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Conference paperLeene L, Constandinou TG, 2017,
A 0.5V time-domain instrumentation circuit with clocked and unclocked ΔΣ operation
, IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, Pages: 2619-2622, ISSN: 2379-447XThis paper presents a time-domain instrumentation circuit with exceptional noise efficiency directed at using nanometre CMOS for next generation neural interfaces. Current efforts to realize closed loop neuromodulation and high fidelity BMI prosthetics rely extensively on digital processing which isnot well integrated with conventional analogue instrumentation. The proposed time-domain topology employs a differential ring oscillator that is put into feedback using a chopper stabilized low noise transconductor and capacitive feedback. This realization promises better digital integration by extensively using time encoded digital signals and seamlessly allows both clocked & unclocked ΔΣ behavior which is useful on-chip characterizationand interfacing with synchronous systems. A 0.5V instrumentation system is implemented using a 65nm TSMC technology to realize a highly compact footprint that is 0.006mm2 in size. Simulation results demonstrate an excess of 55 dB dynamic range with 3.5 Vrms input referred noise for the given 810nW total system power budget corresponding to an NEF of 1.64.
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Conference paperKegler M, Etard O, Forte AE, et al., 2017,
Complex statistical model for detecting the auditory brainstem response to natural speech and for decoding attention
, Basic Auditory Science 2017 -
Conference paperForte AE, Etard O, Reichenbach J, 2017,
Selective auditory attention modulates the human brainstem's response to running speech
, Basic Auditory Science 2017 -
Journal articleBass C, Helkkula P, De Paola V, et al., 2017,
Detection of axonal synapses in 3D two-photon images
, PLoS One, Vol: 12, Pages: 1-18, ISSN: 1932-6203Studies of structural plasticity in the brain often require the detection and analysis of axonal synapses (boutons). To date, bouton detection has been largely manual or semi-automated, relying on a step that traces the axons before detection the boutons. If tracing the axon fails, the accuracy of bouton detection is compromised. In this paper, we propose a new algorithm that does not require tracing the axon to detect axonal boutons in 3D two-photon images taken from the mouse cortex. To find the most appropriate techniques for this task, we compared several well-known algorithms for interest point detection and feature descriptor generation. The final algorithm proposed has the following main steps: (1) a Laplacian of Gaussian (LoG) based feature enhancement module to accentuate the appearance of boutons; (2) a Speeded Up Robust Features (SURF) interest point detector to find candidate locations for feature extraction; (3) non-maximum suppression to eliminate candidates that were detected more than once in the same local region; (4) generation of feature descriptors based on Gabor filters; (5) a Support Vector Machine (SVM) classifier, trained on features from labelled data, and was used to distinguish between bouton and non-bouton candidates. We found that our method achieved a Recall of 95%, Precision of 76%, and F1 score of 84% within a new dataset that we make available for accessing bouton detection. On average, Recall and F1 score were significantly better than the current state-of-the-art method, while Precision was not significantly different. In conclusion, in this article we demonstrate that our approach, which is independent of axon tracing, can detect boutons to a high level of accuracy, and improves on the detection performance of existing approaches. The data and code (with an easy to use GUI) used in this article are available from open source repositories.
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Conference paperQuicke P, Neil M, Knopfel T, et al., 2017,
Source-Localized Multifocal Two-Photon Microscopy for High-Speed Functional Imaging
, 71st Annual Meeting of the Society-of-General-Physiologists (SGP) on Optical Revolution in Physiology - From Membrane to Brain, Publisher: ROCKEFELLER UNIV PRESS, Pages: 13A-14A, ISSN: 0022-1295 -
Journal articleSherlock B, Warren SC, Alexandrov Y, et al., 2017,
In vivo multiphoton microscopy using a handheld scanner with lateral and axial motion compensation
, Journal of Biophotonics, Vol: 11, ISSN: 1864-063XThis paper reports a handheld multiphoton fluorescence microscope designed for clinical imaging that incorporates axial motion compensation and lateral image stabilization. Spectral domain optical coherence tomography is employed to track the axial position of the skin surface, and lateral motion compensation is realised by imaging the speckle pattern arising from the optical coherence tomography beam illuminating the sample. Our system is able to correct lateral sample velocities of up to ~65 μm s-1. Combined with the use of negative curvature microstructured optical fibre to deliver tunable ultrafast radiation to the handheld multiphoton scanner without the need of a dispersion compensation unit, this instrument has potential for a range of clinical applications. The system is used to compensate for both lateral and axial motion of the sample when imaging human skin in vivo.
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Journal articleCazé RD, Jarvis S, Foust AJ, et al., 2017,
Dendrites enable a robust mechanism for neuronal stimulus selectivity
, Neural Computation, Vol: 29, Pages: 2511-2527, ISSN: 0899-7667Hearing, vision, touch: underlying all of these senses is stimulus selectivity, a robust information processing operation in which cortical neurons respond more to some stimuli than to others. Previous models assume that these neurons receive the highest weighted input from an ensemble encoding the preferred stimulus, but dendrites enable other possibilities. Nonlinear dendritic processing can produce stimulus selectivity based on the spatial distribution of synapses, even if the total preferred stimulus weight does not exceed that of nonpreferred stimuli. Using a multi-subunit nonlinear model, we demonstrate that stimulus selectivity can arise from the spatial distribution of synapses. We propose this as a general mechanism for information processing by neurons possessing dendritic trees. Moreover, we show that this implementation of stimulus selectivity increases the neuron's robustness to synaptic and dendritic failure. Importantly, our model can maintain stimulus selectivity for a larger range of loss of synapses or dendrites than an equivalent linear model. We then use a layer 2/3 biophysical neuron model to show that our implementation is consistent with two recent experimental observations: (1) one can observe a mixture of selectivities in dendrites that can differ from the somatic selectivity, and (2) hyperpolarization can broaden somatic tuning without affecting dendritic tuning. Our model predicts that an initially nonselective neuron can become selective when depolarized. In addition to motivating new experiments, the model's increased robustness to synapses and dendrites loss provides a starting point for fault-resistant neuromorphic chip development.
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Conference paperMaimon-Mor RO, Fernandez-Quesada J, Zito GA, et al., 2017,
Towards free 3D end-point control for robotic-assisted human reaching using binocular eye tracking
, 15th IEEE Conference on Rehabilitation Robotics (ICORR 2017), Publisher: IEEE, Pages: 1049-1054Eye-movements are the only directly observable behavioural signals that are highly correlated with actions at the task level, and proactive of body movements and thus reflect action intentions. Moreover, eye movements are preserved in many movement disorders leading to paralysis (or amputees) from stroke, spinal cord injury, Parkinson's disease, multiple sclerosis, and muscular dystrophy among others. Despite this benefit, eye tracking is not widely used as control interface for robotic interfaces in movement impaired patients due to poor human-robot interfaces. We demonstrate here how combining 3D gaze tracking using our GT3D binocular eye tracker with custom designed 3D head tracking system and calibration method enables continuous 3D end-point control of a robotic arm support system. The users can move their own hand to any location of the workspace by simple looking at the target and winking once. This purely eye tracking based system enables the end-user to retain free head movement and yet achieves high spatial end point accuracy in the order of 6 cm RMSE error in each dimension and standard deviation of 4 cm. 3D calibration is achieved by moving the robot along a 3 dimensional space filling Peano curve while the user is tracking it with their eyes. This results in a fully automated calibration procedure that yields several thousand calibration points versus standard approaches using a dozen points, resulting in beyond state-of-the-art 3D accuracy and precision.
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Journal articleGhoreishizadeh S, Haci D, Liu Y, et al., 2017,
Four-Wire Interface ASIC for a Multi-Implant Link
, IEEE Transactions on Circuits and Systems I: Regular Papers, Vol: 64, Pages: 3056-3067, ISSN: 1549-8328This paper describes an on-chip interface for recovering power and providing full-duplex communication over an AC-coupled 4-wire lead between active implantable devices. The target application requires two modules to be implanted in the brain (cortex) and upper chest; connected via a subcutaneous lead. The brain implant consists of multiple identical ‘optrodes’ that facilitate a bidirectional neural interface (electrical recording, optical stimulation), and chest implant contains the power source (battery) and processor module. The proposed interface is integrated within each optrode ASIC allowing full-duplex and fully-differential communication based on Manchester encoding. The system features a head-to-chest uplink data rate(up to 1.6 Mbps) that is higher than that of the chest-to-head downlink (100 kbps) which is superimposed on a power carrier. On-chip power management provides an unregulated 5V DC supply with up to 2.5mA output current for stimulation, and two regulated voltages (3.3V and 3V) with 60 dB PSRR for recording and logic circuits. The 4-wire ASIC has been implemented in a 0.35 um CMOS technology, occupying 1.5mm2 silicon area,and consumes a quiescent current of 91.2u A. The system allows power transmission with measured efficiency of up to 66% from the chest to the brain implant. The downlink and uplink communication are successfully tested in a system with two optrodes and through a 4-wire implantable lead.
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Conference paperNoronha B, Dziemian S, Zito GA, et al., 2017,
"Wink to grasp" – comparing eye, voice & EMG gesture control of grasp with soft-robotic gloves
, IEEE Conference on Rehabilitation Robotics (ICORR 2017), Publisher: IEEE, Pages: 1043-1048The ability of robotic rehabilitation devices to support paralysed end-users is ultimately limited by the degree to which human-machine-interaction is designed to be effective and efficient in translating user intention into robotic action. Specifically, we evaluate the novel possibility of binocular eye-tracking technology to detect voluntary winks from involuntary blink commands, to establish winks as a novel low-latency control signal to trigger robotic action. By wearing binocular eye-tracking glasses we enable users to directly observe their environment or the actuator and trigger movement actions, without having to interact with a visual display unit or user interface. We compare our novel approach to two conventional approaches for controlling robotic devices based on electromyo-graphy (EMG) and speech-based human-computer interaction technology. We present an integrated software framework based on ROS that allows transparent integration of these multiple modalities with a robotic system. We use a soft-robotic SEM glove (Bioservo Technologies AB, Sweden) to evaluate how the 3 modalities support the performance and subjective experience of the end-user when movement assisted. All 3 modalities are evaluated in streaming, closed-loop control operation for grasping physical objects. We find that wink control shows the lowest error rate mean with lowest standard deviation of (0.23 ± 0.07, mean ± SEM) followed by speech control (0.35 ± 0. 13) and EMG gesture control (using the Myo armband by Thalamic Labs), with the highest mean and standard deviation (0.46 ± 0.16). We conclude that with our novel own developed eye-tracking based approach to control assistive technologies is a well suited alternative to conventional approaches, especially when combined with 3D eye-tracking based robotic end-point control.
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Conference paperEtard, Reichenbach J, 2017,
EEG-measured correlates of comprehension in speech-in-noise listening
, Basic Auditory Science 2017 -
Conference paperTroiani F, Nikolic K, Constandinou TG, 2017,
Optical coherence tomography for compound action potential detection: a computational study
, SPIE/OSA European Conferences on Biomedical Optics (ECBO), Publisher: Optical Society of America / SPIE, Pages: 1-3The feasibility of using time domain optical coherence tomography (TD-OCT) to detect compound action potential in a peripheral nerve and the setup characteristics, are studied through the use of finite-difference time-domain (FDTD) technique.
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Journal articleHuntley JD, Hampshire A, Bor D, et al., 2017,
The importance of sustained attention in early Alzheimer's disease.
, Int J Geriatr Psychiatry, Vol: 32, Pages: 860-867INTRODUCTION: There is conflicting evidence regarding impairment of sustained attention in early Alzheimer's disease (AD). We examine whether sustained attention is impaired and predicts deficits in other cognitive domains in early AD. METHODS: Fifty-one patients with early AD (MMSE > 18) and 15 healthy elderly controls were recruited. The sustained attention to response task (SART) was used to assess sustained attention. A subset of 25 patients also performed tasks assessing general cognitive function (ADAS-Cog), episodic memory (Logical memory scale, Paired Associates Learning), executive function (verbal fluency, grammatical reasoning) and working memory (digit and spatial span). RESULTS: AD patients were significantly impaired on the SART compared to healthy controls (total error β = 19.75, p = 0.027). SART errors significantly correlated with MMSE score (Spearman's rho = -0.338, p = 0.015) and significantly predicted deficits in ADAS-Cog (β = 0.14, p = 0.004). DISCUSSIONS: Patients with early AD have significant deficits in sustained attention, as measured using the SART. This may impair performance on general cognitive testing, and therefore should be taken into account during clinical assessment, and everyday management of individuals with early AD. Copyright © 2016 John Wiley & Sons, Ltd.
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Journal articleSidiras C, Iliadou V, Nimatoudis I, et al., 2017,
Spoken word recognition enhancement due to preceding synchronized beats compared to unsynchronized or unrhythmic beats
, Frontiers in Neuroscience, Vol: 11, ISSN: 1662-4548The relation between rhythm and language has been investigated over the last decades, with evidence that these share overlapping perceptual mechanisms emerging from several different strands of research. The dynamic Attention Theory posits that neural entrainment to musical rhythm results in synchronized oscillations in attention, enhancing perception of other events occurring at the same rate. In this study, this prediction was tested in 10 year-old children by means of a psychoacoustic speech recognition in babble paradigm. It was hypothesized that rhythm effects evoked via a short isochronous sequence of beats would provide optimal word recognition in babble when beats and word are in sync. We compared speech recognition in babble performance in the presence of isochronous and in sync vs. non-isochronous or out of sync sequence of beats. Results showed that (a) word recognition was the best when rhythm and word were in sync, and (b) the effect was not uniform across syllables and gender of subjects. Our results suggest that pure tone beats affect speech recognition at early levels of sensory or phonemic processing.
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Conference paperLuo JW, Firfilionis D, Ramezani R, et al., 2017,
Live demonstration: A closed-loop cortical brain implant for optogenetic curing epilepsy
A closed-loop optogenetic system for curing epilepsy is presented in this work. As it shown at figure 1, the system consists of a cortical brain implant with LEDs and recording electrodes, a customer designed CMOS chip[1][2][3] and a controller. The brain activities are recorded by the implant with recording electronics in a CMOS chip, the signals are processed by the controller, and the results are send back to the CMOS chip for delivering LED stimulation commands.
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Journal articleBurridge JH, Lee ACW, Turk R, et 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 -
Journal articleLeene L, Constandinou TG, 2017,
A 0.016² 12b ΔΣSAR With 14fJ/conv. for ultra low power biosensor arrays
, IEEE Transactions on Circuits and Systems. Part 1: Regular Papers, Vol: 64, Pages: 2655-2665, ISSN: 1549-8328The instrumentation systems for implantable brain-machine interfaces represent one of the most demanding applications for ultra low-power analogue-to-digital-converters (ADC) to date. To address this challenge, this paper proposes a ΔΣSAR topology for very large sensor arrays that allows an exceptional reduction in silicon footprint by using a continuous time 0-2 MASH topology. This configuration uses a specialized FIR window to decimate the ΔΣ modulator output and reject mismatch errors from the SAR quantizer, which mitigates the overhead from dynamic element matching techniques commonly used to achieve high precision. A fully differential prototype was fabricated using 0.18 μm CMOS to demonstrate 10.8 ENOB precision with a 0.016 mm² silicon footprint. Moreover, a 14 fJ/conv figure-of-merit can be achieved, while resolving signals with the maximum input amplitude of ±1.2,Vpp sampled at 200 kS/s. The ADC topology exhibits a number of promising characteristics for both high speed and ultra low-power systems due to the reduced complexity, switching noise, sampling load, and oversampling ratio, which are critical parameters for many sensor applications.
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Conference paperGhoreishizadeh S, Haci D, Liu Y, et al., 2017,
A 4-wire interface SoC for shared multi-implant power transfer and full-duplex communication
, IEEE Latin American symposium on Circuits and Systems (LASCAS), Publisher: IEEE, Pages: 49-52, ISSN: 2473-4667This paper describes a novel system for recovering power and providing full-duplex communication over an AC-coupled 4-wire lead between active implantable devices. The target application requires a single Chest Device be connected to a Brain Implant consisting of multiple identical optrodes that record neural activity and provide closed loop optical stimulation. The interface is integrated within each optrode SoC allowing full-duplex and fully-differential communication based on Manchester encoding. The system features a head-to-chest uplink data rate (1.6 Mbps) that is higher than that of the chest-to-head downlink (100kbps) superimposed on a power carrier. On-chip power management provides an unregulated 5 V DC supply with up to 2.5 mA output current for stimulation, and a regulated 3.3 V with 60 dB PSRR for recording and logic circuits. The circuit has been implemented in a 0.35 μm CMOS technology, occupying 1.4 mm 2 silicon area, and requiring a 62.2 μA average current consumption.
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Journal articleCiganovic N, Wolde-Kidan A, Reichenbach JDT, 2017,
Hair bundles of cochlear outer hair cells are shaped to minimize their fluid-dynamic resistance
, Scientific Reports, Vol: 7, ISSN: 2045-2322The mammalian sense of hearing relies on two types of sensory cells: inner hair cells transmit the auditory stimulus to the brain, while outer hair cells mechanically modulate the stimulus through active feedback. Stimulation of a hair cell is mediated by displacements of its mechanosensitive hair bundle which protrudes from the apical surface of the cell into a narrow fluid-filled space between reticular lamina and tectorial membrane. While hair bundles of inner hair cells are of linear shape, those of outer hair cells exhibit a distinctive V-shape. The biophysical rationale behind this morphology, however, remains unknown. Here we use analytical and computational methods to study the fluid flow across rows of differently shaped hair bundles. We find that rows of V-shaped hair bundles have a considerably reduced resistance to crossflow, and that the biologically observed shapes of hair bundles of outer hair cells are near-optimal in this regard. This observation accords with the function of outer hair cells and lends support to the recent hypothesis that inner hair cells are stimulated by a net flow, in addition to the well-established shear flow that arises from shearing between the reticular lamina and the tectorial membrane.
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Conference paperAngeles P, Tai Y, Pavese N, et 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 -
Journal articleRogers ML, Leong CL, Gowers SAN, et al., 2017,
Simultaneous monitoring of potassium, glucose and lactate during spreading depolarisation in the injured human brain - proof of principle of a novel real-time neurochemical analysis system, continuous online microdialysis
, Journal of Cerebral Blood Flow and Metabolism, Vol: 37, Pages: 1883-1895, ISSN: 1559-7016Spreading Depolarisations (SDs) occur spontaneously and frequently in injured human brain. They propagate slowly through injured tissue often cycling around a local area of damage. Tissue recovery after an SD requires greatly augmented energy utilisation to normalise ionic gradients from a virtually complete loss of membrane potential. In the injured brain this is difficult because local blood flow is often low and unreactive. In this study we use a new variant of microdialysis, continuous on-line microdialysis (coMD), to observe the effects of SDs on brain metabolism. The neurochemical changes are dynamic and take place on the timescale of the passage of an SD past the microdialysis probe. Dialysate potassium levels provide an ionic correlate of cellular depolarisation and show a clear transient increase. Dialysate glucose levels reflect a balance between local tissue glucose supply and utilization. These show a clear transient decrease of variable magnitude and duration. Dialysate lactate levels indicate non-oxidative metabolism of glucose and show a transient increase. Preliminary data suggest that the transient changes recover more slowly after the passage of a sequence of multiple SD’s giving rise to a decrease in basal dialysate glucose and an increase in basal dialysate potassium and lactate levels.
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Conference paperAngeles P, Tai Y, Pavese N, et al., 2017,
Automated assessment of symptom severity changes during deep brain stimulation (DBS) therapy for Parkinson's disease.
, Publisher: Institute of Electrical and Electronics Engineers Inc., ISSN: 1945-7901 -
Conference paperLuan S, Williams I, De-Carvalho F, et al., 2017,
Standalone headstage for neural recording with real-time spike sorting and data logging
, BNA Festival of Neuroscience, Publisher: The British Neuroscience Association Ltd -
Journal articleQuicke P, Barnes SJ, Knöpfel T, 2017,
Imaging of Brain Slices with a Genetically Encoded Voltage Indicator.
, Methods Mol Biol, Vol: 1563, Pages: 73-84Functional fluorescence microscopy of brain slices using voltage sensitive fluorescent proteins (VSFPs) allows large scale electrophysiological monitoring of neuronal excitation and inhibition. We describe the equipment and techniques needed to successfully record functional responses optical voltage signals from cells expressing a voltage indicator such as VSFP Butterfly 1.2. We also discuss the advantages of voltage imaging and the challenges it presents.
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Conference paperForte AE, Etard O, Reichenbach J, 2017,
Complex Auditory-brainstem Response to the Fundamental Frequency of Continuous Natural Speech
, ARO 2017 -
Conference paperLeene L, Constandinou TG, 2017,
A 0.45V continuous time-domain filter using asynchronous oscillator structures
, IEEE International Conference on Electronics, Circuits and Systems (ICECS), Publisher: IEEE, Pages: 49-52This paper presents a novel oscillator based filter structure for processing time-domain signals with linear dynamics that extensively uses digital logic by construction. Such a mixed signal topology is a key component for allowing efficient processing of asynchronous time encoded signals that does not necessitate external clocking. A miniaturized primitive is introduced as analogue time-domain memory that can be modelled, synthesized, and incorporated in closed loop mixed signal accelerators to realize more complex linear or non-linear computational systems. This is contextualized by demonstrating a compact low power filter operating at 0.45 V in 65 nm CMOS. Simulation results are presented showing an excess of 50 dB dynamic range with a FOM of 7fJ/pole which promises an order of magnitude improvement on state-of-the-art filters in nanometre CMOS.
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Conference paperSundarasaradula Y, Constandinou TG, Thanachayanont A, 2017,
A 6-bit, two-step, successive approximation logarithmic ADC for biomedical applications
, IEEE International Conference on Electronics, Circuits and Systems (ICECS), Publisher: IEEE, Pages: 25-28This paper presents the design and realization of a novel low-power 6-bit successive approximation logarithmic ADC for biomedical applications. A two-step successive approximation method is proposed to obtain a piecewise-linear approximation of the desired logarithmic transfer function. The proposed ADC has been designed and simulated using process parameters from a standard 0.35 μm 2P4M CMOS technology with a single 1.8 V power supply voltage. Simulation results show that, at a sampling rate of 25 kS/s, the proposed ADC consumes 4.36 μW to 14.6 μW (proportional to input amplitudes). The proposed ADC achieves 18.6 pJ/conversion-step, maximum INL of 0.45 LSB, an ENOB of 4.97-bits, and SNDR of 31.7 dB with 1 V full-scale input range.
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Journal articleGhajari M, Hellyer P, Sharp D, 2017,
Computational modelling of traumatic brain injury predicts the location of chronic traumatic encephalopathy pathology
, Brain, Vol: 140, Pages: 333-343, ISSN: 0006-8950Traumatic brain injury can lead to the neurodegenerative disease chronic traumatic encephalopathy. This condition has a clear neuropathological definition but the relationship between the initial head impact and the pattern of progressive brain pathology is poorly understood. We test the hypothesis that mechanical strain and strain rate are greatest in sulci, where neuropathology is prominently seen in chronic traumatic encephalopathy, and whether human neuroimaging observations converge with computational predictions. Three distinct types of injury were simulated. Chronic traumatic encephalopathy can occur after sporting injuries, so we studied a helmet-to-helmet impact in an American football game. In addition, we investigated an occipital head impact due to a fall from ground level and a helmeted head impact in a road traffic accident involving a motorcycle and a car. A high fidelity 3D computational model of brain injury biomechanics was developed and the contours of strain and strain rate at the grey matter–white matter boundary were mapped. Diffusion tensor imaging abnormalities in a cohort of 97 traumatic brain injury patients were also mapped at the grey matter–white matter boundary. Fifty-one healthy subjects served as controls. The computational models predicted large strain most prominent at the depths of sulci. The volume fraction of sulcal regions exceeding brain injury thresholds were significantly larger than that of gyral regions. Strain and strain rates were highest for the road traffic accident and sporting injury. Strain was greater in the sulci for all injury types, but strain rate was greater only in the road traffic and sporting injuries. Diffusion tensor imaging showed converging imaging abnormalities within sulcal regions with a significant decrease in fractional anisotropy in the patient group compared to controls within the sulci. Our results show that brain tissue deformation induced by head impact loading is greatest in sulcal
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Conference paperFrehlick Z, Williams I, Constandinou TG, 2017,
Improving Neural Spike Sorting Performance Using Template Enhancement
, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 524-527This paper presents a novel method for improving the performance of template matching in neural spike sorting for similar shaped spikes, without increasing computational complexity. Mean templates for similar shaped spikes are enhanced to emphasise distinguishing features. Template optimisation is based on the variance of sample distributions. Improved spike sorting performance is demonstrated on simulated neural recordings with two and three neuron spike shapes. The method is designed for implementation on a Next Generation Neural Interface (NGNI) device at Imperial College London.
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Conference paperLeene L, Constandinou TG, 2017,
A 2.7uW/Mips, 0.88GOPS/mm^2 Distributed Processor for Implantable Brain Machine Interfaces
, IEEE Biomedical Circuits and Systems (BioCAS) Conference, Publisher: IEEE, Pages: 360-363This paper presents a scalable architecture in 0.18u m CMOS for implantable brain machine interfaces (BMI) that enables micro controller flexibility for data analysis at the sensor interface. By introducing more generic computational capabilities the system is capable of high level adaptive function to potentially improve the long term efficacy of invasive implants. This topology features a compact ultra low power distributedprocessor that supports 64-channel neural recording system on chip (SOC) with a computational efficiency of 2.7uW/MIPS with a total chip area of 1.37mm2. This configuration executes 1024 instructions on each core at 20MHz to consolidate full spectrum high precision recordings from 4 analogue channels for filtering, spike detection, and feature extraction in the digital domain.
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