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  • JOURNAL ARTICLE
    De Marcellis A, Palange E, Nubile L, Faccio M, Stanchieri GDP, Constandinou TGet al., 2016,

    A Pulsed Coding Technique Based on Optical UWB Modulation for High Data Rate Low Power Wireless Implantable Biotelemetry

    , ELECTRONICS, Vol: 5, ISSN: 2079-9292
  • CONFERENCE PAPER
    Elia M, Leene LB, Constandinou TG, 2016,

    Continuous-Time Micropower Interface for Neural Recording Applications

    , IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, Pages: 534-537, ISSN: 0271-4302
  • JOURNAL ARTICLE
    Evans BD, Jarvis S, Schultz SR, Nikolic Ket al., 2016,

    PyRhO: A Multiscale Optogenetics Simulation Platform

    , FRONTIERS IN NEUROINFORMATICS, Vol: 10, ISSN: 1662-5196
  • JOURNAL ARTICLE
    Fagerholm ED, Scott G, Shew WL, Song C, Leech R, Knopfel T, Sharp DJet al., 2016,

    Cortical Entropy, Mutual Information and Scale-Free Dynamics in Waking Mice

    , CEREBRAL CORTEX, Vol: 26, Pages: 3945-3952, ISSN: 1047-3211
  • CONFERENCE PAPER
    Faisal A, Krebs HI, Pedotti A, 2016,

    Hands on neurotechnology

    , Pages: VII-VIII
  • BOOK CHAPTER
    Faisal AA, Neishabouri A, 2016,

    Fundamental Constraints on the Evolution of Neurons

    , The Wiley-Blackwell Handbook of Evolutionary Neuroscience, Pages: 153-172, ISBN: 9781118316757

    © 2017 John Wiley & Sons, Ltd. All rights reserved. This chapter focuses on two fundamental constraints that apply to any form of information processing system, be it a cell, a brain or a computer: Noise (random variability) and Energy (metabolic demand). It shows how these two constraints are fundamentally limited by the basic biophysical properties of the brain's building blocks (protein, fats, and salty water) and link nervous system structure to function. The understanding of the interdependence of information and energy has profoundly influenced the development of efficient telecommunication systems and computers. Noise diminishes the capacity to receive, process, and direct information, the key tasks of the brain. Investing in the brain's design can reduce the effects of noise, but this investment often increases energetic requirements, which is likely to be evolutionary unfavourable. The stochasticity of the system becomes critical when its inherent randomness makes it operationally infeasible, that is, when random action potential (APs) become as common as evoked APs.

  • BOOK CHAPTER
    Fernández-Dueñas V, Morató X, Knöpfel T, Ciruela Fet al., 2016,

    Dynamic recording of membrane potential from hippocampal neurons by using a FRET-based voltage biosensor

    , Neuromethods, Pages: 447-454

    © Springer Science+Business Media New York 2016. Fluorescence-based biosensors for membrane voltage (mV) allow dynamic optical recording of neuronal activity. Interestingly, the development of genetically encoded voltage indicators constitute a good alternative to classical voltage-sensitive dyes, thus allowing overcoming some of the inherent problems (e.g., optical noise, etc.) associated with these organic compounds. Here, we show the use of a genetically encoded voltage-sensitive fluorescent protein (VSFP), namely the VSFP2.32, which contains a mCerulean and Citrine tandem engaging in a constitutive fluorescent resonance energy transfer (FRET) process. By expressing VSFP2.32 in hippocampal cultured neurons, we were able to monitor mV alterations in single neurons by recording VSFP2.32 conformation-mediated FRET changes in a real-time mode.

  • CONFERENCE PAPER
    Frehlick Z, Williams I, Constandinou TG, 2016,

    Improving Neural Spike Sorting Performance using Template Enhancement

    , 12th IEEE Biomedical Circuits and Systems Conference (BioCAS), Publisher: IEEE, Pages: 524-527, ISSN: 2163-4025
  • SOFTWARE
    Goodman DFM, Stimberg M, Brette R, 2016,

    Brian 2.0 simulator

    Brian is a simulator for spiking neural networks. It is written in the Python programming language and is available on almost all platforms. We believe that a simulator should not only save the time of processors, but also the time of scientists. Brian is therefore designed to be easy to learn and use, highly flexible and easily extensible.

  • JOURNAL ARTICLE
    Guven O, Eftekhar A, Kindt W, Constandinou TGet al., 2016,

    Computationally efficient real-time interpolation algorithm for non-uniform sampled biosignals

    , HEALTHCARE TECHNOLOGY LETTERS, Vol: 3, Pages: 105-110, ISSN: 2053-3713
  • JOURNAL ARTICLE
    Hahne JM, Farina D, Jiang N, Liebetanz Det al., 2016,

    A novel percutaneous electrode implant for improving robustness in advanced myoelectric control

    , Frontiers in Neuroscience, Vol: 10, ISSN: 1662-4548

    © 2016 Hahne, Farina, Jiang and Liebetanz. Despite several decades of research, electrically powered hand and arm prostheses are still controlled with very simple algorithms that process the surface electromyogram (EMG) of remnant muscles to achieve control of one prosthetic function at a time. More advanced machine learning methods have shown promising results under laboratory conditions. However, limited robustness has largely prevented the transfer of these laboratory advances to clinical applications. In this paper, we introduce a novel percutaneous EMG electrode to be implanted chronically with the aim of improving the reliability of EMG detection in myoelectric control. The proposed electrode requires a minimally invasive procedure for its implantation, similar to a cosmetic micro-dermal implant. Moreover, being percutaneous, it does not require power and data telemetry modules. Four of these electrodes were chronically implanted in the forearm of an able-bodied human volunteer for testing their characteristics. The implants showed significantly lower impedance and greater robustness against mechanical interference than traditional surface EMG electrodes used for myoelectric control. Moreover, the EMG signals detected by the proposed systems allowed more stable control performance across sessions in different days than that achieved with classic EMG electrodes. In conclusion, the proposed implants may be a promising interface for clinically available prostheses.

  • JOURNAL ARTICLE
    Hammad SH, Kamavuako EN, Farina D, Jensen Wet al., 2016,

    Simulation of a Real-Time Brain Computer Interface for Detecting a Self-Paced Hitting Task.

    , Neuromodulation, Vol: 19, Pages: 804-811

    OBJECTIVES: An invasive brain-computer interface (BCI) is a promising neurorehabilitation device for severely disabled patients. Although some systems have been shown to work well in restricted laboratory settings, their utility must be tested in less controlled, real-time environments. Our objective was to investigate whether a specific motor task could be reliably detected from multiunit intracortical signals from freely moving animals in a simulated, real-time setting. MATERIALS AND METHODS: Intracortical signals were first obtained from electrodes placed in the primary motor cortex of four rats that were trained to hit a retractable paddle (defined as a "Hit"). In the simulated real-time setting, the signal-to-noise-ratio was first increased by wavelet denoising. Action potentials were detected, and features were extracted (spike count, mean absolute values, entropy, and combination of these features) within pre-defined time windows (200 ms, 300 ms, and 400 ms) to classify the occurrence of a "Hit." RESULTS: We found higher detection accuracy of a "Hit" (73.1%, 73.4%, and 67.9% for the three window sizes, respectively) when the decision was made based on a combination of features rather than on a single feature. However, the duration of the window length was not statistically significant (p = 0.5). CONCLUSION: Our results showed the feasibility of detecting a motor task in real time in a less restricted environment compared to environments commonly applied within invasive BCI research, and they showed the feasibility of using information extracted from multiunit recordings, thereby avoiding the time-consuming and complex task of extracting and sorting single units.

  • CONFERENCE PAPER
    Hassan S, Nightingale AM, Leong CL, Zhang Y, Evans G, Boutelle MG, Niu XZet al., 2016,

    Wearable droplet-based microfluidic sensor device for continuous sampling and real-time analysis

    , Pages: 43-44

    This paper reports a wearable droplet-microfluidic based continuous chemical sensing device. The device combines microdialysis and droplet microfluidic techniques, can continuously sample from interstitial or other body fluids into nanolitre droplets and perform biochemical assays and measurements in situ and in real-time.

  • JOURNAL ARTICLE
    Hemakom A, Goverdovsky V, Looney D, Mandic DPet al., 2016,

    Adaptive-projection intrinsically transformed multivariate empirical mode decomposition in cooperative brain-computer interface applications

    , PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, Vol: 374, ISSN: 1364-503X
  • CONFERENCE PAPER
    Huang JV, Wang Y, Krapp HG, 2016,

    Wall Following in a Semi-closed-loop Fly-Robotic Interface

    , 5th International Conference on Biomimetic and Biohybrid Systems (Living Machines), Publisher: SPRINGER INT PUBLISHING AG, Pages: 85-96, ISSN: 0302-9743
  • JOURNAL ARTICLE
    Imtiaz SA, Mardell J, Saremi-Yarahmadi S, Rodriguez-Villegas Eet al., 2016,

    ECG artefact identification and removal in mHealth systems for continuous patient monitoring

    , HEALTHCARE TECHNOLOGY LETTERS, Vol: 3, Pages: 171-176, ISSN: 2053-3713
  • JOURNAL ARTICLE
    Jager P, Ye Z, Yu X, Zagoraiou L, Prekop H-T, Partanen J, Jessell TM, Wisden W, Brickley SG, Delogu Aet al., 2016,

    Tectal-derived interneurons contribute to phasic and tonic inhibition in the visual thalamus

    , Nature Communications, Vol: 7, ISSN: 2041-1723
  • CONFERENCE PAPER
    Jameel ASMM, Mace M, Wang S, Vaidyanathan R, Al Mamun KAet al., 2016,

    Predicting Movement and Laterality From Deep Brain Local Field Potentials

    , 1st International Conference on Medical Engineering, Health Informatics and Technology (MediTec), Publisher: IEEE
  • CONFERENCE PAPER
    Jeanneret M, Bagnato C, Allievi AG, Burdet Eet al., 2016,

    A Versatile Robotic Haptic Stimulator to Study the Influence of Pain on Human Motor Control and Learning

    , 10th International Conference on Haptics - Perception, Devices, Control, and Applications (EuroHaptics), Publisher: SPRINGER INT PUBLISHING AG, Pages: 101-110, ISSN: 0302-9743
  • JOURNAL ARTICLE
    Kim Y, Warren SC, Stone JM, Knight JC, Neil MAA, Paterson C, Dunsby CW, French PMWet al., 2016,

    Adaptive Multiphoton Endomicroscope Incorporating a Polarization-Maintaining Multicore Optical Fibre

    , IEEE JOURNAL OF SELECTED TOPICS IN QUANTUM ELECTRONICS, Vol: 22, ISSN: 1077-260X
  • JOURNAL ARTICLE
    Kovac M, 2016,

    ROBOTICS. Learning from nature how to land aerial robots.

    , Science, Vol: 352, Pages: 895-896
  • JOURNAL ARTICLE
    Kozlov AS, Gentner TQ, 2016,

    Central auditory neurons have composite receptive fields

    , PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, Vol: 113, Pages: 1441-1446, ISSN: 0027-8424
  • CONFERENCE PAPER
    Lauteslager T, Tommer M, Kjelgard KG, Lande TS, Constandinou TGet al., 2016,

    Intracranial Heart Rate Detection Using UWB Radar

    , 12th IEEE Biomedical Circuits and Systems Conference (BioCAS), Publisher: IEEE, Pages: 119-122, ISSN: 2163-4025
  • CONFERENCE PAPER
    Leene LB, Constandinou TG, 2016,

    A 2.7 mu W/MIPS, 0.88GOPS/mm(2) Distributed Processor for Implantable Brain Machine Interfaces

    , 12th IEEE Biomedical Circuits and Systems Conference (BioCAS), Publisher: IEEE, Pages: 360-363, ISSN: 2163-4025
  • JOURNAL ARTICLE
    Leppa E, Linden A-M, Aller MI, Wulff P, Vekovischeva O, Luscher B, Lueddens H, Wisden W, Korpi ERet al., 2016,

    Increased Motor-Impairing Effects of the Neuroactive Steroid Pregnanolone in Mice with Targeted Inactivation of the GABA(A) Receptor gamma 2 Subunit in the Cerebellum

    , FRONTIERS IN PHARMACOLOGY, Vol: 7, ISSN: 1663-9812
  • CONFERENCE PAPER
    Li L, Violante I, Ross E, Leech R, Hampshire A, Carmichael D, Sharp Det al., 2016,

    BRAIN NETWORK MODULATION WITH NON-INVASIVE BRAIN STIMULATION

    , Annual Meeting of the Association-of-British-Neurologists (ABN), Publisher: BMJ PUBLISHING GROUP, ISSN: 0022-3050
  • JOURNAL ARTICLE
    Li Z, Yang C, Burdet E, 2016,

    An Overview of Biomedical Robotics and Bio-Mechatronics Systems and Applications

    , IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, Vol: 46, Pages: 869-874, ISSN: 2168-2216
  • JOURNAL ARTICLE
    Lin C, Wang B-H, Jiang N, Xu R, Mrachacz-Kersting N, Farina Det al., 2016,

    Discriminative Manifold Learning Based Detection of Movement-Related Cortical Potentials.

    , IEEE Trans Neural Syst Rehabil Eng, Vol: 24, Pages: 921-927

    The detection of voluntary motor intention from EEG has been applied to closed-loop brain-computer interfacing (BCI). The movement-related cortical potential (MRCP) is a low frequency component of the EEG signal, which represents movement intention, preparation, and execution. In this study, we aim at detecting MRCPs from single-trial EEG traces. For this purpose, we propose a detector based on a discriminant manifold learning method, called locality sensitive discriminant analysis (LSDA), and we test it in both online and offline experiments with executed and imagined movements. The online and offline experimental results demonstrated that the proposed LSDA approach for MRCP detection outperformed the Locality Preserving Projection (LPP) approach, which was previously shown to be the most accurate algorithm so far tested for MRCP detection. For example, in the online tests, the performance of LSDA was superior than LPP in terms of a significant reduction in false positives (FP) (passive FP: 1.6 ±0.9/min versus 2.9 ±1.0/min, p = 0.002, active FP: 2.2 ±0.8/min versus 2.7 ±0.6/min , p = 0.03 ), for a similar rate of true positives. In conclusion, the proposed LSDA based MRCP detection method is superior to previous approaches and is promising for developing patient-driven BCI systems for motor function rehabilitation as well as for neuroscience research.

  • CONFERENCE PAPER
    Liu Y, Pereira JL, Constandinou TG, 2016,

    Clockless Continuous-Time Neural Spike Sorting: Method, Implementation and Evaluation

    , IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, Pages: 538-541, ISSN: 0271-4302
  • JOURNAL ARTICLE
    Looney D, Goverdovsky V, Rosenzweig I, Morrell MJ, Mandic DPet al., 2016,

    Wearable In-Ear Encephalography Sensor for Monitoring Sleep Preliminary Observations from Nap Studies

    , ANNALS OF THE AMERICAN THORACIC SOCIETY, Vol: 13, Pages: 2229-2233, ISSN: 1546-3222

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