1
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Ali YH, Bodkin K, Rigotti-Thompson M, Patel K, Card NS, Bhaduri B, Nason-Tomaszewski SR, Mifsud DM, Hou X, Nicolas C, Allcroft S, Hochberg LR, Au Yong N, Stavisky SD, Miller LE, Brandman DM, Pandarinath C. BRAND: a platform for closed-loop experiments with deep network models. J Neural Eng 2024; 21:026046. [PMID: 38579696 PMCID: PMC11021878 DOI: 10.1088/1741-2552/ad3b3a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 01/27/2024] [Accepted: 04/05/2024] [Indexed: 04/07/2024]
Abstract
Objective.Artificial neural networks (ANNs) are state-of-the-art tools for modeling and decoding neural activity, but deploying them in closed-loop experiments with tight timing constraints is challenging due to their limited support in existing real-time frameworks. Researchers need a platform that fully supports high-level languages for running ANNs (e.g. Python and Julia) while maintaining support for languages that are critical for low-latency data acquisition and processing (e.g. C and C++).Approach.To address these needs, we introduce the Backend for Realtime Asynchronous Neural Decoding (BRAND). BRAND comprises Linux processes, termednodes, which communicate with each other in agraphvia streams of data. Its asynchronous design allows for acquisition, control, and analysis to be executed in parallel on streams of data that may operate at different timescales. BRAND uses Redis, an in-memory database, to send data between nodes, which enables fast inter-process communication and supports 54 different programming languages. Thus, developers can easily deploy existing ANN models in BRAND with minimal implementation changes.Main results.In our tests, BRAND achieved <600 microsecond latency between processes when sending large quantities of data (1024 channels of 30 kHz neural data in 1 ms chunks). BRAND runs a brain-computer interface with a recurrent neural network (RNN) decoder with less than 8 ms of latency from neural data input to decoder prediction. In a real-world demonstration of the system, participant T11 in the BrainGate2 clinical trial (ClinicalTrials.gov Identifier: NCT00912041) performed a standard cursor control task, in which 30 kHz signal processing, RNN decoding, task control, and graphics were all executed in BRAND. This system also supports real-time inference with complex latent variable models like Latent Factor Analysis via Dynamical Systems.Significance.By providing a framework that is fast, modular, and language-agnostic, BRAND lowers the barriers to integrating the latest tools in neuroscience and machine learning into closed-loop experiments.
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Affiliation(s)
- Yahia H Ali
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, United States of America
| | - Kevin Bodkin
- Department of Neuroscience, Northwestern University, Chicago, IL, United States of America
| | - Mattia Rigotti-Thompson
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, United States of America
| | - Kushant Patel
- Department of Neurological Surgery, University of California, Davis, CA, United States of America
| | - Nicholas S Card
- Department of Neurological Surgery, University of California, Davis, CA, United States of America
| | - Bareesh Bhaduri
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, United States of America
| | - Samuel R Nason-Tomaszewski
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, United States of America
| | - Domenick M Mifsud
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, United States of America
| | - Xianda Hou
- Department of Neurological Surgery, University of California, Davis, CA, United States of America
| | - Claire Nicolas
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, United States of America
| | - Shane Allcroft
- School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI, United States of America
| | - Leigh R Hochberg
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, United States of America
- School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI, United States of America
- Harvard Medical School, Boston, MA, United States of America
- Veterans Affairs Rehabilitation Research & Development Center for Neurorestoration and Neurotechnology, Providence VA Medical Center, Providence, RI, United States of America
| | - Nicholas Au Yong
- Department of Neurosurgery, Emory University, Atlanta, GA, United States of America
| | - Sergey D Stavisky
- Department of Neurological Surgery, University of California, Davis, CA, United States of America
| | - Lee E Miller
- Department of Neuroscience, Northwestern University, Chicago, IL, United States of America
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, United States of America
- Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL, United States of America
- Shirley Ryan AbilityLab, Chicago, IL, United States of America
| | - David M Brandman
- Department of Neurological Surgery, University of California, Davis, CA, United States of America
| | - Chethan Pandarinath
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, United States of America
- Department of Neurosurgery, Emory University, Atlanta, GA, United States of America
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Garrido-Peña A, Sanchez-Martin P, Reyes-Sanchez M, Levi R, Rodriguez FB, Castilla J, Tornero J, Varona P. Modulation of neuronal dynamics by sustained and activity-dependent continuous-wave near-infrared laser stimulation. NEUROPHOTONICS 2024; 11:024308. [PMID: 38764942 PMCID: PMC11100521 DOI: 10.1117/1.nph.11.2.024308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 04/19/2024] [Accepted: 04/22/2024] [Indexed: 05/21/2024]
Abstract
Significance Near-infrared laser illumination is a non-invasive alternative/complement to classical stimulation methods in neuroscience but the mechanisms underlying its action on neuronal dynamics remain unclear. Most studies deal with high-frequency pulsed protocols and stationary characterizations disregarding the dynamic modulatory effect of sustained and activity-dependent stimulation. The understanding of such modulation and its widespread dissemination can help to develop specific interventions for research applications and treatments for neural disorders. Aim We quantified the effect of continuous-wave near-infrared (CW-NIR) laser illumination on single neuron dynamics using sustained stimulation and an open-source activity-dependent protocol to identify the biophysical mechanisms underlying this modulation and its time course. Approach We characterized the effect by simultaneously performing long intracellular recordings of membrane potential while delivering sustained and closed-loop CW-NIR laser stimulation. We used waveform metrics and conductance-based models to assess the role of specific biophysical candidates on the modulation. Results We show that CW-NIR sustained illumination asymmetrically accelerates action potential dynamics and the spiking rate on single neurons, while closed-loop stimulation unveils its action at different phases of the neuron dynamics. Our model study points out the action of CW-NIR on specific ionic-channels and the key role of temperature on channel properties to explain the modulatory effect. Conclusions Both sustained and activity-dependent CW-NIR stimulation effectively modulate neuronal dynamics by a combination of biophysical mechanisms. Our open-source protocols can help to disseminate this non-invasive optical stimulation in novel research and clinical applications.
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Affiliation(s)
- Alicia Garrido-Peña
- Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, Madrid, Spain
| | - Pablo Sanchez-Martin
- Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, Madrid, Spain
| | - Manuel Reyes-Sanchez
- Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, Madrid, Spain
| | - Rafael Levi
- Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, Madrid, Spain
| | - Francisco B. Rodriguez
- Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, Madrid, Spain
| | - Javier Castilla
- Hospital los Madroños, Center for Clinical Neuroscience, Brunete, Spain
| | - Jesus Tornero
- Hospital los Madroños, Center for Clinical Neuroscience, Brunete, Spain
| | - Pablo Varona
- Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, Madrid, Spain
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3
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Weiss DA, Borsa AM, Pala A, Sederberg AJ, Stanley GB. A machine learning approach for real-time cortical state estimation. J Neural Eng 2024; 21:016016. [PMID: 38232377 PMCID: PMC10868597 DOI: 10.1088/1741-2552/ad1f7b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 01/17/2024] [Indexed: 01/19/2024]
Abstract
Objective.Cortical function is under constant modulation by internally-driven, latent variables that regulate excitability, collectively known as 'cortical state'. Despite a vast literature in this area, the estimation of cortical state remains relatively ad hoc, and not amenable to real-time implementation. Here, we implement robust, data-driven, and fast algorithms that address several technical challenges for online cortical state estimation.Approach. We use unsupervised Gaussian mixture models to identify discrete, emergent clusters in spontaneous local field potential signals in cortex. We then extend our approach to a temporally-informed hidden semi-Markov model (HSMM) with Gaussian observations to better model and infer cortical state transitions. Finally, we implement our HSMM cortical state inference algorithms in a real-time system, evaluating their performance in emulation experiments.Main results. Unsupervised clustering approaches reveal emergent state-like structure in spontaneous electrophysiological data that recapitulate arousal-related cortical states as indexed by behavioral indicators. HSMMs enable cortical state inferences in a real-time context by modeling the temporal dynamics of cortical state switching. Using HSMMs provides robustness to state estimates arising from noisy, sequential electrophysiological data.Significance. To our knowledge, this work represents the first implementation of a real-time software tool for continuously decoding cortical states with high temporal resolution (40 ms). The software tools that we provide can facilitate our understanding of how cortical states dynamically modulate cortical function on a moment-by-moment basis and provide a basis for state-aware brain machine interfaces across health and disease.
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Affiliation(s)
- David A Weiss
- Program in Bioengineering, Georgia Institute of Technology, Atlanta, GA, United States of America
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States of America
| | - Adriano Mf Borsa
- Program in Bioengineering, Georgia Institute of Technology, Atlanta, GA, United States of America
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States of America
| | - Aurélie Pala
- Department of Biology, Emory University, Atlanta, GA, United States of America
| | - Audrey J Sederberg
- Department of Neuroscience, University of Minnesota Medical School, Minneapolis, MN, United States of America
- Medical Discovery Team in Optical Imaging and Brain Science, University of Minnesota, Minneapolis, MN, United States of America
| | - Garrett B Stanley
- Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, United States of America
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Ördög B, De Coster T, Dekker SO, Bart CI, Zhang J, Boink GJJ, Bax WH, Deng S, den Ouden BL, de Vries AAF, Pijnappels DA. Opto-electronic feedback control of membrane potential for real-time control of action potentials. CELL REPORTS METHODS 2023; 3:100671. [PMID: 38086387 PMCID: PMC10753386 DOI: 10.1016/j.crmeth.2023.100671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 10/09/2023] [Accepted: 11/19/2023] [Indexed: 12/21/2023]
Abstract
To unlock new research possibilities by acquiring control of action potential (AP) morphologies in excitable cells, we developed an opto-electronic feedback loop-based system integrating cellular electrophysiology, real-time computing, and optogenetic approaches and applied it to monolayers of heart muscle cells. This allowed accurate restoration and preservation of cardiac AP morphologies in the presence of electrical perturbations of different origin in an unsupervised, self-regulatory manner, without any prior knowledge of the disturbance. Moreover, arbitrary AP waveforms could be enforced onto these cells. Collectively, these results set the stage for the refinement and application of opto-electronic control systems to enable in-depth investigation into the regulatory role of membrane potential in health and disease.
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Affiliation(s)
- Balázs Ördög
- Laboratory of Experimental Cardiology, Department of Cardiology, Heart Lung Center Leiden, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands.
| | - Tim De Coster
- Laboratory of Experimental Cardiology, Department of Cardiology, Heart Lung Center Leiden, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Sven O Dekker
- Laboratory of Experimental Cardiology, Department of Cardiology, Heart Lung Center Leiden, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Cindy I Bart
- Laboratory of Experimental Cardiology, Department of Cardiology, Heart Lung Center Leiden, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Juan Zhang
- Laboratory of Experimental Cardiology, Department of Cardiology, Heart Lung Center Leiden, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Gerard J J Boink
- Amsterdam Cardiovascular Sciences, Department of Cardiology, Amsterdam UMC, Location AMC, University of Amsterdam, 1105 AZ Amsterdam, the Netherlands; Department of Medical Biology, Amsterdam UMC, Location AMC, University of Amsterdam, 1105 AZ Amsterdam, the Netherlands
| | - Wilhelmina H Bax
- Laboratory of Experimental Cardiology, Department of Cardiology, Heart Lung Center Leiden, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Shanliang Deng
- Laboratory of Experimental Cardiology, Department of Cardiology, Heart Lung Center Leiden, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands; Department of Microelectronics, Delft University of Technology, 2628 CD Delft, the Netherlands
| | - Bram L den Ouden
- Laboratory of Experimental Cardiology, Department of Cardiology, Heart Lung Center Leiden, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands; Department of Microelectronics, Delft University of Technology, 2628 CD Delft, the Netherlands
| | - Antoine A F de Vries
- Laboratory of Experimental Cardiology, Department of Cardiology, Heart Lung Center Leiden, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Daniël A Pijnappels
- Laboratory of Experimental Cardiology, Department of Cardiology, Heart Lung Center Leiden, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands.
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Lu J, Yan M, Wang Q, Li P, Jing Y, Gao D. A system based on machine learning for improving sleep. J Neurosci Methods 2023; 397:109936. [PMID: 37524247 DOI: 10.1016/j.jneumeth.2023.109936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 07/17/2023] [Accepted: 07/28/2023] [Indexed: 08/02/2023]
Abstract
Closed-loop auditory stimulation is one of the well-known and emerging sensory stimulation techniques, which achieves the purpose of sleep regulation by driving the EEG slow oscillation (SO, <1 Hz) through auditory stimulation. The main challenge is to accurately identify the stimulation timing and provide feedback in real-time, which has high requirements on the response time and recognition accuracy of the closed-loop auditory stimulation system. To reduce the impact of systematic errors on the regulation results, most traditional closed-loop auditory stimulation systems try to identify a single feature to determine the timing of stimulus delivery and reduce the system feedback delay by simplifying the calculation. Unlike existing closed-loop regulation systems that identify specific brain features, this paper proposes a closed-loop auditory stimulation sleep regulation system deploying machine learning. The process is: through online sleep real-time automatic staging, tracking the sleep stage to provide feedback quickly, and continuously offering external auditory stimulation at a specific SO phase. This paper uses this system to conduct sleep auditory stimulation regulation experiments on ten subjects. The experimental results show that the sleep closed-loop regulation system proposed in this paper can achieve consistency (effective for almost all subjects in the experiment) and immediate (taking effect immediately after stimulation) modulation effects on SOs. More importantly, the proposed method is superior to existing advanced methods. Therefore, the system designed in this paper has great potential to be more reliable and flexible in sleep regulation.
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Affiliation(s)
- Jiale Lu
- School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China
| | - Mingjing Yan
- School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China
| | - Qinghua Wang
- Hubi Wuhan Public Security Bureau, No. 798, Wuluo Road, Wuhan City, Hubei 430070, China
| | - Pengrui Li
- School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China
| | - Yuan Jing
- School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China
| | - Dongrui Gao
- School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China; School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.
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6
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Newman JP, Zhang J, Cuevas-López A, Miller NJ, Honda T, van der Goes MSH, Leighton AH, Carvalho F, Lopes G, Lakunina A, Siegle JH, Harnett MT, Wilson MA, Voigts J. A unified open-source platform for multimodal neural recording and perturbation during naturalistic behavior. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.30.554672. [PMID: 37693443 PMCID: PMC10491150 DOI: 10.1101/2023.08.30.554672] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Behavioral neuroscience faces two conflicting demands: long-duration recordings from large neural populations and unimpeded animal behavior. To meet this challenge, we developed ONIX, an open-source data acquisition system with high data throughput (2GB/sec) and low closed-loop latencies (<1ms) that uses a novel 0.3 mm thin tether to minimize behavioral impact. Head position and rotation are tracked in 3D and used to drive active commutation without torque measurements. ONIX can acquire from combinations of passive electrodes, Neuropixels probes, head-mounted microscopes, cameras, 3D-trackers, and other data sources. We used ONIX to perform uninterrupted, long (~7 hours) neural recordings in mice as they traversed complex 3-dimensional terrain. ONIX allowed exploration with similar mobility as non-implanted animals, in contrast to conventional tethered systems which restricted movement. By combining long recordings with full mobility, our technology will enable new progress on questions that require high-quality neural recordings during ethologically grounded behaviors.
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Affiliation(s)
- Jonathan P Newman
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Open Ephys Inc. Atlanta, GA, USA
| | - Jie Zhang
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
| | - Aarón Cuevas-López
- Open Ephys Inc. Atlanta, GA, USA
- Dept. of Electrical Engineering, Polytechnic University of Valencia, Valencia, Spain
- Open Ephys Production Site, Lisbon, Portugal
| | - Nicholas J Miller
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
| | - Takato Honda
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
| | - Marie-Sophie H van der Goes
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
| | | | | | | | - Anna Lakunina
- Allen Institute for Neural Dynamics, Seattle, Washington, USA
| | - Joshua H Siegle
- Allen Institute for Neural Dynamics, Seattle, Washington, USA
| | - Mark T Harnett
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
| | - Matthew A Wilson
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
| | - Jakob Voigts
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- Open Ephys Inc. Atlanta, GA, USA
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
- HHMI Janelia Research Campus, Ashburn, VA, USA
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7
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Ali YH, Bodkin K, Rigotti-Thompson M, Patel K, Card NS, Bhaduri B, Nason-Tomaszewski SR, Mifsud DM, Hou X, Nicolas C, Allcroft S, Hochberg LR, Yong NA, Stavisky SD, Miller LE, Brandman DM, Pandarinath C. BRAND: A platform for closed-loop experiments with deep network models. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.08.552473. [PMID: 37609167 PMCID: PMC10441362 DOI: 10.1101/2023.08.08.552473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Artificial neural networks (ANNs) are state-of-the-art tools for modeling and decoding neural activity, but deploying them in closed-loop experiments with tight timing constraints is challenging due to their limited support in existing real-time frameworks. Researchers need a platform that fully supports high-level languages for running ANNs (e.g., Python and Julia) while maintaining support for languages that are critical for low-latency data acquisition and processing (e.g., C and C++). To address these needs, we introduce the Backend for Realtime Asynchronous Neural Decoding (BRAND). BRAND comprises Linux processes, termed nodes , which communicate with each other in a graph via streams of data. Its asynchronous design allows for acquisition, control, and analysis to be executed in parallel on streams of data that may operate at different timescales. BRAND uses Redis to send data between nodes, which enables fast inter-process communication and supports 54 different programming languages. Thus, developers can easily deploy existing ANN models in BRAND with minimal implementation changes. In our tests, BRAND achieved <600 microsecond latency between processes when sending large quantities of data (1024 channels of 30 kHz neural data in 1-millisecond chunks). BRAND runs a brain-computer interface with a recurrent neural network (RNN) decoder with less than 8 milliseconds of latency from neural data input to decoder prediction. In a real-world demonstration of the system, participant T11 in the BrainGate2 clinical trial performed a standard cursor control task, in which 30 kHz signal processing, RNN decoding, task control, and graphics were all executed in BRAND. This system also supports real-time inference with complex latent variable models like Latent Factor Analysis via Dynamical Systems. By providing a framework that is fast, modular, and language-agnostic, BRAND lowers the barriers to integrating the latest tools in neuroscience and machine learning into closed-loop experiments.
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8
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Altomare C, Bartolucci C, Sala L, Balbi C, Burrello J, Pietrogiovanna N, Burrello A, Bolis S, Panella S, Arici M, Krause R, Rocchetti M, Severi S, Barile L. A dynamic clamping approach using in silico IK1 current for discrimination of chamber-specific hiPSC-derived cardiomyocytes. Commun Biol 2023; 6:291. [PMID: 36934210 PMCID: PMC10024709 DOI: 10.1038/s42003-023-04674-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 03/07/2023] [Indexed: 03/20/2023] Open
Abstract
Human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes (CM) constitute a mixed population of ventricular-, atrial-, nodal-like cells, limiting the reliability for studying chamber-specific disease mechanisms. Previous studies characterised CM phenotype based on action potential (AP) morphology, but the classification criteria were still undefined. Our aim was to use in silico models to develop an automated approach for discriminating the electrophysiological differences between hiPSC-CM. We propose the dynamic clamp (DC) technique with the injection of a specific IK1 current as a tool for deriving nine electrical biomarkers and blindly classifying differentiated CM. An unsupervised learning algorithm was applied to discriminate CM phenotypes and principal component analysis was used to visualise cell clustering. Pharmacological validation was performed by specific ion channel blocker and receptor agonist. The proposed approach improves the translational relevance of the hiPSC-CM model for studying mechanisms underlying inherited or acquired atrial arrhythmias in human CM, and for screening anti-arrhythmic agents.
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Affiliation(s)
- Claudia Altomare
- Cardiovascular Theranostics, Istituto Cardiocentro Ticino, Ente Ospedaliero Cantonale, Lugano, Switzerland
- Laboratories for Translational Research, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
- Euler institute, Università Svizzera italiana, Lugano, Switzerland
| | - Chiara Bartolucci
- Department of Electrical, Electronic and Information Engineering 'Guglielmo Marconi', University of Bologna, Cesena, Italy
| | - Luca Sala
- Istituto Auxologico Italiano IRCCS, Center for Cardiac Arrhythmias of Genetic Origin and Laboratory of Cardiovascular Genetics, Milan, Italy
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Milano, Italy
| | - Carolina Balbi
- Laboratories for Translational Research, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
- Cellular and Molecular Cardiology, Istituto Cardiocentro Ticino, Ente Ospedaliero Cantonale, Lugano, Switzerland
- Center for Molecular Cardiology, University of Zurich, Zurich, Switzerland
| | - Jacopo Burrello
- Cardiovascular Theranostics, Istituto Cardiocentro Ticino, Ente Ospedaliero Cantonale, Lugano, Switzerland
- Division of Internal Medicine 4 and Hypertension Unit, Department of Medical Sciences, University of Torino, Torino, Italy
| | - Nicole Pietrogiovanna
- Cardiovascular Theranostics, Istituto Cardiocentro Ticino, Ente Ospedaliero Cantonale, Lugano, Switzerland
| | - Alessio Burrello
- Department of Electrical, Electronic and Information Engineering (DEI), University of Bologna, Bologna, Italy
| | - Sara Bolis
- Cardiovascular Theranostics, Istituto Cardiocentro Ticino, Ente Ospedaliero Cantonale, Lugano, Switzerland
- Laboratories for Translational Research, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
- Cellular and Molecular Cardiology, Istituto Cardiocentro Ticino, Ente Ospedaliero Cantonale, Lugano, Switzerland
| | - Stefano Panella
- Cardiovascular Theranostics, Istituto Cardiocentro Ticino, Ente Ospedaliero Cantonale, Lugano, Switzerland
- Laboratories for Translational Research, Ente Ospedaliero Cantonale, Bellinzona, Switzerland
| | - Martina Arici
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Milano, Italy
| | - Rolf Krause
- Euler institute, Università Svizzera italiana, Lugano, Switzerland
| | - Marcella Rocchetti
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Milano, Italy
| | - Stefano Severi
- Department of Electrical, Electronic and Information Engineering 'Guglielmo Marconi', University of Bologna, Cesena, Italy.
| | - Lucio Barile
- Cardiovascular Theranostics, Istituto Cardiocentro Ticino, Ente Ospedaliero Cantonale, Lugano, Switzerland.
- Laboratories for Translational Research, Ente Ospedaliero Cantonale, Bellinzona, Switzerland.
- Euler institute, Università Svizzera italiana, Lugano, Switzerland.
- Faculty of Biomedical Sciences, Università Svizzera italiana, Lugano, Switzerland.
- Institute of Life Science, Scuola Superiore Sant'Anna, Pisa, Italy.
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Delgadillo Bonequi I, Stroschein A, Koerner LJ. A field-programmable gate array (FPGA)-based data acquisition system for closed-loop experiments. THE REVIEW OF SCIENTIFIC INSTRUMENTS 2022; 93:114712. [PMID: 36461500 PMCID: PMC9665961 DOI: 10.1063/5.0121898] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Accepted: 10/29/2022] [Indexed: 06/17/2023]
Abstract
We describe a custom and open source field-programmable gate array (FPGA)-based data acquisition (DAQ) system developed for electrophysiology and generally useful for closed-loop feedback experiments. FPGA acquisition and processing are combined with high-speed analog and digital converters to enable real-time feedback. The digital approach eases experimental setup and repeatability by allowing for system identification and in situ tuning of filter bandwidths. The FPGA system includes I2C and serial peripheral interface controllers, 1 GiB dynamic RAM for data buffering, and a USB3 interface to Python software. The DAQ system uses common HDMI connectors to support daughtercards that can be customized for a given experiment to make the system modular and expandable. The FPGA-based digital signal processing (DSP) is used to generate fourth-order digital infinite impulse response filters and feedback with microsecond latency. The FPGA-based DSP and an analog inner-loop are demonstrated via an experiment that rapidly steps the voltage of a capacitor isolated from the system by a considerable resistance using a feedback approach that adjusts the driving voltage based on the digitized capacitor current.
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Affiliation(s)
- Ian Delgadillo Bonequi
- Department of Electrical and Computer Engineering, University of St. Thomas, St. Paul, Minnesota 55105, USA
| | - Abraham Stroschein
- Department of Electrical and Computer Engineering, University of St. Thomas, St. Paul, Minnesota 55105, USA
| | - Lucas J. Koerner
- Department of Electrical and Computer Engineering, University of St. Thomas, St. Paul, Minnesota 55105, USA
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10
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Pfeiffer P, Barreda Tomás FJ, Wu J, Schleimer JH, Vida I, Schreiber S. A dynamic clamp protocol to artificially modify cell capacitance. eLife 2022; 11:75517. [PMID: 35362411 PMCID: PMC9135398 DOI: 10.7554/elife.75517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 03/17/2022] [Indexed: 11/13/2022] Open
Abstract
Dynamics of excitable cells and networks depend on the membrane time constant, set by membrane resistance and capacitance. Whereas pharmacological and genetic manipulations of ionic conductances of excitable membranes are routine in electrophysiology, experimental control over capacitance remains a challenge. Here, we present capacitance clamp, an approach that allows electrophysiologists to mimic a modified capacitance in biological neurons via an unconventional application of the dynamic clamp technique. We first demonstrate the feasibility to quantitatively modulate capacitance in a mathematical neuron model and then confirm the functionality of capacitance clamp in in vitro experiments in granule cells of rodent dentate gyrus with up to threefold virtual capacitance changes. Clamping of capacitance thus constitutes a novel technique to probe and decipher mechanisms of neuronal signaling in ways that were so far inaccessible to experimental electrophysiology.
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Affiliation(s)
- Paul Pfeiffer
- Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany
| | | | - Jiameng Wu
- Institute for Integrative Neuroanatomy, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Jan-Hendrik Schleimer
- Institute of Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Imre Vida
- Institute for Integrative Neuroanatomy, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Susanne Schreiber
- Institute of Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Berlin, Germany
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11
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Ghazizadeh Z, Zhu J, Fattahi F, Tang A, Sun X, Amin S, Tsai SY, Khalaj M, Zhou T, Samuel RM, Zhang T, Ortega FA, Gordillo M, Moroziewicz D, Paull D, Noggle SA, Xiang JZ, Studer L, Christini DJ, Pitt GS, Evans T, Chen S. A dual SHOX2:GFP; MYH6:mCherry knockin hESC reporter line for derivation of human SAN-like cells. iScience 2022; 25:104153. [PMID: 35434558 PMCID: PMC9010642 DOI: 10.1016/j.isci.2022.104153] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 01/25/2022] [Accepted: 03/22/2022] [Indexed: 01/19/2023] Open
Abstract
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.
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Affiliation(s)
- Zaniar Ghazizadeh
- Department of Surgery, Weill Cornell Medical College, New York, NY 10065, USA,Corresponding author
| | - Jiajun Zhu
- Department of Surgery, Weill Cornell Medical College, New York, NY 10065, USA
| | - Faranak Fattahi
- The Center for Stem Cell Biology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA,Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA,Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Alice Tang
- Department of Surgery, Weill Cornell Medical College, New York, NY 10065, USA
| | - Xiaolu Sun
- Cardiovascular Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Sadaf Amin
- Department of Surgery, Weill Cornell Medical College, New York, NY 10065, USA
| | - Su-Yi Tsai
- Department of Life Science, National Taiwan University, Taipei 10617, Taiwan
| | - Mona Khalaj
- Department of Surgery, Weill Cornell Medical College, New York, NY 10065, USA
| | - Ting Zhou
- The Center for Stem Cell Biology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Ryan M. Samuel
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA,Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Tuo Zhang
- Genomic Resource Core Facility, Weill Cornell Medical College, New York, NY 10065, USA
| | - Francis A. Ortega
- Physiology, Biophysics, and Systems Biology Graduate Program, Weill Cornell Medical College, New York, NY 10065, USA,Department of Physiology & Pharmacology, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Miriam Gordillo
- Department of Surgery, Weill Cornell Medical College, New York, NY 10065, USA
| | - Dorota Moroziewicz
- The New York Stem Cell Foundation Research Institute, 619 West 54th Street, 3rd Floor, New York, NY 10019, USA
| | | | - Daniel Paull
- The New York Stem Cell Foundation Research Institute, 619 West 54th Street, 3rd Floor, New York, NY 10019, USA
| | - Scott A. Noggle
- The New York Stem Cell Foundation Research Institute, 619 West 54th Street, 3rd Floor, New York, NY 10019, USA
| | - Jenny Zhaoying Xiang
- Genomic Resource Core Facility, Weill Cornell Medical College, New York, NY 10065, USA
| | - Lorenz Studer
- The Center for Stem Cell Biology, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - David J. Christini
- Department of Physiology & Pharmacology, SUNY Downstate Health Sciences University, Brooklyn, NY 11203, USA
| | - Geoffrey S. Pitt
- Cardiovascular Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Todd Evans
- Department of Surgery, Weill Cornell Medical College, New York, NY 10065, USA,Corresponding author
| | - Shuibing Chen
- Department of Surgery, Weill Cornell Medical College, New York, NY 10065, USA,Corresponding author
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12
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Morozova E, Newstein P, Marder E. Reciprocally inhibitory circuits operating with distinct mechanisms are differently robust to perturbation and modulation. eLife 2022; 11:74363. [PMID: 35103594 PMCID: PMC8884723 DOI: 10.7554/elife.74363] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 01/26/2022] [Indexed: 11/13/2022] Open
Abstract
Reciprocal inhibition is a building block in many sensory and motor circuits. We studied the features that underly robustness in reciprocally inhibitory two neuron circuits. We used the dynamic clamp to create reciprocally inhibitory circuits from pharmacologically isolated neurons of the crab stomatogastric ganglion by injecting artificial graded synaptic (ISyn) and hyperpolarization-activated inward (IH) currents. There is a continuum of mechanisms in circuits that generate antiphase oscillations, with ‘release’ and ‘escape’ mechanisms at the extremes, and mixed mode oscillations between these extremes. In release, the active neuron primarily controls the off/on transitions. In escape, the inhibited neuron controls the transitions. We characterized the robustness of escape and release circuits to alterations in circuit parameters, temperature, and neuromodulation. We found that escape circuits rely on tight correlations between synaptic and H conductances to generate bursting but are resilient to temperature increase. Release circuits are robust to variations in synaptic and H conductances but fragile to temperature increase. The modulatory current (IMI) restores oscillations in release circuits but has little effect in escape circuits. Perturbations can alter the balance of escape and release mechanisms and can create mixed mode oscillations. We conclude that the same perturbation can have dramatically different effects depending on the circuits’ mechanism of operation that may not be observable from basal circuit activity.
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Affiliation(s)
| | - Peter Newstein
- Biology Department, University of Oregon, Eugene, United States
| | - Eve Marder
- Volen Center, Brandeis University, Waltham, United States
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13
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Environmental Enrichment Sharpens Sensory Acuity by Enhancing Information Coding in Barrel Cortex and Premotor Cortex. eNeuro 2021; 8:ENEURO.0309-20.2021. [PMID: 33893166 PMCID: PMC8143018 DOI: 10.1523/eneuro.0309-20.2021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 04/13/2021] [Accepted: 04/17/2021] [Indexed: 12/20/2022] Open
Abstract
Environmental enrichment (EE) is beneficial to sensory functions. Thus, elucidating the neural mechanism underlying improvement of sensory stimulus discrimination is important for developing therapeutic strategies. We aim to advance the understanding of such neural mechanism. We found that tactile enrichment improved tactile stimulus feature discrimination. The neural correlate of such improvement was revealed by analyzing single-cell information coding in both the primary somatosensory cortex and the premotor cortex of awake behaving animals. Our results show that EE enhances the decision-information coding capacity of cells that are tuned to adjacent whiskers, and of premotor cortical cells.
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14
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Bolus MF, Willats AA, Rozell CJ, Stanley GB. State-space optimal feedback control of optogenetically driven neural activity. J Neural Eng 2021; 18. [PMID: 32932241 DOI: 10.1088/1741-2552/abb89c] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Accepted: 09/15/2020] [Indexed: 11/11/2022]
Abstract
Objective.The rapid acceleration of tools for recording neuronal populations and targeted optogenetic manipulation has enabled real-time, feedback control of neuronal circuits in the brain. Continuously-graded control of measured neuronal activity poses a wide range of technical challenges, which we address through a combination of optogenetic stimulation and a state-space optimal control framework implemented in the thalamocortical circuit of the awake mouse.Approach.Closed-loop optogenetic control of neurons was performed in real-time via stimulation of channelrhodopsin-2 expressed in the somatosensory thalamus of the head-fixed mouse. A state-space linear dynamical system model structure was used to approximate the light-to-spiking input-output relationship in both single-neuron as well as multi-neuron scenarios when recording from multielectrode arrays. These models were utilized to design state feedback controller gains by way of linear quadratic optimal control and were also used online for estimation of state feedback, where a parameter-adaptive Kalman filter provided robustness to model-mismatch.Main results.This model-based control scheme proved effective for feedback control of single-neuron firing rate in the thalamus of awake animals. Notably, the graded optical actuation utilized here did not synchronize simultaneously recorded neurons, but heterogeneity across the neuronal population resulted in a varied response to stimulation. Simulated multi-output feedback control provided better control of a heterogeneous population and demonstrated how the approach generalizes beyond single-neuron applications.Significance.To our knowledge, this work represents the first experimental application of state space model-based feedback control for optogenetic stimulation. In combination with linear quadratic optimal control, the approaches laid out and tested here should generalize to future problems involving the control of highly complex neural circuits. More generally, feedback control of neuronal circuits opens the door to adaptively interacting with the dynamics underlying sensory, motor, and cognitive signaling, enabling a deeper understanding of circuit function and ultimately the control of function in the face of injury or disease.
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Affiliation(s)
- M F Bolus
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, United States of America
| | - A A Willats
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, United States of America
| | - C J Rozell
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States of America
| | - G B Stanley
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, United States of America
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15
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Verkerk AO, Wilders R. Dynamic Clamp in Electrophysiological Studies on Stem Cell-Derived Cardiomyocytes-Why and How? J Cardiovasc Pharmacol 2021; 77:267-279. [PMID: 33229908 DOI: 10.1097/fjc.0000000000000955] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Accepted: 10/31/2020] [Indexed: 12/15/2022]
Abstract
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.
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Affiliation(s)
- Arie O Verkerk
- Department of Medical Biology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands ; and
- Department of Experimental Cardiology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Ronald Wilders
- Department of Medical Biology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands ; and
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16
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Zelmann R, Paulk AC, Basu I, Sarma A, Yousefi A, Crocker B, Eskandar E, Williams Z, Cosgrove GR, Weisholtz DS, Dougherty DD, Truccolo W, Widge AS, Cash SS. CLoSES: A platform for closed-loop intracranial stimulation in humans. Neuroimage 2020; 223:117314. [PMID: 32882382 PMCID: PMC7805582 DOI: 10.1016/j.neuroimage.2020.117314] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2020] [Revised: 07/15/2020] [Accepted: 08/25/2020] [Indexed: 01/02/2023] Open
Abstract
Targeted interrogation of brain networks through invasive brain stimulation has become an increasingly important research tool as well as therapeutic modality. The majority of work with this emerging capability has been focused on open-loop approaches. Closed-loop techniques, however, could improve neuromodulatory therapies and research investigations by optimizing stimulation approaches using neurally informed, personalized targets. Implementing closed-loop systems is challenging particularly with regard to applying consistent strategies considering inter-individual variability. In particular, during intracranial epilepsy monitoring, where much of this research is currently progressing, electrodes are implanted exclusively for clinical reasons. Thus, detection and stimulation sites must be participant- and task-specific. The system must run in parallel with clinical systems, integrate seamlessly with existing setups, and ensure safety features are in place. In other words, a robust, yet flexible platform is required to perform different tests with a single participant and to comply with clinical requirements. In order to investigate closed-loop stimulation for research and therapeutic use, we developed a Closed-Loop System for Electrical Stimulation (CLoSES) that computes neural features which are then used in a decision algorithm to trigger stimulation in near real-time. To summarize CLoSES, intracranial electroencephalography (iEEG) signals are acquired, band-pass filtered, and local and network features are continuously computed. If target features are detected (e.g. above a preset threshold for a certain duration), stimulation is triggered. Not only could the system trigger stimulation while detecting real-time neural features, but we incorporated a pipeline wherein we used an encoder/decoder model to estimate a hidden cognitive state from the neural features. CLoSES provides a flexible platform to implement a variety of closed-loop experimental paradigms in humans. CLoSES has been successfully used with twelve patients implanted with depth electrodes in the epilepsy monitoring unit. During cognitive tasks (N=5), stimulation in closed loop modified a cognitive hidden state on a trial by trial basis. Sleep spindle oscillations (N=6) and sharp transient epileptic activity (N=9) were detected in near real-time, and stimulation was applied during the event or at specified delays (N=3). In addition, we measured the capabilities of the CLoSES system. Total latency was related to the characteristics of the event being detected, with tens of milliseconds for epileptic activity and hundreds of milliseconds for spindle detection. Stepwise latency, the actual duration of each continuous step, was within the specified fixed-step duration and increased linearly with the number of channels and features. We anticipate that probing neural dynamics and interaction between brain states and stimulation responses with CLoSES will lead to novel insights into the mechanism of normal and pathological brain activity, the discovery and evaluation of potential electrographic biomarkers of neurological and psychiatric disorders, and the development and testing of patient-specific stimulation targets and control signals before implanting a therapeutic device.
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Affiliation(s)
- Rina Zelmann
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
| | - Angelique C Paulk
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Ishita Basu
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA; Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA; Department of Neurosurgery, University of Cincinnati, OH, USA
| | - Anish Sarma
- Department of Neuroscience, Brown University, Providence, RI, USA
| | - Ali Yousefi
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA; Department of Computer Science, Worcester Polytechnic Institute, Worcester, MA, USA
| | - Britni Crocker
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Emad Eskandar
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA; Department of Neurosurgery, Albert Einstein College of Medicine, NY, USA
| | - Ziv Williams
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - G Rees Cosgrove
- Department of Neurosurgery, Brigham and Women's Hospital, Boston, MA, USA
| | | | - Darin D Dougherty
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Wilson Truccolo
- Department of Neuroscience, Brown University, Providence, RI, USA
| | - Alik S Widge
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA; Department of Psychiatry, University of Minnesota, MI, USA
| | - Sydney S Cash
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
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17
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Dynamic Clamp on a Windows PC. Methods Mol Biol 2020. [PMID: 33119851 DOI: 10.1007/978-1-0716-0818-0_8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register]
Abstract
Dynamic clamp is a powerful tool for interfacing computational models and real cells. We describe here how to set up and carry out dynamic clamp experiments using a patch clamp amplifier, a National Instruments data acquisition card, and the freely available QuB software that operates on a PC running MS Windows.
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18
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Hilderink S, Devalla HD, Bosch L, Wilders R, Verkerk AO. Ultrarapid Delayed Rectifier K + Channelopathies in Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes. Front Cell Dev Biol 2020; 8:536. [PMID: 32850774 PMCID: PMC7399090 DOI: 10.3389/fcell.2020.00536] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Accepted: 06/08/2020] [Indexed: 12/12/2022] Open
Abstract
Atrial fibrillation (AF) is the most common cardiac arrhythmia. About 5-15% of AF patients have a mutation in a cardiac gene, including mutations in KCNA5, encoding the Kv1.5 α-subunit of the ion channel carrying the atrial-specific ultrarapid delayed rectifier K+ current (IKur). Both loss-of-function and gain-of-function AF-related mutations in KCNA5 are known, but their effects on action potentials (APs) of human cardiomyocytes have been poorly studied. Here, we assessed the effects of wild-type and mutant IKur on APs of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). We found that atrial-like hiPSC-CMs, generated by a retinoic acid-based differentiation protocol, have APs with faster repolarization compared to ventricular-like hiPSC-CMs, resulting in shorter APs with a lower AP plateau. Native IKur, measured as current sensitive to 50 μM 4-aminopyridine, was 1.88 ± 0.49 (mean ± SEM, n = 17) and 0.26 ± 0.26 pA/pF (n = 17) in atrial- and ventricular-like hiPSC-CMs, respectively. In both atrial- and ventricular-like hiPSC-CMs, IKur blockade had minimal effects on AP parameters. Next, we used dynamic clamp to inject various amounts of a virtual IKur, with characteristics as in freshly isolated human atrial myocytes, into 11 atrial-like and 10 ventricular-like hiPSC-CMs, in which native IKur was blocked. Injection of IKur with 100% density shortened the APs, with its effect being strongest on the AP duration at 20% repolarization (APD20) of atrial-like hiPSC-CMs. At IKur densities < 100% (compared to 100%), simulating loss-of-function mutations, significant AP prolongation and raise of plateau were observed. At IKur densities > 100%, simulating gain-of-function mutations, APD20 was decreased in both atrial- and ventricular-like hiPSC-CMs, but only upon a strong increase in IKur. In ventricular-like hiPSC-CMs, lowering of the plateau resulted in AP shortening. We conclude that a decrease in IKur, mimicking loss-of-function mutations, has a stronger effect on the AP of hiPSC-CMs than an increase, mimicking gain-of-function mutations, whereas in ventricular-like hiPSC-CMs such increase results in AP shortening, causing their AP morphology to become more atrial-like. Effects of native IKur modulation on atrial-like hiPSC-CMs are less pronounced than effects of virtual IKur injection because IKur density of atrial-like hiPSC-CMs is substantially smaller than that of freshly isolated human atrial myocytes.
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Affiliation(s)
- Sarah Hilderink
- Department of Medical Biology, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Harsha D Devalla
- Department of Medical Biology, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Leontien Bosch
- Department of Medical Biology, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Ronald Wilders
- Department of Medical Biology, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Arie O Verkerk
- Department of Medical Biology, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.,Department of Experimental Cardiology, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
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19
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Majumder R, De Coster T, Kudryashova N, Verkerk AO, Kazbanov IV, Ördög B, Harlaar N, Wilders R, de Vries AA, Ypey DL, Panfilov AV, Pijnappels DA. Self-restoration of cardiac excitation rhythm by anti-arrhythmic ion channel gating. eLife 2020; 9:55921. [PMID: 32510321 PMCID: PMC7316504 DOI: 10.7554/elife.55921] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Accepted: 06/02/2020] [Indexed: 12/21/2022] Open
Abstract
Homeostatic regulation protects organisms against hazardous physiological changes. However, such regulation is limited in certain organs and associated biological processes. For example, the heart fails to self-restore its normal electrical activity once disturbed, as with sustained arrhythmias. Here we present proof-of-concept of a biological self-restoring system that allows automatic detection and correction of such abnormal excitation rhythms. For the heart, its realization involves the integration of ion channels with newly designed gating properties into cardiomyocytes. This allows cardiac tissue to i) discriminate between normal rhythm and arrhythmia based on frequency-dependent gating and ii) generate an ionic current for termination of the detected arrhythmia. We show in silico, that for both human atrial and ventricular arrhythmias, activation of these channels leads to rapid and repeated restoration of normal excitation rhythm. Experimental validation is provided by injecting the designed channel current for arrhythmia termination in human atrial myocytes using dynamic clamp.
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Affiliation(s)
- Rupamanjari Majumder
- Laboratory of Experimental Cardiology, Department of Cardiology, Leiden University Medical Center, Leiden, Netherlands
| | - Tim De Coster
- Laboratory of Experimental Cardiology, Department of Cardiology, Leiden University Medical Center, Leiden, Netherlands.,Department of Physics and Astronomy, Ghent University, Ghent, Belgium.,Department of Cardiovascular Sciences, KU Leuven, Leuven, Belgium
| | - Nina Kudryashova
- Laboratory of Experimental Cardiology, Department of Cardiology, Leiden University Medical Center, Leiden, Netherlands.,Department of Physics and Astronomy, Ghent University, Ghent, Belgium
| | - Arie O Verkerk
- Department of Medical Biology, Amsterdam UMC, Amsterdam, Netherlands.,Department of Experimental Cardiology, Amsterdam UMC, Amsterdam, Netherlands
| | - Ivan V Kazbanov
- Department of Physics and Astronomy, Ghent University, Ghent, Belgium
| | - Balázs Ördög
- Laboratory of Experimental Cardiology, Department of Cardiology, Leiden University Medical Center, Leiden, Netherlands
| | - Niels Harlaar
- Laboratory of Experimental Cardiology, Department of Cardiology, Leiden University Medical Center, Leiden, Netherlands
| | - Ronald Wilders
- Department of Medical Biology, Amsterdam UMC, Amsterdam, Netherlands
| | - Antoine Af de Vries
- Laboratory of Experimental Cardiology, Department of Cardiology, Leiden University Medical Center, Leiden, Netherlands
| | - Dirk L Ypey
- Laboratory of Experimental Cardiology, Department of Cardiology, Leiden University Medical Center, Leiden, Netherlands
| | - Alexander V Panfilov
- Laboratory of Experimental Cardiology, Department of Cardiology, Leiden University Medical Center, Leiden, Netherlands.,Department of Physics and Astronomy, Ghent University, Ghent, Belgium.,Laboratory of Computational Biology and Medicine, Ural Federal University, Ekaterinburg, Russian Federation
| | - Daniël A Pijnappels
- Laboratory of Experimental Cardiology, Department of Cardiology, Leiden University Medical Center, Leiden, Netherlands
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20
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Shmygol A. Pacing made easy: dynamic clamp promotes quantitative understanding of cardiac autorhythmicity and boosts the development of new pacemakers. Pflugers Arch 2020; 472:549-550. [PMID: 32415462 DOI: 10.1007/s00424-020-02392-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 04/29/2020] [Accepted: 05/04/2020] [Indexed: 11/29/2022]
Affiliation(s)
- Anatoly Shmygol
- Department of Physiology, College of Medicine and Health Sciences, United Arab University, Al Ain, UAE.
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21
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A Systematic Review of Closed-Loop Feedback Techniques in Sleep Studies-Related Issues and Future Directions. SENSORS 2020; 20:s20102770. [PMID: 32414060 PMCID: PMC7285770 DOI: 10.3390/s20102770] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 04/13/2020] [Accepted: 05/10/2020] [Indexed: 01/09/2023]
Abstract
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.
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Gaur N, Ortega F, Verkerk AO, Mengarelli I, Krogh-Madsen T, Christini DJ, Coronel R, Vigmond EJ. Validation of quantitative measure of repolarization reserve as a novel marker of drug induced proarrhythmia. J Mol Cell Cardiol 2020; 145:122-132. [PMID: 32325153 DOI: 10.1016/j.yjmcc.2020.04.019] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Revised: 04/01/2020] [Accepted: 04/14/2020] [Indexed: 11/25/2022]
Abstract
Repolarization reserve, the robustness of a cell to repolarize even when one of the repolarization mechanisms is failing, has been described qualitatively in terms of ionic currents, but has not been quantified by a generic metric that is applicable to drug screening. Prolonged repolarization leading to repolarization failure is highly arrhythmogenic. It may lead to ventricular tachycardia caused by triggered activity from early afterdepolarizations (EADs), or it may promote the occurrence of unidirectional conduction block and reentry. Both types of arrhythmia may deteriorate into ventricular fibrillation (VF) and death. We define the Repolarization Reserve Current (RRC) as the minimum constant current necessary to prevent normal repolarization of a cell. After developing and testing RRC for nine computational ionic models of various species, we applied it experimentally to atrial and ventricular human induced pluripotent stem cell-derived cardiomyocyte (hiPSC-CM), and isolated guinea-pig ventricular cardiomyocytes. In simulations, repolarization was all-or-none with a precise, model-dependent critical RRC, resulting in a discrete shift in the Action Potential Duration (APD) - RRC relation, in the occurrence of EADs and repolarization failure. These data were faithfully reproduced in cellular experiments. RRC allows simple, fast, unambiguous quantification of the arrhythmogenic propensity in cardiac cells of various origins and species without the need of prior knowledge of underlying currents and is suitable for high throughput applications, and personalized medicine applications.
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Affiliation(s)
- Namit Gaur
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, F-33600 Pessac-Bordeaux, France; Univ. Bordeaux, IMB, UMR 5251, F-33400 Talence, France
| | | | - Arie O Verkerk
- Dept. of Medical Biology, Academic Medical Center, Amsterdam, the Netherlands; Dept. of Experimental Cardiology, Academic Medical Center, Amsterdam, the Netherlands
| | - Isabella Mengarelli
- Dept. of Experimental Cardiology, Academic Medical Center, Amsterdam, the Netherlands
| | | | | | - Ruben Coronel
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, F-33600 Pessac-Bordeaux, France; Dept. of Experimental Cardiology, Academic Medical Center, Amsterdam, the Netherlands
| | - Edward J Vigmond
- IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, F-33600 Pessac-Bordeaux, France; Univ. Bordeaux, IMB, UMR 5251, F-33400 Talence, France.
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Tsai SY, Ghazizadeh Z, Wang HJ, Amin S, Ortega FA, Badieyan ZS, Hsu ZT, Gordillo M, Kumar R, Christini DJ, Evans T, Chen S. A human embryonic stem cell reporter line for monitoring chemical-induced cardiotoxicity. Cardiovasc Res 2020; 116:658-670. [PMID: 31173076 PMCID: PMC7252441 DOI: 10.1093/cvr/cvz148] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2018] [Revised: 04/02/2019] [Accepted: 05/28/2019] [Indexed: 12/28/2022] Open
Abstract
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.
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Affiliation(s)
- Su-Yi Tsai
- Department of Life Science, National Taiwan University, Taipei 10617, Taiwan
- Genome and Systems Biology Degree Program, National Taiwan University, Taipei 10617, Taiwan
| | - Zaniar Ghazizadeh
- Department of Surgery, Weill Cornell Medical College, New York, NY 10065, USA
| | - Hou-Jun Wang
- Department of Life Science, National Taiwan University, Taipei 10617, Taiwan
| | - Sadaf Amin
- Department of Surgery, Weill Cornell Medical College, New York, NY 10065, USA
| | - Francis A Ortega
- Physiology, Biophysics, and Systems Biology Graduate Program, Weill Cornell Medical College, New York, NY 10065, USA
| | | | - Zi-Ting Hsu
- Department of Life Science, National Taiwan University, Taipei 10617, Taiwan
| | - Miriam Gordillo
- Department of Surgery, Weill Cornell Medical College, New York, NY 10065, USA
| | - Ritu Kumar
- Department of Surgery, Weill Cornell Medical College, New York, NY 10065, USA
| | - David J Christini
- Physiology, Biophysics, and Systems Biology Graduate Program, Weill Cornell Medical College, New York, NY 10065, USA
- Greenberg Division of Cardiology, Department of Medicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Todd Evans
- Department of Surgery, Weill Cornell Medical College, New York, NY 10065, USA
| | - Shuibing Chen
- Department of Surgery, Weill Cornell Medical College, New York, NY 10065, USA
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Dynamic clamp constructed phase diagram for the Hodgkin and Huxley model of excitability. Proc Natl Acad Sci U S A 2020; 117:3575-3582. [PMID: 32024761 PMCID: PMC7035484 DOI: 10.1073/pnas.1916514117] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Excitability-a threshold-governed transient in transmembrane voltage-is a fundamental physiological process that controls the function of the heart, endocrine, muscles, and neuronal tissues. The 1950s Hodgkin and Huxley explicit formulation provides a mathematical framework for understanding excitability, as the consequence of the properties of voltage-gated sodium and potassium channels. The Hodgkin-Huxley model is more sensitive to parametric variations of protein densities and kinetics than biological systems whose excitability is apparently more robust. It is generally assumed that the model's sensitivity reflects missing functional relations between its parameters or other components present in biological systems. Here we experimentally assembled excitable membranes using the dynamic clamp and voltage-gated potassium ionic channels (Kv1.3) expressed in Xenopus oocytes. We take advantage of a theoretically derived phase diagram, where the phenomenon of excitability is reduced to two dimensions defined as combinations of the Hodgkin-Huxley model parameters, to examine functional relations in the parameter space. Moreover, we demonstrate activity dependence and hysteretic dynamics over the phase diagram due to the impacts of complex slow inactivation kinetics. The results suggest that maintenance of excitability amid parametric variation is a low-dimensional, physiologically tenable control process. In the context of model construction, the results point to a potentially significant gap between high-dimensional models that capture the full measure of complexity displayed by ion channel function and the lower dimensionality that captures physiological function.
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Reyes-Sanchez M, Amaducci R, Elices I, Rodriguez FB, Varona P. Automatic Adaptation of Model Neurons and Connections to Build Hybrid Circuits with Living Networks. Neuroinformatics 2020; 18:377-393. [PMID: 31930463 DOI: 10.1007/s12021-019-09440-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
Hybrid circuits built by creating mono- or bi-directional interactions among living cells and model neurons and synapses are an effective way to study neuron, synaptic and neural network dynamics. However, hybrid circuit technology has been largely underused in the context of neuroscience studies mainly because of the inherent difficulty in implementing and tuning this type of interactions. In this paper, we present a set of algorithms for the automatic adaptation of model neurons and connections in the creation of hybrid circuits with living neural networks. The algorithms perform model time and amplitude scaling, real-time drift adaptation, goal-driven synaptic and model tuning/calibration and also automatic parameter mapping. These algorithms have been implemented in RTHybrid, an open-source library that works with hard real-time constraints. We provide validation examples by building hybrid circuits in a central pattern generator. The results of the validation experiments show that the proposed dynamic adaptation facilitates closed-loop communication among living and artificial model neurons and connections, and contributes to characterize system dynamics, achieve control, automate experimental protocols and extend the lifespan of the preparations.
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Affiliation(s)
- Manuel Reyes-Sanchez
- Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, 28049, Madrid, Spain.
| | - Rodrigo Amaducci
- Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, 28049, Madrid, Spain
| | - Irene Elices
- Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, 28049, Madrid, Spain
| | - Francisco B Rodriguez
- Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, 28049, Madrid, Spain
| | - Pablo Varona
- Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, 28049, Madrid, Spain.
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Darrow DP, O'Brien P, Richner TJ, Netoff TI, Ebbini ES. Reversible neuroinhibition by focused ultrasound is mediated by a thermal mechanism. Brain Stimul 2019; 12:1439-1447. [PMID: 31377096 PMCID: PMC6851480 DOI: 10.1016/j.brs.2019.07.015] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Revised: 07/18/2019] [Accepted: 07/21/2019] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Transcranial focused ultrasound (tFUS) at low intensities has been reported to directly evoke responses and reversibly inhibit function in the central nervous system. While some doubt has been cast on the ability of ultrasound to directly evoke neuronal responses, spatially-restricted transcranial ultrasound has demonstrated consistent, inhibitory effects, but the underlying mechanism of reversible suppression in the central nervous system is not well understood. OBJECTIVE/HYPOTHESIS In this study, we sought to characterize the effect of transcranial, low-intensity, focused ultrasound on the thalamus during somatosensory evoked potentials (SSEP) and investigate the mechanism by modulating the parameters of ultrasound. METHODS TFUS was applied to the ventral posterolateral nucleus of the thalamus of a rodent while electrically stimulating the tibial nerve to induce an SSEP. Thermal changes were also induced through an optical fiber that was image-guided to the same target. RESULTS Focused ultrasound reversibly suppressed SSEPs in a spatially and intensity-dependent manner while remaining independent of duty cycle, peak pressure, or modulation frequency. Suppression was highly correlated and temporally consistent with in vivo temperature changes while producing no pathological changes on histology. Furthermore, stereotactically-guided delivery of thermal energy through an optical fiber produced similar thermal effects and suppression. CONCLUSION We confirm that tFUS predominantly causes neuroinhibition and conclude that the most primary biophysical mechanism is the thermal effect of focused ultrasound.
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Affiliation(s)
- David P Darrow
- Department of Neurosurgery, University of Minnesota, MMC 96, Room D-429, 420 Delaware St SE, Minneapolis, MN, 55455, USA.
| | - Parker O'Brien
- Department of Electrical and Computer Engineering, University of Minnesota, 7-174 Keller Hall, 200 Union Street Se. Minneapolis, MN, 55455, USA.
| | - Thomas J Richner
- Department of Biomedical Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church St. SE, Minneapolis, MN, 55455, USA.
| | - Theoden I Netoff
- Department of Biomedical Engineering, University of Minnesota, 7-105 Nils Hasselmo Hall, 312 Church St. SE, Minneapolis, MN, 55455, USA.
| | - Emad S Ebbini
- Department of Electrical and Computer Engineering, University of Minnesota, 7-174 Keller Hall, 200 Union Street Se. Minneapolis, MN, 55455, USA.
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Murphy M, Buccelli S, Bornat Y, Bundy D, Nudo R, Guggenmos D, Chiappalone M. Improving an open-source commercial system to reliably perform activity-dependent stimulation. J Neural Eng 2019; 16:066022. [PMID: 31315090 PMCID: PMC7703379 DOI: 10.1088/1741-2552/ab3319] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Activity-dependent stimulation (ADS) is designed to strengthen the connections between neuronal circuits and therefore may be a promising tool for promoting neurophysiological reorganization following a brain injury. To successfully perform this technique, two criteria must be met: (1) spikes in the extracellular electrical field potential must be detected accurately at one site of interest, and (2) stimulation pulses generated at fixed (<1 ms jitter), low-latency (<10 ms) intervals relative to each detected spike must be delivered reliably to a second site of interest. Here, we aimed to improve noise rejection in a low-cost commercial system to reliably perform ADS in awake, behaving rats, while maintaining latency requirements. APPROACH We implemented a spike detection state machine on a field-programmable gate array (FPGA). Because the accuracy of spike detection can be heavily reduced in awake and behaving animals due to biological artifacts such as movement and chewing, the state machine tracks candidate spike waveforms, checking them against multiple programmable thresholds and rejecting any spikes that fail to meet a programmed threshold criterion. MAIN RESULTS A series of offline analyses showed that our implementation was able to appropriately trigger stimulation during epochs of biological artifacts with an overall accuracy between 72% and 97%, fixed computational latency of 167 µs, and an algorithmic latency of 300 µs to 800 µs. SIGNIFICANCE Our improvements have been made open-source and are freely available to all scientists working on closed-loop neuroprosthetic devices. Importantly, the improvements are easily incorporated into existing workflows that utilize the Intan Stimulation and Recording Controller.
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Affiliation(s)
- Maxwell Murphy
- Department of Rehabilitation Medicine, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, 66160 KS, United States of America. Bioengineering Graduate Program, University of Kansas, Lawrence, KS, United States of America
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Abstract
OBJECTIVE Close-loop control of brain and behavior will benefit from real-time detection of behavioral events to enable low-latency communication with peripheral devices. In animal experiments, this is typically achieved by using sparsely distributed (embedded) sensors that detect animal presence in select regions of interest. High-speed cameras provide high-density sampling across large arenas, capturing the richness of animal behavior, however, the image processing bottleneck prohibits real-time feedback in the context of rapidly evolving behaviors. APPROACH Here we developed an open-source software, named PolyTouch, to track animal behavior in large arenas and provide rapid close-loop feedback in ~5.7 ms, ie. average latency from the detection of an event to analog stimulus delivery, e.g. auditory tone, TTL pulse, when tracking a single body. This stand-alone software is written in JAVA. The included wrapper for MATLAB provides experimental flexibility for data acquisition, analysis and visualization. MAIN RESULTS As a proof-of-principle application we deployed the PolyTouch for place awareness training. A user-defined portion of the arena was used as a virtual target; visit (or approach) to the target triggered auditory feedback. We show that mice develop awareness to virtual spaces, tend to stay shorter and move faster when they reside in the virtual target zone if their visits are coupled to relatively high stimulus intensity (⩾49 dB). Thus, close-loop presentation of perceived aversive feedback is sufficient to condition mice to avoid virtual targets within the span of a single session (~20 min). SIGNIFICANCE Neuromodulation techniques now allow control of neural activity in a cell-type specific manner in spiking resolution. Using animal behavior to drive closed-loop control of neural activity would help to address the neural basis of behavioral state and environmental context-dependent information processing in the brain.
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Bolus MF, Willats AA, Whitmire CJ, Rozell CJ, Stanley GB. Design strategies for dynamic closed-loop optogenetic neurocontrol in vivo. J Neural Eng 2019; 15:026011. [PMID: 29300002 DOI: 10.1088/1741-2552/aaa506] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
OBJECTIVE Controlling neural activity enables the possibility of manipulating sensory perception, cognitive processes, and body movement, in addition to providing a powerful framework for functionally disentangling the neural circuits that underlie these complex phenomena. Over the last decade, optogenetic stimulation has become an increasingly important and powerful tool for understanding neural circuit function, owing to the ability to target specific cell types and bidirectionally modulate neural activity. To date, most stimulation has been provided in open-loop or in an on/off closed-loop fashion, where previously-determined stimulation is triggered by an event. Here, we describe and demonstrate a design approach for precise optogenetic control of neuronal firing rate modulation using feedback to guide stimulation continuously. APPROACH Using the rodent somatosensory thalamus as an experimental testbed for realizing desired time-varying patterns of firing rate modulation, we utilized a moving average exponential filter to estimate firing rate online from single-unit spiking measured extracellularly. This estimate of instantaneous rate served as feedback for a proportional integral (PI) controller, which was designed during the experiment based on a linear-nonlinear Poisson (LNP) model of the neuronal response to light. MAIN RESULTS The LNP model fit during the experiment enabled robust closed-loop control, resulting in good tracking of sinusoidal and non-sinusoidal targets, and rejection of unmeasured disturbances. Closed-loop control also enabled manipulation of trial-to-trial variability. SIGNIFICANCE Because neuroscientists are faced with the challenge of dissecting the functions of circuit components, the ability to maintain control of a region of interest in spite of changes in ongoing neural activity will be important for disambiguating function within networks. Closed-loop stimulation strategies are ideal for control that is robust to such changes, and the employment of continuous feedback to adjust stimulation in real-time can improve the quality of data collected using optogenetic manipulation.
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Affiliation(s)
- M F Bolus
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, United States of America
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Amaducci R, Reyes-Sanchez M, Elices I, Rodriguez FB, Varona P. RTHybrid: A Standardized and Open-Source Real-Time Software Model Library for Experimental Neuroscience. Front Neuroinform 2019; 13:11. [PMID: 30914940 PMCID: PMC6423167 DOI: 10.3389/fninf.2019.00011] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2018] [Accepted: 02/14/2019] [Indexed: 12/05/2022] Open
Abstract
Closed-loop technologies provide novel ways of online observation, control and bidirectional interaction with the nervous system, which help to study complex non-linear and partially observable neural dynamics. These protocols are often difficult to implement due to the temporal precision required when interacting with biological components, which in many cases can only be achieved using real-time technology. In this paper we introduce RTHybrid (www.github.com/GNB-UAM/RTHybrid), a free and open-source software that includes a neuron and synapse model library to build hybrid circuits with living neurons in a wide variety of experimental contexts. In an effort to encourage the standardization of real-time software technology in neuroscience research, we compared different open-source real-time operating system patches, RTAI, Xenomai 3 and Preempt-RT, according to their performance and usability. RTHybrid has been developed to run over Linux operating systems supporting both Xenomai 3 and Preempt-RT real-time patches, and thus allowing an easy implementation in any laboratory. We report a set of validation tests and latency benchmarks for the construction of hybrid circuits using this library. With this work we want to promote the dissemination of standardized, user-friendly and open-source software tools developed for open- and closed-loop experimental neuroscience.
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Affiliation(s)
- Rodrigo Amaducci
- Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, Madrid, Spain
| | | | | | | | - Pablo Varona
- Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, Madrid, Spain
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Widge AS, Boggess M, Rockhill AP, Mullen A, Sheopory S, Loonis R, Freeman DK, Miller EK. Altering alpha-frequency brain oscillations with rapid analog feedback-driven neurostimulation. PLoS One 2018; 13:e0207781. [PMID: 30517149 PMCID: PMC6281199 DOI: 10.1371/journal.pone.0207781] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Accepted: 11/06/2018] [Indexed: 01/11/2023] Open
Abstract
Oscillations of the brain's local field potential (LFP) may coordinate neural ensembles and brain networks. It has been difficult to causally test this model or to translate its implications into treatments, because there are few reliable ways to alter LFP oscillations. We developed a closed-loop analog circuit to enhance brain oscillations by feeding them back into cortex through phase-locked transcranial electrical stimulation. We tested the system in a rhesus macaque with chronically implanted electrode arrays, targeting 8-15 Hz (alpha) oscillations. Ten seconds of stimulation increased alpha oscillatory power for up to 1 second after stimulation offset. In contrast, open-loop stimulation decreased alpha power. There was no effect in the neighboring 15-30 Hz (beta) LFP rhythm or on a neighboring array that did not participate in closed-loop feedback. Analog closed-loop neurostimulation might thus be a useful strategy for altering brain oscillations, both for basic research and the treatment of neuro-psychiatric disease.
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Affiliation(s)
- Alik S. Widge
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Matthew Boggess
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Alexander P. Rockhill
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Andrew Mullen
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Shivani Sheopory
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- College of Engineering, Boston University, Boston, Massachusetts, United States of America
| | - Roman Loonis
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Daniel K. Freeman
- The Charles Stark Draper Laboratory, Inc., Cambridge, Massachusetts, United States of America
| | - Earl K. Miller
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
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Ciliberti D, Michon F, Kloosterman F. Real-time classification of experience-related ensemble spiking patterns for closed-loop applications. eLife 2018; 7:36275. [PMID: 30373716 PMCID: PMC6207426 DOI: 10.7554/elife.36275] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Accepted: 09/27/2018] [Indexed: 02/06/2023] Open
Abstract
Communication in neural circuits across the cortex is thought to be mediated by spontaneous temporally organized patterns of population activity lasting ~50 –200 ms. Closed-loop manipulations have the unique power to reveal direct and causal links between such patterns and their contribution to cognition. Current brain–computer interfaces, however, are not designed to interpret multi-neuronal spiking patterns at the millisecond timescale. To bridge this gap, we developed a system for classifying ensemble patterns in a closed-loop setting and demonstrated its application in the online identification of hippocampal neuronal replay sequences in the rat. Our system decodes multi-neuronal patterns at 10 ms resolution, identifies within 50 ms experience-related patterns with over 70% sensitivity and specificity, and classifies their content with 95% accuracy. This technology scales to high-count electrode arrays and will help to shed new light on the contribution of internally generated neural activity to coordinated neural assembly interactions and cognition.
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Affiliation(s)
- Davide Ciliberti
- Neuro-Electronics Research Flanders, Leuven, Belgium.,Brain and Cognition, KU Leuven, Leuven, Belgium.,VIB, Leuven, Belgium
| | - Frédéric Michon
- Neuro-Electronics Research Flanders, Leuven, Belgium.,Brain and Cognition, KU Leuven, Leuven, Belgium.,VIB, Leuven, Belgium
| | - Fabian Kloosterman
- Neuro-Electronics Research Flanders, Leuven, Belgium.,Brain and Cognition, KU Leuven, Leuven, Belgium.,VIB, Leuven, Belgium.,imec, Leuven, Belgium
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Correlation between cortical beta power and gait speed is suppressed in a parkinsonian model, but restored by therapeutic deep brain stimulation. Neurobiol Dis 2018; 117:137-148. [DOI: 10.1016/j.nbd.2018.05.013] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2017] [Revised: 05/03/2018] [Accepted: 05/29/2018] [Indexed: 12/23/2022] Open
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Matsumura R, Yamamoto H, Hayakawa T, Katsurabayashi S, Niwano M, Hirano-Iwata A. Dependence and Homeostasis of Membrane Impedance on Cell Morphology in Cultured Hippocampal Neurons. Sci Rep 2018; 8:9905. [PMID: 29967389 PMCID: PMC6028398 DOI: 10.1038/s41598-018-28232-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2018] [Accepted: 06/20/2018] [Indexed: 11/09/2022] Open
Abstract
The electrical impedance of cell membranes is important for excitable cells, such as neurons, because it strongly influences the amount of membrane potential change upon a flow of ionic current across the membrane. Here, we report on an investigation of how neuronal morphology affects membrane impedance of cultured hippocampal neurons. Microfabricated substrates with patterned scaffolding molecules were used to restrict the neurite growth of hippocampal neurons, and the impedance was measured via whole-cell patch-clamp recording under the inhibition of voltage-dependent ion channels. Membrane impedance was found to depend inversely on the dendrite length and soma area, as would be expected from the fact that its electrical property is equivalent to a parallel RC circuit. Moreover, we found that in biological neurons, the membrane impedance is homeostatically regulated to impede changes in the membrane area. The findings provide direct evidence on cell-autonomous regulation of neuronal impedance and pave the way towards elucidating the mechanism responsible for the resilience of biological neuronal networks.
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Affiliation(s)
- Ryosuke Matsumura
- Research Institute of Electrical Communication, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai, 980-8577, Japan
| | - Hideaki Yamamoto
- Frontier Research Institute for Interdisciplinary Sciences, Tohoku University, 6-3 Aramaki-aza Aoba, Aoba-ku, Sendai, 980-8578, Japan.
- WPI-AIMR, Tohoku University, Sendai, Japan.
| | - Takeshi Hayakawa
- Research Institute of Electrical Communication, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai, 980-8577, Japan
| | - Shutaro Katsurabayashi
- Faculty of Pharmaceutical Sciences, Fukuoka University, 8-19-1 Nanakuma, Jonan-ku, Fukuoka, 814-0180, Japan
| | - Michio Niwano
- Research Institute of Electrical Communication, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai, 980-8577, Japan
- Kansei Fukushi Research Institute, Tohoku Fukushi University, 6-149-1 Kunimigaoka, Aoba-ku, Sendai, 989-3201, Japan
| | - Ayumi Hirano-Iwata
- Research Institute of Electrical Communication, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai, 980-8577, Japan
- WPI-Advanced Institute for Materials Research (WPI-AIMR), Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai, 980-8577, Japan
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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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Perrier R, Pirog A, Jaffredo M, Gaitan J, Catargi B, Renaud S, Raoux M, Lang J. Bioelectronic organ-based sensor for microfluidic real-time analysis of the demand in insulin. Biosens Bioelectron 2018; 117:253-259. [PMID: 29909196 DOI: 10.1016/j.bios.2018.06.015] [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: 05/18/2018] [Revised: 06/04/2018] [Accepted: 06/06/2018] [Indexed: 12/31/2022]
Abstract
On-line and real-time analysis of micro-organ activity permits to use the endogenous analytical power of cellular signal transduction algorithms as biosensors. We have developed here such a sensor using only a few pancreatic endocrine islets and the avoidance of transgenes or chemical probes reduces bias and procures general usage. Nutrient and hormone-induced changes in islet ion fluxes through channels provide the first integrative read-out of micro-organ activity. Using extracellular electrodes we captured this read-out non-invasively as slow potentials which reflect glucose concentration-dependent (3-15 mM) micro-organ activation and coupling. Custom-made PDMS-based microfluidics with platinum black micro-electrode arrays required only some tens of islets and functioned at flow rates of 1-10 µl/min which are compatible with microdialysis. We developed hardware solutions for on-line real-time analysis on a reconfigurable Field-Programmable Gate Array (FPGA) that offered resource-efficient architecture and storage of intermediary processing stages. Moreover, real-time adaptive and reconfigurable algorithms accounted for signal disparities and noise distribution. Based on islet slow potentials, this integrated set-up allowed within less than 40 μs the discrimination and precise automatic ranking of small increases (2 mM steps) of glucose concentrations in real time and within the physiological glucose range. This approach shall permit further development in continuous monitoring of the demand for insulin in type 1 diabetes as well as monitoring of organs-on-chip or maturation of stem-cell derived islets.
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Affiliation(s)
- R Perrier
- Laboratoire de Chimie et Biologie des Membranes et des Nano-Objets (CBMN), UMR CNRS 5248, Univ. Bordeaux, 18 Av Geoffroy St Hilaire, 33600 Pessac, France
| | - A Pirog
- Laboratoire d'Intégration du Matériau au Système (IMS), UMR CNRS 5218, Univ. Bordeaux, Bordeaux INP, 33400 Talence, France
| | - M Jaffredo
- Laboratoire de Chimie et Biologie des Membranes et des Nano-Objets (CBMN), UMR CNRS 5248, Univ. Bordeaux, 18 Av Geoffroy St Hilaire, 33600 Pessac, France
| | - J Gaitan
- Laboratoire de Chimie et Biologie des Membranes et des Nano-Objets (CBMN), UMR CNRS 5248, Univ. Bordeaux, 18 Av Geoffroy St Hilaire, 33600 Pessac, France
| | - B Catargi
- Laboratoire de Chimie et Biologie des Membranes et des Nano-Objets (CBMN), UMR CNRS 5248, Univ. Bordeaux, 18 Av Geoffroy St Hilaire, 33600 Pessac, France; Hôpital St André, Bordeaux University Hospital, Univ. Bordeaux, 1 rue Jean Burguet, 33000 Bordeaux, France
| | - S Renaud
- Laboratoire d'Intégration du Matériau au Système (IMS), UMR CNRS 5218, Univ. Bordeaux, Bordeaux INP, 33400 Talence, France
| | - M Raoux
- Laboratoire de Chimie et Biologie des Membranes et des Nano-Objets (CBMN), UMR CNRS 5248, Univ. Bordeaux, 18 Av Geoffroy St Hilaire, 33600 Pessac, France
| | - J Lang
- Laboratoire de Chimie et Biologie des Membranes et des Nano-Objets (CBMN), UMR CNRS 5248, Univ. Bordeaux, 18 Av Geoffroy St Hilaire, 33600 Pessac, France.
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Esch L, Sun L, Klüber V, Lew S, Baumgarten D, Grant PE, Okada Y, Haueisen J, Hämäläinen MS, Dinh C. MNE Scan: Software for real-time processing of electrophysiological data. J Neurosci Methods 2018; 303:55-67. [PMID: 29621570 PMCID: PMC5940556 DOI: 10.1016/j.jneumeth.2018.03.020] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2017] [Revised: 03/31/2018] [Accepted: 03/31/2018] [Indexed: 12/29/2022]
Abstract
BACKGROUND Magnetoencephalography (MEG) and Electroencephalography (EEG) are noninvasive techniques to study the electrophysiological activity of the human brain. Thus, they are well suited for real-time monitoring and analysis of neuronal activity. Real-time MEG/EEG data processing allows adjustment of the stimuli to the subject's responses for optimizing the acquired information especially by providing dynamically changing displays to enable neurofeedback. NEW METHOD We introduce MNE Scan, an acquisition and real-time analysis software based on the multipurpose software library MNE-CPP. MNE Scan allows the development and application of acquisition and novel real-time processing methods in both research and clinical studies. The MNE Scan development follows a strict software engineering process to enable approvals required for clinical software. RESULTS We tested the performance of MNE Scan in several device-independent use cases, including, a clinical epilepsy study, real-time source estimation, and Brain Computer Interface (BCI) application. COMPARISON WITH EXISTING METHOD(S) Compared to existing tools we propose a modular software considering clinical software requirements expected by certification authorities. At the same time the software is extendable and freely accessible. CONCLUSION We conclude that MNE Scan is the first step in creating a device-independent open-source software to facilitate the transition from basic neuroscience research to both applied sciences and clinical applications.
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Affiliation(s)
- Lorenz Esch
- Massachusetts General Hospital, Massachusetts Institute of Technology, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, 149 13th St., Charlestown, MA 02129, USA; Boston Children's Hospital, Division of Newborn Medicine, Department of Medicine, Harvard Medical School, Boston, MA 02115 USA; Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, Gustav-Kirchhoff- Str. 2, 98693 Ilmenau, Germany.
| | - Limin Sun
- Massachusetts General Hospital, Massachusetts Institute of Technology, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, 149 13th St., Charlestown, MA 02129, USA; Boston Children's Hospital, Division of Newborn Medicine, Department of Medicine, Harvard Medical School, Boston, MA 02115 USA
| | - Viktor Klüber
- Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, Gustav-Kirchhoff- Str. 2, 98693 Ilmenau, Germany; Institute of Nuclear and Energy Technologies, KIT - Karlsruher Institut für Technologie, 76344 Eggenstein-Leopoldshafen, Germany
| | - Seok Lew
- Massachusetts General Hospital, Massachusetts Institute of Technology, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, 149 13th St., Charlestown, MA 02129, USA; Department of Engineering, Olivet Nazarene University, 1 University Ave, Bourbonnais, 60914 IL, USA
| | - Daniel Baumgarten
- Institute of Electrical and Biomedical Engineering, UMIT - University of Health Sciences, Medical Informatics and Technology, 6060 Hall in Tirol, Austria
| | - P Ellen Grant
- Boston Children's Hospital, Division of Newborn Medicine, Department of Medicine, Harvard Medical School, Boston, MA 02115 USA; Boston Children's Hospital, Division of Neuroradiology, Department of Radiology, Harvard Medical School, Boston, MA 02115 USA
| | - Yoshio Okada
- Boston Children's Hospital, Division of Newborn Medicine, Department of Medicine, Harvard Medical School, Boston, MA 02115 USA
| | - Jens Haueisen
- Institute of Biomedical Engineering and Informatics, Technische Universität Ilmenau, Gustav-Kirchhoff- Str. 2, 98693 Ilmenau, Germany; Biomagnetic Center, Clinic for Neurology, Jena University Hospital, Erlanger Allee 101, 07743 Jena, Germany
| | - Matti S Hämäläinen
- Massachusetts General Hospital, Massachusetts Institute of Technology, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, 149 13th St., Charlestown, MA 02129, USA; Boston Children's Hospital, Division of Newborn Medicine, Department of Medicine, Harvard Medical School, Boston, MA 02115 USA
| | - Christoph Dinh
- Massachusetts General Hospital, Massachusetts Institute of Technology, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, 149 13th St., Charlestown, MA 02129, USA; Boston Children's Hospital, Division of Newborn Medicine, Department of Medicine, Harvard Medical School, Boston, MA 02115 USA
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Ortega FA, Grandi E, Krogh-Madsen T, Christini DJ. Applications of Dynamic Clamp to Cardiac Arrhythmia Research: Role in Drug Target Discovery and Safety Pharmacology Testing. Front Physiol 2018; 8:1099. [PMID: 29354069 PMCID: PMC5758594 DOI: 10.3389/fphys.2017.01099] [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: 09/01/2017] [Accepted: 12/13/2017] [Indexed: 12/31/2022] Open
Abstract
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.
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Affiliation(s)
- Francis A Ortega
- Physiology, Biophysics, and Systems Biology Graduate Program, Weill Cornell Graduate School of Medical Sciences, New York, NY, United States
| | - Eleonora Grandi
- Department of Pharmacology, University of California, Davis, Davis, CA, United States
| | - Trine Krogh-Madsen
- Greenberg Division of Cardiology, Weill Cornell Medical College, New York, NY, United States
| | - David J Christini
- Physiology, Biophysics, and Systems Biology Graduate Program, Weill Cornell Graduate School of Medical Sciences, New York, NY, United States.,Greenberg Division of Cardiology, Weill Cornell Medical College, New York, NY, United States
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Patel YA, Kim BS, Butera RJ. Kilohertz Electrical Stimulation Nerve Conduction Block: Effects of Electrode Material. IEEE Trans Neural Syst Rehabil Eng 2018; 26:11-17. [DOI: 10.1109/tnsre.2017.2737954] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Lustenberger C, Patel YA, Alagapan S, Page JM, Price B, Boyle MR, Fröhlich F. High-density EEG characterization of brain responses to auditory rhythmic stimuli during wakefulness and NREM sleep. Neuroimage 2017; 169:57-68. [PMID: 29217404 DOI: 10.1016/j.neuroimage.2017.12.007] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2017] [Revised: 11/13/2017] [Accepted: 12/02/2017] [Indexed: 01/12/2023] Open
Abstract
Auditory rhythmic sensory stimulation modulates brain oscillations by increasing phase-locking to the temporal structure of the stimuli and by increasing the power of specific frequency bands, resulting in Auditory Steady State Responses (ASSR). The ASSR is altered in different diseases of the central nervous system such as schizophrenia. However, in order to use the ASSR as biological markers for disease states, it needs to be understood how different vigilance states and underlying brain activity affect the ASSR. Here, we compared the effects of auditory rhythmic stimuli on EEG brain activity during wake and NREM sleep, investigated the influence of the presence of dominant sleep rhythms on the ASSR, and delineated the topographical distribution of these modulations. Participants (14 healthy males, 20-33 years) completed on the same day a 60 min nap session and two 30 min wakefulness sessions (before and after the nap). During these sessions, amplitude modulated (AM) white noise auditory stimuli at different frequencies were applied. High-density EEG was continuously recorded and time-frequency analyses were performed to assess ASSR during wakefulness and NREM periods. Our analysis revealed that depending on the electrode location, stimulation frequency applied and window/frequencies analysed the ASSR was significantly modulated by sleep pressure (before and after sleep), vigilance state (wake vs. NREM sleep), and the presence of slow wave activity and sleep spindles. Furthermore, AM stimuli increased spindle activity during NREM sleep but not during wakefulness. Thus, (1) electrode location, sleep history, vigilance state and ongoing brain activity needs to be carefully considered when investigating ASSR and (2) auditory rhythmic stimuli during sleep might represent a powerful tool to boost sleep spindles.
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Affiliation(s)
- Caroline Lustenberger
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yogi A Patel
- Bioengineering Graduate Program, Georgia Institute of Technology, Atlanta, GA 30332, USA; Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA 30332, USA
| | - Sankaraleengam Alagapan
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jessica M Page
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Betsy Price
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Michael R Boyle
- Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
| | - Flavio Fröhlich
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA; Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA; Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
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Hazan H, Ziv NE. Closed Loop Experiment Manager (CLEM)-An Open and Inexpensive Solution for Multichannel Electrophysiological Recordings and Closed Loop Experiments. Front Neurosci 2017; 11:579. [PMID: 29093659 PMCID: PMC5651259 DOI: 10.3389/fnins.2017.00579] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Accepted: 10/03/2017] [Indexed: 11/13/2022] Open
Abstract
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.
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Affiliation(s)
- Hananel Hazan
- Faculty of Medicine, Technion, Haifa, Israel.,Network Biology Research Laboratories, Lorry Lokey Center for Life Sciences and Engineering, Technion, Haifa, Israel
| | - Noam E Ziv
- Faculty of Medicine, Technion, Haifa, Israel.,Network Biology Research Laboratories, Lorry Lokey Center for Life Sciences and Engineering, Technion, Haifa, Israel
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Patel YA, Kim BS, Rountree WS, Butera RJ. Kilohertz Electrical Stimulation Nerve Conduction Block: Effects of Electrode Surface Area. IEEE Trans Neural Syst Rehabil Eng 2017; 25:1906-1916. [DOI: 10.1109/tnsre.2017.2684161] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Correction: Hard real-time closed-loop electrophysiology with the Real-Time eXperiment Interface (RTXI). PLoS Comput Biol 2017; 13:e1005656. [PMID: 28715502 PMCID: PMC5513696 DOI: 10.1371/journal.pcbi.1005656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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