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  • CONFERENCE PAPER
    Ahmadi N, Constandinou TG, Bouganis C, 2018,

    Spike rate estimation using Bayesian Adaptive Kernel Smoother (BAKS) and its application to brain machine interfaces

    , 40th International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Publisher: IEEE

    Brain Machine Interfaces (BMIs) mostly utilise spike rate as an input feature for decoding a desired motor output as it conveys a useful measure to the underlying neuronal activity. The spike rate is typically estimated by a using non-overlap binning method that yields a coarse estimate. There exist several methods that can produce a smooth estimate which could potentially improve the decoding performance. However, these methods are relatively computationally heavy for real-time BMIs. To address this issue, we propose a new method for estimating spike rate that is able to yield a smooth estimate and also amenable to real-time BMIs. The proposed method, referred to as Bayesian adaptive kernel smoother (BAKS), employs kernel smoothing technique that considers the bandwidth as a random variable with prior distribution which is adaptively updated through a Bayesian framework. With appropriate selection of prior distribution and kernel function, an analytical expression can be achieved for the kernel bandwidth. We apply BAKS and evaluate its impact on of fline BMI decoding performance using Kalman filter. The results show that overlap BAKS improved the decoding performance up to 3.33% and 12.93% compared to overlap and non-overlapbinning methods, respectively, depending on the window size. This suggests the feasibility and the potential use of BAKS method for real-time BMIs.

  • JOURNAL ARTICLE
    Etard OE, Kegler M, Braiman C, Forte AE, Reichenbach JDTet al., 2018,

    Real-time decoding of selective attention from the human auditory brainstem response to continuous speech

    , BioRxiv
  • CONFERENCE PAPER
    Forte AE, Etard OE, Reichenbach JDT, 2018,

    Selective Auditory Attention At The Brainstem Level

    , ARO 2018
  • CONFERENCE PAPER
    Kegler M, Etard OE, Forte AE, Reichenbach JDTet al., 2018,

    Complex Statistical Model for Detecting the Auditory Brainstem Response to Natural Speech and for Decoding Attention from High-Density EEG Recordings

    , ARO 2018
  • JOURNAL ARTICLE
    Liu Y, Pereira JL, Constandinou TG, 2018,

    Event-driven processing for hardware-efficient neural spike sorting

    , JOURNAL OF NEURAL ENGINEERING, Vol: 15, ISSN: 1741-2560
  • JOURNAL ARTICLE
    Luan S, Williams I, Maslik M, Liu Y, De Carvalho F, Jackson A, Quiroga RQ, Constandinou TGet al., 2018,

    Compact standalone platform for neural recording with real-time spike sorting and data logging.

    , J Neural Eng, Vol: 15

    OBJECTIVE: Longitudinal observation of single unit neural activity from large numbers of cortical neurons in awake and mobile animals is often a vital step in studying neural network behaviour and towards the prospect of building effective brain-machine interfaces (BMIs). These recordings generate enormous amounts of data for transmission and storage, and typically require offline processing to tease out the behaviour of individual neurons. Our aim was to create a compact system capable of: (1) reducing the data bandwidth by circa 2 to 3 orders of magnitude (greatly improving battery lifetime and enabling low power wireless transmission in future versions); (2) producing real-time, low-latency, spike sorted data; and (3) long term untethered operation. APPROACH: We have developed a headstage that operates in two phases. In the short training phase a computer is attached and classic spike sorting is performed to generate templates. In the second phase the system is untethered and performs template matching to create an event driven spike output that is logged to a micro-SD card. To enable validation the system is capable of logging the high bandwidth raw neural signal data as well as the spike sorted data. MAIN RESULTS: The system can successfully record 32 channels of raw neural signal data and/or spike sorted events for well over 24 h at a time and is robust to power dropouts during battery changes as well as SD card replacement. A 24 h initial recording in a non-human primate M1 showed consistent spike shapes with the expected changes in neural activity during awake behaviour and sleep cycles. SIGNIFICANCE: The presented platform allows neural activity to be unobtrusively monitored and processed in real-time in freely behaving untethered animals-revealing insights that are not attainable through scheduled recording sessions. This system achieves the lowest power per channel to date and provides a robust, low-latency, low-bandwidth and verifiable outp

  • JOURNAL ARTICLE
    Maslik M, Liu Y, Lande TS, Constandinou TGet al., 2018,

    Continuous-Time Acquisition of Biosignals Using a Charge-Based ADC Topology

    , IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS, Vol: 12, Pages: 471-482, ISSN: 1932-4545
  • CONFERENCE PAPER
    Rapeaux A, Brunton E, Nazarpour K, Constandinou TGet al., 2018,

    Preliminary study of time to recovery of rat sciatic nerve from high frequency alternating current nerve block

    , 40th International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Publisher: IEEE

    High-Frequency alternating current nerve block has great potential for neuromodulation-based therapies. However, no precise measurements have been made of the time needed for nerves to recover from block once the signal has been turned off. This study aims to characterise time to recoveryof the rat sciatic nerve after 30 seconds of block at varying amplitudes and frequencies. Experiments were carried out in-vivo to quantify recovery times and recovery completeness within 0.7s from the end of block. The sciatic nerve was blocked with an alternating square wave signal of amplitudeand frequency ranging from 2 to 9mA and 10 to 50 kHz respectively. To determine the recovery dynamics the nerve was stimulated at 100 Hz after cessation of the blocking stimulus. Electromyogram signals were measured from the gastrocnemius medialis and tibialis anterior muscles during trials as indicators of nerve function. This allowed for nerve recovery to bemeasured with a resolution of 10 ms. This resolution is much greater than previous measurements of nerve recovery in the literature. Times for the nerve to recover to a steady state of activity ranged from 20 to 430 milliseconds and final relative recovery activity at 0.7 seconds spanned 0.2 to 1 approximately. Higher blocking signal amplitudes increased recovery time and decreased recovery completeness. These results suggestthat blocking signal properties affect nerve recovery dynamics, which could help improve neuromodulation therapies and allow more precise comparison of results across studies using different blocking signal parameters.

  • CONFERENCE PAPER
    Saiz Alia M, Askari A, Forte AE, Reichenbach JDTet al., 2018,

    A model of the human auditory brainstem response to running speech

    , ARO 2018
  • JOURNAL ARTICLE
    Sherlock B, Warren SC, Alexandrov Y, Yu F, Stone J, Knight J, Neil MAA, Paterson C, French PMW, Dunsby Cet al., 2018,

    In vivo multiphoton microscopy using a handheld scanner with lateral and axial motion compensation

    , JOURNAL OF BIOPHOTONICS, Vol: 11, ISSN: 1864-063X
  • CONFERENCE PAPER
    Szostak KM, Constandinou TG, 2018,

    Hermetic packaging for implantable microsystems: effectiveness of sequentially electroplated AuSn alloy

    , 40th International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Publisher: IEEE

    With modern microtechnology, there is an aggressive miniaturization of smart devices, despite an increasing level of integration and overall complexity. It is therefore becoming increasingly important to be achieve reliable, compact packaging. For implantable medical devices (IMDs), the package must additionally provide a high quality hermetic environmentto protect the device from the human body. For chip-scale devices, AuSn eutectic bonding offers the possibility of forming compact seals that achieve ultra-low permeability. A key feature is this can be achieved at process temperatures of below 350 C, therefore allowing for the integration of sensors and microsystems with CMOS electronics within a single package. Issueshowever such as solder wetting, void formation and controlling composition make formation of high-quality repeatable seals highly challenging. Towards this aim, this paper presents our experimental work characterizing the eutectic stack deposition. We detail our design methods and process flow, share our experiences in controlling electrochemical deposition of AuSnalloy and finally discuss usability of sequential electroplating process for the formation of hermetic eutectic bonds.

  • BOOK CHAPTER
    Williams I, Leene L, Constandinou TG, 2018,

    Next Generation Neural Interface Electronics

    , Circuit Design Considerations for Implantable Devices, Editors: Cong, Publisher: River Publishers, Pages: 141-178, ISBN: 978-87-93519-86-2
  • JOURNAL ARTICLE
    Yao L, Sheng X, Mrachacz-Kersting N, Zhu X, Farina D, Jiang Net al., 2018,

    Decoding Covert Somatosensory Attention by a BCI System Calibrated with Tactile Sensation

    , IEEE Transactions on Biomedical Engineering, Vol: 65, Pages: 1689-1695, ISSN: 0018-9294

    © 1964-2012 IEEE. Objective: We propose a novel calibration strategy to facilitate the decoding of covert somatosensory attention by exploring the oscillatory dynamics induced by tactile sensation. Methods: It was hypothesized that the similarity of the oscillatory pattern between stimulation sensation (SS, real sensation) and somatosensory attentional orientation (SAO) provides a way to decode covert somatic attention. Subjects were instructed to sense the tactile stimulation, which was applied to the left (SS-L) or the right (SS-R) wrist. The brain-computer interface (BCI) system was calibrated with the sensation data and then applied for online SAO decoding. Results: Both SS and SAO showed oscillatory activation concentrated on the contralateral somatosensory hemisphere. Offline analysis showed that the proposed calibration method led to a greater accuracy than the traditional calibration method based on SAO only. This is confirmed by online experiments, where the online accuracy on 15 subjects was 78.8 ± 13.1%, with 12 subjects >70% and 4 subject >90%. Conclusion: By integrating the stimulus-induced oscillatory dynamics from sensory cortex, covert somatosensory attention can be reliably decoded by a BCI system calibrated with tactile sensation. Significance: Indeed, real tactile sensation is more consistent during calibration than SAO. This brain-computer interfacing approach may find application for stroke and completely locked-in patients with preserved somatic sensation.

  • CONFERENCE PAPER
    Angeles P, Tai Y, Pavese N, Vaidyanathan Ret al., 2017,

    Assessing Parkinson's disease motor symptoms using supervised learning algorithms

    , 21st International Congress of Parkinson's Disease and Movement Disorders, Publisher: WILEY, ISSN: 0885-3185
  • CONFERENCE PAPER
    Angeles P, Tai Y, Pavese N, Wilson S, Vaidyanathan Ret al., 2017,

    Automated assessment of symptom severity changes during Deep Brain Stimulation (DBS) therapy for Parkinson's disease

    , International Conference on Rehabilitation Robotics (ICORR), Publisher: IEEE, Pages: 1512-1517, ISSN: 1945-7898
  • JOURNAL ARTICLE
    Bass C, Helkkula P, De Paola V, Clopath C, Bharath AAet al., 2017,

    Detection of axonal synapses in 3D two-photon images

    , PLOS ONE, Vol: 12, ISSN: 1932-6203
  • JOURNAL ARTICLE
    Bishop CA, Newbould RD, Lee JSZ, Honeyfield L, Quest R, Colasanti A, Ali R, Mattoscio M, Cortese A, Nicholas R, Matthews PM, Muraro PA, Waldman ADet al., 2017,

    Analysis of ageing-associated grey matter volume in patients with multiple sclerosis shows excess atrophy in subcortical regions

    , NEUROIMAGE-CLINICAL, Vol: 13, Pages: 9-15, ISSN: 2213-1582
  • JOURNAL ARTICLE
    Burridge JH, Lee ACW, Turk R, Stokes M, Whitall J, Vaidyanathan R, Clatworthy P, Hughes A-M, Meagher C, Franco E, Yardley Let al., 2017,

    Telehealth, Wearable Sensors, and the Internet: Will They Improve Stroke Outcomes Through Increased Intensity of Therapy, Motivation, and Adherence to Rehabilitation Programs?

    , JOURNAL OF NEUROLOGIC PHYSICAL THERAPY, Vol: 41, Pages: S32-S38, ISSN: 1557-0576
  • CONFERENCE PAPER
    Castronovo M, Mrachacz-Kersting N, Landi F, Jørgensen HR, Severinsen K, Farina Det al., 2017,

    Motor Unit Coherence at Low Frequencies Increases Together with Cortical Excitability Following a Brain-Computer Interface Intervention in Acute Stroke Patients

    , Pages: 1001-1005, ISSN: 2195-3562

    © Springer International Publishing AG 2017. This study aims at investigating the neurophysiological correlates of increased cortical excitability following a Brain-Computer interface based intervention in three acute stroke survivors. The analysis was performed on high-density EMG signals recorded from the Tibialis Anterior muscle. All patients showed an increased excitability in the motor cortex area of interest following the BCI intervention. Moreover, coherence between motor unit spike trains increased in the frequency band 1–5, Hz, suggesting an increase in the common oscillatory drive to the target muscle.

  • JOURNAL ARTICLE
    Cayco-Gajic NA, Clopath C, Silver RA, 2017,

    Sparse synaptic connectivity is required for decorrelation and pattern separation in feedforward networks

    , NATURE COMMUNICATIONS, Vol: 8, ISSN: 2041-1723
  • JOURNAL ARTICLE
    Caze RD, Jarvis S, Foust AJ, Schultz SRet al., 2017,

    Dendrites Enable a Robust Mechanism for Neuronal Stimulus Selectivity

    , NEURAL COMPUTATION, Vol: 29, Pages: 2511-2527, ISSN: 0899-7667
  • JOURNAL ARTICLE
    Datta G, Violante IR, Scott G, Zimmerman K, Santos-Ribeiro A, Rabiner EA, Gunn RN, Malik O, Ciccarelli O, Nicholas R, Matthews PMet al., 2017,

    Translocator positron-emission tomography and magnetic resonance spectroscopic imaging of brain glial cell activation in multiple sclerosis

    , MULTIPLE SCLEROSIS JOURNAL, Vol: 23, Pages: 1469-1478, ISSN: 1352-4585
  • CONFERENCE PAPER
    Davila-Montero S, Barsakcioglu DY, Jackson A, Constandinou TG, Mason AJet al., 2017,

    Real-time Clustering Algorithm that Adapts to Dynamic Changes in Neural Recordings

    , IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, Pages: 690-693, ISSN: 0271-4302
  • CONFERENCE PAPER
    De Marcellis A, Palange E, Faccio M, Stanchieri GDP, Constandinou TGet al., 2017,

    A 250Mbps 24pJ/bit UWB-inspired Optical Communication System for Bioimplants

    , Turin, Italy, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Pages: 132-135
  • JOURNAL ARTICLE
    Farina D, Castronovo AM, Vujaklija I, Sturma A, Salminger S, Hofer C, Aszmann Oet al., 2017,

    Common Synaptic Input to Motor Neurons and Neural Drive to Targeted Reinnervated Muscles

    , JOURNAL OF NEUROSCIENCE, Vol: 37, Pages: 11285-11292, ISSN: 0270-6474
  • CONFERENCE PAPER
    Feng P, Constandinou TG, Yeon P, Ghovanloo Met al., 2017,

    Millimeter-Scale Integrated and Wirewound Coils for Powering Implantable Neural Microsystems

    , IEEE Biomedical Circuits and Systems (BioCAS) Conference, Pages: 488-491
  • CONFERENCE PAPER
    Forte AE, Etard O, Reichenbach J, 2017,

    Complex Auditory-brainstem Response to the Fundamental Frequency of Continuous Natural Speech

    , ARO 2017
  • CONFERENCE PAPER
    Forte AE, Etard O, Reichenbach J, 2017,

    Selective auditory attention modulates the human brainstem's response to running speech

    , Basic Auditory Science 2017
  • JOURNAL ARTICLE
    Forte AE, Etard O, Reichenbach T, 2017,

    The human auditory brainstem response to running speech reveals a subcortical mechanism for selective attention

    , ELIFE, Vol: 6, ISSN: 2050-084X
  • CONFERENCE PAPER
    Gao C, Ghoreishizadeh S, Liu Y, Constandinou Tet al., 2017,

    On-chip ID Generation for Multi-node Implantable Devices using SA-PUF

    , IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, Pages: 678-681, ISSN: 0271-4302

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