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Vakilipour P, Fekrvand S. Brain-to-brain interface technology: A brief history, current state, and future goals. Int J Dev Neurosci 2024; 84:351-367. [PMID: 38711277 DOI: 10.1002/jdn.10334] [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: 11/29/2023] [Revised: 04/05/2024] [Accepted: 04/18/2024] [Indexed: 05/08/2024] Open
Abstract
A brain-to-brain interface (BBI), defined as a combination of neuroimaging and neurostimulation methods to extract and deliver information between brains directly without the need for the peripheral nervous system, is a budding communication technique. A BBI system is made up of two parts known as the brain-computer interface part, which reads a sender's brain activity and digitalizes it, and the computer-brain interface part, which writes the delivered brain activity to a receiving brain. As with other technologies, BBI systems have gone through an evolutionary process since they first appeared. The BBI systems have been employed for numerous purposes, including rehabilitation for post-stroke patients, communicating with patients suffering from amyotrophic lateral sclerosis, locked-in syndrome and speech problems following stroke. Also, it has been proposed that a BBI system could play an important role on future battlefields. This technology was not only employed for communicating between two human brains but also for making a direct communication path among different species through which motor or sensory commands could be sent and received. However, the application of BBI systems has provoked significant challenges to human rights principles due to their ability to access and manipulate human brain information. In this study, we aimed to review the brain-computer interface and computer-brain interface technologies as components of BBI systems, the development of BBI systems, applications of this technology, arising ethical issues and expectations for future use.
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Affiliation(s)
- Pouya Vakilipour
- Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran
- Universal Scientific Education and Research Network (USERN), Tehran, Iran
| | - Saba Fekrvand
- Universal Scientific Education and Research Network (USERN), Tehran, Iran
- Brain and Spinal Cord Injury Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
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2
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Ghazizadeh E, Naseri Z, Deigner HP, Rahimi H, Altintas Z. Approaches of wearable and implantable biosensor towards of developing in precision medicine. Front Med (Lausanne) 2024; 11:1390634. [PMID: 39091290 PMCID: PMC11293309 DOI: 10.3389/fmed.2024.1390634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Accepted: 04/30/2024] [Indexed: 08/04/2024] Open
Abstract
In the relentless pursuit of precision medicine, the intersection of cutting-edge technology and healthcare has given rise to a transformative era. At the forefront of this revolution stands the burgeoning field of wearable and implantable biosensors, promising a paradigm shift in how we monitor, analyze, and tailor medical interventions. As these miniature marvels seamlessly integrate with the human body, they weave a tapestry of real-time health data, offering unprecedented insights into individual physiological landscapes. This log embarks on a journey into the realm of wearable and implantable biosensors, where the convergence of biology and technology heralds a new dawn in personalized healthcare. Here, we explore the intricate web of innovations, challenges, and the immense potential these bioelectronics sentinels hold in sculpting the future of precision medicine.
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Affiliation(s)
- Elham Ghazizadeh
- Department of Bioinspired Materials and Biosensor Technologies, Faculty of Engineering, Institute of Materials Science, Kiel University, Kiel, Germany
- Department of Medical Biotechnology, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Zahra Naseri
- Department of Medical Biotechnology, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Hans-Peter Deigner
- Institute of Precision Medicine, Furtwangen University, Villingen-Schwenningen, Germany
- Fraunhofer Institute IZI (Leipzig), Rostock, Germany
- Faculty of Science, Eberhard-Karls-University Tuebingen, Tuebingen, Germany
| | - Hossein Rahimi
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Zeynep Altintas
- Department of Bioinspired Materials and Biosensor Technologies, Faculty of Engineering, Institute of Materials Science, Kiel University, Kiel, Germany
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3
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Lyreskog DM, Zohny H, Mann SP, Singh I, Savulescu J. Decentralising the Self - Ethical Considerations in Utilizing Decentralised Web Technology for Direct Brain Interfaces. SCIENCE AND ENGINEERING ETHICS 2024; 30:28. [PMID: 39012561 PMCID: PMC11252225 DOI: 10.1007/s11948-024-00492-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 06/08/2024] [Indexed: 07/17/2024]
Abstract
The rapidly advancing field of brain-computer (BCI) and brain-to-brain interfaces (BBI) is stimulating interest across various sectors including medicine, entertainment, research, and military. The developers of large-scale brain-computer networks, sometimes dubbed 'Mindplexes' or 'Cloudminds', aim to enhance cognitive functions by distributing them across expansive networks. A key technical challenge is the efficient transmission and storage of information. One proposed solution is employing blockchain technology over Web 3.0 to create decentralised cognitive entities. This paper explores the potential of a decentralised web for coordinating large brain-computer constellations, and its associated benefits, focusing in particular on the conceptual and ethical challenges this innovation may pose pertaining to (1) Identity, (2) Sovereignty (encompassing Autonomy, Authenticity, and Ownership), (3) Responsibility and Accountability, and (4) Privacy, Safety, and Security. We suggest that while a decentralised web can address some concerns and mitigate certain risks, underlying ethical issues persist. Fundamental questions about entity definition within these networks, the distinctions between individuals and collectives, and responsibility distribution within and between networks, demand further exploration.
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Affiliation(s)
- David M Lyreskog
- Department of Psychiatry, Warneford Hospital, University of Oxford, Warneford Ln, Oxford, OX3 7JX, UK.
- Wellcome Centre for Ethics and Humanities, University of Oxford, Oxford, UK.
| | - Hazem Zohny
- Department of Psychiatry, Warneford Hospital, University of Oxford, Warneford Ln, Oxford, OX3 7JX, UK
- Oxford Uehiro Centre for Practical Ethics, University of Oxford, Oxford, UK
| | | | - Ilina Singh
- Department of Psychiatry, Warneford Hospital, University of Oxford, Warneford Ln, Oxford, OX3 7JX, UK
- Wellcome Centre for Ethics and Humanities, University of Oxford, Oxford, UK
| | - Julian Savulescu
- Wellcome Centre for Ethics and Humanities, University of Oxford, Oxford, UK
- Oxford Uehiro Centre for Practical Ethics, University of Oxford, Oxford, UK
- Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Queenstown, Singapore
- Murdoch Children's Research Institute, Melbourne, Australia
- University of Melbourne, Melbourne, Australia
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4
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Zohny H, Savulescu J. When Two Become One: Singular Duos and the Neuroethical Frontiers of Brain-to-Brain Interfaces. Camb Q Healthc Ethics 2024:1-13. [PMID: 38606432 DOI: 10.1017/s0963180124000197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/13/2024]
Abstract
Advances in brain-brain interface technologies raise the possibility that two or more individuals could directly link their minds, sharing thoughts, emotions, and sensory experiences. This paper explores conceptual and ethical issues posed by such mind-merging technologies in the context of clinical neuroethics. Using hypothetical examples along a spectrum from loosely connected pairs to fully merged minds, the authors sketch out a range of factors relevant to identifying the degree of a merger. They then consider potential new harms like loss of identity, psychological domination, loss of mental privacy, and challenges for notions of autonomy and patient benefit when applied to merged minds. While radical technologies may seem to necessitate new ethical paradigms, the authors suggest the individual-focus underpinning clinical ethics can largely accommodate varying degrees of mind mergers so long as individual patient interests remain identifiable. However, advanced decisionmaking and directives may have limitations in addressing the dilemmas posed. Overall, mind-merging possibilities amplify existing challenges around loss of identity, relating to others, autonomy, privacy, and the delineation of patient interests. This paper lays the groundwork for developing resources to address the novel issues raised, while suggesting the technologies reveal continuity with current healthcare ethics tensions.
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Affiliation(s)
- Hazem Zohny
- Oxford Uehiro Centre for Practical Ethics, University of Oxford, Oxford, UK
| | - Julian Savulescu
- Chen Su Lan Centennial Professor in Medical Ethics, Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Uehiro Chair in Practical Ethics, Faculty of Philosophy, University of Oxford, Oxford, UK
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5
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Lyreskog DM, Zohny H, Savulescu J, Singh I. Merging Minds: The Conceptual and Ethical Impacts of Emerging Technologies for Collective Minds. NEUROETHICS-NETH 2023; 16:12. [PMID: 37009261 PMCID: PMC10050050 DOI: 10.1007/s12152-023-09516-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 02/26/2023] [Indexed: 03/30/2023]
Abstract
AbstractA growing number of technologies are currently being developed to improve and distribute thinking and decision-making. Rapid progress in brain-to-brain interfacing and swarming technologies promises to transform how we think about collective and collaborative cognitive tasks across domains, ranging from research to entertainment, and from therapeutics to military applications. As these tools continue to improve, we are prompted to monitor how they may affect our society on a broader level, but also how they may reshape our fundamental understanding of agency, responsibility, and other key concepts of our moral landscape.In this paper we take a closer look at this class of technologies – Technologies for Collective Minds – to see not only how their implementation may react with commonly held moral values, but also how they challenge our underlying concepts of what constitutes collective or individual agency. We argue that prominent contemporary frameworks for understanding collective agency and responsibility are insufficient in terms of accurately describing the relationships enabled by Technologies for Collective Minds, and that they therefore risk obstructing ethical analysis of the implementation of these technologies in society. We propose a more multidimensional approach to better understand this set of technologies, and to facilitate future research on the ethics of Technologies for Collective Minds.
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Affiliation(s)
- David M. Lyreskog
- Department of Psychiatry, Warneford Hospital, University of Oxford, Warneford Ln, Oxford, OX3 7JX UK
- Oxford Uehiro Centre for Practical Ethics, University of Oxford, Oxford, UK
- Wellcome Centre for Ethics and Humanities, University of Oxford, Oxford, UK
| | - Hazem Zohny
- Department of Psychiatry, Warneford Hospital, University of Oxford, Warneford Ln, Oxford, OX3 7JX UK
- Oxford Uehiro Centre for Practical Ethics, University of Oxford, Oxford, UK
- Wellcome Centre for Ethics and Humanities, University of Oxford, Oxford, UK
| | - Julian Savulescu
- Oxford Uehiro Centre for Practical Ethics, University of Oxford, Oxford, UK
- Wellcome Centre for Ethics and Humanities, University of Oxford, Oxford, UK
- Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Murdoch Children’s Research Institute, Melbourne, Australia
- University of Melbourne, Melbourne, Australia
| | - Ilina Singh
- Department of Psychiatry, Warneford Hospital, University of Oxford, Warneford Ln, Oxford, OX3 7JX UK
- Wellcome Centre for Ethics and Humanities, University of Oxford, Oxford, UK
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6
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Lotter LD, Kohl SH, Gerloff C, Bell L, Niephaus A, Kruppa JA, Dukart J, Schulte-Rüther M, Reindl V, Konrad K. Revealing the neurobiology underlying interpersonal neural synchronization with multimodal data fusion. Neurosci Biobehav Rev 2023; 146:105042. [PMID: 36641012 DOI: 10.1016/j.neubiorev.2023.105042] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 12/22/2022] [Accepted: 01/10/2023] [Indexed: 01/13/2023]
Abstract
Humans synchronize with one another to foster successful interactions. Here, we use a multimodal data fusion approach with the aim of elucidating the neurobiological mechanisms by which interpersonal neural synchronization (INS) occurs. Our meta-analysis of 22 functional magnetic resonance imaging and 69 near-infrared spectroscopy hyperscanning experiments (740 and 3721 subjects) revealed robust brain regional correlates of INS in the right temporoparietal junction and left ventral prefrontal cortex. Integrating this meta-analytic information with public databases, biobehavioral and brain-functional association analyses suggested that INS involves sensory-integrative hubs with functional connections to mentalizing and attention networks. On the molecular and genetic levels, we found INS to be associated with GABAergic neurotransmission and layer IV/V neuronal circuits, protracted developmental gene expression patterns, and disorders of neurodevelopment. Although limited by the indirect nature of phenotypic-molecular association analyses, our findings generate new testable hypotheses on the neurobiological basis of INS.
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Affiliation(s)
- Leon D Lotter
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital RWTH Aachen, Aachen, Germany; Institute of Neuroscience and Medicine - Brain & Behaviour (INM-7), Jülich Research Centre, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Max Planck School of Cognition, Stephanstrasse 1A, 04103 Leipzig, Germany.
| | - Simon H Kohl
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital RWTH Aachen, Aachen, Germany; JARA Brain Institute II, Molecular Neuroscience and Neuroimaging (INM-11), Jülich Research Centre, Jülich, Germany
| | - Christian Gerloff
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital RWTH Aachen, Aachen, Germany; JARA Brain Institute II, Molecular Neuroscience and Neuroimaging (INM-11), Jülich Research Centre, Jülich, Germany; Chair II of Mathematics, Faculty of Mathematics, Computer Science and Natural Sciences, RWTH Aachen University, Aachen, Germany
| | - Laura Bell
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital RWTH Aachen, Aachen, Germany; Audiovisual Media Center, Medical Faculty, RWTH Aachen University, Aachen, Germany
| | - Alexandra Niephaus
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital RWTH Aachen, Aachen, Germany
| | - Jana A Kruppa
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital RWTH Aachen, Aachen, Germany; JARA Brain Institute II, Molecular Neuroscience and Neuroimaging (INM-11), Jülich Research Centre, Jülich, Germany; Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Juergen Dukart
- Institute of Neuroscience and Medicine - Brain & Behaviour (INM-7), Jülich Research Centre, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Martin Schulte-Rüther
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital RWTH Aachen, Aachen, Germany; JARA Brain Institute II, Molecular Neuroscience and Neuroimaging (INM-11), Jülich Research Centre, Jülich, Germany; Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Vanessa Reindl
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital RWTH Aachen, Aachen, Germany; JARA Brain Institute II, Molecular Neuroscience and Neuroimaging (INM-11), Jülich Research Centre, Jülich, Germany; Psychology, School of Social Sciences, Nanyang Technological University, S639818, Singapore
| | - Kerstin Konrad
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital RWTH Aachen, Aachen, Germany; JARA Brain Institute II, Molecular Neuroscience and Neuroimaging (INM-11), Jülich Research Centre, Jülich, Germany
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7
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Bialecki J. Strange Aeons: Transhumanism, H.P. Lovecraft, and the affective index of posthuman dread. THE AUSTRALIAN JOURNAL OF ANTHROPOLOGY 2022. [DOI: 10.1111/taja.12450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Jon Bialecki
- Department of Anthropology University of California San Diego California USA
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8
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Silvernagel MP, Ling AS, Nuyujukian P. A markerless platform for ambulatory systems neuroscience. Sci Robot 2021; 6:eabj7045. [PMID: 34516749 DOI: 10.1126/scirobotics.abj7045] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Motor systems neuroscience seeks to understand how the brain controls movement. To minimize confounding variables, large-animal studies typically constrain body movement from areas not under observation, ensuring consistent, repeatable behaviors. Such studies have fueled decades of research, but they may be artificially limiting the richness of neural data observed, preventing generalization to more natural movements and settings. Neuroscience studies of unconstrained movement would capture a greater range of behavior and a more complete view of neuronal activity, but instrumenting an experimental rig suitable for large animals presents substantial engineering challenges. Here, we present a markerless, full-body motion tracking and synchronized wireless neural electrophysiology platform for large, ambulatory animals. Composed of four depth (RGB-D) cameras that provide a 360° view of a 4.5-square-meters enclosed area, this system is designed to record a diverse range of neuroethologically relevant behaviors. This platform also allows for the simultaneous acquisition of hundreds of wireless neural recording channels in multiple brain regions. As behavioral and neuronal data are generated at rates below 200 megabytes per second, a single desktop can facilitate hours of continuous recording. This setup is designed for systems neuroscience and neuroengineering research, where synchronized kinematic behavior and neural data are the foundation for investigation. By enabling the study of previously unexplored movement tasks, this system can generate insights into the functioning of the mammalian motor system and provide a platform to develop brain-machine interfaces for unconstrained applications.
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Affiliation(s)
| | - Alissa S Ling
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Paul Nuyujukian
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA.,Department of Bioengineering, Stanford University, Stanford, CA, USA.,Department of Neurosurgery, Stanford University, Stanford, CA, USA.,Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA.,Stanford Bio-X, Stanford University, Stanford, CA, USA
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9
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Yang L, Li M, Yang L, Wang H, Wan H, Shang Z. Functional connectivity changes in the intra- and inter-brain during the construction of the multi-brain network of pigeons. Brain Res Bull 2020; 161:147-157. [DOI: 10.1016/j.brainresbull.2020.04.015] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Revised: 04/15/2020] [Accepted: 04/20/2020] [Indexed: 02/07/2023]
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10
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Lu L, Wang R, Luo M. An optical brain-to-brain interface supports rapid information transmission for precise locomotion control. SCIENCE CHINA-LIFE SCIENCES 2020; 63:875-885. [PMID: 32266609 DOI: 10.1007/s11427-020-1675-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Accepted: 03/05/2020] [Indexed: 10/24/2022]
Abstract
Brain-to-brain interfaces (BtBIs) hold exciting potentials for direct communication between individual brains. However, technical challenges often limit their performance in rapid information transfer. Here, we demonstrate an optical brain-to-brain interface that transmits information regarding locomotor speed from one mouse to another and allows precise, real-time control of locomotion across animals with high information transfer rate. We found that the activity of the genetically identified neuromedin B (NMB) neurons within the nucleus incertus (NI) precisely predicts and critically controls locomotor speed. By optically recording Ca2+ signals from the NI of a "Master" mouse and converting them to patterned optogenetic stimulations of the NI of an "Avatar" mouse, the BtBI directed the Avatar mice to closely mimic the locomotion of their Masters with information transfer rate about two orders of magnitude higher than previous BtBIs. These results thus provide proof-of-concept that optical BtBIs can rapidly transmit neural information and control dynamic behaviors across individuals.
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Affiliation(s)
- Lihui Lu
- School of Life Sciences, Tsinghua University, Beijing, 100084, China.,Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing, 100084, China.,National Institute of Biological Sciences (NIBS), Beijing, 102206, China
| | - Ruiyu Wang
- National Institute of Biological Sciences (NIBS), Beijing, 102206, China.,School of Life Sciences, Peking University, Beijing, 100871, China.,Peking University-Tsinghua University-NIBS Joint Graduate Program, Beijing, 102206, China
| | - Minmin Luo
- Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing, 100084, China. .,National Institute of Biological Sciences (NIBS), Beijing, 102206, China. .,Peking University-Tsinghua University-NIBS Joint Graduate Program, Beijing, 102206, China. .,Chinese Institute for Brain Research, Beijing, 102206, China. .,Tsinghua Institute of Multidisciplinary Biomedical Research (TIMBR), Beijing, 102206, China.
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11
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Hildt E. Multi-Person Brain-To-Brain Interfaces: Ethical Issues. Front Neurosci 2019; 13:1177. [PMID: 31827418 PMCID: PMC6849447 DOI: 10.3389/fnins.2019.01177] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Accepted: 10/18/2019] [Indexed: 12/03/2022] Open
Affiliation(s)
- Elisabeth Hildt
- Center for the Study of Ethics in the Professions, Illinois Institute of Technology, Chicago, IL, United States
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12
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Teunisse W, Youssef S, Schmidt M. Human enhancement through the lens of experimental and speculative neurotechnologies. HUMAN BEHAVIOR AND EMERGING TECHNOLOGIES 2019; 1:361-372. [PMID: 31894206 PMCID: PMC6919332 DOI: 10.1002/hbe2.179] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2019] [Revised: 09/04/2019] [Accepted: 09/05/2019] [Indexed: 12/11/2022]
Abstract
Human enhancement deals with improving on and overcoming limitations of the human body and mind. Pharmaceutical compounds that alter consciousness and cognitive performance have been used and discussed for a long time. The prospect of neurotechnological applications such as brain-steered devices or using invasive and noninvasive electromagnetic stimulations of the human brain, however, has received less attention-especially outside of therapeutic practices-and remains relatively unexplored. Reflection and debates about neurotechnology for human enhancement are limited and remain predominantly with neurotech engineers, science-fiction enthusiasts and a small circle of academics in the field of neuroethics. It is well known, and described as the Collingridge dilemma, that at an early stage of development, changes can easily be enacted, but the need for changes can hardly be foreseen. Once the technology is entrenched, opportunities and risks start to materialize, and the need to adapt and change is clearly visible. However, carrying out these changes at such a late stage, in turn, becomes very difficult, tremendously expensive, and sometimes practically impossible. In this manuscript, we compile and categorize an overview of existing experimental and speculative applications of neurotechnologies, with the aim to find out, if these real or diegetic prototypes could be used to better understand the paths these applications are forging. In particular, we will investigate what kind of tools, motivations, and normative goals underpin experimental implementations by neurohackers, speculative designers and artists.
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BrainNet: A Multi-Person Brain-to-Brain Interface for Direct Collaboration Between Brains. Sci Rep 2019; 9:6115. [PMID: 30992474 PMCID: PMC6467884 DOI: 10.1038/s41598-019-41895-7] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Accepted: 03/20/2019] [Indexed: 11/08/2022] Open
Abstract
We present BrainNet which, to our knowledge, is the first multi-person non-invasive direct brain-to-brain interface for collaborative problem solving. The interface combines electroencephalography (EEG) to record brain signals and transcranial magnetic stimulation (TMS) to deliver information noninvasively to the brain. The interface allows three human subjects to collaborate and solve a task using direct brain-to-brain communication. Two of the three subjects are designated as "Senders" whose brain signals are decoded using real-time EEG data analysis. The decoding process extracts each Sender's decision about whether to rotate a block in a Tetris-like game before it is dropped to fill a line. The Senders' decisions are transmitted via the Internet to the brain of a third subject, the "Receiver," who cannot see the game screen. The Senders' decisions are delivered to the Receiver's brain via magnetic stimulation of the occipital cortex. The Receiver integrates the information received from the two Senders and uses an EEG interface to make a decision about either turning the block or keeping it in the same orientation. A second round of the game provides an additional chance for the Senders to evaluate the Receiver's decision and send feedback to the Receiver's brain, and for the Receiver to rectify a possible incorrect decision made in the first round. We evaluated the performance of BrainNet in terms of (1) Group-level performance during the game, (2) True/False positive rates of subjects' decisions, and (3) Mutual information between subjects. Five groups, each with three human subjects, successfully used BrainNet to perform the collaborative task, with an average accuracy of 81.25%. Furthermore, by varying the information reliability of the Senders by artificially injecting noise into one Sender's signal, we investigated how the Receiver learns to integrate noisy signals in order to make a correct decision. We found that like conventional social networks, BrainNet allows Receivers to learn to trust the Sender who is more reliable, in this case, based solely on the information transmitted directly to their brains. Our results point the way to future brain-to-brain interfaces that enable cooperative problem solving by humans using a "social network" of connected brains.
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Martins NRB, Angelica A, Chakravarthy K, Svidinenko Y, Boehm FJ, Opris I, Lebedev MA, Swan M, Garan SA, Rosenfeld JV, Hogg T, Freitas RA. Human Brain/Cloud Interface. Front Neurosci 2019; 13:112. [PMID: 30983948 PMCID: PMC6450227 DOI: 10.3389/fnins.2019.00112] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2018] [Accepted: 01/30/2019] [Indexed: 12/25/2022] Open
Abstract
The Internet comprises a decentralized global system that serves humanity's collective effort to generate, process, and store data, most of which is handled by the rapidly expanding cloud. A stable, secure, real-time system may allow for interfacing the cloud with the human brain. One promising strategy for enabling such a system, denoted here as a "human brain/cloud interface" ("B/CI"), would be based on technologies referred to here as "neuralnanorobotics." Future neuralnanorobotics technologies are anticipated to facilitate accurate diagnoses and eventual cures for the ∼400 conditions that affect the human brain. Neuralnanorobotics may also enable a B/CI with controlled connectivity between neural activity and external data storage and processing, via the direct monitoring of the brain's ∼86 × 109 neurons and ∼2 × 1014 synapses. Subsequent to navigating the human vasculature, three species of neuralnanorobots (endoneurobots, gliabots, and synaptobots) could traverse the blood-brain barrier (BBB), enter the brain parenchyma, ingress into individual human brain cells, and autoposition themselves at the axon initial segments of neurons (endoneurobots), within glial cells (gliabots), and in intimate proximity to synapses (synaptobots). They would then wirelessly transmit up to ∼6 × 1016 bits per second of synaptically processed and encoded human-brain electrical information via auxiliary nanorobotic fiber optics (30 cm3) with the capacity to handle up to 1018 bits/sec and provide rapid data transfer to a cloud based supercomputer for real-time brain-state monitoring and data extraction. A neuralnanorobotically enabled human B/CI might serve as a personalized conduit, allowing persons to obtain direct, instantaneous access to virtually any facet of cumulative human knowledge. Other anticipated applications include myriad opportunities to improve education, intelligence, entertainment, traveling, and other interactive experiences. A specialized application might be the capacity to engage in fully immersive experiential/sensory experiences, including what is referred to here as "transparent shadowing" (TS). Through TS, individuals might experience episodic segments of the lives of other willing participants (locally or remote) to, hopefully, encourage and inspire improved understanding and tolerance among all members of the human family.
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Affiliation(s)
- Nuno R. B. Martins
- Lawrence Berkeley National Laboratory, Berkeley, CA, United States
- Center for Research and Education on Aging (CREA), University of California, Berkeley and LBNL, Berkeley, CA, United States
| | | | - Krishnan Chakravarthy
- UC San Diego Health Science, San Diego, CA, United States
- VA San Diego Healthcare System, San Diego, CA, United States
| | | | | | - Ioan Opris
- Miami Project to Cure Paralysis, University of Miami, Miami, FL, United States
- Department of Biomedical Engineering, University of Miami, Coral Gables, FL, United States
| | - Mikhail A. Lebedev
- Center for Neuroengineering, Duke University, Durham, NC, United States
- Center for Bioelectric Interfaces of the Institute for Cognitive Neuroscience of the National Research University Higher School of Economics, Moscow, Russia
- Department of Information and Internet Technologies of Digital Health Institute, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Melanie Swan
- Department of Philosophy, Purdue University, West Lafayette, IN, United States
| | - Steven A. Garan
- Lawrence Berkeley National Laboratory, Berkeley, CA, United States
- Center for Research and Education on Aging (CREA), University of California, Berkeley and LBNL, Berkeley, CA, United States
| | - Jeffrey V. Rosenfeld
- Monash Institute of Medical Engineering, Monash University, Clayton, VIC, Australia
- Department of Neurosurgery, Alfred Hospital, Melbourne, VIC, Australia
- Department of Surgery, Monash University, Clayton, VIC, Australia
- Department of Surgery, F. Edward Hébert School of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, United States
| | - Tad Hogg
- Institute for Molecular Manufacturing, Palo Alto, CA, United States
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15
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Nayak L, Dasgupta A, Das R, Ghosh K, De RK. Computational neuroscience and neuroinformatics: Recent progress and resources. J Biosci 2018; 43:1037-1054. [PMID: 30541962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
The human brain and its temporal behavior correlated with development, structure, and function is a complex natural system even for its own kind. Coding and automation are necessary for modeling, analyzing and understanding the 86.1 +/- 8.1 +/- billion neurons, an almost equal number of non-neuronal glial cells, and the neuronal networks of the human brain comprising about 100 trillion connections. 'Computational neuroscience' which is heavily dependent on biology, physics, mathematics and computation addresses such problems while the archival, retrieval and merging of the huge amount of generated data in the form of clinical records, scientific literature, and specialized databases are carried out by 'neuroinformatics' approaches. Neuroinformatics is thus an interface between computer science and experimental neuroscience. This article provides an introduction to computational neuroscience and neuroinformatics fields along with their state-ofthe- art tools, software, and resources. Furthermore, it describes a few innovative applications of these fields in predicting and detecting brain network organization, complex brain disorder diagnosis, large-scale 3D simulation of the brain, brain- computer, and brain-to-brain interfaces. It provides an integrated overview of the fields in a non-technical way, appropriate for broad general readership. Moreover, the article is an updated unified resource of the existing knowledge and sources for researchers stepping into these fields.
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Affiliation(s)
- Losiana Nayak
- Machine Intelligence Unit, Indian Statistical Institute, 203 Barrackpore Trunk Road, Kolkata 700 108, India
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16
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17
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Rascoe A, Sharma P, Shah PK. Development of an Activity-Dependent Epidural Stimulation System in Freely Moving Spinal Cord Injured Rats: A Proof of Concept Study. Front Neurosci 2018; 12:472. [PMID: 30083089 PMCID: PMC6064745 DOI: 10.3389/fnins.2018.00472] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2017] [Accepted: 06/21/2018] [Indexed: 11/13/2022] Open
Abstract
Purpose: Extensive pre-clinical and clinical experimentation has yielded data on the robustness and versatility of epidural stimulation (ES) strategies to activate spinal neural circuitry to produce functional benefits. Increasing studies are now reporting that closed-loop electrical stimulation delivery methods significantly enhance the neuromodulation effects of stimulation, to in turn, improve physiological outcomes of the intervention. No studies have yet explored the feasibility and usage of closed-loop systems to neuromodulate the cervical spinal cord using ES. Methods: We developed an activity-dependent system that utilizes electromyography (EMG) activity to trigger epidural stimulation (tES) of the cervical spinal cord in awake, freely moving rats. Experiments were performed on rats that were implanted with chronic forelimb EMG and cervical epidural implants, with (n = 7) and without (n = 2) a complete C4 spinal hemisection. Results: Our results show that the EMG triggered activity-dependent system can be reliably applied and reproduced for: (i) stimulating multiple rats simultaneously throughout the night during free home-cage activity and (ii) use as a mobile system for testing and training during various short-term behavioral testing conditions. The system was able to consistently generate stimulation pulse trains in response to attempted EMG activity that crossed a user-defined threshold in all rats for all experiments, including the overnight experiments that lasts for 7 h/session for 6 days/week through the 3-month period. Conclusion: The developed closed-loop system can be considered to represent a class of bidirectional neural prostheses via a circuit that enables two-way interactions between neural activity (real-time processing of EMG activity) and external devices (such as a stimulator). It can operate autonomously for extended periods of time in unrestrained rats, allowing its use as a long-term therapeutic tool. It can also enable us to study the long-term physiological effects of incorporating electrical stimulation techniques into the nervous system. The system can also be experimented for connecting several neural systems into a Brainet by combining neural signals from multiple rats dynamically and in real-time so as to enhance motor performance. Studies are ongoing in our laboratory to test the usefulness of this system in the recovery of hand function after cervical spinal cord injuries.
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Affiliation(s)
- Avi Rascoe
- Division of Rehabilitation Sciences, Department of Physical Therapy, School of Health Technology and Management, Stony Brook University, Stony Brook, NY, United States.,Department of Neurobiology and Behavior, Stony Brook University, Stony Brook, NY, United States
| | - Pawan Sharma
- Division of Rehabilitation Sciences, Department of Physical Therapy, School of Health Technology and Management, Stony Brook University, Stony Brook, NY, United States
| | - Prithvi K Shah
- Division of Rehabilitation Sciences, Department of Physical Therapy, School of Health Technology and Management, Stony Brook University, Stony Brook, NY, United States.,Department of Neurobiology and Behavior, Stony Brook University, Stony Brook, NY, United States
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18
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Interbrain cortical synchronization encodes multiple aspects of social interactions in monkey pairs. Sci Rep 2018; 8:4699. [PMID: 29599529 PMCID: PMC5876380 DOI: 10.1038/s41598-018-22679-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2017] [Accepted: 02/27/2018] [Indexed: 11/09/2022] Open
Abstract
While it is well known that the primate brain evolved to cope with complex social contingencies, the neurophysiological manifestation of social interactions in primates is not well understood. Here, concurrent wireless neuronal ensemble recordings from pairs of monkeys were conducted to measure interbrain cortical synchronization (ICS) during a whole-body navigation task that involved continuous social interaction of two monkeys. One monkey, the passenger, was carried in a robotic wheelchair to a food dispenser, while a second monkey, the observer, remained stationary, watching the passenger. The two monkeys alternated the passenger and the observer roles. Concurrent neuronal ensemble recordings from the monkeys' motor cortex and the premotor dorsal area revealed episodic occurrence of ICS with probability that depended on the wheelchair kinematics, the passenger-observer distance, and the passenger-food distance - the social-interaction factors previously described in behavioral studies. These results suggest that ICS represents specific aspects of primate social interactions.
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19
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Deolindo CS, Kunicki ACB, da Silva MI, Lima Brasil F, Moioli RC. Neuronal Assemblies Evidence Distributed Interactions within a Tactile Discrimination Task in Rats. Front Neural Circuits 2018; 11:114. [PMID: 29375324 PMCID: PMC5768614 DOI: 10.3389/fncir.2017.00114] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2017] [Accepted: 12/26/2017] [Indexed: 11/30/2022] Open
Abstract
Accumulating evidence suggests that neural interactions are distributed and relate to animal behavior, but many open questions remain. The neural assembly hypothesis, formulated by Hebb, states that synchronously active single neurons may transiently organize into functional neural circuits-neuronal assemblies (NAs)-and that would constitute the fundamental unit of information processing in the brain. However, the formation, vanishing, and temporal evolution of NAs are not fully understood. In particular, characterizing NAs in multiple brain regions over the course of behavioral tasks is relevant to assess the highly distributed nature of brain processing. In the context of NA characterization, active tactile discrimination tasks with rats are elucidative because they engage several cortical areas in the processing of information that are otherwise masked in passive or anesthetized scenarios. In this work, we investigate the dynamic formation of NAs within and among four different cortical regions in long-range fronto-parieto-occipital networks (primary somatosensory, primary visual, prefrontal, and posterior parietal cortices), simultaneously recorded from seven rats engaged in an active tactile discrimination task. Our results first confirm that task-related neuronal firing rate dynamics in all four regions is significantly modulated. Notably, a support vector machine decoder reveals that neural populations contain more information about the tactile stimulus than the majority of single neurons alone. Then, over the course of the task, we identify the emergence and vanishing of NAs whose participating neurons are shown to contain more information about animal behavior than randomly chosen neurons. Taken together, our results further support the role of multiple and distributed neurons as the functional unit of information processing in the brain (NA hypothesis) and their link to active animal behavior.
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Affiliation(s)
| | | | | | | | - Renan C. Moioli
- Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Macaiba, Brazil
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20
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Yuste R, Goering S, Arcas BAY, Bi G, Carmena JM, Carter A, Fins JJ, Friesen P, Gallant J, Huggins JE, Illes J, Kellmeyer P, Klein E, Marblestone A, Mitchell C, Parens E, Pham M, Rubel A, Sadato N, Sullivan LS, Teicher M, Wasserman D, Wexler A, Whittaker M, Wolpaw J. Four ethical priorities for neurotechnologies and AI. Nature 2017; 551:159-163. [PMID: 29120438 PMCID: PMC8021272 DOI: 10.1038/551159a] [Citation(s) in RCA: 121] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Artificial intelligence and brain-computer interfaces must respect and preserve people’s privacy, identity, agency and equality, say Rafael Yuste, Sara Goering and colleagues.
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Affiliation(s)
- Rafael Yuste
- Columbia University, New York City, New York, USA
| | | | | | - Guoqiang Bi
- University of Science and Technology of China, Hefei, China
| | | | | | | | | | | | | | - Judy Illes
- University of British Columbia, Vancouver, Canada
| | | | - Eran Klein
- University of Washington, Seattle; and Oregon Health & Science University, Portland, USA
| | - Adam Marblestone
- Kernel, Los Angeles, California; and Massachusetts Institute of Technology Media Lab, Cambridge, Massachusetts, USA
| | | | - Erik Parens
- The Hastings Center, Garrison, New York, USA
| | | | - Alan Rubel
- University of Wisconsin-Madison, Wisconsin, USA
| | - Norihiro Sadato
- the National Institute for Physiological Sciences, Okazaki, Aichi, Japan
| | | | | | | | - Anna Wexler
- University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | | | - Jonathan Wolpaw
- the National Center for Adaptive Neurotechnologies, Albany, New York
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21
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Ramakrishnan A, Byun YW, Rand K, Pedersen CE, Lebedev MA, Nicolelis MAL. Cortical neurons multiplex reward-related signals along with sensory and motor information. Proc Natl Acad Sci U S A 2017; 114:E4841-E4850. [PMID: 28559307 PMCID: PMC5474796 DOI: 10.1073/pnas.1703668114] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Rewards are known to influence neural activity associated with both motor preparation and execution. This influence can be exerted directly upon the primary motor (M1) and somatosensory (S1) cortical areas via the projections from reward-sensitive dopaminergic neurons of the midbrain ventral tegmental areas. However, the neurophysiological manifestation of reward-related signals in M1 and S1 are not well understood. Particularly, it is unclear how the neurons in these cortical areas multiplex their traditional functions related to the control of spatial and temporal characteristics of movements with the representation of rewards. To clarify this issue, we trained rhesus monkeys to perform a center-out task in which arm movement direction, reward timing, and magnitude were manipulated independently. Activity of several hundred cortical neurons was simultaneously recorded using chronically implanted microelectrode arrays. Many neurons (9-27%) in both M1 and S1 exhibited activity related to reward anticipation. Additionally, neurons in these areas responded to a mismatch between the reward amount given to the monkeys and the amount they expected: A lower-than-expected reward caused a transient increase in firing rate in 60-80% of the total neuronal sample, whereas a larger-than-expected reward resulted in a decreased firing rate in 20-35% of the neurons. Moreover, responses of M1 and S1 neurons to reward omission depended on the direction of movements that led to those rewards. These observations suggest that sensorimotor cortical neurons corepresent rewards and movement-related activity, presumably to enable reward-based learning.
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Affiliation(s)
- Arjun Ramakrishnan
- Department of Neurobiology, Duke University, Durham, NC 27710
- Duke University Center for Neuroengineering, Duke University, Durham, NC 27710
| | - Yoon Woo Byun
- Duke University Center for Neuroengineering, Duke University, Durham, NC 27710
- Department of Biomedical Engineering, Duke University, Durham, NC 27708
| | - Kyle Rand
- Department of Biomedical Engineering, Duke University, Durham, NC 27708
| | - Christian E Pedersen
- Joint Department of Biomedical Engineering, University of North Carolina-Chapel Hill and North Carolina State University, Raleigh, NC 27695
| | - Mikhail A Lebedev
- Department of Neurobiology, Duke University, Durham, NC 27710
- Duke University Center for Neuroengineering, Duke University, Durham, NC 27710
| | - Miguel A L Nicolelis
- Department of Neurobiology, Duke University, Durham, NC 27710;
- Duke University Center for Neuroengineering, Duke University, Durham, NC 27710
- Department of Biomedical Engineering, Duke University, Durham, NC 27708
- Department of Psychology and Neuroscience, Duke University, Durham, NC 27708
- Department of Neurology, Duke University, Durham, NC 27710
- Edmund and Lily Safra International Institute of Neurosciences, Natal 59066060, Brazil
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22
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Lebedev MA, Nicolelis MAL. Brain-Machine Interfaces: From Basic Science to Neuroprostheses and Neurorehabilitation. Physiol Rev 2017; 97:767-837. [PMID: 28275048 DOI: 10.1152/physrev.00027.2016] [Citation(s) in RCA: 235] [Impact Index Per Article: 33.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
Brain-machine interfaces (BMIs) combine methods, approaches, and concepts derived from neurophysiology, computer science, and engineering in an effort to establish real-time bidirectional links between living brains and artificial actuators. Although theoretical propositions and some proof of concept experiments on directly linking the brains with machines date back to the early 1960s, BMI research only took off in earnest at the end of the 1990s, when this approach became intimately linked to new neurophysiological methods for sampling large-scale brain activity. The classic goals of BMIs are 1) to unveil and utilize principles of operation and plastic properties of the distributed and dynamic circuits of the brain and 2) to create new therapies to restore mobility and sensations to severely disabled patients. Over the past decade, a wide range of BMI applications have emerged, which considerably expanded these original goals. BMI studies have shown neural control over the movements of robotic and virtual actuators that enact both upper and lower limb functions. Furthermore, BMIs have also incorporated ways to deliver sensory feedback, generated from external actuators, back to the brain. BMI research has been at the forefront of many neurophysiological discoveries, including the demonstration that, through continuous use, artificial tools can be assimilated by the primate brain's body schema. Work on BMIs has also led to the introduction of novel neurorehabilitation strategies. As a result of these efforts, long-term continuous BMI use has been recently implicated with the induction of partial neurological recovery in spinal cord injury patients.
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23
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Silva-dos-Santos A. The Hypothesis of Connecting Two Spinal Cords as a Way of Sharing Information between Two Brains and Nervous Systems. Front Psychol 2017; 8:105. [PMID: 28197119 PMCID: PMC5281600 DOI: 10.3389/fpsyg.2017.00105] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2016] [Accepted: 01/16/2017] [Indexed: 11/18/2022] Open
Abstract
Direct communication between different nervous systems has been recently reported through Brain-to-Brain-Interfaces and brainet. Closed loops systems between the brain and the spinal cord from the same individual have also been demonstrated. However, the connection between different nervous systems through the spinal cord has not yet been considered. This paper raises the hypothesis that connecting two spinal cords (spinal cord - spinal cord connection) is an indirect mean for communication of two brains and a direct way of communication between two nervous systems. A concept of electrical fingerprint of a drug is introduced. The notion of connection between two parts of the same spinal cord to treat a paraplegic patient is also introduced. Possible applications of this technique are discussed in the context of psychology, psychiatry and mental health. Also, it is discussed that external information injected to a spinal cord as well as spinal cord - spinal cord connection can become new tools to (1) study the physiology of the nervous system, (2) model specific behaviors, (3) study and model disease traits (4) treat neuropsychiatric disorders and (5) share information between two nervous systems.
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Affiliation(s)
- Amílcar Silva-dos-Santos
- Department of Psychiatry, Hospital Vila Franca de XiraVila Franca de Xira, Portugal
- Institute of Pharmacology and Neurosciences, Faculty of Medicine, University of LisbonLisbon, Portugal
- Unit of Neurosciences, Institute of Molecular Medicine, University of LisbonLisbon, Portugal
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24
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Yang S, Deng B, Wang J, Li H, Liu C, Fietkiewicz C, Loparo KA. Efficient implementation of a real-time estimation system for thalamocortical hidden Parkinsonian properties. Sci Rep 2017; 7:40152. [PMID: 28065938 PMCID: PMC5220381 DOI: 10.1038/srep40152] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2016] [Accepted: 12/01/2016] [Indexed: 12/13/2022] Open
Abstract
Real-time estimation of dynamical characteristics of thalamocortical cells, such as dynamics of ion channels and membrane potentials, is useful and essential in the study of the thalamus in Parkinsonian state. However, measuring the dynamical properties of ion channels is extremely challenging experimentally and even impossible in clinical applications. This paper presents and evaluates a real-time estimation system for thalamocortical hidden properties. For the sake of efficiency, we use a field programmable gate array for strictly hardware-based computation and algorithm optimization. In the proposed system, the FPGA-based unscented Kalman filter is implemented into a conductance-based TC neuron model. Since the complexity of TC neuron model restrains its hardware implementation in parallel structure, a cost efficient model is proposed to reduce the resource cost while retaining the relevant ionic dynamics. Experimental results demonstrate the real-time capability to estimate thalamocortical hidden properties with high precision under both normal and Parkinsonian states. While it is applied to estimate the hidden properties of the thalamus and explore the mechanism of the Parkinsonian state, the proposed method can be useful in the dynamic clamp technique of the electrophysiological experiments, the neural control engineering and brain-machine interface studies.
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Affiliation(s)
- Shuangming Yang
- School of Electrical Engineering and Automation, Tianjin University, 300072, Tianjin, China
| | - Bin Deng
- School of Electrical Engineering and Automation, Tianjin University, 300072, Tianjin, China
| | - Jiang Wang
- School of Electrical Engineering and Automation, Tianjin University, 300072, Tianjin, China
| | - Huiyan Li
- School of Automation and Electrical Engineering, Tianjin University of Technology and Educations, 300222, Tianjin, China
| | - Chen Liu
- School of Electrical Engineering and Automation, Tianjin University, 300072, Tianjin, China.,Department of Electrical Engineering and Computer Science, Case Western Reserve University, 44106, Cleveland, Ohio, USA
| | - Chris Fietkiewicz
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, 44106, Cleveland, Ohio, USA
| | - Kenneth A Loparo
- Department of Electrical Engineering and Computer Science, Case Western Reserve University, 44106, Cleveland, Ohio, USA
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25
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Krucoff MO, Rahimpour S, Slutzky MW, Edgerton VR, Turner DA. Enhancing Nervous System Recovery through Neurobiologics, Neural Interface Training, and Neurorehabilitation. Front Neurosci 2016; 10:584. [PMID: 28082858 PMCID: PMC5186786 DOI: 10.3389/fnins.2016.00584] [Citation(s) in RCA: 85] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2016] [Accepted: 12/06/2016] [Indexed: 12/21/2022] Open
Abstract
After an initial period of recovery, human neurological injury has long been thought to be static. In order to improve quality of life for those suffering from stroke, spinal cord injury, or traumatic brain injury, researchers have been working to restore the nervous system and reduce neurological deficits through a number of mechanisms. For example, neurobiologists have been identifying and manipulating components of the intra- and extracellular milieu to alter the regenerative potential of neurons, neuro-engineers have been producing brain-machine and neural interfaces that circumvent lesions to restore functionality, and neurorehabilitation experts have been developing new ways to revitalize the nervous system even in chronic disease. While each of these areas holds promise, their individual paths to clinical relevance remain difficult. Nonetheless, these methods are now able to synergistically enhance recovery of native motor function to levels which were previously believed to be impossible. Furthermore, such recovery can even persist after training, and for the first time there is evidence of functional axonal regrowth and rewiring in the central nervous system of animal models. To attain this type of regeneration, rehabilitation paradigms that pair cortically-based intent with activation of affected circuits and positive neurofeedback appear to be required-a phenomenon which raises new and far reaching questions about the underlying relationship between conscious action and neural repair. For this reason, we argue that multi-modal therapy will be necessary to facilitate a truly robust recovery, and that the success of investigational microscopic techniques may depend on their integration into macroscopic frameworks that include task-based neurorehabilitation. We further identify critical components of future neural repair strategies and explore the most updated knowledge, progress, and challenges in the fields of cellular neuronal repair, neural interfacing, and neurorehabilitation, all with the goal of better understanding neurological injury and how to improve recovery.
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Affiliation(s)
- Max O Krucoff
- Department of Neurosurgery, Duke University Medical Center Durham, NC, USA
| | - Shervin Rahimpour
- Department of Neurosurgery, Duke University Medical Center Durham, NC, USA
| | - Marc W Slutzky
- Department of Physiology, Feinberg School of Medicine, Northwestern UniversityChicago, IL, USA; Department of Neurology, Feinberg School of Medicine, Northwestern UniversityChicago, IL, USA
| | - V Reggie Edgerton
- Department of Integrative Biology and Physiology, University of California, Los Angeles Los Angeles, CA, USA
| | - Dennis A Turner
- Department of Neurosurgery, Duke University Medical CenterDurham, NC, USA; Department of Neurobiology, Duke University Medical CenterDurham, NC, USA; Research and Surgery Services, Durham Veterans Affairs Medical CenterDurham, NC, USA
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26
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Mirabella G, Lebedev MА. Interfacing to the brain's motor decisions. J Neurophysiol 2016; 117:1305-1319. [PMID: 28003406 DOI: 10.1152/jn.00051.2016] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2016] [Revised: 12/18/2016] [Accepted: 12/18/2016] [Indexed: 12/18/2022] Open
Abstract
It has been long known that neural activity, recorded with electrophysiological methods, contains rich information about a subject's motor intentions, sensory experiences, allocation of attention, action planning, and even abstract thoughts. All these functions have been the subject of neurophysiological investigations, with the goal of understanding how neuronal activity represents behavioral parameters, sensory inputs, and cognitive functions. The field of brain-machine interfaces (BMIs) strives for a somewhat different goal: it endeavors to extract information from neural modulations to create a communication link between the brain and external devices. Although many remarkable successes have been already achieved in the BMI field, questions remain regarding the possibility of decoding high-order neural representations, such as decision making. Could BMIs be employed to decode the neural representations of decisions underlying goal-directed actions? In this review we lay out a framework that describes the computations underlying goal-directed actions as a multistep process performed by multiple cortical and subcortical areas. We then discuss how BMIs could connect to different decision-making steps and decode the neural processing ongoing before movements are initiated. Such decision-making BMIs could operate as a system with prediction that offers many advantages, such as shorter reaction time, better error processing, and improved unsupervised learning. To present the current state of the art, we review several recent BMIs incorporating decision-making components.
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Affiliation(s)
- Giovanni Mirabella
- Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Italy.,Department of Physiology and Pharmacology "V. Erspamer," University of Rome La Sapienza, Rome, Italy; and
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27
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Yin A, An J, Lehew G, Lebedev MA, Nicolelis MAL. An automatic experimental apparatus to study arm reaching in New World monkeys. J Neurosci Methods 2016; 264:57-64. [PMID: 26928257 DOI: 10.1016/j.jneumeth.2016.02.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2015] [Revised: 02/18/2016] [Accepted: 02/22/2016] [Indexed: 11/30/2022]
Abstract
BACKGROUND Several species of the New World monkeys have been used as experimental models in biomedical and neurophysiological research. However, a method for controlled arm reaching tasks has not been developed for these species. NEW METHOD We have developed a fully automated, pneumatically driven, portable, and reconfigurable experimental apparatus for arm-reaching tasks suitable for these small primates. RESULTS We have utilized the apparatus to train two owl monkeys in a visually-cued arm-reaching task. Analysis of neural recordings demonstrates directional tuning of the M1 neurons. COMPARISON WITH EXISTING METHOD(S) Our apparatus allows automated control, freeing the experimenter from manual experiments. CONCLUSION The presented apparatus provides a valuable tool for conducting neurophysiological research on New World monkeys.
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Affiliation(s)
- Allen Yin
- Department of Biomedical Engineering, Duke University, Durham, NC, USA; Duke Center for Neuroengineering, Duke University, Durham, NC, USA
| | - Jehi An
- Department of Biomedical Engineering, Duke University, Durham, NC, USA; Duke Center for Neuroengineering, Duke University, Durham, NC, USA
| | - Gary Lehew
- Duke Center for Neuroengineering, Duke University, Durham, NC, USA
| | - Mikhail A Lebedev
- Department of Biomedical Engineering, Duke University, Durham, NC, USA; Duke Center for Neuroengineering, Duke University, Durham, NC, USA
| | - Miguel A L Nicolelis
- Department of Biomedical Engineering, Duke University, Durham, NC, USA; Duke Center for Neuroengineering, Duke University, Durham, NC, USA; Department of Neurobiology, Duke University Medical Center, Durham, NC, USA; Edmond and Lily Safra International Institute of Neuroscience of Natal, Natal, Brazil; Department of Psychology and Neuroscience, Duke University, Durham, NC, USA.
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28
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Pais-Vieira M, Chiuffa G, Lebedev M, Yadav A, Nicolelis MAL. Building an organic computing device with multiple interconnected brains. Sci Rep 2015; 5:11869. [PMID: 26158615 PMCID: PMC4497302 DOI: 10.1038/srep11869] [Citation(s) in RCA: 56] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2015] [Accepted: 06/09/2015] [Indexed: 11/29/2022] Open
Abstract
Recently, we proposed that Brainets, i.e. networks formed by multiple animal brains, cooperating and exchanging information in real time through direct brain-to-brain interfaces, could provide the core of a new type of computing device: an organic computer. Here, we describe the first experimental demonstration of such a Brainet, built by interconnecting four adult rat brains. Brainets worked by concurrently recording the extracellular electrical activity generated by populations of cortical neurons distributed across multiple rats chronically implanted with multi-electrode arrays. Cortical neuronal activity was recorded and analyzed in real time, and then delivered to the somatosensory cortices of other animals that participated in the Brainet using intracortical microstimulation (ICMS). Using this approach, different Brainet architectures solved a number of useful computational problems, such as discrete classification, image processing, storage and retrieval of tactile information, and even weather forecasting. Brainets consistently performed at the same or higher levels than single rats in these tasks. Based on these findings, we propose that Brainets could be used to investigate animal social behaviors as well as a test bed for exploring the properties and potential applications of organic computers.
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Affiliation(s)
- Miguel Pais-Vieira
- Department of Neurobiology, Duke University, Durham, North Carolina 27710
| | - Gabriela Chiuffa
- Department of Neurobiology, Duke University, Durham, North Carolina 27710
| | - Mikhail Lebedev
- 1] Department of Neurobiology, Duke University, Durham, North Carolina 27710 [2] Duke Center for Neuroengineering, Duke University, Durham, North Carolina 27710
| | - Amol Yadav
- Department of Biomedical Engineering, Duke University, Durham, North Carolina 27710
| | - Miguel A L Nicolelis
- 1] Department of Neurobiology, Duke University, Durham, North Carolina 27710 [2] Department of Biomedical Engineering, Duke University, Durham, North Carolina 27710 [3] Department of Psychology and Neuroscience, Duke University, Durham, North Carolina 27710 [4] Duke Center for Neuroengineering, Duke University, Durham, North Carolina 27710 [5] Edmond and Lily Safra International Institute for Neuroscience of Natal, Natal, Brazil
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