ON NEURON MEMBRANE POTENTIAL DISTRIBUTIONS FOR VOLTAGE AND TIME DEPENDENT CURRENT MODULATION

2012 ◽  
Vol 17 ◽  
pp. 19-22
Author(s):  
J. B. SALIG ◽  
M. V. CARPIO-BERNIDO ◽  
C. C. BERNIDO ◽  
J. B. BORNALES
Keyword(s):  
Membrane Potential ◽  
Planck Equation ◽  
Theoretical Models ◽  
Dynamical Variable ◽  
Integral Approach ◽  
Conditional Probability Density ◽  
Neuronal Membrane ◽  
Neuron Membrane ◽  
Current Modulation ◽  
Brain Functions

Tracking variations of neuronal membrane potential in response to multiple synaptic inputs remains an important open field of investigation since information about neural network behavior and higher brain functions can be inferred from such studies. Much experimental work has been done, with recent advances in multi-electrode recordings and imaging technology giving exciting results. However, experiments have also raised questions of compatibility with available theoretical models. Here we show how methods of modern infinite dimensional analysis allow closed form expressions for important quantities rich in information such as the conditional probability density (cpd). In particular, we use a Feynman integral approach where fluctuations in the dynamical variable are parametrized with Hida white noise variables. The stochastic process described then gives variations in time of the relative membrane potential defined as the difference between the neuron membrane and firing threshold potentials. We obtain the cpd for several forms of current modulation coefficients reflecting the flow of synaptic currents, and which are analogous to drift coefficients in the configuration space Fokker-Planck equation. In particular, we consider cases of voltage and time dependence for current modulation for periodic and non-periodic oscillatory current modulation described by sinusoidal and Bessel functions.

Measurement of spontaneous neuronal membrane activity by time lapse confocal microscopy

1995 ◽  
Vol 53 ◽  
pp. 972-973
Author(s):  
R H. Selinfreund ◽  
A. H. Cornell-Bell
Keyword(s):  
Membrane Potential ◽  
Confocal Microscopy ◽  
Patch Clamp ◽  
Electrical Activity ◽  
Time Lapse ◽  
Neuronal Firing ◽  
Neuronal Membrane ◽  
Pituitary Cells ◽  
Patch Clamp Recording ◽  
Spontaneous Electrical Activity

Cellular electrophysiological properties are normally monitored by standard patch clamp techniques . The combination of membrane potential dyes with time-lapse laser confocal microscopy provides a more direct, least destructive rapid method for monitoring changes in neuronal electrical activity. Using membrane potential dyes we found that spontaneous action potential firing can be detected using time-lapse confocal microscopy. Initially, patch clamp recording techniques were used to verify spontaneous electrical activity in GH4\C1 pituitary cells. It was found that serum depleted cells had reduced spontaneous electrical activity. Brief exposure to the serum derived growth factor, IGF-1, reconstituted electrical activity. We have examined the possibility of developing a rapid fluorescent assay to measure neuronal activity using membrane potential dyes. This neuronal regeneration assay has been adapted to run on a confocal microscope. Quantitative fluorescence is then used to measure a compounds ability to regenerate neuronal firing.The membrane potential dye di-8-ANEPPS was selected for these experiments. Di-8- ANEPPS is internalized slowly, has a high signal to noise ratio (40:1), has a linear fluorescent response to change in voltage.

scholarly journals Biosensing Motor Neuron Membrane Potential in Live Zebrafish Embryos

10.3791/55297 ◽  
2017 ◽  
Author(s):  
Lorena Benedetti ◽  
Anna Ghilardi ◽  
Laura Prosperi ◽  
Maura Francolini ◽  
Luca Del Giacco
Keyword(s):  
Membrane Potential ◽  
Motor Neuron ◽  
Zebrafish Embryos ◽  
Neuron Membrane

scholarly journals Magnesium Ions Depolarize the Neuronal Membrane via Quantum Tunneling through the Closed Channels

2020 ◽  
Vol 2 (1) ◽  
pp. 57-63 ◽  
Author(s):  
Abdallah Barjas Qaswal
Keyword(s):  
Membrane Potential ◽  
Quantum Tunneling ◽  
Magnesium Concentration ◽  
Resting Membrane Potential ◽  
Neuronal Membrane ◽  
Magnesium Ions ◽  
Quantum Conductance ◽  
Depolarization Effect ◽  
Bipolar Patients ◽  
Quantum Mechanical Approach

Magnesium ions have many cellular actions including the suppression of the excitability of neurons; however, the depolarization effect of magnesium ions seems to be contradictory. Thus several hypotheses have aimed to explain this effect. In this study, a quantum mechanical approach is used to explain the depolarization action of magnesium. The model of quantum tunneling of magnesium ions through the closed sodium voltage-gated channels was adopted to calculate the quantum conductance of magnesium ions, and a modified version of Goldman–Hodgkin–Katz equation was used to determine whether this quantum conductance was significant in affecting the resting membrane potential of neurons. Accordingly, it was found that extracellular magnesium ions can exhibit a depolarization effect on membrane potential, and the degree of this depolarization depends on the tunneling probability, the channels’ selectivity to magnesium ions, the channels’ density in the neuronal membrane, and the extracellular magnesium concentration. In addition, extracellular magnesium ions achieve a quantum conductance much higher than intracellular ones because they have a higher kinetic energy. This study aims to identify the mechanism of the depolarization action of magnesium because this may help in offering better therapeutic solutions for fetal neuroprotection and in stabilizing the mood of bipolar patients.

scholarly journals Optical spike detection and connectivity analysis with a far-red voltage-sensitive fluorophore reveals changes to network connectivity in development and disease

2020 ◽  
Author(s):  
Alison S. Walker ◽  
Benjamin K. Raliski ◽  
Kaveh Karbasi ◽  
Patrick Zhang ◽  
Kate Sanders ◽  
...  
Keyword(s):  
Membrane Potential ◽  
Patch Clamp ◽  
Amyloid Beta ◽  
Transmembrane Potential ◽  
Network Connectivity ◽  
Neuronal Membrane ◽  
Connectivity Analysis ◽  
Neuronal Connectivity ◽  
Voltage Imaging ◽  
Patch Clamp Electrophysiology

AbstractThe ability to optically record dynamics of neuronal membrane potential promises to revolutionize our understanding of neurobiology. In this study, we show that the far-red voltage sensitive fluorophore, Berkeley Red Sensor of Transmembrane potential −1, or BeRST 1, can be used to monitor neuronal membrane potential changes across dozens of neurons at a sampling rate of 500 Hz. Notably, voltage imaging with BeRST 1 can be implemented with affordable, commercially available illumination sources, optics, and detectors. BeRST 1 is well-tolerated in cultures of rat hippocampal neurons and provides exceptional optical recording fidelity, as judged by dual fluorescence imaging and patch-clamp electrophysiology. We developed a semi-automated spike-picking program to reduce user bias when calling action potentials and used this in conjunction with BeRST 1 to develop an optical spike and connectivity analysis workflow (OSCA) for high-throughput dissection of neuronal activity dynamics in development and disease. The high temporal resolution of BeRST 1 enables dissection of firing rate changes in response to acute, pharmacological interventions with commonly used inhibitors like gabazine and picrotoxin. Over longer periods of time, BeRST 1 also tracks chronic perturbations to neurons exposed to amyloid beta (Aβ1-42), revealing modest changes to spiking frequency but profound changes to overall network connectivity. Finally, we use OSCA to track changes in neuronal connectivity during development, providing a functional readout of network assembly. We envision that use of BeRST 1 and OSCA described here will be of use to the broad neuroscience community.Significance StatementOptical methods to visualize membrane potential dynamics provide a powerful complement to Ca2+ imaging, patch clamp electrophysiology, and multi-electrode array recordings. However, modern voltage imaging strategies often require complicated optics, custom-built microscopes, or genetic manipulations that are impractical outside of a subset of model organisms. Here, we describe the use of Berkeley Red Sensor of Transmembrane potential, or BeRST 1, a far-red voltage-sensitive fluorophore that can directly visualize membrane potential changes with millisecond resolution across dozens of neurons. Using only commercially available components, voltage imaging with BeRST 1 reveals profound changes in neuronal connectivity during development, exposes changes to firing rate during acute pharmacological perturbation, and illuminates substantial increases in network connectivity in response to chronic exposure to amyloid beta.

scholarly journals Feasibility analysis of semiconductor voltage nanosensors for neuronal membrane potential sensing

2019 ◽  
Author(s):  
Anastasia Ludwig ◽  
Pablo Serna ◽  
Lion Morgenstein ◽  
Gaoling Yang ◽  
Omri Bar-Elli ◽  
...  
Keyword(s):  
Membrane Potential ◽  
Electric Fields ◽  
Stark Effect ◽  
High Sensitivity ◽  
Time Lapse ◽  
Neuronal Membrane ◽  
Attractive Alternative ◽  
Wide Field ◽  
Particle Level ◽  
Semiconductor Voltage

AbstractIn the last decade, optical imaging methods have significantly improved our understanding of the information processing principles in the brain. Although many promising tools have been designed, sensors of membrane potential are lagging behind the rest. Semiconductor nanoparticles are an attractive alternative to classical voltage indicators, such as voltage-sensitive dyes and proteins. Such nanoparticles exhibit high sensitivity to external electric fields via the quantum-confined Stark effect. Here we report the development of lipid-coated semiconductor voltage-sensitive nanorods (vsNRs) that self-insert into the neuronal membrane. We describe a workflow to detect and process the photoluminescent signal of vsNRs after wide-field time-lapse recordings. We also present data indicating that vsNRs are feasible for sensing membrane potential in neurons at a single-particle level. This shows the potential of vsNRs for detection of neuronal activity with unprecedentedly high spatial and temporal resolution.

The Neuron at Rest

2017 ◽  
Author(s):  
Peggy Mason
Keyword(s):  
Membrane Potential ◽  
Ion Channels ◽  
Ionic Species ◽  
Membrane Resistance ◽  
Chloride Ions ◽  
Resting Membrane Potential ◽  
Neuronal Membrane ◽  
Nernst Potential ◽  
State Potential ◽  
Pass Through

Neuronal membrane potential depends on the distribution of ions across the plasma membrane and the permeability of the membrane to those ions afforded by transmembrane proteins. Ions cannot pass through a lipid bilayer but enter or exit neurons through ion channels. When activated by voltage or a ligand, ion channels open to form a pore through which selective ions can pass. The ion channels that support a resting membrane potential are critical to setting a cell’s excitability. From the distribution of an ionic species, the Nernst potential can be used to predict the steady-state potential for that one ion. Neurons are permeable to potassium, sodium, and chloride ions at rest. The Goldman-Hodgkin-Katz equation takes into consideration the influence of multiple ionic species and can be used to predict neuronal membrane potential. Finally, how synaptic inputs affect neurons through synaptic currents and changes in membrane resistance is described.

scholarly journals Some aspects of the inertial spin model for flocks and related kinetic equations

2020 ◽  
Vol 30 (10) ◽  
pp. 1987-2022 ◽  
Author(s):  
D. Benedetto ◽  
P. Buttà ◽  
E. Caglioti
Keyword(s):  
Thermal Noise ◽  
Kinetic Equations ◽  
Mean Field ◽  
Planck Equation ◽  
Dynamical Variable ◽  
Spin Model ◽  
Field Limit ◽  
Mean Field Limit ◽  
Macroscopic Behavior ◽  
The Mean

In this paper, we study the macroscopic behavior of the inertial spin (IS) model. This model has been recently proposed to describe the collective dynamics of flocks of birds, and its main feature is the presence of an auxiliary dynamical variable, a sort of internal spin, which conveys the interaction among the birds with the effect of better describing the turning of flocks. After discussing the geometrical and mechanical properties of the IS model, we show that, in the case of constant interaction among the birds, its mean-field limit is described by a nonlinear Fokker–Planck equation, whose equilibria are fully characterized. Finally, in the case of non-constant interactions, we derive the kinetic equation for the mean-field limit of the model in the absence of thermal noise, and explore its macroscopic behavior by analyzing the mono-kinetic solutions.

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