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      Intraneural stimulation elicits discrimination of textural features by artificial fingertip in intact and amputee humans

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          Abstract

          Restoration of touch after hand amputation is a desirable feature of ideal prostheses. Here, we show that texture discrimination can be artificially provided in human subjects by implementing a neuromorphic real-time mechano-neuro-transduction (MNT), which emulates to some extent the firing dynamics of SA1 cutaneous afferents. The MNT process was used to modulate the temporal pattern of electrical spikes delivered to the human median nerve via percutaneous microstimulation in four intact subjects and via implanted intrafascicular stimulation in one transradial amputee. Both approaches allowed the subjects to reliably discriminate spatial coarseness of surfaces as confirmed also by a hybrid neural model of the median nerve. Moreover, MNT-evoked EEG activity showed physiologically plausible responses that were superimposable in time and topography to the ones elicited by a natural mechanical tactile stimulation. These findings can open up novel opportunities for sensory restoration in the next generation of neuro-prosthetic hands.

          DOI: http://dx.doi.org/10.7554/eLife.09148.001

          eLife digest

          Our hands provide us with a wide variety of information about our surroundings, enabling us to detect pain, temperature and pressure. Our sense of touch also allows us to interact with objects by feeling their texture and solidity. However, completely reproducing a sense of touch in artificial or prosthetic hands has proven challenging. While commercial prostheses can mimic the range of movements of natural limbs, even the latest experimental prostheses have only a limited ability to ‘feel’ the objects being manipulated. Oddo, Raspopovic et al. have now brought this ability a step closer by exploiting an artificial fingertip and appropriate neural interfaces through which different textures can be identified.

          The initial experiments were performed in four healthy volunteers with intact limbs. Oddo, Raspopovic et al. connected the artificial fingertip to the volunteers via an electrode inserted into a nerve in the arm. When moved over a rough surface, sensors in the fingertip produced patterns of electrical pulses that stimulated the nerve, causing the volunteers to feel like they were touching the surface. The volunteers were even able to tell the difference between the different surface textures the artificial fingertip moved across.

          The temporary electrodes used in this group of volunteers are unsuitable for use with prosthetic limbs because they can easily be knocked out of position. Therefore, in a further experiment involving a volunteer who had undergone an arm amputation a number of years previously, Oddo, Raspopovic et al. tested an implanted electrode array that could, in principle, remain in place long-term. This volunteer could also identify the different textures the artificial fingertip touched, with a slightly higher degree of accuracy than the previous group of intact volunteers. Further studies are now required to explore the potential of this approach in larger groups of volunteers.

          DOI: http://dx.doi.org/10.7554/eLife.09148.002

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          FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data

          This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow experimental neuroscientists to analyze experimental data. It includes algorithms for simple and advanced analysis, such as time-frequency analysis using multitapers, source reconstruction using dipoles, distributed sources and beamformers, connectivity analysis, and nonparametric statistical permutation tests at the channel and source level. The implementation as toolbox allows the user to perform elaborate and structured analyses of large data sets using the MATLAB command line and batch scripting. Furthermore, users and developers can easily extend the functionality and implement new algorithms. The modular design facilitates the reuse in other software packages.
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            Simple model of spiking neurons.

            A model is presented that reproduces spiking and bursting behavior of known types of cortical neurons. The model combines the biologically plausibility of Hodgkin-Huxley-type dynamics and the computational efficiency of integrate-and-fire neurons. Using this model, one can simulate tens of thousands of spiking cortical neurons in real time (1 ms resolution) using a desktop PC.
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              Coding and use of tactile signals from the fingertips in object manipulation tasks.

              During object manipulation tasks, the brain selects and implements action-phase controllers that use sensory predictions and afferent signals to tailor motor output to the physical properties of the objects involved. Analysis of signals in tactile afferent neurons and central processes in humans reveals how contact events are encoded and used to monitor and update task performance.
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                Author and article information

                Contributors
                Role: Reviewing editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                08 March 2016
                2016
                : 5
                : e09148
                Affiliations
                [1 ]deptThe BioRobotics Institute , Scuola Superiore Sant'Anna , Pisa, Italy
                [2 ]deptBertarelli Foundation Chair in Translational NeuroEngineering, Institute of Bioengineering, School of Engineering , École Polytechnique Fédérale de Lausanne , Lausanne, Switzerland
                [3 ]deptCenter for Neuroprosthetics , École Polytechnique Fédérale de Lausanne , Lausanne, Switzerland
                [4 ]deptLaboratory of Biomedical Robotics & Biomicrosystems , Università Campus Bio-Medico di Roma , Roma, Italy
                [5 ]deptBrain Connectivity Laboratory , IRCCS San Raffaele Pisana , Roma, Italy
                [6 ]deptInstitute of Neurology , Università Campus Bio-Medico di Roma , Roma, Italy
                [7 ]deptInstitute of Neurology , Catholic University of The Sacred Heart , Roma, Italy
                [8 ]Azienda Ospedaliero-Universitaria Pisana , Pisa, Italy
                [9 ]IRCCS Stella Maris Foundation , Pisa, Italy
                [10 ]deptDipartimento di Ricerca Traslazionale e delle Nuove Tecnologie in Medicina e Chirurgia , Università di Pisa , Pisa, Italy
                [11]Massachusetts Institute of Technology , United States
                [12]Massachusetts Institute of Technology , United States
                Author notes
                [†]

                These authors contributed equally to this work.

                Author information
                http://orcid.org/0000-0002-1489-5701
                http://orcid.org/0000-0003-4396-8217
                Article
                09148
                10.7554/eLife.09148
                4798967
                26952132
                e4cc9d98-47e9-4904-b704-193c57dee9f4
                © 2016, Oddo et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 02 June 2015
                : 28 January 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100002207, Directorate-General for Communications Networks, Content and Technology;
                Award ID: EU Grant CP-FP-INFSO 224012 TIME project
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100002207, Directorate-General for Communications Networks, Content and Technology;
                Award ID: EU Grant FET 611687 NEBIAS Project
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100002207, Directorate-General for Communications Networks, Content and Technology;
                Award ID: EU Grant FP7-NMP 228844 NANOBIOTOUCH project
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100003196, Ministero della Salute;
                Award ID: Italian NEMESIS (Neurocontrolled mechatronic hand prosthesis)
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100003407, Ministero dell’Istruzione, dell’Università e della Ricerca;
                Award ID: Italian project PRIN/HandBot
                Award Recipient :
                Funded by: Italian National Institute for Insturance against Industrial Injuries;
                Award ID: National project PPR2 (Control of hand prosthesis by invasive neural interfaces)
                Award Recipient :
                Funded by: Swiss National Competence Center in Research in Robotics;
                Award ID: NCCR Robotics
                Award Recipient :
                Funded by: Wyss Center for Bio and Neuroengineering;
                Award ID: ENABLE Project
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Neuroscience
                Custom metadata
                2.5
                Delivering specific patterns of electrical activity to the median nerve of the arm triggers reliable sensations of texture, suggesting that it may ultimately be possible to restore complex tactile information to users of prosthetic limbs.

                Life sciences
                intraneural stimulation,touch restoration,artificial touch,hand neuroprosthetics,tactile code,neuromorphic stimuli,human

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