Voltage Traces Research Articles

Collection of Simulated Data from a Thalamocortical Network Model

A major challenge in experimental data analysis is the validation of analytical methods in a fully controlled scenario where the justification of the interpretation can be made directly and not just by plausibility. In some sciences, this could be a mathematical proof, yet biological systems usually do not satisfy assumptions of mathematical theorems. One solution is to use simulations of realistic models to generate ground truth data. In neuroscience, creating such data requires plausible models of neural activity, access to high performance computers, expertise and time to prepare and run the simulations, and to process the output. To facilitate such validation tests of analytical methods we provide rich data sets including intracellular voltage traces, transmembrane currents, morphologies, and spike times. Moreover, these data can be used to study the effects of different tissue models on the measurement. The data were generated using the largest publicly available multicompartmental model of thalamocortical network (Traub et al., Journal of Neurophysiology, 93(4), 2194–2232 (Traub et al. 2005)), with activity evoked by different thalamic stimuli.

Estimation of excitatory and inhibitory synaptic conductance variations in motoneurons during locomotor-like rhythmic activity

The rhythmic activity of motoneurons (MNs) that underlies locomotion in mammals is generated by synaptic inputs from the locomotor network in the spinal cord. Thus, the quantitative estimation of excitatory and inhibitory synaptic conductances is essential to understand the mechanism by which the network generates the functional motor output. Conductance estimation is obtained from the voltage–current relationship measured by voltage-clamp- or current-clamp-recording with knowledge of the leak parameters of the recorded neuron. However, it is often difficult to obtain sufficient data to estimate synaptic conductances due to technical difficulties in electrophysiological experiments using in vivo or in vitro preparations. To address this problem, we estimated the average variations in excitatory and inhibitory synaptic conductance during a locomotion cycle from a single voltage trace without measuring the leak parameters. We found that the conductance variations can be accurately reconstructed from a voltage trace of 10 cycles by analyzing synthetic data generated from a computational model. Next, the conductance variations were estimated from mouse spinal MNs in vitro during drug-induced-locomotor-like activity. We found that the peak of excitatory conductance occurred during the depolarizing phase of the locomotor cycle, whereas the peak of inhibitory conductance occurred during the hyperpolarizing phase. These results suggest that the locomotor-like activity is generated by push–pull modulation via excitatory and inhibitory synaptic inputs.

Operando Visual and Electrochemical Correlation of Dendrite Evolution in Li Metal Electrodes

Thermodynamic and kinetic limitations in battery materials have prevented the cost effective development of a 300 mile/per charge electric vehicle using current lithium-ion battery technology. One of the most attractive strategies to increase energy density is the use of a Li metal anode instead of graphite. Unfortunately, significant technological hurdles including low Coulombic efficiency, poor cycle life, and safety concerns are preventing widespread Li metal anode commercialization in rechargeable batteries. These hurdles can all be traced back to uncontrolled dendrite formation and growth. Hundreds of researchers have tried to solve this problem over the last 50 years, but little knowledge exists on the cause, mechanism, and continued propagation of dendritic growth. Recently, in-situ microscopy has provided great insight into some aspects of general Li dendrite growth1–3, however many questions remain on the effects of dendrites in real systems and specifically in regard to growth of Li dendrites on a bulk Li metal surface. To this end we explore the effects of current density, substrate, electrolyte, and protective coatings on the transient morphological evolution of pitting and dendrite growth by operandooptical visualization of Li metal. This insight allows for the direct correlation between the evolution of dendrite morphology and the chronopotentiometric traces resulting from galvanostatic charge/discharge cycles. These voltage traces appear in a variety of battery architectures employing Li metal anodes (coin cells, Swagelok cells) and allows for an in-depth understanding of dendritic development as function of applied current. Our results show that a detailed quantification of the amount of Li lost during each individual half cycle on lithium metal can be determined through careful interpretation of potential traces as a function of time. Furthermore, by varying cell operating parameters, electrolyte composition, and introduction of surface passivation layers directly onto Li metal anodes using Atomic Layer Deposition (ALD), we are able to gain a mechanistic insight into lithium metal electrode performance, including loss of active lithium and variations in Coulombic Efficiency. In particular, ultrathin (~2nm) Al2O3 coatings by ALD were shown to double the lifetime of Li anodes before failure,4 and the operando visualization cell allows for an improved mechanistic understanding of the coupled morphological and electrochemical behavior of these ALD protected electrodes during operation. The consequences of these results can be applied to a wide range of systems, and provide a platform for quantitative comparison of a wide variety of Li metal anode protection strategies. References (1) Xu, W.; Wang, J.; Ding, F.; Chen, X.; Nasybulin, E.; Zhang, Y.; Zhang, J.-G. Energy Environ. Sci. 2014, 7, 513. (2) Mehdi, B. L.; Qian, J.; Nasybulin, E.; Park, C.; Welch, D. a.; Faller, R.; Mehta, H.; Henderson, W. a.; Xu, W.; Wang, C. M.; Evans, J. E.; Liu, J.; Zhang, J.-G.; Mueller, K. T.; Browning, N. D. Nano Lett. 2015, 15, 2168–2173. (3) Zheng, G.; Lee, S. W.; Liang, Z.; Lee, H.-W.; Yan, K.; Yao, H.; Wang, H.; Li, W.; Chu, S.; Cui, Y. Nat. Nanotechnol. 2014, 9(8), 618–623. (4) Kazyak, E.; Wood, K. N.; Dasgupta, N. P. Chem. Mater. 2015, 27 (18), 6457–6462.

Computing rates of Markov models of voltage-gated ion channels by inverting partial differential equations governing the probability density functions of the conducting and non-conducting states

Markov models are ubiquitously used to represent the function of single ion channels. However, solving the inverse problem to construct a Markov model of single channel dynamics from bilayer or patch-clamp recordings remains challenging, particularly for channels involving complex gating processes. Methods for solving the inverse problem are generally based on data from voltage clamp measurements. Here, we describe an alternative approach to this problem based on measurements of voltage traces. The voltage traces define probability density functions of the functional states of an ion channel. These probability density functions can also be computed by solving a deterministic system of partial differential equations. The inversion is based on tuning the rates of the Markov models used in the deterministic system of partial differential equations such that the solution mimics the properties of the probability density function gathered from (pseudo) experimental data as well as possible. The optimization is done by defining a cost function to measure the difference between the deterministic solution and the solution based on experimental data. By evoking the properties of this function, it is possible to infer whether the rates of the Markov model are identifiable by our method. We present applications to Markov model well-known from the literature.

Power-Law Dynamics of Membrane Conductances Increase Spiking Diversity in a Hodgkin-Huxley Model.

We studied the effects of non-Markovian power-law voltage dependent conductances on the generation of action potentials and spiking patterns in a Hodgkin-Huxley model. To implement slow-adapting power-law dynamics of the gating variables of the potassium, n, and sodium, m and h, conductances we used fractional derivatives of order η≤1. The fractional derivatives were used to solve the kinetic equations of each gate. We systematically classified the properties of each gate as a function of η. We then tested if the full model could generate action potentials with the different power-law behaving gates. Finally, we studied the patterns of action potential that emerged in each case. Our results show the model produces a wide range of action potential shapes and spiking patterns in response to constant current stimulation as a function of η. In comparison with the classical model, the action potential shapes for power-law behaving potassium conductance (n gate) showed a longer peak and shallow hyperpolarization; for power-law activation of the sodium conductance (m gate), the action potentials had a sharp rise time; and for power-law inactivation of the sodium conductance (h gate) the spikes had wider peak that for low values of η replicated pituitary- and cardiac-type action potentials. With all physiological parameters fixed a wide range of spiking patterns emerged as a function of the value of the constant input current and η, such as square wave bursting, mixed mode oscillations, and pseudo-plateau potentials. Our analyses show that the intrinsic memory trace of the fractional derivative provides a negative feedback mechanism between the voltage trace and the activity of the power-law behaving gate variable. As a consequence, power-law behaving conductances result in an increase in the number of spiking patterns a neuron can generate and, we propose, expand the computational capacity of the neuron.

Temporal distribution of the electrical energy on an exploding wire

AbstractAn exploding wire system has been experimentally studied by the observation of its plasma dynamics and the electrical energy delivered by the supporting circuit to the metallic wire. Plasma radial expansion has been obtained from visible light streak images, meanwhile electrical energy transfer dynamics was derived from the analysis of voltage and current traces of the exploding wire circuit. In these measurements, a significant portion of the electrical energy has been transferred to the exploding wire circuit during the plasma expansion, and lower limits for the resistivity during the plasma expansion confirm the existence of a central liquid or solid metallic core in addition to the expanding plasma.

Diode-like electrical characteristics of SiGe wrinkled heterostructure operating under both forward and reverse bias

We report the electrical behaviour of heterostructure channels with spatially deformed wrinkle patterns at the edge. Instead of the linear current–voltage relationship, a diode-like current–voltage trace is observed under both forward and reverse bias. Analysing the position-dependent strain and energy levels of the wrinkled heterostructure shows that the energy minimum transforms from a two-dimensional plane at the heterointerface to a one-dimensional trajectory at the wrinkled edge characterized by a potential. When a voltage is applied, the carriers at the left and right electrodes travel through a one-dimensional potential, analogously to how carriers move across a potential in the p-n junction, resulting in diode-like electrical characteristics. This work represents a step forward in developing the wrinkled structure for electronic devices.

Is Bursting More Effective than Spiking in Evoking Pituitary Hormone Secretion? A Spatiotemporal Simulation Study of Calcium Diffusion and Exocytosis

Pituitary cells are electrically excitable, in particular there are two main voltage patterns: continuous spiking and pseudo-plateau bursting. During cell depolarization, Ca2+ enters and induce elevation in the intracellular Ca2+ concentration leading to hormone secretion. Experimentally, the calcium concentration is higher during bursting compared to spiking. In this work we investigate whether pseudo-plateau bursting is more effective than spiking in evoking hormone secretion by exploiting computer simulations.Experimental voltage traces measured from GH4C1 lacto-somatotroph cells were used as input to a stochastic mathematical model of Ca2+ channel activity coupled to simulations of Ca2+ diffusion and buffering inside the cell. Furthermore, we used the computed submembrane Ca2+ profiles at varying distances from the calcium channels to drive an exocytosis model to get the resulting hormone release. We considered scenarios where Ca2+ channels were either spatially discrete or located in clusters. Finally, we used the dynamic clamp technique to convert a spiking cell to a bursting cell by injecting a model BK current, in order to investigate the effect on secretion.We found that when the release site is close to the channel, regardless of the channel configuration, spiking is as effective as bursting at evoking hormone release. In contrast, when the release site is situated farther from the channel (300-500 nm) bursting is superior to spiking. This result can be explained by the fact that bursting induces the entrance of more Ca2+. However, bursting is more effective than spiking even when normalizing to Ca2+ influx, which we explain by hormone release being facilitated by sustained Ca2+ concentration levels, since three Ca2+ ions have to bind to induce vesicle fusion, and this is more likely to occur during bursting.

Wavelength-sensitivity of mouse retinal ganglion cells recorded by a high-density micro electrode array (MEA)

Event Abstract Back to Event Wavelength-sensitivity of mouse retinal ganglion cells recorded by a high-density micro electrode array (MEA) Florian Jetter1, Gabriel Bertotti2, Roland Thewes3 and Günther Zeck4* 1 NMI at the University Tuebingen, Neurochip Research, Germany 2 Technische Universität Berlin, Chair of Sensor and Actuator Systems, Germany 3 Technische Universität Berlin, Chair of Sensor and Actuator Systems, Germany 4 NMI at the University Tuebingen, Neurochip Research, Germany Motivation: High-density CMOS-MEAs can be used to simultaneously record the electrical spiking activity from hundreds of neurons [Bertotti et al., 2014]. Neuronal spiking can be induced by electrical stimulation [Eickenscheidt and Zeck 2014], by light stimulation applied to a light-sensitive retina [Zeck et al. 2011], or by light stimulation of optogenetically transfected neurons [Herrmann et al. 2014]. In this work, we investigate the wavelength-sensitivity of different mouse retinal ganglion cells and the intrinsic wavelength-sensitivity of the response of high-density CMOS-MEAs. Material and Methods: A CMOS-based high-density MEA comprising 4225 recording sites is used for recording the ganglion cell activity in C57/Bl6 mouse retina during flickering light stimulation (1 and 5 Hz, respectively) with different wavelength and of different light stimulus sizes. Light stimuli presented on a DMD (µ-matrix, Rapp Optoelectronic, Germany) are focused through a microscope objective on the retina. The DMD is illuminated by an LED system commonly used for optogenetic activation (pe-4000, coolLED, UK). Here the results for four stimulation wavelengths are presented (405, 470, 525, and 635nm) at intensities as high as 2 mW/mm² (470 nm). Recorded data is sampled at 25 kHz. Results: Light stimulation (stimulus area: 1 mm2) evokes spiking in the interfaced retina. Based on the stimulus polarity retinal ganglion cells are broadly classified in ON or OFF type, depending on whether they respond to light on- or offset, respectively. In Fig. 1A filtered recordings are shown of the measured extracellular voltage from two selected sensors during 1 Hz stimulation. Both, ON and OFF cell types respond to the three highest wavelengths used here. The sensor site recording the ON transient cell also detects activity from a second OFF cell with smaller amplitude. In Fig.1B we present the unfiltered extracellular voltage traces recorded by a third selected sensor site for all four wavelengths. Light onset leads to a measurable change of the current in the sensing transistor (cf. Bertotti et al., 2014) or more generally speaking of the sensed recording site response, reflected as a low-frequency change of signal back-converted into the voltage domain. However, this does not prevent the detection of light-induced spiking. We note, that the ganglion cell shown in Fig. 1B is not activated by the 635 nm light stimulus. Ongoing experiments investigate the sensitivity of retinal ganglion cells to chromatic stimulation and to stimuli presented at various intensities. The induced variations of the sensor signals are wavelength-dependent, with the highest change obtained for the lowest wavelength (405 nm) and undetectable changes for red light (635 nm). Conclusion: It is shown that recording of cellular spiking activity with CMOS-based MEAs is possible during optical stimulation. Ganglion cells in the mouse retina have different wavelength-sensitivities. The light-induced low-frequency drift of the sensor signals can be completely removed for the tested wavelengths and intensities using high-pass filtering.

Mapping Micro-Circuits with Extra-Cellular Arrays in Three Layered Cortex

Mapping Micro-Circuits with Extra-Cellular Arrays in Three Layered Cortex

Developing software tools for parameter fitting and validation of neuronal models

Developing software tools for parameter fitting and validation of neuronal models

Qualitatively different scenarios for co-activation of NMDA, AMPA and GABA receptor currents on dopaminergic neuron

We introduced a reduced functional model that qualitatively describes fundamental properties of the dopaminergic (DA) neuron. The neuron is a low-frequency pacemaker, and requires special conditions to increase the frequency of its firing [1]. In more detail, only N-methyl-D-aspartate receptor (NMDAR) current can significantly elevate the frequency (more than 5 fold in comparison with pacemaking). α-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) current is not able to evoke such a high frequency. Instead, it suppresses firing at a conductance much lower than NMDAR. γ-Aminobutyric acid receptor (GABAR) activation first decreases the firing frequency, and only then suppresses firing. Thus, the latter property determines type 1 excitability for the DA neuron, whereas the difference in responses to AMPA and NMDA receptor activation make the neuron different from other well-studied types. We focus this report on the co-activation of these receptors. Co-activation of AMPA together with NMDA receptor may obscure the high frequency firing and lead directly to its suppression. There are contradictory experimental data in this case [2,3]. We show that AMPAR can do both: further contribute to the frequency increase produced by NMDAR, or impede the high-frequency firing. We show that the distinction between these two cases is the level of the background NMDAR activation. Co-activation of GABA together with NMDA receptor may also lead directly to the suppression of high-frequency oscillations (e.g. by shunting inhibition), or reduce the frequency first. Experiments clearly show the latter [4]: the frequency can be reduced back to that in control conditions when GABA and NMDA receptor currents are balanced. This property allows us to recalibrate the model so that it retains type 1 excitability not only in control, but also with activated synaptic currents. In general, activation of synaptic currents changes neural excitability, and we investigate the dynamical mechanisms responsible for the transition. As a result, we were able to construct a model of the DA neuron that collects all the properties described above. The model is essential for further research of behaviorally-relevant modulations of the DA neuron activity, which involves simultaneous excitatory and inhibitory inputs to the neuron. Figure 1 Influence of the synaptic currents on the neuron activity. A and B: dependences of the frequency on the AMPAR and NMDAR, GABAR and NMDAR conductances respectively. C: a voltage trace corresponding to the case of balanced GABAR and NMDAR currents.

Fully-automated multi-objective optimization for fitting a neuronal model with real morphology

Morphologically realistic models have successfully been used to elucidate many complex mechanisms in neuronal dendrites. However, the tuning of such models to match experimental data remains challenging. Here we introduce a fully automated parameter optimization methodology that uses the Python programming language to control the NEURON simulator in parallel on a high performance computing cluster. Using targeted experimental protocols, including sub- and supra-threshold somatic as well as dendritic voltage recordings, we constrain a model hippocampal CA1 pyramidal cell built with a complete reconstructed morphology. The optimization is performed using the non-dominated sorting genetic algorithm (NSGA-II), and model fitness is evaluated by directly comparing the simulated and recorded voltage traces. In order to impose minimal a priori assumptions, we use a multi-objective framework, which tunes all of the free parameters with respect to all of the experimental objectives simultaneously. Furthermore, the multi-objective approach avoids the pitfalls of overfitting, because the algorithm produces a diverse family of solutions on the so-called Pareto-optimal front. To facilitate model selection, we have developed a clickable interface for visually browsing the set of optimal solutions, which permits the explicit and rapid identification of trade-offs among the fitting objectives and the biophysical parameters that govern variability in the solution set. Figure 1 Clickable interface for browsing the Pareto front of solutions produced by our multiobjective optimization platform. Top row: Scatterplot of error scores across a 6-dimensional error space. The abscissa and ordinal represent errors in the objectives shown ...

High-Voltage Pulsed-Power Supply Operating at Repetitive Discharge Mode for Driving Very Small Plasma Focus Devices

The technology of switched-mode power supplies (SMPSs) has been employed to design and build a much simpler and portable high-voltage pulsed-power supply (HVPPS) as an efficient pulse drive unit for very small plasma focus devices (PFDs). The HVPPS is designed in such a way that it is able to charge a low-energy capacitor bank (84 nF, 7 kV, 2.1 J), from 4 to 7 kV at a repetitive discharge mode of 5 Hz. All control processes are carried out via a laptop through a graphical interface, written in C# language. The experimental runs were carried out in argon at 4-mbar gas pressure and the 7-kV maximum charging voltage level of the HVPPS. The results of diagnostics at a repetitive discharge mode of 5 Hz successfully confirmed the accurate performance of the SMPS and the spark gap switch for driving a very small PFD. The rise time of 10%–90% of the charging voltage, at each single-shot trace was obtained to be 110 ms. This consequence demonstrated that the control and sampling circuits were being implemented as well. After discharging, the pinching evidence was genuinely observed in the capacitor bank voltage trace. The quarter period of the discharge traces was observed to be 100 ns, which leads to a total system inductance of about 48 nH. The measured inductance was low enough to be compatible with successful performance of the very low energy PFD, leading to fast and high magnitude discharge pulses to assist the pinching evidence. This HVPPS could emerge as one of the very low cost, compact, light weight, and highly efficient power supplies used for driving the very small PFDs so far.

Nonlinear saturation of the ion-electron Buneman instability in a spherical positively pulsed gridded inertial electrostatic confinement device

A pulsed, positively biased gridded inertial electrostatic confinement device has been investigated experimentally, using Doppler broadened spectra and current and voltage traces as primary diagnostics. In the high current and energy regime explored in this paper resulting from the removal of the series ballast resistance from the external biasing circuit, large amplitude oscillations in the plasma current and potential were observed within 100 ns of the discharge onset. These oscillations are attributed to the nonlinear and saturated Buneman instability, characterised by a locked oscillation frequency as a function of increasing anode potential. The saturated Buneman instability is known to exhibit ion mass independent behaviour and cause electron trapping, resulting in a transient spatio-temporal virtual cathode and ponderomotive ion confinement, as evidenced by broadened spectra when operated at high currents.

MultiElec: A MATLAB Based Application for MEA Data Analysis.

We present MultiElec, an open source MATLAB based application for data analysis of microelectrode array (MEA) recordings. MultiElec displays an extremely user-friendly graphic user interface (GUI) that allows the simultaneous display and analysis of voltage traces for 60 electrodes and includes functions for activation-time determination, the production of activation-time heat maps with activation time and isoline display. Furthermore, local conduction velocities are semi-automatically calculated along with their corresponding vector plots. MultiElec allows ad hoc signal suppression, enabling the user to easily and efficiently handle signal artefacts and for incomplete data sets to be analysed. Voltage traces and heat maps can be simply exported for figure production and presentation. In addition, our platform is able to produce 3D videos of signal progression over all 60 electrodes. Functions are controlled entirely by a single GUI with no need for command line input or any understanding of MATLAB code. MultiElec is open source under the terms of the GNU General Public License as published by the Free Software Foundation, version 3. Both the program and source code are available to download from http://www.cancer.manchester.ac.uk/MultiElec/.

Experimental Study of the Normal Zone Propagation Velocity in Double-Layer 2G-HTS Wires by Thermal and Electrical Methods

The Normal zone propagation velocity (NZPV) of a double-layer second generation high temperature superconducting wire manufactured by American Superconductor has been measured by electrical and thermal methods, and the results have been compared and discussed. The NZPV values determined by the voltage traces are ranging from 3.8 mm/s at 0.4 I <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> to 19.2 mm/s at 0.9 I <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> ; while from 5.9 to 18.3 mm/s by the temperature traces. NZPV determined by these two approaches agrees well with each other. Also, NZPV of double-layer YBCO tape is close to that of conventional single-layer superconducting tape.

Evaluation of Electrical and Thermal Properties of Stacked YBCO Coated Conductors for Current Lead Application

This paper deals with the electrical and thermal characteristics analysis of stacked coated conductors (CCs) for current lead application. A test sample is fabricated using YBCO CCs with a stainless steel laminated stabilizer and has a heater made of the Ni-Cr wire to generate external heat disturbance. In order to evaluate a thermal stability behavior, minimum quench energy, voltage, and temperature trace are measured as a function of operating current. To verify thermal behavior in stacked CCs, numerical analysis on temperature trace is carried out using the finite-element method. The numerical simulation results are compared with the experimental data to check the validity of the simulation model.

EEG background features that predict outcome in term neonates with hypoxic ischaemic encephalopathy: A structured review

ObjectivesHypoxic ischaemic encephalopathy is a significant cause of mortality and morbidity in the term infant. Electroencephalography (EEG) is a useful tool in the assessment of newborns with HIE. This systematic review of published literature identifies those background features of EEG in term neonates with HIE that best predict neurodevelopmental outcome. MethodsA literature search was conducted using the PubMed, EMBASE and CINAHL databases from January 1960 to April 2014. Studies included in the review described recorded EEG background features, neurodevelopmental outcomes at a minimum age of 12months and were published in English. Pooled sensitivities and specificities of EEG background features were calculated and meta-analyses were performed for each background feature. ResultsOf the 860 articles generated by the initial search strategy, 52 studies were identified as potentially relevant. Twenty-one studies were excluded as they did not distinguish between different abnormal background features, leaving 31 studies from which data were extracted for the meta-analysis. The most promising neonatal EEG features are: burst suppression (sensitivity 0.87 [95% CI (0.78–0.92)]; specificity 0.82 [95% CI (0.72–0.88)]), low voltage (sensitivity 0.92 [95% CI (0.72–0.97)]; specificity 0.99 [95% CI (0.88–1.0)]), and flat trace (sensitivity 0.78 [95% CI (0.58–0.91)]; specificity 0.99 [95% CI (0.88–1.0)]). ConclusionBurst suppression, low voltage and flat trace in the EEG of term neonates with HIE most accurately predict long term neurodevelopmental outcome. SignificanceThis structured review and meta-analysis provides quality evidence of the background EEG features that best predict neurodevelopmental outcome.

Estimation of the synaptic input firing rates and characterization of the stimulation effects in an auditory neuron.

To understand information processing in neuronal circuits, it is important to infer how a sensory stimulus impacts on the synaptic input to a neuron. An increase in neuronal firing during the stimulation results from pure excitation or from a combination of excitation and inhibition. Here, we develop a method for estimating the rates of the excitatory and inhibitory synaptic inputs from a membrane voltage trace of a neuron. The method is based on a modified Ornstein-Uhlenbeck neuronal model, which aims to describe the stimulation effects on the synaptic input. The method is tested using a single-compartment neuron model with a realistic description of synaptic inputs, and it is applied to an intracellular voltage trace recorded from an auditory neuron in vivo. We find that the excitatory and inhibitory inputs increase during stimulation, suggesting that the acoustic stimuli are encoded by a combination of excitation and inhibition.