251
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de Haan R, Lim J, van der Burg SA, Pieneman AW, Nigade V, Mansvelder HD, de Kock CPJ. Neural Representation of Motor Output, Context and Behavioral Adaptation in Rat Medial Prefrontal Cortex During Learned Behavior. Front Neural Circuits 2018; 12:75. [PMID: 30327591 PMCID: PMC6174330 DOI: 10.3389/fncir.2018.00075] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Accepted: 09/04/2018] [Indexed: 11/13/2022] Open
Abstract
Selecting behavioral outputs in a dynamic environment is the outcome of integrating multiple information streams and weighing possible action outcomes with their value. Integration depends on the medial prefrontal cortex (mPFC), but how mPFC neurons encode information necessary for appropriate behavioral adaptation is poorly understood. To identify spiking patterns of mPFC during learned behavior, we extracellularly recorded neuronal action potential firing in the mPFC of rats performing a whisker-based "Go"/"No-go" object localization task. First, we identify three functional groups of neurons, which show different degrees of spiking modulation during task performance. One group increased spiking activity during correct "Go" behavior (positively modulated), the second group decreased spiking (negatively modulated) and one group did not change spiking. Second, the relative change in spiking was context-dependent and largest when motor output had contextual value. Third, the negatively modulated population spiked more when rats updated behavior following an error compared to trials without integration of error information. Finally, insufficient spiking in the positively modulated population predicted erroneous behavior under dynamic "No-go" conditions. Thus, mPFC neuronal populations with opposite spike modulation characteristics differentially encode context and behavioral updating and enable flexible integration of error corrections in future actions.
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Affiliation(s)
- Roel de Haan
- Center for Neurogenomics and Cognitive Research, Department of Integrative Neurophysiology, VU Amsterdam, Amsterdam, Netherlands
| | - Judith Lim
- Center for Neurogenomics and Cognitive Research, Department of Integrative Neurophysiology, VU Amsterdam, Amsterdam, Netherlands
| | - Sven A van der Burg
- Center for Neurogenomics and Cognitive Research, Department of Integrative Neurophysiology, VU Amsterdam, Amsterdam, Netherlands
| | - Anton W Pieneman
- Center for Neurogenomics and Cognitive Research, Department of Integrative Neurophysiology, VU Amsterdam, Amsterdam, Netherlands
| | - Vinod Nigade
- Center for Neurogenomics and Cognitive Research, Department of Integrative Neurophysiology, VU Amsterdam, Amsterdam, Netherlands
| | - Huibert D Mansvelder
- Center for Neurogenomics and Cognitive Research, Department of Integrative Neurophysiology, VU Amsterdam, Amsterdam, Netherlands
| | - Christiaan P J de Kock
- Center for Neurogenomics and Cognitive Research, Department of Integrative Neurophysiology, VU Amsterdam, Amsterdam, Netherlands
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252
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Dunham JP, Sales AC, Pickering AE. Ultrasound-guided, open-source microneurography: Approaches to improve recordings from peripheral nerves in man. Clin Neurophysiol 2018; 129:2475-2481. [PMID: 30107982 DOI: 10.1016/j.clinph.2018.07.011] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Revised: 07/03/2018] [Accepted: 07/20/2018] [Indexed: 11/17/2022]
Abstract
OBJECTIVE Microneurography 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. METHODS We 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. RESULTS In 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. CONCLUSIONS Ultrasound guidance for microneurography with Open Ephys facilitates cutaneous C nociceptor recordings and allows recordings to be made from nerves previously considered inaccessible. SIGNIFICANCE We 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.
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Affiliation(s)
- James P Dunham
- School of Physiology, Pharmacology & Neuroscience, University of Bristol, Bristol, United Kingdom; Anaesthesia, Pain & Critical Care Sciences, Translational Health Sciences, Bristol Medical School, University of Bristol, BS2 8HW, United Kingdom.
| | - Anna C Sales
- School of Physiology, Pharmacology & Neuroscience, University of Bristol, Bristol, United Kingdom
| | - Anthony E Pickering
- School of Physiology, Pharmacology & Neuroscience, University of Bristol, Bristol, United Kingdom; Anaesthesia, Pain & Critical Care Sciences, Translational Health Sciences, Bristol Medical School, University of Bristol, BS2 8HW, United Kingdom
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253
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Buccino AP, Lepperød ME, Dragly SA, Häfliger P, Fyhn M, Hafting T. Open source modules for tracking animal behavior and closed-loop stimulation based on Open Ephys and Bonsai. J Neural Eng 2018; 15:055002. [DOI: 10.1088/1741-2552/aacf45] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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254
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Ciliberti D, Kloosterman F. Falcon: a highly flexible open-source software for closed-loop neuroscience. J Neural Eng 2018; 14:045004. [PMID: 28548044 DOI: 10.1088/1741-2552/aa7526] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
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.
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Affiliation(s)
- Davide Ciliberti
- Neuro-Electronic Research Flanders (NERF), Leuven, Belgium. Brain & Cognition Research Unit, KU Leuven, Belgium. VIB, Leuven, Belgium
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255
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Pirog A, Bornat Y, Perrier R, Raoux M, Jaffredo M, Quotb A, Lang J, Lewis N, Renaud S. Multimed: An Integrated, Multi-Application Platform for the Real-Time Recording and Sub-Millisecond Processing of Biosignals. SENSORS (BASEL, SWITZERLAND) 2018; 18:E2099. [PMID: 29966339 PMCID: PMC6069272 DOI: 10.3390/s18072099] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Revised: 06/23/2018] [Accepted: 06/27/2018] [Indexed: 12/30/2022]
Abstract
Enhanced understanding and control of electrophysiology mechanisms are increasingly being hailed as key knowledge in the fields of modern biology and medicine. As more and more excitable cell mechanics are being investigated and exploited, the need for flexible electrophysiology setups becomes apparent. With that aim, we designed Multimed, which is a versatile hardware platform for the real-time recording and processing of biosignals. Digital processing in Multimed is an arrangement of generic processing units from a custom library. These can freely be rearranged to match the needs of the application. Embedded onto a Field Programmable Gate Array (FPGA), these modules utilize full-hardware signal processing to lower processing latency. It achieves constant latency, and sub-millisecond processing and decision-making on 64 channels. The FPGA core processing unit makes Multimed suitable as either a reconfigurable electrophysiology system or a prototyping platform for VLSI implantable medical devices. It is specifically designed for open- and closed-loop experiments and provides consistent feedback rules, well within biological microseconds timeframes. This paper presents the specifications and architecture of the Multimed system, then details the biosignal processing algorithms and their digital implementation. Finally, three applications utilizing Multimed in neuroscience and diabetes research are described. They demonstrate the system’s configurability, its multi-channel, real-time processing, and its feedback control capabilities.
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Affiliation(s)
- Antoine Pirog
- Laboratoire de l'Intégration du Matériau au Système (IMS), University of Bordeaux, Bordeaux INP, CNRS UMR 5218, F-33400 Talence, France.
| | - Yannick Bornat
- Laboratoire de l'Intégration du Matériau au Système (IMS), University of Bordeaux, Bordeaux INP, CNRS UMR 5218, F-33400 Talence, France.
| | - Romain Perrier
- Signalisation et physiopathologie cardiovasculaire, INSERM S-1180, University of Paris Sud, F-92296 Châtenay-Malabry, France.
| | - Matthieu Raoux
- Institut de Chimie et Biologie des Membranes et des Nano-objets (CBMN), University of Bordeaux, CNRS UMR 5248, F-33600 Pessac, France.
| | - Manon Jaffredo
- Institut de Chimie et Biologie des Membranes et des Nano-objets (CBMN), University of Bordeaux, CNRS UMR 5248, F-33600 Pessac, France.
| | - Adam Quotb
- Laboratoire d'Analyse et d'Architecture des Systèmes (LAAS), Federal University of Toulouse Midi-Pyrénées, CNRS UMR 8001, F-31031 Toulouse, France.
| | - Jochen Lang
- Institut de Chimie et Biologie des Membranes et des Nano-objets (CBMN), University of Bordeaux, CNRS UMR 5248, F-33600 Pessac, France.
| | - Noëlle Lewis
- Laboratoire de l'Intégration du Matériau au Système (IMS), University of Bordeaux, Bordeaux INP, CNRS UMR 5218, F-33400 Talence, France.
| | - Sylvie Renaud
- Laboratoire de l'Intégration du Matériau au Système (IMS), University of Bordeaux, Bordeaux INP, CNRS UMR 5218, F-33400 Talence, France.
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256
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Oscillatory Encoding of Visual Stimulus Familiarity. J Neurosci 2018; 38:6223-6240. [PMID: 29915138 DOI: 10.1523/jneurosci.3646-17.2018] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2017] [Revised: 06/02/2018] [Accepted: 06/04/2018] [Indexed: 11/21/2022] Open
Abstract
Familiarity of the environment changes the way we perceive and encode incoming information. However, the neural substrates underlying this phenomenon are poorly understood. Here we describe a new form of experience-dependent low-frequency oscillations in the primary visual cortex (V1) of awake adult male mice. The oscillations emerged in visually evoked potentials and single-unit activity following repeated visual stimulation. The oscillations were sensitive to the spatial frequency content of a visual stimulus and required the mAChRs for their induction and expression. Finally, ongoing visually evoked θ (4-8 Hz) oscillations boost the visually evoked potential amplitude of incoming visual stimuli if the stimuli are presented at the high excitability phase of the oscillations. Our results demonstrate that an oscillatory code can be used to encode familiarity and serves as a gate for oncoming sensory inputs.SIGNIFICANCE STATEMENT Previous experience can influence the processing of incoming sensory information by the brain and alter perception. However, the mechanistic understanding of how this process takes place is lacking. We have discovered that persistent low-frequency oscillations in the primary visual cortex encode information about familiarity and the spatial frequency of the stimulus. These familiarity evoked oscillations influence neuronal responses to the oncoming stimuli in a way that depends on the oscillation phase. Our work demonstrates a new mechanism of visual stimulus feature detection and learning.
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257
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Erickson JC, Hayes JA, Bustamante M, Joshi R, Rwagaju A, Paskaranandavadivel N, Angeli TR. Intsy: a low-cost, open-source, wireless multi-channel bioamplifier system. Physiol Meas 2018; 39:035008. [PMID: 29406314 DOI: 10.1088/1361-6579/aaad51] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
OBJECTIVE Multi-channel electrical recordings of physiologically generated signals are common to a wide range of biomedical fields. The aim of this work was to develop, validate, and demonstrate the practical utility of a high-quality, low-cost 32/64-channel bioamplifier system with real-time wireless data streaming capability. APPROACH The new 'Intsy' system integrates three main off-the-shelf hardware components: (1) Intan RHD2132 bioamplifier; (2) Teensy 3.2 microcontroller; and (3) RN-42 Bluetooth 2.1 module with a custom LabView interface for real-time data streaming and visualization. Practical utility was validated by measuring serosal gastric slow waves and surface EMG on the forearm with various contraction force levels. Quantitative comparisons were made to a gold-standard commercial system (Biosemi ActiveTwo). MAIN RESULTS Intsy signal quality was quantitatively comparable to that of the ActiveTwo. Recorded slow wave signals had high SNR (24 ± 2.7 dB) and wavefront propagation was accurately mapped. EMG spike bursts were characterized by high SNR (⩾10 dB) and activation timing was readily identified. Stable data streaming rates achieved were 3.5 kS s-1 for wireless and 64 kS s-1 for USB-wired transmission. SIGNIFICANCE Intsy has the highest channel count of any existing open-source, wireless-enabled module. The flexibility, portability and low cost ($1300 for the 32-channel version, or $2500 for 64 channels) of this new hardware module reduce the entry barrier for a range of electrophysiological experiments, as are typical in the gastrointestinal (EGG), cardiac (ECG), neural (EEG), and neuromuscular (EMG) domains.
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Affiliation(s)
- Jonathan C Erickson
- Department of Physics and Engineering, Washington and Lee University, Lexington, VA 24450, United States of America
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258
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Schander A, Stemmann H, Kreiter AK, Lang W. Silicon-Based Microfabrication of Free-Floating Neural Probes and Insertion Tool for Chronic Applications. MICROMACHINES 2018; 9:E131. [PMID: 30424065 PMCID: PMC6187723 DOI: 10.3390/mi9030131] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/08/2018] [Revised: 03/06/2018] [Accepted: 03/14/2018] [Indexed: 12/31/2022]
Abstract
Bidirectional neural interfaces for multi-channel, high-density recording and electrical stimulation of neural activity in the central nervous system are fundamental tools for neuroscience and medical applications. Especially for clinical use, these electrical interfaces must be stable over several years, which is still a major challenge due to the foreign body response of neural tissue. A feasible solution to reduce this inflammatory response is to enable a free-floating implantation of high-density, silicon-based neural probes to avoid mechanical coupling between the skull and the cortex during brain micromotion. This paper presents our latest development of a reproducible microfabrication process, which allows a monolithic integration of a highly-flexible, polyimide-based cable with a silicon-stiffened neural probe at a high resolution of 1 µm. For a precise and complete insertion of the free-floating probes into the cortex, a new silicon-based, vacuum-actuated insertion tool is presented, which can be attached to commercially available electrode drives. To reduce the electrode impedance and enable safe and stable microstimulation an additional coating with the electrical conductive polymer PEDOT:PSS is used. The long-term stability of the presented free-floating neural probes is demonstrated in vitro and in vivo. The promising results suggest the feasibility of these neural probes for chronic applications.
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Affiliation(s)
- Andreas Schander
- Institute for Microsensors, -actuators and -systems (IMSAS), University of Bremen, Bremen 28359, Germany.
| | - Heiko Stemmann
- Brain Research Institute, University of Bremen, Bremen 28359, Germany.
| | - Andreas K Kreiter
- Brain Research Institute, University of Bremen, Bremen 28359, Germany.
| | - Walter Lang
- Institute for Microsensors, -actuators and -systems (IMSAS), University of Bremen, Bremen 28359, Germany.
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259
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Han C, Chaineau M, Chen CXQ, Beitel LK, Durcan TM. Open Science Meets Stem Cells: A New Drug Discovery Approach for Neurodegenerative Disorders. Front Neurosci 2018; 12:47. [PMID: 29467610 PMCID: PMC5808201 DOI: 10.3389/fnins.2018.00047] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2017] [Accepted: 01/19/2018] [Indexed: 12/31/2022] Open
Abstract
Neurodegenerative diseases are a challenge for drug discovery, as the biological mechanisms are complex and poorly understood, with a paucity of models that faithfully recapitulate these disorders. Recent advances in stem cell technology have provided a paradigm shift, providing researchers with tools to generate human induced pluripotent stem cells (iPSCs) from patient cells. With the potential to generate any human cell type, we can now generate human neurons and develop "first-of-their-kind" disease-relevant assays for small molecule screening. Now that the tools are in place, it is imperative that we accelerate discoveries from the bench to the clinic. Using traditional closed-door research systems raises barriers to discovery, by restricting access to cells, data and other research findings. Thus, a new strategy is required, and the Montreal Neurological Institute (MNI) and its partners are piloting an "Open Science" model. One signature initiative will be that the MNI biorepository will curate and disseminate patient samples in a more accessible manner through open transfer agreements. This feeds into the MNI open drug discovery platform, focused on developing industry-standard assays with iPSC-derived neurons. All cell lines, reagents and assay findings developed in this open fashion will be made available to academia and industry. By removing the obstacles many universities and companies face in distributing patient samples and assay results, our goal is to accelerate translational medical research and the development of new therapies for devastating neurodegenerative disorders.
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Affiliation(s)
| | | | | | | | - Thomas M. Durcan
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
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260
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Abstract
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.
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261
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Patel YA, George A, Dorval AD, White JA, Christini DJ, Butera RJ. Hard real-time closed-loop electrophysiology with the Real-Time eXperiment Interface (RTXI). PLoS Comput Biol 2017; 13:e1005430. [PMID: 28557998 PMCID: PMC5469488 DOI: 10.1371/journal.pcbi.1005430] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2016] [Revised: 06/13/2017] [Accepted: 02/10/2017] [Indexed: 01/24/2023] Open
Abstract
The ability to experimentally perturb biological systems has traditionally been limited to static pre-programmed or operator-controlled protocols. In contrast, real-time control allows dynamic probing of biological systems with perturbations that are computed on-the-fly during experimentation. Real-time control applications for biological research are available; however, these systems are costly and often restrict the flexibility and customization of experimental protocols. The Real-Time eXperiment Interface (RTXI) is an open source software platform for achieving hard real-time data acquisition and closed-loop control in biological experiments while retaining the flexibility needed for experimental settings. RTXI has enabled users to implement complex custom closed-loop protocols in single cell, cell network, animal, and human electrophysiology studies. RTXI is also used as a free and open source, customizable electrophysiology platform in open-loop studies requiring online data acquisition, processing, and visualization. RTXI is easy to install, can be used with an extensive range of external experimentation and data acquisition hardware, and includes standard modules for implementing common electrophysiology protocols.
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Affiliation(s)
- Yogi A. Patel
- Bioengineering Graduate Program, Georgia Institute of Technology, Atlanta, Georgia, United States of America
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, United States of America
| | - Ansel George
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, United States of America
| | - Alan D. Dorval
- Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America
| | - John A. White
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America
| | - David J. Christini
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, United States of America
- * E-mail: (DJC); (RJB)
| | - Robert J. Butera
- Bioengineering Graduate Program, Georgia Institute of Technology, Atlanta, Georgia, United States of America
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America
- * E-mail: (DJC); (RJB)
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