Spike Frequency Research Articles

Sleep and circadian disruptors: Unhealthy noise and light levels for hospitalized pediatric patients.

Noise and light levels during hospitalizations can disrupt sleep and circadian health, resulting in worsened health outcomes. This study describes patterns of noise and light for inpatient children undergoing stem cell transplants. Objective meters tracked noise and light levels every minute for 6 months. Median overnight sound was 55 dB (equivalent to conversational speech). There were 3.4 loud noises (>80 dB) per night on average. Children spent 62% of the 24-h cycle in nonoptimal lighting, with daytime light dimmer than recommended 98% of the time. Over the 6-month period, the lowest overnight noise level recorded exceeded World Health Organization recommendations for sleep, with frequent spikes into ranges known to cause wakings. During the day, children were rarely exposed to light sufficient to preserve healthy circadian rhythms. Hospitals should address systematic environmental and workflow disruptors to improve the sleep and circadian health of patients, particularly those already at elevated risk for health morbidities.

Artificial Neurons Using Ag−In−Zn−S/Sericin Peptide‐Based Threshold Switching Memristors for Spiking Neural Networks

AbstractMemristive devices with threshold switching characteristics can be effectively utilized to mimic biological neurons acting as one of the key building blocks for constructing advanced hardware neural networks. In this work, the emulation of leaky integrate‐and‐fire memristive neuron is realized in one single cell with Ag/Ag−In−Zn−S/silk sericin/W architecture without the need for additional auxiliary circuits. The studied devices demonstrate excellent electrical properties, such as stably repeatable threshold switching, concentratedly low threshold voltage (≈0.4 V), and relatively small device‐to‐device variation. In addition, multiple neural features, such as leaky integrate‐and‐fire neuron functionality and strength‐modulated spike frequency characteristic, have been successfully emulated owing to the forming‐free volatile threshold switching effect. The stable volatile threshold switching behaviors and regular firing event may be attributed to the controllable metallic Ag filamentary mechanism. Furthermore, a solid accuracy of 91.44% of the pattern recognition of Modified National Institute of Standards and Technology (MNIST) data is obtained via a trained spiking neural network (SNN) based on the leaky integrate‐and‐fire behavior of sericin‐based device. These achievements shed light on the fact that employing sericin biomaterials has great application potential in advanced neuromorphic computation.

Self-adaptation of networks of nonidentical pulse-coupled excitatory and inhibitory oscillators in the presence of distance-related delays to achieve frequency synchronization.

We show that a network of nonidentical nodes, with excitable dynamics, pulse-coupled, with coupling delays depending on the Euclidean distance between nodes, is able to adapt the topology of its connections to obtain spike frequency synchronization. The adapted network exhibits remarkable properties: sparse, anticluster, necessary presence of a minimum of inhibitory nodes, predominance of connections from inhibitory nodes over those from excitatory nodes, and finally spontaneous spatial structuring of the inhibitory projections: the furthest are the most intense. In a second step, we discuss the possible implications of our findings to neural systems.

Role of garbage classification in air pollution improvement of a municipal solid waste disposal base

Assessing the impact of garbage classification on air pollution in rapidly developing economic regions is particularly necessary in light of the current policy trends. We evaluated the resulting changes in air pollution levels before and after garbage classification based on a three-year field observation using high-resolution online instruments in a municipal solid waste comprehensive disposal base. A targeted scheme is proposed to analyze the variation characteristics of major sources in a complex multi-source environment (Environments with multiple sources of pollution). We found that the concentrations of hydrogen sulfide (H2S) and volatile organic compounds (VOCs) in ambient air decreased by 48% and 43% respectively after garbage classification, and their spike frequency was controlled at approximately 0.01. The average H2S and VOC concentrations were generally low during the daytime, but relatively high during the nighttime because of meteorology and photochemistry. The ozone formation potential of the base decreased by 56%. Alternatively, emissions from transportation and combustion sources increased, while landfill pollution decreased owing to changes in the method of waste disposal. This finding suggests that garbage classification is an effective means of improving the air quality. This new scheme has a good potential in actual research scenarios.

Laws of taxation for multicellular organisms: The economics of sleep

In macro-public finance, the Ramsey rule (RR) concerns variable taxation to maximize social welfare and economic efficiency in a purely competitive monopolistic system. To extract tax revenue with the least loss of utility to the representative individual, RR dictates that optimal, proportionate taxes should be such as to diminish in the same proportion the production of each commodity taxed. The sources of supply that are inelastic, i.e., necessities/utilities, must be taxed more. We hypothesize that the Ramsey's economical approach might provide a general mechanism to investigate far-flung biological issues, such as preys/predators dynamics, food restriction in ecological niches, local changes in blood flow in rival or complementary organs of multicellular organisms. In particular, RR suggests a quantifiable relationship between the physiological decrease in cortical spike frequency occurring during sleep and energy consumption. Since small decreases in spike frequency during sleep are correlated with large decreases in the amount of consumed ATP, the brain could be considered an inelastic commodity which can be “taxed” more than other organs, allowing the whole organism to spare energy. Shedding light on the energy budget of the central nervous system, RR improves our knowledge of cerebral perfusion during sensory-evoked responses and tissue hypoxia caused by decreased blood flow, suggesting that energy from outside can be provided to counteract brain ischemia. In sum, the economical approach provided by Ramsey stands for a useful methodological tool that could be used in biological contexts to investigate the dynamical correlations among different organs in multicellular organisms.

Three-dimensional Simulations of Massive Stars. II. Age Dependence

We present 3D full star simulations, reaching up to 90% of the total stellar radius, for three 7 M ⊙ stars of different ages: zero-age main sequence (ZAMS), mid–main sequence (midMS), and terminal-age main sequence (TAMS). A comparison with several theoretical prescriptions shows that the generation spectra for all three ages are dominated by convective plumes. Two distinct overshooting layers are observed, with most plumes stopped within the layer situated directly above the convective boundary; overshooting to the second, deeper layer becomes progressively more infrequent with increasing stellar age. Internal gravity wave (IGW) propagation is significantly impacted in the midMS and TAMS models as a result of some IGWs getting trapped within their Brunt–Väisälä frequency spikes. A fundamental change in the wave structure across radius is also observed, driven by the effect of density stratification on IGW propagation causing waves to become evanescent within the radiative zone, with older stars being affected more strongly. We find that the steepness of the frequency spectrum at the surface increases from ZAMS to the older models, with older stars also showing more modes in their spectra.

Structural and functional changes of deep layer pyramidal neurons surrounding microelectrode arrays implanted in rat motor cortex.

Devices capable of recording or stimulating neuronal signals have created new opportunities to understand normal physiology and treat sources of pathology in the brain. However, it is possible that the tissue response to implanted electrodes may influence the nature of the signals detected or stimulated. In this study, we characterized structural and functional changes in deep layer pyramidal neurons surrounding silicon or polyimide-based electrodes implanted in the motor cortex of rats. Devices were captured in 300µm-thick tissue slices collected at the 1 or 6 week time point post-implantation, and individual neurons were assessed using a combination of whole-cell electrophysiology and 2-photon imaging. We observed disrupted dendritic arbors and a significant reduction in spine densities in neurons surrounding devices. These effects were accompanied by a decrease in the frequency of spontaneous excitatory post-synaptic currents, a reduction in sag amplitude, an increase in spike frequency adaptation, and an increase in filopodia density. We hypothesize that the effects observed in this study may contribute to the signal loss and instability that often accompany chronically implanted electrodes. STATEMENT OF SIGNIFICANCE: Implanted electrodes in the brain can be used to treat sources of pathology and understand normal physiology by recording or stimulating electrical signals generated by local neurons. However, a foreign body response following implantation undermines the performance of these devices. While several studies have investigated the biological mechanisms of device-tissue interactions through histology, transcriptomics, and imaging, our study is the first to directly interrogate effects on the function of neurons surrounding electrodes using single-cell electrophysiology. Additionally, we provide new, detailed assessments of the impacts of electrodes on the dendritic structure and spine morphology of neurons, and we assess effects for both traditional (silicon) and newer polymer electrode materials. These results reveal new potential mechanisms of electrode-tissue interactions.

Spinal motoneurons respond aberrantly to serotonin in a rabbit model of cerebral palsy.

Cerebral palsy (CP) is caused by a variety of factors that damage the developing central nervous system. Impaired motor control, including muscle stiffness and spasticity, is the hallmark of spastic CP. Rabbits that experience hypoxic-ischaemic (HI) injury in utero (at 70%-83% gestation) are born with muscle stiffness, hyperreflexia and, as recently discovered, increased 5-HT in the spinal cord. To determine whether serotonergic modulation of spinal motoneurons (MNs) contributes to motor deficits, we performed ex vivo whole cell patch clamp in neonatal rabbit spinal cord slices at postnatal day (P) 0-5. HI MNs responded to the application of α-methyl 5-HT (a 5-HT1 /5-HT2 receptor agonist) and citalopram (a selective 5-HT reuptake inhibitor) with increased amplitude and hyperpolarization of persistent inward currents and hyperpolarized threshold voltage for action potentials, whereas control MNs did not exhibit any of these responses. Although 5-HT similarly modulated MN properties of HI motor-unaffected and motor-affected kits, it affected sag/hyperpolarization-activated cation current (Ih ) and spike frequency adaptation only in HI motor-affected MNs. To further explore the differential sensitivity of MNs to 5-HT, we performed immunostaining for inhibitory 5-HT1A receptors in lumbar spinal MNs at P5. Fewer HI MNs expressed the 5-HT1A receptor compared to age-matched control MNs. This suggests that HI MNs may lack a normal mechanism of central fatigue, mediated by 5-HT1A receptors. Altered expression of other 5-HT receptors (including 5-HT2 ) likely also contributes to the robust increase in HI MN excitability. In summary, by directly exciting MNs, the increased concentration of spinal 5-HT in HI-affected rabbits can cause MN hyperexcitability, muscle stiffness and spasticity characteristic of CP. Therapeutic strategies that target serotonergic neuromodulation may be beneficial to individuals with CP. KEY POINTS: We used whole cell patch clamp electrophysiology to test the responsivity of spinal motoneurons (MNs) from neonatal control and hypoxia-ischaemia (HI) rabbits to 5-HT, which is elevated in the spinal cord after prenatal HI injury. HI rabbit MNs showed a more robust excitatory response to 5-HT than control rabbit MNs, including hyperpolarization of the persistent inward current and threshold voltage for action potentials. Although most MN properties of HI motor-unaffected and motor-affected kits responded similarly to 5-HT, 5-HT caused larger sag/hyperpolarization-activated cation current (Ih ) and altered repetitive firing patterns only in HI motor-affected MNs. Immunostaining revealed that fewer lumbar MNs expressed inhibitory 5-HT1A receptors in HI rabbits compared to controls, which could account for the more robust excitatory response of HI MNs to 5-HT. These results suggest that elevated 5-HT after prenatal HI injury could trigger a cascade of events that lead to muscle stiffness and altered motor unit development.

First Records of Heartbeats via ECG in a Stingless Bee, Melipona flavolineata (Apidae, Meliponini), during Contention Stress Using Isoflurane as an Anesthetic.

The hemodynamic activity of Melipona flavolineata workers was evaluated during restraint stress for a period of 30 min. The observed parameters were power variation in the elapsed time, and subsequently, six periods of one second were divided and called A, B, C, D, E and F; in each period, the electrocardiographic parameters were evaluated: spike frequency, amplitude, spike intervals and spike duration. The experiment was carried out with eight worker bees of M. flavolineata, for which electrodes of a nickel-chromium alloy were made. The bees were previously anesthetized with isoflurane and properly contained and fixed in a base for stereotaxis in which the electrode was implanted. All these procedures were performed inside a Faraday cage. The results showed power oscillations during the recording, with the highest energy level being between 300 and 600 s. Spike frequency, spike amplitude, interval between spikes and spike duration parameters underwent changes during the restraint stress period. Thus, the cardiac activity of M. flavolineata can be used as a biomarker and can be used to clarify physiological issues or alterations caused by toxic agents and indicate risk factors for these animals.

Hyperpolarization-activated cation channels shape the spiking frequency preference of human cortical layer 5 pyramidal neurons.

Discerning the contribution of specific ionic currents to complex neuronal dynamics is a difficult, but important, task. This challenge is exacerbated in the human setting, although the widely-characterized uniqueness of the human brain as compared to preclinical models necessitates the direct study of human neurons. Neuronal spiking frequency preference is of particular interest given its role in rhythm generation and signal transmission in cortical circuits. Here, we combine the frequency-dependent gain (FDG), a measure of spiking frequency preference, and novel in silico analyses to dissect the contributions of individual ionic currents to the suprathreshold features of human L5 neurons captured by the FDG. We confirm that a contemporary model of such a neuron, primarily constrained to capture subthreshold activity driven by the hyperpolarization-activated cyclic nucleotide gated (h-) current, replicates key features of the in vitro FDG both with and without h-current activity. With the model confirmed as a viable approximation of the biophysical features of interest, we applied new analysis techniques to quantify the activity of each modeled ionic current in the moments prior to spiking, revealing unique dynamics of the h-current. These findings motivated patch-clamp recordings in analogous rodent neurons to characterize their FDG, which confirmed that a biophysically-detailed model of these neurons captures key inter-species differences in the FDG. These differences are correlated with distinct contributions of the h-current to neuronal activity. Together, this interdisciplinary and multi-species study provides new insights directly relating the dynamics of the h-current to suprathreshold spiking frequency preference in human L5 neurons.Significance StatementUnderstanding the contributions of individual ionic currents to neuronal activity is vital, considering the established role of ion channel modifications in neuropsychiatric conditions. We combine in vitro characterization of the spiking frequency preference of human L5 cortical pyramidal neurons via the frequency-dependent gain (FDG) with new analyses of a biophysically-detailed computational model of such a neuron to delineate the connection between the dynamics of the hyperpolarization-activated cyclic nucleotide gated (h-) current prior to spiking and key properties of the FDG. By further determining that both these FDG properties and h-current dynamics are distinct in analogous rodent neurons, we provide convincing evidence for the key role of the h-current in the suprathreshold frequency preference of human L5 cortical neurons.

Simulation analysis of visual perception model based on pulse coupled neural network

Pulse-coupled neural networks perform well in many fields such as information retrieval, depth estimation and object detection. Based on pulse coupled neural network (PCNN) theory, this paper constructs a visual perception model framework and builds a real image reproduction platform. The model firstly analyzes the structure and generalization ability of neural network multi-class classifier, uses the minimax criterion of feature space as the splitting criterion of visual perception decision node, which solves the generalization problem of neural network learning algorithm. In the simulation process, the initial threshold is optimized by the two-dimensional maximum inter-class variance method, and in order to improve the real-time performance of the algorithm, the fast recurrence formula of neural network is derived and given. The PCNN image segmentation method based on genetic algorithm is analyzed. The genetic algorithm improves the loop termination condition and the adaptive setting of model parameters of PCNN image segmentation algorithm, but the PCNN image segmentation algorithm still has the problem of complexity. In order to solve this problem, this paper proposed an IGA-PCNN image segmentation method combining the improved algorithm and PCNN model. Firstly, it used the improved immune genetic algorithm to adaptively obtain the optimal threshold, and then replaced the dynamic threshold in PCNN model with the optimal threshold, and finally used the pulse coupling characteristics of PCNN model to complete the image segmentation. From the coupling characteristics of PCNN, junction close space of image and gray level characteristics, it determined the local gray mean square error of image connection strength coefficient. The feature extraction and object segmentation properties of PCNN come from the spike frequency of neurons, and the number of neurons in PCNN is equal to the number of pixels in the input image. In addition, the spatial and gray value differences of pixels should be considered comprehensively to determine their connection matrix. Digital experiments show that the multi-scale multi-task pulse coupled neural network model can shorten the total training time by 17 h, improve the comprehensive accuracy of the task test data set by 1.04%, and shorten the detection time of each image by 4.8 s compared with the series network model of multiple single tasks. Compared with the traditional PCNN algorithm, it has the advantages of fast visual perception and clear target contour segmentation, and effectively improves the anti-interference performance of the model.

Suppression and frequency control of repetitive spiking in the FitzHugh-Nagumo model.

The FitzHugh-Nagumo equationis a simple model equationthat exhibits spiking. The output signal of a neuron is represented in the spiking frequency or firing rate. We consider a few control methods for spiking from the viewpoint of nonlinear dynamics. The repetitive spiking can be suppressed in the FitzHugh-Nagumo model by the periodic sinusoidal force with high frequency. We study the transition to the suppressed state numerically and perform a linear stability analysis to understand the suppression of the spiking. Next, we study coupled FitzHugh-Nagumo equations. We find that the periodic forcing makes the system chaotic, and the desynchronization induced by chaos weakens the total output of spiking in a certain parameter range. Finally, we propose a method of feedback control for the spiking frequency. We can get the desired spiking and bursting frequency using this feedback control. The feedback control method is analyzed using a mapping for the input.

Early classification of Alzheimer's disease phenotype based on hippocampal electrophysiology in the TgF344-AD rat model

The hippocampus plays a vital role in navigation, learning, and memory, and is affected in Alzheimer's disease (AD). This study investigated the classification of AD-transgenic rats versus wild-type littermates using electrophysiological activity recorded from the hippocampus at an early, presymptomatic stage of the disease (6months old) in the TgF344-AD rat model. The recorded signals were filtered into low frequency (LFP) and high frequency (spiking activity) signals, and machine learning classifiers were employed to identify the rat genotype (TG vs. WT). By analyzing specific frequency bands in the low frequency signals and calculating distance metrics between spike trains in the high frequency signals, accurate classification was achieved. Gamma band power emerged as a valuable signal for classification, and combining information from both low and high frequency signals improved the accuracy further. These findings provide valuable insights into the early stage effects of AD on different regions of the hippocampus.

Preventing development of post-stroke hyperexcitability by optogenetic or pharmacological stimulation of cortical excitatory activity

Stroke is the most common cause of acquired epilepsy, but treatment for preventing the development of post-stroke epilepsy is still unavailable. Since stroke results in neuronal damage and death as well as initial loss of activity in the affected brain region, homeostatic plasticity may be trigged and contribute to an increase in network hyperexcitability that underlies epileptogenesis. Correspondingly, enhancing brain activity may inhibit hyperexcitability from enhanced homeostatic plasticity and prevent post-stroke epileptogenesis. To test these hypotheses, we first used in vivo two-photon and mesoscopic imaging of activity of cortical pyramidal neurons in Thy1-GCaMP6 transgenic mice to determine longitudinal changes in excitatory activity after a photothrombotic ischemic stroke. At 3-days post-stroke, there was a significant loss of neuronal activity in the peri-injury area as indicated by reductions in the frequency of calcium spikes and percentage of active neurons, which recovered to baseline level at day 7, supporting a homeostatic activity regulation of the surviving neurons in the peri-injury area. We further used optogenetic stimulation to specifically stimulate activity of pyramidal neurons in the peri-injury area of Thy-1 channelrhodopsin transgenic mice from day 5 to day 15 after stroke. Using pentylenetetrazole test to evaluate seizure susceptibility, we showed that stroke mice are more susceptible to Racine stage V seizures (time latency 54.3 ± 12.9 min) compared to sham mice (107.1 ± 13.6 min), but optogenetic stimulation reversed the increase in seizure susceptibility (114.0 ± 9.2 min) in mice with stroke. Similarly, administration of D-cycloserine, a partial N-methyl-d-aspartate (NMDA) receptor agonist that can mildly enhance neuronal activity without causing post-stroke seizure, from day 5 to day 15 after a stroke significantly reversed the increase in seizure susceptibility. The treatment also resulted in an increased survival of glutamic acid decarboxylase 67 (GAD67) positive interneurons and a reduced activation of glial fibrillary acidic protein (GFAP) positive reactive astrocytes. Thus, this study supports the involvement of homeostatic activity regulation in the development of post-stroke hyperexcitability and potential application of activity enhancement as a novel strategy to prevent post-stroke late-onset seizure and epilepsy through regulating cortical homeostatic plasticity.

Subclinical Epileptiform Activity in Dementia with Lewy Bodies.

Patients with dementia with Lewy bodies (DLB) have a higher probability of seizures than in normal aging and in other types of neurodegenerative disorders. Depositions of α-synuclein, a pathological hallmark of DLB, can induce network excitability, which can escalate into seizure activity. Indicator of seizures are epileptiform discharges as observed using electroencephalography (EEG). However, no studies have so far investigated the occurrence of interictal epileptiform discharges (IED) in patients with DLB. To investigate if IED as measured with ear-EEG occurs with a higher frequency in patients with DLB compared to healthy controls (HC). In this longitudinal observational exploratory study, 10 patients with DLB and 15 HC were included in the analysis. Patients with DLB underwent up to three ear-EEG recordings, each lasting up to 2 days, over a period of 6 months. At baseline, IED were detected in 80% of patients with DLB and in 46.7% of HC. The spike frequency (spikes or sharp waves/24 hours) was significantly higher in patients with DLB as compared to HC with a risk ratio of 2.52 (CI, 1.42-4.61; P-value = 0.001). Most IED occurred at night. Long-term outpatient ear-EEG monitoring detects IED in most patients with DLB with an increased spike frequency compared to HC. This study extends the spectrum of neurodegenerative disorders in which epileptiform discharges occurs at an elevated frequency. It is possible that epileptiform discharges are, therefore, a consequence of neurodegeneration. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Robust bursting dynamics based on the interaction of persistent Na and Na/K pump currents: a dynamic clamp approach.

Life-supporting rhythmic motor functions like heart-beating in invertebrates and breathing in vertebrates require an indefatigable generation of a robust rhythm by specialized oscillatory circuits, Central Pattern Generators (CPGs). These CPGs should be sufficiently flexible to adjust to environmental changes and behavioral goals. Continuous self-sustained operation of bursting neurons requires intracellular Na+ concentration to remain in a functional range and to have checks and balances of the Na+ fluxes met on a cycle-to-cycle basis during bursting. We hypothesize that at a high excitability state, the interaction of the Na+/K+ pump current, Ipump and persistent Na+ current, INaP, produces a mechanism supporting functional bursting. INaP is a low voltage-activated inward current that initiates and supports the bursting phase. This current does not inactivate and is a significant source of Na+ influx. Ipump is an outward current activated by [Na+]i and is the major source of Na+ efflux. Both currents are active and counteract each other between and during bursts. We apply a combination of electrophysiology, computational modeling, and dynamic clamp to investigate the role of Ipump and INaP in the leech heartbeat CPG interneurons (HN neurons). Applying dynamic clamp to introduce additional Ipump and INaP into the dynamics of living synaptically isolated HN neurons in real-time, we show that their joint increase produces transition into a new bursting regime characterized by higher spike frequency and larger amplitude of the membrane potential oscillations. Further increase of Ipump speeds up this rhythm by shortening burst duration and interburst interval.Significance statementCentral Pattern Generators (CPGs) are neuronal networks that control rhythmic motor functions such as breathing and walking. Synaptic and membrane properties enable participating neurons to generate functional bursting patterns; intracellular Na+ concentration reflects the intensity of the spiking activity during bursts and regulates the Na+/K+ pump current playing a critical role in sculpting these patterns by providing negative feedback in response to excitation. Here, we show that the dynamic interaction of Na+/K+ pump current with persistent Na+ current offers a mechanism for the generation of a robust and flexible pattern of bursting activity. We provide physiological data and present a simple model that explains the underlying dynamics of the oscillatory mechanism.

Neurophysiology State Dynamics Underlying Acute Neurologic Recovery After Cardiac Arrest.

Epileptiform activity and burst suppression are neurophysiology signatures reflective of severe brain injury after cardiac arrest. We aimed to delineate the evolution of coma neurophysiology feature ensembles associated with recovery from coma after cardiac arrest. Adults in acute coma after cardiac arrest were included in a retrospective database involving 7 hospitals. The combination of 3 quantitative EEG features (burst suppression ratio [BSup], spike frequency [SpF], and Shannon entropy [En]) was used to define 5 distinct neurophysiology states: epileptiform high entropy (EHE: SpF ≥4 per minute and En ≥5); epileptiform low entropy (ELE: SpF ≥4 per minute and <5 En); nonepileptiform high entropy (NEHE: SpF <4 per minute and ≥5 En); nonepileptiform low entropy (NELE: SpF <4 per minute and <5 En), and burst suppression (BSup ≥50% and SpF <4 per minute). State transitions were measured at consecutive 6-hour blocks between 6 and 84 hours after return of spontaneous circulation. Good neurologic outcome was defined as best cerebral performance category 1-2 at 3-6 months. One thousand thirty-eight individuals were included (50,224 hours of EEG), and 373 (36%) had good outcome. Individuals with EHE state had a 29% rate of good outcome, while those with ELE had 11%. Transitions out of an EHE or BSup state to an NEHE state were associated with good outcome (45% and 20%, respectively). No individuals with ELE state lasting >15 hours had good recovery. Transition to high entropy states is associated with an increased likelihood of good outcome despite preceding epileptiform or burst suppression states. High entropy may reflect mechanisms of resilience to hypoxic-ischemic brain injury.

Spike performance transgression degree and frequency in F2 winter bread wheat hybrids

Purpose and Objectives. To analyze the spike performance transgression degree and frequency in F2 winter bread wheat hybrids.&#x0D; Materials and Methods. The study was carried out in the Laboratory of Genetic Resources of Cereals of the Plant Production Institute named after V.Ya. Yuriev of NAAS in 2019–2021. Thirty 30 F2 hybrids from diallel crossings and 20 F2 hybrids from tester crossings were investigated. The experiments were carried out in accordance with the requirements for field experiments in breeding. F2 hybrids and their parents were sown with a manual single-row planter within the optimal timeframe. The row length was 1 m; the interrow distance was 20 cm; the depth was 4–6 cm; wheat was sown after bare fallow. Twenty seeds per row were sown. Data were statistically processed, as B.A. Dospekhov recommended. The transgression degrees and frequencies for quantitative traits were determined by the formulae proposed by H.S. Voskresenskaya and V.I. Shpota.&#x0D; Results and Discussion. Analyzing the F2 hybrids from diallel crossings, positive transgressions of the “pike length” trait were found in all the analyzed hybrids. The highest degree of transgressions was recorded for Ladyzhynka / Dyvo (Td = 18.0%) and Vodohrai Bilotserkivskyi / Ladyzhynka (Td = 12.1%); the highest frequency of transgressions of this trait was observed in Ladyzhynka / Dyvo (Tf = 89.7%) and Khvala / Dyvo (Tf = 85.0%). The maximum degree of transgressions for the kernel number per spike was detected in Vodohrai Bilotserkivskyi / Khvala (Td = 12.9%), and the maximum frequency of transgressions of this trait was noted in Kubok / Ladyzhynka (Tf = 50.7%). Kubok / Dyvo was selected due to degree and frequency of spike weight transgressions (Td = 25.7%; Tf = 54.3%). The maximum advantage over the better parent in terms of the spikelet number per spike and the maximum frequency of transgressions of this trait were noted in Vodohrai Bilotserkivskyi / Khvala (Td = 18.6%; Tf = 88.7%). The maximum advantage over the better parent in terms of kernel weight per spike was detected in Kubok / Dyvo (Td = 27.7%); but the highest frequency of transgressions of this trait was recorded for Kubok / Korovaina (Tf = 54.3%). As to thousand kernel transgression degree and frequency, Kubok / Dyvo was distinguished (Td = 12.4%; Tf = 82.7%).&#x0D; Analyzing the F2 hybrids from tester crossings, the Khvala / Kanada (Td = 10.7%) and Dyvo / Arktis (Td = 10.6%) hybrids were distinguished by spike length transgression degree; Khvala / Kanada was noticeable for transgression frequency for this trait (Tf = 79.7%). As to the spikelet number per spike, the highest degree of transgressions were observed in Khvala / Viglanka (Td = 16.4%) and the highest frequency of transgressions - in Khvala / Viglanka (Tf = 51.3%) and Vodohrai Bilotserkivskyi / Arktis (Tf = 51.3%). The maximum advantage over the better parent in terms of the kernel number per spike was detected in Ladyzhynka / Arktis (Td = 13.6%); this combination was also noticeable for the maximum frequency of transgressions of this trait (Tf = 47.0%). By spike weight transgression degree, Ladyzhinka / Arktis was distinguished (Td = 26.2%); by transgression frequency for this trait – Vodohrai Bilotserkivskyi / Kanada (Tf = 60.7 %). The maximum degree of transgressions of kernel weight per spike was observed in Ladyzhynka / Arktis (Td = 29.7%) and the maximum frequency of transgressions of this trait - in Dyvo / Viglanka (Tf = 55.0%). By thousand kernel weight transgression degree, Dyvo / Donera (Td = 11.9%) and Vodohrai Bilotserkivskyi / Viglanka (Td = 11.2%) were selected and by transgression frequency for this trait - Vodohrai Bilotserkivskyi / Viglanka (Tf = 92.0%).&#x0D; Conclusions. The degree of positive transgressions of spike length among F2 hybrids from diallel crossings averaged 6.9% and the frequency – 52.6%; for the spikelet number per spike the corresponding parameters were 7.8% and 44.8%; for the kernel number per spike – 5.4% and 21.4%; for spike weight – 6.3% and 23.4%; for kernel weight per spike – 6.9% and 22.5%; and for thousand kernel weight – 0.1% and 31.2%. The degree of positive transgressions of spike length among F2 hybrids from tester crossings averaged 4.6% and the frequency – 36.5%; for the spikelet number per spike the corresponding parameters were 6.9% and 30.5%; for the kernel number per spike – 5.4% and 26.0%; for spike weight – 10.1% and 30.2%; for kernel weight per spike – 11.8% and 30.3%; and for thousand kernel weight – 2.4% and 34.0%.&#x0D;

Intracellular Loop in the Brain Isoforms of Anoctamin 2 Channels Regulates Calcium-dependent Activation.

Anoctamin 2 (ANO2 or TMEM16B), a calcium-activated chloride channel (CaCC), performs diverse roles in neurons throughout the central nervous system. In hippocampal neurons, ANO2 narrows action potential width and reduces postsynaptic depolarization with high sensitivity to Ca2+ at relatively fast kinetics. In other brain regions, including the thalamus, ANO2 mediates activity-dependent spike frequency adaptations with low sensitivity to Ca2+ at relatively slow kinetics. How this same channel can respond to a wide range of Ca2+ levels remains unclear. We hypothesized that splice variants of ANO2 may contribute to its distinct Ca2+ sensitivity, and thus its diverse neuronal functions. We identified two ANO2 isoforms expressed in mouse brains and examined their electrophysiological properties: isoform 1 (encoded by splice variants with exons 1a, 2, 4, and 14) was expressed in the hippocampus, while isoform 2 (encoded by splice variants with exons 1a, 2, and 4) was broadly expressed throughout the brain, including in the cortex and thalamus, and had a slower calcium-dependent activation current than isoform 1. Computational modeling revealed that the secondary structure of the first intracellular loop of isoform 1 forms an entrance cavity to the calcium-binding site from the cytosol that is relatively larger than that in isoform 2. This difference provides structural evidence that isoform 2 is involved in accommodating spike frequency, while isoform 1 is involved in shaping the duration of an action potential and decreasing postsynaptic depolarization. Our study highlights the roles and molecular mechanisms of specific ANO2 splice variants in modulating neuronal functions.

Modeling Long-term Spike Frequency Adaptation in SA-I Afferent Neurons Using an Izhikevich-based Biological Neuron Model.

To develop a biomimetic artificial tactile sensing system capable of detecting sustained mechanical touch, we propose a novel biological neuron model (BNM) for slowly adapting type I (SA-I) afferent neurons. The proposed BNM is designed by modifying the Izhikevich model to incorporate long-term spike frequency adaptation. Adjusting the parameters renders the Izhikevich model describing various neuronal firing patterns. We also search for optimal parameter values for the proposed BNM to describe firing patterns of biological SA-I afferent neurons in response to sustained pressure longer than 1-second. We obtain the firing data of SA-I afferent neurons for six different mechanical pressure ranging from 0.1 mN to 300 mN from the ex-vivo experiment on SA-I afferent neurons in rodents. Upon finding the optimal parameters, we generate spike trains using the proposed BNM and compare the resulting spike trains to those of biological SA-I afferent neurons using the spike distance metrics. We verify that the proposed BNM can generate spike trains showing long-term adaptation, which is not achievable by other conventional models. Our new model may offer an essential function to artificial tactile sensing technology to perceive sustained mechanical touch.