Dynamic clamp in cardiac and neuronal systems using RTXI

Computational cardiac physiology for new modelers: Origins, foundations, and future

Mathematical models of the cardiovascular system have come a long way since they were first introduced in the early 19th century. Driven by a rapid development of experimental techniques, numerical methods, and computer hardware, detailed models that describe physical scales from the molecular level up to organs and organ systems have been derived and used for physiological research. Mathematical and computational models can be seen as condensed and quantitative formulations of extensive physiological knowledge and are used for formulating and testing hypotheses, interpreting and directing experimental research, and have contributed substantially to our understanding of cardiovascular physiology. However, in spite of the strengths of mathematics to precisely describe complex relationships and the obvious need for the mathematical and computational models to be informed by experimental data, there still exist considerable barriers between experimental and computational physiological research. In this review, we present a historical overview of the development of mathematical and computational models in cardiovascular physiology, including the current state of the art. We further argue why a tighter integration is needed between experimental and computational scientists in physiology, and point out important obstacles and challenges that must be overcome in order to fully realize the synergy of experimental and computational physiological research.

A dual SHOX2:GFP; MYH6:mCherry knockin hESC reporter line for derivation of human SAN-like cells

The sinoatrial node (SAN) is the primary pacemaker of the heart. The human SAN is poorly understood due to limited primary tissue access and limitations in robust in vitro derivation methods. We developed a dual SHOX2:GFP; MYH6:mCherry knockin human embryonic stem cell (hESC) reporter line, which allows the identification and purification of SAN-like cells. Using this line, we performed several rounds of chemical screens and developed an efficient strategy to generate and purify hESC-derived SAN-like cells (hESC-SAN). The derived hESC-SAN cells display molecular and electrophysiological characteristics of bona fide nodal cells, which allowed exploration of their transcriptional profile at single-cell level. In sum, our dual reporter system facilitated an effective strategy for deriving human SAN-like cells, which can potentially be used for future disease modeling and drug discovery.

Dynamic Clamp in Electrophysiological Studies on Stem Cell-Derived Cardiomyocytes-Why and How?

ABSTRACT

Human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) are supposed to be a good human-based model, with virtually unlimited cell source, for studies on mechanisms underlying cardiac development and cardiac diseases, and for identification of drug targets. However, a major drawback of hPSC-CMs as a model system, especially for electrophysiological studies, is their depolarized state and associated spontaneous electrical activity. Various approaches are used to overcome this drawback, including the injection of "synthetic" inward rectifier potassium current (IK1), which is computed in real time, based on the recorded membrane potential ("dynamic clamp"). Such injection of an IK1-like current results in quiescent hPSC-CMs with a nondepolarized resting potential that show "adult-like" action potentials on stimulation, with functional availability of the most important ion channels involved in cardiac electrophysiology. These days, dynamic clamp has become a widely appreciated electrophysiological tool. However, setting up a dynamic clamp system can still be laborious and difficult, both because of the required hardware and the implementation of the dedicated software. In the present review, we first summarize the potential mechanisms underlying the depolarized state of hPSC-CMs and the functional consequences of this depolarized state. Next, we explain how an existing manual patch clamp setup can be extended with dynamic clamp. Finally, we shortly validate the extended setup with atrial-like and ventricular-like hPSC-CMs. We feel that dynamic clamp is a highly valuable tool in the field of cellular electrophysiological studies on hPSC-CMs and hope that our directions for setting up such dynamic clamp system may prove helpful.

A Systematic Review of Closed-Loop Feedback Techniques in Sleep Studies-Related Issues and Future Directions

Advances in computer processing technology have enabled researchers to analyze real-time brain activity and build real-time closed-loop paradigms. In many fields, the effectiveness of these closed-loop protocols has proven to be better than that of the simple open-loop paradigms. Recently, sleep studies have attracted much attention as one possible application of closed-loop paradigms. To date, several studies that used closed-loop paradigms have been reported in the sleep-related literature and recommend a closed-loop feedback system to enhance specific brain activity during sleep, which leads to improvements in sleep's effects, such as memory consolidation. However, to the best of our knowledge, no report has reviewed and discussed the detailed technical issues that arise in designing sleep closed-loop paradigms. In this paper, we reviewed the most recent reports on sleep closed-loop paradigms and offered an in-depth discussion of some of their technical issues. We found 148 journal articles strongly related with 'sleep and stimulation' and reviewed 20 articles on closed-loop feedback sleep studies. We focused on human sleep studies conducting any modality of feedback stimulation. Then we introduced the main component of the closed-loop system and summarized several open-source libraries, which are widely used in closed-loop systems, with step-by-step guidelines for closed-loop system implementation for sleep. Further, we proposed future directions for sleep research with closed-loop feedback systems, which provide some insight into closed-loop feedback systems.

A human embryonic stem cell reporter line for monitoring chemical-induced cardiotoxicity

AIMS

Human embryonic stem cells (hESCs) can be used to generate scalable numbers of cardiomyocytes (CMs) for studying cardiac biology, disease modelling, drug screens, and potentially for regenerative therapies. A fluorescence-based reporter line will significantly enhance our capacities to visualize the derivation, survival, and function of hESC-derived CMs. Our goal was to develop a reporter cell line for real-time monitoring of live hESC-derived CMs.

METHODS AND RESULTS

We used CRISPR/Cas9 to knock a mCherry reporter gene into the MYH6 locus of hESC lines, H1 and H9, enabling real-time monitoring of the generation of CMs. MYH6:mCherry+ cells express atrial or ventricular markers and display a range of cardiomyocyte action potential morphologies. At 20 days of differentiation, MYH6:mCherry+ cells show features characteristic of human CMs and can be used successfully to monitor drug-induced cardiotoxicity and oleic acid-induced cardiac arrhythmia.

CONCLUSION

We created two MYH6:mCherry hESC reporter lines and documented the application of these lines for disease modelling relevant to cardiomyocyte biology.

Light-Activated Dynamic Clamp Using iPSC-Derived Cardiomyocytes

iPSC-derived cardiomyocytes (iPSC-CMs) are a potentially advantageous platform for drug screening because they provide a renewable source of human cardiomyocytes. One obstacle to their implementation is their immature electrophysiology, which reduces relevance to adult arrhythmogenesis. To address this, dynamic clamp is used to inject current representing the insufficient potassium current, IK1, thereby producing more adult-like electrophysiology. However, dynamic clamp requires patch clamp and is therefore low throughput and ill-suited for large-scale drug screening. Here, we use optogenetics to generate such a dynamic-clamp current. The optical dynamic clamp (ODC) uses outward-current-generating opsin, ArchT, to mimic IK1, resulting in more adult-like action potential morphology, similar to IK1 injection via classic dynamic clamp. Furthermore, in the presence of an IKr blocker, ODC revealed expected action potential prolongation and reduced spontaneous excitation. The ODC presented here still requires an electrode to measure Vm but provides a first step toward contactless dynamic clamp, which will not only enable high-throughput screening but may also allow control within multicellular iPSC-CM formats to better recapitulate adult in vivo physiology.

Falcon: a highly flexible open-source software for closed-loop neuroscience

OBJECTIVE

Closed-loop experiments provide unique insights into brain dynamics and function. To facilitate a wide range of closed-loop experiments, we created an open-source software platform that enables high-performance real-time processing of streaming experimental data.

APPROACH

We wrote Falcon, a C++ multi-threaded software in which the user can load and execute an arbitrary processing graph. Each node of a Falcon graph is mapped to a single thread and nodes communicate with each other through thread-safe buffers. The framework allows for easy implementation of new processing nodes and data types. Falcon was tested both on a 32-core and a 4-core workstation. Streaming data was read from either a commercial acquisition system (Neuralynx) or the open-source Open Ephys hardware, while closed-loop TTL pulses were generated with a USB module for digital output. We characterized the round-trip latency of our Falcon-based closed-loop system, as well as the specific latency contribution of the software architecture, by testing processing graphs with up to 32 parallel pipelines and eight serial stages. We finally deployed Falcon in a task of real-time detection of population bursts recorded live from the hippocampus of a freely moving rat.

MAIN RESULTS

On Neuralynx hardware, round-trip latency was well below 1 ms and stable for at least 1 h, while on Open Ephys hardware latencies were below 15 ms. The latency contribution of the software was below 0.5 ms. Round-trip and software latencies were similar on both 32- and 4-core workstations. Falcon was used successfully to detect population bursts online with ~40 ms average latency.

SIGNIFICANCE

Falcon is a novel open-source software for closed-loop neuroscience. It has sub-millisecond intrinsic latency and gives the experimenter direct control of CPU resources. We envisage Falcon to be a useful tool to the neuroscientific community for implementing a wide variety of closed-loop experiments, including those requiring use of complex data structures and real-time execution of computationally intensive algorithms, such as population neural decoding/encoding from large cell assemblies.

A Hybrid Model for Safety Pharmacology on an Automated Patch Clamp Platform: Using Dynamic Clamp to Join iPSC-Derived Cardiomyocytes and Simulations of Ik1 Ion Channels in Real-Time

An important aspect of the Comprehensive In Vitro Proarrhythmia Assay (CiPA) proposal is the use of human stem cell-derived cardiomyocytes and the confirmation of their predictive power in drug safety assays. The benefits of this cell source are clear; drugs can be tested in vitro on human cardiomyocytes, with patient-specific genotypes if needed, and differentiation efficiencies are generally excellent, resulting in a virtually limitless supply of cardiomyocytes. There are, however, several challenges that will have to be surmounted before successful establishment of hSC-CMs as an all-round predictive model for drug safety assays. An important factor is the relative electrophysiological immaturity of hSC-CMs, which limits arrhythmic responses to unsafe drugs that are pro-arrhythmic in humans. Potentially, immaturity may be improved functionally by creation of hybrid models, in which the dynamic clamp technique joins simulations of lacking cardiac ion channels (e.g., I_K1) with hSC-CMs in real-time during patch clamp experiments. This approach has been used successfully in manual patch clamp experiments, but throughput is low. In this study, we combined dynamic clamp with automated patch clamp of iPSC-CMs in current clamp mode, and demonstrate that I_K1 conductance can be added to iPSC-CMs on an automated patch clamp platform, resulting in an improved electrophysiological maturity.

Applications of Dynamic Clamp to Cardiac Arrhythmia Research: Role in Drug Target Discovery and Safety Pharmacology Testing

Dynamic clamp, a hybrid-computational-experimental technique that has been used to elucidate ionic mechanisms underlying cardiac electrophysiology, is emerging as a promising tool in the discovery of potential anti-arrhythmic targets and in pharmacological safety testing. Through the injection of computationally simulated conductances into isolated cardiomyocytes in a real-time continuous loop, dynamic clamp has greatly expanded the capabilities of patch clamp outside traditional static voltage and current protocols. Recent applications include fine manipulation of injected artificial conductances to identify promising drug targets in the prevention of arrhythmia and the direct testing of model-based hypotheses. Furthermore, dynamic clamp has been used to enhance existing experimental models by addressing their intrinsic limitations, which increased predictive power in identifying pro-arrhythmic pharmacological compounds. Here, we review the recent advances of the dynamic clamp technique in cardiac electrophysiology with a focus on its future role in the development of safety testing and discovery of anti-arrhythmic drugs.

A Dynamic Clamp on Every Rig

The dynamic clamp should be a standard part of every cellular electrophysiologist’s toolbox. That it is not, even 25 years after its introduction, comes down to three issues: money, the disruption that adding dynamic clamp to an existing electrophysiology rig entails, and the technical prowess required of experimenters. These have been valid and limiting issues in the past, but no longer. Technological advances associated with the so-called maker movement render them moot. We demonstrate this by implementing a fast (∼100 kHz) dynamic clamp system using an inexpensive microcontroller (Teensy 3.6). The overall cost of the system is less than USD$100, and assembling it requires no prior electronics experience. Modifying it—for example, to add Hodgkin–Huxley-style conductances—requires no prior programming experience. The system works together with existing electrophysiology data acquisition systems (for Macintosh, Windows, and Linux); it does not attempt to supplant them. Moreover, the process of assembling, modifying, and using the system constitutes a useful pedagogical exercise for students and researchers with no background but an interest in electronics and programming. We demonstrate the system’s utility by implementing conductances as fast as a transient sodium conductance and as complex as the Ornstein–Uhlenbeck conductances of the “point conductance” model of synaptic background activity.

Closed Loop Experiment Manager (CLEM)-An Open and Inexpensive Solution for Multichannel Electrophysiological Recordings and Closed Loop Experiments

There is growing need for multichannel electrophysiological systems that record from and interact with neuronal systems in near real-time. Such systems are needed, for example, for closed loop, multichannel electrophysiological/optogenetic experimentation in vivo and in a variety of other neuronal preparations, or for developing and testing neuro-prosthetic devices, to name a few. Furthermore, there is a need for such systems to be inexpensive, reliable, user friendly, easy to set-up, open and expandable, and possess long life cycles in face of rapidly changing computing environments. Finally, they should provide powerful, yet reasonably easy to implement facilities for developing closed-loop protocols for interacting with neuronal systems. Here, we survey commercial and open source systems that address these needs to varying degrees. We then present our own solution, which we refer to as Closed Loop Experiments Manager (CLEM). CLEM is an open source, soft real-time, Microsoft Windows desktop application that is based on a single generic personal computer (PC) and an inexpensive, general-purpose data acquisition board. CLEM provides a fully functional, user-friendly graphical interface, possesses facilities for recording, presenting and logging electrophysiological data from up to 64 analog channels, and facilities for controlling external devices, such as stimulators, through digital and analog interfaces. Importantly, it includes facilities for running closed-loop protocols written in any programming language that can generate dynamic link libraries (DLLs). We describe the application, its architecture and facilities. We then demonstrate, using networks of cortical neurons growing on multielectrode arrays (MEA) that despite its reliance on generic hardware, its performance is appropriate for flexible, closed-loop experimentation at the neuronal network level.

Differential roles of two delayed rectifier potassium currents in regulation of ventricular action potential duration and arrhythmia susceptibility

KEY POINTS

Arrhythmias result from disruptions to cardiac electrical activity, although the factors that control cellular action potentials are incompletely understood. We combined mathematical modelling with experiments in heart cells from guinea pigs to determine how cellular electrical activity is regulated. A mismatch between modelling predictions and the experimental results allowed us to construct an improved, more predictive mathematical model. The balance between two particular potassium currents dictates how heart cells respond to perturbations and their susceptibility to arrhythmias.

ABSTRACT

Imbalances of ionic currents can destabilize the cardiac action potential and potentially trigger lethal cardiac arrhythmias. In the present study, we combined mathematical modelling with information-rich dynamic clamp experiments to determine the regulation of action potential morphology in guinea pig ventricular myocytes. Parameter sensitivity analysis was used to predict how changes in ionic currents alter action potential duration, and these were tested experimentally using dynamic clamp, a technique that allows for multiple perturbations to be tested in each cell. Surprisingly, we found that a leading mathematical model, developed with traditional approaches, systematically underestimated experimental responses to dynamic clamp perturbations. We then re-parameterized the model using a genetic algorithm, which allowed us to estimate ionic current levels in each of the cells studied. This unbiased model adjustment consistently predicted an increase in the rapid delayed rectifier K⁺ current and a drastic decrease in the slow delayed rectifier K⁺ current, and this prediction was validated experimentally. Subsequent simulations with the adjusted model generated the clinically relevant prediction that the slow delayed rectifier is better able to stabilize the action potential and suppress pro-arrhythmic events than the rapid delayed rectifier. In summary, iterative coupling of simulations and experiments enabled novel insight into how the balance between cardiac K⁺ currents influences ventricular arrhythmia susceptibility.

Stochastic slowly adapting ionic currents may provide a decorrelation mechanism for neural oscillators by causing wander in the intrinsic period

Oscillatory neurons integrate their synaptic inputs in fundamentally different ways than normally quiescent neurons. We show that the oscillation period of invertebrate endogenous pacemaker neurons wanders, producing random fluctuations in the interspike intervals (ISI) on a time scale of seconds to minutes, which decorrelates pairs of neurons in hybrid circuits constructed using the dynamic clamp. The autocorrelation of the ISI sequence remained high for many ISIs, but the autocorrelation of the ΔISI series had on average a single nonzero value, which was negative at a lag of one interval. We reproduced these results using a simple integrate and fire (IF) model with a stochastic population of channels carrying an adaptation current with a stochastic component that was integrated with a slow time scale, suggesting that a similar population of channels underlies the observed wander in the period. Using autoregressive integrated moving average (ARIMA) models, we found that a single integrator and a single moving average with a negative coefficient could simulate both the experimental data and the IF model. Feeding white noise into an integrator with a slow time constant is sufficient to produce the autocorrelation structure of the ISI series. Moreover, the moving average clearly accounted for the autocorrelation structure of the ΔISI series and is biophysically implemented in the IF model using slow stochastic adaptation. The observed autocorrelation structure may be a neural signature of slow stochastic adaptation, and wander generated in this manner may be a general mechanism for limiting episodes of synchronized activity in the nervous system.

Cell-specific Dynamic Clamp analysis of the role of funny If current in cardiac pacemaking

We used the Dynamic Clamp technique for i) comparative validation of conflicting computational models of the hyperpolarization-activated funny current, If, and ii) quantification of the role of If in mediating autonomic modulation of heart rate. Experimental protocols based on the injection of a real-time recalculated synthetic If current in sinoatrial rabbit cells were developed. Preliminary results of experiments mimicking the autonomic modulation of If demonstrated the need for a customization procedure to compensate for cellular heterogeneity. For this reason, we used a cell-specific approach, scaling the maximal conductance of the injected current based on the cell's spontaneous firing rate. The pacemaking rate, which was significantly reduced after application of Ivabradine, was restored by the injection of synthetic current based on the Severi-DiFrancesco formulation, while the injection of synthetic current based on the Maltsev-Lakatta formulation did not produce any significant variation. A positive virtual shift of the If activation curve, mimicking the Isoprenaline effects, led to a significant increase in pacemaking rate (+17.3 ± 6.7%, p < 0.01), although of lower magnitude than that induced by real Isoprenaline (+45.0 ± 26.1%). Similarly, a negative virtual shift of the activation curve significantly lowered the pacemaking rate (-11.8 ± 1.9%, p < 0.001), as did the application of real Acetylcholine (-20.5 ± 5.1%). The Dynamic Clamp approach, applied to the If study in cardiomyocytes for the first time and rate-adapted to manage intercellular variability, indicated that: i) the quantitative description of the If current in the Severi-DiFrancesco model accurately reproduces the effects of the real current on rabbit sinoatrial cell pacemaking rate and ii) a significant portion (50-60%) of the physiological autonomic rate modulation is due to the shift of the If activation curve.

I Kr Impact on Repolarization and Its Variability Assessed by Dynamic Clamp

Background—

Repolarization and its stability are exquisitely sensitive to I Kr features. Information on the relative importance of specific I Kr abnormalities is missing and would assist in the evaluation of arrhythmogenic risk.

Methods and Results—

In single guinea-pig myocytes, endogenous I Kr was replaced by modeled I Kr (m I Kr ) by dynamic clamp (DC) at a cycle length of 1 s. m I Kr parameters were systematically modified, and the resulting changes in action potential duration (APD) and its short term variability (SD1) were measured. We observed that (1) I Kr blockade increased SD1 more than expected by its dependency on APD; (2) m I Kr completely reversed APD and SD1 changes caused by I Kr blockade; (3) repolarization was most sensitive to inactivation shifts, which affected APD and SD1 concordantly; (4) activation shifts of the same magnitude had marginal impact on APD, but only when reducing m I Kr , they significantly increased SD1; (5) changes in maximal conductance resulted in a pattern similar to that of activation shifts.

Conclusions—

The largest effect on repolarization and its stability are expected from changes in I Kr inactivation. APD is less sensitive to changes in other I Kr gating parameters, which are better revealed by SD1 changes. SD1 may be more sensitive than APD in detecting I Kr -dependent repolarization abnormalities.

Cell-specific cardiac electrophysiology models

The traditional cardiac model-building paradigm involves constructing a composite model using data collected from many cells. Equations are derived for each relevant cellular component (e.g., ion channel, exchanger) independently. After the equations for all components are combined to form the composite model, a subset of parameters is tuned, often arbitrarily and by hand, until the model output matches a target objective, such as an action potential. Unfortunately, such models often fail to accurately simulate behavior that is dynamically dissimilar (e.g., arrhythmia) to the simple target objective to which the model was fit. In this study, we develop a new approach in which data are collected via a series of complex electrophysiology protocols from single cardiac myocytes and then used to tune model parameters via a parallel fitting method known as a genetic algorithm (GA). The dynamical complexity of the electrophysiological data, which can only be fit by an automated method such as a GA, leads to more accurately parameterized models that can simulate rich cardiac dynamics. The feasibility of the method is first validated computationally, after which it is used to develop models of isolated guinea pig ventricular myocytes that simulate the electrophysiological dynamics significantly better than does a standard guinea pig model. In addition to improving model fidelity generally, this approach can be used to generate a cell-specific model. By so doing, the approach may be useful in applications ranging from studying the implications of cell-to-cell variability to the prediction of intersubject differences in response to pharmacological treatment.

Mathematical models of cardiac cell electrophysiology are widely used as predictive and illuminatory tools, but have been developed for decades using a suboptimal process. The models are typically constructed by manual adjustment of parameters to fit simple data and therefore often underperform when used to predict complex behavior such as arrhythmias. We present a novel method of model parameterization using automated optimization and dynamically rich fitting data and then demonstrate that this approach is better at finding the “real” model of a cell. Application of the method to cardiac myocytes leads to cell-specific models, which may enable well-controlled studies of both cellular- and subject-level population heterogeneity in disease propensity and response to therapies.

High-speed dynamic-clamp interface

The dynamic-clamp technique is highly useful for mimicking synaptic or voltage-gated conductances. However, its use remains rare in part because there are few systems, and they can be expensive and difficult for less-experienced programmers to implement. Furthermore, some conductances (such as sodium channels) can be quite rapid or may have complex voltage sensitivity, so high speeds are necessary. To address these issues, we have developed a new interface that uses a common personal computer platform with National Instruments data acquisition and WaveMetrics IGOR to provide a simple user interface. This dynamic clamp implements leak and linear synaptic conductances as well as a voltage-dependent synaptic conductance and kinetic channel conductances based on Hodgkin-Huxley or Markov models. The speed of the system can be assayed using a testing mode, and currently speeds of >100 kHz (10 μs per cycle) are achievable with short latency and little jitter.