Bringing together the best of chemistry and biology: hybrid indicators for imaging neuronal membrane potential

2021 ◽  
Vol 363 ◽  
pp. 109348
Author(s):  
Shuzhang Liu ◽  
Junqi Yang ◽  
Peng Zou
Author(s):  
R H. Selinfreund ◽  
A. H. Cornell-Bell

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.


2020 ◽  
Vol 2 (1) ◽  
pp. 57-63 ◽  
Author(s):  
Abdallah Barjas Qaswal

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.


2020 ◽  
Author(s):  
Alison S. Walker ◽  
Benjamin K. Raliski ◽  
Kaveh Karbasi ◽  
Patrick Zhang ◽  
Kate Sanders ◽  
...  

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.


2019 ◽  
Author(s):  
Anastasia Ludwig ◽  
Pablo Serna ◽  
Lion Morgenstein ◽  
Gaoling Yang ◽  
Omri Bar-Elli ◽  
...  

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.


Author(s):  
Peggy Mason

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.


Author(s):  
J. B. SALIG ◽  
M. V. CARPIO-BERNIDO ◽  
C. C. BERNIDO ◽  
J. B. BORNALES

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.


2011 ◽  
Vol 23 (12) ◽  
pp. 3070-3093 ◽  
Author(s):  
Ryota Kobayashi ◽  
Shigeru Shinomoto ◽  
Petr Lansky

The set of firing rates of the presynaptic excitatory and inhibitory neurons constitutes the input signal to the postsynaptic neuron. Estimation of the time-varying input rates from intracellularly recorded membrane potential is investigated here. For that purpose, the membrane potential dynamics must be specified. We consider the Ornstein-Uhlenbeck stochastic process, one of the most common single-neuron models, with time-dependent mean and variance. Assuming the slow variation of these two moments, it is possible to formulate the estimation problem by using a state-space model. We develop an algorithm that estimates the paths of the mean and variance of the input current by using the empirical Bayes approach. Then the input firing rates are directly available from the moments. The proposed method is applied to three simulated data examples: constant signal, sinusoidally modulated signal, and constant signal with a jump. For the constant signal, the estimation performance of the method is comparable to that of the traditionally applied maximum likelihood method. Further, the proposed method accurately estimates both continuous and discontinuous time-variable signals. In the case of the signal with a jump, which does not satisfy the assumption of slow variability, the robustness of the method is verified. It can be concluded that the method provides reliable estimates of the total input firing rates, which are not experimentally measurable.


2017 ◽  
Author(s):  
David M. Fox ◽  
Hua-an Tseng ◽  
Tomasz G. Smolinski ◽  
Horacio G. Rotstein ◽  
Farzan Nadim

AbstractNeuronal membrane potential resonance (MPR) is associated with subthreshold and network oscillations. A number of voltage-gated ionic currents can contribute to the generation or amplification of MPR, but how the interaction of these currents with linear currents contributes to MPR is not well understood. We explored this in the pacemaker PD neurons of the crab pyloric network. The PD neuron MPR is sensitive to blockers of H- (IH) and calcium-currents (ICa). We used the impedance profile of the biological PD neuron, measured in voltage clamp, to constrain parameter values of a conductance-based model using a genetic algorithm and obtained many optimal parameter combinations. Unlike most cases of MPR, in these optimal models, the values of resonant- (fres) and phasonant- (fφ=0) frequencies were almost identical. Taking advantage of this fact, we linked the peak phase of ionic currents to their amplitude, in order to provide a mechanistic explanation the dependence of MPR on the ICa gating variable time constants. Additionally, we found that distinct pairwise correlations between ICa parameters contributed to the maintenance of fres and resonance power (QZ). Measurements of the PD neuron MPR at more hyperpolarized voltages resulted in a reduction of fres but no change in QZ. Constraining the optimal models using these data unmasked a positive correlation between the maximal conductances of IH and ICa. Thus, although IH is not necessary for MPR in this neuron type, it contributes indirectly by constraining the parameters of ICa.Author SummaryMany neuron types exhibit membrane potential resonance (MPR) in which the neuron produces the largest response to oscillatory input at some preferred (resonant) frequency and, in many systems, the network frequency is correlated with neuronal MPR. MPR is captured by a peak in the impedance vs. frequency curve (Z-profile), which is shaped by the dynamics of voltage-gated ionic currents. Although neuron types can express variable levels of ionic currents, they may have a stable resonant frequency. We used the PD neuron of the crab pyloric network to understand how MPR emerges from the interplay of the biophysical properties of multiple ionic currents, each capable of generating resonance. We show the contribution of an inactivating current at the resonant frequency in terms of interacting time constants. We measured the Z-profile of the PD neuron and explored possible combinations of model parameters that fit this experimentally measured profile. We found that the Z-profile constrains and defines correlations among parameters associated with ionic currents. Furthermore, the resonant frequency and amplitude are sensitive to different parameter sets and can be preserved by co-varying pairs of parameters along their correlation lines. Furthermore, although a resonant current may be present in a neuron, it may not directly contribute to MPR, but constrain the properties of other currents that generate MPR. Finally, constraining model parameters further to those that modify their MPR properties to changes in voltage range produces maximal conductance correlations.


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