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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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Lareo A, Forlim CG, Pinto RD, Varona P, Rodriguez FDB. Temporal Code-Driven Stimulation: Definition and Application to Electric Fish Signaling. Front Neuroinform 2016; 10:41. [PMID: 27766078 PMCID: PMC5052257 DOI: 10.3389/fninf.2016.00041] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2016] [Accepted: 09/21/2016] [Indexed: 11/18/2022] Open
Abstract
Closed-loop activity-dependent stimulation is a powerful methodology to assess information processing in biological systems. In this context, the development of novel protocols, their implementation in bioinformatics toolboxes and their application to different description levels open up a wide range of possibilities in the study of biological systems. We developed a methodology for studying biological signals representing them as temporal sequences of binary events. A specific sequence of these events (code) is chosen to deliver a predefined stimulation in a closed-loop manner. The response to this code-driven stimulation can be used to characterize the system. This methodology was implemented in a real time toolbox and tested in the context of electric fish signaling. We show that while there are codes that evoke a response that cannot be distinguished from a control recording without stimulation, other codes evoke a characteristic distinct response. We also compare the code-driven response to open-loop stimulation. The discussed experiments validate the proposed methodology and the software toolbox.
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Affiliation(s)
- Angel Lareo
- Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politécnica superior, Universidad Autónoma de MadridMadrid, Spain
| | - Caroline G. Forlim
- Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent UniversityGhent, Belgium
| | - Reynaldo D. Pinto
- Laboratory of Neurodynamics/Neurobiophysics, Department of Physics and Interdisciplinary Sciences, Institute of Physics of São Carlos, Universidade de São PauloSão Paulo, Brazil
| | - Pablo Varona
- Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politécnica superior, Universidad Autónoma de MadridMadrid, Spain
| | - Francisco de Borja Rodriguez
- Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politécnica superior, Universidad Autónoma de MadridMadrid, Spain
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Fernandez-Vargas J, Pfaff HU, Rodríguez FB, Varona P. Assisted closed-loop optimization of SSVEP-BCI efficiency. Front Neural Circuits 2013; 7:27. [PMID: 23443214 PMCID: PMC3580891 DOI: 10.3389/fncir.2013.00027] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2012] [Accepted: 02/06/2013] [Indexed: 11/23/2022] Open
Abstract
We designed a novel assisted closed-loop optimization protocol to improve the efficiency of brain-computer interfaces (BCI) based on steady state visually evoked potentials (SSVEP). In traditional paradigms, the control over the BCI-performance completely depends on the subjects' ability to learn from the given feedback cues. By contrast, in the proposed protocol both the subject and the machine share information and control over the BCI goal. Generally, the innovative assistance consists in the delivery of online information together with the online adaptation of BCI stimuli properties. In our case, this adaptive optimization process is realized by (1) a closed-loop search for the best set of SSVEP flicker frequencies and (2) feedback of actual SSVEP magnitudes to both the subject and the machine. These closed-loop interactions between subject and machine are evaluated in real-time by continuous measurement of their efficiencies, which are used as online criteria to adapt the BCI control parameters. The proposed protocol aims to compensate for variability in possibly unknown subjects' state and trait dimensions. In a study with N = 18 subjects, we found significant evidence that our protocol outperformed classic SSVEP-BCI control paradigms. Evidence is presented that it takes indeed into account interindividual variabilities: e.g., under the new protocol, baseline resting state EEG measures predict subjects' BCI performances. This paper illustrates the promising potential of assisted closed-loop protocols in BCI systems. Probably their applicability might be expanded to innovative uses, e.g., as possible new diagnostic/therapeutic tools for clinical contexts and as new paradigms for basic research.
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Affiliation(s)
- Jacobo Fernandez-Vargas
- Grupo de Neurocomputación Biológica, Departamento de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid Madrid, Spain
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Chamorro P, Muñiz C, Levi R, Arroyo D, Rodríguez FB, Varona P. Generalization of the dynamic clamp concept in neurophysiology and behavior. PLoS One 2012; 7:e40887. [PMID: 22829895 PMCID: PMC3400657 DOI: 10.1371/journal.pone.0040887] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2012] [Accepted: 06/14/2012] [Indexed: 11/19/2022] Open
Abstract
The idea of closed-loop interaction in in vitro and in vivo electrophysiology has been successfully implemented in the dynamic clamp concept strongly impacting the research of membrane and synaptic properties of neurons. In this paper we show that this concept can be easily generalized to build other kinds of closed-loop protocols beyond (or in addition to) electrical stimulation and recording in neurophysiology and behavioral studies for neuroethology. In particular, we illustrate three different examples of goal-driven real-time closed-loop interactions with drug microinjectors, mechanical devices and video event driven stimulation. Modern activity-dependent stimulation protocols can be used to reveal dynamics (otherwise hidden under traditional stimulation techniques), achieve control of natural and pathological states, induce learning, bridge between disparate levels of analysis and for a further automation of experiments. We argue that closed-loop interaction calls for novel real time analysis, prediction and control tools and a new perspective for designing stimulus-response experiments, which can have a large impact in neuroscience research.
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Affiliation(s)
- Pablo Chamorro
- Grupo de Neurocomputación Biológica, Dpto. de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, Madrid, Spain
| | - Carlos Muñiz
- Grupo de Neurocomputación Biológica, Dpto. de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, Madrid, Spain
| | - Rafael Levi
- Grupo de Neurocomputación Biológica, Dpto. de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, Madrid, Spain
- Department of Neurobiology and Behavior, University of California Irvine, Irvine, California, United States of America
| | - David Arroyo
- Grupo de Neurocomputación Biológica, Dpto. de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, Madrid, Spain
| | - Francisco B. Rodríguez
- Grupo de Neurocomputación Biológica, Dpto. de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, Madrid, Spain
| | - Pablo Varona
- Grupo de Neurocomputación Biológica, Dpto. de Ingeniería Informática, Escuela Politécnica Superior, Universidad Autónoma de Madrid, Madrid, Spain
- * E-mail:
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Muñiz C, Forlim CG, Guariento RT, Pinto RD, Rodríguez FB, Varona P. Online video tracking for activity-dependent stimulation in neuroethology. BMC Neurosci 2011. [PMCID: PMC3240476 DOI: 10.1186/1471-2202-12-s1-p358] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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Abstract
Dynamic clamp is a powerful method that allows the introduction of artificial electrical components into target cells to simulate ionic conductances and synaptic inputs. This method is based on a fast cycle of measuring the membrane potential of a cell, calculating the current of a desired simulated component using an appropriate model and injecting this current into the cell. Here we present a dynamic clamp protocol using free, fully integrated, open-source software (StdpC, for spike timing-dependent plasticity clamp). Use of this protocol does not require specialist hardware, costly commercial software, experience in real-time operating systems or a strong programming background. The software enables the configuration and operation of a wide range of complex and fully automated dynamic clamp experiments through an intuitive and powerful interface with a minimal initial lead time of a few hours. After initial configuration, experimental results can be generated within minutes of establishing cell recording.
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Affiliation(s)
- Ildikó Kemenes
- School of Life Sciences, University of Sussex, Brighton, UK,
| | - Vincenzo Marra
- School of Life Sciences, University of Sussex, Brighton, UK,
| | | | - Dávid Samu
- School of Informatics, University of Sussex, Brighton, UK,
| | - Kevin Staras
- School of Life Sciences, University of Sussex, Brighton, UK,
| | - György Kemenes
- School of Life Sciences, University of Sussex, Brighton, UK,
| | - Thomas Nowotny
- School of Informatics, University of Sussex, Brighton, UK, , web: http://www.sussex.ac.uk/informatics/tnowotny, corresponding author, telephone +44-1273-601652, fax +44-1273-877873
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Muñiz C, Rodríguez FDB, Varona P. RTBiomanager: a software platform to expand the applications of real-time technology in neuroscience. BMC Neurosci 2009. [DOI: 10.1186/1471-2202-10-s1-p49] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Chamorro P, Levi R, Rodríguez FB, Pinto RD, Varona P. Real-time activity-dependent drug microinjection. BMC Neurosci 2009. [DOI: 10.1186/1471-2202-10-s1-p296] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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