January 2019 - Comp-neuro - lists.cnsorg.org

Call for applications - 2019 Nengo Summer School
by Peter Blouw Jan. 3, 2019

Jan. 3, 2019

[All details about this school can be found online at https://www.nengo.ai/summerschool] The Centre for Theoretical Neuroscience at the University of Waterloo is excited to announce our 6th annual Nengo summer school on large-scale brain modelling and neuromorphic computing. This two-week school will teach participants to use the Nengo simulation package to build state-of-the-art cognitive and neural models to run both in simulation and on neuromorphic hardware. Summer school participants will be given on-site access to Loihi, Intel’s new neuromorphic research chip [1], and will learn to run high-level applications on Loihi using Nengo! More generally, Nengo provides users with a versatile and powerful environment for designing cognitive and neural systems, and has been used to build what is currently the world's largest functional brain model, Spaun [2], which includes spiking deep learning, reinforcement learning, adaptive motor control, and cognitive control networks. For a look at last year's summer school, check out this short video: https://www.youtube.com/watch?v=NwtYgBB2N6I We welcome applications from all interested graduate students, postdocs, professors, and industry professionals with a relevant background. [1] Davies, et al. (2018). Loihi: A neuromorphic manycore processor with on-chip learning. IEEE Micro. Vol. 38 no. 1 pp. 82-99. [ https://ieeexplore.ieee.org/document/8259423] [2] Eliasmith, C., Stewart T. C., Choo X., Bekolay T., DeWolf T., Tang Y., Rasmussen, D. (2012). A large-scale model of the functioning brain. Science. Vol. 338 no. 6111 pp. 1202-1205. DOI: 10.1126/science.1225266. [ http://compneuro.uwaterloo.ca/files/publications/eliasmith.2012.pdf] ***Application Deadline: February 15, 2019*** Format: A combination of tutorials and project-based work. Participants are encouraged to bring their own ideas for projects, which may focus on testing hypotheses, modeling neural or cognitive data, implementing specific behavioural functions with neurons, expanding past models, or providing a proof-of-concept of various neural mechanisms. Hands-on tutorials, work on individual or group projects, and talks from invited faculty members will make up the bulk of day-to-day activities. A project demonstration event will be held on the last day of the school, with prizes for strong projects! Participants will have the opportunity to learn how to: - interface Nengo with neuromorphic hardware (e.g. Loihi, SpiNNaker) - build perceptual, motor, and cognitive models using spiking neurons - model anatomical, electrophysiological, cognitive, and behavioural data - use a variety of single cell models within a large-scale model - integrate machine learning methods into biologically oriented models - interface Nengo with cameras and robotic systems - implement modern nonlinear control methods in neural models - and much more… Date and Location: June 9th to June 21st, 2019 at the University of Waterloo, Ontario, Canada. Applications: Please visit http://www.nengo.ai/summerschool, where you can find more information regarding costs, travel, lodging, along with an application form listing required materials. If you have any questions about the school or the application process, please contact Peter Blouw (peter.blouw(a)appliedbrainresearch.com) The school is also partly supported by ONR and ABR, Inc. We look forward to hearing from you!

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PhD in Computational and Mathematical Neuroscience (EPSRC funded, 3.5 yrs, Sept 2019 start)
by James Rankin Jan. 3, 2019

Jan. 3, 2019

*PhD in Computational and Mathematical Neuroscience (EPSRC funded, 3.5 yrs, Sept 2019 start)* General information & apply (funding is primarily targeted at UK students): http://www.exeter.ac.uk/studying/funding/award/index.php?id=3386 Project description: http://www.exeter.ac.uk/codebox/phdprojects/Rankin-EPSRC-DTP-Project.pdf *Closing date 7th Jan 2019* This interdisciplinary project will develop computational and mathematical models of the auditory system to understand how complex stimuli like speech are encoded by spiking neurons in the midbrain. The auditory midbrain is a key hub in the auditory processing pathway, functioning as an important junction that relays and shapes neural signals as they ascend towards auditory cortex. Knowledge of the way in which complex sounds, e.g. speech, are encoded in the midbrain is crucial for understanding how dysfunction in the earlier auditory processing pathway (cochlea, auditory nerve, cochlear nucleus) leads to different types of hearing loss (a problem affecting 1 in 6 people in the UK). Working with neural recordings from the auditory midbrain in gerbils, a commonly-used animal for the study of low-frequency hearing, this project will develop mathematical and computational models of the auditory processing pathway. The aim is to understand the different roles of the patterns of inputs to midbrain neurons and their intrinsic response properties (e.g. their spiking rate) in shaping their responses to complex sounds. The project will use a dynamical systems approach to model the intrinsic properties of individual neurons in the midbrain in a biologically plausible way (working with, e.g. adaptive exponential integrate-and-fire neurons or the Hodgkin-Huxley equations). Inputs to these neurons will be based on established cochlear models and the biological details of the auditory nerve and cochlear nucleus. The resulting model will produce firing patterns directly comparable with neural recordings provided by the experimental supervisor. This data will be used to train and parameter fit the model using e.g. Bayesian optimisation or genetic algorithms. The resultant model will have explanatory power for the extent to which midbrain responses are shaped by its inputs from cochlear nucleus. Further, it will make predictions, testable in new experiments, of how midbrain responses will be affected by different dysfunctions of the early auditory system relating to hearing loss. The successful candidate will receive training dynamical systems theory and in the development and analysis of individual neuron and neural network models. An interdisciplinary approach, incorporating known biological details of the auditory processing pathway, will require the candidate to learn the relevant biology and neuroscience along with mathematical and computational techniques. The project will involve working closely with experimental neuroscientists and experimental data. This project provides a unique opportunity to receive training in mathematical modelling in close collaboration with experimentalists using cutting-edge methods recording spikes simultaneously from hundreds of neurons. Experience working on such interdisciplinary projects is highly sought after. Candidates with quantitative backgrounds (mathematics, physics, engineering) and from neuroscience programmes are encouraged to apply. Programming experience, knowledge of dynamical systems theory and experience in biological modelling are a plus. For further information, please contact me at the email address above. *For further information, please contact Dr James Rankin, email j.a.rankin(a)exeter.ac.uk <j.a.rankin(a)exeter.ac.uk>* http://emps.exeter.ac.uk/mathematics/staff/jar226

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NIH-funded Postdoctoral Position at the Italian Institute of Technology
by Stefano Panzeri Jan. 3, 2019

Jan. 3, 2019

I am seeking to hire one or more postdoctoral scientists to research with me and my Neural Computation laboratory at the Istituto Italiano di Tecnologia. The project, funded by a Brain Initiative multi-PI RO1 Grant from the National Institute of Health, will be performed in collaboration with my experimental collaborators Christopher Harvey (Harvard Medical School) and Wei-Chung Lee (Children’s Hospital). The proposed computational research will use data-driven models of recurrent neural networks and information-theoretic methods to analyze functional activity of hundreds of neurons recorded during cognitive tasks, together with anatomical electron-microscopy data collected from the same subjects and brain regions. The aim of the project is to establish novel and firm relationships between the anatomical structure of a cortical microcircuit and its neural population coding function. The laboratory offers a wide range of interdisciplinary expertise in computational neuroscience, including both advanced neural analysis techniques and neural network modeling. The laboratory also offers a thriving, well-funded and ambitious research environment with extensive international collaborations and ample opportunities for advanced training and personal scientific growth. We seek candidates holding a PhD in a numerate or neuroscientific discipline, with a solid computational background and a keen interest in neuroscience. They must be highly motivated and creative individuals who want to work in a dynamic, multi-disciplinary research environment and be willing to interact with both experimental and theoretical neuroscientists. The successful candidate will have the opportunity to conduct research at either the IIT in Italy, or at the IIT outstation at Harvard Medical School, in Boston, depending on the nature of the agreed research and on personal preferences. For representative recent publications from the PI, see: Runyan C. A., et al (2017) Distinct timescales of population coding across cortex, *Nature*: 548: 92-96. Panzeri S., et al (2017) Cracking the neural code for sensory perception by combining statistics, intervention and behaviour. *Neuron* 93: 491-507 Safaai, H., et al (2015) Modelling the effect of Locus Coeruleous firing on single trial cortical state dynamics and sensory processing. *Proc. Natl. Acad. Sci. USA* 112(41): 12834–12839 Further information about my research can be found at my IIT and Google Scholar web pages: https://www.iit.it/people/stefano-panzeri https://scholar.google.it/citations?user=C-HCQ9cAAAAJ&hl=en Applications (full CV, statement of research interest and name and contact of 2 referees) should be sent by e-mail to stefano.panzeri(a)iit.it, quoting “Postdoctoral position in Computational Neuroscience” in the subject line. The deadline for applications is January 31th, 2019. Applications will be examined until the position is filled. Interested applicants are advised to contact me by email informally *as soon as possible* to discuss about the science and the position informally. Thanks! Stefano Panzeri

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CFP 28th International Conference on Artificial Neural Networks ICANN 2019, Sept 17-19, Munich, DE
by Paolo Masulli ENNS Jan. 2, 2019

Jan. 2, 2019

28th International Conference on Artificial Neural Networks http://icann2019.org Munich, Germany 17 - 19 September 2019 Special event: BIGCHEM (http://bigchem.eu) final meeting ============================================================ The International Conference on Artificial Neural Networks (ICANN) is the annual flagship conference of the European Neural Network Society (ENNS). In 2019 the Helmholtz Zentrum Muenchen - German Research Center for Environmental Health GmbH (HMGU) and the Technical University of Munich (TUM) together with the "Big Data in Chemistry" Marie Skłodowska-Curie Innovative Training Network European Industrial Doctorate project (BIGCHEM) organize the 28th ICANN Conference from the 17th to the 19th of September 2019 in Munich, Germany. CONFERENCE TOPICS ICANN 2019 is a dual-track conference featuring tracks in Brain Inspired Computing and Machine Learning and Artificial Neural Networks, with strong cross-disciplinary interactions and applications. All research fields dealing with Neural Networks will be present at the conference. A non-exhaustive list of topics includes: Machine Learning: Deep Learning, Neural Network Theory, Neural Network Models, Graphical Models, Bayesian Networks, Kernel Methods, Generative Models, Information Theoretic Learning, Reinforcement Learning, Relational Learning, Dynamical Models Recurrent Networks. Brain Inspired Computing: Cognitive models, Computational Neuroscience, Self-organisation, Reinforcement Learning, Neural Control and Planning, Hybrid Neural-Symbolic Architectures, Neural Dynamics. Neural Applications for: Bioinformatics, Biomedicine, Intelligent Robotics, Neurorobotics, Language Processing, Image Processing, Sensor Fusion, Pattern Recognition, Data Mining, Neural Agents, Brain-Computer Interaction, Neural Hardware, Evolutionary Neural Networks. Special session (BIGCHEM): Big Data analysis in chemistry, chemoinformatics, use of deep learning to predict molecular properties, drug-discovery, modelling and prediction of chemical reaction data, synthetic route prediction, structure generation, molecular dynamics simulations and quantum chemistry. CALL FOR CONTRIBUTED SCIENTIFIC COMMUNICATIONS All scientific communications presented at ICANN 2019 will be reviewed and scientifically evaluated by a panel of experts. The conference will feature three categories of communications: - oral communications (15'+5') - poster communications - demonstrations Call for Special Sessions: ICANN2019 organizers cordially invite internationally recognised experts to organise Special Sessions (including workshops and competitions) within the general scope of the conference. Special Session Proposal request should be sent to icann2019(a)bigchem.eu Call for Papers: Authors willing to present original contributions in either oral or poster category may submit: - a proceedings paper manuscript of about 10 - 12 pages to be published in Springer-Verlag Lecture Notes in Computer Science (LNCS) series with individual DOI - extended abstracts of a maximum length of 2 pages to be published in Springer-Verlag Lecture Notes in Computer Science (LNCS) series. The number of oral slots is limited. In case the number of requested oral presentations is larger than the available slots the ICANN scientific committee will select which papers will be reassigned to a poster session. This selections will be based on the coherence of the programme and is totally independent of the category of submission. Submission of communications will be online. More details will be made available soon on the conference website: http://icann2019.org IMPORTANT DATES Deadline of special sessions submission: 1 February 2019 Opening of contribution submissions: 1 February 2019 Submission of demonstration proposals: 1 March 2019 Deadline of proceedings paper submission: 15 March 2019 Deadline of extended abstracts submission: 1 April 2019 Notification of acceptance: 1 May 2019 Camera-ready paper and registration opening: 1 June 2019 Deadline early registration at discount rate: 15 June 2019 Conference dates: 17-19 September 2019 BEST PAPER AWARDS ENNS will sponsor a maximum of four best paper awards, two in the Brain Inspired Computing track (one poster and one oral communication) and, analogously, two in the Machine Learning Research track. All awardees will be presented during the final ceremony. TRAVEL GRANTS The European Neural Network Society sponsors a number of Student Travel Grants covering part of the costs for attending ICANN. Details on the conference website. ORGANISATION General Chair: Igor Tetko (ENNS/HMGU Munich, Germany) and Fabian Theis (HMGU/TUM Munich, Germany) Organising Committee Chairs: Monica Campillos (HMGU Munich, Germany), Alessandra Lintas (ENNS Lausanne, Switzerland) Honorary Chair: Vera Kurkova, Czech Academy of Sciences (ENNS President) Communication Chair: Paolo Masulli (ENNS Lausanne, Switzerland) -- Paolo Masulli European Neural Network Society https://e-nns.org

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