Publications
129 results found
Cork SC, Eftekhar A, Mirza KB, et al., 2018, Extracellular pH monitoring for use in closed-loop vagus nerve stimulation, Journal of Neural Engineering, Vol: 15, Pages: 1-11, ISSN: 1741-2552
Objective: Vagal nerve stimulation (VNS) has shown potential benefits for obesity treatment; however, current devices lack physiological feedback, which limit their efficacy. Changes in extracellular pH (pHe) have shown to be correlated with neural activity, but have traditionally been measured with glass microelectrodes, which limit their in vivo applicability. Approach. Iridium oxide has previously been shown to be sensitive to fluctuations in pH and is biocompatible. Iridium oxide microelectrodes were inserted into the subdiaphragmatic vagus nerve of anaesthetised rats. Introduction of the gut hormone cholecystokinin (CCK) or distension of the stomach was used to elicit vagal nerve activity. Main results. Iridium oxide microelectrodes have sufficient pH sensitivity to readily detect changes in pHe associated with both CCK and gastric distension. Furthermore, a custom-made Matlab script was able to use these changes in pHe to automatically trigger an implanted VNS device. Significance. This is the first study to show pHe changes in peripheral nerves in vivo. In addition, the demonstration that iridium oxide microelectrodes are sufficiently pH sensitive as to measure changes in pHe associated with physiological stimuli means they have the potential to be integrated into closed-loop neurostimulating devices.
Troiani 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: 1-3
The 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.
Gaspar N, Sondhi A, Evans B, et al., 2017, A Low-power Neuromorphic System for Retinal Implants and Sensory Substitution, 12th IEEE Biomedical Circuits and Systems Conference (BioCAS), Publisher: IEEE, Pages: 78-81, ISSN: 2163-4025
This paper describes the design and operation of a system which can be used as a Visual to Auditory Sensory Substitution Device (SSD), as well as the front-end of a real-time retinal prosthesis (RP) or Vision Augmentation (VA) system. Such systems consist of three components: a sensory block to capture the visual scene, a processing block to manage the collected data and generate stimulus patterns, and an output block. For the sensory block we use a Dynamic Vision Sensor (DVS) instead of a conventional camera. A microcontroller is used as the processing block, which receives asynchronous inputs from the DVS in the form of ON/OFF events and treats them like post-synaptic potentials. A simple algorithm based on an Integrate & Fire neuron model is used to emulate temporal contrast sensitive Retinal Ganglion Cells (RGCs). For an RP system the output would be an implanted electrode array, whereas for the SSD a sound is activated based on a certain mapping algorithm. The results are shown in the form of ON or OFF events on the LED matrix (equivalent to the stimulation pattern on an electrode array in the case of an RP), and in the form of a stereo sound output.
Evans BD, Nikolic K, 2017, From bytes to insights with modelling as a service a new paradigm for computational modelling illustrated with PyRhO, 12th IEEE Biomedical Circuits and Systems Conference (BioCAS), Publisher: IEEE, Pages: 316-319, ISSN: 2163-4025
Increasingly large datasets are being made publically available yet the methods and modelling skills to analyze them are lagging behind. In an effort to overcome barriers to analyzing and modelling data we propose the paradigm of Modelling as a Service (MaaS). As a proof-of-concept, we present a case study of the MaaS paradigm with computational tools for optogenetics based upon PyRhO. We demonstrate the benefits it confers in terms of enhanced scope for collaboration, reproducibility and ease of use, especially for scientists with a limited computational background, and discuss directions for future growth. Eventually we aim to grow this project in scope to encompass other modelling and analysis tools, and migrate to JupyterHub for persistent individual user accounts and storage. In the meantime, we hope that this approach will serve to demonstrate how MaaS can substantially increase the appeal and accessibility of modelling.
Mirza KB, Wildner K, Kulasekeram N, et al., 2017, Live Demo: Platform for Closed Loop Neuromodulation Based on Dual Mode Biosignals, IEEE Biomedical Circuits and Systems Conference (BioCAS), Publisher: IEEE, ISSN: 2163-4025
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- Citations: 2
Luo J, Nikolic K, Evans BD, et al., 2016, Optogenetics in silicon: a neural processor for predicting optically active neural networks, IEEE Transactions on Biomedical Circuits and Systems, Vol: 11, Pages: 15-27, ISSN: 1940-9990
We present a reconfigurable neural processor for real-time simulation and prediction of opto-neural behaviour. We combined a detailed Hodgkin–Huxley CA3 neuron integrated with a four-state Channelrhodopsin-2 (ChR2) model into reconfigurable silicon hardware. Our architecture consists of a Field Programmable Gated Array (FPGA) with a custom-built computing data-path, a separate data management system and a memory approach based router. Advancements over previous work include the incorporation of short and long-term calcium and light-dependent ion channels in reconfigurable hardware. Also, the developed processor is computationally efficient, requiring only 0.03 ms processing time per sub-frame for a single neuron and 9.7 ms for a fully connected network of 500 neurons with a given FPGA frequency of 56.7 MHz. It can therefore be utilized for exploration of closed loop processing and tuning of biologically realistic optogenetic circuitry.
Benjamin E, Konstantin N, 2016, Raining fire upon modelling difficulties: PyRhO in the cloud
Nikolic K, Evans B, 2016, Identifying optimal feature transforms for classification and prediction in biological systems: recovering receptive field vectors from sparse recordings, International Conference on Machine Learning (ICML), Workshop on Computational Biology
With biological systems it is often hard to adequately sample the entire input space. With sensoryneural systems this can be a particularly acute problem, with very high dimensional natural inputs andtypically sparse spiking outputs. Here we present an information theory based approach to analysespiking data of an early sensory pathway, demonstrated on retinal ganglion cells (RGC) responding tonatural visual scene stimuli (Katz et al., 2016). We used a non-parametric technique based on theconcept of mutual information (MI), in particular, Quadratic Mutual Information (QMI). The QMIallowed us to very efficiently search the high dimensional space formed by the visual input for a muchsmaller dimensional subspace of Receptive Field Vectors (RFV). RFVs give the most informationabout the response of the cell to natural stimuli. This approach allows us to identify the RFVs far moreefficiently using limited data as we can search the complete stimulus space for multiple vectorssimultaneously. The RFVs were also used to predict the RGCs’ responses to any natural stimuli.Another suitable area of application of this algorithm is in diagnostic inference. Currently we areadapting the method to be used for identifying the cancer markers in the volatile organic compoundspresent in exhaled breath. Once the maximally informative features are established they can be usedfor diagnostic predictions on new breath samples. Preliminary results of the breathomics analysis willbe discussed at the conference.There are several other potential applications such as multiclass categorisation for bacterial strainsusing ISFET arrays for DNA sequencing. This algorithm can be part of a rapid point-of-care device foridentifying the specific infectious agents and recommending appropriate antibiotics.Here we will focus on presenting the algorithm using the example of RFVs of RGCs.
Troiani F, Nikolic K, Constandinou TG, 2016, Optical Coherence Tomography for detection of compound action potential in Xenopus Laevis sciatic nerve, SPIE Photonics West (BIOS)
Due to optical coherence tomography (OCT) high spatial and temporal resolution, this technique could be used to observe the quick changes in the refractive index that accompany action potential. In this study we explorethe use of time domain Optical Coherence Tomography (TD-OCT) for real time action potential detection in ex vivo Xenopus Laevis sciatic nerve. TD-OCT is the easiest and less expensive OCT technique and, if successful indetecting real time action potential, it could be used for low cost monitoring devices. A theoretical investigation into the order of magnitude of the signals detected by a TD-OCT setup is provided by this work. A lineardependence between the refractive index and the intensity changes is observed and the minimum SNR for which the setup could work is found to be SNR = 2 x10⁴.
Evans B, Jarvis S, Schultz S, et al., 2016, PyRhO: A Multiscale Optogenetics Simulation Platform, Frontiers in Neuroinformatics, Vol: 10, ISSN: 1662-5196
Optogenetics has become a key tool for understanding the function of neural circuits and controlling their behavior. An array of directly light driven opsins have been genetically isolated from several families of organisms, with a wide range of temporal and spectral properties. In order to characterize, understand and apply these opsins, we present an integrated suite of open-source, multi-scale computational tools called PyRhO. The purpose of developing PyRhO is three-fold: (i) to characterize new (and existing) opsins by automatically fitting a minimal set of experimental data to three-, four-, or six-state kinetic models, (ii) to simulate these models at the channel, neuron and network levels, and (iii) provide functional insights through model selection and virtual experiments in silico. The module is written in Python with an additional IPython/Jupyter notebook based GUI, allowing models to be fit, simulations to be run and results to be shared through simply interacting with a webpage. The seamless integration of model fitting algorithms with simulation environments (including NEURON and Brian2) for these virtual opsins will enable neuroscientists to gain a comprehensive understanding of their behavior and rapidly identify the most suitable variant for application in a particular biological system. This process may thereby guide not only experimental design and opsin choice but also alterations of the opsin genetic code in a neuro-engineering feed-back loop. In this way, we expect PyRhO will help to significantly advance optogenetics as a tool for transforming biological sciences.
Katz ML, Viney TJ, Nikolic K, 2016, Receptive field vectors of genetically-identified retinal ganglion cells reveal cell-type-dependent visual functions, PLOS One, Vol: 11, ISSN: 1932-6203
Sensory stimuli are encoded by diverse kinds of neurons but the identities of the recorded neurons that are studied are often unknown. We explored in detail the firing patterns of eight previously defined genetically-identified retinal ganglion cell (RGC) types from a single transgenic mouse line. We first introduce a new technique of deriving receptive field vectors (RFVs) which utilises a modified form of mutual information (“Quadratic Mutual Information”). We analysed the firing patterns of RGCs during presentation of short duration (~10 second) complex visual scenes (natural movies). We probed the high dimensional space formed by the visual input for a much smaller dimensional subspace of RFVs that give the most information about the response of each cell. The new technique is very efficient and fast and the derivation of novel types of RFVs formed by the natural scene visual input was possible even with limited numbers of spikes per cell. This approach enabled us to estimate the 'visual memory' of each cell type and the corresponding receptive field area by calculating Mutual Information as a function of the number of frames and radius. Finally, we made predictions of biologically relevant functions based on the RFVs of each cell type. RGC class analysis was complemented with results for the cells’ response to simple visual input in the form of black and white spot stimulation, and their classification on several key physiological metrics. Thus RFVs lead to predictions of biological roles based on limited data and facilitate analysis of sensory-evoked spiking data from defined cell types.
Evans BD, Jarvis S, Schultz SR, et al., 2015, PyRhO: a virtual optogenetics laboratory, BMC Neuroscience, Vol: 16
Gaspar N, Sondhi A, Evans B, et al., 2015, Live demonstration: A low-power neuromorphic system for retinal implants and sensory substitution, BioCAS 2015, Publisher: IEEE
This demonstration shows a new type of front end for a Retinal Prosthesis/Vision Augmentation (RP/VA) System, as well as a Visual to Auditory Sensory Substitution Device (SSD). Each system serves to process visual scenes then present them in a simplified form (augmented with auditory signals) to assist visually impaired people. Both systems consist of three components: a sensory block to capture the visual scene, a processing block to manage the collected data and generate stimulus patterns, and an output block. Here we are presenting two possible setups. In both setups we use a “silicon retina” in the form of a Dynamic Vision Sensor (DVS) for the sensory block. In the hardware implementation, the processing block consists of a microcontroller, with an additional circuit for visual to audio conversion. The result of the visual processing is presented on an LED-matrix, while the SSD (audio) output can be heard on stereo headphones. In the second setup the processing block is an Android device, running an application called SounDVS. This solution also outputs both audio and video signals. The systems represent wearable, low-power, real-time solutions for receiving and processing video input and creating simplified outputs containing the most salient information about the visual scene.
Rapeaux A, Nikolic K, Williams I, et al., 2015, Fiber size-selective stimulation using action potential filtering for a peripheral nerve interface: A simulation study, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Pages: 3411-3414
Functional electrical stimulation is a powerfultool for restoration of function after nerve injury. Howeverselectivity of stimulation remains an issue. This paper presentsan alternative stimulation technique to obtain fiber size-selectivestimulation of nerves using FDA-approved electrode implants.The technique was simulated for the ventral roots ofXenopus Laevis, motivated by an application in bladder control. Thetechnique relies on applying a high frequency alternatingcurrent to filter out action potentials in larger fibers, resultingin selective stimulation of the smaller fibers. Results predict thatthe technique can distinguish fibers with only a 2 µm differencein diameter (for nerves not exceeding 2 mm in diameter). Thestudy investigates the behaviour of electrically blocked nervesin detail. Model imperfections and simplifications yielded someartefacts in the results, as well as unexpected nerve behaviourwhich is tentatively explained.
Leow L, Nikolic K, 2015, Machine vision using combined frame-based and event-based vision sensor, Circuits and Systems (ISCAS), 2015 IEEE International Symposium on
Wadehn F, Schieban K, Nikolic K, 2015, Motion Sensitivity Analysis of Retinal Ganglion Cells in Mouse Retina using Natural Visual Stimuli, 2015 37TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), Pages: 1658-1662, ISSN: 1557-170X
Luan S, Williams I, Constandinou TG, et al., 2014, Neuromodulation: present and emerging methods, Frontiers of Neuroengineering, Vol: 7, ISSN: 1662-6443
Neuromodulation has wide ranging potential applications in replacing impaired neural function (prosthetics), as a novel form of medical treatment (therapy), and as a tool for investigating neurons and neural function (research). Voltage and current controlled electrical neural stimulation (ENS) are methods that have already been widely applied in both neuroscience and clinical practice for neuroprosthetics. However, there are numerous alternative methods of stimulating or inhibiting neurons. This paper reviews the state-of-the-art in ENS as well as alternative neuromodulation techniques - presenting the operational concepts, technical implementation and limitations - in order to inform system design choices.
Jarvis SJ, Nikolic K, Schultz SR, 2014, Optical coactivation in cortical cells: reprogramming the excitation-inhibition balancing act to control neuronal gain in abstract and detailed models, BMC Neuroscience, Vol: 15, Pages: F1-F1, ISSN: 1471-2202
Reverter F, Prodromakis T, Liu Y, et al., 2014, Design Considerations for a CMOS Lab-on-Chip Microheater Array to Facilitate the in vitro Thermal Stimulation of Neurons, IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, Pages: 630-633
Nikolic K, Jarvis S, Schultz S, et al., 2013, Controlling the neuronal balancing act: optical coactivation of excitation and inhibition in neuronal subdomains, Publisher: BioMed Central, ISSN: 1471-2202
Grossman N, Simiaki V, Martinet C, et al., 2013, The spatial pattern of light determines the kinetics and modulates backpropagation of optogenetic action potentials, JOURNAL OF COMPUTATIONAL NEUROSCIENCE, Vol: 34, Pages: 477-488, ISSN: 0929-5313
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- Citations: 30
Nikolic K, Loizu J, 2013, Drosophila Photo-transduction Simulator, Journal of Open Research Software, Vol: 1, Pages: 1-7
Nikolic K, Jarvis S, Grossman N, et al., 2013, Computational Models of Optogenetic Tools for Controlling Neural Circuits with Light, 35th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), Publisher: IEEE, Pages: 5934-5937, ISSN: 1557-170X
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- Citations: 18
Mou Z, Triantis IF, Woods VM, et al., 2012, A Simulation Study of the Combined Thermoelectric Extracellular Stimulation of the Sciatic Nerve of the <i>Xenopus Laevis</i>: The Localized Transient Heat Block, IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, Vol: 59, Pages: 1758-1769, ISSN: 0018-9294
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- Citations: 39
Katz ML, Nikolic K, Delbruck T, 2012, Behavioural Emulation of Event-Based Vision Sensors, IEEE International Symposium on Circuits and Systems, Publisher: IEEE, Pages: 737-740, ISSN: 0271-4302
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- Citations: 1
Katz ML, Nikolic K, Delbruck T, 2012, Live Demonstration: Behavioural Emulation of Event-Based Vision Sensorsh, IEEE International Symposium on Circuits and Systems, Publisher: IEEE, Pages: 736-736, ISSN: 0271-4302
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- Citations: 14
Katz ML, Lutterbeck C, Nikolic K, 2012, An Implementation of Magnocellular Pathways in Event-Based Retinomorphic Systems, IEEE Biomedical Circuits and Systems Conference (BioCAS), Publisher: IEEE, Pages: 17-20, ISSN: 2163-4025
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- Citations: 2
Nikolic K, Grossman N, 2011, Multicompartmental Model of Neurons Expressing Channelrhodopsin, 4th INCF Congress of Neuroinformatics, Frontiers in Neuroscience
Nikolic K, Serb A, Constandinou TG, 2011, An Optical Modulator in Unmodified, Commercially-Available CMOS Technology, IEEE Photonics Technology Letters, Vol: 23, Pages: 1115-1117, ISSN: 1041-1135
Here we present a method and structures for mid-infrared, free-space optical communication using unmodified, commercially available complementary metal-oxide semiconductor integrated circuits. The modulator is based onthe free carrier absorption in parasitic PN junction structures under reverse bias. Measured results demonstrate the proof-of-concept with speeds of 100bps (1.55um wavelength), but at least two orders of magnitude improvement can be achieved. This technology will enable non-galvanic chip-to-chip and chip-to-package communication as an alternative to wirebonding in applications that benefit from a planar top chip surface, such as chemical sensing lab-on-chip systems as well as general sensorsand mid-infrared communication.
Nikolic K, Constandinou TG, Toumazou C, 2011, Method and Apparatus for Optically Outputting Information from a Semiconductor Device
A method of optically outputting information (e.g. digital data) from a semiconductor device, the method comprising: providing a semiconductor device having a semiconducting p-n junction, the p-n junction having a region of reduced free charge carrier density; applying an electrical signal to modulate the extent of the said region, the electrical signal being representative of the information to be outputted; arranging incident light to pass through at least part of the said region, such that the light is at least partially absorbed in dependence upon the modulated extent of the said region, thereby producing intensity-modulated output light; and detecting the intensity of the output light and thereby determining the outputted information. Also provided is an electro-optical assembly, a package module for mounting a semiconductor device on a printed circuit board, and an integrated circuit chip.
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