97 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, ISSN: 1741-2560
Jarvis S, Nikolic K, Schultz SR, 2018, Neuronal gain modulability is determined by dendritic morphology: A computational optogenetic study., PLoS Comput Biol, Vol: 14
The mechanisms by which the gain of the neuronal input-output function may be modulated have been the subject of much investigation. However, little is known of the role of dendrites in neuronal gain control. New optogenetic experimental paradigms based on spatial profiles or patterns of light stimulation offer the prospect of elucidating many aspects of single cell function, including the role of dendrites in gain control. We thus developed a model to investigate how competing excitatory and inhibitory input within the dendritic arbor alters neuronal gain, incorporating kinetic models of opsins into our modeling to ensure it is experimentally testable. To investigate how different topologies of the neuronal dendritic tree affect the neuron's input-output characteristics we generate branching geometries which replicate morphological features of most common neurons, but keep the number of branches and overall area of dendrites approximately constant. We found a relationship between a neuron's gain modulability and its dendritic morphology, with neurons with bipolar dendrites with a moderate degree of branching being most receptive to control of the gain of their input-output relationship. The theory was then tested and confirmed on two examples of realistic neurons: 1) layer V pyramidal cells-confirming their role in neural circuits as a regulator of the gain in the circuit in addition to acting as the primary excitatory neurons, and 2) stellate cells. In addition to providing testable predictions and a novel application of dual-opsins, our model suggests that innervation of all dendritic subdomains is required for full gain modulation, revealing the importance of dendritic targeting in the generation of neuronal gain control and the functions that it subserves. Finally, our study also demonstrates that neurophysiological investigations which use direct current injection into the soma and bypass the dendrites may miss some important neuronal functions, such as gain m
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.
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.
Luo J, Nikolic K, Evans BD, et al., 2017, 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: 1932-4545
Troiani F, Nikolic K, Constandinou TG, 2017, Optical coherence tomography for compound action potential detection: a computational study, Conference on Optical Coherence Imaging Techniques and Imaging in Scattering Media II, Publisher: SPIE-INT SOC OPTICAL ENGINEERING, ISSN: 0277-786X
Evans BD, Jarvis S, Schultz SR, et al., 2016, PyRhO: A Multiscale Optogenetics Simulation Platform, FRONTIERS IN NEUROINFORMATICS, Vol: 10, ISSN: 1662-5196
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
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, Conference on Clinical and Translational Neurophotonics; Neural Imaging and Sensing; and Optogenetics and Optical Manipulation, Publisher: SPIE-INT SOC OPTICAL ENGINEERING, ISSN: 0277-786X
Gaspar N, Sondhi A, Evans B, et al., 2015, Live Demonstration: A Low-power Neuromorphic System for Retinal Implants and Sensory Substitution, 11th IEEE Annual Biomedical Circuits and Systems Conference (BioCAS), Publisher: IEEE, Pages: 178-178, ISSN: 2163-4025
Leow HS, Nikolic K, 2015, Machine Vision Using Combined Frame-based and Event-based Vision Sensor, IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, Pages: 706-709, ISSN: 0271-4302
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 (EMBC), Publisher: IEEE, Pages: 3411-3414, ISSN: 1557-170X
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
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
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.
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, ISSN: 0271-4302
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
Jarvis S, Nikolic K, Grossman N, et al., 2013, Controlling the neuronal balancing act: optical coactivation of excitation and inhibition in neuronal subdomains., Pages: P348-P348
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
Nikolic K, Loizu J, 2013, Drosophila Photo-transduction Simulator, Journal of Open Research Software, Vol: 1, ISSN: 2049-9647
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
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
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
Mou Z, Triantis IF, Woods VM, et al., 2012, A Simulation Study of the Combined Thermoelectric Extracellular Stimulation of the Sciatic Nerve of the Xenopus Laevis: The Localized Transient Heat Block, IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, Vol: 59, Pages: 1758-1769, ISSN: 0018-9294
Grossman N, Degenaar P, Nikolic K, 2011, Spike engineering with Channelrhodopsin-2, Pages: e27-e27, ISSN: 0304-3940
Grossman N, Nikolic K, Grubb M, et al., 2011, High-frequency limit of neural stimulation with ChR2, Conf Proc IEEE Eng Med Biol Soc, Pages: 4167-4170, ISSN: 1557-170X
Optogenetic technology based on light activation of genetically targeted single component opsins such as Channelrhodopsin-2 (ChR2) has been changing the way neuroscience research is conducted. This technology is becoming increasingly important for neural engineering as well. The efficiency of neural stimulation with ChR2 drops at high frequencies, often before the natural limit of the neuron is reached. This study aims to investigate the underlying mechanisms that limit the efficiency of the stimulation at high frequencies. The study analyzes the dynamics of the spikes induced by ChR2 in comparison to control stimulations using patch clamp current injection. It shows that the stimulation dynamics is limited by two mechanisms: 1) a frequency independent reduction in the conductance-to-irradiance yield due to the ChR2 light adaptation process and 2) a frequency dependent reduction in the conductance-to-current yield due to a decrease in membrane re-polarization level between spikes that weakens the ionic driving force. The effect of the first mechanism can be minimized by using ChR2 mutants with lower irradiance threshold. In contrast the effect of the second mechanism is fundamentally limited by the rate the native ion channels re-polarize the membrane potential.
Grossman N, Nikolic K, Toumazou C, et al., 2011, Modeling Study of the Light Stimulation of a Neuron Cell With Channelrhodopsin-2 Mutants, IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, Vol: 58, Pages: 1742-1751, ISSN: 0018-9294
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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