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  • Conference paper
    Ramezani R, Dehkhoda F, Soltan A, Degenaar P, Liu Y, Constandinou TGet al., 2016,

    An optrode with built-in self-diagnostic and fracture sensor for cortical brain stimulation

    , IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 392-395

    This paper proposes a self-diagnostic subsystem for a new generation of brain implants with active electronics. The primary objective of such probes is to deliver optical pulses to optogenetic tissue and record the subsequent activity, but lifetime is currently unknown. Our proposed circuits aim to increase the safety of implanting active electronic probes into human brain tissue. Therefore, prolonging the lifetime of the implant and reducing the risks to the patient. The self-diagnostic circuit will examine the optical emitter against any abnormality or malfunctioning. The fracture sensor examinesthe optrode against any rapture or insertion breakage. The optrode including our diagnostic subsystem and fracture sensor has been designed and successfully simulated at 350nm AMS technology node and sent for manufacture.

  • Journal article
    Matthews PM, Hampshire A, 2016,

    Clinical concepts emerging from fMRI functional connectomics

    , Neuron, Vol: 91, Pages: 511-528, ISSN: 0896-6273

    Recent advances in connectomics have led to a synthesis of perspectives regarding the brain's functional organization that reconciles classical concepts of localized specialization with an appreciation for properties that emerge from interactions across distributed functional networks. This provides a more comprehensive framework for understanding neural mechanisms of normal cognition and disease. Although fMRI has not become a routine clinical tool, research has already had important influences on clinical concepts guiding diagnosis and patient management. Here we review illustrative examples. Studies demonstrating the network plasticity possible in adults and the global consequences of even focal brain injuries or disease both have had substantial impact on modern concepts of disease evolution and expression. Applications of functional connectomics in studies of clinical populations are challenging traditional disease classifications and helping to clarify biological relationships between clinical syndromes (and thus also ways of extending indications for, or "re-purposing," current treatments). Large datasets from prospective, longitudinal studies promise to enable the discovery and validation of functional connectomic biomarkers with the potential to identify people at high risk of disease before clinical onset, at a time when treatments may be most effective. Studies of pain and consciousness have catalyzed reconsiderations of approaches to clinical management, but also have stimulated debate about the clinical meaningfulness of differences in internal perceptual or cognitive states inferred from functional connectomics or other physiological correlates. By way of a closing summary, we offer a personal view of immediate challenges and potential opportunities for clinically relevant applications of fMRI-based functional connectomics.

  • Journal article
    Warren RL, Ramamoorthy S, Ciganovic N, Zhang Y, Wilson T, Petrie T, Wang RK, Jacques SL, Reichenbach JDT, Nuttall AL, Fridberger Aet al., 2016,

    Minimal basilar membrane motion in low-frequency hearing

    , Proceedings of the National Academy of Sciences of the United States of America, Vol: 113, Pages: E4304-E4310, ISSN: 1091-6490

    Low-frequency hearing is critically important for speech and music perception, but no mechanical measurements have previously been available from inner ears with intact low-frequency parts. These regions of the cochlea may function in ways different from the extensively studied high-frequency regions, where the sensory outer hair cells produce force that greatly increases the sound-evoked vibrations of the basilar membrane. We used laser interferometry in vitro and optical coherence tomography in vivo to study the low-frequency part of the guinea pig cochlea, and found that sound stimulation caused motion of a minimal portion of the basilar membrane. Outside the region of peak movement, an exponential decline in motion amplitude occurred across the basilar membrane. The moving region had different dependence on stimulus frequency than the vibrations measured near the mechanosensitive stereocilia. This behavior differs substantially from the behavior found in the extensively studied high-frequency regions of the cochlea.

  • Journal article
    Fagerholm ED, Scott G, Shew WL, Song C, Leech R, Knöpfel T, Sharp DJet al., 2016,

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

    , Cerebral Cortex, Vol: 26, Pages: 3945-3952, ISSN: 1460-2199

    Some neural circuits operate with simple dynamics characterized by one or a few well-defined spatiotemporal scales (e.g. central pattern generators). In contrast, cortical neuronal networks often exhibit richer activity patterns in which all spatiotemporal scales are represented. Such "scale-free" cortical dynamics manifest as cascades of activity with cascade sizes that are distributed according to a power-law. Theory and in vitro experiments suggest that information transmission among cortical circuits is optimized by scale-free dynamics. In vivo tests of this hypothesis have been limited by experimental techniques with insufficient spatial coverage and resolution, i.e., restricted access to a wide range of scales. We overcame these limitations by using genetically encoded voltage imaging to track neural activity in layer 2/3 pyramidal cells across the cortex in mice. As mice recovered from anesthesia, we observed three changes: (a) cortical information capacity increased, (b) information transmission among cortical regions increased and (c) neural activity became scale-free. Our results demonstrate that both information capacity and information transmission are maximized in the awake state in cortical regions with scale-free network dynamics.

  • Conference paper
    Luan S, Williams I, de Carvalho F, Jackson A, Quian Quiroga R, Constandinou TGet al., 2016,

    Next Generation Neural Interfaces for low-power multichannel spike sorting

    , FENS Forum of Neuroscience, Publisher: FENS
  • Conference paper
    Nicolaou N, Constandinou TG, 2016,

    Phase-Amplitude Coupling during propofol-induced sedation: an exploratory approach

    , FENS Forum of Neuroscience, Publisher: FENS
  • Journal article
    Antic SD, Empson RM, Knopfel T, 2016,

    Voltage imaging to understand connections and functions of neuronal circuits.

    , Journal of Neurophysiology, Vol: 116, Pages: 135-152, ISSN: 1522-1598

    Understanding of the cellular mechanisms underlying brain functions such as cognition and emotions requires monitoring of membrane voltage at the cellular, circuit, and system levels. Seminal voltage-sensitive dye and calcium-sensitive dye imaging studies have demonstrated parallel detection of electrical activity across populations of interconnected neurons in a variety of preparations. A game-changing advance made in recent years has been the conceptualization and development of optogenetic tools, including genetically encoded indicators of voltage (GEVIs) or calcium (GECIs) and genetically encoded light-gated ion channels (actuators, e.g., channelrhodopsin2). Compared with low-molecular-weight calcium and voltage indicators (dyes), the optogenetic imaging approaches are 1) cell type specific, 2) less invasive, 3) able to relate activity and anatomy, and 4) facilitate long-term recordings of individual cells' activities over weeks, thereby allowing direct monitoring of the emergence of learned behaviors and underlying circuit mechanisms. We highlight the potential of novel approaches based on GEVIs and compare those to calcium imaging approaches. We also discuss how novel approaches based on GEVIs (and GECIs) coupled with genetically encoded actuators will promote progress in our knowledge of brain circuits and systems.

  • Journal article
    Sweeney Y, Clopath C, 2016,

    Emergent spatial synaptic structure from diffusive plasticity

    , European Journal of Neuroscience, ISSN: 1460-9568

    Some neurotransmitters can diffuse freely across cell membranes, influencing neighbouring neurons regardless of their synaptic coupling. This provides a means of neural communication, alternative to synaptic transmission, which can influence the way in which neural networks process information. Here, we ask whether diffusive neurotransmission can also influence the structure of synaptic connectivity in a network undergoing plasticity. We propose a form of Hebbian synaptic plasticity which is mediated by a diffusive neurotransmitter. Whenever a synapse is modified at an individual neuron through our proposed mechanism, similar but smaller modifications occur in synapses connecting to neighbouring neurons. The effects of this diffusive plasticity are explored in networks of rate-based neurons. This leads to the emergence of spatial structure in the synaptic connectivity of the network. We show that this spatial structure can coexist with other forms of structure in the synaptic connectivity, such as with groups of strongly interconnected neurons that form in response to correlated external drive. Finally, we explore diffusive plasticity in a simple feedforward network model of receptive field development. We show that, as widely observed across sensory cortex, the preferred stimulus identity of neurons in our network become spatially correlated due to diffusion. Our proposed mechanism of diffusive plasticity provides an efficient mechanism for generating these spatial correlations in stimulus preference which can flexibly interact with other forms of synaptic organisation.

  • Journal article
    Hartings JA, Shuttleworth CW, Kirov SA, Ayata C, Hinzman JM, Foreman B, Andrew RD, Boutelle MG, Brennan KC, Carlson AP, Dahlem MA, Drenckhahn C, Dohmen C, Fabricius M, Farkas E, Feuerstein D, Graf R, Helbok R, Lauritzen M, Major S, Oliveira-Ferreira AI, Richter F, Rosenthal ES, Sakowitz OW, Sánchez-Porras R, Santos E, Schöll M, Strong AJ, Urbach A, Westover MB, Winkler MK, Witte OW, Woitzik J, Dreier JPet al., 2016,

    The continuum of spreading depolarizations in acute cortical lesion development: Examining Leão's legacy.

    , Journal of Cerebral Blood Flow & Metabolism, Vol: 37, Pages: 1571-1594, ISSN: 0271-678X

    A modern understanding of how cerebral cortical lesions develop after acute brain injury is based on Aristides Leão's historic discoveries of spreading depression and asphyxial/anoxic depolarization. Treated as separate entities for decades, we now appreciate that these events define a continuum of spreading mass depolarizations, a concept that is central to understanding their pathologic effects. Within minutes of acute severe ischemia, the onset of persistent depolarization triggers the breakdown of ion homeostasis and development of cytotoxic edema. These persistent changes are diagnosed as diffusion restriction in magnetic resonance imaging and define the ischemic core. In delayed lesion growth, transient spreading depolarizations arise spontaneously in the ischemic penumbra and induce further persistent depolarization and excitotoxic damage, progressively expanding the ischemic core. The causal role of these waves in lesion development has been proven by real-time monitoring of electrophysiology, blood flow, and cytotoxic edema. The spreading depolarization continuum further applies to other models of acute cortical lesions, suggesting that it is a universal principle of cortical lesion development. These pathophysiologic concepts establish a working hypothesis for translation to human disease, where complex patterns of depolarizations are observed in acute brain injury and appear to mediate and signal ongoing secondary damage.

  • Conference paper
    Marcos Tostado P, Abbott WW, Faisal AA, 2016,

    3D gaze cursor: continuous calibration and end-point grasp control of robotic actuators

    , IEEE International Conference on Robotics and Automation (ICRA), Publisher: IEEE, Pages: 3295-3300

    Eye movements are closely related to motor ac-tions, and hence can be used to infer motor intentions. Ad-ditionally, eye movements are in some cases the only meansof communication and interaction with the environment forparalysed and impaired patients with severe motor deficiencies.Despite this, eye-tracking technology still has a very limiteduse as a human-robot control interface and its applicability ishighly restricted to 2D simple tasks that operate on screen basedinterfaces and do not suffice for natural physical interactionwith the environment. We propose that decoding the gazeposition in 3D space rather than in 2D results into a muchricher "spatial cursor" signal that allows users to performeveryday tasks such as grasping and moving objects via gaze-based robotic teleoperation. Eye tracking in 3D calibration isusually slow – we demonstrate here that by using a full 3Dtrajectory for system calibration generated by a robotic armrather than a simple grid of discrete points, gaze calibration inthe 3 dimensions can be successfully achieved in short time andwith high accuracy. We perform the non-linear regression fromeye-image to 3D-end point using Gaussian Process regressors,which allows us to handle uncertainty in end-point estimatesgracefully. Our telerobotic system uses a multi-joint robot armwith a gripper and is integrated with our in-house "GT3D"binocular eye tracker. This prototype system has been evaluatedand assessed in a test environment with 7 users, yielding gaze-estimation errors of less than 1cm in the horizontal, vertical anddepth dimensions, and less than 2cm in the overall 3D Euclideanspace. Users reported intuitive, low-cognitive load, control of thesystem right from their first trial and were straightaway ableto simply look at an object and command through a

  • Journal article
    Dreier JP, Fabricius M, Ayata C, Sakowitz OW, William Shuttleworth C, Dohmen C, Graf R, Vajkoczy P, Helbok R, Suzuki M, Schiefecker AJ, Major S, Winkler MK, Kang EJ, Milakara D, Oliveira-Ferreira AI, Reiffurth C, Revankar GS, Sugimoto K, Dengler NF, Hecht N, Foreman B, Feyen B, Kondziella D, Friberg CK, Piilgaard H, Rosenthal ES, Westover MB, Maslarova A, Santos E, Hertle D, Sánchez-Porras R, Jewell SL, Balança B, Platz J, Hinzman JM, Lückl J, Schoknecht K, Schöll M, Drenckhahn C, Feuerstein D, Eriksen N, Horst V, Bretz JS, Jahnke P, Scheel M, Bohner G, Rostrup E, Pakkenberg B, Heinemann U, Claassen J, Carlson AP, Kowoll CM, Lublinsky S, Chassidim Y, Shelef I, Friedman A, Brinker G, Reiner M, Kirov SA, Andrew RD, Farkas E, Güresir E, Vatter H, Chung LS, Brennan KC, Lieutaud T, Marinesco S, Maas AI, Sahuquillo J, Dahlem MA, Richter F, Herreras O, Boutelle MG, Okonkwo DO, Bullock MR, Witte OW, Martus P, van den Maagdenberg AM, Ferrari MD, Dijkhuizen RM, Shutter LA, Andaluz N, Schulte AP, MacVicar B, Watanabe T, Woitzik J, Lauritzen M, Strong AJ, Hartings JAet al., 2016,

    Recording, analysis, and interpretation of spreading depolarizations in neurointensive care: Review and recommendations of the COSBID research group.

    , Journal of Cerebral Blood Flow & Metabolism, ISSN: 0271-678X

    Spreading depolarizations (SD) are waves of abrupt, near-complete breakdown of neuronal transmembrane ion gradients, are the largest possible pathophysiologic disruption of viable cerebral gray matter, and are a crucial mechanism of lesion development. Spreading depolarizations are increasingly recorded during multimodal neuromonitoring in neurocritical care as a causal biomarker providing a diagnostic summary measure of metabolic failure and excitotoxic injury. Focal ischemia causes spreading depolarization within minutes. Further spreading depolarizations arise for hours to days due to energy supply-demand mismatch in viable tissue. Spreading depolarizations exacerbate neuronal injury through prolonged ionic breakdown and spreading depolarization-related hypoperfusion (spreading ischemia). Local duration of the depolarization indicates local tissue energy status and risk of injury. Regional electrocorticographic monitoring affords even remote detection of injury because spreading depolarizations propagate widely from ischemic or metabolically stressed zones; characteristic patterns, including temporal clusters of spreading depolarizations and persistent depression of spontaneous cortical activity, can be recognized and quantified. Here, we describe the experimental basis for interpreting these patterns and illustrate their translation to human disease. We further provide consensus recommendations for electrocorticographic methods to record, classify, and score spreading depolarizations and associated spreading depressions. These methods offer distinct advantages over other neuromonitoring modalities and allow for future refinement through less invasive and more automated approaches.

  • Conference paper
    Reynolds S, Copeland CS, Schultz SR, Dragotti PLet al., 2016,

    An extension of the FRI framework for calcium transient detection

    , IEEE 13th International Symposium on Biomedical Imaging (ISBI), Publisher: IEEE, Pages: 676-679, ISSN: 1945-7928

    Two-photon calcium imaging of the brain allows the spatiotemporal activity of neuronal networks to be monitored at cellular resolution. In order to analyse this activity it must first be possible to detect, with high temporal resolution, spikes from the time series corresponding to single neurons. Previous work has shown that finite rate of innovation (FRI) theory can be used to reconstruct spike trains from noisy calcium imaging data. In this paper we extend the FRI framework for spike detection from calcium imaging data to encompass data generated by a larger class of calcium indicators, including the genetically encoded indicator GCaMP6s. Furthermore, we implement least squares model-order estimation and perform a noise reduction procedure ('pre-whitening') in order to increase the robustness of the algorithm. We demonstrate high spike detection performance on real data generated by GCaMP6s, detecting 90% of electrophysiologically-validated spikes.

  • Journal article
    Štrbac M, Belić M, Isaković M, Kojić V, Bijelić G, Popović I, Radotić M, Došen S, Marković M, Farina D, Keller Tet al., 2016,

    Integrated and flexible multichannel interface for electrotactile stimulation

    , Journal of Neural Engineering, Vol: 13, ISSN: 1741-2560

    © 2016 IOP Publishing Ltd. Objective. The aim of the present work was to develop and test a flexible electrotactile stimulation system to provide real-time feedback to the prosthesis user. The system requirements were to accommodate the capabilities of advanced multi-DOF myoelectric hand prostheses and transmit the feedback variables (proprioception and force) using intuitive coding, with high resolution and after minimal training. Approach. We developed a fully-programmable and integrated electrotactile interface supporting time and space distributed stimulation over custom designed flexible array electrodes. The system implements low-level access to individual stimulation channels as well as a set of high-level mapping functions translating the state of a multi-DoF prosthesis (aperture, grasping force, wrist rotation) into a set of predefined dynamic stimulation profiles. The system was evaluated using discrimination tests employing spatial and frequency coding (10 able-bodied subjects) and dynamic patterns (10 able-bodied and 6 amputee subjects). The outcome measure was the success rate (SR) in discrimination. Main results. The more practical electrode with the common anode configuration performed similarly to the more usual concentric arrangement. The subjects could discriminate six spatial and four frequency levels with SR > 90% after a few minutes of training, whereas the performance significantly deteriorated for more levels. The dynamic patterns were intuitive for the subjects, although amputees showed lower SR than able-bodied individuals (86% 10% versus 99% 3%). Significance. The tests demonstrated that the system was easy to setup and apply. The design and resolution of the multipad electrode was evaluated. Importantly, the novel dynamic patterns, which were successfully tested, can be superimposed to transmit multiple feedback variables intuitively and simultaneously. This is especially relevant for closing the loop in modern multifunction prost

  • Journal article
    Berditchevskaia A, Caze R, Schultz SR, 2016,

    Performance in a GO/NOGO perceptual task reflects a balance between impulsive and instrumental components of behaviour

    , Scientific Reports, Vol: 6, ISSN: 2045-2322

    In recent years, simple GO/NOGO behavioural tasks have become popular due to the relative ease with which they can be combined with technologies such as in vivo multiphoton imaging. To date, it has been assumed that behavioural performance can be captured by the average performance across a session, however this neglects the effect of motivation on behaviour within individual sessions. We investigated the effect of motivation on mice performing a GO/NOGO visual discrimination task. Performance within a session tended to follow a stereotypical trajectory on a Receiver Operating Characteristic (ROC) chart, beginning with an over-motivated state with many false positives, and transitioning through a more or less optimal regime to end with a low hit rate after satiation. Our observations are reproduced by a new model, the Motivated Actor-Critic, introduced here. Our results suggest that standard measures of discriminability, obtained by averaging across a session, may significantly underestimate behavioural performance.

  • Journal article
    Rivera-Rubio J, Arulkumaran K, Rishi H, Alexiou I, Bharath AAet al., 2016,

    An assistive haptic interface for appearance-based indoor navigation

    , Computer Vision and Image Understanding, Vol: 149, Pages: 126-145, ISSN: 1090-235X

    Computer vision remains an under-exploited technology for assistive devices. Here, we propose a navigation technique using low-resolution images from wearable or hand-held cameras to identify landmarks that are indicative of a user’s position along crowdsourced paths. We test the components of a system that is able to provide blindfolded users with information about location via tactile feedback. We assess the accuracy of vision-based localisation by making comparisons with estimates of location derived from both a recent SLAM-based algorithm and from indoor surveying equipment. We evaluate the precision and reliability by which location information can be conveyed to human subjects by analysing their ability to infer position from electrostatic feedback in the form of textural (haptic) cues on a tablet device. Finally, we describe a relatively lightweight systems architecture that enables images to be captured and location results to be served back to the haptic device based on journey information from multiple users and devices.

  • 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
    Nicolaou N, Constandinou TG, 2016,

    A nonlinear causality estimator based on Non-Parametric Multiplicative Regression

    , Frontiers in Neuroinformatics, Vol: 10, ISSN: 1662-5196

    Causal prediction has become a popular tool for neuroscience applications, as it allows the study of relationships between different brain areas during rest, cognitive tasks or brain disorders. We propose a nonparametric approach for the estimation of nonlinear causal prediction for multivariate time series. In the proposed estimator, C-NPMR, Autoregressive modelling is replaced by Nonparametric Multiplicative Regression (NPMR). NPMR quantifies interactions between a response variable (effect) and a set of predictor variables (cause); here, we modified NPMR for model prediction. We also demonstrate how a particular measure, the sensitivity Q, could be used to reveal the structure of the underlying causal relationships. We apply C-NPMR on artificial data with known ground truth (5 datasets), as well as physiological data (2 datasets). C-NPMR correctly identifies both linear and nonlinear causal connections that are present in the artificial data, as well as physiologically relevant connectivity in the real data, and does not seem to be affected by filtering. The Sensitivity measure also provides useful information about the latent connectivity.The proposed estimator addresses many of the limitations of linear Granger causality and other nonlinear causality estimators. C-NPMR is compared with pairwise and conditional Granger causality (linear) and Kernel-Granger causality (nonlinear). The proposed estimator can be applied to pairwise or multivariate estimations without any modifications to the main method. Its nonpametric nature, its ability to capture nonlinear relationships and its robustness to filtering make it appealing for a number of applications.

  • Journal article
    Yao L, Sheng X, Zhang D, Jiang N, Farina D, Zhu Xet al., 2016,

    A BCI System Based on Somatosensory Attentional Orientation

    , IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol: 25, Pages: 78-87, ISSN: 1534-4320

    © 2001-2011 IEEE. We propose and test a novel brain-computer interface (BCI) based on imagined tactile sensation. During an imagined tactile sensation, referred to as somatosensory attentional orientation (SAO), the subject shifts and maintains somatosensory attention on a body part, e.g., left or right hand. The SAO can be detected from EEG recordings for establishing a communication channel. To test for the hypothesis that SAO on different body parts can be discriminated from EEG, 14 subjects were assigned to a group who received an actual sensory stimulation (STE-Group), and 18 subjects were assigned to the SAO only group (SAO-Group). In single trials, the STE-Group received tactile stimulation first (both wrists simultaneously stimulated), and then maintained the attention on the selected body part (without stimulation). The same group also performed the SAO task first and then received the tactile stimulation. Conversely, the SAO-Group performed SAO without any stimulation, neither before nor after the SAO. In both the STE-Group and SAO-Group, it was possible to identify the SAO-related oscillatory activation that corresponded to a contralateral event-related desynchronization (ERD) stronger than the ipsilateral ERD. Discriminative information, represented as R 2 , was found mainly on the somatosensory area of the cortex. In the STE-Group, the average classification accuracy of SAO was 83.6%, and it was comparable with tactile BCI based on selective sensation (paired-T test, $P > 0.05$ ). In the SAO-Group the average online performance was 75.7%. For this group, after frequency band selection the offline performance reached 82.5% on average, with ≥ 80% for 12 subjects and ≥ 95% for four subjects. Complementary to tactile sensation, the SAO does not require sensory stimulation, with the advantage of being completely independent from the stimulus.

  • Conference paper
    Elia M, Leene L, Constandinou TG, 2016,

    Continuous-Time Micropower Interface for Neural Recording Applications

    , IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, Pages: 534-637

    This paper presents a novel amplifier architectureintended for low power neural recording applications. By usingcontinuous-time signal representation, the proposed topologypredominantly leverages digital topologies taking advantage ofefficient techniques used in time domain systems. This includeshigher order feedback dynamics that allow direct analoguesignal quantization and near ideal integrator structures for noiseshaping. The system implemented in 0.18 μ m standard CMOSdemonstrates the capability for low noise instrumentation witha bandwidth of 6 kHz and highly linear full dynamic range.Simulation results indicate 1.145 μW budget from 0.5 V supplyvoltage with an input referred thermal noise of 7.7 μVrms.

  • Conference paper
    Barsakcioglu DY, Constandinou TG, 2016,

    A 32-Channel MCU-Based Feature Extraction and Classification for Scalable on-Node Spike Sorting

    , IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, Pages: 1310-1313

    This paper describes a new hardware-efficientmethod and implementation for neural spike sorting basedon selection of a channel-specific near-optimal subset of fea-tures given a larger predefined set. For each channel, real-time classification is achieved using a simple decision matrixthat considers the features that provide the highest separabilitydetermined through off-line training. A 32-channel system for on-line feature extraction and classification has been implementedin an ARM Cortex-M0+ processor. Measured results of thehardware platform consumes 268 W per channel during spikesorting (includes detection). The proposed method provides atleast x10 reduction in computational requirements compared toliterature, while achieving an average classification error of lessthan 10% across wide range of datasets and noise levels.

  • Conference paper
    Liu Y, Pereira J, 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

    In this paper, we present a new method for neuralspike sorting based on Continuous Time (CT) signal processing.A set of CT based features are proposed and extracted fromCT sampled pulses, and a complete event-driven spike sortingalgorithm that performs classification based on these features isdeveloped. Compared to conventional methods for spike sorting,the hardware implementation of the proposed method does notrequire any synchronisation clock for logic circuits, and thusits power consumption depend solely on the spike activity. Thishas been implemented using a variable quantisation step CTanalogue to digital converter (ADC) with custom digital logicthat is driven by level crossing events. Simulation results usingsynthetic neural data shows a comparable accuracy comparedto template matching (TM) and Principle Components Analysis(PCA) based discrete sampled classification.

  • Journal article
    Kovac M, 2016,

    Learning from nature how to land aerial robots

    , Science, Vol: 352, Pages: 895-896, ISSN: 0036-8075

    One of the main challenges for aerial robots is the high-energy consumption of powered flight, which limits flight times to typically only tens of minutes for systems below 2 kg in weight (1). This limitation greatly reduces their utility for sensing and inspection tasks, where longer hovering times would be beneficial. Perching onto structures can save energy and maintain a high, stable observation or resting position, but it requires a coordination of flight dynamics and some means of attaching to the structure. Birds and insects have mastered the ability to perch successfully and have inspired perching robots at various sizes. On page 978 of this issue, Graule et al. (2) describe a perching robotic insect that represents the smallest flying robot platform that can autonomously attach to surfaces. At a mass of only 100 mg, it combines advanced flight control with adaptive mechanical dampers and electro-adhesion to perch on a variety of natural and artificial structures.

  • Journal article
    Papadimitriou K, Wang C, Rogers M, Gowers S, Leong C, Boutelle M, Drakakis EMet al., 2016,

    High-Performance Bioinstrumentation for Real-Time Neuroelectrochemical Traumatic Brain Injury Monitoring

    , Frontiers in Human Neuroscience, Vol: 10, ISSN: 1662-5161

    Traumatic brain injury (TBI) has been identified as an important cause of death and severe disability in all age groups and particularly in children and young adults. Central to TBI’s devastation is a delayed secondary injury that occurs in 30-40% of TBI patients each year, while they are in the hospital Intensive Care Unit (ICU). Secondary injuries reduce survival rate after TBI and usually occur within 7 days post-injury. State-of-art monitoring of secondary brain injuries benefits from the acquisition of high-quality and time-aligned electrical data i.e. ElectroCorticoGraphy (ECoG) recorded by means of strip electrodes placed on the brain’s surface, and neurochemical data obtained via rapid sampling microdialysis and microfluidics-based biosensors measuring brain tissue levels of glucose, lactate and potassium. This article progresses the field of multi-modal monitoring of the injured human brain by presenting the design and realisation of a new, compact, medical-grade amperometry, potentiometry and ECoG recording bioinstrumentation. Our combined TBI instrument enables the high-precision, real-time neuroelectrochemical monitoring of TBI patients, who have undergone craniotomy neurosurgery and are treated sedated in the ICU. Electrical and neurochemical test measurements are presented, confirming the high-performance of the reported TBI bioinstrumentation.

  • Journal article
    De Guio F, Jouvent E, Biessels GJ, Black SE, Brayne C, Chen C, Cordonnier C, De Leeuw FE, Dichgans M, Doubal F, Duering M, Dufouil C, Duzel E, Fazekas F, Hachinski V, Ikram MA, Linn J, Matthews PM, Mazoyer B, Mok V, Norrving B, O'Brien JT, Pantoni L, Ropele S, Sachdev P, Schmidt R, Seshadri S, Smith EE, Sposato LA, Stephan B, Swartz RH, Tzourio C, van Buchem M, van der Lugt A, van Oostenbrugge R, Vernooij MW, Viswanathan A, Werring D, Wollenweber F, Wardlaw JM, Chabriat Het al., 2016,

    Reproducibility and variability of quantitative magnetic resonance imaging markers in cerebral small vessel disease.

    , Journal of Cerebral Blood Flow & Metabolism, Vol: 36, Pages: 1319-1337, ISSN: 0271-678X

    Brain imaging is essential for the diagnosis and characterization of cerebral small vessel disease. Several magnetic resonance imaging markers have therefore emerged, providing new information on the diagnosis, progression, and mechanisms of small vessel disease. Yet, the reproducibility of these small vessel disease markers has received little attention despite being widely used in cross-sectional and longitudinal studies. This review focuses on the main small vessel disease-related markers on magnetic resonance imaging including: white matter hyperintensities, lacunes, dilated perivascular spaces, microbleeds, and brain volume. The aim is to summarize, for each marker, what is currently known about: (1) its reproducibility in studies with a scan-rescan procedure either in single or multicenter settings; (2) the acquisition-related sources of variability; and, (3) the techniques used to minimize this variability. Based on the results, we discuss technical and other challenges that need to be overcome in order for these markers to be reliably used as outcome measures in future clinical trials. We also highlight the key points that need to be considered when designing multicenter magnetic resonance imaging studies of small vessel disease.

  • 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: 1558-4542

    We present a laser scanning multiphoton endomicroscopewith no distal optics or mechanical components that incorporatesa polarization-maintaining (PM) multicore optical fibre todeliver, focus, and scan ultrashort pulsed radiation for two-photonexcited fluorescence imaging. We show theoretically that the use ofa PM multicore fibre in our experimental configuration enhancesthe fluorescence excitation intensity achieved in the focal spot comparedto a non-PM optical fibre with the same geometry and con-firm this by computer simulations based on numerical wavefrontpropagation. In our experimental system, a spatial light modulator(SLM) is utilised to program the phase of the light input to each ofthe cores of the endoscope fibre such that the radiation emergingfrom the distal end of the fibre interferes to provide the focusedscanning excitation beam. We demonstrate that the SLM can enabledynamic phase correction of path-length variations across themulticore optical fibre whilst the fibre is perturbed with an updaterate of 100 Hz.

  • Journal article
    Reinkensmeyer DJ, Burdet E, Casadio M, Krakauer JW, Kwakkel G, Lang CE, Swinnen SP, Ward NS, Schweighofer Net al., 2016,

    Computational neurorehabilitation: modeling plasticity and learning to predict recovery

    , Journal of Neuroengineering and Rehabilitation, Vol: 13, ISSN: 1743-0003

    Despite progress in using computational approaches to inform medicine and neuroscience in the last 30 years, there have been few attempts to model the mechanisms underlying sensorimotor rehabilitation. We argue that a fundamental understanding of neurologic recovery, and as a result accurate predictions at the individual level, will be facilitated by developing computational models of the salient neural processes, including plasticity and learning systems of the brain, and integrating them into a context specific to rehabilitation. Here, we therefore discuss Computational Neurorehabilitation, a newly emerging field aimed at modeling plasticity and motor learning to understand and improve movement recovery of individuals with neurologic impairment. We first explain how the emergence of robotics and wearable sensors for rehabilitation is providing data that make development and testing of such models increasingly feasible. We then review key aspects of plasticity and motor learning that such models will incorporate. We proceed by discussing how computational neurorehabilitation models relate to the current benchmark in rehabilitation modeling – regression-based, prognostic modeling. We then critically discuss the first computational neurorehabilitation models, which have primarily focused on modeling rehabilitation of the upper extremity after stroke, and show how even simple models have produced novel ideas for future investigation. Finally, we conclude with key directions for future research, anticipating that soon we will see the emergence of mechanistic models of motor recovery that are informed by clinical imaging results and driven by the actual movement content of rehabilitation therapy as well as wearable sensor-based records of daily activity.

  • Journal article
    Reichenbach CS, Braiman C, Schiff ND, Hudspeth AJ, Reichenbach JDTet al., 2016,

    The auditory-brainstem response to continuous, non repetitive speech is modulated by the speech envelope and reflects speech processing

    , Frontiers in Computational Neuroscience, Vol: 10, ISSN: 1662-5188

    The auditory-brainstem response (ABR) to short and simple acoustical signals is an important clinical tool used to diagnose the integrity of the brainstem. The ABR is also employed to investigate the auditory brainstem in a multitude of tasks related to hearing, such as processing speech or selectively focusing on one speaker in a noisy environment. Such research measures the response of the brainstem to short speech signals such as vowels or words. Because the voltage signal of the ABR has a tiny amplitude, several hundred to a thousand repetitions of the acoustic signal are needed to obtain a reliable response. The large number of repetitions poses a challenge to assessing cognitive functions due to neural adaptation. Here we show that continuous, non-repetitive speech, lasting several minutes, may be employed to measure the ABR. Because the speech is not repeated during the experiment, the precise temporal form of the ABR cannot be determined. We show, however, that important structural features of the ABR can nevertheless be inferred. In particular, the brainstem responds at the fundamental frequency of the speech signal, and this response is modulated by the envelope of the voiced parts of speech. We accordingly introduce a novel measure that assesses the ABR as modulated by the speech envelope, at the fundamental frequency of speech and at the characteristic latency of the response. This measure has a high signal-to-noise ratio and can hence be employed effectively to measure the ABR to continuous speech. We use this novel measure to show that the auditory brainstem response is weaker to intelligible speech than to unintelligible, time-reversed speech. The methods presented here can be employed for further research on speech processing in the auditory brainstem and can lead to the development of future clinical diagnosis of brainstem function.

  • Book
    Merletti R, Farina D, 2016,

    Surface Electromyography: Physiology, Engineering and Applications

    , ISBN: 9781118987025

    © 2016 by The Institute of Electricaland Electronics Engineers, Inc. All rights reserved. Reflects on developments in noninvasive electromyography, and includes advances and applications in signal detection, processing and interpretation. Addresses EMG imaging technology together with the issue of decomposition of surface EMG. Includes advanced single and multi-channel techniques for information extraction from surface EMG signals. Presents the analysis and information extraction of surface EMG at various scales, from motor units to the concept of muscle synergies.

  • Journal article
    Braga RM, Fu RZ, Seemungal BM, Wise RJS, Leech Ret al., 2016,

    Eye movements during auditory attention predict individual differences in dorsal attention network activity

    , Frontiers in Human Neuroscience, Vol: 10, ISSN: 1662-5161

    The neural mechanisms supporting auditory attention are not fully understood. A dorsal frontoparietal network of brain regions is thought to mediate the spatial orienting of attention across all sensory modalities. Key parts of the this network, the frontal eye fields (FEF) and the superior parietal lobes (SPL), contain retinotopic maps and elicit saccades when stimulated. This suggests that their recruitment during auditory attention might reflect crossmodal oculomotor processes; however this has not been confirmed experimentally. Here we investigate whether task-evoked eye movements during an auditory task can predict the magnitude of activity within the dorsal frontoparietal network. A spatial and non-spatial listening task was used with on-line eye-tracking and functional magnetic resonance imaging. No visual stimuli or cues were used. The auditory task elicited systematic eye movements, with saccade rate and gaze position predicting attentional engagement and the cued sound location, respectively. Activity associated with these separate aspects of evoked eye-movements dissociated between the SPL and FEF. However these observed eye movements could not account for all the activation in the frontoparietal network. Our results suggest that the recruitment of the SPL and FEF during attentive listening reflects, at least partly, overt crossmodal oculomotor processes during non-visual attention. Further work is needed to establish whether the network’s remaining contribution to auditory attention is through covert crossmodal processes, or is directly involved in the manipulation of auditory information.

  • Journal article
    Negro F, Muceli S, Castronovo AM, Holobar A, Farina Det al., 2016,

    Multi-channel intramuscular and surface EMG decomposition by convolutive blind source separation


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