Search Results (718)

Spin–orbit torque (SOT)-based spintronic devices have emerged as a preferred candidate for next-generation artificial synaptic devices due to their advantages of non-volatility, high speed, and low power consumption. The development of high-performance SOT-based artificial synaptic devices relies on the breakthrough in SOT-driven magnetization switching, wherein the performance regulation and structural design of the magnetic layer are the core critical factors. In this work, the Co/Ho multilayer system is employed as the magnetic layer to investigate its SOT-driven magnetization switching characteristics and application potential in artificial synapses. By regulating the periodic parameters of the Co/Ho multilayer structure, high perpendicular magnetic anisotropy (PMA) can be stably maintained in devices with relatively thick ferrimagnetic layers. Moreover, we elucidate the role of the antiferromagnetic coupling interface between Co and Ho in the multilayer structure in enhancing SOT efficiency and demonstrate the achievement of a high spin Hall angle of up to 0.22. The high SOT efficiency of the system enables it to drive the 8.4 nm-thick magnetic layer to achieve highly stable magnetization switching. Multistate magnetization switching behavior is observed, which can be used to simulate synaptic weight updates in neuromorphic networks, demonstrating the broad application prospects of this system in the field of artificial neural networks. Full article

All-optical memristors possess light-sensing and storage capabilities while simultaneously simulating human synaptic functions, demonstrating immense potential in the field of brain-inspired computing for realizing bionic synapses and brain-like intelligence. In this work, we successfully produced ε-Ga₂O₃ films, ε/β-Ga₂O₃ mixed-phase films, and β-Ga₂O₃ films via chemical vapor deposition (CVD). The optical output and optical response characteristics of the thin films are investigated under 254 nm and 365 nm lasers. The CVD-grown ε-Ga₂O₃ is found to process a small amount of defects and insignificant memristive properties and the β-Ga₂O₃ obtained from the annealing of ε-Ga₂O₃ exhibits superior crystal quality but lacks memristive properties, while the ε/β-Ga₂O₃ mixed-phase films grown directly by CVD contain a fair amount of defects and demonstrate persistent resistance retention exceeding 104 s. Based on the excellent memristive properties of ε/β-Ga₂O₃ mixed-phase films, we conducted experiments simulating optical synapses. By adjusting optical pulse parameters (intensity, repetition rate, and duration), we successfully modeled the short-term plasticity (STP) and long-term plasticity (LTP) observed in biological synapses. Experiments confirm that light stimulation can effectively induce synaptic behaviors, such as the progressive conversion of short-term memory (STM) into long-term memory (LTM), and further fully reproduce the neuroplasticity process of “learning-forgetting-relearning.” This study demonstrates a photoconductive synapse memristor based on the wide-bandgap material gallium oxide, exhibiting exceptional air stability with sustained photoconductivity maintained for over a year. This study provides new insights into the practical application feasibility of all-optical artificial synapses based on gallium oxide. Full article

Thymosin β4 (Tβ4) is a highly acidic, intrinsically disordered 43-amino-acid peptide with diverse biological functions, yet its interactions with metal ions remain poorly understood. In this study, we provide the first experimental demonstration that Tβ4 forms discrete Zn²⁺-bound adducts and undergoes Zn²⁺-induced aggregation under physiological pH conditions. Combining zeta potential analysis, dynamic light scattering (DLS), electrospray ionization mass spectrometry (ESI-MS), nuclear magnetic resonance (NMR) spectroscopy, and scanning electron microscopy with elemental mapping (SEM/EDS), we show that Zn(II) binding progressively neutralizes Tβ4’s negative surface charge and triggers a sharp aggregation transition. ESI-MS unambiguously identifies Tβ4/Zn(II) complexes of peptide-to-zinc molar ratio 1:3, while DLS and SEM reveal the formation of compact, low-solubility supramolecular assemblies. NMR measurements support a metal-induced aggregation, confirming the absence of folding upon Zn(II) binding. By quantitatively comparing the experimentally determined critical aggregation concentration with physiologically observed extracellular Zn(II) ranges, we demonstrate that aggregation is unlikely in plasma or basal interstitial environments but may become feasible in Zn-rich microdomains, such as the synaptic cleft, where transient Zn(II) levels can exceed 1 μM. These findings introduce a previously unrecognized dimension of Tβ4 chemistry and suggest that a Zn(II)-mediated supramolecular assembly of Tβ4 could influence peptide behavior in neurological or inflammatory conditions characterized by elevated extracellular Zn(II). This work establishes a foundational biochemical framework for future studies aimed at elucidating the biological implications of Tβ4/Zn(II) complexation and aggregation in vivo. Full article

The efficacy of stigmasterol (STG) has not been previously evaluated in post-traumatic stress disorder (PTSD) models. Mice exposed to single prolonged stress with foot shock (SPS + FS) received oral STG (25 or 50 mg/kg) for 14 days. Serum corticosterone and serotonin levels were measured, anxiety and cognition were assessed, synaptic plasticity-related proteins and genes were quantified, and neuronal nitric oxide synthase (nNOS), nitric oxide (NO) accumulation, nNOS-postsynaptic density protein 95 (PSD95), and nNOS-carboxy-terminal PDZ ligand of nNOS (CAPON) interactions were evaluated. STG significantly reduced serum corticosterone levels and increased serotonin levels altered by SPS+FS exposure. Behavioral analyses revealed attenuation of anxiety-like behavior and cognitive deficits. STG increased hippocampal synaptic plasticity-related proteins and genes and increased the number and maturation of doublecortin⁺ cells. Additionally, STG suppressed the PTSD-induced nNOS overactivation and NO accumulation in the hippocampus and serum, and altered nNOS-PSD95 and nNOS-CAPON associations in the hippocampus. Together, these findings provide integrated in vivo evidence suggesting that STG may influence stress-related neurobiological pathways relevant to PTSD. Full article

The endocannabinoid system is a ubiquitous neuromodulatory network that links internal physiological state to neural circuit function across the brain. While its roles in memory, reward, pain, and motor control are well established, its contribution to olfactory processing has only recently gained attention. This review synthesizes the current knowledge on the anatomical, cellular, and functional interactions between the endocannabinoid system and the olfactory pathway, from the olfactory epithelium and main olfactory bulb to higher order cortical targets. We highlight how endocannabinoid signaling, primarily via cannabinoid receptor type 1 (CB1), shapes synaptic transmission within olfactory bulb microcircuits, modulates centrifugal feedback, and adjusts sensory gain in a state-dependent manner, particularly in relation to hunger, feeding behavior, stress, and reward. In addition, we review evidence that the endocannabinoid system regulates olfactory neurodevelopment and adult neurogenesis by influencing neural stem cell proliferation, migration, and integration into existing circuits. Emerging links between endocannabinoid signaling, olfactory dysfunction, neuropsychiatric disease, metabolic disorders, and neurodegeneration underscore the translational relevance of this system. We also discuss methodological challenges inherent to studying endocannabinoid signaling and outline future directions, including circuit-specific targeting and intranasal delivery strategies. Together, these findings position the olfactory system as a powerful and accessible model for understanding how endocannabinoids couple internal state to perception and behavior, with important implications for therapeutic development. Full article

Optical synaptic transistors employing polymer dielectrics have emerged as promising building blocks for neuromorphic computing due to their low power consumption and rich photo-induced memory behaviors. While extensive experimental studies have demonstrated various synaptic functions, a unified physical understanding of the coupled charge trapping and ionic polarization processes governing device dynamics remains incomplete. In this work, we develop a unified physical model to investigate optical synaptic behaviors in polymer-based transistors with oxide interlayers. The model explicitly describes the time-dependent evolution of photo-induced charge trapping at the semiconductor–dielectric interface and ionic polarization within the polymer dielectric, which jointly modulate the effective threshold voltage of the transistor channel. Based on this framework, key synaptic functions including excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and pulse-dependent potentiation are quantitatively reproduced. The model further reveals how dielectric structure and trapping strength govern the transition between short-term and long-term plasticity. This study provides a physically intuitive and experimentally relevant modeling framework for understanding optical synaptic transistors, offering guidance for the rational design and optimization of polymer-based neuromorphic devices. Although simplified, the proposed model captures the essential physics governing optical synaptic behaviors and provides a general framework applicable to a wide class of ion–electronic neuromorphic devices. Experimental measurements are used as physically motivated proxies to validate the multi-timescale structure of the model rather than direct numerical fitting. Full article

Background/Objectives: Tributyltin (TBT) remains a persistent aquatic contaminant with documented neurotoxic effects, yet the underlying mechanisms of its neurotoxicity remain poorly understood. Methods: We investigated the comprehensive molecular mechanisms of TBT-induced neurotoxicity in zebrafish (Danio rerio) through an integrated approach combining histopathological examination, metabolomics analysis, transcriptional profiling, and behavioral assays. Results: Histopathological analysis revealed significant TBT-induced damage to brain tissue architecture. Metabolomic profiling demonstrated that TBT exposure (500 ng/L) severely disrupted cellular energy metabolism, particularly the TCA cycle and purine/pyrimidine metabolism, while exhibiting hormetic responses at lower concentrations. Transcriptional analysis identified widespread downregulation of SNARE complex proteins and neurotransmitter transporters, indicating comprehensive deterioration of synaptic machinery. Conclusions: These molecular perturbations corresponded with systematic disruption of antioxidant defense mechanisms and neurotransmitter signaling pathways, establishing a direct mechanistic link to observed behavioral deficits. Our findings reveal a hierarchical cascade of molecular disruptions triggered by TBT exposure, bridging the critical gap between metabolic dysregulation and synaptic dysfunction. This mechanistic framework provides fundamental insights into the neurotoxicological impact of this widespread environmental contaminant, highlighting potential therapeutic targets for intervention. Full article

Background: Alzheimer’s disease (AD) is a multifactorial neurodegenerative disorder and the leading cause of dementia worldwide. Progressive synaptic dysfunction underlies declines in cognition, daily functioning, and the development of neuropsychiatric syndromes. Neuropsychiatric syndromes that include agitation and aggression affect 40–60% of patients and represent a major source of caregiver burden. Serotonin 5-HT_2B receptor levels are increased in the AD patient brain, and thus, treatment of AD animal models with the selective 5-HT_2B receptor antagonist MW073 in prevention or disease stage paradigms attenuates Aβ- or tau-induced dysfunction. Methods: We investigated the effects of MW073 treatment on the aggressive behavior of Tg2576 mice in a resident–intruder assay. Results: MW073 treatment significantly reduced aggressive behavior in male Tg2576 mice. Conclusions: MW073 efficacy in treating aggression in Tg2576 mice implicates 5-HT_2B receptor-mediated signaling in AD neuropsychiatric symptoms as well as cognitive and behavioral dysfunction. Full article

Dopamine (DA) is a critical catecholaminergic neurotransmitter that facilitates signal transduction across synaptic junctions and modulates essential neurophysiological processes, including motor coordination, motivational drive, and reward-motivated behaviors. The fabrication of cost-effective, miniaturized, and high-fidelity analytical platforms is imperative for real-time DA monitoring. Due to its inherent electrochemical activity, carbon-based amperometric sensors constitute the primary modality for DA quantification. In this study, graphite, multi-walled carbon nanotubes (MWCNTs), and graphene were immobilized within an ethyl 2-cyanoacrylate (ECA) polymer matrix. ECA was selected for its rapid polymerization kinetics and established biocompatibility in electrochemical frameworks. All fabricated composites demonstrated robust electrocatalytic activity toward DA; however, MWCNT- and graphene-based sensors exhibited superior analytical performance, characterized by highly competitive limits of detection (LOD) and quantification (LOQ). Specifically, MWCNT-modified electrodes achieved an interesting LOD of 0.030 ± 0.001 µM and an LOQ of 0.101 ± 0.008 µM. Discrepancies in baseline current amplitudes suggest that the spatial orientation of carbonaceous nanomaterials within the cyanoacrylate matrix significantly influences the electrochemical surface area and resulting baseline characteristics. The impact of interfering species commonly found in biological environments on the sensors’ response was systematically evaluated. The best-performing sensor, the graphene-based one, was used to measure the DA intracellular content of PC12 cells. Full article

Major depressive disorder (MDD) is a leading cause of global morbidity and mortality. Although pharmacological treatments are widely used, their effects are often limited, and nearly half of patients show resistance to current antidepressants, including those unresponsive to all available therapies. These challenges highlight the need to better understand the neurobiological mechanisms driving MDD and to develop novel therapeutic strategies, especially those involving natural compounds with multitarget actions. Baicalin, a bioactive flavonoid from Scutellaria baicalensis, exhibits antioxidant, anti-inflammatory, and neuroprotective properties and has recently gained attention for its potential to improve cognitive deficits and mood disorders. In this study, we investigated baicalin’s antidepressant potential and its underlying mechanisms across multiple experimental levels. We found that oral administration of baicalin produced antidepressant-like effects in both naïve mice and those subjected to chronic restraint stress (CRS). CRS impaired hippocampal long-term potentiation (LTP), whereas baicalin restored these synaptic deficits. Importantly, intra-dorsal hippocampal microinjection of the TrkB receptor antagonist ANA-12 abolished baicalin’s antidepressant effects, indicating the involvement of BDNF–TrkB signaling. Baicalin also reduced reactive oxygen species (ROS)/H₂O₂ production in a BDNF-associated manner, demonstrating clear antioxidant activity. Molecular docking further suggested that baicalin binds more effectively to the TrkB receptor than ANA-12, supporting its capacity to activate TrkB-mediated signaling. By integrating in vivo, ex vivo, in vitro, and in silico approaches, our study shows that baicalin exerts robust antioxidant in vitro and antidepressant effects in vivo. These benefits are primarily mediated through activation of BDNF–TrkB signaling, leading to reduced ROS/H₂O₂ accumulation and alleviation of CRS-induced depression-like behaviors. Full article

Emerging research indicates that neuronal activity is maintained by an architectural system of protons in a multi-scale fashion. Proton architecture is formed when organelles (such as mitochondria, endoplasmic reticulum, lysosomes, synaptic vesicles, etc.) are coupled together to produce dynamic energy domains. Techniques have been developed to visualize protons in neurons; recent advances include near-atomic structural imaging of organelle interfaces using cryo-tomography and nanoscale resolution imaging of organelle interfaces and proton tracking using ultra-fast spectroscopy. Results of these studies indicate that protons in neurons do not diffuse randomly throughout the neuron but instead exist in organized geometric configurations. The cristae of mitochondrial cells create oscillating proton micro-domains that are influenced by the curvature of the cristae, hydrogen bonding between molecules, and localized changes in dielectric properties that result in time-patterned proton signals that can be used to determine the metabolic load of the cell and the redox state of its mitochondria. These proton patterns also communicate to the rest of the cell via hydrated aligned proton-conductive pathways at the mitochon-dria-endoplasmic reticulum junctions, through acidic lipid regions, and through nano-tethered contact sites between mitochondria and other organelles, which are typically spaced approximately 10–25 nm apart. Other proton architectures exist in lysosomes, endosomes, and synaptic vesicles. In each of these organelles, the V-ATPase generates steep concentration gradients across their membranes, controlling the rate of cargo removal from the lumen of the organelle, recycling receptors from the surface of the membrane, and loading neurotransmitters into the vesicles. Recent super-resolution pH mapping has indicated that populations of synaptic vesicles contain significant heterogeneity in the amount of protons they contain, thereby influencing the amount of neurotransmitter released per vesicle, the probability of vesicle release, and the degree of post-synaptic receptor protonation. Additionally, proton gradients in each organelle interact with the cytoskeleton: the protonation status of actin and microtubules influences filament stiffness, protein–protein interactions, and organelle movement, resulting in the formation of localized spatial structures that may possess some type of computational significance. At multiple scales, it appears that neurons integrate the proton micro-domains with mechanical tension fields, dielectric nanodomains, and phase-state transitions to form distributed computing elements whose behavior is determined by the integration of energy flow, organelle geometry, and the organization of soft materials. Alterations to the proton landscape in neurons (e.g., due to alterations in cristae structure, drift in luminal pH, disruption in the hydration-structure of the cell, or imbalance in the protonation of cytoskeletal components) could disrupt the intracellular signaling network well before the onset of measurable electrical or biochemical pathologies. This article will summarize evidence indicating that proton–organelle interaction provides a previously unknown source of energetic substrate for neural computation. Using an integrated approach combining nanoscale proton energy, organelle interface geometry, cytoskeletal mechanics, and AI-based multiscale models, this article outlines current principles and unresolved questions related to the subject area as well as possible new approaches to early detection and precise intervention of pathological conditions related to altered intracellular energy flow. Full article

Background: Aging is traditionally characterized by progressive structural and cognitive decline; however, increasing evidence shows that the aging brain retains a remarkable capacity for reorganization. This adaptive neuroplasticity supports cognitive resilience—defined as the ability to maintain efficient cognitive performance despite age-related neural vulnerability. Objective: To synthesize current molecular, cellular, neuroimaging, and electrophysiological neuromarkers that characterize adaptive neuroplasticity and to examine how these mechanisms contribute to cognitive resilience across aging. Methods: This narrative review integrates findings from molecular neuroscience, multimodal neuroimaging (fMRI, DTI, PET), electrophysiology (EEG, MEG, TMS), and behavioral research to outline multiscale biomarkers associated with compensatory and efficient neural reorganization in older adults. Results: Adaptive neuroplasticity emerges from the coordinated interaction of neurotrophic signaling (BDNF, CREB, IGF-1), glial modulation (astrocytic lactate metabolism, regulated microglial activity), synaptic remodeling, and neurovascular support (VEGF, nitric oxide). Multimodal neuromarkers—including preserved frontoparietal connectivity, DMN–FPCN coupling, synaptic density (SV2A-PET), theta–gamma coherence, and LTP-like excitability—consistently correlate with resilience in executive functions, memory, and processing speed. Behavioral enrichment, physical activity, and cognitive training further enhance these biomarkers, creating a bidirectional loop between experience and neural adaptability. Conclusions: Adaptive neuroplasticity represents a fundamental mechanism through which older adults maintain cognitive function despite biological aging. Integrating molecular, imaging, electrophysiological, and behavioral neuromarkers provides a comprehensive framework to identify resilience trajectories and to guide personalized interventions aimed at preserving cognition. Understanding these multilevel adaptive mechanisms reframes aging not as passive decline but as a dynamic continuum of biological compensation and cognitive preservation. Full article

Mild traumatic brain injury (mTBI) disrupts hippocampal network function through coordinated alterations in glial reactivity, synaptic integrity, and adult neurogenesis. Effective therapeutic approaches targeting these interconnected processes remain limited. Lipid-derived molecules capable of modulating these mTBI-induced disturbances are emerging as promising neuroprotective candidates. Here, we investigated the effects of N-stearidonylethanolamine (SDEA), an ω-3 ethanolamide, in a mouse model of mTBI. SDEA treatment attenuated astrocytic reactivity, restored Arc expression, and improved dendritic spine density and morphology in the CA1 hippocampal area. In the dentate gyrus, mTBI reduced Ki-67-indexed proliferation while leaving DCX-positive immature neurons unchanged, and SDEA partially rescued proliferative activity. These effects were accompanied by improvements in anxiety-like behavior and working-memory performance. Together, these findings demonstrate that SDEA modulates several key components of the glia-synapse-neurogenesis axis and supports functional recovery of hippocampal circuits following mTBI. These results suggest that ω-3 ethanolamides may represent promising candidates for multi-target therapeutic strategies in mTBI. Full article

Background: The three Synuclein family members (α-, β-, and γ-synuclein) are presynaptic proteins that regulate synaptic vesicle trafficking and thereby influence neurotransmitter release. Synucleins belong to a class of intrinsically disordered proteins and are prone to aggregation into pathological deposits, which may impair their physiological synaptic functions. Knockout (KO) mouse lines, commonly used to model synuclein depletion in the nervous system, reveal a range of phenotypes with different motor and behavioral deficits. However, given the high sequence homology and functional interplay among the three synucleins, the specific contribution of each family member to these phenotypes remains poorly understood. Objective: In this study, we conducted a comparative phenotypic analysis of γ-synuclein KO, α- and β-synuclein KO, and αβγ-synuclein KO mice. Methods: Mice were subjected to a battery of behavioral tests assessing motor activity and coordination, anxiety-like behavior, and spatial learning and memory. Synaptic vesicle proteins were analyzed in brain tissues using Western blotting. Results: We observed that knocking out γ-synuclein but not α- and β-synucleins reduces mouse lifespan and leads to sustained reduction in muscle strength implicating that γ-synuclein is essential for longevity and motor system function. Another consequence of γ-synuclein deficiency is altered anxiety-like behavior manifested as a diminished aversive response, while exploratory behavior and memory remain intact. The triple KO mice mirror γ-synuclein KO mice in some behavioral changes, including shortened lifespan, reduced muscle strength, and decreased anxiety-like behavior. However, the triple KO mice additionally exhibit hyperactivity, which is not present in the other groups. No changes in synaptic vesicle marker levels were detected, indicating that the observed motor and behavioral abnormalities are not attributable to impaired synaptic connectivity. Conclusions: Taken together, these findings demonstrate nonredundant functions of individual synuclein family members and highlight a distinct role of γ-synuclein in regulating motor performance and behavioral responses. Full article

Circuit implementation is a widely accepted method for validating theoretical insights observed in chaotic systems. It also serves as a basis for numerous chaos-based engineering applications, including data encryption, random number generation, secure communication, neuromorphic computing, and so forth. To get feasible, compact, and cost-effective circuit implementations of chaotic systems, the underlying mathematical model may be simplified while preserving all rich nonlinear behaviors. In this framework, this manuscript presents a simplified Hopfield Neural Network (HNN) capable of generating a broad spectrum of complex behaviors using a minimal number of electronic elements. Based on Shil’nikov’s theorem for heteroclinic orbits, the number of non-zero synaptic connections in the matrix weights is reduced, while simultaneously using only one nonlinear activation function. As a result of these simplifications, we obtain the most compact electronic implementation of a tri-neuron HNN with the lowest component count but retaining complex dynamics. Comprehensive theoretical and numerical analyses by equilibrium points, density-colored continuation diagrams, basin of attraction, and Lyapunov exponents, confirm the presence of periodic oscillations, spiking, bursting, and chaos. Such chaotic dynamics range from single-scroll chaotic attractors to double-scroll chaotic attractors, as well as coexisting attractors to transient chaos. A brief security application of an S-Box utilizing the presented HNN is also given. Finally, a physical implementation of the HNN is given to confirm the proposed approach. Experimental observations are in good agreement with numerical results, demonstrating the usefulness of the proposed approach. Full article