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Journal articleSeemungal BM, Yousif N, Abou-El-Ela-Bourquin B, et al., 2016,
Dopamine activation preserves visual motion perception despite noise interference of human V5/MT
, Journal of Neuroscience, Vol: 36, Pages: 9303-9312, ISSN: 1529-2401When processing sensory signals, the brain must account for noise, both noise in the stimulus and that arising from within its own neuronal circuitry. Dopamine receptor activation is known to enhance both visual cortical signal-to-noise-ratio (SNR) and visual perceptual performance; however, it is unknown whether these two dopamine-mediated phenomena are linked. To assess this, we used single-pulse transcranial magnetic stimulation (TMS) applied to visual cortical area V5/MT to reduce the SNR focally and thus disrupt visual motion discrimination performance to visual targets located in the same retinotopic space. The hypothesis that dopamine receptor activation enhances perceptual performance by improving cortical SNR predicts that dopamine activation should antagonize TMS disruption of visual perception. We assessed this hypothesis via a double-blinded, placebo-controlled study with the dopamine receptor agonists cabergoline (a D2 agonist) and pergolide (a D1/D2 agonist) administered in separate sessions (separated by 2 weeks) in 12 healthy volunteers in a William's balance-order design. TMS degraded visual motion perception when the evoked phosphene and the visual stimulus overlapped in time and space in the placebo and cabergoline conditions, but not in the pergolide condition. This suggests that dopamine D1 or combined D1 and D2 receptor activation enhances cortical SNR to boost perceptual performance. That local visual cortical excitability was unchanged across drug conditions suggests the involvement of long-range intracortical interactions in this D1 effect. Because increased internal noise (and thus lower SNR) can impair visual perceptual learning, improving visual cortical SNR via D1/D2 agonist therapy may be useful in boosting rehabilitation programs involving visual perceptual training.
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Conference paperDe Marcellis A, Palange E, Faccio M, et al., 2016,
A new optical UWB modulation technique for 250Mbps wireless link in implantable biotelemetry systems
, Eurosensors, Publisher: Elsevier: Creative Commons Attribution Non-Commercial No-Derivatives License, Pages: 1676-1680, ISSN: 1877-7058We propose a new UWB modulation technique for wireless optical communications in transcutaneous biotelemetry. The solution, based on the generation of sub-nanoseconds laser pulses, allows for a high data rate link whilst achieving a significant power reduction (energy per bit) compared to the state-ofthe- art. These features make this particularly suitable for emerging biomedical applications such as implantable neural/biosensor systems. The relatively simple architecture consists of a transmitter and receiver that can be integrated in a standard CMOS technology in a compact Silicon footprint (lower than 1mm^2 in a 0.18μm technology). These parts, optimised for low-voltage/low-power operation, include coding and decoding digital systems, biasing and driving analogue circuits for laser pulse generation and photodiode signal conditioning. Experimental findings with prototype PCBs have validated the new paradigm showing the system capabilities to achieve a BER less than 10^-9 with data rate up to 250Mbps and estimated total power consumption lower than 5mW.
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Conference paperPeress L, Violante IR, Scott G, et al., 2016,
Thalamic magnetic resonance spectroscopy in highly active multiple sclerosis
, 32nd Congress of the European-Committee-for-Treatment-and-Research-in-Multiple-Sclerosis (ECTRIMS), Publisher: SAGE PUBLICATIONS LTD, Pages: 210-211, ISSN: 1352-4585 -
Conference paperLauteslager T, Nicolaou N, Lande TS, et al., 2016,
Functional neuroimaging Using UWB Impulse Radar: a Feasibility Study
, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 406-409Microwave imaging is a promising new modalityfor studying brain function. In the current paper we assess thefeasibility of using a single chip implementation of an ultra-wideband impulse radar for developing a portable and low-costfunctional neuroimaging device. A numerical model is used topredict the level of attenuation that will occur when detectinga volume of blood in the cerebral cortex. A phantom liquid ismade, to study the radar’s performance at different attenuationlevels. Although the radar is currently capable of detecting apoint reflector in a phantom liquid with submillimeter accuracyand high temporal resolution, object detection at the desired levelof attenuation remains a challenge.
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Conference paperZhao H, Dehkhoda F, Ramezani R, et al., 2016,
A CMOS-Based Neural Implantable Optrode for Optogenetic Stimulation and Electrical Recording
, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 286-289This paper presents a novel integrated optrode for simultaneous optical stimulation and electrical recording for closed -loop optogenetic neuro-prosthetic applications. The design has been implemented in a commercially available 0.35μm CMOS process. The system includes circuits for controlling the optical stimulations; recording local field potentials (LFPs); and onboard diagnostics. The neural interface has two clusters of stimulation and recording sites. Each stimulation site has a bonding point for connecting a micro light emitting diode (μLED) to deliver light to the targeted area of brain tissue. Each recording site is designed to be post-processed with electrode materials to provide monitoring ofneural activity. On-chip diagnostic sensing has been included to provide real-time diagnostics for post-implantation and during normal operation.
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Journal articleTorricelli D, Gonzalez J, Weckx M, et al., 2016,
Human-like compliant locomotion: state of the art of robotic implementations
, Bioinspiration and Biomimetics, Vol: 11, ISSN: 1748-3182This review paper provides a synthetic yet critical overview of the key biomechanical principles of human bipedal walking and their current implementation in robotic platforms. We describe the functional role of human joints, addressing in particular the relevance of the compliant properties of the different degrees of freedom throughout the gait cycle. We focused on three basic functional units involved in locomotion, i.e. the ankle-foot complex, the knee, and the hip-pelvis complex, and their relevance to whole-body performance. We present an extensive review of the current implementations of these mechanisms into robotic platforms, discussing their potentialities and limitations from the functional and energetic perspectives. We specifically targeted humanoid robots, but also revised evidence from the field of lower-limb prosthetics, which presents innovative solutions still unexploited in the current humanoids. Finally, we identified the main critical aspects of the process of translating human principles into actual machines, providing a number of relevant challenges that should be addressed in future research.
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Journal articleSchweisfurth MA, Markovic M, Dosen S, et al., 2016,
Electrotactile EMG feedback improves the control of prosthesis grasping force
, Journal of Neural Engineering, Vol: 13, ISSN: 1741-2560© 2016 IOP Publishing Ltd. Objective. A drawback of active prostheses is that they detach the subject from the produced forces, thereby preventing direct mechanical feedback. This can be compensated by providing somatosensory feedback to the user through mechanical or electrical stimulation, which in turn may improve the utility, sense of embodiment, and thereby increase the acceptance rate. Approach. In this study, we compared a novel approach to closing the loop, namely EMG feedback (emgFB), to classic force feedback (forceFB), using electrotactile interface in a realistic task setup. Eleven intact-bodied subjects and one transradial amputee performed a routine grasping task while receiving emgFB or forceFB. The two feedback types were delivered through the same electrotactile interface, using a mixed spatial/frequency coding to transmit 8 discrete levels of the feedback variable. In emgFB, the stimulation transmitted the amplitude of the processed myoelectric signal generated by the subject (prosthesis input), and in forceFB the generated grasping force (prosthesis output). The task comprised 150 trials of routine grasping at six forces, randomly presented in blocks of five trials (same force). Interquartile range and changes in the absolute error (AE) distribution (magnitude and dispersion) with respect to the target level were used to assess precision and overall performance, respectively. Main results. Relative to forceFB, emgFB significantly improved the precision of myoelectric commands (min/max of the significant levels) for 23%/36% as well as the precision of force control for 12%/32%, in intact-bodied subjects. Also, the magnitude and dispersion of the AE distribution were reduced. The results were similar in the amputee, showing considerable improvements. Significance. Using emgFB, the subjects therefore decreased the uncertainty of the forward pathway. Since there is a correspondence between the EMG and force, where the former anticipates the latte
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Journal articleHammad SH, Kamavuako EN, Farina D, et al., 2016,
Simulation of a Real-Time Brain Computer Interface for Detecting a Self-Paced Hitting Task.
, Neuromodulation, Vol: 19, Pages: 804-811OBJECTIVES: 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.
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Conference paperRamezani R, Dehkhoda F, Soltan A, et 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: 392-395This 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.
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Journal articleMatthews PM, Hampshire A, 2016,
Clinical concepts emerging from fMRI functional connectomics
, Neuron, Vol: 91, Pages: 511-528, ISSN: 0896-6273Recent 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.
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Journal articleRivera-Rubio J, Arulkumaran K, Rishi H, et al., 2016,
An assistive haptic interface for appearance-based indoor navigation
, Computer Vision and Image Understanding, Vol: 149, Pages: 126-145, ISSN: 1077-3142Computer 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.
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Journal articleWarren RL, Ramamoorthy S, Ciganovic N, et 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: 1091-6490Low-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.
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Journal articleFagerholm ED, Scott G, Shew WL, et al., 2016,
Cortical Entropy, Mutual Information and Scale-Free Dynamics in Waking Mice
, Cerebral Cortex, Vol: 26, Pages: 3945-3952, ISSN: 1460-2199Some 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.
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Conference paperNicolaou N, Constandinou TG, 2016,
Phase-Amplitude Coupling during propofol-induced sedation: an exploratory approach
, FENS Forum of Neuroscience, Publisher: FENS -
Conference paperLuan S, Williams I, de Carvalho F, et al., 2016,
Next Generation Neural Interfaces for low-power multichannel spike sorting
, FENS Forum of Neuroscience, Publisher: FENS -
Journal articleSweeney Y, Clopath C, 2016,
Emergent spatial synaptic structure from diffusive plasticity
, European Journal of Neuroscience, ISSN: 1460-9568Some 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.
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Journal articleHartings JA, Shuttleworth CW, Kirov SA, et 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: 0271-678XA 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.
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Conference paperMarcos 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: 3295-3300Eye 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
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Journal articleDreier JP, Fabricius M, Ayata C, et 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: 0271-678XSpreading 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.
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Conference paperReynolds S, Copeland CS, Schultz SR, et 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: 1945-7928Two-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.
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Journal articleŠtrbac M, Belić M, Isaković M, et 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
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Journal articleBerditchevskaia 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: 2045-2322In 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.
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Journal articleLi 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 articleNicolaou N, Constandinou TG, 2016,
A nonlinear causality estimator based on Non-Parametric Multiplicative Regression
, Frontiers in Neuroinformatics, Vol: 10, ISSN: 1662-5196Causal 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.
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Journal articleYao L, Sheng X, Zhang D, et 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.
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Conference paperElia 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: 534-637This 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.
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Conference paperLiu 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: 538-541In 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.
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Conference paperBarsakcioglu 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: 1310-1313This 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.
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Journal articleKovac M, 2016,
Learning from nature how to land aerial robots
, Science, Vol: 352, Pages: 895-896, ISSN: 0036-8075One 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.
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Journal articlePapadimitriou K, Wang C, Rogers M, et al., 2016,
High-Performance Bioinstrumentation for Real-Time Neuroelectrochemical Traumatic Brain Injury Monitoring
, Frontiers in Human Neuroscience, Vol: 10, ISSN: 1662-5161Traumatic 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.
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