif21b binds myosin Va and mediates changes in actin dynamics underlying homeostatic synaptic downscaling

Homeostatic synaptic plasticity adjusts the strength of synapses to restrain neuronal activity within a physiological range. Postsynaptic guanylate kinase-associated protein (GKAP) controls the bidirectional synaptic scaling of AMPA receptors (AMPARs); however, mechanisms by which chronic activity triggers cytoskeletal remodeling to downscale synaptic transmission are barely understood. Here, we report that the microtubule-dependent kinesin motor Kif21b binds GKAP and likewise is located in dendritic spines in a myosin Va- and neuronal-activity-dependent manner. Kif21b depletion unexpectedly alters actin dynamics in spines, and adaptation of actin turnover following chronic activity is lost in Kif21b-knockout neurons. Consistent with a role of the kinesin in regulating actin dynamics, Kif21b overexpression promotes actin polymerization. Moreover, Kif21b controls GKAP removal from spines and the decrease of GluA2-containing AMPARs from the neuronal surface, thereby inducing homeostatic synaptic downscaling. Our data highlight a critical role of Kif21b at the synaptic actin cytoskeleton underlying homeostatic scaling of neuronal firing.

Comparative Analysis of Water Extracts from Roselle (Hibiscus sabdariffa L.) Plants and Callus Cells: Constituents, Effects on Human Skin Cells, and Transcriptome Profiles

Roselle (Hibiscus sabdariffa L.) is a plant that has traditionally been used in various food and beverage products. Here, we investigated the potential of water extracts derived from Roselle leaves and callus cells for cosmetic and pharmaceutical purposes. We generated calluses from Roselle leaves and produced two different water extracts through heat extraction, which we named Hibiscus sabdariffa plant extract (HSPE) and Hibiscus sabdariffa callus extract (HSCE). HPLC analysis showed that the two extracts have different components, with nucleic acids and metabolites such as phenylalanine and tryptophan being the most common components in both extracts. In vitro assays demonstrated that HSCE has strong anti-melanogenic effects and functions for skin barrier and antioxidant activity. Transcriptome profiling of human skin cells treated with HSPE and HSCE showed significant differences, with HSPE having more effects on human skin cells. Up-regulated genes by HSPE function in angiogenesis, the oxidation-reduction process, and glycolysis, while up-regulated genes by HSCE encode ribosome proteins and IFI6, functioning in the healing of radiation-injured skin cells. Therefore, we suggest that the two extracts from Roselle should be applied differently for cosmetics and pharmaceutical purposes. Our findings demonstrate the potential of Roselle extracts as a natural source for skincare products.

Synaptic boutons are smaller in chandelier cell cartridges in autism

Chandelier (Ch) cells are cortical interneurons with axon terminal structures known as cartridges that synapse on the axon initial segment of excitatory pyramidal neurons. Previous studies indicate that the number of Ch cells is decreased in autism, and that GABA receptors are decreased in the Ch cell synaptic target in the prefrontal cortex. To further identify Ch cell alterations, we examined whether the length of cartridges, and the number, density, and size of Ch cell synaptic boutons, differed in the prefrontal cortex of cases with autism versus control cases. We collected samples of postmortem human prefrontal cortex (Brodmann Area (BA) 9, 46, and 47) from 20 cases with autism and 20 age- and sex-matched control cases. Ch cells were labeled using an antibody against parvalbumin, a marker that labeles soma, cartridges, and synaptic boutons. We found no significant difference in the average length of cartridges, or in the total number or density of boutons in control subjects vs. subjects with autism. However, we found a significant decrease in the size of Ch cell boutons in those with autism. The reduced size of Ch cell boutons may result in reduced inhibitory signal transmission and impact the balance of excitation to inhibition in the prefrontal cortex in autism.

Molecular mechanisms of AMPAR reversible stabilization at synapses

In the central nervous system, glutamatergic synapses play a central role in the regulation of excitatory neuronal transmission. With the membrane-associated guanylate kinase (MAGUK) family of proteins as their structuring scaffold, glutamatergic receptors serve as the powerhouse of glutamatergic synapses. Glutamatergic receptors can be categorized as metabotropic and ionotropic receptors. The latter are then categorized into N-methyl-d-aspartate, kainate receptors, and α-amino-3-hydroxy-5-methyl-isoxazole-propionic acid receptors (AMPARs). Over the past two decades, genetic tagging technology and super-resolution microscopy have been of the utmost importance to unravel how the different receptors are organized at glutamatergic synapses. At the plasma membrane, receptors are highly mobile but show reduced mobility when at synaptic sites. This partial immobilization of receptors at synaptic sites is attributed to the stabilization/anchoring of receptors with the postsynaptic MAGUK proteins and auxiliary proteins, and presynaptic proteins. These partial immobilizations and localization of glutamatergic receptors within the synaptic sites are fundamental for proper basal transmission and synaptic plasticity. Perturbations of the stabilization of glutamatergic receptors are often associated with cognitive deficits. In this review, we describe the proposed mechanisms for synaptic localization and stabilization of AMPARs, the major players of fast excitatory transmission in the central nervous system.

Computational insights into mRNA and protein dynamics underlying synaptic plasticity rules

Recent advances in experimental techniques provide an unprecedented peek into the intricate molecular dynamics inside synapses and dendrites. The experimental insights into the molecular turnover revealed that such processes as diffusion, active transport, spine uptake, and local protein synthesis could dynamically modulate the copy numbers of plasticity-related molecules in synapses. Subsequently, theoretical models were designed to understand the interaction of these processes better and to explain how local synaptic plasticity cues can up or down-regulate the molecular copy numbers across synapses. In this review, we discuss the recent advances in experimental techniques and computational models to highlight how these complementary approaches can provide insight into molecular cross-talk across synapses, ultimately allowing us to develop biologically-inspired neural network models to understand brain function.

Presynaptic Plasticity Is Associated with Actin Polymerization

Modulation of presynaptic short-term plasticity induced by actin polymerization was studied in rat hippocampal slices using the paired-pulse paradigm. Schaffer collaterals were stimulated with paired pulses with a 70-ms interstimulus interval every 30 s before and during perfusion with jasplakinolide, an activator of actin polymerization. Jasplakinolide application resulted in the increase in the amplitudes of CA3-CA1 responses (potentiation) accompanied by a decrease in the paired-pulse facilitation, suggesting induction of presynaptic modifications. Jasplakinolide-induced potentiation depended on the initial paired-pulse rate. These data indicate that the jasplakinolide-mediated changes in actin polymerization increased the probability of neurotransmitter release. Less typical for CA3-CA1 synapses responses, such as a very low paired-pulse ratio (close to 1 or even lower) or even paired-pulse depression, were affected differently. Thus, jasplakinolide caused potentiation of the second, but not the first response to the paired stimulus, which increased the paired-pulse ratio from 0.8 to 1.0 on average, suggesting a negative impact of jasplakinolide on the mechanisms promoting paired-pulse depression. In general, actin polymerization facilitated potentiation, although the patterns of potentiation differed depending on the initial synapse characteristics. We conclude that in addition to the increase in the neurotransmitter release probability, jasplakinolide induced other actin polymerization-dependent mechanisms, including those involved in the paired-pulse depression.

Recent progress in three-terminal artificial synapses based on 2D materials: from mechanisms to applications

Synapses are essential for the transmission of neural signals. Synaptic plasticity allows for changes in synaptic strength, enabling the brain to learn from experience. With the rapid development of neuromorphic electronics, tremendous efforts have been devoted to designing and fabricating electronic devices that can mimic synapse operating modes. This growing interest in the field will provide unprecedented opportunities for new hardware architectures for artificial intelligence. In this review, we focus on research of three-terminal artificial synapses based on two-dimensional (2D) materials regulated by electrical, optical and mechanical stimulation. In addition, we systematically summarize artificial synapse applications in various sensory systems, including bioplastic bionics, logical transformation, associative learning, image recognition, and multimodal pattern recognition. Finally, the current challenges and future perspectives involving integration, power consumption and functionality are outlined.

Lateral Diffusion of NKCC1 Contributes to Chloride Homeostasis in Neurons and Is Rapidly Regulated by the WNK Signaling Pathway

An upregulation of the Na⁺-K⁺-2Cl^- cotransporter NKCC1, the main chloride importer in mature neurons, can lead to depolarizing/excitatory responses mediated by GABA type A receptors (GABA_ARs) and, thus, to hyperactivity. Understanding the regulatory mechanisms of NKCC1 would help prevent intra-neuronal chloride accumulation that occurs in pathologies with defective inhibition. The cell mechanisms regulating NKCC1 are poorly understood. Here, we report in mature hippocampal neurons that GABAergic activity controls the membrane diffusion and clustering of NKCC1 via the chloride-sensitive WNK lysine deficient protein kinase 1 (WNK1) and the downstream Ste20 Pro-line Asparagine Rich Kinase (SPAK) kinase that directly phosphorylates NKCC1 on key threonine residues. At rest, this signaling pathway has little effect on intracellular Cl^- concentration, but it participates in the elevation of intraneuronal Cl^- concentration in hyperactivity conditions associated with an up-regulation of NKCC1. The fact that the main chloride exporter, the K⁺-Cl^- cotransporter KCC2, is also regulated in mature neurons by the WNK1 pathway indicates that this pathway will be a target of choice in the pathology.

mGluR5 is transiently confined in perisynaptic nanodomains to shape synaptic function

The unique perisynaptic distribution of postsynaptic metabotropic glutamate receptors (mGluRs) at excitatory synapses is predicted to directly shape synaptic function, but mechanistic insight into how this distribution is regulated and impacts synaptic signaling is lacking. We used live-cell and super-resolution imaging approaches, and developed molecular tools to resolve and acutely manipulate the dynamic nanoscale distribution of mGluR5. Here we show that mGluR5 is dynamically organized in perisynaptic nanodomains that localize close to, but not in the synapse. The C-terminal domain of mGluR5 critically controlled perisynaptic confinement and prevented synaptic entry. We developed an inducible interaction system to overcome synaptic exclusion of mGluR5 and investigate the impact on synaptic function. We found that mGluR5 recruitment to the synapse acutely increased synaptic calcium responses. Altogether, we propose that transient confinement of mGluR5 in perisynaptic nanodomains allows flexible modulation of synaptic function.

Trafficking proteins show limited differences in mobility across different postsynaptic spines

The function of the postsynaptic compartment is based on the presence and activity of postsynaptic receptors, whose dynamics are controlled by numerous scaffolding, signaling and trafficking proteins. Although the receptors and the scaffolding proteins have received substantial attention, the trafficking proteins have not been investigated extensively. Their mobility rates are unknown, and it is unclear how the postsynaptic environment affects their dynamics. To address this, we analyzed several trafficking proteins (α-synuclein, amphiphysin, calmodulin, doc2a, dynamin, and endophilin), estimating their movement rates in the dendritic shaft, as well as in morphologically distinct "mushroom" and "stubby" postsynapse types. The diffusion parameters were surprisingly similar across dendritic compartments, and a few differences between proteins became evident only in the presence of a synapse neck. We conclude that the movement of trafficking proteins is not strongly affected by the postsynaptic compartment, in stark contrast to the presynapse, which regulates strongly the movement of such proteins.

Filamin A organizes γ‑aminobutyric acid type B receptors at the plasma membrane

The γ-aminobutyric acid type B (GABA_B) receptor is a prototypical family C G protein-coupled receptor (GPCR) that plays a key role in the regulation of synaptic transmission. Although growing evidence suggests that GPCR signaling in neurons might be highly organized in time and space, limited information is available about the mechanisms controlling the nanoscale organization of GABA_B receptors and other GPCRs on the neuronal plasma membrane. Using a combination of biochemical assays in vitro, single-particle tracking, and super-resolution microscopy, we provide evidence that the spatial organization and diffusion of GABA_B receptors on the plasma membrane are governed by dynamic interactions with filamin A, which tethers the receptors to sub-cortical actin filaments. We further show that GABA_B receptors are located together with filamin A in small nanodomains in hippocampal neurons. These interactions are mediated by the first intracellular loop of the GABA_B1 subunit and modulate the kinetics of Gα_i protein activation in response to GABA stimulation.

High- and Super-Resolution Imaging of Cell-Cell Interfaces

Physical interfaces mediate interactions between multiple types of cells. Despite the importance of such interfaces to the cells' function, their high-resolution optical imaging has been typically limited due to poor alignment of the interfaces relative to the optical plane of imaging. Here, we present a simple and robust method to align cell-cell interfaces in parallel to the coverslip by adhering the interacting cells to two opposing coverslips and bringing them into contact in a controlled and stable fashion. We demonstrate aberration-free high-resolution imaging of interfaces between live T cells and antigen-presenting cells, known as immune synapses, as an outstanding example. Imaging methods may include multiple diffraction-limited and super-resolution microscopy techniques (e.g., bright-field, confocal, STED, and dSTORM). Thus, our simple and widely compatible approach allows imaging with high- and super-resolution the intricate structure and molecular organization within a variety of cell-cell interfaces.

Mapping the Nicotinic Acetylcholine Receptor Nanocluster Topography at the Cell Membrane with STED and STORM Nanoscopies

The cell-surface topography and density of nicotinic acetylcholine receptors (nAChRs) play a key functional role in the synapse. Here we employ in parallel two labeling and two super-resolution microscopy strategies to characterize the distribution of this receptor at the plasma membrane of the mammalian clonal cell line CHO-K1/A5. Cells were interrogated with two targeted techniques (confocal microscopy and stimulated emission depletion (STED) nanoscopy) and single-molecule nanoscopy (stochastic optical reconstruction microscopy, STORM) using the same fluorophore, Alexa Fluor 647, tagged onto either α-bungarotoxin (BTX) or the monoclonal antibody mAb35. Analysis of the topography of nanometer-sized aggregates (“nanoclusters”) was carried out using STORMGraph, a quantitative clustering analysis for single-molecule localization microscopy based on graph theory and community detection, and ASTRICS, an inter-cluster similarity algorithm based on computational geometry. Antibody-induced crosslinking of receptors resulted in nanoclusters with a larger number of receptor molecules and higher densities than those observed in BTX-labeled samples. STORM and STED provided complementary information, STED rendering a direct map of the mesoscale nAChR distribution at distances ~10-times larger than the nanocluster centroid distances measured in STORM samples. By applying photon threshold filtering analysis, we show that it is also possible to detect the mesoscale organization in STORM images.

Flexible Artificial Optoelectronic Synapse based on Lead-Free Metal Halide Nanocrystals for Neuromorphic Computing and Color Recognition

Optoelectronic synapses combining optical-sensing and synaptic functions are playing an increasingly vital role in the neuromorphic computing systems development, which can efficiently process visual information and complex recognition, memory, and learning. Metal halides are considered promising candidates for synaptic devices due to their excellent optoelectronic properties. However, the toxicity of lead and the further development of device functions are the recognized problems at present. Herein, a flexible optoelectronic synapses system based on high-quality lead-free Cs3 Bi2 I9 nanocrystals is demonstrated, in which the carrier confinement caused by the band mismatching between the Cs3 Bi2 I9 and the organic semiconductor layer provides the possibility to simulate synaptic behaviors. The synaptic functions including long/short-term memory and learning-forgetting-relearning are demonstrated in this device and visual perception, visual memory, and color recognition functions are successfully implemented. Additionally, the flexible device exhibits excellent robustness and can realize imaging of light distribution under curved hemispheres similar to the human eye. Finally, through the simulation based on an artificial neural network algorithm, the device successfully realizes the high-precision recognition of handwritten digital images and possesses a strong fault tolerant capability even in bending states. These results are expected to drive the practical progress of metal halide for neuromorphic computing.

High-resolution imaging and manipulation of endogenous AMPA receptor surface mobility during synaptic plasticity and learning

Regulation of synaptic neurotransmitter receptor content is a fundamental mechanism for tuning synaptic efficacy during experience-dependent plasticity and behavioral adaptation. However, experimental approaches to track and modify receptor movements in integrated experimental systems are limited. Exploiting AMPA-type glutamate receptors (AMPARs) as a model, we generated a knock-in mouse expressing the biotin acceptor peptide (AP) tag on the GluA2 extracellular N-terminal. Cell-specific introduction of biotin ligase allows the use of monovalent or tetravalent avidin variants to respectively monitor or manipulate the surface mobility of endogenous AMPAR containing biotinylated AP-GluA2 in neuronal subsets. AMPAR immobilization precluded the expression of long-term potentiation and formation of contextual fear memory, allowing target-specific control of the expression of synaptic plasticity and animal behavior. The AP tag knock-in model offers unprecedented access to resolve and control the spatiotemporal dynamics of endogenous receptors, and opens new avenues to study the molecular mechanisms of synaptic plasticity and learning.

Visualizing synaptic dopamine efflux with a 2D composite nanofilm

Chemical neurotransmission constitutes one of the fundamental modalities of communication between neurons. Monitoring release of these chemicals has traditionally been difficult to carry out at spatial and temporal scales relevant to neuron function. To understand chemical neurotransmission more fully, we need to improve the spatial and temporal resolutions of measurements for neurotransmitter release. To address this, we engineered a chemi-sensitive, two-dimensional composite nanofilm that facilitates visualization of the release and diffusion of the neurochemical dopamine with synaptic resolution, quantal sensitivity, and simultaneously from hundreds of release sites. Using this technology, we were able to monitor the spatiotemporal dynamics of dopamine release in dendritic processes, a poorly understood phenomenon. We found that dopamine release is broadcast from a subset of dendritic processes as hotspots that have a mean spatial spread of ≈ 3.2 µm (full width at half maximum [FWHM]) and are observed with a mean spatial frequency of one hotspot per ≈ 7.5 µm of dendritic length. Major dendrites of dopamine neurons and fine dendritic processes, as well as dendritic arbors and dendrites with no apparent varicose morphology participated in dopamine release. Remarkably, these release hotspots co-localized with Bassoon, suggesting that Bassoon may contribute to organizing active zones in dendrites, similar to its role in axon terminals.

To form the vast and complex network necessary for an organism to sense and react to the world, neurons must connect at highly specialized junctions. Individual cells communicate at these ‘synapses’ by releasing chemical signals (or neurotransmitters) such as dopamine, a molecule involved in learning and motivation.

Despite the central role that synapses play in the brain, it remains challenging to measure exactly where neurotransmitters are released and how far they travel from their release site. Currently, most tools available to scientists only allow bulk measurements of neurotransmitter release.

To tackle this limitation, Bulumulla et al. developed a new way to measure neurotransmitter release from neurons, harnessing a technique which uses fluorescent nanosensors that glow brighter when exposed to dopamine. These sensors form a very thin film upon which neurons can grow; when the cells release dopamine, the sensors ‘light up’ as they encounter the molecule. Dubbed DopaFilm, the technology reveals exactly where the neurotransmitter comes from and how it spreads between cells in real time. In particular, the approach showed that dopamine emerges from 'hot spots' at specific sites in cells; it also helped Bulumulla et al. study how dopamine is released from subcellular compartments that have previously not been well characterized.

Improving the sensors so that the film could detect other neurotransmitters besides dopamine would broaden the use of this approach. In the future, combining this technology with other types of imaging should enable studies of individual synapses with intricate detail.

Complex regulation of Gephyrin splicing is a determinant of inhibitory postsynaptic diversity

Gephyrin (GPHN) regulates the clustering of postsynaptic components at inhibitory synapses and is involved in pathophysiology of neuropsychiatric disorders. Here, we uncover an extensive diversity of GPHN transcripts that are tightly controlled by splicing during mouse and human brain development. Proteomic analysis reveals at least a hundred isoforms of GPHN incorporated at inhibitory Glycine and gamma-aminobutyric acid A receptors containing synapses. They exhibit different localization and postsynaptic clustering properties, and altering the expression level of one isoform is sufficient to affect the number, size, and density of inhibitory synapses in cerebellar Purkinje cells. Furthermore, we discovered that splicing defects reported in neuropsychiatric disorders are carried by multiple alternative GPHN transcripts, demonstrating the need for a thorough analysis of the GPHN transcriptome in patients. Overall, we show that alternative splicing of GPHN is an important genetic variation to consider in neurological diseases and a determinant of the diversity of postsynaptic inhibitory synapses.

The protein gephyrin is involved in organizing synapses. Here, the authors show how different transcripts of gephyrin form and regulate inhibitory synapses.

Local accumulation times in a diffusion-trapping model of receptor dynamics at proximal axodendritic synapses

The lateral diffusion and trapping of neurotransmitter receptors within the postsynaptic membrane of a neuron play a key role in determining synaptic strength and plasticity. Trapping is mediated by the reversible binding of receptors to scaffolding proteins (slots) within a synapse. In this paper we introduce a method for analyzing the transient dynamics of proximal axodendritic synapses in a diffusion-trapping model of receptor trafficking. Given a population of spatially distributed synapses, each of which has a fixed number of slots, we calculate the rate of relaxation to the steady-state distribution of bound slots (synaptic weights) in terms of a set of local accumulation times. Assuming that the rates of exocytosis and endocytosis are sufficiently slow, we show that the steady-state synaptic weights are independent of each other (purely local). On the other hand, the local accumulation time of a given synapse depends on the number of slots and the spatial location of all the synapses, indicating a form of transient heterosynaptic plasticity. This suggests that local accumulation time measurements could provide useful information regarding the distribution of synaptic weights within a dendrite.

Improvement of synaptic plasticity by nanoparticles and the related mechanisms: Applications and prospects

Synaptic plasticity is an important basis of learning and memory and participates in brain network remodelling after different types of brain injury (such as that caused by neurodegenerative diseases, cerebral ischaemic injury, posttraumatic stress disorder (PTSD), and psychiatric disorders). Therefore, improving synaptic plasticity is particularly important for the treatment of nervous system-related diseases. With the rapid development of nanotechnology, increasing evidence has shown that nanoparticles (NPs) can cross the blood-brain barrier (BBB) in different ways, directly or indirectly act on nerve cells, regulate synaptic plasticity, and ultimately improve nerve function. Therefore, to better elucidate the effect of NPs on synaptic plasticity, we review evidence showing that NPs can improve synaptic plasticity by regulating different influencing factors, such as neurotransmitters, receptors, presynaptic membrane proteins and postsynaptic membrane proteins, and further discuss the possible mechanism by which NPs improve synaptic plasticity. We conclude that NPs can improve synaptic plasticity and restore the function of damaged nerves by inhibiting neuroinflammation and oxidative stress, inducing autophagy, and regulating ion channels on the cell membrane. By reviewing the mechanism by which NPs regulate synaptic plasticity and the applications of NPs for the treatment of neurological diseases, we also propose directions for future research in this field and provide an important reference for follow-up research.

Autoregulation of switching behavior by cellular compartment size

Biochemical reactions often occur in small volumes within a cell, restricting the number of molecules to the hundreds or even tens. At this scale, reactions are discrete and stochastic, making reliable signaling difficult. This paper shows that the transition between discrete, stochastic reactions and macroscopic reactions can be exploited to make a self-regulating switch. This constitutes a previously unidentified kind of reaction network that may be present in small structures, such as synapses.

Many kinds of cellular compartments comprise decision-making mechanisms that control growth and shrinkage of the compartment in response to external signals. Key examples include synaptic plasticity mechanisms that regulate the size and strength of synapses in the nervous system. However, when synaptic compartments and postsynaptic densities are small, such mechanisms operate in a regime where chemical reactions are discrete and stochastic due to low copy numbers of the species involved. In this regime, fluctuations are large relative to mean concentrations, and inherent discreteness leads to breakdown of mass-action kinetics. Understanding how synapses and other small compartments achieve reliable switching in the low–copy number limit thus remains a key open problem. We propose a self-regulating signaling motif that exploits the breakdown of mass-action kinetics to generate a reliable size-regulated switch. We demonstrate this in simple two- and three-species chemical reaction systems and uncover a key role for inhibitory loops among species in generating switching behavior. This provides an elementary motif that could allow size-dependent regulation in more complex reaction pathways and may explain discrepant experimental results on well-studied biochemical pathways.

Decreased Reactive Oxygen Species Signaling Alters Glutamate Receptor Transport to Synapses in C. elegans AVA Neurons

Reactive oxygen species (ROS) are chemically reactive molecules normally produced during cellular respiration. High ROS levels negatively impact forms of synaptic plasticity that rely on changes in the number of ionotropic glutamate receptors (iGluRs) at synapses. More recently, we have shown that physiological increases in ROS reduce iGluR transport to synapses by acting on activity-dependent calcium signaling. Here, we show that decreasing mitochondria-derived ROS decrease iGluR transport albeit in a calcium-independent manner. These data demonstrate differential regulatory mechanisms by elevated or diminished ROS levels which further support a physiological signaling role for ROS in regulating iGluR transport to synapses.

The needs of a synapse—How local organelles serve synaptic proteostasis

Synaptic function crucially relies on the constant supply and removal of neuronal membranes. The morphological complexity of neurons poses a significant challenge for neuronal protein transport since the machineries for protein synthesis and degradation are mainly localized in the cell soma. In response to this unique challenge, local micro‐secretory systems have evolved that are adapted to the requirements of neuronal membrane protein proteostasis. However, our knowledge of how neuronal proteins are synthesized, trafficked to membranes, and eventually replaced and degraded remains scarce. Here, we review recent insights into membrane trafficking at synaptic sites and into the contribution of local organelles and micro‐secretory pathways to synaptic function. We describe the role of endoplasmic reticulum specializations in neurons, Golgi‐related organelles, and protein complexes like retromer in the synthesis and trafficking of synaptic transmembrane proteins. We discuss the contribution of autophagy and of proteasome‐mediated and endo‐lysosomal degradation to presynaptic proteostasis and synaptic function, as well as nondegradative roles of autophagosomes and lysosomes in signaling and synapse remodeling. We conclude that the complexity of neuronal cyto‐architecture necessitates long‐distance protein transport that combines degradation with signaling functions.