Chairs
Dr Stephen Larson, The OpenWorm Foundation, USA
Dr Stephen Larson, The OpenWorm Foundation, USA
Stephen Larson is the CEO of MetaCell, a custom software services company for the life sciences with clients like the University College London and Pfizer. He has presented at more than two dozen forums, published over a dozen articles in academic journals such as Nature and Frontiers in Neuroscience, and has had his work featured in the Economist, the New York Times, Wired, the Atlantic, at two TEDx forums and a Science Channel show with Morgan Freeman. He is a graduate of MIT in Computer Science and received a PhD in Neuroscience from the University of California, San Diego. He previously served as the Chief Information Officer of One Mind for Research, a nonprofit dedicated to eradicating brain disease through innovative public-private partnerships. He has worked as a professional software engineer for a major global investment bank and co-developed a patent. He has served as a mentor in the Google Summer of Code program, a volunteer leader in the Startup Leadership Program, an entrepreneurial incubator, and the INCF, an international organization for coordinating the information science of neuroscience.
09:00-09:25
Modelling, visualizing and understanding the neural dynamics of Caenorhabditis elegans
Dr Eli Shlizerman, University of Washington, USA
Abstract
Connectomes of organisms, such as the nematode Caenorhabditis elegans (C. elegans), have been mapped on various scales: from macro to single neuron level. In addition, decades of research in describing biophysical processes have provided foundations for modeling single neuron dynamics as well as synaptic and electric processes between neurons. Thereby, models which incorporate biophysical dynamical system acting on top of the static connectome, called dynomes, become more detailed and realizable. Availability of near-complete connectome data along with experimental quantification of responses and interactions allowed us to develop a detailed dynome model for C. elegans’ somatic nervous system. Employing an interactive visualization platform to simulate the dynome we apply various stimuli regimes and show robust low-dimensional bifurcation structures which drive a variety of multistable neural voltage modes, such as fixed points, limit cycles, multi-oscillatory dynamics. Comparison of these modes with experimental studies allows us to link behavioral states with network responses in the form of low-dimensional attractors and transitions between them.
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Dr Eli Shlizerman, University of Washington, USA
Dr Eli Shlizerman, University of Washington, USA
Eli Shlizerman is a Washington Research Foundation Assistant Professor of Applied Mathematics and Electrical Engineering at the University of Washington. Shlizerman’s research focuses on analysing complex dynamic networks, such as the nervous system. Typically, such networks are extremely challenging to study due to their complex structure and intricate time-dependent dynamics. To overcome these challenges, Shlizerman developed analysis methods that fuse data analysis with dynamical system theory to determine the behaviour of complex systems. Particular interests of Shlizerman’s lab are in applying analysis methods to invertebrates sensory systems. He is currently researching the olfactory system in moths, sun-compass navigation in Monarch butterflies and the nervous system in the C. elegans worm. Shlizerman’s research has resulted in answers to longstanding questions. His analysis of the olfactory system in moths led to the development of a prototype of the antennal lobe, published in Science and covered by popular media. His work on Monarch butterflies’ time compensated sun-compass showed how neural signals can be integrated to support long directional migration by the butterfly, featured on the cover of Cell Reports and covered by popular media such as the BBC. For C. elegans Shlizerman and his collaborators developed a neural activity model of the full C. elegans nervous system and were able to find stimuli that lead to oscillation enabling bifurcations that correspond to behaviors of the worm. Shlizerman was honored with a joint NSF-NIGMS Award, Boeing Awards for outstanding research and teaching and Washington Research Foundation Innovation award.
09:30-09:55
Modelling the neural network of C. elegans at multiple scales with c302
Dr Padraig Gleeson, University College London, UK
Abstract
Computational models of the nervous system are developed at multiple scales to answer questions about how low level interactions between biological entities lead to higher level functions. Models of the nematode C. elegans have also been created at levels from individual neurons and muscles, subcircuits responsible for processing specific sensory inputs, body wide processes including locomotion, and detailed nervous system/musculature models. These models usually select a subset of anatomical and physiological properties of the worm and can address a specific set of questions relevant to that level of detail. The OpenWorm project has developed c302, a framework in Python which aims to facilitate creation of models of the nervous system and musculature of C. elegans, comprising all known cells or subsets thereof, and incorporating varying levels of detail for neurons, muscles and synapses. Information on the numbers, types, and polarity of synaptic connections are included in the models from the structured information on these gathered by the project. The models generated can be used with a variety of tools for model visualisation, simulation and analysis. Dr Padraig Gleeson will present c302 and show how these nervous system models are being incorporated into detailed 3D worm body models in OpenWorm.
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Dr Padraig Gleeson, University College London, UK
Dr Padraig Gleeson, University College London, UK
Padraig Gleeson is a Principal Research Associate in the Department of Neuroscience, Physiology and Pharmacology at UCL. He is leading the development of Open Source Brain, for online model sharing, visualization, analysis and simulation in neuroscience. He is a major contributor to the NeuroML language for computational neuroscience, and developed neuroConstruct, for building complex 3D neuronal networks. He is a core contributor to OpenWorm, which seeks to build an in-silico model of the roundworm C. elegans. He is also a coordinator of the COmputational Modelling in BIology NEtwork (COMBINE) which promotes interoperability of standards and tools across the biological sciences, and was elected a director of the Organization for Computational Neurosciences in 2014.
10:00-10:25
Taming complexity: controlling networks
Professor Albert-László Barabási, Northeastern University and Harvard Medical School, USA
Abstract
The ultimate proof of our understanding of biological or technological systems is reflected in our ability to control them. While control theory offers mathematical tools to steer engineered and natural systems towards a desired state, we lack a framework to control complex self-organized systems. Here Albert-László will explore the controllability of an arbitrary complex network, identifying the set of driver nodes whose time-dependent control can guide the system’s entire dynamics. Virtually all technological and biological networks must be able to control their internal processes. Given that, issues related to control deeply shape the topology and the vulnerability of real systems. Consequently, unveiling the control principles of real networks, the goal of our research, forces us to address series of fundamental questions pertaining to our understanding of complex systems. Finally, Albert-László will discuss how control principles inform our ability to predict neurons involved in specific processes in the brain, offering an avenue to experimentally falsify and test the predictions of network control.
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Professor Albert-László Barabási, Northeastern University and Harvard Medical School, USA
Professor Albert-László Barabási, Northeastern University and Harvard Medical School, USA
Albert-László Barabási is both the Robert Gray Dodge Professor of Network Science and a Distinguished University Professor at Northeastern University, where he directs the Center for Complex Network Research, and holds appointments in the Departments of Physics and Computer Science, as well as in the Department of Medicine, Harvard Medical School and Brigham and Women Hospital, and is a member of the Center for Cancer Systems Biology at Dana Farber Cancer Institute. A Hungarian born native of Transylvania, Romania, he received his Masters in Theoretical Physics at the Eötvös University in Budapest, Hungary and was awarded a PhD three years later at Boston University. Barab‡si latest book is 'Bursts: The Hidden Pattern Behind Everything We Do' (Dutton, 2010) available in five languages. He has also authored 'Linked: The New Science of Networks' (Perseus, 2002), currently available in eleven languages, and is the co-editor of 'The Structure and Dynamics of Networks' (Princeton, 2005). His work lead to the discovery of scale-free networks in 1999, and proposed the Barabási-Albert model to explain their widespread emergence in natural, technological and social systems, from the cellular telephone to the WWW or online communities.
Barabási is a Fellow of the American Physical Society. In 2005 he was awarded the FEBS Anniversary Prize for Systems Biology and in 2006 the John von Neumann Medal by the John von Neumann Computer Society from Hungary, for outstanding achievements in computer-related science and technology. In 2004 he was elected into the Hungarian Academy of Sciences and in 2007 into the Academia Europaea. He received the C&C Prize from the NEC C&C Foundation in 2008. In 2009 APS chose him Outstanding Referee and the US National Academies of Sciences awarded him the 2009 Cozzarelli Prize. In 2011 Barabási was awarded the Lagrange Prize-CRT Foundation for his contributions to complex systems, awarded Doctor Honoris Causa from Universidad PolitŽcnica de Madrid, became an elected Fellow in AAAS (Physics) and is an 2013 Fellow of the Massachusetts Academy of Sciences.
10:30-10:35
Geppetto - An open platform for biology data exploration, visualization and simulation
Mr Matteo Cantarelli, OpenWorm Foundation, USA
Abstract
Geppetto (geppetto.org) is an open-source web-based platform to explore and simulate neuroscience data and models. The platform, originally designed to support the simulation of a cell-level model of C. elegans as part of the OpenWorm project, has grown into a generic framework suitable for various neuroscience applications, offering out of the box solutions for data visualisation, integration and simulation. Geppetto is today used by Open Source Brain (opensourcebrain.org), to explore and simulate computational neuroscience models described in NeuroML version 2 with a variety of simulators and by the Virtual Fly Brain (virtualflybrain.org) to explore and visualise anatomy (including neuropil, segmented neurons and gene expression pattern data) and ontology knowledge base of Drosophila melanogaster. Geppetto is also being used to build a new experimental UI for the NEURON simulation environment based on Python and Jupyter. WormSim (wormsim.org) embeds Geppetto to let users explore dynamic mechanical and electrophysiological models of C. elegans produced by the OpenWorm project. Geppetto is capable of reading and visualising experimental data in the NWB format (nwb.org) to allow experimental and computational neuroscientists to share and compare data and models using a common platform.
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Mr Matteo Cantarelli, OpenWorm Foundation, USA
Mr Matteo Cantarelli, OpenWorm Foundation, USA
Matteo Cantarelli is a software architect and entrepreneur. He is the architect and project coordinator of Geppetto an open source platform to build neuroscience and biology applications aimed at visualizing and simulating experimental and computational data and models in the web browser. Matteo is co-founder and CTO of MetaCell a US and UK based company developing advanced software for neuroscience research. In 2011 Matteo co-founded OpenWorm, a not for profit foundation building a cellular model of the C. elegans. Matteo worked also as a Principal Research Associate with the Department of Neuroscience, Physiology and Pharmacology at the University College of London contributing to developing Open Source Brain, a Wellcome Trust funded platform to share and develop computational models of neurons and networks. He earned a Master in Systems Engineering at the École Normale Supérieure de Cachan, France in 2005 and a Master and Bachelor degree in Electronic Engineering from the University of Cagliari, Italy.
11:30-11:55
Reproducibility and rigour: testing the data driven model in C. elegans
Professor Sharon Crook, Arizona State University, USA
Abstract
Computational models provide a framework for integrating data across spatial scales and for exploring hypotheses about the mechanisms underlying neuronal and network dynamics. We have contributed to a successful system of interoperable, open source tools to address issues around creating, exchanging, and re-using models in neuroscience. In spite of this promising movement toward model sharing and reproducibility in the neuroscience community, it is extremely rare to see a specific, rigorous statement of the criteria used for evaluating models against experimental data. Another collaborative project from our group is providing a flexible infrastructure for assessing the scope and quality of models. The goal is to integrate experimental data with modeling efforts for more efficiency, better transparency, and greater impact of computational models in neuroscience research. We highlight examples of model validation from the C. elegans nervous system and also propose how hierarchical model validation, proceeding from the testing of small model components all the way to entire systems, can be used to systematically build a biologically-inspired model of an entire organism.
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Professor Sharon Crook, Arizona State University, USA
Professor Sharon Crook, Arizona State University, USA
Dr Crook earned her PhD in Applied Mathematics at the University of Maryland at College Park. Her dissertation research with John Rinzel at the Mathematical Research Branch of the National Institutes of Health focused on coupled oscillator models for cortical dynamics in collaboration with Bard Ermentrout at the University of Pittsburgh. She then held a postdoctoral appointment at the Center for Computational Biology at Montana State University with John Miller and Gwen Jacobs, where she did joint work in neurophysiology, modeling, and neuroinformatics. Dr Crook now holds a joint appointment between the School of Mathematical and Statistical Sciences and the School of Life Sciences at Arizona State University, where she uses computational approaches to study the dynamics of neurons and neuronal networks and the mechanisms underlying plasticity. Dr Crook also contributes to the development of NeuroML, an international effort to create a common standard for describing computational models for neuroscience research, and related tools.
12:00-12:45
Panel discussion