Open Ephys Research Articles

An Integrated Platform for In Vivo Electrophysiology in Spatial Cognition Experiments.

Spatial cognition research requires behavioral paradigms that can distinguish between different navigational elements, such as allocentric (map-like) navigation and egocentric (e.g., body centered) navigation. To fill this need, we developed a flexible experimental platform that can be quickly modified without the need for significant changes to software and hardware. In this paper, we present this inexpensive and flexible behavioral platform paired with software which we are making freely available. Our behavioral platform serves as the foundation for a range of experiments, and although developed for assessing spatial cognition, it also has applications in the nonspatial domain of behavioral testing. There are two components of the software platform, "Maze" and "Stim Trigger." While intended as a general platform, presently both programs can work in conjunction with Neuralynx and Open Ephys electrophysiology acquisition systems, allowing for precise time stamping of neural events. The Maze program includes functionality for automatic reward delivery based on user defined zones. "Stim Trigger" permits control of brain stimulation via any equipment that can be paired with an Arduino board. We seek to share our software and leverage the potential by expanding functionality in the future to meet the needs of a larger community of researchers.

Open-Source Real-Time Closed-Loop Electrical Threshold Tracking for Translational Pain Research.

Nociceptors are a class of primary afferent neurons that signal potentially harmful noxious stimuli. An increase in nociceptor excitability occurs in acute and chronic pain conditions. This produces abnormal ongoing activity or reduced activation thresholds to noxious stimuli. Identifying the cause of this increased excitability is required for the development and validation of mechanism-based treatments. Single-neuron electrical threshold tracking can quantify nociceptor excitability. Therefore, we have developed an application to allow such measurements and demonstrate its use in humans and rodents. APTrack provides real-time data visualization and action potential identification using a temporal raster plot. Algorithms detect action potentials by threshold crossing and monitor their latency after electrical stimulation. The plugin then modulates the electrical stimulation amplitude using an up-down method to estimate the electrical threshold of the nociceptors. The software was built upon the Open Ephys system (V0.54) and coded in C++ using the JUCE framework. It runs on Windows, Linux, and Mac operating systems. The open-source code is available (https://github.com/Microneurography/APTrack). The electrophysiological recordings were taken from nociceptors in both a mouse skin-nerve preparation using the teased fiber method in the saphenous nerve and in healthy human volunteers using microneurography in the superficial peroneal nerve. Nociceptors were classified by their response to thermal and mechanical stimuli, as well as by monitoring the activity-dependent slowing of the conduction velocity. The software facilitated the experiment by simplifying the action potential identification through the temporal raster plot. We demonstrate real-time closed-loop electrical threshold tracking of single-neuron action potentials duringin vivohuman microneurography, for the first time, and duringex vivomouse electrophysiological recordings of C-fibers and Aδ-fibers. We establish proof of principle by showing that the electrical threshold of a human heat-sensitive C-fiber nociceptor is reduced by heating the receptive field. This plugin enables the electrical threshold tracking of single-neuron action potentials and allows the quantification of changes in nociceptor excitability.

FreiBox: A Versatile Open-Source Behavioral Setup for Investigating the Neuronal Correlates of Behavioral Flexibility via 1-Photon Imaging in Freely Moving Mice.

To survive in a complex and changing environment, animals must adapt their behavior. This ability is called behavioral flexibility and is classically evaluated by a reversal learning paradigm. During such a paradigm, the animals adapt their behavior according to a change of the reward contingencies. To study these complex cognitive functions (from outcome evaluation to motor adaptation), we developed a versatile, low-cost, open-source platform, allowing us to investigate the neuronal correlates of behavioral flexibility with 1-photon calcium imaging. This platform consists of FreiBox, a novel low-cost Arduino behavioral setup, as well as further open-source tools, which we developed and integrated into our framework. FreiBox is controlled by a custom Python interface and integrates a new licking sensor (strain gauge lickometer) for controlling spatial licking behavioral tasks. In addition to allowing both discriminative and serial reversal learning, the Arduino can track mouse licking behavior in real time to control task events in a submillisecond timescale. To complete our setup, we also developed and validated an affordable commutator, which is crucial for recording calcium imaging with the Miniscope V4 in freely moving mice. Further, we demonstrated that FreiBox can be associated with 1-photon imaging and other open-source initiatives (e.g., Open Ephys) to form a versatile platform for exploring the neuronal substrates of licking-based behavioral flexibility in mice. The combination of the FreiBox behavioral setup and our low-cost commutator represents a highly competitive and complementary addition to the recently emerging battery of open-source initiatives.

Low-Cost Platform for Multianimal Chronic Local Field Potential Video Monitoring with Graphical User Interface (GUI) for Seizure Detection and Behavioral Scoring.

Experiments employing chronic monitoring of neurophysiological signals and video are commonly used in studies of epilepsy to characterize behavioral correlates of seizures. Our objective was to design a low-cost platform that enables chronic monitoring of several animals simultaneously, synchronizes bilateral local field potential (LFP) and video streams in real time, and parses recorded data into manageable file sizes. We present a hardware solution leveraging Intan and Open Ephys acquisition systems and a software solution implemented in Bonsai. The platform was tested in 48-h continuous recordings simultaneously from multiple mice (male and female) with chronic epilepsy. To enable seizure detection and scoring, we developed a graphical user interface (GUI) that reads the data produced by our workflow and allows a user with no coding expertise to analyze events. Our Bonsai workflow was designed to maximize flexibility for a wide variety of experimental applications, and our use of the Open Ephys acquisition board would allow for scaling recordings up to 128 channels per animal.

An open-source, ready-to-use and validated ripple detector plugin for the Open Ephys GUI

Objective. Sharp wave-ripples (SWRs, 100–250 Hz) are oscillatory events extracellularly recorded in the CA1 subfield of the hippocampus during sleep and quiet wakefulness. Many studies employed closed-loop strategies to either detect and abolish SWRs within the hippocampus or manipulate other relevant areas upon ripple detection. However, the code and schematics necessary to replicate the detection system are not always available, which hinders the reproducibility of experiments among different research groups. Furthermore, information about performance is not usually reported. Here, we sought to provide an open-source, validated ripple detector for the scientific community. Approach. We developed and validated a ripple detection plugin integrated into the Open Ephys graphical user’s interface. It contains a built-in movement detector based on accelerometer or electromyogram data that prevents false ripple events (due to chewing, grooming, or moving, for instance) from triggering the stimulation/manipulation device. Main results. To determine the accuracy of the detection algorithm, we first carried out simulations in MATLAB with real ripple recordings. Using a specific combination of detection parameters (amplitude threshold of 5 standard deviations above the mean, time threshold of 10 ms, and root mean square block size of 7 samples), we obtained a 97% true positive rate and 2.48 false positives per minute. Next, an Open Ephys plugin based on the same detection algorithm was developed, and a closed-loop system was set up to evaluate the round trip (ripple onset-to-stimulation) latency over synthetic data. The lowest latency obtained was 34.5 ± 0.5 ms. The embedded movement monitoring was effective in reducing false positives and the plugin’s flexibility to detect pathological events was also verified. Significance. Besides contributing to increased reproducibility, we anticipate that the developed ripple detector plugin will be helpful for many closed-loop applications in the field of systems neuroscience.

Toolkit for Oscillatory Real-time Tracking and Estimation (TORTE)

BackgroundClosing the loop between brain activity and behavior is one of the most active areas of development in neuroscience. There is particular interest in developing closed-loop control of neural oscillations. Many studies report correlations between oscillations and functional processes. Oscillation-informed closed-loop experiments might determine whether these relationships are causal and would provide important mechanistic insights which may lead to new therapeutic tools. These closed-loop perturbations require accurate estimates of oscillatory phase and amplitude, which are challenging to compute in real time. New methodWe developed an easy to implement, fast and accurate Toolkit for Oscillatory Real-time Tracking and Estimation (TORTE). TORTE operates with the open-source Open Ephys GUI (OEGUI) system, making it immediately compatible with a wide range of acquisition systems and experimental preparations. ResultsTORTE efficiently extracts oscillatory phase and amplitude from a target signal and includes a variety of options to trigger closed-loop perturbations. Implementing these tools into existing experiments is easy and adds minimal latency to existing protocols. Comparison with existing methodsMost labs use in-house lab-specific approaches, limiting replication and extension of their experiments by other groups. Accuracy of the extracted analytic signal and accuracy of oscillation-informed perturbations with TORTE match presented results by these groups. However, TORTE provides access to these tools in a flexible, easy to use toolkit without requiring proprietary software. ConclusionWe hope that the availability of a high-quality, open-source, and broadly applicable toolkit will increase the number of labs able to perform oscillatory closed-loop experiments, and will improve the replicability of protocols and data across labs.

A state space modeling approach to real-time phase estimation.

Brain rhythms have been proposed to facilitate brain function, with an especially important role attributed to the phase of low-frequency rhythms. Understanding the role of phase in neural function requires interventions that perturb neural activity at a target phase, necessitating estimation of phase in real-time. Current methods for real-time phase estimation rely on bandpass filtering, which assumes narrowband signals and couples the signal and noise in the phase estimate, adding noise to the phase and impairing detections of relationships between phase and behavior. To address this, we propose a state space phase estimator for real-time tracking of phase. By tracking the analytic signal as a latent state, this framework avoids the requirement of bandpass filtering, separately models the signal and the noise, accounts for rhythmic confounds, and provides credible intervals for the phase estimate. We demonstrate in simulations that the state space phase estimator outperforms current state-of-the-art real-time methods in the contexts of common confounds such as broadband rhythms, phase resets, and co-occurring rhythms. Finally, we show applications of this approach to in vivo data. The method is available as a ready-to-use plug-in for the Open Ephys acquisition system, making it widely available for use in experiments.

OPETH: Open Source Solution for Real-Time Peri-Event Time Histogram Based on Open Ephys.

Single cell electrophysiology remains one of the most widely used approaches of systems neuroscience. Decisions made by the experimenter during electrophysiology recording largely determine recording quality, duration of the project and value of the collected data. Therefore, online feedback aiding these decisions can lower monetary and time investment, and substantially speed up projects as well as allow novel studies otherwise not possible due to prohibitively low throughput. Real-time feedback is especially important in studies that involve optogenetic cell type identification by enabling a systematic search for neurons of interest. However, such tools are scarce and limited to costly commercial systems with high degree of specialization, which hitherto prevented wide-ranging benefits for the community. To address this, we present an open-source tool that enables online feedback during electrophysiology experiments and provides a Python interface for the widely used Open Ephys open source data acquisition system. Specifically, our software allows flexible online visualization of spike alignment to external events, called the online peri-event time histogram (OPETH). These external events, conveyed by digital logic signals, may indicate photostimulation time stamps for in vivo optogenetic cell type identification or the times of behaviorally relevant events during in vivo behavioral neurophysiology experiments. Therefore, OPETH allows real-time identification of genetically defined neuron types or behaviorally responsive populations. By allowing “hunting” for neurons of interest, OPETH significantly reduces experiment time and thus increases the efficiency of experiments that combine in vivo electrophysiology with behavior or optogenetic tagging of neurons.

Ultrasound-guided, open-source microneurography: Approaches to improve recordings from peripheral nerves in man

ObjectiveMicroneurography is the only method for recording from single neurons in intact human nerves. It is challenging - requiring technical expertise, investment in specialised equipment and has sparse data yields. MethodsWe assessed whether ultrasound guidance in combination with an ‘open access’ amplifier and data capture system (Open-Ephys) would simplify and expand the scope of microneurographic recordings in humans. ResultsIn 32 healthy consenting volunteers, ultrasound-guidance improved success rates for obtaining cutaneous C-fibres and reduced “Skin to Nerve” times from 28.5 min to 4.5 min for recordings of the peroneal nerve (P < 0.0001).We illustrate the potential utility of ultrasound-guided microneurography for difficult to access nerves with phrenic nerve recording during a Valsalva manoeuvre.We show that Open Ephys is a viable alternative to commercially available recording systems and offers advantages in terms of cost and software customisability. ConclusionsUltrasound guidance for microneurography with Open Ephys facilitates cutaneous C nociceptor recordings and allows recordings to be made from nerves previously considered inaccessible. SignificanceWe anticipate that the adoption of these techniques will improve microneurography experimental efficiency, adds an important visual learning aid and increases the generalisability of the approach.

Open source modules for tracking animal behavior and closed-loop stimulation based on Open Ephys and Bonsai

Objective. A major goal in systems neuroscience is to determine the causal relationship between neural activity and behavior. To this end, methods that combine monitoring neural activity, behavioral tracking, and targeted manipulation of neurons in closed-loop are powerful tools. However, commercial systems that allow these types of experiments are usually expensive and rely on non-standardized data formats and proprietary software which may hinder user-modifications for specific needs. In order to promote reproducibility and data-sharing in science, transparent software and standardized data formats are an advantage. Here, we present an open source, low-cost, adaptable, and easy to set-up system for combined behavioral tracking, electrophysiology, and closed-loop stimulation. Approach. Based on the Open Ephys system (www.open-ephys.org) we developed multiple modules to include real-time tracking and behavior-based closed-loop stimulation. We describe the equipment and provide a step-by-step guide to set up the system. Combining the open source software Bonsai (bonsai-rx.org) for analyzing camera images in real time with the newly developed modules in Open Ephys, we acquire position information, visualize tracking, and perform tracking-based closed-loop stimulation experiments. To analyze the acquired data we provide an open source file reading package in Python. Main results. The system robustly visualizes real-time tracking and reliably recovers tracking information recorded from a range of sampling frequencies (30–1000 Hz). We combined electrophysiology with the newly-developed tracking modules in Open Ephys to record place cell and grid cell activity in the hippocampus and in the medial entorhinal cortex, respectively. Moreover, we present a case in which we used the system for closed-loop optogenetic stimulation of entorhinal grid cells. Significance. Expanding the Open Ephys system to include animal tracking and behavior-based closed-loop stimulation extends the availability of high-quality, low-cost experimental setup within standardized data formats serving the neuroscience community.

Microelectrode array and multichannel system for recording the electrical activity of neurons in vitro

Microelectrode array and multichannel system for recording the electrical activity of neurons in vitro

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.

Open Ephys: an open-source, plugin-based platform for multichannel electrophysiology

Objective. Closed-loop experiments, in which causal interventions are conditioned on the state of the system under investigation, have become increasingly common in neuroscience. Such experiments can have a high degree of explanatory power, but they require a precise implementation that can be difficult to replicate across laboratories. We sought to overcome this limitation by building open-source software that makes it easier to develop and share algorithms for closed-loop control. Approach. We created the Open Ephys GUI, an open-source platform for multichannel electrophysiology experiments. In addition to the standard ‘open-loop’ visualization and recording functionality, the GUI also includes modules for delivering feedback in response to events detected in the incoming data stream. Importantly, these modules can be built and shared as plugins, which makes it possible for users to extend the functionality of the GUI through a simple API, without having to understand the inner workings of the entire application. Main results. In combination with low-cost, open-source hardware for amplifying and digitizing neural signals, the GUI has been used for closed-loop experiments that perturb the hippocampal theta rhythm in a phase-specific manner. Significance. The Open Ephys GUI is the first widely used application for multichannel electrophysiology that leverages a plugin-based workflow. We hope that it will lower the barrier to entry for electrophysiologists who wish to incorporate real-time feedback into their research.

Open Ephys electroencephalography (Open Ephys + EEG): a modular, low-cost, open-source solution to human neural recording

Objective. Electroencephalography (EEG) offers a unique opportunity to study human neural activity non-invasively with millisecond resolution using minimal equipment in or outside of a lab setting. EEG can be combined with a number of techniques for closed-loop experiments, where external devices are driven by specific neural signals. However, reliable, commercially available EEG systems are expensive, often making them impractical for individual use and research development. Moreover, by design, a majority of these systems cannot be easily altered to the specification needed by the end user. We focused on mitigating these issues by implementing open-source tools to develop a new EEG platform to drive down research costs and promote collaboration and innovation. Approach. Here, we present methods to expand the open-source electrophysiology system, Open Ephys (www.openephys.org), to include human EEG recordings. We describe the equipment and protocol necessary to interface various EEG caps with the Open Ephys acquisition board, and detail methods for processing data. We present applications of Open Ephys + EEG as a research tool and discuss how this innovative EEG technology lays a framework for improved closed-loop paradigms and novel brain-computer interface experiments. Main results. The Open Ephys + EEG system can record reliable human EEG data, as well as human EMG data. A side-by-side comparison of eyes closed 8–14 Hz activity between the Open Ephys + EEG system and the Brainvision ActiCHamp EEG system showed similar average power and signal to noise. Significance. Open Ephys + EEG enables users to acquire high-quality human EEG data comparable to that of commercially available systems, while maintaining the price point and extensibility inherent to open-source systems.

Open Ephys Electroencephalography: A Novel Method for Real-Time Recording during Transcranial Alternating Current Stimulation

Open Ephys Electroencephalography: A Novel Method for Real-Time Recording during Transcranial Alternating Current Stimulation

A clinic compatible, open source electrophysiology system.

Open source electrophysiology (ephys) recording systems have several advantages over commercial systems such as customization and affordability enabling more researchers to conduct ephys experiments. Notable open source ephys systems include Open-Ephys, NeuroRighter and more recently Willow, all of which have high channel count (64+), scalability, and advanced software to develop on top of. However, little work has been done to build an open source ephys system that is clinic compatible, particularly in the operating room where acute human electrocorticography (ECoG) research is performed. We developed an affordable (<; $10,000) and open system for research purposes that features power isolation for patient safety, compact and water resistant enclosures and 256 recording channels sampled up to 20ksam/sec, 16-bit. The system was validated by recording ECoG with a high density, thin film device for an acute, awake craniotomy study at UC San Diego, Thornton Hospital Operating Room.