System Identification and Information Processing for Complex Systems
Lead Research Organisation:
University of Sheffield
Department Name: Automatic Control and Systems Eng
Abstract
The main aim of this Platform Grant proposal is to build upon the expertise of the Sheffield team in signal processing and system identification for nonlinear and complex systems to develop new research themes and application areas. The applicants developed the narmax methodology, a theory for nonlinear systems in the frequency domain, and a class of algorithms for the identification and analysis of spatio-temporal systems. Recent developments at Sheffield mean we are now in a unique position to develop new multi-disciplinary research themes to exploit and build upon this expertise. The new multi-disciplinary research directions that we plan to develop as part of this research proposal include studies of drosophila brain, stem cell dynamics, diffuse optical tomography of brain, space weather systems, and crystal growth phenomena. Each of these offers unique challenges in signal processing and system identification and each requires scoping or feasibility studies to establish the potential to develop each new research area into a core research proposal. The core theme of this Platform Grant proposal is therefore to provide funding to conduct initial scoping research studies into each of these new multi-disciplinary projects with the objective that this will allow the development of each theme to the point where a responsive mode application can be submitted to take the research forward.Career development for members of our group including RA's is a core part of our strategy. The Platform Grant will provide stability for the collaboration by our research team with other disciplines, and should provide a critical mass of researchers and a longer term stable environment around which the career development of outstanding young researchers can be nurtured. The Platform Grant will enable the group to maintain the momentum that has been generated by the formation of two new research centres, and to build upon and exploit the multi-disciplinary partnerships that have been developed to date. The opportunity to take risks, try out completely new approaches, and completely new application fields produces an excitement in the research, enhances moral and longer term strategic research planning and development, allows flexibility, creates opportunities, and provides support for everyone in our group.
Publications
Friederich, U
(2013)
We now know what fly photoreceptors compute
Guo Y
(2013)
Volterra Series Approximation of a Class of Nonlinear Dynamical Systems Using the Adomian Decomposition Method
in Nonlinear Dynamics
Ho C
(2013)
Vibration isolation using nonlinear damping implemented by a feedback-controlled MR damper
in Smart Materials and Structures
Boynton R
(2011)
Using the NARMAX OLS-ERR algorithm to obtain the most influential coupling functions that affect the evolution of the magnetosphere DATA-DEDUCED COUPLING FUNCTIONS
in Journal of Geophysical Research: Space Physics
Balikhin M
(2011)
Using the NARMAX approach to model the evolution of energetic electrons fluxes at geostationary orbit NARMAX MODELLING OF RADIATION BELT ELECTRON FLUXES
in Geophysical Research Letters
Aram P
(2013)
Use of kernel-based Bayesian models to predict late osteolysis after hip replacement.
in Journal of the Royal Society, Interface
Zhao Y
(2012)
Tracking time-varying causality and directionality of information flow using an error reduction ratio test with applications to electroencephalography data.
in Physical review. E, Statistical, nonlinear, and soft matter physics
Nehmzow U
(2010)
Towards modelling complex robot training tasks through system identification
in Robotics and Autonomous Systems
Li Y
(2018)
Time-Varying System Identification Using an Ultra-Orthogonal Forward Regression and Multiwavelet Basis Functions With Applications to EEG.
in IEEE transactions on neural networks and learning systems
| Description | New ways to model and analyse complex nonlinear dynamic systems. |
| Exploitation Route | They are generic system theory results and so can be used by others and applied in many different fields. |
| Sectors | Aerospace, Defence and Marine,Agriculture, Food and Drink,Environment,Healthcare,Pharmaceuticals and Medical Biotechnology |
| Description | The results from this research have been used in a wide range of multidisciplinary applications. Space weather: Models and algorithms developed as part of this research have been used to develop the most accurate models for forecasting geomagnetic indices, solar wind parameters and the radiation environment in the geospace. The forecasts are continuously updated based on real-time data and made available online. NASA is using the models to forecast radiation bursts that could damage or render 'blind' satellites. Systems biology Modelling methodologies developed as part of this grant were instrumental in the development of advanced mathematical models of the fruit fly photoreceptors. These models are now publicly available as part of the fruit fly brain observatory, a major resource for modelling, simulation and visualisation of the Drosophila brain. Modelling and analysis methodologies developed as part of this grant were also instrumental in furthering our understanding of stem cell heterogeneity, adaptation and differentiation. Systems medicine: Modelling and analysis methodologies arising from this grant have been used to understand disease mechanisms using time-course genome-wide gene expression data sets - polycystic kidney disease, acute coronary syndrome- as well as (currently) the impact of ageing on macrophage activity. Signal and information processing algorithms arising from this research formed the basis for novel algorithms for predicting the onset of epilepsy and diagnosing Alzheimer's disease based on EEG data Econometrics: New methods and models for volatility forecasting are being used to better estimate value-at-risk Conflict modelling: Research carried out as part of the project led to new dynamic spatiotemporal modelling tools for the identification of complex underlying processes in conflict, such as diffusion, relocation, heterogeneous escalation, and volatility. The models were used to provide a strikingly statistically accurate forward prediction of armed opposition group activity in Afghanistan in 2010, based solely on data from previous years. The models have been made available to NATO following publication. Climate change: Nonlinear system identification and coupled ocean-iceberg modelling, was used to demonstrate that variability in the number of Greenland icebergs recorded over more than 100 years is predominantly caused by fluctuation in the Greenland ice sheet calving discharge rather than open ocean iceberg melting. |
| First Year Of Impact | 2014 |
| Sector | Aerospace, Defence and Marine,Agriculture, Food and Drink,Chemicals,Communities and Social Services/Policy,Digital/Communication/Information Technologies (including Software),Environment,Financial Services, and Management Consultancy,Healthcare,Pharmaceuticals and Medical Biotechnology,Security and Diplomacy |
| Impact Types | Societal |
| Description | Artificial Intelligence Technology for Cell Therapy Manufacturing |
| Amount | £80,000 (GBP) |
| Funding ID | 2106198 |
| Organisation | Medical Research Council (MRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 10/2018 |
| End | 08/2022 |
| Description | CMMI-EPSRC - Right First Time Manufacture of Pharmaceuticals (RiFTMaP) |
| Amount | £1,543,632 (GBP) |
| Funding ID | EP/V034723/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 08/2021 |
| End | 08/2024 |
| Description | DAFNI-ROSE |
| Amount | £1,083,755 (GBP) |
| Funding ID | EP/V054082/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 06/2021 |
| End | 06/2023 |
| Description | Open Science Prize |
| Amount | $80,000 (USD) |
| Organisation | Wellcome Trust |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 04/2016 |
| End | 12/2016 |
| Description | Platform Grant |
| Amount | £1,210,660 (GBP) |
| Funding ID | EP/H00453X/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 01/2010 |
| End | 01/2015 |
| Description | Program Grant |
| Amount | $900,000 (USD) |
| Funding ID | RGP0001/2012 |
| Organisation | Human Frontier Science Program (HFSP) |
| Sector | Charity/Non Profit |
| Country | France |
| Start | 06/2012 |
| End | 06/2015 |
| Description | Responsive Mode |
| Amount | £615,105 (GBP) |
| Funding ID | BB/K010123/1 |
| Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 04/2013 |
| End | 04/2016 |
| Description | Responsive Mode |
| Amount | £480,313 (GBP) |
| Funding ID | EP/G042209/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 01/2010 |
| End | 01/2014 |
| Description | SURE: Sheffield Undergraduate Research Experience |
| Amount | £1,080 (GBP) |
| Organisation | University of Sheffield |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 06/2018 |
| End | 08/2018 |
| Description | Sustainable microwave manufacturing of functional inorganic materials (SuMMa) |
| Amount | £1,683,171 (GBP) |
| Funding ID | EP/W018950/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 03/2022 |
| End | 02/2025 |
| Description | System Identification and Data Modelling of Complex Nonlinear and Nonstationary Processes |
| Amount | £101,004 (GBP) |
| Funding ID | EP/I011056/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 06/2011 |
| End | 08/2012 |
| Description | The Active Building Centre Research Programme (ABC RP) |
| Amount | £9,324,025 (GBP) |
| Funding ID | EP/V012053/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 04/2020 |
| End | 09/2022 |
| Description | UK Collaboratorium for Research in Infrastructure & Cities: Urban Observatories (Strand B) |
| Amount | £8,000,000 (GBP) |
| Funding ID | EP/P016782/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 04/2017 |
| End | 03/2022 |
| Description | UKCRIC National Infrastructure Database, Modelling, Simulation and Visualisation Facilities |
| Amount | £8,000,000 (GBP) |
| Funding ID | EP/R012202/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 04/2017 |
| End | 09/2021 |
| Title | Bioinformatics tools develoment |
| Description | Development of bioinformatics pipeline for inference of dynamic models of Gene Regulatory Networks |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2017 |
| Provided To Others? | No |
| Impact | Analysis of genome wide gene expression array data from polycystic kidney disease studies |
| Title | Early Olfaction Parkinson's Disease Model |
| Description | This app investigates the effect of the Parkinson's Disease in the early olfactory system. The antennal lobe is the first neuropil in the olfaction sensory pathway, which can be decomposed to ~50 subregions, called glomerulus. Each glomerulus consists of some 50 olfactory sensory neurons (input), and 3-5 projection neurons (output). Glomeruli are interconnected by over 100 local neurons. In total, the antennal lobe has about 2500 olfactory sensory neurons, 150 projection neurons, and 100 local neurons. A healthy model of the antennal lobe developed by the research team is simulated for a given input odorant profile. The ensemble response of projection neurons of each glomerulus is viusalised in both biological view and as an interactive plot. A separate disease model based on the hypothesis that the Parkinson's Disease causes the abnormal inhibitory neurotransmitter (GABA) release was also implemented. The diseased model is simulated with the same input odorant as the healthy model, and its response is provide below alongside the result of the healthy model. |
| Type Of Material | Model of mechanisms or symptoms - human |
| Year Produced | 2018 |
| Provided To Others? | Yes |
| Impact | NA at this time |
| URL | https://neuroapps.fruitflybrain.org/parkinsons/olfaction/ |
| Title | FPGA System for Protein Identification and Quantitation |
| Description | Developed high-performance FPGA-based bioinformatics solution for high-throughput proteomics. Solution consists of a PC server equipped with FPGA board, FPGA implementation of data processing and database search algorithms, server side user interface and data processing software. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2010 |
| Provided To Others? | Yes |
| Impact | The hardware-implemented algorithms for de-noising, baseline correction, peak identification and deisotoping, running on a Xilinx Virtex 2 FPGA at 180 MHz, generate a mass fingerprint over 100 times faster than an equivalent algorithm written in C, running on a Dual 3 GHz Xeon workstation. |
| URL | https://www.liverpool.ac.uk/pfg/Pubs/files/00fe1160f83e43a71c582afd3e5ef1dc-28.html |
| Title | Fruit Fly Brain Observatory |
| Description | Mental and neurological disorders pose major medical and socioeconomic challenges for society. Understanding human brain function and disease is arguably the biggest challenge in neuroscience. To address this challenge, smaller but sufficiently complex brains like that of the fruit fly have been increasingly used for investigating the mechanisms of human neurological and psychiatric disorders, such as Epilepsy or Parkinson's disease, at molecular, cellular and circuit level. The Fruit Fly Brain Observatory (FFBO) is an open source software platform that stores and processes data related to the neural circuits of the fly brain including location, morphology, connectivity and biophysical properties of every neuron; seamlessly integrates the structural and genetic data from multiple sources that can be queried, visualized and interpreted; automatically generates models of the fly brain that can be simulated efficiently using multiple Graphics Processing Units (GPUs) to help elucidate the mechanisms of human neurological disorders and identify drug targets. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2016 |
| Provided To Others? | Yes |
| Impact | Using computational disease models, researchers make targeted modifications that are difficult to perform in vivo with current genetic techniques. Models of neural circuits affected by disease will enable parallel recording of the responses of multiple components of a model circuit that are currently difficult - if not impossible - to perform in vivo. These capabilities significantly accelerate the development of powerful new ways to predict the effects of pharmaceuticals upon neural circuit functions. The software platform has been used to develop and simulate models of Parkinson's disease, retinal degeneration and epilepsy. |
| URL | http://fruitflybrain.org/ |
| Title | Method for modelling adaptation in sensory systems |
| Description | Adaptation is a fundamental characteristic of sensory processing. It enables sensory neurones to map efficiently the extensive range of environmental signals onto their limited dynamic range in order to prevent saturation and to maximize the amount of information collected. We developed a novel two-step approach for identifying both the nonlinear dynamical model and the time evolution of the gain of a self-adaptive sensory system based on experimental data. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2012 |
| Provided To Others? | Yes |
| Impact | We have demonstrated that the processing of visual stimuli at photoreceptor level involves nonlinear transformations which extract and encode efficiently the biologically relevant higher-order statistical properties of natural stimuli. In particular, we have shown that photoreceptors detect and encode local phase correlations, which occur at the location of an edge or line, as well as long-range phase correlations, which characterize symmetry and texture properties of natural images. |
| URL | http://www.dflybrain.org/GainControlModel.html |
| Title | Modelling cell heterogeneity tool |
| Description | Modelling tool for characterising dynamical mechanisms which underpin heterogeneity of cell populations. It allows inferring a dynamical model based on sequences of distribution functions generated using Fluorescence Activated Flow Cytometry. |
| Type Of Material | Model of mechanisms or symptoms - human |
| Year Produced | 2013 |
| Provided To Others? | Yes |
| Impact | Identification of substates within the stem cell compartment. |
| Title | Motility Analysis |
| Description | We developed a framework for characterizing quantitatively different cell lines in terms of their motility and colony-forming properties using individual cell trajectories extracted from time-lapse microscopy images. |
| Type Of Material | Data analysis technique |
| Provided To Others? | No |
| Impact | No major impact yet. We have started to apply this framework to characterize motility of polycystic kidney cells under the the influence of different drugs. |
| Title | NeuroApp - retina degeneration |
| Description | This app that is part of the Fruit Fly Brain Observatory implements a simulation model of retinal degeneration and a rescue scheme by optogenetics means. The compound eye of the fruit fly consists of 700-800 facets, called ommatidia. We model the retina here to have 721 ommatidia, positioned on a hemispherical surface. Each ommatidium hosts 8 photoreceptors. For simplicity, we consider only one photoreceptor in each ommatidium. Each photoreceptor has a microvillar structure called rhabdomere, which is the functional equivalent of the rod and cone outer segment in vertebrate retina. The rhabdomere contains ~30000 microvilli where rhodopsin (light receptor) are hosted. Retinal degeneration often results in reduced size of rhabdomere and partially or completely lacking of rhodopsin. Consequently, the diseased eye has low or no light sensitivity. This simulate a diseased eye by reducing the number of microvilli in each photoreceptor to 5% of the health photoreceptors. The simulated responses of the diseased photoreceptor array can be visualised in real time. |
| Type Of Material | Model of mechanisms or symptoms - human |
| Year Produced | 2018 |
| Provided To Others? | Yes |
| Impact | NA |
| URL | https://neuroapps.fruitflybrain.org/retinal_degeneration/ |
| Title | NeuroApp: Epilepsy model |
| Description | This application implements a whole-brain simulation model of epileptic activity using the fruit-fly brain connectome. In the Healthy model, when stimulus is onset at 2000ms, average rate rise to 2Hz and decrease to below 0.5Hz. Epilepsy is induced by diseased sodium channel that leads to an average firing rate change rapidly from 5Hz to 25Hz. In a rescued model. high activity only emerges in 2000~2100ms. After 2100ms brain reaches a low activity level. |
| Type Of Material | Model of mechanisms or symptoms - human |
| Year Produced | 2018 |
| Provided To Others? | Yes |
| Impact | NA at this time |
| URL | https://neuroapps.fruitflybrain.org/epilepsy/ |
| Title | NeuroApp: Parkinsons Disease Model |
| Description | Parkinson's is a progressive neurological condition. It is estimated that 6.3 million people have Parkinson's worldwide. Some people with Parkinson's disease notice that as the disease progresses their vision loses sharpness or becomes blurred. Difficulties related to the eyes and vision often progress alongside other Parkinson's symptoms. This model-based study investigates the role of Parkinson's disease in the Visual System, using a mathematical model of the early visual system of Drosophila. It has been shown experimentally that both human, and fly models of the disease show a loss of visual acuity, caused by underlying changes in the photoreceptors ability to deal with changing light contrast levels. The disease state is modelled as a change in the capacity of photoreceptors to adapt to changes in contrast in the visual stimuli. |
| Type Of Material | Model of mechanisms or symptoms - human |
| Year Produced | 2018 |
| Provided To Others? | Yes |
| Impact | NA at this time |
| URL | https://neuroapps.fruitflybrain.org/parkinsons/vision/ |
| Title | NeuroGFX |
| Description | NeuroGFX provides an environment to easily explore circuit structure and function ultimately leading to biological validation. On the whole brain level NeuroGFX lays out the guidelines for the development of whole brain emulation. On the neuropil level, NeuroGFX allows users to study the I/O of each LPU. The canonical circuits (circuit motifs) are also identified on this level and NeuroGFX can be used to study the effect of different compositions mediated by local neurons. NeuroGFX features a set of highly intuitive tools for exploring the function of neural circuit models, which can be accessed through. It provides a graphical user interface (GUI), allowing the user that can be used to (i) associate circuit diagrams with biological data, (ii) graphically construct an in silico experiment and execute manipulated circuits on GPUs, (iii) visualize the execution results in the context of biological brain structure. These capabilities are supported by a seamless integration of the NeuroArch database and the Neurokernel engine in the FFBO architecture. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2018 |
| Provided To Others? | Yes |
| Impact | This tool is actively used by a number of research groups in US and UK |
| URL | https://neurogfx.fruitflybrain.org/ |
| Title | NeuroNLP |
| Description | NeuroNLP provides a modern web-based portal for navigating biological data relating to fruit fly brain circuits. It is equipped with a user-friendly, graphical interface to aggregate cell-type, connectome, synaptome and physiology data in the NeuroArch database, with the ability to simultaneously query against and retrieve information from disparate datasets. NeuroNLP features a novel natural language interface that constructs complex queries against the underlying database from plain English instructions such as "show GABAergic neurons that have dendrites in left antennal lobe and axons in both left lateral horn and right dorsolateral protocerebrum" (or simply "show GABAergic neurons that have dendrites in al and axons in both lh and DLP"). This provides highly intuitive access to the integrated fruit fly brain circuit data, without the presumption of knowledge of a query language, syntax or cumbersome user interfaces. The results of the queries are presented using powerful 3D visualization and can be shared using a tag for publication and collaboration. In addition, any neuron in the scene can be explored in greater detail using the information panel, which provides a one stop access to all data associated with a particular neuron. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2018 |
| Provided To Others? | Yes |
| Impact | The tool is being used both by researchers as well as educators |
| URL | https://neuronlp.fruitflybrain.org/ |
| Title | New algorithms for image segementation and tracking |
| Description | New algorithms for image segmentation and tracking based on geometric active contours and information theoretic criteria were developed and used to process images obtained from time-lapse experiments and generate data automatically. Previously, because the existing commercial/open source software available did not work well with the phase contrast images generated by the time-lapse experiments carried out in the lab, the imaging data used to be sent to a group in Germany for analysis. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2010 |
| Provided To Others? | Yes |
| Impact | The new algorithms were used to analyse time-lapse images of normal and adapted hESC colonies providing information about the movement type (random difussion, directed diffusion etc) and interactions (number and duration of contacts with other cells) of individual stem cells in vitro. A journal paper which will incorpoare rhe results of these studies is currently in preparation. |
| Title | New identification approach for neural circuits |
| Description | We developed two new algorithmic tool for identifying sensory circuit models consisting of linear and nonlinear filters in series with spiking neuron models, based on experimental data. |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2018 |
| Provided To Others? | Yes |
| Impact | The new tool was used successfully to analyse data from the Allen Brain Atlas. Too early to quantify the full impact. |
| URL | https://www.mitpressjournals.org/doi/abs/10.1162/neco_a_01051 |
| Description | Ann-Shyn Chiang Laboratrory Taiwan |
| Organisation | National Tsing Hua University (Taiwan) |
| Country | Taiwan, Province of China |
| Sector | Academic/University |
| PI Contribution | Developed analysis and visualisation tools for the fruit fly connectome. See http://fruitflybrain.org/. |
| Collaborator Contribution | Constructed a brain-wide wiring diagram at single-cell resolution |
| Impact | http://fruitflybrain.org/ |
| Start Year | 2016 |
| Description | Bionet |
| Organisation | Columbia University |
| Department | Electrical Engineering |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | We developed, and refined models of the retina for simulation on the Neurokernel platform. |
| Collaborator Contribution | Developed the initial open source simulation platform Neurokernel. Provided tools and resources for our group to use. |
| Impact | Open Science Prize Application This is a multi-disciplinary collaboration to develop models and a software platform for simulating the entire brain of the fruit fly: biology, computer science, control and systems engineering |
| Start Year | 2015 |
| Description | NVIDIA |
| Organisation | NVIDIA |
| Country | Global |
| Sector | Private |
| PI Contribution | Evaluation of new GPU architectures |
| Collaborator Contribution | Training and technical support. In-kind contribution of £30K |
| Impact | None yet |
| Start Year | 2015 |
| Description | Oxford |
| Organisation | University of Oxford |
| Department | Department of Physiology, Anatomy and Genetics |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | We are developing modelling and simulation tools to make experimentally plausible and accurate models of the fruit fly brain. |
| Collaborator Contribution | They support the drosophila brain project with data, evaluation & testing of the software, and to help validate models. |
| Impact | No outputs yet. Multi-disciplinary: biology, systems engineering, control engineering |
| Start Year | 2015 |
| Description | Stem Cell Australia |
| Organisation | University of Melbourne |
| Department | Centre for Neuroscience Research |
| Country | Australia |
| Sector | Academic/University |
| PI Contribution | Modelling and analysis of experimental data |
| Collaborator Contribution | Single cell QPCR data Microdiscetion and subfractionation experiments |
| Impact | Multidisciplinary collaboration funded by a HFSP program grant started in June 2012 We presented new research results at the 2013 Awardees Meeting in Strasbourg |
| Start Year | 2012 |