Firing Threshold Research Articles

Artificial mechano-nociceptive system based on transparent ITO/AlN/ITO memristor nociceptor neuron

Artificial nociceptors demonstrate significant potential in emerging fields such as intelligent prosthetics, humanoid robotics, and electronic skin, capable of transducing external noxious stimuli to the central nervous system. Unlike common sensory neurons, nociceptors exhibit unique characteristics, including “no adaptation,” “relaxation,” “threshold firing,” and “sensitization of allodynia/hyperalgesia.” This study presents a forming-free volatile transparent ITO/AlN/ITO memristor that emulates biological nociceptor behaviors. Leveraging this artificial nociceptor, an artificial mechano-nociceptive system is developed by integrating the ITO/AlN/ITO memristor into a piezoelectric force sensor system for pain sensing and noxious stimuli warning. This research contributes to the advancement of human cognitive capability emulation and artificial intelligence systems, particularly in the domain of pain perception and response.

Synchronized stepwise control of firing and learning thresholds in a spiking randomly connected neural network toward hardware implementation

Spiking randomly connected neural network (RNN) hardware is promising as ultimately low power devices for temporal data processing at the edge. Although the potential of RNNs for temporal data processing has been demonstrated, randomness of the network architecture often causes performance degradation. To mitigate such degradation, self-organization mechanism using intrinsic plasticity (IP) and synaptic plasticity (SP) should be implemented in the spiking RNN. Therefore, we propose hardware-oriented models of these functions. To implement the function of IP, a variable firing threshold is introduced to each excitatory neuron in the RNN that changes stepwise in accordance with its activity. We also define other thresholds for SP that synchronize with the firing threshold, which determine the direction of stepwise synaptic update that is executed on receiving a pre-synaptic spike. To discuss the effectiveness of our model, we perform simulations of temporal data learning and anomaly detection using publicly available electrocardiograms (ECGs) with a spiking RNN. We observe that the spiking RNN with our IP and SP models realizes the true positive rate of 1 with the false positive rate being suppressed at 0 successfully, which does not occur otherwise. Furthermore, we find that these thresholds as well as the synaptic weights can be reduced to binary if the RNN architecture is appropriately designed. This contributes to minimization of the circuit of the neuronal system having IP and SP.

Multi-Sensor Photoelectric Fire Alarm Device Implementation for Early Fire Detection in Campsites

With the growing popularity of leisure activities such as camping and glamping, the incidence of fires at camping sites has increased. This study focuses on improving the effectiveness of photoelectric fire alarm devices by incorporating temperature and humidity data for early fire detection in confined spaces, such as campsites. This study proposes a novel multi-sensor fire alarm system that dynamically adjusts fire detection threshold values based on temperature and humidity data collected by unmanned automatic weather observation systems. The prototype, which was implemented using Raspberry Pi and multiple sensors, demonstrated approximately 20% faster fire detection speed than existing photoelectric fire alarm systems, as verified through experiments in a simulated camping environment. The proposed approach is expected to advance fire alarm systems, enabling faster and more accurate fire detection in diverse environments, particularly at campsites.

Egr1 Expression Is Correlated With Synaptic Activity but Not Intrinsic Membrane Properties in Mouse Adult-Born Dentate Granule Cells.

The discovery of adult-born granule cells (aDGCs) in the dentate gyrus of the hippocampus has raised questions regarding how they develop, incorporate into the hippocampal circuitry, and contribute to learning and memory. Here, we used patch-clamp electrophysiology to investigate the intrinsic and synaptic excitability of mouse aDGCs as they matured, enabled by using a tamoxifen-induced genetic label to birth date the aDGCs at different animal ages. Importantly, we also undertook immunofluorescence studies of the expression of the immediate early gene Egr1 and compared these findings with the electrophysiology data in the same animals. We examined two groups of animals, with aDGC birthdating when the mice were 2 months and at 7-9 months of age. In both groups, cells 4 weeks old had lower thresholds for current-evoked action potentials than older cells but fired fewer spikes during long current pulses and responded more poorly to synaptic activation. aDGCs born in both 2 and 7-9-month-old mice matured in their intrinsic excitability and synaptic properties from 4-12 weeks postgenesis, but this occurred more slowly for the older age animals. Interestingly, this pattern of intrinsic excitability changes did not correlate with the pattern of Egr1 expression. Instead, the development of Egr1 expression was correlated with the frequency of spontaneous excitatory postsynaptic currents. These results suggest that in order for aDGCs to fully participate in hippocampal circuitry, as indicated by Egr1 expression, they must have developed enough synaptic input, in spite of the greater input resistance and reduced firing threshold that characterizes young aDGCs.

Interactions between soil and other environmental variables modulate forest expansion and ecotone dynamics in humid savannas of Central Africa.

Forest expansion into savanna is a pervasive phenomenon in West and Central Africa, warranting comparative studies under diverse environmental conditions. We collected vegetation data from the woody and grassy components within 73 plots of 0.16 ha distributed along a successional gradient from humid savanna to forest in Central Africa. We associated spatially collocated edaphic parameters and fire frequency derived from remote sensing to investigate their combined influence on the vegetation. Soil texture was more influential in shaping savanna structure and species distribution than soil fertility, with clay-rich soils promoting higher grass productivity and fire frequency. Savanna featuring woody aboveground biomass surpassing 40 Mg ha-1 could escape the grass-fire feedback loop, by depressing grass biomass below 4 Mg ha-1. This thicker woody layer also favoured the establishment of fire-tolerant forest pioneers, which synergically contributed to the expansion of forests. Conversely, savannas below this fire suppression threshold sustained a balance between trees and grasses through the grass-fire feedback mechanism. This hysteresis loop, particularly pronounced on clayey soils, suggests that the contrast between grassy savanna and young forests might represent alternative ecosystem states, although savannas with low woody biomass remained vulnerable to forest edge encroachment.

Construction and assessment of a fire risk index system for typical grasslands in Xinjiang, China

BackgroundFire hazards have a substantial impact on grassland ecosystems, and they are becoming more frequent and widespread because of global changes and human activities. However, there is still a lack of a widely accepted or practical method to evaluate grassland fire risk. In our study of typical grasslands in northern Xinjiang, we selected 18 evaluation indicators for grassland fires from three aspects of hazard, exposure, and vulnerability. Employing the analytic hierarchy process, weighted comprehensive evaluation method, and standard deviation classification, we determined the fire risk level thresholds, aiming to develop efficient and precise methods for assessing grassland fire risks, and ultimately created a grid-based map of grassland fire risk levels.ResultsThe risk level of grassland fires is determined by the combined spatial heterogeneity of fire-causing factors’ hazard and fire hazard-bearing bodies’ vulnerability and exposure. The hazard of grassland fire and fire hazard-bearing bodies’ vulnerability and exposure are dominated by medium level and medium–low level. Most areas of grassland fire risk levels are medium–low, medium, or medium–high risk, with few areas being high risk or low risk. The grassland fire risk exhibits a spatial distribution characterized by higher risks in the western and lower in the eastern; high and medium–high risk areas are primarily distributed in the western and some northeastern regions of the study area. The simulate result effectively represents the spatial distribution of grassland fire in the research area.ConclusionWe established a grassland fire risk index system and model, creating a spatial distribution map of grassland fire risk levels based on grid. Few grassland areas have fire risks and show a patchy distribution. The results generally reflect the spatial distribution pattern of grassland fire risks in the study area. This research provides technical support for scientifically formulating local grassland fire disaster prevention and relief strategies.

Efficacy of a novel oxygen scavenger mask in reducing local oxygen concentrations below the surgical fire risk threshold: an experimental proof-of-concept study

BackgroundThis study aims to evaluate the efficacy of an oxygen scavenging mask device in reducing local oxygen concentrations from nasal cannula ventilation compared to a standard open facial surgical field.MethodsThis is a controlled experiment using a custom-fabricated silicone midfacial oxygen scavenging device, SimMan airway management trainer manikin (Laerdal Medical, Stavanger, Norway), handheld oxygen detector (Forensics Detectors, Los Angeles, United States) and oxygen from a Datex Ohmeda Aisys Carestation anesthesia unit (GE HealthCare, Chicago, United States). Oxygen concentrations were measured at 18 facial landmarks (Fig. 1) with nasal cannula flow of 2, 4, and 6 L/min of 100% FiO2 in both masked and unmasked conditions (Fig. 2).ResultsThe mean oxygen concentration in the facial surgical field was 20.95% with the scavenger mask and 24.8% without (P < 0.001; two-tailed paired t-test). The unmasked condition was associated with suprathreshold oxygen concentration levels at 13 of 18 facial landmarks (Table 1). The device significantly reduced local oxygen concentration at 16 of 18 facial landmarks (Table 1). The device provided safe oxygen concentration levels at all three flow rates, and measured oxygen concentrations directly correlated with oxygen flow rate in the unmasked condition (Table 2).ConclusionsAn oxygen scavenger mask device reduced local oxygen concentrations from nasal cannula ventilation to below the 23% fire threshold in the entire facial surgical field external to the mask in these experiments. The device may reduce intraoperative fire risk in patients that require supplementary oxygen during surgery.

Nonlinearities and timescales in neural models of temporal interference stimulation.

In temporal interference (TI) stimulation, neuronal cells react to two interfering sinusoidal electric fields with a slightly different frequency ( , in the range of about 1-4 kHz, in the range of about 1-100 Hz). It has been previously observed that for the same input intensity, the neurons do not react to a purely sinusoidal signal at or . This study seeks a better understanding of the largely unknown mechanisms underlying TI neuromodulation. To this end, single-compartment models are used to simulate computationally the response of neurons to the sinusoidal and TI waveform. This study compares five different neuron models: Hodgkin-Huxley (HH), Frankenhaeuser-Huxley (FH), along with leaky, exponential, and adaptive-exponential integrate-and-fire (IF). It was found that IF models do not entirely reflect the experimental behavior while the HH and FH model did qualitatively replicate the observed neural responses. Changing the time constants and steady state values of the ion gates in the FH model alters the response to both the sinusoidal and TI signal, possibly reducing the firing threshold of the sinusoidal input below that of the TI input. The results show that in the modified (simplified) model, TI stimulation is not qualitatively impacted by nonlinearities in the current-voltage relation. In contrast, ion channels have a significant impact on the neuronal response. This paper offers insights into neuronal biophysics and computational models of TI stimulation.

The recovery of parabolic avalanches in spatially subsampled neuronal networks at criticality

Scaling relationships are key in characterizing complex systems at criticality. In the brain, they are evident in neuronal avalanches—scale-invariant cascades of neuronal activity quantified by power laws. Avalanches manifest at the cellular level as cascades of neuronal groups that fire action potentials simultaneously. Such spatiotemporal synchronization is vital to theories on brain function yet avalanche synchronization is often underestimated when only a fraction of neurons is observed. Here, we investigate biases from fractional sampling within a balanced network of excitatory and inhibitory neurons with all-to-all connectivity and critical branching process dynamics. We focus on how mean avalanche size scales with avalanche duration. For parabolic avalanches, this scaling is quadratic, quantified by the scaling exponent, χ = 2, reflecting rapid spatial expansion of simultaneous neuronal firing over short durations. However, in networks sampled fractionally, χ is significantly lower. We demonstrate that applying temporal coarse-graining and increasing a minimum threshold for coincident firing restores χ = 2, even when as few as 0.1% of neurons are sampled. This correction crucially depends on the network being critical and fails for near sub- and supercritical branching dynamics. Using cellular 2-photon imaging, our approach robustly identifies χ = 2 over a wide parameter regime in ongoing neuronal activity from frontal cortex of awake mice. In contrast, the common ‘crackling noise’ approach fails to determine χ under similar sampling conditions at criticality. Our findings overcome scaling bias from fractional sampling and demonstrate rapid, spatiotemporal synchronization of neuronal assemblies consistent with scale-invariant, parabolic avalanches at criticality.

Evaluation of mechanisms involved in regulation of intrinsic excitability by extracellular calcium in CA1 pyramidal neurons of rat.

It is well recognized that changes in the extracellular concentration of calcium ions influence the excitability of neurons, yet what mechanism(s) mediate these effects is still a matter of debate. Using patch-clamp recordings from rat hippocampal CA1 pyramidal neurons, we examined the contribution of G-proteins and intracellular calcium-dependent signaling mechanisms to changes in intrinsic excitability evoked by altering the extracellular calcium concentration from physiological (1.2 mM) to a commonly used experimental (2 mM) level. We find that the inhibitory effect on intrinsic excitability of calcium ions is mainly expressed as an increased threshold for action potential firing (with no significant effect on resting membrane potential) that is not blocked by either the G-protein inhibitor GDPβS or the calcium chelator BAPTA. Our results therefore argue that in the concentration range studied, G-protein coupled calcium-sensing receptors, non-selective cation conductances, and intracellular calcium signaling pathways are not involved in mediating the effect of extracellular calcium ions on intrinsic excitability. Analysis of the derivative of the action potential, dV/dt versus membrane potential, indicates a current shift towards more depolarized membrane potentials at the higher calcium concentration. Our results are thus consistent with a mechanism in which extracellular calcium ions act directly on the voltage-gated sodium channels by neutralizing negative charges on the extracellular surface of these channels to modulate the threshold for action potential activation.

Simple model for the prediction of seizure durations.

A simple model is used to simulate seizures in a population of spiking excitatory neurons experiencing a uniform effect from inhibitory neurons. A key feature is introduced into the model, i.e., a mechanism that weakens the firing thresholds. This weakening mechanism adds memory to the dynamics. We find a seizure-prone state in a "mode-switching" phase. In this phase, the system can suddenly switch from a "healthy" state with small scale-free avalanches to a "seizure" state with almost periodic large avalanches ("seizures"). Simulations of the model predict statistics for the average time spent in the seizure state (the seizure "duration") that agree with experiments and theoretical examples of similar behavior in neuronal systems. Our study points to. different connections between seizures and fracture and also offers an alternative view on the type of critical point controlling neuronal avalanches.

Low-power perovskite-based threshold switching memristor for artificial nociceptor

Organic-inorganic halide perovskites (OHPs) with good ion diffusion paths are effective functional materials for simulating biological neurons. In this work, we utilize the Ag diffusion threshold switching phenomenon in FAPbI3 films to investigate the nociceptor function. The threshold switching device exhibits a low threshold voltage (0.075 V) and a large characteristic switching ratio of 107 in volatile resistance switching, along with a minimum switching slope (SS< 2.6 mV/dec), and the device achieves low power consumption of 150 pW. Importantly, the nociceptor functions of threshold firing and sensitization have been successfully simulated based on the volatile threshold switching characteristics, which demonstrates the potential in practical neuromorphic applications.

Mimicking the retinal neuron functions by a photoresponsive single transistor with a double gate

To realize a low-cost neuromorphic visual system, employing an artificial neuron capable of mimicking the retinal neuron functions is essential. A photoresponsive single transistor neuron composed of a vertical silicon nanowire is proposed. Similar to retinal neurons, various photoresponsive characteristics of the single transistor neuron can be modulated by light intensity as well as wavelength and have a high responsivity to green light like the human eye. The device is designed with a cylindrical surrounding double-gate structure, enclosed by an independently controlled outer gate and inner gate. The outer gate has the function of selectively inhibiting neuron activity, which can mimic lateral inhibition of amacrine cells to ganglion cells, and the inner gate can be utilized for the adjustment of the firing threshold voltage, which can be used to mimic the regulation of photoresponsivity by horizontal cells for adaptive visual perception. Furthermore, a myelination function that controls the speed of information transmission is obtained according to the inherent asymmetric source/drain structure of a vertical silicon nanowire. This work can enable photoresponsive neuronal function using only a single transistor, providing a promising hardware implementation for building miniaturized neuromorphic vision systems at low cost.

Electrical signaling in three-dimensional bacterial biofilms using an agent-based fire-diffuse-fire model.

Agent-based models were used to describe electrical signaling in bacterial biofilms in three dimensions. Specifically, wavefronts of potassium ions in Escherichia coli biofilms subjected to stress from blue light were modeled from experimental data. Electrical signaling occurs only when the biofilms grow beyond a threshold size, which we have shown to vary with the K^{+} ion diffusivity, and the K^{+} ion threshold concentration, which triggered firing in the fire-diffuse-fire model. The transport of the propagating wavefronts shows superdiffusive scaling on time. K^{+} ion diffusivity is the main factor that affects the wavefront velocity. The K^{+} ion diffusivity and the firing threshold also affect the anomalous exponent for the propagation of the wavefront determining whether the wavefront is subdiffusive or superdiffusive. The geometry of the biofilm and its relation to the mean-square displacement (MSD) of the wavefront as a function of time was investigated for spherical, cylindrical, cubical, and mushroom-like structures. The MSD varied significantly with geometry; an additional regime to the kinetics occurred when the potassium wavefront leaves the biofilm. Adding cylindrical defects to the biofilm, which are known to occur in E. coli biofilms, also gave an extra kinetic regime to the wavefront MSD for the propagation through the defect.

Intrinsic and Extrinsic Tongue Muscles are Driven by Physiologically Distinct Motoneuron Pools

The hypoglossal motor nucleus innervates six of the seven tongue muscles responsible for wide-ranging behaviors including speech, breathing, and swallowing. Despite the task-specific nature of tongue movements, neurophysiologic research has historically treated hypoglossal motoneurons as a homogeneous population. Our previous work showed that hypoglossal motoneurons innervating specific tongue muscles had different firing thresholds and resting membrane potential. Here, we extend this work by comparing potassium conductance in motor neurons innervating the superior longitudinalis (SL; intrinsic) and genioglossus (GG; extrinsic), tongue muscles with opposing actions of tongue retraction and tongue protrusion, respectively. Experiments were performed using N=10 neonatal rat pups aged post-natal day 0-5 ( n=5 each of SL and GG). Motoneurons were back-labeled by injection of dextran rhodamine conjugated to Texas Red into either the SL or GG muscle. &gt; 24-hours after injection, animals were anesthetized on ice and decapitated. The brainstem and spinal cord were removed and 250 μm transverse slices of the medulla containing the hypoglossal nucleus were obtained. SL or GG motor neurons were visualized under a fluorescence microscope and resting membrane potential, rheobase current, frequency-current relation and potassium currents were recorded using whole-cell patch clamp. Statistical analysis revealed that SL motoneurons were ~11 mV more depolarized than GG motoneurons (resting membrane potential of -49 vs -60 mV, p&lt;0.05). Rheobase current (the minimal electrical current required to evoke an action potential) was greater in GG motoneurons than SL motoneurons (approximately 300 vs 150 pA, p&lt;0.05). SL motoneurons had a higher firing rate than GG motoneurons in response to current injection ( p&lt;0.05). Evaluation of neuronal potassium channel conductance showed that the magnitude of transient ( p &lt; 0.01) and sustained (p &lt; 0.01) potassium currents were greater in GG than SL motoneurons, consistent with our finding that resting membrane potential was more negative, and firing rate was slower, in GG than SL motoneurons. Finally, additional SL motoneuron recordings were performed to evaluate for potential sex differences in N=12 (6 male) rat pups aged post-natal day 0-5. Preliminary analysis revealed no significant difference in resting membrane potential between male (-49 mV) and female (-52 mV) SL motoneurons, suggesting that the properties of a specific hypoglossal motoneuron pool are consistent across sexes. Overall, these results demonstrate that GG motoneurons are less excitable than SL motoneurons, which supports the idea that intrinsic and extrinsic tongue muscles are driven by physiologically distinct motoneuron pools. This work has potential to guide development of therapeutics for disordered speech, breathing, and swallowing, all of which depend on proper neuromotor control of the tongue. This work was funded by NIH 5R01DC020889-02. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Neuro-inflammatory interactions as a mediator of the Exaggerated Exercise Pressor Reflex (EPR) in a mouse model of Peripheral Artery Disease

Introduction and rationale: The Exercise pressor reflex (EPR) is a physiological mechanism in which the contraction of skeletal muscle results in a rise in heart rate (HR) and mean arterial pressure (MAP). In patients with Peripheral Artery Disease (PAD), this reflex is exaggerated, leading to abnormally high elevations in blood pressure during exercise. These cardiovascular responses in patients with PAD have been linked to increased morbidity and mortality, thus limiting the prescription of exercise for these patients. Using a novel murine model of the EPR, our laboratory has demonstrated that mice with femoral artery ligation (a well-established model of PAD), exhibit augmented increases in MAP which is mediated by PIEZO2 positive, mechanosensitive afferent neurons. We have demonstrated that inhibition of PIEZO2 expressing channels normalizes the MAP response to exercise. Patients with PAD also display increased macrophage infiltration in their ischemia-injured limbs, indicating a pro-inflammatory environment. Sensory neurons have been reported to detect various signals produced by immune cells including IL-1β and TNFα. The immune-derived signals can sensitize the peripheral terminals of the sensory neurons, thereby reducing their firing threshold and increasing their responsiveness. Previous studies have also reported the enhancement of Piezo2-mediated mechanosensitive currents in the presence of inflammatory signals. Hypothesis: We, therefore, hypothesize that in mice with femoral artery ligation, muscle inflammation increases the expression and activation of resident ion channels (e.g., Piezo2) in mechanosensitive afferent neurons to mediate the exaggerated EPR in PAD.Study objective: To mechanistically investigate the interaction between muscle inflammation and Piezo2 in mechanosensitive afferent neurons.Methods: We performed sham surgery or ligation of the femoral artery ipsilaterally in C57BL/6 mice. After 72 hours, we harvested the gastrocnemius muscle for histological and molecular analyses.Data and summary and results: Our preliminary findings reveal that there is significantly increased expression of pro-inflammatory genes and infiltrating immune cells in the ischemic muscle when compared to non-ischemic muscle.Specifically, H&amp;E staining revealed the presence and accumulation of inflammatory cells, including macrophages, in the ischemic muscle compared to control, along with observed necrosis. Transcript analysis of the ischemic gastrocnemius muscle showed significantly increased IL-1β and TNFα, two pan-proinflammatory genes that encode cytokines released by macrophages. TNFα is known to induce the synthesis of adhesion molecules (E-selectin and ICAM-1) on endothelial cells, allowing leukocytes to adhere and cross the endothelial wall into the injured tissue. Indeed, we observed significantly increased ICAM-1 and E-selectin transcripts in the ischemic muscle compared to controls. MCP1, a well-established chemokine, was also significantly increased, further emphasizing the recruitment of leukocytes to the ischemic muscle. In addition, inducible NOS ( iNOS), which is known to be expressed in IL-1β- and TNFα-rich proinflammatory environment was also significantly increased in our FAL model compared to Sham. These data establish that the ischemic muscle of a femoral-artery ligated mouse has a high proinflammatory phenotype. We are currently exploring the impact of proinflammatory mediators on Piezo2 channel expression and activity, as well as the effect of macrophage depletion on Piezo2 in afferent neurons. The data from these studies will provide novel insights regarding the influence of neuroimmune interactions on cardiovascular responses to exercise in PAD. These data hold the potential to reveal innovative therapies enabling safe prescription of exercise, thus alleviating the burden of PAD, and improving the quality of life for those affected by this condition. Internal sources. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Change of voltage-gated sodium channel repertoire in skeletal muscle of a MuSK myasthenia gravis mouse model.

Muscle-specific kinase myasthenia gravis (MuSK MG) is caused by autoantibodies against MuSK in the neuromuscular junction (NMJ). MuSK MG patients have fluctuating, fatigable skeletal muscle weakness, in particular of bulbar muscles. Severity differs greatly between patients, in spite of comparable autoantibody levels. One explanation for inter-patient and inter-muscle variability in sensitivity might be variations in compensatory muscle responses. Previously, we developed a passive transfer mouse model for MuSK MG. In preliminary ex vivo experiments, we observed that muscle contraction of some mice, in particular those with milder myasthenia, had become partially insensitive to inhibition by μ-Conotoxin-GIIIB, a blocker of skeletal muscle NaV1.4 voltage-gated sodium channels. We hypothesised that changes in NaV channel expression profile, possibly co-expression of (μ-Conotoxin-GIIIB insensitive) NaV1.5 type channels, might lower the muscle fibre's firing threshold and facilitate neuromuscular synaptic transmission. To test this hypothesis, we here performed passive transfer in immuno-compromised mice, using 'high', 'intermediate' and 'low' dosing regimens of purified MuSK MG patient IgG4. We compared myasthenia levels, μ-Conotoxin-GIIIB resistance and muscle fibre action potential characteristics and firing thresholds. High- and intermediate-dosed mice showed clear, progressive myasthenia, not seen in low-dosed animals. However, diaphragm NMJ electrophysiology demonstrated almost equal myasthenic severities amongst all regimens. Nonetheless, low-dosed mouse diaphragms showed a much higher degree of μ-Conotoxin-GIIIB resistance. This was not explained by upregulation of Scn5a (the NaV1.5 gene), lowered muscle fibre firing thresholds or histologically detectable upregulated NaV1.5 channels. It remains to be established which factors are responsible for the observed μ-Conotoxin-GIIIB insensitivity and whether the NaV repertoire change is compensatory beneficial or a bystander effect.

Motor learning changes the axon initial segment of the spinal motoneuron.

We are studying the mechanisms of H-reflex operant conditioning, a simple form of learning. Modelling studies in the literature and our previous data suggested that changes in the axon initial segment (AIS) might contribute. To explore this, we used blinded quantitative histological and immunohistochemical methods to study in adult rats the impact of H-reflex conditioning on the AIS of the spinal motoneuron that produces the reflex. Successful, but not unsuccessful, H-reflex up-conditioning was associated with greater AIS length and distance from soma; greater length correlated with greater H-reflex increase. Modelling studies in the literature suggest that these increases may increase motoneuron excitability, supporting the hypothesis that they may contribute to H-reflex increase. Up-conditioning did not affect AIS ankyrin G (AnkG) immunoreactivity (IR), p-p38 protein kinase IR, or GABAergic terminals. Successful, but not unsuccessful, H-reflex down-conditioning was associated with more GABAergic terminals on the AIS, weaker AnkG-IR, and stronger p-p38-IR. More GABAergic terminals and weaker AnkG-IR correlated with greater H-reflex decrease. These changes might potentially contribute to the positive shift in motoneuron firing threshold underlying H-reflex decrease; they are consistent with modelling suggesting that sodium channel change may be responsible. H-reflex down-conditioning did not affect AIS dimensions. This evidence that AIS plasticity is associated with and might contribute to H-reflex conditioning adds to evidence that motor learning involves both spinal and brain plasticity, and both neuronal and synaptic plasticity. AIS properties of spinal motoneurons are likely to reflect the combined influence of all the motor skills that share these motoneurons. KEY POINTS: Neuronal action potentials normally begin in the axon initial segment (AIS). AIS plasticity affects neuronal excitability in development and disease. Whether it does so in learning is unknown. Operant conditioning of a spinal reflex, a simple learning model, changes the rat spinal motoneuron AIS. Successful, but not unsuccessful, H-reflex up-conditioning is associated with greater AIS length and distance from soma. Successful, but not unsuccessful, down-conditioning is associated with more AIS GABAergic terminals, less ankyrin G, and more p-p38 protein kinase. The associations between AIS plasticity and successful H-reflex conditioning are consistent with those between AIS plasticity and functional changes in development and disease, and with those predicted by modelling studies in the literature. Motor learning changes neurons and synapses in spinal cord and brain. Because spinal motoneurons are the final common pathway for behaviour, their AIS properties probably reflect the combined impact of all the behaviours that use these motoneurons.

Transforming growth factor-beta 1 enhances discharge activity of cortical neurons.

JOURNAL/nrgr/04.03/01300535-202502000-00031/figure1/v/2024-05-28T214302Z/r/image-tiff Transforming growth factor-beta 1 (TGF-β1) has been extensively studied for its pleiotropic effects on central nervous system diseases. The neuroprotective or neurotoxic effects of TGF-β1 in specific brain areas may depend on the pathological process and cell types involved. Voltage-gated sodium channels (VGSCs) are essential ion channels for the generation of action potentials in neurons, and are involved in various neuroexcitation-related diseases. However, the effects of TGF-β1 on the functional properties of VGSCs and firing properties in cortical neurons remain unclear. In this study, we investigated the effects of TGF-β1 on VGSC function and firing properties in primary cortical neurons from mice. We found that TGF-β1 increased VGSC current density in a dose- and time-dependent manner, which was attributable to the upregulation of Nav1.3 expression. Increased VGSC current density and Nav1.3 expression were significantly abolished by preincubation with inhibitors of mitogen-activated protein kinase kinase (PD98059), p38 mitogen-activated protein kinase (SB203580), and Jun NH2-terminal kinase 1/2 inhibitor (SP600125). Interestingly, TGF-β1 significantly increased the firing threshold of action potentials but did not change their firing rate in cortical neurons. These findings suggest that TGF-β1 can increase Nav1.3 expression through activation of the ERK1/2-JNK-MAPK pathway, which leads to a decrease in the firing threshold of action potentials in cortical neurons under pathological conditions. Thus, this contributes to the occurrence and progression of neuroexcitatory-related diseases of the central nervous system.

Low Latency and Sparse Computing Spiking Neural Networks With Self-Driven Adaptive Threshold Plasticity.

Spiking neural networks (SNNs) have captivated the attention worldwide owing to their compelling advantages in low power consumption, high biological plausibility, and strong robustness. However, the intrinsic latency associated with SNNs during inference poses a significant challenge, impeding their further development and application. This latency is caused by the need for spiking neurons to collect electrical stimuli and generate spikes only when their membrane potential exceeds a firing threshold. Considering the firing threshold plays a crucial role in SNN performance, this article proposes a self-driven adaptive threshold plasticity (SATP) mechanism, wherein neurons autonomously adjust the firing thresholds based on their individual state information using unsupervised learning rules, of which the adjustment is triggered by their own firing events. SATP is based on the principle of maximizing the information contained in the output spike rate distribution of each neuron. This article derives the mathematical expression of SATP and provides extensive experimental results, demonstrating that SATP effectively reduces SNN inference latency, further reduces the computation density while improving computational accuracy, so that SATP facilitates SNN models to be with low latency, sparse computing, and high accuracy.