Search Results (85)

The dynamics of signal transmission in neuronal networks remain incompletely understood. In this study, we propose a novel Rulkov neuronal network model that incorporates Q-learning, a reinforcement learning method, to establish efficient signal transmission pathways. Using a simulated neuronal network, we focused on a key parameter that modulates both the intrinsic dynamics of individual neurons and the input signals received from active neighbors. We investigated how variations in this parameter affect signal transmission efficiency by analyzing changes in attenuation rate, as well as the maximum and minimum firing intervals of the start and goal neurons. Our simulations revealed that signal transmission efficiency between distant neurons was significantly impaired in the parameter region, where a chaotic attractor and an attractor of the eight-periodic points are observed to co-exist. A key finding was that low-frequency oscillatory bursts, while failing long-distance transmission, were capable of amplifying signals in neighboring neurons. Furthermore, we observed variation in signal transmission even when individual neuron dynamics remained similar. This variability, despite similar presynaptic activity, is a biologically significant phenomenon, and it is argued that it may contribute to the flexibility and robustness of information processing. These findings are discussed in the context of their biological implications. Full article

With the rapid development of internet technologies, enhancing security protection for patient information during its transmission has become increasingly important. Compared with traditional image encryption methods, chaotic image encryption schemes leveraging sensitivity to initial conditions and pseudo-randomness demonstrate superior suitability for high-security-demand scenarios like medical image encryption. In this paper, a novel 3D fractional-order memristive Hopfield neural network (FMHNN) chaotic model with a minimum number of neurons is proposed and applied in medical image encryption. The chaotic characteristics of the proposed FMHNN model are systematically verified through various dynamical analysis methods. The parameter-dependent dynamical behaviors of the proposed FMHNN model are further investigated using Lyapunov exponent spectra, bifurcation diagrams, and spectral entropy analysis. Furthermore, the chaotic behaviors of the proposed FMHNN model are successfully implemented on FPGA hardware, with oscilloscope observations showing excellent agreement with numerical simulations. Finally, a medical image encryption scheme based on the proposed FMHNN model is designed, and comprehensive security analyses are conducted to validate its security for medical image encryption. The analytical results demonstrate that the designed encryption scheme based on the FMHNN model achieves high-level security performance, making it particularly suitable for protecting sensitive medical image transmission. Full article

Post-traumatic stress disorder (PTSD) is a debilitating mental health condition that develops in response to traumatic events. The endocannabinoid, glutamatergic, and GABAergic systems play crucial roles in the neurobiological mechanisms of PTSD. Both the endocannabinoid, glutamatergic, and GABAergic systems are involved in synaptic remodeling and neuronal differentiation, ensuring efficient information transmission in the brain. Their interplay influences motivation, behavior, sensory perception, pain regulation, and visual processing. Additionally, these systems regulate processes such as cellular proliferation, adhesion, apoptosis, and immune responses. This article explores the involvement of the endocannabinoid, glutamatergic, and GABAergic systems in PTSD pathogenesis. A literature review was conducted on studies examining the relationship between the endocannabinoid, glutamatergic, and GABAergic systems in PTSD. Relevant publications were sourced from the Web of Science and Scopus databases, covering research up to 29 February 2025. Neurobiological mechanisms underlying PTSD may share common pathways with other mental and somatic disorders, particularly those involving inflammatory processes. The identification of biomarkers is crucial for assessing PTSD risk and implementing targeted interventions to improve patient outcomes. A deeper understanding of these mechanisms could enhance therapeutic strategies, ultimately improving the quality of life for individuals affected by PTSD. Full article

Preventing false signals of phantom pain after limb amputation is crucial. The development of neurointerfaces capable of bidirectional information exchange between the brain and external devices, along with long-term use, is a key research priority. The main problem with existing devices lies in the potential formation of scar tissue and the death of adjacent neurons. To address this issue, a polymer composite based on new composition: chitosan, bovine serum albumin, single-walled carbon nanotubes, and Eosin Y, which was created for the fabrication of a neurointerface. A polymer composite of the required shape was formed by two-photon polymerization. In studying its nonlinear optical properties, the new effect of phase self-modulation was discovered, which is observed after exposure to laser radiation prior to the formation of the composite. The time of appearance of diffraction rings was measured. This allowed optimization of laser parameters—scanner speed and intensity. The resulting homogeneous composite exhibited a specific conductivity of 20 mS × cm⁻¹, sufficient for electrophysiological signal transmission. Full article

Understanding the distribution of electrical potential within neurons is critical for advancing our comprehension of neuronal signaling and communication. Neurons, the fundamental units of the nervous system, rely on complex electrochemical processes to transmit information. The intricate structure of neurons, especially those with multiple dendrites, plays a crucial role in how these electrical signals are generated, propagated, and integrated. Despite significant progress in neuroscience, accurately modeling the electrical potential within neurons with elaborate dendritic architectures remains a challenge. This article introduces a novel approach to modeling the electrical potential in multi-dendritic neurons using Bessel functions, which offers a more precise and detailed representation of these processes. The proposed method involves solving the electric potential diffusion equation in cylindrical coordinates, a mathematical framework that naturally aligns with the geometry of dendrites. The radial and axial components of the solution are expressed using Bessel functions and sinusoidal functions, respectively. Bessel functions are particularly well-suited for this purpose due to their ability to describe waveforms in cylindrical systems, making them ideal for capturing the spatial variations in electrical potential within the cylindrical shape of dendrites. By leveraging this mathematical approach, we obtain a complete representation of the potential distribution across the neuron, from the soma (cell body) through the dendrites to the synaptic terminals. This model accurately captures the spatial variations of electrical potential in different regions of the neuron, including areas with complex dendritic arborizations, which are branching structures that significantly influence the neuron’s electrical characteristics. Simulation results underscore the effectiveness of this approach in reproducing realistic neuronal behavior. The model successfully mimics the way electrical signals propagate and interact within dendritic structures, providing crucial insights into the underlying mechanisms of signal integration and transmission in neurons. Full article

From learning environments to battlefields to marketing teams, the desire to measure cognition and cognitive fatigue in real time has been a grand challenge in optimizing human performance. Near-infrared spectroscopy (NIRS) is an effective optical technique for measuring changes in subdermal hemodynamics, and it has been championed as a more practical method for monitoring brain function compared to MRI. This study reports on an innovative functional NIRS (fNIRS) sensor that integrates the entire system into a compact and wearable device, enabling long-term monitoring of patients. The device provides unrestricted mobility to the user with a Bluetooth connection for settings configuration and data transmission. A connected device, such as a smartphone or laptop equipped with the appropriate interface software, collects raw data, then stores and generates real-time analyses. Tests confirm the sensor is sensitive to oxy- and deoxy-hemoglobin changes on the forehead region, which indicate neuronal activity and provide information for brain activity monitoring studies. Full article

Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals used in various products, such as firefighting foams and non-stick cookware, due to their resistance to heat and degradation. However, these same properties make them persistent in the environment and human body, raising public health concerns. This study selected eleven PFAS commonly found in drinking water and exposed Caenorhabditis elegans to concentrations ranging from 0.1 to 200 µM to assess neurodevelopmental toxicity using a high-throughput, high-content screening (HTS) platform coupled with artificial intelligence for image analysis. Our findings showed that PFAS such as 6:2 FTS, HFPO-DA, PFBA, PFBS, PFHxA, and PFOS inhibited dopaminergic neuron activity, with fluorescence intensity reductions observed across concentrations from 0.1 to 100 µM. PFOS and PFBS also disrupted synaptic transmission, causing reduced motility and increased paralysis in aldicarb-induced assays, with the most pronounced effects at higher concentrations. These impairments in both neuron activity and synaptic function led to behavioral deficits. Notably, PFOS was one of the most toxic PFAS, affecting multiple neurodevelopmental endpoints. These results emphasize the developmental risks of PFAS exposure, highlighting the impact of both individual compounds and mixtures on neurodevelopment. This knowledge is essential for assessing PFAS-related health risks and informing mitigation strategies. Full article

Nociceptive information is transmitted by action potentials (APs) through primary afferent neurons from the periphery to the central nervous system. Voltage-gated Na⁺ channels are involved in this AP production, while transient receptor potential (TRP) channels, which are non-selective cation channels, are involved in receiving and transmitting nociceptive stimuli in the peripheral and central terminals of the primary afferent neurons. Peripheral terminal TRP vanilloid-1 (TRPV1), ankylin-1 (TRPA1) and melastatin-8 (TRPM8) activation produces APs, while central terminal TRP activation enhances the spontaneous release of L-glutamate from the terminal to spinal cord and brain stem lamina II neurons that play a pivotal role in modulating nociceptive transmission. There is much evidence demonstrating that chemical compounds involved in Na⁺ channel (or nerve AP conduction) inhibition modify TRP channel functions. Among these compounds are local anesthetics, anti-epileptics, α₂-adrenoceptor agonists, antidepressants (all of which are used as analgesic adjuvants), general anesthetics, opioids, non-steroidal anti-inflammatory drugs and plant-derived compounds, many of which are involved in antinociception. This review mentions the modulation of Na⁺ channels and TRP channels including TRPV1, TRPA1 and TRPM8, both of which modulations are produced by pain-related compounds. Full article

The endoplasmic reticulum (ER) is a key organelle in cellular homeostasis, regulating calcium levels and coordinating protein synthesis and folding. In neurons, the ER forms interconnected sheets and tubules that facilitate the propagation of calcium-based signals. Calcium plays a central role in the modulation and regulation of numerous functions in excitable cells. It is a versatile signaling molecule that influences neurotransmitter release, muscle contraction, gene expression, and cell survival. This review focuses on the intricate dynamics of calcium signaling in hippocampal neurons, with particular emphasis on the activation of voltage-gated and ionotropic glutamate receptors in the plasma membrane and ryanodine and inositol 1,4,5-trisphosphate receptors in the ER. These channels and receptors are involved in the generation and transmission of electrical signals and the modulation of calcium concentrations within the neuronal network. By analyzing calcium fluctuations in neurons and the associated calcium handling mechanisms at the ER, mitochondria, endo-lysosome and cytosol, we can gain a deeper understanding of the mechanistic pathways underlying neuronal interactions and information transfer. Full article

Road safety through point-to-point interaction autonomous vehicles (AVs) assimilate different communication technologies for reliable and persistent information sharing. Vehicle interaction resilience and consistency require novel sharing knowledge for retaining driving and pedestrian safety. This article proposes a control optimiser interaction framework (COIF) for organising information transmission between the AV and interacting “Thing”. The framework relies on the neuro-batch learning algorithm to improve the consistency measure’s adaptability with the interacting “Things”. In the information-sharing process, the maximum extraction and utilisation are computed to track the AV with precise environmental knowledge. The interactions are batched with the type of traffic information obtained, such as population, accidents, objects, hindrances, etc. Throughout travel, the vehicle’s learning rate and the surrounding environment’s familiarity with it are classified. The learning neurons are connected to the information actuated and sensed by the AV to identify any unsafe vehicle activity in unknown or unidentified scenarios. Based on the risk and driving parameters, the safe and unsafe activity of the vehicles is categorised with a precise learning rate. Therefore, minor changes in vehicular decisions are monitored, and driving control is optimised accordingly to retain 7.93% of navigation assistance through a 9.76% high learning rate for different intervals. Full article

Memristors have become important components in artificial synapses due to their ability to emulate the information transmission and memory functions of biological synapses. Unlike their biological counterparts, which adjust synaptic weights, memristor-based artificial synapses operate by altering conductance or resistance, making them useful for enhancing the processing capacity and storage capabilities of neural networks. When integrated into systems like Hopfield neural networks, memristors enable the study of complex dynamic behaviors, such as chaos and multistability. Moreover, fractional calculus is significant for their ability to model memory effects, enabling more accurate simulations of complex systems. Fractional-order Hopfield networks, in particular, exhibit chaotic and multistable behaviors not found in integer-order models. By combining memristors with fractional-order Hopfield neural networks, these systems offer the possibility of investigating different dynamic phenomena in artificial neural networks. This study investigates the dynamical behavior of a fractional-order Hopfield neural network (HNN) incorporating a memristor with a piecewise segment function in one of its synapses, highlighting the impact of fractional-order derivatives and memristive synapses on the stability, robustness, and dynamic complexity of the system. Using a network of four neurons as a case study, it is demonstrated that the memristive fractional-order HNN exhibits multistability, coexisting chaotic attractors, and coexisting limit cycles. Through spectral entropy analysis, the regions in the initial condition space that display varying degrees of complexity are mapped, highlighting those areas where the chaotic series approach a pseudo-random sequence of numbers. Finally, the proposed fractional-order memristive HNN is implemented on a Field-Programmable Gate Array (FPGA), demonstrating the feasibility of real-time hardware realization. Full article

Background/Objectives: Dopamine dysfunction (DA) is a hallmark of many neurological disorders. In this case, the mechanism of changes in dopamine transmission on behavior remains unclear. This study is a look into the intricate link between disrupted DA signaling, neuronal activity patterns, and behavioral abnormalities in a hyperdopaminergic animal model. Methods: To study the relationship between altered DA levels, neuronal activity, and behavioral deficits, local field potentials (LFPs) were recorded during four different behaviors in dopamine transporter knockout rats (DAT-KO). At the same time, local field potentials were recorded in the striatum and prefrontal cortex. Correlates of LFP and accompanying behavioral patterns in genetically modified (DAT-KO) and control animals were studied. Results: DAT-KO rats exhibited desynchronization between LFPs of the striatum and prefrontal cortex, particularly during exploratory behavior. A suppressive effect of high dopamine levels on the striatum was also observed. Wild-type rats showed greater variability in LFP patterns across certain behaviors, while DAT-KO rats showed more uniform patterns. Conclusions: The decisive role of the synchrony of STR and PFC neurons in the organization of motor acts has been revealed. The greater variability of control animals in certain forms of behavior probably suggests greater adaptability. More uniform patterns in DAT-KO rats, indicating a loss of striatal flexibility when adapting to specific motor tasks. It is likely that hyperdopaminergy in the DAT-KO rat reduces the efficiency of information processing due to less synchronized activity during active behavior. Full article

Alphaherpesviruses, including herpes simplex virus type 1 (HSV-1), herpes simplex virus type 2 (HSV-2), and varicella-zoster virus (VZV), infect a diverse array of hosts, spanning both humans and animals. Alphaherpesviruses have developed a well-adapted relationship with their hosts through long-term evolution. Some alphaherpesviruses exhibit a typical neurotropic characteristic, which has garnered widespread attention and in-depth research. Virus latency involves the retention of viral genomes without producing infectious viruses. However, under stress, this can be reversed, resulting in lytic infection. Such reactivation events can lead to recurrent infections, manifesting as diseases like herpes labialis, genital herpes, and herpes zoster. Reactivation is a complex process influenced by both viral and host factors, and identifying how latency and reactivation work is vital to developing new antiviral therapies. Recent research highlights a complex interaction among the virus, neurons, and the immune system in regulating alphaherpesvirus latency and reactivation. Neurotropic alphaherpesviruses can breach host barriers to infect neurons, proliferate extensively within their cell bodies, and establish latent infections or spread further. Whether infecting neurons or spreading further, the virus undergoes transmission along axons or dendrites, making this process an indispensable part of the viral life cycle and a critical factor influencing the virus’s invasion of the nervous system. Research on the transmission process of neurotropic alphaherpesviruses within neurons can not only deepen our understanding of the virus but can also facilitate the targeted development of corresponding vaccines. This review concentrates on the relationship between the transmission, latency, and activation of alphaherpesviruses within neurons, summarizes recent advancements in the field, and discusses how these findings can inform the design of live virus vaccines for alphaherpesviruses. Full article

The use of multimodal anaesthesia and analgesia is desirable as part of a complete analgesic plan. Analgesic strategies for perioperative pain treatment include combinations of drugs with different means of action to increase their efficacy and to reduce the required doses and adverse effects. Local anaesthetics prevent the transduction and transmission of painful stimuli through their action on neuronal cell membranes. They undergo minimal systemic absorption and are therefore ideal alternatives to drugs that could result in systemic toxicity. Numerous benefits have been recognised for the use of local anaesthesia, such as a decreased need for systemic analgesics and decreased hospitalisation periods. Local anaesthetics have been used in veterinary medicine in several ways. Anatomical landmarks can be used to identify the target nerves and the clinician can employ an electrical nerve stimulator or ultrasound guidance to perform a more accurate injection. Local anaesthetic techniques can implement other drugs, apart from or in combination with local anaesthetics, such as opioids, α₂−adrenergic agonists or vasoconstricting agents. This review article presents and discusses the most common techniques of local anaesthetic use in small animals, with the aim of providing the clinician with further and comprehensive information regarding the analgesic options during the perioperative period. Full article

Chronic pain is a pathological state defined as daily pain sensation over three consecutive months. It affects up to 30% of the general population. Although significant research efforts have been made in the past 30 years, only a few and relatively low effective molecules have emerged to treat chronic pain, with a considerable translational failure rate. Most preclinical models have focused on sensory neurotransmission, with particular emphasis on the dorsal horn of the spinal cord as the first relay of nociceptive information. Beyond impaired nociceptive transmission, chronic pain is also accompanied by numerous comorbidities, such as anxiety–depressive disorders, anhedonia and motor and cognitive deficits gathered under the term “pain matrix”. The emergence of cutting-edge techniques assessing specific neuronal circuits allow in-depth studies of the connections between “pain matrix” circuits and behavioural outputs. Pain behaviours are assessed not only by reflex-induced responses but also by various or more complex behaviours in order to obtain the most complete picture of an animal’s pain state. This review summarises the latest findings on pain modulation by brain component of the pain matrix and proposes new opportunities to unravel the mechanisms of chronic pain. Full article