Complexin has a dual synaptic function as checkpoint protein in vesicle priming and as a promoter of vesicle fusion.

The presynaptic SNARE-complex regulator complexin (Cplx) enhances the fusogenicity of primed synaptic vesicles (SVs). Consequently, Cplx deletion impairs action potential-evoked transmitter release. Conversely, though, Cplx loss enhances spontaneous and delayed asynchronous release at certain synapse types. Using electrophysiology and kinetic modeling, we show that such seemingly contradictory transmitter release phenotypes seen upon Cplx deletion can be explained by an additional of Cplx in the control of SV priming, where its ablation facilitates the generation of a "faulty" SV fusion apparatus. Supporting this notion, a sequential two-step priming scheme, featuring reduced vesicle fusogenicity and increased transition rates into the faulty primed state, reproduces all aberrations of transmitter release modes and short-term synaptic plasticity seen upon Cplx loss. Accordingly, we propose a dual presynaptic function for the SNARE-complex interactor Cplx, one as a "checkpoint" protein that guarantees the proper assembly of the fusion machinery during vesicle priming, and one in boosting vesicle fusogenicity.

T-wave inversion through inhomogeneous voltage diffusion within the FK3V cardiac model.

The heart beats are due to the synchronized contraction of cardiomyocytes triggered by a periodic sequence of electrical signals called action potentials, which originate in the sinoatrial node and spread through the heart's electrical system. A large body of work is devoted to modeling the propagation of the action potential and to reproducing reliably its shape and duration. Connection of computational modeling of cells to macroscopic phenomenological curves such as the electrocardiogram has been also intense, due to its clinical importance in analyzing cardiovascular diseases. In this work, we simulate the dynamics of action potential propagation using the three-variable Fenton-Karma model that can account for both normal and damaged cells through a the spatially inhomogeneous voltage diffusion coefficient. We monitor the action potential propagation in the cardiac tissue and calculate the pseudo-electrocardiogram that reproduces the R and T waves. The R-wave amplitude varies according to a double exponential law as a function of the (spatially homogeneous, for an isotropic tissue) diffusion coefficient. The addition of spatial inhomogeneity in the diffusion coefficient by means of a defected region representing damaged cardiac cells may result in T-wave inversion in the calculated pseudo-electrocardiogram. The transition from positive to negative polarity of the T-wave is analyzed as a function of the length and the depth of the defected region.

Online prediction of sustained muscle force from individual motor unit activities using adaptive surface EMG decomposition.

Decoding movement intentions from motor unit (MU) activities to represent neural drive information plays a central role in establishing neural interfaces, but there remains a great challenge for obtaining precise MU activities during sustained muscle contractions. In this paper, we presented an online muscle force prediction method driven by individual MU activities that were decomposed from prolonged surface electromyogram (SEMG) signals in real time. In the training stage of the proposed method, a set of separation vectors was initialized for decomposing MU activities. After transferring each decomposed MU activity into a twitch force train according to its action potential waveform, a neural network was designed and trained for predicting muscle force. In the subsequent online stage, a practical double-thread-parallel algorithm was developed. One frontend thread predicted the muscle force in real time utilizing the trained network and the other backend thread simultaneously updated the separation vectors. To assess the performance of the proposed method, SEMG signals were recorded from the abductor pollicis brevis muscles of eight subjects and the contraction force was simultaneously collected. With the update procedure in the backend thread, the force prediction performance of the proposed method was significantly improved in terms of lower root mean square deviation (RMSD) of around 10% and higher fitness (R2) of around 0.90, outperforming two conventional methods. This study provides a promising technique for real-time myoelectric applications in movement control and health.

Tension activation of mechanosensitive two-pore domain K+ channels TRAAK, TREK-1, and TREK-2.

TRAAK, TREK-1, and TREK-2 are mechanosensitive two-pore domain K+ (K2P) channels that contribute to action potential propagation, sensory transduction, and muscle contraction. While structural and functional studies have led to models that explain their mechanosensitivity, we lack a quantitative understanding of channel activation by membrane tension. Here, we define the tension response of mechanosensitive K2Ps using patch-clamp recording and imaging. All are low-threshold mechanosensitive channels (T10%/50% 0.6-2.7 / 4.4-6.4 mN/m) with distinct response profiles. TRAAK is most sensitive, TREK-1 intermediate, and TREK-2 least sensitive. TRAAK and TREK-1 are activated broadly over a range encompassing nearly all physiologically relevant tensions. TREK-2, in contrast, activates over a narrower range like mechanosensitive channels Piezo1, MscS, and MscL. We further show that low-frequency, low-intensity focused ultrasound increases membrane tension to activate TRAAK and MscS. This work provides insight into tension gating of mechanosensitive K2Ps relevant to understanding their physiological roles and potential applications for ultrasonic neuromodulation.

Enhanced Release Probability without Changes in Synaptic Delay during Analogue-Digital Facilitation.

Neuronal timing with millisecond precision is critical for many brain functions such as sensory perception, learning and memory formation. At the level of the chemical synapse, the synaptic delay is determined by the presynaptic release probability (Pr) and the waveform of the presynaptic action potential (AP). For instance, paired-pulse facilitation or presynaptic long-term potentiation are associated with reductions in the synaptic delay, whereas paired-pulse depression or presynaptic long-term depression are associated with an increased synaptic delay. Parallelly, the AP broadening that results from the inactivation of voltage gated potassium (Kv) channels responsible for the repolarization phase of the AP delays the synaptic response, and the inactivation of sodium (Nav) channels by voltage reduces the synaptic latency. However, whether synaptic delay is modulated during depolarization-induced analogue-digital facilitation (d-ADF), a form of context-dependent synaptic facilitation induced by prolonged depolarization of the presynaptic neuron and mediated by the voltage-inactivation of presynaptic Kv1 channels, remains unclear. We show here that despite Pr being elevated during d-ADF at pyramidal L5-L5 cell synapses, the synaptic delay is surprisingly unchanged. This finding suggests that both Pr- and AP-dependent changes in synaptic delay compensate for each other during d-ADF. We conclude that, in contrast to other short- or long-term modulations of presynaptic release, synaptic timing is not affected during d-ADF because of the opposite interaction of Pr- and AP-dependent modulations of synaptic delay.

Biophysical mechanisms underlying tefluthrin-induced modulation of gating changes and resurgent current generation in the human Nav1.4 channel.

Human skeletal muscle contraction is triggered by activation of Nav1.4 channels. Nav1.4 channels can generate resurgent currents by channel reopening at hyperpolarized potentials through a gating transition dependent on the intracellular Navß4 peptide in the physiological conditions. Tefluthrin (TEF) is a pyrethroid insecticide that can disrupt electrical signaling in nerves and skeletal muscle, resulting in seizures, muscle spasms, fasciculations, and mental confusion. TEF can also induce tail currents through other voltage-gated sodium channels in the absence of Navß4 peptide, suggesting that muscle spasms may be caused by resurgent currents. Further, intracellular Navß4 peptide and extracellular TEF may show competitive or synergistic effects; however, their binding sites are still unknown. To address these issues, electrophysiological recordings were performed on CHO-K1 cells expressing Nav1.4 channels with intracellular Navß4 peptide, extracellular TEF, or both. TEF and Navß4 peptide induced a hyperpolarizing shift of activation and inactivation curves in the Nav1.4 channel. TEF also substantially prolonged the inactivation time constants, while simultaneous application of Navß4 peptide partially reversed this effect. Resurgent currents were enhanced by TEF and Navß4 peptide at negative potentials, but TEF more potently enhances resurgent currents and dampens decay of resurgent currents. With longer depolarization, peak resurgent currents decay was fastest with the TEF alone. Molecular docking suggested that TEF and Navß4 peptide binding site(s) are not in the narrowest part of the channel pore, but rather in the bundle-crossing regions and in the domain linkers, respectively. TEF can induce resurgent currents independently and synergistically with Navß4 peptide, which may explain the muscle spasms observed in TEF intoxication.

Neural network emulation of the human ventricular cardiomyocyte action potential for more efficient computations in pharmacological studies.

Computer models of the human ventricular cardiomyocyte action potential (AP) have reached a level of detail and maturity that has led to an increasing number of applications in the pharmaceutical sector. However, interfacing the models with experimental data can become a significant computational burden. To mitigate the computational burden, the present study introduces a neural network (NN) that emulates the AP for given maximum conductances of selected ion channels, pumps, and exchangers. Its applicability in pharmacological studies was tested on synthetic and experimental data. The NN emulator potentially enables massive speed-ups compared to regular simulations and the forward problem (find drugged AP for pharmacological parameters defined as scaling factors of control maximum conductances) on synthetic data could be solved with average root-mean-square errors (RMSE) of 0.47 mV in normal APs and of 14.5 mV in abnormal APs exhibiting early afterdepolarizations (72.5% of the emulated APs were alining with the abnormality, and the substantial majority of the remaining APs demonstrated pronounced proximity). This demonstrates not only very fast and mostly very accurate AP emulations but also the capability of accounting for discontinuities, a major advantage over existing emulation strategies. Furthermore, the inverse problem (find pharmacological parameters for control and drugged APs through optimization) on synthetic data could be solved with high accuracy shown by a maximum RMSE of 0.22 in the estimated pharmacological parameters. However, notable mismatches were observed between pharmacological parameters estimated from experimental data and distributions obtained from the Comprehensive in vitro Proarrhythmia Assay initiative. This reveals larger inaccuracies which can be attributed particularly to the fact that small tissue preparations were studied while the emulator was trained on single cardiomyocyte data. Overall, our study highlights the potential of NN emulators as powerful tool for an increased efficiency in future quantitative systems pharmacology studies.

A modular organic neuromorphic spiking circuit for retina-inspired sensory coding and neurotransmitter-mediated neural pathways.

Signal communication mechanisms within the human body rely on the transmission and modulation of action potentials. Replicating the interdependent functions of receptors, neurons and synapses with organic artificial neurons and biohybrid synapses is an essential first step towards merging neuromorphic circuits and biological systems, crucial for computing at the biological interface. However, most organic neuromorphic systems are based on simple circuits which exhibit limited adaptability to both external and internal biological cues, and are restricted to emulate only specific the functions of an individual neuron/synapse. Here, we present a modular neuromorphic system which combines organic spiking neurons and biohybrid synapses to replicate a neural pathway. The spiking neuron mimics the sensory coding function of afferent neurons from light stimuli, while the neuromodulatory activity of interneurons is emulated by neurotransmitters-mediated biohybrid synapses. Combining these functions, we create a modular connection between multiple neurons to establish a pre-processing retinal pathway primitive.

Impact on backpropagation of the spatial heterogeneity of sodium channel kinetics in the axon initial segment.

In a variety of neurons, action potentials (APs) initiate at the proximal axon, within a region called the axon initial segment (AIS), which has a high density of voltage-gated sodium channels (NaVs) on its membrane. In pyramidal neurons, the proximal AIS has been reported to exhibit a higher proportion of NaVs with gating properties that are "right-shifted" to more depolarized voltages, compared to the distal AIS. Further, recent experiments have revealed that as neurons develop, the spatial distribution of NaV subtypes along the AIS can change substantially, suggesting that neurons tune their excitability by modifying said distribution. When neurons are stimulated axonally, computational modelling has shown that this spatial separation of gating properties in the AIS enhances the backpropagation of APs into the dendrites. In contrast, in the more natural scenario of somatic stimulation, our simulations show that the same distribution can impede backpropagation, suggesting that the choice of orthodromic versus antidromic stimulation can bias or even invert experimental findings regarding the role of NaV subtypes in the AIS. We implemented a range of hypothetical NaV distributions in the AIS of three multicompartmental pyramidal cell models and investigated the precise kinetic mechanisms underlying such effects, as the spatial distribution of NaV subtypes is varied. With axonal stimulation, proximal NaV availability dominates, such that concentrating right-shifted NaVs in the proximal AIS promotes backpropagation. However, with somatic stimulation, the models are insensitive to availability kinetics. Instead, the higher activation threshold of right-shifted NaVs in the AIS impedes backpropagation. Therefore, recently observed developmental changes to the spatial separation and relative proportions of NaV1.2 and NaV1.6 in the AIS differentially impact activation and availability. The observed effects on backpropagation, and potentially learning via its putative role in synaptic plasticity (e.g. through spike-timing-dependent plasticity), are opposite for orthodromic versus antidromic stimulation, which should inform hypotheses about the impact of the developmentally regulated subcellular localization of these NaV subtypes.

Mean-field method for generic conductance-based integrate-and-fire neurons with finite timescales.

The construction of transfer functions in theoretical neuroscience plays an important role in determining the spiking rate behavior of neurons in networks. These functions can be obtained through various fitting methods, but the biological relevance of the parameters is not always clear. However, for stationary inputs, such functions can be obtained without the adjustment of free parameters by using mean-field methods. In this work, we expand current Fokker-Planck approaches to account for the concurrent influence of colored and multiplicative noise terms on generic conductance-based integrate-and-fire neurons. We reduce the resulting stochastic system through the application of the diffusion approximation to a one-dimensional Langevin equation. An effective Fokker-Planck is then constructed using Fox Theory, which is solved numerically using a newly developed double integration procedure to obtain the transfer function and the membrane potential distribution. The solution is capable of reproducing the transfer function and the stationary voltage distribution of simulated neurons across a wide range of parameters. The method can also be easily extended to account for different sources of noise with various multiplicative terms, and it can be used in other types of problems in principle.

Intracellular ion accumulation in the genesis of complex action potential dynamics under cardiac diseases.

Intracellular ions, including sodium (Na^{+}), calcium (Ca^{2+}), and potassium (K^{+}), etc., accumulate slowly after a change of the state of the heart, such as a change of the heart rate. The goal of this study is to understand the roles of slow ion accumulation in the genesis of cardiac memory and complex action-potential duration (APD) dynamics that can lead to lethal cardiac arrhythmias. We carry out numerical simulations of a detailed action potential model of ventricular myocytes under normal and diseased conditions, which exhibit memory effects and complex APD dynamics. We develop a low-dimensional iterated map (IM) model to describe the dynamics of Na^{+}, Ca^{2+}, and APD and use it to uncover the underlying dynamical mechanisms. The development of the IM model is informed by simulation results under the normal condition. We then use the IM model to perform linear stability analyses and computer simulations to investigate the bifurcations and complex APD dynamics, which depend on the feedback loops between APD and intracellular Ca^{2+} and Na^{+} concentrations and the steepness of the APD response to the ion concentrations. When the feedback between APD and Ca^{2+} concentration is positive, a Hopf bifurcation leading to periodic oscillatory behavior occurs as the steepness of the APD response to the ion concentrations increases. The negative feedback loop between APD and Na^{+} concentration is required for the Hopf bifurcation. When the feedback between APD and Ca^{2+} concentration is negative, period-doubling bifurcations leading to high periodicity and chaos occurs. In this case, Na^{+} accumulation plays little role in the dynamics. Finally, we carry out simulations of the detailed action potential model under two diseased conditions, which exhibit steep APD responses to ion concentrations. Under both conditions, Hopf bifurcations leading to slow oscillations or period-doubling bifurcations leading to high periodicity and chaotic APD dynamics occur, depending on the strength of the ion pump-Na^{+}-Ca^{2+} exchanger. Using functions reconstructed from the simulation data, the IM model accurately captures the bifurcations and dynamics under the two diseased conditions. In conclusion, besides using computer simulations of a detailed high-dimensional action-potential model to investigate the effects of slow ion accumulation and short-term memory on bifurcations and genesis of complex APD dynamics in cardiac myocytes under diseased conditions, this study also provides a low-dimensional mathematical tool, i.e., the IM model, to allow stability analyses for uncovering the underlying mechanisms.

Linear and nonlinear integrate-and-fire neurons driven by synaptic shot noise with reversal potentials.

The steady-state firing rate and firing-rate response of the leaky and exponential integrate-and-fire models receiving synaptic shot noise with excitatory and inhibitory reversal potentials is examined. For the particular case where the underlying synaptic conductances are exponentially distributed, it is shown that the master equation for a population of such model neurons can be reduced from an integrodifferential form to a more tractable set of three differential equations. The system is nevertheless more challenging analytically than for current-based synapses: where possible, analytical results are provided with an efficient numerical scheme and code provided for other quantities. The increased tractability of the framework developed supports an ongoing critical comparison between models in which synapses are treated with and without reversal potentials, such as recently in the context of networks with balanced excitatory and inhibitory conductances.

How neuronal morphology impacts the synchronisation state of neuronal networks.

The biophysical properties of neurons not only affect how information is processed within cells, they can also impact the dynamical states of the network. Specifically, the cellular dynamics of action-potential generation have shown relevance for setting the (de)synchronisation state of the network. The dynamics of tonically spiking neurons typically fall into one of three qualitatively distinct types that arise from distinct mathematical bifurcations of voltage dynamics at the onset of spiking. Accordingly, changes in ion channel composition or even external factors, like temperature, have been demonstrated to switch network behaviour via changes in the spike onset bifurcation and hence its associated dynamical type. A thus far less addressed modulator of neuronal dynamics is cellular morphology. Based on simplified and anatomically realistic mathematical neuron models, we show here that the extent of dendritic arborisation has an influence on the neuronal dynamical spiking type and therefore on the (de)synchronisation state of the network. Specifically, larger dendritic trees prime neuronal dynamics for in-phase-synchronised or splayed-out activity in weakly coupled networks, in contrast to cells with otherwise identical properties yet smaller dendrites. Our biophysical insights hold for generic multicompartmental classes of spiking neuron models (from ball-and-stick-type to anatomically reconstructed models) and establish a connection between neuronal morphology and the susceptibility of neural tissue to synchronisation in health and disease.

Beyond a Transmission Cable-New Technologies to Reveal the Richness in Axonal Electrophysiology.

The axon is a neuronal structure capable of processing, encoding, and transmitting information. This assessment contrasts with a limiting, but deeply rooted, perspective where the axon functions solely as a transmission cable of somatodendritic activity, sending signals in the form of stereotypical action potentials. This perspective arose, at least partially, because of the technical difficulties in probing axons: their extreme length-to-diameter ratio and intricate growth paths preclude the study of their dynamics through traditional techniques. Recent findings are challenging this view and revealing a much larger repertoire of axonal computations. Axons display complex signaling processes and structure-function relationships, which can be modulated via diverse activity-dependent mechanisms. Additionally, axons can exhibit patterns of activity that are dramatically different from those of their corresponding soma. Not surprisingly, many of these recent discoveries have been driven by novel technology developments, which allow for in vitro axon electrophysiology with unprecedented spatiotemporal resolution and signal-to-noise ratio. In this review, we outline the state-of-the-art in vitro toolset for axonal electrophysiology and summarize the recent discoveries in axon function it has enabled. We also review the increasing repertoire of microtechnologies for controlling axon guidance which, in combination with the available cutting-edge electrophysiology and imaging approaches, have the potential for more controlled and high-throughput in vitro studies. We anticipate that a larger adoption of these new technologies by the neuroscience community will drive a new era of experimental opportunities in the study of axon physiology and consequently, neuronal function.

Mono-allelic KCNB2 variants lead to a neurodevelopmental syndrome caused by altered channel inactivation.

Ion channels mediate voltage fluxes or action potentials that are central to the functioning of excitable cells such as neurons. The KCNB family of voltage-gated potassium channels (Kv) consists of two members (KCNB1 and KCNB2) encoded by KCNB1 and KCNB2, respectively. These channels are major contributors to delayed rectifier potassium currents arising from the neuronal soma which modulate overall excitability of neurons. In this study, we identified several mono-allelic pathogenic missense variants in KCNB2, in individuals with a neurodevelopmental syndrome with epilepsy and autism in some individuals. Recurrent dysmorphisms included a broad forehead, synophrys, and digital anomalies. Additionally, we selected three variants where genetic transmission has not been assessed, from two epilepsy studies, for inclusion in our experiments. We characterized channel properties of these variants by expressing them in oocytes of Xenopus laevis and conducting cut-open oocyte voltage clamp electrophysiology. Our datasets indicate no significant change in absolute conductance and conductance-voltage relationships of most disease variants as compared to wild type (WT), when expressed either alone or co-expressed with WT-KCNB2. However, variants c.1141A>G (p.Thr381Ala) and c.641C>T (p.Thr214Met) show complete abrogation of currents when expressed alone with the former exhibiting a left shift in activation midpoint when expressed alone or with WT-KCNB2. The variants we studied, nevertheless, show collective features of increased inactivation shifted to hyperpolarized potentials. We suggest that the effects of the variants on channel inactivation result in hyper-excitability of neurons, which contributes to disease manifestations.

An operating principle of the cerebral cortex, and a cellular mechanism for attentional trial-and-error pattern learning and useful classification extraction.

A feature of the brains of intelligent animals is the ability to learn to respond to an ensemble of active neuronal inputs with a behaviorally appropriate ensemble of active neuronal outputs. Previously, a hypothesis was proposed on how this mechanism is implemented at the cellular level within the neocortical pyramidal neuron: the apical tuft or perisomatic inputs initiate "guess" neuron firings, while the basal dendrites identify input patterns based on excited synaptic clusters, with the cluster excitation strength adjusted based on reward feedback. This simple mechanism allows neurons to learn to classify their inputs in a surprisingly intelligent manner. Here, we revise and extend this hypothesis. We modify synaptic plasticity rules to align with behavioral time scale synaptic plasticity (BTSP) observed in hippocampal area CA1, making the framework more biophysically and behaviorally plausible. The neurons for the guess firings are selected in a voluntary manner via feedback connections to apical tufts in the neocortical layer 1, leading to dendritic Ca2+ spikes with burst firing, which are postulated to be neural correlates of attentional, aware processing. Once learned, the neuronal input classification is executed without voluntary or conscious control, enabling hierarchical incremental learning of classifications that is effective in our inherently classifiable world. In addition to voluntary, we propose that pyramidal neuron burst firing can be involuntary, also initiated via apical tuft inputs, drawing attention toward important cues such as novelty and noxious stimuli. We classify the excitations of neocortical pyramidal neurons into four categories based on their excitation pathway: attentional versus automatic and voluntary/acquired versus involuntary. Additionally, we hypothesize that dendrites within pyramidal neuron minicolumn bundles are coupled via depolarization cross-induction, enabling minicolumn functions such as the creation of powerful hierarchical "hyperneurons" and the internal representation of the external world. We suggest building blocks to extend the microcircuit theory to network-level processing, which, interestingly, yields variants resembling the artificial neural networks currently in use. On a more speculative note, we conjecture that principles of intelligence in universes governed by certain types of physical laws might resemble ours.

Local origin of excitatory-inhibitory tuning equivalence in a cortical network.

The interplay between excitation and inhibition determines the fidelity of cortical representations. The receptive fields of excitatory neurons are often finely tuned to encoded features, but the principles governing the tuning of inhibitory neurons remain elusive. In this study, we recorded populations of neurons in the mouse postsubiculum (PoSub), where the majority of excitatory neurons are head-direction (HD) cells. We show that the tuning of fast-spiking (FS) cells, the largest class of cortical inhibitory neurons, was broad and frequently radially symmetrical. By decomposing tuning curves using the Fourier transform, we identified an equivalence in tuning between PoSub-FS and PoSub-HD cell populations. Furthermore, recordings, optogenetic manipulations of upstream thalamic populations and computational modeling provide evidence that the tuning of PoSub-FS cells has a local origin. These findings support the notion that the equivalence of neuronal tuning between excitatory and inhibitory cell populations is an intrinsic property of local cortical networks.

Synaptotagmin 7 docks synaptic vesicles to support facilitation and Doc2α-triggered asynchronous release.

Despite decades of intense study, the molecular basis of asynchronous neurotransmitter release remains enigmatic. Synaptotagmin (syt) 7 and Doc2 have both been proposed as Ca2+ sensors that trigger this mode of exocytosis, but conflicting findings have led to controversy. Here, we demonstrate that at excitatory mouse hippocampal synapses, Doc2α is the major Ca2+ sensor for asynchronous release, while syt7 supports this process through activity-dependent docking of synaptic vesicles. In synapses lacking Doc2α, asynchronous release after single action potentials is strongly reduced, while deleting syt7 has no effect. However, in the absence of syt7, docked vesicles cannot be replenished on millisecond timescales. Consequently, both synchronous and asynchronous release depress from the second pulse onward during repetitive activity. By contrast, synapses lacking Doc2α have normal activity-dependent docking, but continue to exhibit decreased asynchronous release after multiple stimuli. Moreover, disruption of both Ca2+ sensors is non-additive. These findings result in a new model whereby syt7 drives activity-dependent docking, thus providing synaptic vesicles for synchronous (syt1) and asynchronous (Doc2 and other unidentified sensors) release during ongoing transmission.

Single-cell ionic current phenotyping explains stem cell-derived cardiomyocyte action potential morphology.

Human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) are a promising tool to study arrhythmia-related factors, but the variability of action potential (AP) recordings from these cells limits their use as an in vitro model. In this study, we use recently published brief (10 s), dynamic voltage-clamp (VC) data to provide mechanistic insights into the ionic currents contributing to AP heterogeneity; we call this approach rapid ionic current phenotyping (RICP). Features of this VC data were correlated to AP recordings from the same cells, and we used computational models to generate mechanistic insights into cellular heterogeneity. This analysis uncovered several interesting links between AP morphology and ionic current density: both L-type calcium and sodium currents contribute to upstroke velocity, rapid delayed rectifier K+ current is the main determinant of the maximal diastolic potential, and an outward current in the activation range of slow delayed rectifier K+ is the main determinant of AP duration. Our analysis also identified an outward current in several cells at 6 mV that is not reproduced by iPSC-CM mathematical models but contributes to determining AP duration. RICP can be used to explain how cell-to-cell variability in ionic currents gives rise to AP heterogeneity. Because of its brief duration (10 s) and ease of data interpretation, we recommend the use of RICP for single-cell patch-clamp experiments that include the acquisition of APs.NEW & NOTEWORTHY We present rapid ionic current phenotyping (RICP), a current quantification approach based on an optimized voltage-clamp protocol. The method captures a rich snapshot of the ionic current dynamics, providing quantitative information about multiple currents (e.g., ICa,L, IKr) in the same cell. The protocol helped to identify key ionic determinants of cellular action potential heterogeneity in iPSC-CMs. This included unexpected results, such as the critical role of IKr in establishing the maximum diastolic potential.

A red-emitting carborhodamine for monitoring and measuring membrane potential.

Biological membrane potentials, or voltages, are a central facet of cellular life. Optical methods to visualize cellular membrane voltages with fluorescent indicators are an attractive complement to traditional electrode-based approaches, since imaging methods can be high throughput, less invasive, and provide more spatial resolution than electrodes. Recently developed fluorescent indicators for voltage largely report changes in membrane voltage by monitoring voltage-dependent fluctuations in fluorescence intensity. However, it would be useful to be able to not only monitor changes but also measure values of membrane potentials. This study discloses a fluorescent indicator which can address both. We describe the synthesis of a sulfonated tetramethyl carborhodamine fluorophore. When this carborhodamine is conjugated with an electron-rich, methoxy (-OMe) containing phenylenevinylene molecular wire, the resulting molecule, CRhOMe, is a voltage-sensitive fluorophore with red/far-red fluorescence. Using CRhOMe, changes in cellular membrane potential can be read out using fluorescence intensity or lifetime. In fluorescence intensity mode, CRhOMe tracks fast-spiking neuronal action potentials (APs) with greater signal-to-noise than state-of-the-art BeRST 1 (another voltage-sensitive fluorophore). CRhOMe can also measure values of membrane potential. The fluorescence lifetime of CRhOMe follows a single exponential decay, substantially improving the quantification of membrane potential values using fluorescence lifetime imaging microscopy (FLIM). The combination of red-shifted excitation and emission, mono-exponential decay, and high voltage sensitivity enable fast FLIM recording of APs in cardiomyocytes. The ability to both monitor and measure membrane potentials with red light using CRhOMe makes it an important approach for studying biological voltages.