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Farkhondeh Tale Navi F, Heysieattalab S, Ramanathan DS, Raoufy MR, Nazari MA. Closed-loop Modulation of the Self-regulating Brain: A Review on Approaches, Emerging Paradigms, and Experimental Designs. Neuroscience 2021; 483:104-126. [PMID: 34902494 DOI: 10.1016/j.neuroscience.2021.12.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 11/30/2021] [Accepted: 12/06/2021] [Indexed: 11/27/2022]
Abstract
Closed-loop approaches, setups, and experimental designs have been applied within the field of neuroscience to enhance the understanding of basic neurophysiology principles (closed-loop neuroscience; CLNS) and to develop improved procedures for modulating brain circuits and networks for clinical purposes (closed-loop neuromodulation; CLNM). The contents of this review are thus arranged into the following sections. First, we describe basic research findings that have been made using CLNS. Next, we provide an overview of the application, rationale, and therapeutic aspects of CLNM for clinical purposes. Finally, we summarize methodological concerns and critics in clinical practice of neurofeedback and novel applications of closed-loop perspective and techniques to improve and optimize its experiments. Moreover, we outline the theoretical explanations and experimental ideas to test animal models of neurofeedback and discuss technical issues and challenges associated with implementing closed-loop systems. We hope this review is helpful for both basic neuroscientists and clinical/ translationally-oriented scientists interested in applying closed-loop methods to improve mental health and well-being.
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Affiliation(s)
- Farhad Farkhondeh Tale Navi
- Department of Cognitive Neuroscience, Faculty of Education and Psychology, University of Tabriz, Tabriz, Iran
| | - Soomaayeh Heysieattalab
- Department of Cognitive Neuroscience, Faculty of Education and Psychology, University of Tabriz, Tabriz, Iran
| | | | - Mohammad Reza Raoufy
- Department of Physiology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Mohammad Ali Nazari
- Department of Cognitive Neuroscience, Faculty of Education and Psychology, University of Tabriz, Tabriz, Iran; Department of Neuroscience, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran, Iran.
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2
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Saha S, Mamun KA, Ahmed K, Mostafa R, Naik GR, Darvishi S, Khandoker AH, Baumert M. Progress in Brain Computer Interface: Challenges and Opportunities. Front Syst Neurosci 2021; 15:578875. [PMID: 33716680 PMCID: PMC7947348 DOI: 10.3389/fnsys.2021.578875] [Citation(s) in RCA: 82] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 01/06/2021] [Indexed: 12/13/2022] Open
Abstract
Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree of freedom either by strengthening or by substituting human peripheral working capacity and have potential applications in various fields such as rehabilitation, affective computing, robotics, gaming, and neuroscience. Significant research efforts on a global scale have delivered common platforms for technology standardization and help tackle highly complex and non-linear brain dynamics and related feature extraction and classification challenges. Time-variant psycho-neurophysiological fluctuations and their impact on brain signals impose another challenge for BCI researchers to transform the technology from laboratory experiments to plug-and-play daily life. This review summarizes state-of-the-art progress in the BCI field over the last decades and highlights critical challenges.
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Affiliation(s)
- Simanto Saha
- School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA, Australia
- Department of Electrical and Electronic Engineering, United International University, Dhaka, Bangladesh
| | - Khondaker A. Mamun
- Advanced Intelligent Multidisciplinary Systems (AIMS) Lab, Department of Computer Science and Engineering, United International University, Dhaka, Bangladesh
| | - Khawza Ahmed
- Department of Electrical and Electronic Engineering, United International University, Dhaka, Bangladesh
| | - Raqibul Mostafa
- Department of Electrical and Electronic Engineering, United International University, Dhaka, Bangladesh
| | - Ganesh R. Naik
- Adelaide Institute for Sleep Health, College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia
| | - Sam Darvishi
- School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA, Australia
| | - Ahsan H. Khandoker
- Healthcare Engineering Innovation Center, Department of Biomedical Engineering, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates
| | - Mathias Baumert
- School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA, Australia
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3
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Yang GZ, Bellingham J, Dupont PE, Fischer P, Floridi L, Full R, Jacobstein N, Kumar V, McNutt M, Merrifield R, Nelson BJ, Scassellati B, Taddeo M, Taylor R, Veloso M, Wang ZL, Wood R. The grand challenges of Science Robotics. Sci Robot 2021; 3:3/14/eaar7650. [PMID: 33141701 DOI: 10.1126/scirobotics.aar7650] [Citation(s) in RCA: 366] [Impact Index Per Article: 122.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2017] [Accepted: 01/12/2018] [Indexed: 12/17/2022]
Abstract
One of the ambitions of Science Robotics is to deeply root robotics research in science while developing novel robotic platforms that will enable new scientific discoveries. Of our 10 grand challenges, the first 7 represent underpinning technologies that have a wider impact on all application areas of robotics. For the next two challenges, we have included social robotics and medical robotics as application-specific areas of development to highlight the substantial societal and health impacts that they will bring. Finally, the last challenge is related to responsible innovation and how ethics and security should be carefully considered as we develop the technology further.
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Affiliation(s)
- Guang-Zhong Yang
- Hamlyn Centre for Robotic Surgery, Imperial College London, London, UK.
| | - Jim Bellingham
- Center for Marine Robotics, Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA
| | - Pierre E Dupont
- Department of Cardiovascular Surgery, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Peer Fischer
- Institute of Physical Chemistry, University of Stuttgart, Stuttgart, Germany.,Micro, Nano, and Molecular Systems Laboratory, Max Planck Institute for Intelligent Systems, Stuttgart, Germany
| | - Luciano Floridi
- Centre for Practical Ethics, Faculty of Philosophy, University of Oxford, Oxford, UK.,Digital Ethics Lab, Oxford Internet Institute, University of Oxford, Oxford, UK.,Department of Computer Science, University of Oxford, Oxford, UK.,Data Ethics Group, Alan Turing Institute, London, UK.,Department of Economics, American University, Washington, DC 20016, USA
| | - Robert Full
- Department of Integrative Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Neil Jacobstein
- Singularity University, NASA Research Park, Moffett Field, CA 94035, USA.,MediaX, Stanford University, Stanford, CA 94305, USA
| | - Vijay Kumar
- Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Marcia McNutt
- National Academy of Sciences, Washington, DC 20418, USA
| | - Robert Merrifield
- Hamlyn Centre for Robotic Surgery, Imperial College London, London, UK
| | - Bradley J Nelson
- Institute of Robotics and Intelligent Systems, Department of Mechanical and Process Engineering, ETH Zürich, Zurich, Switzerland
| | - Brian Scassellati
- Department of Computer Science, Yale University, New Haven, CT 06520, USA.,Department Mechanical Engineering and Materials Science, Yale University, New Haven, CT 06520, USA
| | - Mariarosaria Taddeo
- Digital Ethics Lab, Oxford Internet Institute, University of Oxford, Oxford, UK.,Department of Computer Science, University of Oxford, Oxford, UK.,Data Ethics Group, Alan Turing Institute, London, UK
| | - Russell Taylor
- Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Manuela Veloso
- Machine Learning Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Zhong Lin Wang
- School of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Robert Wood
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.,Wyss Institute for Biologically Inspired Engineering, Harvard University, Cambridge, MA 02138, USA
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4
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5-Methoxy-N,N-dimethyltryptamine: An Ego-Dissolving Endogenous Neurochemical Catalyst of Creativity. ACTA ACUST UNITED AC 2019. [DOI: 10.1007/s41470-019-00063-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
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5
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Hammer J, Pistohl T, Fischer J, Kršek P, Tomášek M, Marusič P, Schulze-Bonhage A, Aertsen A, Ball T. Predominance of Movement Speed Over Direction in Neuronal Population Signals of Motor Cortex: Intracranial EEG Data and A Simple Explanatory Model. Cereb Cortex 2016; 26:2863-81. [PMID: 26984895 PMCID: PMC4869816 DOI: 10.1093/cercor/bhw033] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
How neuronal activity of motor cortex is related to movement is a central topic in motor neuroscience. Motor-cortical single neurons are more closely related to hand movement velocity than speed, that is, the magnitude of the (directional) velocity vector. Recently, there is also increasing interest in the representation of movement parameters in neuronal population activity, such as reflected in the intracranial EEG (iEEG). We show that in iEEG, contrasting to what has been previously found on the single neuron level, speed predominates over velocity. The predominant speed representation was present in nearly all iEEG signal features, up to the 600–1000 Hz range. Using a model of motor-cortical signals arising from neuronal populations with realistic single neuron tuning properties, we show how this reversal can be understood as a consequence of increasing population size. Our findings demonstrate that the information profile in large population signals may systematically differ from the single neuron level, a principle that may be helpful in the interpretation of neuronal population signals in general, including, for example, EEG and functional magnetic resonance imaging. Taking advantage of the robust speed population signal may help in developing brain–machine interfaces exploiting population signals.
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Affiliation(s)
- Jiří Hammer
- Epilepsy Center, University Medical Center Freiburg, 79106 Freiburg, Germany Neurobiology and Biophysics, Faculty of Biology, University of Freiburg, 79104 Freiburg, Germany Department of Paediatric Neurology, 2nd Faculty of Medicine and Motol University Hospital Department of Neurology, 2nd Faculty of Medicine and Motol University Hospital, Charles University, 150 06 Prague, Czech Republic
| | - Tobias Pistohl
- Neurobiology and Biophysics, Faculty of Biology, University of Freiburg, 79104 Freiburg, Germany Bernstein Center Freiburg, University of Freiburg, 79104 Freiburg, Germany
| | - Jörg Fischer
- Neurobiology and Biophysics, Faculty of Biology, University of Freiburg, 79104 Freiburg, Germany CorTec GmbH, 79110 Freiburg, Germany
| | - Pavel Kršek
- Department of Paediatric Neurology, 2nd Faculty of Medicine and Motol University Hospital
| | - Martin Tomášek
- Department of Neurology, 2nd Faculty of Medicine and Motol University Hospital, Charles University, 150 06 Prague, Czech Republic
| | - Petr Marusič
- Department of Neurology, 2nd Faculty of Medicine and Motol University Hospital, Charles University, 150 06 Prague, Czech Republic
| | - Andreas Schulze-Bonhage
- Epilepsy Center, University Medical Center Freiburg, 79106 Freiburg, Germany Bernstein Center Freiburg, University of Freiburg, 79104 Freiburg, Germany
| | - Ad Aertsen
- Neurobiology and Biophysics, Faculty of Biology, University of Freiburg, 79104 Freiburg, Germany Bernstein Center Freiburg, University of Freiburg, 79104 Freiburg, Germany
| | - Tonio Ball
- Epilepsy Center, University Medical Center Freiburg, 79106 Freiburg, Germany Bernstein Center Freiburg, University of Freiburg, 79104 Freiburg, Germany
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6
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Vidu R, Rahman M, Mahmoudi M, Enachescu M, Poteca TD, Opris I. Nanostructures: a platform for brain repair and augmentation. Front Syst Neurosci 2014; 8:91. [PMID: 24999319 PMCID: PMC4064704 DOI: 10.3389/fnsys.2014.00091] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2014] [Accepted: 04/30/2014] [Indexed: 01/04/2023] Open
Abstract
Nanoscale structures have been at the core of research efforts dealing with integration of nanotechnology into novel electronic devices for the last decade. Because the size of nanomaterials is of the same order of magnitude as biomolecules, these materials are valuable tools for nanoscale manipulation in a broad range of neurobiological systems. For instance, the unique electrical and optical properties of nanowires, nanotubes, and nanocables with vertical orientation, assembled in nanoscale arrays, have been used in many device applications such as sensors that hold the potential to augment brain functions. However, the challenge in creating nanowires/nanotubes or nanocables array-based sensors lies in making individual electrical connections fitting both the features of the brain and of the nanostructures. This review discusses two of the most important applications of nanostructures in neuroscience. First, the current approaches to create nanowires and nanocable structures are reviewed to critically evaluate their potential for developing unique nanostructure based sensors to improve recording and device performance to reduce noise and the detrimental effect of the interface on the tissue. Second, the implementation of nanomaterials in neurobiological and medical applications will be considered from the brain augmentation perspective. Novel applications for diagnosis and treatment of brain diseases such as multiple sclerosis, meningitis, stroke, epilepsy, Alzheimer's disease, schizophrenia, and autism will be considered. Because the blood brain barrier (BBB) has a defensive mechanism in preventing nanomaterials arrival to the brain, various strategies to help them to pass through the BBB will be discussed. Finally, the implementation of nanomaterials in neurobiological applications is addressed from the brain repair/augmentation perspective. These nanostructures at the interface between nanotechnology and neuroscience will play a pivotal role not only in addressing the multitude of brain disorders but also to repair or augment brain functions.
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Affiliation(s)
- Ruxandra Vidu
- Department of Chemical Engineering and Materials Science, University of California DavisDavis, CA, USA
| | - Masoud Rahman
- Department of Chemical Engineering and Materials Science, University of California DavisDavis, CA, USA
| | - Morteza Mahmoudi
- Department of Nanotechnology and Nanotechnology Research Center, Faculty of Pharmacy, Tehran University of Medical SciencesTehran, Iran
| | - Marius Enachescu
- Center for Surface Science and Nanotechnology, University “Politehnica” BucharestBucharest, Romania
- Academy of Romanian ScientistsBucharest, Romania
| | - Teodor D. Poteca
- Carol Davila University of Medicine and PharmacyBucharest, Romania
| | - Ioan Opris
- Wake Forest University Health SciencesWinston-Salem, NC, USA
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7
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Jotterand F. Psychopathy, neurotechnologies, and neuroethics. THEORETICAL MEDICINE AND BIOETHICS 2014; 35:1-6. [PMID: 24464085 DOI: 10.1007/s11017-014-9280-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Affiliation(s)
- Fabrice Jotterand
- Department of Health Care Ethics, Rueckert-Hatman College of Health Professions, Regis University, 3333 Regis Boulevard, G-5, Denver, CO, 80221, USA,
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8
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Andoralov V, Falk M, Suyatin DB, Granmo M, Sotres J, Ludwig R, Popov VO, Schouenborg J, Blum Z, Shleev S. Biofuel cell based on microscale nanostructured electrodes with inductive coupling to rat brain neurons. Sci Rep 2013; 3:3270. [PMID: 24253492 PMCID: PMC3834879 DOI: 10.1038/srep03270] [Citation(s) in RCA: 45] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2013] [Accepted: 10/31/2013] [Indexed: 01/18/2023] Open
Abstract
Miniature, self-contained biodevices powered by biofuel cells may enable a new generation of implantable, wireless, minimally invasive neural interfaces for neurophysiological in vivo studies and for clinical applications. Here we report on the fabrication of a direct electron transfer based glucose/oxygen enzymatic fuel cell (EFC) from genuinely three-dimensional (3D) nanostructured microscale gold electrodes, modified with suitable biocatalysts. We show that the process underlying the simple fabrication method of 3D nanostructured electrodes is based on an electrochemically driven transformation of physically deposited gold nanoparticles. We experimentally demonstrate that mediator-, cofactor-, and membrane-less EFCs do operate in cerebrospinal fluid and in the brain of a rat, producing amounts of electrical power sufficient to drive a self-contained biodevice, viz. 7 μW cm−2in vitro and 2 μW cm−2in vivo at an operating voltage of 0.4 V. Last but not least, we also demonstrate an inductive coupling between 3D nanobioelectrodes and living neurons.
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Affiliation(s)
- Viktor Andoralov
- 1] Biomedical Sciences, Health & Society, Malmö University, 205 06 Malmö, Sweden [2]
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9
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Sulzer J, Haller S, Scharnowski F, Weiskopf N, Birbaumer N, Blefari M, Bruehl A, Cohen L, deCharms R, Gassert R, Goebel R, Herwig U, LaConte S, Linden D, Luft A, Seifritz E, Sitaram R. Real-time fMRI neurofeedback: progress and challenges. Neuroimage 2013; 76:386-99. [PMID: 23541800 PMCID: PMC4878436 DOI: 10.1016/j.neuroimage.2013.03.033] [Citation(s) in RCA: 292] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2012] [Revised: 03/14/2013] [Accepted: 03/19/2013] [Indexed: 01/30/2023] Open
Abstract
In February of 2012, the first international conference on real time functional magnetic resonance imaging (rtfMRI) neurofeedback was held at the Swiss Federal Institute of Technology Zurich (ETHZ), Switzerland. This review summarizes progress in the field, introduces current debates, elucidates open questions, and offers viewpoints derived from the conference. The review offers perspectives on study design, scientific and clinical applications, rtfMRI learning mechanisms and future outlook.
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Affiliation(s)
- J. Sulzer
- Department of Health Sciences and Technology, Swiss Federal Institute of Technology, (ETH), Zurich CH-8092, Switzerland
| | - S. Haller
- University of Geneva, Geneva University Hospital CH-1211, Switzerland
| | - F. Scharnowski
- Department of Radiology and Medical Informatics - CIBM, University of Geneva, Switzerland
- Institute of Bioengineering, Swiss Institute of Technology Lausanne (EPFL) CH-1015, Switzerland
| | - N. Weiskopf
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London WC1E 6BT, UK
| | - N. Birbaumer
- The Institute of Medical Psychology and Behavioral Neurobiology, University of Tuebingen 72074, Germany
- Ospedale San Camillo, IRCCS, Venice 30126, Italy
| | - M.L. Blefari
- Department of Health Sciences and Technology, Swiss Federal Institute of Technology, (ETH), Zurich CH-8092, Switzerland
| | - A.B. Bruehl
- Department of Psychiatry, Psychotherapy and Psychosomatica, Zürich University Hospital for Psychiatry, Zurich CH-8032, Switzerland
| | - L.G. Cohen
- National Institutes of Health, Bethesda 20892, USA
| | | | - R. Gassert
- Department of Health Sciences and Technology, Swiss Federal Institute of Technology, (ETH), Zurich CH-8092, Switzerland
| | - R. Goebel
- Department of Neurocognition, University of Maastricht 6200, The Netherlands
| | - U. Herwig
- Department of Psychiatry, Psychotherapy and Psychosomatica, Zürich University Hospital for Psychiatry, Zurich CH-8032, Switzerland
- Department of Psychiatry and Psychotherapy III, University of Ulm, Germany
| | - S. LaConte
- Virginia Tech Carilion Research Institute 24016, USA
| | | | - A. Luft
- Department of Neurology, University Hospital Zurich, Switzerland
- University of Zurich CH-8008, Switzerland
| | - E. Seifritz
- Department of Psychiatry, Psychotherapy and Psychosomatica, Zürich University Hospital for Psychiatry, Zurich CH-8032, Switzerland
| | - R. Sitaram
- The Institute of Medical Psychology and Behavioral Neurobiology, University of Tuebingen 72074, Germany
- Department of Biomedical Engineering, University of Florida, Gainesville 32611, USA
- Sri Chitra Tirunal Institute of Medical Science and Technology, Trivandrum, India
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10
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Nanowire-based electrode for acute in vivo neural recordings in the brain. PLoS One 2013; 8:e56673. [PMID: 23431387 PMCID: PMC3576334 DOI: 10.1371/journal.pone.0056673] [Citation(s) in RCA: 51] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2012] [Accepted: 01/16/2013] [Indexed: 12/03/2022] Open
Abstract
We present an electrode, based on structurally controlled nanowires, as a first step towards developing a useful nanostructured device for neurophysiological measurements in vivo. The sensing part of the electrode is made of a metal film deposited on top of an array of epitaxially grown gallium phosphide nanowires. We achieved the first functional testing of the nanowire-based electrode by performing acute in vivo recordings in the rat cerebral cortex and withstanding multiple brain implantations. Due to the controllable geometry of the nanowires, this type of electrode can be used as a model system for further analysis of the functional properties of nanostructured neuronal interfaces in vivo.
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11
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Zhang Q, Zhang S, Hao Y, Zhang H, Zhu J, Zhao T, Zhang J, Wang Y, Zheng X, Chen W. Development of an invasive brain-machine interface with a monkey model. ACTA ACUST UNITED AC 2012. [DOI: 10.1007/s11434-012-5096-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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12
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Pinto MADS, de Souza JKS, Baron J, Tierra-Criollo CJ. A low-cost, portable, micro-controlled device for multi-channel LED visual stimulation. J Neurosci Methods 2011; 197:82-91. [PMID: 21320530 DOI: 10.1016/j.jneumeth.2011.02.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2010] [Revised: 01/31/2011] [Accepted: 02/01/2011] [Indexed: 10/18/2022]
Abstract
Light emitting diodes (LEDs) are extensively used as light sources to investigate visual and visually related function and dysfunction. Here, we describe the design of a compact, low-cost, stand-alone LED-based system that enables the configuration, storage and presentation of elaborate visual stimulation paradigms. The core functionality of this system is provided by a microcontroller whose ultra-low power consumption makes it well suited for long lasting battery applications. The effective use of hardware resources is managed by multi-layered architecture software that provides an intuitive and user-friendly interface. In the configuration mode, different stimulation sequences can be created and memorized for ten channels, independently. LED-driving current output can be set either as continuous or pulse modulated, up to 500 Hz, by duty cycle adjustments. In run mode, multiple-channel stimulus sequences are automatically applied according to the pre-programmed protocol. Steady state visual evoked potentials were successfully recorded in five subjects with no visible electromagnetic interferences from the stimulator, demonstrating the efficacy of combining our prototyped equipment with electrophysiological techniques. Finally, we discuss a number of possible improvements for future development of our project.
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Affiliation(s)
- Marcos Antonio da Silva Pinto
- Department of Electrical Engineering, School of Engineering, Laboratory of Biomedical Engineering, Universidade Federal de Minas Gerais, Av. Antônio Carlos 6627, 31270-010 Belo Horizonte, MG, Brazil
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13
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Pfurtscheller G, Allison BZ, Brunner C, Bauernfeind G, Solis-Escalante T, Scherer R, Zander TO, Mueller-Putz G, Neuper C, Birbaumer N. The hybrid BCI. Front Neurosci 2010; 4:30. [PMID: 20582271 PMCID: PMC2891647 DOI: 10.3389/fnpro.2010.00003] [Citation(s) in RCA: 216] [Impact Index Per Article: 15.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2009] [Accepted: 03/15/2010] [Indexed: 11/13/2022] Open
Abstract
Nowadays, everybody knows what a hybrid car is. A hybrid car normally has two engines to enhance energy efficiency and reduce CO2 output. Similarly, a hybrid brain-computer interface (BCI) is composed of two BCIs, or at least one BCI and another system. A hybrid BCI, like any BCI, must fulfill the following four criteria: (i) the device must rely on signals recorded directly from the brain; (ii) there must be at least one recordable brain signal that the user can intentionally modulate to effect goal-directed behaviour; (iii) real time processing; and (iv) the user must obtain feedback. This paper introduces hybrid BCIs that have already been published or are in development. We also introduce concepts for future work. We describe BCIs that classify two EEG patterns: one is the event-related (de)synchronisation (ERD, ERS) of sensorimotor rhythms, and the other is the steady-state visual evoked potential (SSVEP). Hybrid BCIs can either process their inputs simultaneously, or operate two systems sequentially, where the first system can act as a “brain switch”. For example, we describe a hybrid BCI that simultaneously combines ERD and SSVEP BCIs. We also describe a sequential hybrid BCI, in which subjects could use a brain switch to control an SSVEP-based hand orthosis. Subjects who used this hybrid BCI exhibited about half the false positives encountered while using the SSVEP BCI alone. A brain switch can also rely on hemodynamic changes measured through near-infrared spectroscopy (NIRS). Hybrid BCIs can also use one brain signal and a different type of input. This additional input can be an electrophysiological signal such as the heart rate, or a signal from an external device such as an eye tracking system.
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Affiliation(s)
- Gert Pfurtscheller
- Laboratory of Brain-Computer Interfaces, Institute for Knowledge Discovery, Graz University of Technology Graz, Austria.
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