Voltage Traces Research Articles

Patterns of interval correlations in neural oscillators with adaptation

Neural firing is often subject to negative feedback by adaptation currents. These currents can induce strong correlations among the time intervals between spikes. Here we study analytically the interval correlations of a broad class of noisy neural oscillators with spike-triggered adaptation of arbitrary strength and time scale. Our weak-noise theory provides a general relation between the correlations and the phase-response curve (PRC) of the oscillator, proves anti-correlations between neighboring intervals for adapting neurons with type I PRC and identifies a single order parameter that determines the qualitative pattern of correlations. Monotonically decaying or oscillating correlation structures can be related to qualitatively different voltage traces after spiking, which can be explained by the phase plane geometry. At high firing rates, the long-term variability of the spike train associated with the cumulative interval correlations becomes small, independent of model details. Our results are verified by comparison with stochastic simulations of the exponential, leaky, and generalized integrate-and-fire models with adaptation.

Inactivating ion channels augment robustness of subthreshold intrinsic response dynamics to parametric variability in hippocampal model neurons

Voltage-gated ion channels play a critical role in regulating neuronal intrinsic response dynamics (IRD). Here, we computationally analysed the roles of the two inactivating subthreshold conductances (A and T), individually and in various combinations with the non-inactivating h conductance, in regulating several physiological IRD measurements in the theta frequency range. We found that the independent presence of a T conductance, unlike that of an h conductance, was unable to sustain an inductive phase lead in the theta frequency range, despite its ability to mediate theta frequency resonance. The A conductance, on the other hand, when expressed independently, acted in a manner similar to a leak conductance with reference to most IRD measurements. Next, analysing the impact of pair-wise coexpression of these channels, we found that the coexpression of the h and T conductances augmented the range of parameters over which they sustained resonance and inductive phase lead. Additionally, coexpression of the A conductance with the h or the T conductance elicited changes in IRD measurements that were similar to those obtained with the expression of a leak conductance with a resonating conductance. Finally, to understand the global sensitivity of IRD measurements to all parameters associated with models expressing all three channels, we generated 100,000 neuronal models, each built with a unique set of parametric values. We categorized valid models among these by matching their IRD measurements with experimental counterparts, and found that functionally similar models could be achieved even when underlying parameters displayed tremendous variability and exhibited weak pair-wise correlations. Our results suggest that the three prominent subthreshold conductances contribute differently to intrinsic excitability and to phase coding. We postulate that the differential expression and activity-dependent plasticity of these conductances contribute to robustness of subthreshold IRD, whereby response homeostasis is achieved by recruiting several non-unique combinations of these channel parameters.

331 The Prognostic Value of aEEG and NIRS during Therapeutic Hypothermia in Term Asphyxiated Newborns

Background and objectiveInfants with hypoxic-ischemic encephalopathy (HIE) are treated with therapeutic hypothermia (HT). Following perinatal asphyxia amplitude-integrated EEG (aEEG) and near-infrared spectroscopy (NIRS) are used to determine prognosis. We aimed...

The prognostic value of continuous amplitude-integrated electroencephalogram applied immediately after return of spontaneous circulation in therapeutic hypothermia-treated cardiac arrest patients

IntroductionThe purpose of this study was to examine the prognostic value of continuous amplitude-integrated electroencephalogram (aEEG) applied immediately after return of spontaneous circulation (ROSC) in therapeutic hypothermia (TH)-treated cardiac arrest patients. MethodsFrom September 2010 to August 2011, we prospectively studied comatose patients treated with TH after cardiac arrest who were monitored with aEEG. Monitoring at the forehead was applied as soon as possible after ROSC in the emergency department and continued until recovery of consciousness, death, or 72h after ROSC. Neurological outcome was assessed with the Cerebral Performance Category (CPC) scale at hospital discharge, and good neurological outcome was defined as a CPC score of 1 or 2. ResultsA total of 55 TH-treated patients were included. Monitoring started at a median of 96min after ROSC (interquartile range, 49–174). At discharge, 28 patients had a CPC of 1–2, and 27 patients had a CPC of 3–5. Seventeen patients had a continuous normal voltage (CNV) trace at the start of monitoring, and this voltage was strongly associated with a good outcome (16/17 [94.1%]; sensitivity and specificity of 57.1 and 96.3%, respectively). No development of a CNV trace within the recorded period accurately predicted a poor outcome (21/21 [100%]; sensitivity and specificity of 77.8 and 100%, respectively). ConclusionsAn initial CNV trace in aEEG applied to forehead immediately after ROSC is a good early predictor of a good outcome in TH-treated cardiac arrest patients. Conversely, no development of a CNV trace within 72h is an accurate and reliable predictor of a poor outcome with a false-positive rate of 0%.

Application of High-Speed Video and Spectroscopy to Railgun Development

High-speed video and optical spectroscopy have been used to monitor and account for the improved performance of a solid lubricating interfacial compound (SLIC) treatment of Cu armatures and Cu rails in a subsonic railgun. Videos were taken at 68k frames per second both down bore (breech view) and along the exit path of the gun (muzzle view). A spectrometer collected data at 1 spectrum per ms outside the muzzle. Armatures were made by threading Cu or Cu-clad Al staples through a Delrin projectile. The SLIC treatment consisted of rubbing staples and rails with a fiberglass-reinforced PTFE (Rulon). Untreated staples and rails were susceptible to both arcing and subsequent light emissions, with light emission lasting much longer than coincident voltage spikes in muzzle voltage traces. SLIC-treated staples and rails showed significantly less light emissions, which allowed for real time, laser spot tracking of projectile motion. Image analysis showed that projectiles were accelerated at 10–14 kGees within 1 ms to final speeds around 130 ± 10 m/s. These speeds were consistent with exit speeds measured by a dual laser-beam speed detector. Cu staples exited the muzzle with only a small amount of light emission, whereas Al and Cu-clad Al staples produced an extended trail of light. Spectroscopic analysis identified atomic and ionic excitations of Cu and later molecular CuO with both Cu and Cu-clad Al staples. Molecular H2 lines were also detected, suggesting burning of Delrin. Spectroscopy identified the extended trail from Cu-clad Al staples to be AlO vapors from molten Al particles.

The Ferroelectric Field Effect within an Integrated Core/Shell Nanowire

AbstractThe synthesis of cylindrical silicon‐core and ferroelectric oxide perovskite‐shell nanowires and their response characteristics as individual three‐terminal nanoscale electronic devices is reported. The co‐axial nanowire geometry facilitates large ferroelectric field‐effect modulation (>104) of nanowire conductivity following sequential application and removal of an applied dc field. Source‐drain current–voltage traces collected during sweeps of ferroelectric gate potential and switching of the component of shell outward and inward polarization provide direct evidence of ferroelectric coupling on nanowire channel conductance. Despite a very small (1:20) ferroelectric‐to‐semiconductor channel thickness ratio, an unexpectedly strong electrostatic coupling of ferroelectric polarization to channel conductance is observed because of the co‐axial gate geometry and curvature‐induced strain enhancement of ferroelectric polarization.

Rhythm-induced spike-timing patterns characterized by 1D firing maps

We explore patterns in the spike timing of neurons receiving periodic inputs, with an emphasis on stable characteristics which are realized in both models and in-vitro whole-cell recordings. We report on whole-cell recordings of pyramidal CA1 cells from rat hippocampus and entorhinal cortex and compare this data to model simulations. Cells were injected with a constant current to induce a steady firing rate and then a modest rhythm was added which altered the spike times and their corresponding phases relative to the rhythm. For both experiment and theory the relationship between consecutive spike phases is characterized by a probability distribution with peaks concentrated near a one-dimensional firing map. As is well-known, stable fixed points of this map correspond to the neuron phase-locking to the rhythm. We show that the interaction between noise and sufficiently steep maps can also cause a new kind of spike-time organization, in which consecutive spike time pairs organize into discrete clusters, with transitions between these clusters proceeding in a fixed sequence. This structure is not just a vestige of the noise-free dynamics. This slow dynamics and temporal organization in the relationship between consecutive spike phases is not evident in either the neuron's voltage traces or single phase or interspike interval histograms. Furthermore, the consecutive spike relationship is also evident in consecutive ISIs, and hence this ordering can be observed without detailed knowledge of the rhythm (e.g.without concurrent LFP recordings).

NeRvolver: a computational intelligence-based system for automated construction, tuning, and analysis of neuronal models

Building neuronal models, even on the single-cell level, requires tremendous amounts of effort invested in the design of a realistic and functioning structure (e.g., the number and characteristics of compartments) and proper tuning of the model’s parameter values (e.g., membrane and axial conductances). Due to the ever-increasing computational power of modern computers facilitating the use of more and more complex neuronal models, hand-tuning of models’ parameters is becoming less and less feasible. Therefore, automated methods for neuronal model construction have been lately gaining much attention. Although a significant number of techniques for automatic model parameter estimation have been recently proposed (e.g., [1,3,4]), they are predominantly limited to “fine-tuning” of already designed models in a predetermined search space of parameter values. Furthermore, although unquestionably successful, present approaches are almost exclusively domain-specific, designed to deal with particular neuron types, or explicit classes of electrical activity (e.g., spiking neurons). Finally, most of the existing systems attempt to produce a single, best-matching model, and rely on a direct comparison between the voltage trace of the model and its biological equivalent. Here, we propose a computational intelligence-based system for automated construction and tuning of neuronal models that builds upon the existing research in the area of automatic neuron model parameter optimization, but at the same time significantly expands the current approaches. The system, called NeRvolver, is designed to not only optimize the parameters of existing neuronal models, but also to allow for creation of entire sets of models matching some predefined criteria (e.g., in terms of the neuron’s characteristics such as spike height, inter-spiking interval, burst duration, period, etc.) “from scratch” (by utilizing, for example, only a limited set of generic currents as the starting point in the process of model construction). Furthermore, in addition to generating neuronal models, through the hybridization of multi-objective evolutionary algorithms (MOEA) and fuzzy logic (FL), the system generates classification rules describing biological phenomena discovered during the process of model creation or tuning (e.g., “IF sodium axon conductance is low, THEN spike frequency is low”). The purpose of generating such rules is twofold: 1) they can be used in subsequent runs of the modeling algorithm to improve its convergence time, and 2) they may potentially provide insights into the functioning of the biological neurons being modeled. For example, by using the aforementioned rule, the system may automatically increase the sodium axon conductance across the individuals in the evolutionary algorithm’s current population, if a higher spike frequency is desired. This is akin to the idea of local improvement of the genetic material using memes in memetic algorithms [2]. In addition, based on the above-quoted rule, the conclusion may be drawn that sufficient sodium axon conductance is necessary for adequate spike frequency. Such inferences, here automatically generated by the modeling system, can obviously be extremely useful for the understanding of the underlying biological phenomena.

Influence of shock wave propagation on dielectric barrier discharge plasma actuator performance

Interest in plasma actuators as active flow control devices is growing rapidly due to their lack of mechanical parts, light weight and high response frequency. Although the flow induced by these actuators has received much attention, the effect that the external flow has on the performance of the actuator itself must also be considered, especially the influence of unsteady high-speed flows which are fast becoming a norm in the operating flight envelopes. The primary objective of this study is to examine the characteristics of a dielectric barrier discharge (DBD) plasma actuator when exposed to an unsteady flow generated by a shock tube. This type of flow, which is often used in different studies, contains a range of flow regimes from sudden pressure and density changes to relatively uniform high-speed flow regions. A small circular shock tube is employed along with the schlieren photography technique to visualize the flow. The voltage and current traces of the plasma actuator are monitored throughout, and using the well-established shock tube theory the change in the actuator characteristics are related to the physical processes which occur inside the shock tube. The results show that not only is the shear layer outside of the shock tube affected by the plasma but the passage of the shock front and high-speed flow behind it also greatly influences the properties of the plasma.

Embryonic assembly of auditory circuits: spiral ganglion and brainstem

During early development, peripheral sensory systems generate physiological activity prior to exposure to normal environmental stimuli. This activity is thought to facilitate maturation of these neurons and their connections, perhaps even promoting efficacy or modifying downstream circuitry. In the mammalian auditory system, initial connections form at embryonic ages, but the functional characteristics of these early neural connections have not been assayed. We investigated processes of embryonic auditory development using a whole-head slice preparation that preserved connectivity between peripheral and brainstem stations of the auditory pathway. Transgenic mice expressing fluorescent protein provided observation of spiral ganglion and cochlear nucleus neurons to facilitate targeted electrophysiological recording. Here we demonstrate an apparent peripheral-to-central order for circuit maturation. Spiral ganglion cells acquire action potential-generating capacity at embryonic day 14 (E14), the earliest age tested, and action potential waveforms begin to mature in advance of comparable states for neurons of the ventral cochlear nucleus (VCN) and medial nucleus of the trapezoid body (MNTB). In accordance, auditory nerve synapses in the VCN are functional at E15, prior to VCN connectivity with the MNTB, which occurs at least 1 day later. Spiral ganglion neurons exhibit spontaneous activity at least by E14 and are able to drive third-order auditory brainstem neurons by E17. This activity precedes cochlear-generated wave activity by 4 days and ear canal opening by at least 2 weeks. Together, these findings reveal a previously unknown initial developmental phase for auditory maturation, and further implicate the spiral ganglion as a potential controlling centre in this process.

Cerebral function monitoring during therapeutic hypothermia in a tertiary neonatal centre

Introduction Therapeutic hypothermia is a standard of care in the UK for neonates with hypoxic ischaemic encephalopathy. Meeting neurological criteria are essential for recruitment of neonates for treatment. Neurological symptomatology may be subtle and the role of cerebral function monitoring (CFM) though not essential for starting treatment has been endorsed by the BAPM in its position statement. Method An audit to review the management of neonates with suspected hypoxia ischaemia who underwent therapeutic hypothermia was carried out in a tertiary neonatal centre. Information was taken from the patient record and TOBY forms regarding recruitment as per standard criteria, and neurological symptoms. A confidential review of the CFM traces was performed where available and they were classified as being continuous normal voltage, discontinuous normal voltage, burst suppression, low voltage or inactive. Results 29 cases underwent therapeutic hypothermia during the period August 2009-August 2011 with a total of 1979 cooling hours provided. Traces were reviewed in 28 out of 29 cases with one not obtainable. 4 cases had continuous normal voltages, 14 cases had discontinuous normal voltage, 3 had burst suppression, 6 were low voltage or inactive. 2 cases had only seizures. Of 29 cases 2 had neonatal encephalopathy which may have been attributable to other causes. All the cases with burst suppression, low voltage or inactive trace that normalised their CFM records within 72 hours were discharged feeding orally. Cases with burst suppression, low voltage, or inactive trace that didn9t normalise their trace all died. Conclusion All neonates undergoing therapeutic hypothermia should have cerebral function monitoring initiated if available. Used adjunctively with the presentation, clinical course and neuroimaging it may be a prognostic indicator of survival and outcomes in such neonates. Cerebral function monitor traces need cautious interpretation for artefacts. Background and improvement of the trace in neonates may be affected by antiepileptic medication. It is important to investigate other causes for neonatal encephalopathy in neonates undergoing therapeutic hypothermia. It is inevitable that some neonates with borderline neurology and continuous normal voltage appearance will be cooled. This work highlights the pitfalls of interpreting CFM traces of neonates being cooled for trainees.

Automated optimization of a reduced layer 5 pyramidal cell model based on experimental data

The construction of compartmental models of neurons involves tuning a set of parameters to make the model neuron behave as realistically as possible. While the parameter space of single-compartment models or other simple models can be exhaustively searched, the introduction of dendritic geometry causes the number of parameters to balloon. As parameter tuning is a daunting and time-consuming task when performed manually, reliable methods for automatically optimizing compartmental models are desperately needed, as only optimized models can capture the behavior of real neurons. Here we present a three-step strategy to automatically build reduced models of layer 5 pyramidal neurons that closely reproduce experimental data. First, we reduce the pattern of dendritic branches of a detailed model to a set of equivalent primary dendrites. Second, the ion channel densities are estimated using a multi-objective optimization strategy to fit the voltage trace recorded under two conditions – with and without the apical dendrite occluded by pinching. Finally, we tune dendritic calcium channel parameters to model the initiation of dendritic calcium spikes and the coupling between soma and dendrite. More generally, this new method can be applied to construct families of models of different neuron types, with applications ranging from the study of information processing in single neurons to realistic simulations of large-scale network dynamics.

The study on improving the self-protection ability of HTS coils by removing the insulation and lamination of the various metal tapes

The high temperature superconducting (HTS) coils have very low normal zone propagation velocity (NZPV) and complicated quench behaviors. Because of these reasons, it is difficult to expect the self-protection. In this paper, two methods are suggested to improve the self-protection ability of HTS coils. One is to remove the insulation between turn–turn winding in HTS coils to enhance the thermal and electrical contacts along transverse direction and to increase the whole thermal stability of them. The other is Cu or Brass tapes are wound with HTS tape wire instead of the insulation to improve the thermal, electrical and mechanical stability of the HTS coils. To clarify the quench behaviors of the suggested coils, the normal zone propagation properties of the fabricated non-insulated HTS pancake coils were shown by measured voltage and temperature traces during the quench as a function of the operating temperature. And the characteristics of the normal transition and amount of the shared current to adjacent layers were quantitatively measured by a Hall sensor located at the center of HTS coils to measure the change of the self-magnetic field by operating current. The current sharing behaviors in the non-insulated HTS coil and the coil with Cu tape inserted were observed. The minimum quench energy (MQE) of the HTS coil with Cu tape inserted was the largest in the tested coils. It means that the HTS coil with Cu tape inserted had the highest transient stability against the thermal disturbances among the tested coils and the improvement of self protection abilities was proved.

Correlations between Molecular Structure and Single-Junction Conductance: A Case Study with Oligo(phenylene-ethynylene)-Type Wires

The charge transport characteristics of 11 tailor-made dithiol-terminated oligo(phenylene-ethynylene) (OPE)-type molecules attached to two gold electrodes were studied at a solid/liquid interface in a combined approach using an STM break junction (STM-BJ) and a mechanically controlled break junction (MCBJ) setup. We designed and characterized 11 structurally distinct dithiol-terminated OPE-type molecules with varied length and HOMO/LUMO energy. Increase of the molecular length and/or of the HOMO-LUMO gap leads to a decrease of the single-junction conductance of the linearly conjugate acenes. The experimental data and simulations suggest a nonresonant tunneling mechanism involving hole transport through the molecular HOMO, with a decay constant β = 3.4 ± 0.1 nm(-1) and a contact resistance R(c) = 40 kΩ per Au-S bond. The introduction of a cross-conjugated anthraquinone or a dihydroanthracene central unit results in lower conductance values, which are attributed to a destructive quantum interference phenomenon for the former and a broken π-conjugation for the latter. The statistical analysis of conductance-distance and current-voltage traces revealed details of evolution and breaking of molecular junctions. In particular, we explored the effect of stretching rate and junction stability. We compare our experimental results with DFT calculations using the ab initio code SMEAGOL and discuss how the structure of the molecular wires affects the conductance values.

Bioaerosol detection using potentiometric tomography in flames

A method of detection and identification of bioaerosols is described, based on gaseous plasma electrochemistry in a flame. This approach involves the combustion of individual bioaerosol particles entering a laminar hydrogen/oxygen flame, producing a plume rich in ionised species. As the plume expands and moves through the flame it can be comfortably detected at an array of eight individually addressable electrodes. Zero current potentiometric measurements, simultaneously recorded at each electrode, provide spatial distribution of the combustion plume, which depends on the particle's size, density and chemical make-up. We used a statistical classification analysis extracting specific features of the voltage traces from individual particle combustion events to differentiate between four model bioaerosols (Bermuda grass pollen, Bermuda smut spores, Johnson smut spores and Black walnut pollen). From a set of 120 individual combustion events (30 for each bioaerosol) the best case of identification was correct 29 out of 30 events for Bermuda grass pollen, and the worst being 19 out of 30 for Johnson smut spores. We propose a promising and robust analytical methodology for real-time bioaerosol detection.

A simulation framework for acute extracellular recordings

Event Abstract Back to Event A simulation framework for acute extracellular recordings Philipp Meier1*, Felix Franke2, Espen Hagen3, Gaute T. Einevoll3 and Klaus H. Obermayer1 1 Berlin Institute of Technology, School for Electrical Engineering and Computer Science, Germany 2 ETH Zurich, D-BSSE, Switzerland 3 Norwegian University of Life Sciences, Dept. of Mathematical Sciences and Technology, Norway Extracellular recordings are a key tool to study the activity of neurons in vivo. Especially in the case of experiments with behaving animals, however, the procedure of electrode placement can take a considerable amount of expensive and restricted experimental time. Furthermore, due to tissue drifts and other sources of variability in the recording setup, the position of electrodes with respect to the neurons under study can change, causing degraded recording quality (non-stationarities). Here we devloped a simulation framework for acute extracellular recordings. Neurons and electrodes are modelled as objects in a spatio-temporal state space. A generative data model allows to construct putative voltage traces at electrode positions, as the superposition of time-and-distant-dependant characteristic waveforms of the simulated single neurons. All objects may be positioned arbitrarily during the simulation. This kind of framework allows to simulate acute experimental conditions and provides grounds to evaluate feedback-dependant algorithms (positioning systems, online/adaptive spikesorting). The simulated data was found to resemble data acquired from acute extracellular recordings from PFC of awake behaving maquace. Acknowledgements This work was supported by DFG GRK 1589/1 and the German Federal Ministry of Education and Research (BMBF) with the grants 01GQ0743 and 01GQ0410 and by the Research Council of Norway (eScience,NeuroNor). References K.H. Pettersen, H. Linden, A.M. Dale and G.T. Einevoll: Extracellular spikes and current-source density, in Handbook of Neural Activity Measurement, edited by R. Brette and A. Destexhe, Cambridge, to appear Franke F, Natora M, Meier P, Hagen E, Pettersen KH, Linden H, Einevoll GT, Obermayer K. (2010). An automated online positioning system and simulation environment for multi-electrodes in extracellular recordings. Conf Proc IEEE Eng Med Biol Soc. 2010;2010:593-7. Keywords: closed loop experiment, extracellular recording, forward simulation Conference: Bernstein Conference 2012, Munich, Germany, 12 Sep - 14 Sep, 2012. Presentation Type: Poster Topic: Data analysis, machine learning, neuroinformatics Citation: Meier P, Franke F, Hagen E, Einevoll GT and Obermayer KH (2012). A simulation framework for acute extracellular recordings. Front. Comput. Neurosci. Conference Abstract: Bernstein Conference 2012. doi: 10.3389/conf.fncom.2012.55.00015 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 21 Apr 2012; Published Online: 12 Sep 2012. * Correspondence: Mr. Philipp Meier, Berlin Institute of Technology, School for Electrical Engineering and Computer Science, Berlin, Germany, pmeier82@googlemail.com Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Philipp Meier Felix Franke Espen Hagen Gaute T Einevoll Klaus H Obermayer Google Philipp Meier Felix Franke Espen Hagen Gaute T Einevoll Klaus H Obermayer Google Scholar Philipp Meier Felix Franke Espen Hagen Gaute T Einevoll Klaus H Obermayer PubMed Philipp Meier Felix Franke Espen Hagen Gaute T Einevoll Klaus H Obermayer Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Structural, optical and electrical properties of cubic AlN films deposited by laser molecular beam epitaxy

Cubic AlN films were successfully deposited on TiN buffered Si (100) substrates by a laser molecular beam epitaxy (LMBE) technique, and their crystal structure and optical and electrical properties were studied. The results indicate that cubic AlN films show the NaCl-type structure with a (200) preferred orientation, and the lattice parameter is determined to be 0.4027 nm. The Fourier transform infrared (FTIR) pattern of the cubic AlN film displays sharp absorption peaks at 668 cm−1 and 951 cm−1, corresponding to the transverse and longitudinal optical vibration modes. Ellipsometric measurements evidence a refractive index of 1.66–1.71 and an extinction coefficient of about zero for the cubic AlN film in the visible range. Capacitance–voltage (C–V) traces of the metal–insulator–semiconductor (MIS) device exhibit that the cubic AlN film has a dielectric constant of 8.1, and hysteresis in the C–V traces indicates a significant number of charge traps in the film.

Heating liquid dielectrics by time dependent fields

Steady state and time-resolved dielectric relaxation experiments are performed at high fields on viscous glycerol and the effects of energy absorption from the electric field are studied. Time resolution is obtained by a sinusoidal field whose amplitude is switched from a low to a high level and by recording voltage and current traces with an oscilloscope during this transition. Based on their distinct time and frequency dependences, three sources of modifying the dynamics and dielectric loss via an increase in the effective temperature can be distinguished: electrode temperature, real sample temperature, and configurational temperatures of the modes that absorbed the energy. Isothermal conditions that are desired for focusing on the configurational temperature changes (as in dielectric hole burning and related techniques) are maintained only for very thin samples and for moderate power levels. For high frequencies, say ν > 1 MHz, changes of the real temperature will exceed the effects of configurational temperatures in the case of macroscopic samples. Regarding microwave chemistry, heating via cell phone use, and related situations in which materials are subject to fields involving frequencies beyond the MHz regime, we conclude that changes in the configurational (or fictive) temperatures remain negligible compared with the increase of the real temperature. This simplifies the assessment of how time dependent electric fields modify the properties of materials.

An analytical approximation to the AdEx neuron model allows fast fitting to physiological data

Fitting spiking neuron models to physiological data sets is often a tedious, time-consuming business involving several ad-hoc assumptions. At one end of the spectrum, biophysically detailed models can often reproduce electrophysiological data to arbitrary degree. However, because of the large number of parameters, this very laborious process runs into the risk of serious over-fitting: Different parameter configurations may give similarly good fits to a set of ‘training data’ [1], but it is not clear how these different models would perform on test data that has not been used for parameter tuning. At the other end of the spectrum, analytical solutions for leaky-integrate-&-fire (LIF) models would allow a fast fitting process, but their intrinsic dynamics is too poor to reproduce the spiking behaviour of real neurons to a reasonable degree. For many purposes, however, it is important to have simple, yet in some sense still physiologically realistic neuron models. Recent extensions of the basic LIF neuron model [2-4] have made progress into this direction by providing simple models which are able to reproduce voltage traces and spiking dynamics of real neurons to an astonishing degree. Most of these studies used voltage traces to fit the model, which are obtained by somatic injections of fluctuating current inputs into neurons recorded from acute brain slices. Moreover, some of these models [2,4] also perform quite well on sections of these recordings that are different from the data used for training. However, as both training and test data consist of voltage traces that are generated by input currents with the same distribution, this approach come at the price that the considered range of inputs is restricted. Hence, the model may not generalize to different input regimes. In this work, we extend this approach along two directions: First, rather than fitting model parameters to fluctuating voltage traces, we use in-vitro recorded f/I (spike rate over current) curves of cortical layer-5 pyramidal cells in mice, covering the whole range of spike rates up to the point of depolarization block. In this way, the adaptive exponential LIF model (AdEx) [5] is fitted to perfectly match the training set consisting of the f/I curve, and then tested on recordings obtained under fluctuating current input as in previous approaches [2,4]. Second, we derive an analytical approximation to the model [6] which yields a closed expression for the f/I curve. This approach is based on the separation of time scales [6], assuming that the time constant of the adaptive current is much slower than the membrane time constant. Thus, the fitting process can be performed analytically and exactly, which is about one order of magnitude faster than fits produced via numerical integration. The approximated model still produces a remarkably low prediction error on the distinct test set consisting of fluctuating current inputs. Thus, we have created a neuron model which can be adjusted to physiological f/I curves very quickly, which is physiologically realistic in the sense that it generalizes well to independent test sets, and is also mathematically tractable.

Firing frequency response to current and conductance periodic inputs in a Ih/INap biophysical neuron model

Various neurons exhibit membrane potential (or subthreshold) resonance [1], a peak in the subthreshold voltage amplitude response to oscillatory current inputs at a certain preferred (resonant) input frequency. Previous theoretical work using linear models has shown that subthreshold resonance can be communicated to the supra-threshold regime [2,3]; i.e., the firing frequency (or signal gain) response to oscillatory input currents peaks at the subthreshold resonant frequency. Whether this property is maintained under more general conditions and for different types of inputs is still an open question. In this work, we investigate the firing frequency patterns generated in response to both current and conductance sinusoidal inputs in a biophysical (conductance-based) neuron model that includes two ionic currents: h- (Ih) and persistent sodium (INap). This model is based on measurements for stellate cells (SCs) in layer II of the medial entorhinal cortex [4] and captures various phenomena observed in SCs such as membrane potential oscillations and membrane potential (subthreshold) resonance at theta frequencies (4 - 10 Hz)[2]. The Ih/INap model describes the cell's subthreshold dynamics and the onset of spikes [5]. Spikes were generated artificially as in integrate/resonate-and-fire models (see [5]). We computed the firing rate and signal gain responses of the Ih/INap model to both current and conductance sinusoidal inputs for a wide range of frequencies and input amplitudes (Ain). The resulting patterns for current and conductance input are qualitatively different. For current inputs, the firing frequency (and signal gain) patterns show up to three prominent peaks with heights that differ only slightly. The number of peaks increases with increasing values of Ain. For small values of Ain, the peak input frequency coincides with the subthreshold resonant frequency. The voltage traces (voltage vs. time) corresponding different peaks for the same value of Ain have roughly the same number of spikes (and inter-spike intervals of similar size), and differ in the number of subthreshold oscillations interspersed in between two consecutive spikes. For conductance (excitatory) inputs, the firing rate patterns show multiple peaks with different heights. As Ain increases, the highest peak moves to the right. For input frequencies above 60 Hz, the firing rate and gain of the highest peak significantly increases relative to other peaks for the same value of Ain. This prominent peak reflects the fast time scale present in the model that has been shown to underlie hyper-excitable firing in SCs [6] observed in animal models of temporal lobe epilepsy. We use dynamical systems tools to explain the mechanism that govern the generation of the firing frequency patterns described above. We show that the nonlinearities present in the model and the time scale separation between voltage and the h-current gating variables play an important role in determining these patterns.