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Neural interface

Elias Abou Zeid, Alborz Rezazadeh Sereshkeh, Tom Chau
OBJECTIVE: In recent years, the readiness potential (RP), a type of pre-movement neural activity, has been investigated for asynchronous electroencephalogram (EEG)-based brain-computer interfaces (BCIs). Since the RP is attenuated for involuntary movements, a BCI driven by RP alone could facilitate intentional control amid a plethora of unintentional movements. Previous studies have attempted single trial classification of RP via spatial and temporal filtering methods, or by combining the RP with event-related desynchronization...
October 20, 2016: Journal of Neural Engineering
David S Freedman, Joseph B Schroeder, Gregory I Telian, Zhengyang Zhang, Smrithi Sunil, Jason T Ritt
OBJECTIVE: Behavioral neuroscience studies in freely moving rodents require small, light-weight implants to facilitate neural recording and stimulation. Our goal was to develop an integrated package of 3D printed parts and assembly aids for labs to rapidly fabricate, with minimal training, an implant that combines individually positionable microelectrodes, an optical fiber, zero insertion force (ZIF-clip) headstage connection, and secondary recording electrodes, e.g. for electromyography (EMG)...
October 20, 2016: Journal of Neural Engineering
Richard A Normann, Eduardo Fernandez
This paper briefly describes some of the recent progress in the development of penetrating microelectrode arrays and highlights the use of two of these devices, Utah electrode arrays and Utah slanted electrode arrays, in two therapeutic interventions: recording volitional skeletal motor commands from the central nervous system, and recording motor commands and evoking somatosensory percepts in the peripheral nervous system (PNS). The paper also briefly explores other potential sites for microelectrode array interventions that could be profitably pursued and that could have important consequences in enhancing the quality of life of patients that has been compromised by disorders of the central and PNSs...
October 20, 2016: Journal of Neural Engineering
Cyril G Eleftheriou, Jonas B Zimmermann, Henrik D Kjeldsen, Moshe David-Pur, Yael Hanein, Evelyne Sernagor
The choice of electrode material is of paramount importance in neural prosthetic devices. Electrodes must be biocompatible yet able to sustain repetitive current injections in a highly corrosive environment. We explored the suitability of carbon nanotube (CNT) electrodes to stimulate retinal ganglion cells (RGCs) in a mouse model of outer retinal degeneration. We investigated morphological changes at the bio-hybrid interface and changes in RGC responses to electrical stimulation following prolonged in vitro coupling to CNT electrodes...
October 11, 2016: Biomaterials
Jenna K Zalewski, Joshua H Mo, Simone Heber, Annie Heroux, Richard G Gardner, Jeffrey D Hildebrand, Andrew P VanDemark
Shroom-mediated remodeling of the actomyosin cytoskeleton is a critical driver of cellular shape and tissue morphology that underlies the development of many tissues, including the neural tube, eye, intestines, and vasculature. Shroom uses a conserved SD2 domain to direct the subcellular localization of Rho-kinase (Rock) which in turn drives changes in the cytoskeleton and cellular morphology through its ability to phosphorylate and activate non-muscle myosin II. Here, we present the structure of the human Shroom-Rock binding module, revealing an unexpected stoichiometry for Shrm in which two Shrm SD2 domains bind independent surfaces on Rock...
October 10, 2016: Journal of Biological Chemistry
Ferruccio Pisanello, Leonardo Sileo, Massimo De Vittorio
[This corrects the article on p. 70 in vol. 10, PMID: 27013939.].
2016: Frontiers in Neuroscience
Johanna Metsomaa, Jukka Sarvas, Risto J Ilmoniemi
OBJECTIVE: Blind source separation (BSS) can be used to decompose complex electroencephalography (EEG) or magnetoencephalography data into simpler components based on statistical assumptions without using a physical model. Applications include brain-computer interfaces, artifact removal and identifying parallel neural processes. We wish to address the issue of applying BSS to event-related responses which is challenging because of non-stationary data. METHODS: We introduce a new BSS approach called momentary-uncorrelated component analysis (MUCA) which is tailored for event-related multi-trial data...
October 12, 2016: IEEE Transactions on Bio-medical Engineering
Alexey Petrushin, Lorenzo Ferrara, Axel Blau
OBJECTIVE: In light of recent progress in mapping neural function to behavior, we briefly and selectively review past and present endeavors to reveal and reconstruct nervous system function in Caenorhabditis elegans through simulation. APPROACH: Rather than presenting an all-encompassing review on the mathematical modeling of C. elegans, this contribution collects snapshots of pathfinding key works and emerging technologies that recent single- and multi-center simulation initiatives are building on...
October 14, 2016: Journal of Neural Engineering
Yi C Zhang, Alexander C Kagen
TensorFlow is a second-generation open-source machine learning software library with a built-in framework for implementing neural networks in wide variety of perceptual tasks. Although TensorFlow usage is well established with computer vision datasets, the TensorFlow interface with DICOM formats for medical imaging remains to be established. Our goal is to extend the TensorFlow API to accept raw DICOM images as input; 1513 DaTscan DICOM images were obtained from the Parkinson's Progression Markers Initiative (PPMI) database...
October 11, 2016: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
Christian Herff, Tanja Schultz
Speech interfaces have become widely accepted and are nowadays integrated in various real-life applications and devices. They have become a part of our daily life. However, speech interfaces presume the ability to produce intelligible speech, which might be impossible due to either loud environments, bothering bystanders or incapabilities to produce speech (i.e., patients suffering from locked-in syndrome). For these reasons it would be highly desirable to not speak but to simply envision oneself to say words or sentences...
2016: Frontiers in Neuroscience
Noman Naseer, Nauman Khalid Qureshi, Farzan Majeed Noori, Keum-Shik Hong
We analyse and compare the classification accuracies of six different classifiers for a two-class mental task (mental arithmetic and rest) using functional near-infrared spectroscopy (fNIRS) signals. The signals of the mental arithmetic and rest tasks from the prefrontal cortex region of the brain for seven healthy subjects were acquired using a multichannel continuous-wave imaging system. After removal of the physiological noises, six features were extracted from the oxygenated hemoglobin (HbO) signals. Two- and three-dimensional combinations of those features were used for classification of mental tasks...
2016: Computational Intelligence and Neuroscience
Alexei L Vyssotski, Anna E Stepien, Georg B Keller, Richard H R Hahnloser
What cortical inputs are provided to motor control areas while they drive complex learned behaviors? We study this question in the nucleus interface of the nidopallium (NIf), which is required for normal birdsong production and provides the main source of auditory input to HVC, the driver of adult song. In juvenile and adult zebra finches, we find that spikes in NIf projection neurons precede vocalizations by several tens of milliseconds and are insensitive to distortions of auditory feedback. We identify a local isometry between NIf output and vocalizations: quasi-identical notes produced in different syllables are preceded by highly similar NIf spike patterns...
October 2016: PLoS Biology
Shahab Shahdoost, Randolph Nudo, Pedram Mohseni
Brain-machine-body interfaces (BMBIs) aim to create an artificial connection in the nervous system by converting neural activity recorded from one cortical region to electrical stimuli delivered to another cortical region, spinal cord, or muscles in real-time. In particular, conditioning-mode BMBIs utilize such activity-dependent stimulation strategies to induce functional re-organization in the nervous system and promote functional recovery after injury by exploiting mechanisms underlying neuroplasticity. This paper reports on reconfigurable, field-programmable gate array (FPGA)-based implementation of a translation algorithm to extract multichannel stimulus trigger signals from intracortical neural spike activity...
October 5, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Suresh Kondati Natarajan, Jörg Behler
Solid-liquid interfaces have received considerable attention in recent years due to their central role in many technologically relevant fields like electrochemistry, heterogeneous catalysis and corrosion. As the chemical processes in these examples take place primarily at the interface, understanding the structural and dynamical properties of the interfacial water molecules is of vital importance. Here, we use a first-principles quality high-dimensional neural network potential built from dispersion-corrected density functional theory data in molecular dynamics simulations to investigate water-copper interfaces as a prototypical case...
October 7, 2016: Physical Chemistry Chemical Physics: PCCP
Onur Kilic, David Pamies, Emily Lavell, Paula Schiapparelli, Yun Feng, Thomas Hartung, Anna Bal-Price, Helena T Hogberg, Alfredo Quinones-Hinojosa, Hugo Guerrero-Cazares, Andre Levchenko
Migration of neural progenitors in the complex tissue environment of the central nervous system is not well understood. Progress in this area has the potential to drive breakthroughs in neuroregenerative therapies, brain cancer treatments, and neurodevelopmental studies. To a large extent, advances have been limited due to a lack of controlled environments recapitulating characteristics of the central nervous system milieu. Reductionist cell culture models are frequently too simplistic, and physiologically more relevant approaches such as ex vivo brain slices or in situ experiments provide little control and make information extraction difficult...
October 18, 2016: Lab on a Chip
Larissa Brentano Capeletti, Mateus Borba Cardoso, João Henrique Zimnoch Dos Santos, Wei He
Thin films of silica prepared by a sol-gel process are becoming a feasible coating option for surface modification of implantable neural sensors without imposing adverse effects on the devices' electrical properties. In order to advance the application of such silica-based coatings in the context of neural interfacing, the characteristics of silica sol-gel are further tailored to gain active control of interactions between cells and the coating materials. By incorporating various readily available organotrialkoxysilanes carrying distinct organic functional groups during the sol-gel process, a library of hybrid organosilica coatings is developed and investigated...
October 7, 2016: ACS Applied Materials & Interfaces
Sergio Santos, Chia-Yun Lai, Carlo A Amadei, Karim R Gadelrab, Tzu-Chieh Tang, Albert Verdaguer, Victor Barcons, Josep Font, Jaime Colchero, Matteo Chiesa
Here we present the Mendeleev-Meyer Force Project which aims at tabulating all materials and substances in a fashion similar to the periodic table. The goal is to group and tabulate substances using nanoscale force footprints rather than atomic number or electronic configuration as in the periodic table. The process is divided into: (1) acquiring nanoscale force data from materials, (2) parameterizing the raw data into standardized input features to generate a library, (3) feeding the standardized library into an algorithm to generate, enhance or exploit a model to identify a material or property...
October 14, 2016: Nanoscale
Sol Bee Han, Young Cheol Yoon, Jong Won Kwon
BACKGROUND AND PURPOSE: Slice-Encoding Metal Artifact Correction (SEMAC) sequence is one of the metal artifact reduction techniques of anatomical structure, but there has been no report about evaluation of post-operative complications. The purpose of this article is to compare the anatomical visibility between fast spin echo (FSE) and FSE-SEMAC and to evaluate the additional value of FSE-SEMAC in diagnostic confidence of the complications. MATERIALS AND METHODS: We conducted a retrospective study with 54 patients who received lumbar spinal surgery and MR images including FSE-SEMAC...
2016: PloS One
Alianna J Maren
Effective Brain-Computer Interfaces (BCIs) require that the time-varying activation patterns of 2-D neural ensembles be modelled. The cluster variation method (CVM) offers a means for the characterization of 2-D local pattern distributions. This paper provides neuroscientists and BCI researchers with a CVM tutorial that will help them to understand how the CVM statistical thermodynamics formulation can model 2-D pattern distributions expressing structural and functional dynamics in the brain. The premise is that local-in-time free energy minimization works alongside neural connectivity adaptation, supporting the development and stabilization of consistent stimulus-specific responsive activation patterns...
September 30, 2016: Brain Sciences
Peter V Coveney, Edward R Dougherty, Roger R Highfield
The current interest in big data, machine learning and data analytics has generated the widespread impression that such methods are capable of solving most problems without the need for conventional scientific methods of inquiry. Interest in these methods is intensifying, accelerated by the ease with which digitized data can be acquired in virtually all fields of endeavour, from science, healthcare and cybersecurity to economics, social sciences and the humanities. In multiscale modelling, machine learning appears to provide a shortcut to reveal correlations of arbitrary complexity between processes at the atomic, molecular, meso- and macroscales...
November 13, 2016: Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
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