Intrinsic Bursting Research Articles

Analysis to dynamics of complex electrical activities in Wilson model of brain neocortical neuron using fast-slow variable dissection with two slow variables

The neocortex of the brain plays a most important role in achieving functions of the brain via the electrical activities of neurons. Understanding the transition regularity of firing patterns and underlying dynamics of firing patterns of neurons can help to identify the brain functions and to treat some brain diseases. Different neocortical neurons exhibit regular spiking (RS), fast spiking (FS), intrinsic bursting (IB), and continuous bursting (CB), which play vital roles and wide range of functions. Fast-slow variable dissection method combined with bifurcation analysis has been an effective method to identify the underlying dynamical mechanism of spiking and bursting modulated by a single slow variable. The spiking is related to the stable limit cycle of the fast subsystem, and the bursting is associated with the transitions or bifurcations between the stable limit cycle and resting state of the fast subsystem. Such underlying dynamics of bursting has been widely used to distinguish different bursting patterns and identify complex dynamics of bursting modulated by various different factors such as synaptic current, autaptic current, and stimulations applied at a suitable phase related to the bifurcations, which play important roles in the real nervous system to regulate neural firing behaviors. Unfortunately, the bursting of neocortical neuronal model (wilson model) is modulated by two slow variables, i.e. the gating variable of calcium-activated potassium channel <i>H</i> and the gating variable of T-type calcium channel <i>T,</i> with <i>H</i> being slower than <i>T</i>. Then, the underlying dynamical mechanism of the IB and CB of the neocortical neurons cannot be acquired by the fast-slow variable dissection method when <i>H</i> is taken as the sole slow variable, due to the fact that the fast-subsystem contains the slow variable <i>T</i>. In the present paper, we use the fast-slow variable dissection method with two slow variables (<i>H</i> and <i>T </i>) to analyze the bursting patterns. The bifurcations of the fast subsystem, and the intersections between the bifurcation curves and the phase trajectory of bursting in the parameter plane (<i>H</i>, <i>T </i>) are acquired. Owing to the fact that neither of the two slow variables of the bursting is sufficiently slow, the bifurcations of only some intersections are related to the bursting behaviors, but others not. Then, the position relationship between the bifurcation curves and bursting trajectory in the three-dimensional space (<i>H</i>, <i>T</i>, <i>V </i>) (<i>V</i> is membrane potential of bursting) is further acquired, from which the bifurcations related to bursting behaviors are acquired and bifurcations unrelated to bursting behaviors are excluded. The start phase and the termination phase of the burst of the IB are related to the saddle-node on invariant circle (SNIC) bifurcation, but not to the saddle-node (SN) bifurcation. The start phase and termination phase of the burst of the CB are related to the SNIC bifurcation and the supercritical Andronov-Hopf (SupHopf) bifurcation, respectively, but not to the SN bifurcation. The results present a comprehensive and in-depth understanding of the underlying dynamics of bursting patterns in the neocortical neurons, thereby laying the foundation for regulating the firing patterns of the neocortical neurons.

Exploiting the electrothermal timescale in PrMnO3 RRAM for a compact, clock-less neuron exhibiting biological spiking patterns

Spiking neural networks (SNNs) are gaining widespread momentum in the field of neuromorphic computing. These network systems integrated with neurons and synapses provide computational efficiency by mimicking the human brain. It is desired to incorporate the biological neuronal dynamics, including complex spiking patterns which represent diverse brain activities within the neural networks. Earlier hardware realization of neurons was (a) area intensive because of large capacitors in the circuit design, (b) neuronal spiking patterns were demonstrated with clocked neurons at the device level. To achieve more realistic biological neuron spiking behavior, emerging memristive devices are considered promising alternatives. In this paper, we propose, PrMnO3 (PMO)-resistive random-access memory (RRAM) device-based neuron. The voltage-controlled electrothermal timescales of the compact PMO RRAM device replace the electrical timescales of charging a large capacitor. The electrothermal timescale is used to implement an integration block with multiple voltage-controlled timescales coupled with a refractory block to generate biological neuronal dynamics. Here, first, a Verilog-A implementation of the thermal device model is demonstrated, which captures the current-temperature dynamics of the PMO device. Second, a driving circuitry is designed to mimic different spiking patterns of cortical neurons, including intrinsic bursting and chattering. Third, a neuron circuit model is simulated, which includes the PMO RRAM device model and the driving circuitry to demonstrate the asynchronous neuron behavior. Finally, a hardware-software hybrid analysis is done in which the PMO RRAM device is experimentally characterized to mimic neuron spiking dynamics. The work presents a realizable and more biologically comparable hardware-efficient solution for large-scale SNNs.

Intrinsic and synaptic mechanisms controlling the expiratory activity of excitatory lateral parafacial neurones of rats.

Active expiration is essential for increasing pulmonary ventilation during high chemical drive (hypercapnia). The lateral parafacial (pFL ) region, which contains expiratory neurones, drives abdominal muscles during active expiration in response to hypercapnia. However, the electrophysiological properties and synaptic mechanisms determining the activity of pFL expiratory neurones, as well as the specific conditions for their emergence, are not fully understood. Using whole cell electrophysiology and single cell quantitative RT-PCR techniques, we describe the intrinsic electrophysiological properties, the phenotype and the respiratory-related synaptic inputs to the pFL expiratory neurones, as well as the mechanisms for the expression of their expiratory activity under conditions of hypercapnia-induced active expiration, using in situ preparations of juvenile rats. We also evaluated whether these neurones possess intrinsic CO2 /[H+ ] sensitivity and burst generating properties. GABAergic and glycinergic inhibition during inspiration and expiration suppressed the activity of glutamatergic pFL expiratory neurones in normocapnia. In hypercapnia, these neurones escape glycinergic inhibition and generate burst discharges at the end of expiration. Evidence for the contribution of post-inhibitory rebound, CaV 3.2 isoform of T-type Ca2+ channels and intracellular [Ca2+ ] is presented. Neither intrinsic bursting properties, mediated by persistent Na+ current, nor CO2 /[H+ ] sensitivity or expression of CO2 /[H+ ] sensitive ion channels/receptors (TASK or GPR4) were observed. On the other hand, hyperpolarisation-activated cyclic nucleotide-gated and twik-related K+ leak channels were recorded. Post-synaptic disinhibition and the intrinsic electrophysiological properties of glutamatergic neurones play important roles in the generation of the expiratory oscillations in the pFL region during hypercapnia in rats. KEY POINTS: Hypercapnia induces active expiration in rats and the recruitment of a specific population of expiratory neurones in the lateral parafacial (pFL ) region. Post-synaptic GABAergic and glycinergic inhibition both suppress the activity of glutamatergic pFL neurones during inspiratory and expiratory phases in normocapnia. Hypercapnia reduces glycinergic inhibition during expiration leading to burst generation by pFL neurones; evidence for a contribution of post-inhibitory rebound, voltage-gated Ca2+ channels and intracellular [Ca2+ ] is presented. pFL glutamatergic expiratory neurones are neither intrinsic burster neurones, nor CO2 /[H+ ] sensors, and do not express CO2 /[H+ ] sensitive ion channels or receptors. Post-synaptic disinhibition and the intrinsic electrophysiological properties of glutamatergic neurones both play important roles in the generation of the expiratory oscillations in the pFL region during hypercapnia in rats.

Determination of an intrinsic proneness index for strainburst and its verification by true triaxial compression tests

A part of the elastic strain energy stored in Class II rock will be converted into kinetic energy, which results in rock ejection after the peak stress. This part of the strain energy is the intrinsic potential energy for strainburst. Therefore, the strainburst proneness of the rock can be quantitatively estimated by the intrinsic burst energy density or the corresponding intrinsic ejection velocity. This study aims to validate the idea of using the intrinsic ejection velocity as a strainburst proneness index by laboratory true triaxial compression tests. In the study, servo-controlled uniaxial compression tests were conducted on six types of rock. The intrinsic burst energy density of these rocks was determined based on the stress–strain curves of the rocks obtained under uniaxial compression. The strainburst proneness of the rocks was then assessed. The same types of rock were then carried out single-free-face true triaxial compression testing to examine the rationality of the evaluation result.

Simulation of spiking activities neuron models using the Euler method

Simulation of neuron spiking activity models has been carried out using the Euler method. This study aims to simulate spiking activity in a neuron model. The neuron model used is the Hodgkin-Huxley neuron model, Integrate and Fire neuron model, Wilson neuron model, and Izhikevich neuron model. The research was conducted by implementing the mathematical equations of each neuron model used and then recording the membrane potential changes from time to time using the Euler method in MATLAB. The different forms of spiking activity were done by varying the variable’s value in each mathematical equation of a neuron model that describes the processing of action potentials (spikes) influenced by ion channel activity. The results showed that the Integrate and Fire neuron models produce regular spiking (RS), Hodgkin-Huxley neuron models have regular spiking (RS) forms, Wilson neuron models produce regular spiking (RS), fast-spiking (FS), and intrinsic bursting (IB), Izhikevich neuron model produces regular spiking (RS), fast-spiking (FS), intrinsic bursting (IB), chattering neurons (CH), and low threshold spiking (LTS). The complexity of the variables used and the spiking activity generated by each neuron model can provide an overview of computational efficiency and proximity to actual biological neurons.

Rhythmogenic states of the respiratory network reveal differential opioid sensitivity

Opioid induced respiratory depression (OIRD) is the major cause of death associated with opioid use. Although mortality increases dose-dependently, variability in the opioid response makes opioids particularly dangerous. The variability may be partly explained by rhythmogenic properties of the preBötzinger Complex (preBötC), a region that constitutes the minimal circuitry necessary for breathing. At the core of rhythmogenesis are periodic inspiratory bursts that emerge from synchronized activity within the preBötC. Between each burst, excitation builds among a growing number of neurons that synchronize to form a burst. Implicated in this are network-based mechanisms between recurrently connected excitatory and inhibitory neurons, as well as intrinsic-based mechanisms involving intrinsically bursting neurons that express persistently active inward cation currents, such as the persistent sodium current (INaP). Importantly, these mechanisms are sensitive to neuromodulation and depend on network excitability. Here, we test the hypothesis that shifts in the relative rhythmogenic role of network- and intrinsic- based mechanisms allow the preBötC to operate along a continuum of states, and consequently modulates sensitivity to OIRD. Horizontal brainstem slices were exposed to varying concentrations of aCSF [K+] or pharmacological manipulation of INaP prior to bath-application of the µ-opioid receptor agonist DAMGO. The aCSF [K+] required to induce bursting varied amongst slices. 48% required 8mM [K+], 17% required 6.5mM [K+], 10% required 5mM [K+], and 24% were rhythmic at 3mM [K+]. Unexpectedly we found upon initiating bursting, further increases in aCSF [K+] either increased or decreased rhythm stability, following a bell curve. Along this curve, increasing [K+] initially increased rhythm stability from 5% to 30% stabilitymax. After stabilitymax was reached, further 2mM increases in [K+] decreased stability by -40%, -55%, -52%, and -71%. The trajectory of stability to increasing aCSF [K+] predicted OIRD sensitivity. Slices that did not reach stabilitymax by 8mM [K+] displayed high sensitivity to OIRD and were silenced prior to 200nM DAMGO. In contrast, slices that reached stabilitymax at aCSF [K+] lower than 8mM and destabilized in 8mM [K+], were only modestly suppressed (-32% change in burst frequency) by 200nM DAMGO. To test the role of INaP in OIRD sensitivity, INaP was suppressed with 400nM ATTX or 20µM Riluzole prior to DAMGO. Both treatments increased OIRD sensitivity and silenced all slices prior to 200nM DAMGO. Lastly, to test for a protective role of INaP against OIRD INaP was potentiated with 400nM veratridine before or after DAMGO. Veratridine prior to DAMGO prevented OIRD, whereas veratridine following OIRD rescued bursting. Our results suggest the primary mechanisms of rhythm generation are flexible, and shift based upon the amount of network excitability and intrinsic bursting. Further, changing these dynamic properties creates states of rhythmogenesis that become highly sensitive, or insensitive to OIRD.

Intrinsic burst-firing in lamina I spinoparabrachial neurons during adolescence

A subset of glutamatergic interneurons in the neonatal spinal superficial dorsal horn (SDH) exhibits intrinsic burst-firing (i.e. ‘pacemaker’ activity), which is tightly regulated by persistent, voltage-gated Na+ channels and classic inward-rectifying K+ (Kir2) channels and downregulated over the course of postnatal development. Ascending lamina I projection neurons targeting the parabrachial nucleus (PB) or periaqueductal gray (PAG) can also display pacemaker activity during early life. However, the degree to which the ionic mechanisms driving pacemaker activity are conserved across different cell types in the spinal dorsal horn, as well as whether the intrinsic bursting is restricted to newborn projection neurons, remains to be elucidated. Using in vitro patch clamp recordings from identified lamina I spinoparabrachial neurons in rat spinal cord slices, here we demonstrate that adolescent projection neurons retain their ability to generate pacemaker activity. In contrast to previous findings in lamina I interneurons, pacemaker projection neurons possessed higher membrane capacitance, lower membrane resistance, and a greater Kir-mediated conductance compared to adjacent spinoparabrachial neurons that lacked intrinsic burst-firing. Nonetheless, as previously seen in interneurons, the bath application of riluzole to block persistent Na+ channels significantly dampened pacemaker activity in projection neurons. Collectively, these results suggest that intrinsic burst-firing in the developing dorsal horn can be generated by multiple combinations of ionic conductances, and highlight the need for further investigation into the mechanisms governing pacemaker activity within the major output neurons of the SDH network.

First-principles study of intrinsic point defects and Xe impurities in uranium monocarbide

Based on density functional theory (DFT) calculations, we perform an extensive investigation of intrinsic point defects and Xe impurities in uranium monocarbide (UC). The DFT calculations involve both the conventional generalized gradient approximation (GGA) and the GGA+U approach with the Hubbard parametric term (U), using up to 5×5×5 supercells. GGA calculations for the formation energy of intrinsic defects demonstrate the significant effect of using larger supercells than in previous studies. Results confirm that the ⟨111⟩ and ⟨100⟩ dumbbell interstitials are the most stable interstitial configurations for U and C, respectively. The interstitial mechanisms are favored for self-diffusion of both uranium and carbon and diffusion of Xe under equilibrium conditions. Calculations also reveal that the Xe substitutional defect at the C lattice site tends to adopt an off-site configuration, which can be interpreted as a Xe interstitial–C vacancy complex. We also utilize GGA+U to assess the impact of effective U parameter (Ueff) on the results. Moreover, we introduce a method to estimate the carbon chemical potential by fitting the phase diagram composition data and propose a selection Ueff=1.25 eV based on the experimental Xe diffusion activation energy. With this approach, GGA+U calculations reproduce the available experimental data for the formation energy of the carbon Frenkel pair and can explain the stepwise recovery of intrinsic properties and burst Xe release behavior in UC observed in annealing experiments.

A Mean-Field Description of Bursting Dynamics in Spiking Neural Networks with Short-Term Adaptation.

Bursting plays an important role in neural communication. At the population level, macroscopic bursting has been identified in populations of neurons that do not express intrinsic bursting mechanisms. For the analysis of phase transitions between bursting and non-bursting states, mean-field descriptions of macroscopic bursting behavior are a valuable tool. In this article, we derive mean-field descriptions of populations of spiking neurons and examine whether states of collective bursting behavior can arise from short-term adaptation mechanisms. Specifically, we consider synaptic depression and spike-frequency adaptation in networks of quadratic integrate-and-fire neurons. Analyzing the mean-field model via bifurcation analysis, we find that bursting behavior emerges for both types of short-term adaptation. This bursting behavior can coexist with steady-state behavior, providing a bistable regime that allows for transient switches between synchronized and nonsynchronized states of population dynamics. For all of these findings, we demonstrate a close correspondence between the spiking neural network and the mean-field model. Although the mean-field model has been derived under the assumptions of an infinite population size and all-to-all coupling inside the population, we show that this correspondence holds even for small, sparsely coupled networks. In summary, we provide mechanistic descriptions of phase transitions between bursting and steady-state population dynamics, which play important roles in both healthy neural communication and neurological disorders.

Biodegradable Zwitterion/PLGA Scaffold Enables Robust Healing of Rat Calvarial Defects with Ultralow Dose of rhBMP-2.

Designing smart scaffolds to reduce administration dosage under the premise of functional healing of bone defects to avoid the severe side effects associated with BMP-2 treatments is one of the essential goals in bone tissue engineering. Here, we report a novel biodegradable PLGA/PSBMA composite as the scaffold for bone tissue engineering. The introduction of zwitterionic PSBMA components can alter the intrinsic burst degradation behavior of PLGA and enable a sustained degradation of the scaffold over the time. The PLGA/PSBMA scaffold can sequester rhBMP-2 and enable a sustained release of the sequestered rhBMP-2 with preserved bioactivity. Furthermore, PLGA/PSBMA scaffolds were able to guide robust healing of critical-sized nonunion calvarial defects (5 mm) at an ultralow dose of 400 ng/scaffold, at which level successful healing of critical-sized bone defects has never been reported. These findings indicate the PLGA/PSBMA scaffolds as novel high-efficiency rhBMP-2 delivery vehicles for bone tissue engineering, and the concept of utilizing the material, which is capable of maintaining the bioactivity of the proteins in the preparation of scaffolds, may open a new avenue for the design of smart scaffolds/vehicles for high-efficiency protein/bioactive drug therapies.

Which bright fast radio bursts repeat?

ABSTRACT A handful of fast radio bursts (FRBs) are now known to repeat. However, the question remains – do they all? We report on an extensive observational campaign with the Australian Square Kilometre Array Pathfinder (ASKAP), Parkes, and Robert C. Byrd Green Bank Telescope, searching for repeat bursts from FRBs detected by the Commensal Real-time ASKAP Fast Transients survey. In 383.2 h of follow-up observations covering 27 FRBs initially detected as single bursts, only two repeat bursts from a single FRB, FRB 171019, were detected, which have been previously reported by Kumar et al. We use simulations of repeating FRBs that allow for clustering in burst arrival times to calculate new estimates for the repetition rate of FRB 171019, finding only slight evidence for incompatibility with the properties of FRB 121102. Our lack of repeat bursts from the remaining FRBs set limits on the model of all bursts being attributable to repeating FRBs. Assuming a reasonable range of repetition behaviour, at most 60 per cent (90 per cent confidence limit) of these FRBs have an intrinsic burst distribution similar to FRB 121102. This result is shown to be robust against different assumptions on the nature of repeating FRB behaviour, and indicates that if indeed all FRBs repeat, the majority must do so very rarely.

Critical Components for Spontaneous Activity and Rhythm Generation in Spinal Cord Circuits in Culture.

Neuronal excitability contributes to rhythm generation in central pattern generating networks (CPGs). In spinal cord CPGs, such intrinsic excitability partly relies on persistent sodium currents (INaP), whereas respiratory CPGs additionally depend on calcium-activated cation currents (ICAN). Here, we investigated the contributions of INaP and ICAN to spontaneous rhythm generation in neuronal networks of the spinal cord and whether they mainly involve Hb9 neurons. We used cultures of ventral and transverse slices from the E13–14 embryonic rodent lumbar spinal cord on multielectrode arrays (MEAs). All cultures showed spontaneous bursts of network activity. Blocking synaptic excitation with the AMPA receptor antagonist CNQX suppressed spontaneous network bursts and left asynchronous intrinsic activity at about 30% of the electrodes. Such intrinsic activity was completely blocked at all electrodes by both the INaP blocker riluzole as well as by the ICAN blocker flufenamic acid (FFA) and the more specific TRPM4 channel antagonist 9-phenanthrol. All three antagonists also suppressed spontaneous bursting completely and strongly reduced stimulus-evoked bursts. Also, FFA reduced repetitive spiking that was induced in single neurons by injection of depolarizing current pulses to few spikes. Other antagonists of unspecific cation currents or calcium currents had no suppressing effects on either intrinsic activity (gadolinium chloride) or spontaneous bursting (the TRPC channel antagonists clemizole and ML204 and the T channel antagonist TTA-P2). Combined patch-clamp and MEA recordings showed that Hb9 interneurons were activated by network bursts but could not initiate them. Together these findings suggest that both INaP through Na+-channels and ICAN through putative TRPM4 channels contribute to spontaneous intrinsic and repetitive spiking in spinal cord neurons and thereby to the generation of network bursts.

The mechanisms shaping CA2 pyramidal neuron action potential bursting induced by muscarinic acetylcholine receptor activation.

Recent studies have revealed that hippocampal area CA2 plays an important role in hippocampal network function. Disruption of this region has been implicated in neuropsychiatric disorders. It is well appreciated that cholinergic input to the hippocampus plays an important role in learning and memory. While the effect of elevated cholinergic tone has been well studied in areas CA1 and CA3, it remains unclear how changes in cholinergic tone impact synaptic transmission and the intrinsic properties of neurons in area CA2. In this study, we applied the cholinergic agonist carbachol and performed on-cell, whole-cell, and extracellular recordings in area CA2. We observed that under conditions of high cholinergic tone, CA2 pyramidal neurons depolarized and rhythmically fired bursts of action potentials. This depolarization depended on the activation of M1 and M3 cholinergic receptors. Furthermore, we examined how the intrinsic properties and action-potential firing were altered in CA2 pyramidal neurons treated with 10 µM carbachol. While this intrinsic burst firing persisted in the absence of synaptic transmission, bursts were shaped by synaptic inputs in the intact network. We found that both excitatory and inhibitory synaptic transmission were reduced upon carbachol treatment. Finally, we examined the contribution of different channels to the cholinergic-induced changes in neuronal properties. We found that a conductance from Kv7 channels partially contributed to carbachol-induced changes in resting membrane potential and membrane resistance. We also found that D-type potassium currents contributed to controlling several properties of the bursts, including firing rate and burst kinetics. Furthermore, we determined that T-type calcium channels and small conductance calcium-activated potassium channels play a role in regulating bursting activity.

Distinct mechanisms of signal processing by lamina I spino-parabrachial neurons

Lamina I spino-parabrachial neurons (SPNs) receive peripheral nociceptive input, process it and transmit to the supraspinal centres. Although responses of SPNs to cutaneous receptive field stimulations have been intensively studied, the mechanisms of signal processing in these neurons are poorly understood. Therefore, we used an ex-vivo spinal cord preparation to examine synaptic and cellular mechanisms determining specific input-output characteristics of the neurons. The vast majority of the SPNs received a few direct nociceptive C-fiber inputs and generated one spike in response to saturating afferent stimulation, thus functioning as simple transducers of painful stimulus. However, 69% of afferent stimulation-induced action potentials in the entire SPN population originated from a small fraction (19%) of high-output neurons. These neurons received a larger number of direct Aδ- and C-fiber inputs, generated intrinsic bursts and efficiently integrated a local network activity via NMDA-receptor-dependent mechanisms. The high-output SPNs amplified and integrated the nociceptive input gradually encoding its intensity into the number of generated spikes. Thus, different mechanisms of signal processing allow lamina I SPNs to play distinct roles in nociception.

Conditioning by subthreshold synaptic input changes the intrinsic firing pattern of CA3 hippocampal neurons.

Unlike synaptic strength, intrinsic excitability is assumed to be a stable property of neurons. For example, learning of somatic conductances is generally not incorporated into computational models, and the discharge pattern of neurons in response to test stimuli is frequently used as a basis for phenotypic classification. However, it is increasingly evident that signal processing properties of neurons are more generally plastic on the timescale of minutes. Here we demonstrate that the intrinsic firing patterns of CA3 neurons of the rat hippocampus in vitro undergo rapid long-term plasticity in response to a few minutes of only subthreshold synaptic conditioning. This plasticity on the spike timing could also be induced by intrasomatic injection of subthreshold depolarizing pulses and was blocked by kinase inhibitors, indicating that discharge dynamics are modulated locally. Cluster analysis of firing patterns before and after conditioning revealed systematic transitions toward adapting and intrinsic burst behaviors, irrespective of the patterns initially exhibited by the cells. We used a conductance-based model to decide appropriate pharmacological blockade and found that the observed transitions are likely due to recruitment of low-voltage calcium and Kv7 potassium conductances. We conclude that CA3 neurons adapt their conductance profile to the subthreshold activity of their input, so that their intrinsic firing pattern is not a static signature, but rather a reflection of their history of subthreshold activity. In this way, recurrent output from CA3 neurons may collectively shape the temporal dynamics of their embedding circuits.NEW & NOTEWORTHY Although firing patterns are widely conserved across the animal phyla, it is still a mystery why nerve cells present such diversity of discharge dynamics upon somatic step currents. Adding a new timing dimension to the intrinsic plasticity literature, here we show that CA3 neurons rapidly adapt through the space of known firing patterns in response to the subthreshold signals that they receive from their embedding circuit, potentially adjusting their network processing to the temporal statistics of their circuit.

Simple models of quantitative firing phenotypes in hippocampal neurons: Comprehensive coverage of intrinsic diversity.

Patterns of periodic voltage spikes elicited by a neuron help define its dynamical identity. Experimentally recorded spike trains from various neurons show qualitatively distinguishable features such as delayed spiking, spiking with or without frequency adaptation, and intrinsic bursting. Moreover, the input-dependent responses of a neuron not only show different quantitative features, such as higher spike frequency for a stronger input current injection, but can also exhibit qualitatively different responses, such as spiking and bursting under different input conditions, thus forming a complex phenotype of responses. In previous work, the comprehensive knowledge base of hippocampal neuron types Hippocampome.org systematically characterized various spike pattern phenotypes experimentally identified from 120 neuron types/subtypes. In this paper, we present a complete set of simple phenomenological models that quantitatively reproduce the diverse and complex phenotypes of hippocampal neurons. In addition to point-neuron models, we created compact multi-compartment models with up to four compartments, which will allow spatial segregation of synaptic integration in network simulations. Electrotonic compartmentalization observed in our compact multi-compartment models is qualitatively consistent with experimental observations. The models were created using an automated pipeline based on evolutionary algorithms. This work maps 120 neuron types/subtypes in the rodent hippocampus to a low-dimensional model space and adds another dimension to the knowledge accumulated in Hippocampome.org. Computationally efficient representations of intrinsic dynamics, along with other pieces of knowledge available in Hippocampome.org, provide a biologically realistic platform to explore the large-scale interactions of various neuron types at the mesoscopic level.

On the Theory of a Photocurrent Burst in an Intrinsic Photoresistor upon Longitudinal and Transverse Illumination

In this paper, we analyze the intrinsic photoconductivity burst of semiconductors at an increase in the recombination center concentration upon uniform and non-uniform weak illumination along the electric field. An equation for the concentration distribution of nonequilibrium carriers at an arbitrary illumination profile along the electric field is derived without using the quasi-neutrality approximation. Based on this equation, the bursts in photoelectric gain of the transverse and longitudinal photoresistors should significantly differ from each other under any recombination conditions at current contacts due to the photo-induced space charge. If the carrier photogeneration is not uniform, then, unlike uniform photogeneration, the photoelectric gain burst depends on the polarity of the applied voltage. The quasi-neutrality approximation does not produce these results. An analytical expression for the maximum value of the electron photoelectric gain depending on the recombination center concentration is derived in the case of an exponential photogeneration profile and pulling-out contacts. The relationship that was found between the concentrations of nonequilibrium electrons and holes allows derivation of an analytical expression for the maximum value of the hole photoelectric gain.

Optimized Real-Time Biomimetic Neural Network on FPGA for Bio-hybridization.

Neurological diseases can be studied by performing bio-hybrid experiments using a real-time biomimetic Spiking Neural Network (SNN) platform. The Hodgkin-Huxley model offers a set of equations including biophysical parameters which can serve as a base to represent different classes of neurons and affected cells. Also, connecting the artificial neurons to the biological cells would allow us to understand the effect of the SNN stimulation using different parameters on nerve cells. Thus, designing a real-time SNN could useful for the study of simulations of some part of the brain. Here, we present a different approach to optimize the Hodgkin-Huxley equations adapted for Field Programmable Gate Array (FPGA) implementation. The equations of the conductance have been unified to allow the use of same functions with different parameters for all ionic channels. The low resources and high-speed implementation also include features, such as synaptic noise using the Ornstein–Uhlenbeck process and different synapse receptors including AMPA, GABAa, GABAb, and NMDA receptors. The platform allows real-time modification of the neuron parameters and can output different cortical neuron families like Fast Spiking (FS), Regular Spiking (RS), Intrinsically Bursting (IB), and Low Threshold Spiking (LTS) neurons using a Digital to Analog Converter (DAC). Gaussian distribution of the synaptic noise highlights similarities with the biological noise. Also, cross-correlation between the implementation and the model shows strong correlations, and bifurcation analysis reproduces similar behavior compared to the original Hodgkin-Huxley model. The implementation of one core of calculation uses 3% of resources of the FPGA and computes in real-time 500 neurons with 25,000 synapses and synaptic noise which can be scaled up to 15,000 using all resources. This is the first step toward neuromorphic system which can be used for the simulation of bio-hybridization and for the study of neurological disorders or the advanced research on neuroprosthesis to regain lost function.

Convergence of regular spiking and intrinsically bursting Izhikevich neuron models as a function of discretization time with Euler method

This study investigates the trade-off between computational efficiency and accuracy of Izhikevich neuron models by numerically quantifying their convergence to provide design guidelines in choosing the limit time steps during a discretization procedure. This is important for bionic engineering and neuro-robotic applications where the use of embedded computational resources requires the introduction of optimality criteria. Specifically, the regular spiking (RS) and intrinsically bursting (IB) Izhikevich neuron models are evaluated with step inputs of various amplitudes. We analyze the convergence of spike sequences generated under different discretization time steps (10 µs to 10 ms), with respect to an ideal reference spike sequence approximated with a discretization time step of 1 µs. The differences between the ideal reference and the computed spike sequences were quantified by Victor–Purpura (VPd) and van Rossum (VRd) distances. For each distance, we found two limit discretization times (lower dt1 and upper dt2), as a function of the applied input and thus firing rate, beyond which the convergence is lost for each neuron model. The estimated limit time steps were found to be consistent regardless of metric used (VPd and VRd) and neuron type (RS and IB), but also to depend on the average inter-spike interval (ISI) produced by the neurons. However, in most cases, a good trade-off between the quality of the convergence of the models dynamics and the computational load required to simulate them numerically was found for values of the discretization time step between dt1 ∈ (0.1 ms, 1 ms) and dt2 ∈ (2 ms, 3 ms).

The Hyperpolarization-Activated HCN4 Channel is Important for Proper Maintenance of Oscillatory Activity in the Thalamocortical System.

Hyperpolarization-activated cation channels are involved, among other functions, in learning and memory, control of synaptic transmission and epileptogenesis. The importance of the HCN1 and HCN2 isoforms for brain function has been demonstrated, while the role of HCN4, the third major neuronal HCN subunit, is not known. Here we show that HCN4 is essential for oscillatory activity in the thalamocortical (TC) network. HCN4 is selectively expressed in various thalamic nuclei, excluding the thalamic reticular nucleus. HCN4-deficient TC neurons revealed a massive reduction of Ih and strongly reduced intrinsic burst firing, whereas the current was normal in cortical pyramidal neurons. In addition, evoked bursting in a thalamic slice preparation was strongly reduced in the mutant mice probes. HCN4-deficiency also significantly slowed down thalamic and cortical oscillations during active wakefulness. Taken together, these results establish that thalamic HCN4 channels are essential for the production of rhythmic intrathalamic oscillations and determine regular TC oscillatory activity during alert states.