Search Results (774)

This paper addresses a central conceptual challenge in Quantum-like Cognition and Decision-Making (QCDM) and the broader research program of Quantum-like Modeling (QLM): the interpretation of phases in quantum-like state superpositions. In QLM, system states are represented by normalized vectors in a complex Hilbert space, $|\psi ⟩={\sum }_k{X}_k|k⟩$, where the squared amplitudes $P_k={\left|X_k\right|}^2$ are outcome probabilities. However, the meaning of the phase factors $e^{i{\varphi }_k}$ in the coefficients $X_k=P_k{e}^{i{\varphi }_k}$ has remained elusive, often treating them as purely phenomenological parameters. This practice, while successful in describing cognitive interference effects (the "interference of the mind”), has drawn criticism for expanding the model’s parameter space without a clear physical or cognitive underpinning. Building on a recent framework that connects QCDM to neuronal network activity, we propose a concrete interpretation. We argue that the phases in quantum-like superpositions correspond directly to the phases of random oscillations generated by neuronal circuits in the brain. This interpretation not only provides a natural, non-phenomenological basis for phase parameters within QCDM but also helps to bridge the gap between quantum-like models and classical neurocognitive frameworks, offering a consistent physical analogy for the descriptive power of QLM. Full article

Anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis is an immune-mediated neurological disorder driven by dysregulated neuroimmune interactions, yet the molecular architecture linking tumor-associated immune activation, peripheral immunity, and neuronal dysfunction remains insufficiently understood. In this study, we established an integrative computational framework that combines multi-tissue transcriptomic profiling, weighted gene co-expression network analysis, immune deconvolution, and machine learning-based feature prioritization to systematically characterize the regulatory landscape of the disease. Joint analysis of three independent GEO datasets spanning ovarian teratoma tissue and peripheral blood transcriptomes identified 2001 consistently dysregulated mRNAs, defining a shared tumor–immune–neural transcriptional axis. Across multiple feature selection algorithms, ACVR2B and MX1 were reproducibly prioritized as immune-associated candidate genes and were consistently downregulated in anti-NMDAR encephalitis samples, showing negative correlations with neutrophil infiltration. Reconstruction of an integrated mRNA-miRNA-lncRNA regulatory network further highlighted a putative core axis (ENSG00000262580–hsa-miR-22-3p–ACVR2B), proposed as a hypothesis-generating regulatory module linking non-coding RNA regulation to immune-neuronal signaling. Pathway and immune profiling analyses demonstrated convergence of canonical immune signaling pathways, including JAK-STAT and PI3K-Akt, with neuronal communication modules, accompanied by enhanced innate immune signatures. Although limited by reliance on public datasets and small sample size, these findings delineate a systems-level neuroimmune regulatory program in anti-NMDAR encephalitis and provide a scalable, network-based multi-omics framework for investigating immune-mediated neurological and autoimmune disorders and for guiding future experimental validation. Full article

Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation technique that utilizes magnetic fields to induce cortical electric currents, enabling both the measurement and modulation of neuronal activity. Initially developed as a diagnostic tool, TMS now serves dual roles in clinical neurology, offering insight into neurophysiological dysfunctions and the therapeutic modulation of abnormal cortical excitability. This review examines key TMS outcome measures, including motor thresholds (MT), input–output (I/O) curves, cortical silent periods (CSP), and paired-pulse paradigms such as short-interval intracortical inhibition (SICI), short-interval intracortical facilitation (SICF), intracortical facilitation (ICF), long interval cortical inhibition (LICI), interhemispheric inhibition (IHI), and short-latency afferent inhibition (SAI). These biomarkers reflect underlying neurotransmitter systems and can aid in differentiating neurological conditions. Diagnostic applications of TMS are explored in Parkinson’s disease (PD), dystonia, essential tremor (ET), Alzheimer’s disease (AD), and mild cognitive impairment (MCI). Each condition displays characteristic neurophysiological profiles, highlighting the potential for TMS-derived biomarkers in early or differential diagnosis. Therapeutically, repetitive TMS (rTMS) has shown promise in modulating cortical circuits and improving motor and cognitive symptoms. High- and low-frequency stimulation protocols have demonstrated efficacy in PD, dystonia, ET, AD, and MCI, targeting the specific cortical regions implicated in each disorder. Moreover, the successful application of TMS in differentiating and treating AD and MCI underscores its clinical utility and translational potential across all neurodegenerative conditions. As research advances, increased attention and investment in TMS could facilitate similar diagnostic and therapeutic breakthroughs for other neurological disorders that currently lack robust tools for early detection and effective intervention. Moreover, this review also aims to underscore the importance of maintaining standardized TMS protocols. By highlighting inconsistencies and variability in outcomes across studies, we emphasize that careful methodological design is critical for ensuring the reproducibility, comparability, and reliable interpretation of TMS findings. In summary, this review emphasizes the value of TMS as a distinctive, non-invasive approach to probing brain function and highlights its considerable promise as both a diagnostic and therapeutic modality in neurology—roles that are often considered separately. Full article

Excitable neurons are intrinsically capable of firing action potentials (AP), yet a state of hyperexcitability is prevented in the central nervous system by powerful GABAergic inhibition. For this inhibition to be effective, it must occur before excitatory signals can initiate runaway activity, implying the existence of a proactive control system. To test for such proactive inhibition, we used Ca²⁺ imaging and patch-clamp recording to measure how hippocampal neurons respond to depolarization and glutamatergic agonists. In mature hippocampal cultures (14 days in vitro (DIV)) and acute brain slices from two-month-old rats, neurons exhibited non-simultaneous responses to various excitatory stimuli, including KCl, NH₄Cl, forskolin, domoic acid, and glutamate. We observed that the Ca²⁺ rise occurred significantly earlier in GABAergic neurons than in glutamatergic neurons. This delay in glutamatergic neurons was abolished by GABA(A) receptor inhibitors, suggesting a mechanism of preliminary γ-aminobutyric acid (GABA) release. We further found that these early-responding GABAergic neurons express calcium-permeable kainate and AMPA receptors (CP-KARs and CP-AMPARs). Application of domoic acid induced an immediate Ca²⁺ increase in neurons expressing these receptors, but a delayed response in others. Crucially, when domoic acid was applied in the presence of the AMPA receptor inhibitors NBQX or GYKI-52466, the response delay in glutamatergic neurons was significantly prolonged. This confirms that CP-KARs on GABAergic neurons are responsible for the delayed excitation of glutamatergic neurons. In hippocampal slices from two-month-old rats, depolarization with 50 mM KCl revealed two distinct neuronal populations based on their calcium dynamics: a majority group (presumably glutamatergic) exhibited fluctuating Ca²⁺ signals, while a minority (presumably GABAergic) showed a steady, advancing increase in [Ca²⁺]i. This distinction was reinforced by the application of domoic acid. The “advancing-response” neurons reacted to domoic acid with a similar prompt increase, whereas the “fluctuating-response” neurons displayed an even more delayed and fluctuating reaction (80 s delay). Therefore, we identify a subgroup of hippocampal neurons—in both slices and cultures—that respond to depolarization and domoic acid with an early [Ca²⁺]_i signal. Consistent with our data from cultures, we conclude these early-responding neurons are GABAergic. Their early GABA release directly explains the delayed Ca²⁺ response observed in glutamatergic neurons. We propose that this proactive mechanism, mediated by CP-KARs on GABAergic neurons, is a primary means of protecting the network from hyperexcitation. Furthermore, the activity of these CP-KAR-expressing neurons is itself regulated by GABAergic neurons containing CP-AMPARs. Full article

Paraneoplastic neurological syndromes (PNSs) are immune-mediated disorders caused by an antitumor response that cross-reacts with the nervous system, leading to severe and often irreversible neurological disability. Once considered exceedingly rare, PNSs are now increasingly recognized owing to the identification of novel neural autoantibodies, wider use of commercial testing, and the emergence of immune checkpoint inhibitor (ICI)-related neurotoxicity that phenotypically overlaps with classic PNS. In this narrative review, we performed a structured search of PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar, without date restrictions, to summarize contemporary advances in the epidemiology, pathogenesis, diagnosis, and management of PNS. Population-based data show rising incidence, largely reflecting improved ascertainment and expanding indications for ICIs. Pathogenetically, we distinguish T-cell-mediated syndromes associated with intracellular antigens from antibody-mediated disorders targeting neuronal surface proteins, integrating emerging concepts of molecular mimicry, tumor genetics, and HLA-linked susceptibility. The 2021 PNS-Care criteria are also reviewed, which replace earlier “classical/non-classical” definitions with risk-stratified phenotypes and antibodies, and demonstrate superior diagnostic performance while underscoring that “probable” and “definite” PNS should be managed with equal urgency. Newly described antibodies and methodological innovations such as PhIP-Seq, neurofilament light chain, and liquid biopsy are highlighted, which refine tumor search strategies and longitudinal monitoring. Management principles emphasize early tumor control, prompt immunotherapy, and a growing repertoire of targeted agents, alongside specific considerations for ICI-associated neurological syndromes. Remaining challenges include diagnostic delays, limited high-level evidence, and the paucity of validated biomarkers of disease activity. Future work should prioritize prospective, biomarker-driven trials and multidisciplinary pathways to shorten time to diagnosis and improve long-term outcomes in patients with PNS. Full article

Brown adipose tissue (BAT) and beige adipocytes play a crucial role in adaptive thermogenesis, primarily via uncoupling protein 1 (UCP1)-driven heat production. Once considered physiologically irrelevant in adults, BAT is now recognized as an active tissue that contributes to energy expenditure and metabolic homeostasis and represents a potential therapeutic target for obesity and metabolic disorders. This review provides an integrated overview of the molecular regulation of thermogenic adipocytes, emphasizing both canonical UCP1-dependent as well as non-canonical UCP1-independent mechanisms of heat generation. Key transcriptional and epigenetic regulators are discussed in the context of mitochondrial biogenesis, substrate utilization, and thermogenic gene programs. Major upstream signaling routes are further summarized, encompassing classical β-adrenergic pathways, as well as alternative regulatory nodes including AMP-activated protein kinase (AMPK) and mechanistic target of rapamycin (mTOR) together with diverse nutrient- and hormone-responsive cues that converge to activate brown and beige adipocytes. Finally, the cross-talk among neuronal, endocrine, immune, and gut microbiota-derived signals is highlighted as a key determinant of thermogenic adipocyte function. Together, these multilayered regulatory inputs provide a comprehensive framework for understanding how thermogenic adipose tissue integrates environmental, metabolic, and microbial cues to regulate systemic energy balance—knowledge that is essential for developing targeted therapies to combat obesity and metabolic diseases. Full article

Clostridial neurotoxins, botulinum neurotoxins (BoNTs), and tetanus neurotoxin (TeNT) are potent toxins responsible for severe diseases, botulism and tetanus, respectively. BoNTs associate with non-toxic proteins (non-toxic non-hemagglutinin, hemagglutinins, and OrfXs), which protect BoNTs against acidic pH and protease degradation and facilitate BoNT passage through the intestinal barrier. TeNT enters motor neurons and undergoes a retrograde axonal transport until the target inhibitory interneurons in the central nervous system. BoNTs and TeNT recognize specific cell surface receptors which consist of complex sets of protein(s)-glycan-gangliosides and determine specific cell entry pathways. Recent data on structural and functional investigations of BoNT and TeNT receptors bring a better understanding of toxin trafficking in the host and entry into target neuronal cells, which is useful for the development of updated strategies of prevention and treatment of the corresponding diseases. Since clostridial neurotoxins, notably BoNTs, are important therapeutic tools, detailed knowledge of their activity opens the way of the development of engineered molecules for specific clinical applications. Full article

The enteric nervous system (ENS) constitutes a highly organized and intricate neuronal network comprising two principal plexuses: myenteric and submucosal. These plexuses consist of neurons and enteric glial cells (EGCs). Neurons ensure innervation throughout the intestinal wall, whereas EGCs, distributed within the mucosa, contribute to epithelial barrier integrity and modulation of local inflammatory responses. The ENS orchestrates essential gastrointestinal functions, including motility, secretion, absorption, vascular regulation, and immune interactions with gut microbiota. Under physiological conditions, intestinal homeostasis involves moderate generation of reactive oxygen species (ROS) through endogenous processes such as mitochondrial oxidative phosphorylation. Cellular antioxidant systems maintain redox equilibrium; however, excessive ROS production induces oxidative stress, promoting EGCs activation toward a reactive phenotype characterized by pro-inflammatory cytokine release. This disrupts neuron–glia communication, predisposing to enteric neuroinflammation and neurodegeneration. Obesity, associated with hyperglycemia, hyperlipidemia, and micronutrient deficiencies, enhances ROS generation and inflammatory cascades, thereby impairing ENS integrity. Nevertheless, non-pharmacological strategies—including synthetic and natural antioxidants, bioactive dietary compounds, probiotics, and prebiotics—attenuate oxidative and inflammatory damage. This review summarizes preclinical and clinical evidence elucidating the interplay among the ENS, obesity-induced oxidative stress, inflammation, and the modulatory effects of antioxidant interventions. Full article

Malformations of cortical development (MCD) are a group of neurodevelopmental disorders caused by abnormalities in cerebral cortex development, leading to conditions such as intellectual disability and refractory epilepsy. The prenatal phenotypes of MCD are complex and non-specific, complicating accurate diagnosis and prognosis assessment. Genetic testing, particularly chromosomal microarray analysis (CMA) and whole-exome sequencing (WES), has become an important tool for prenatal diagnosis. This review synthesizes current research on prenatal MCD, focusing on the integration of imaging and genetic diagnostic strategies based on the biological foundation of cortical development and the classification system of MCD. Prenatal MCD phenotypes show significant developmental stage clustering, with proliferation-phase abnormalities (62.9%) being the most common and microcephaly as the core phenotype. Genetic studies have revealed a high degree of genetic heterogeneity in MCD, with etiologies encompassing chromosomal abnormalities and a wide range of single-gene mutations. These mutations are clustered by phenotype: microcephaly is associated with neuronal proliferation/DNA repair genes; macrocephaly is driven by genes in the PI3K-AKT-mTOR and RAS-MAPK signaling pathways; and gyral and sulcal abnormalities are closely linked to microtubule-associated genes and migration pathways. De novo mutations account for the majority of pathogenic genetic alterations identified in MCD (50.6%); up to 75.1% of pathogenic mutations cannot be detected by routine prenatal screening. Based on this, the review emphasizes that for fetuses with suspected MCD, NGS, with WES at its core, plays an increasingly important role in achieving early and accurate prenatal diagnosis. Future research should prioritize the advancement of integrated diagnostic methods and large-scale cohort studies to further elucidate genotype–phenotype associations. Full article

Non-coding RNAs have emerged as central regulators of gene expression in neurodegenerative diseases, offering new opportunities for diagnosis and therapy. This review synthesizes current knowledge on microRNAs, long non-coding RNAs, and circular RNAs in Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis, emphasizing their roles in synaptic function, proteostasis, mitochondrial biology, and neuroinflammation. We evaluate evidence supporting non-coding RNAs as circulating and tissue-based biomarkers for early detection, disease monitoring, and patient stratification, and we compare analytical platforms and biofluid sources. Mechanistic insights reveal how non-coding RNAs modulate pathogenic protein aggregation, neuronal excitability, immune cell crosstalk, and blood–brain barrier integrity. Translational efforts toward RNA-targeted interventions are reviewed, including antisense oligonucleotides, small interfering RNAs, miRNA mimics and inhibitors, circular RNA decoys, and extracellular vesicle-mediated delivery systems. We discuss pharmacological modulation, delivery challenges, safety concerns, and strategies to enhance specificity and CNS penetration. Finally, we outline emerging computational and multi-omics approaches to prioritize therapeutic targets and propose a roadmap for advancing non-coding RNA research from preclinical models to clinical trials. Addressing biological heterogeneity and delivery barriers will be pivotal to realizing the diagnostic and therapeutic promise of the non-coding transcriptome in neurodegenerative disease. Collaboration across disciplines and rigorous clinical validation are urgently needed. 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

Over the years, neurons undergo functional changes initially linked to the maturation of the brain and then are progressively linked to normal aging. The curious relationship between brain decay, aging, and neuronal diseases has aroused the interest of numerous studies to better understand and contrast the evolution of these pathologies. The objective of this research is to apply the non-equilibrium thermodynamic theory with the internal variables of the study of the rheological properties of the brain, focusing on the study of viscoelastic properties. After a thermodynamic introduction of the principal rheological phenomena, this paper discusses the results by the application of our mathematical technique, which revealed a prevalence of anelastic properties in the old central nervous system compared to the young one. Furthermore, the entropy production trend tested identifies a greater disorder in the young brain in respect to the old one. The results obtained highlight that a lower stiffness in the old central nervous system may be interpreted with dendritic regression associated with neuronal death, both being potential consequences of an increased production of free radicals due to reduced antioxidant defenses and/or an altered mitochondrial dysfunction in aging. Full article

This review summarizes a growing collection of data on adult neurogenesis in various vertebrate species, with a focus on teleost fish and mammals. Teleost fish serve as exceptional models for studying the dynamics of the cell cycle and the functions of adult neural stem progenitor cells (aNSPCs) throughout the central nervous system (CNS). New information about the characteristics of cells in various areas of the telencephalon of non-model objects—juvenile masu salmon Oncorhynchus masou and chum salmon Oncorhynchus keta—during postembryonic ontogenesis and after traumatic injury expands the current understanding of the issue. The expression of molecular markers of adult-type glial precursors in the model zebrafish and non-model objects, juveniles O. masou and O. keta, was presented. Immunohistochemical (IHC) verification of BrdU and PCNA made it possible to identify a population of rapidly and slowly proliferating cells in the pallium of intact O. masou and after traumatic brain injury (TBI). In salmonids, unlike in mammals, progenitor cells are able to differentiate into neurons after injury. The expression of vimentin and GFAP in the aNSCPs has functional specificity. A comparative analysis of the expression of Pax transcription factors in various vertebrates and juveniles O. masou is presented. Pax genes maintain cells in an undifferentiated state and ensure the spatiotemporal formation of mature cell types in changing developing neurogenic niches. The functions of glutamine synthetase (GS) and H₂S in the brains of vertebrates and juvenile chum salmon under intact conditions and after TBI are characterized. In fish, unlike mammals, as a result of TBI, neuronal conduction is restored in the injury area, whereas in mammals the regenerative process is complicated by neuroinflammation and culminates in the formation of a glial scar. Full article

Parkinson’s disease (PD) is a progressive neurodegenerative disorder whose early symptoms, especially mild tremor, are often clinically imperceptible. Early detection is crucial for initiating neuroprotective interventions to slow dopaminergic neuronal degeneration. Current PD diagnosis relies predominantly on subjective clinical assessments due to the absence of definitive biomarkers. This study proposes a novel approach for the early detection of PD through a custom-developed smart wristband equipped with an inertial measurement unit (IMU). Unlike previous paper-based or resting-tremor approaches, this study introduces a mid-air Archimedean spiral task combined with an attention-enhanced Long Short-Term Memory (LSTM) architecture, enabling substantially more sensitive detection of subtle early-stage Parkinsonian motor abnormalities. We propose LAFNet, a model based on an attention-enhanced LSTM network, which processes motion data that has been filtered using a Kalman algorithm for noise reduction, enabling rapid and accurate diagnosis. Clinical data evaluation demonstrated exceptional performance, with an accuracy of 99.02%. The proposed system shows significant potential for clinical translation as a non-invasive screening tool for early-stage Parkinson’s disease (PD). Full article

This study presents the development process of a digital twin for a complex dynamic object using Artificial Neural Networks. A separately excited DC motor is considered as an example, which, despite its well-known electromechanical properties, remains a non-trivial object for neural network modeling. It is shown that describing the motor using a generalized neural network with various configurations does not yield satisfactory results. The optimal solution was based on a separation into two distinct nonlinear autoregressive with exogenous inputs (NARX) artificial neural networks with cross-connections for the two main machine variables: one for modeling the armature current with exogenous inputs of voltage and armature speed, and another for modeling the angular speed with inputs of voltage and armature current. Both neural networks are characterized by a relatively small number of neurons in the hidden layer and a time delay of no more than 3 time steps. This solution, consistent with the physical understanding of the motor as an object where electromagnetic energy is converted into thermal and mechanical energy (and vice versa), allows the model to be calibrated for the ideal no-load mode and subsequently account for the influence of torque loads of various natures and changes in the control object parameters over a wide range. The study demonstrates that even for modeling an object such as a DC electric drive with cascaded control, reducing errors at the boundaries of the known operating range requires generating test signals covering approximately 120% of the nominal speed range and 250–400% of the nominal current. Analysis of various test signals revealed that training with a sequence of step changes and linear variations across the entire operating range of armature current and speed provides higher accuracy compared to training with random or uniform signals. Furthermore, to ensure the neural network model’s functionality under varying load torque, a mechanical load observer was developed, and a model architecture incorporating an additional input for disturbance was proposed. The SEDCM_NARX_LOAD neural network model demonstrates a theoretically justified response to load application, although dynamic and static errors arise. In the experiment, the current error was 7.4%, and the speed error was 0.5%. The practical significance of the research lies in the potential use of the proposed model for simulating dynamic and static operational modes of electromechanical systems, tuning controllers, and testing control strategies without employing a physical motor. Full article