April 2015 - Comp-neuro - lists.cnsorg.org

NEURAL COMPUTATION - April, 2014
by Terry Sejnowski April 24, 2016

April 24, 2016

Neural Computation - Contents -- Volume 26, Number 4 - April 1, 2014 Available online for download now: http://www.mitpressjournals.org/toc/neco/26/4 ----- Article Parametric Inference in the Large Data Limit Using Maximally Informative Models Justin Block Kinney, Gurinder Singh Atwal Letters Input Statistics and Hebbian Crosstalk Effects Anca R. Radulescu Learning Nonlinear Regularities in Natural Images by Modeling the Outer Product of Image Intensities Peng Qi, Xiaolin Hu Dissociable Forms of Repetition Priming: A Computational Model Kirill Makukhin, Scott Bolland Refined Rademacher Chaos Complexity Bounds With Applications to the Multi-Kernel Learning Problem Yunwen Lei, Lixin Ding Large Margin Low Rank Tensor Analysis Guoqiang Zhong, Mohamed Cheriet Large-scale Linear RankSVM Ching-Pei Lee, Chih-Jen Lin ------------ ON-LINE -- http://www.mitpressjournals.org/neuralcomp SUBSCRIPTIONS - 2014 - VOLUME 26 - 12 ISSUES USA Others Electronic Only Student/Retired $70 $193 $65 Individual $124 $187 $115 Institution $1,035 $1,098 $926 Canada: Add 5% GST MIT Press Journals, 238 Main Street, Suite 500, Cambridge, MA 02142-9902 Tel: (617) 253-2889 FAX: (617) 577-1545 journals-orders(a)mit.edu ------------

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v5.7 of NeuroMorpho.Org released on 30 May, 2014
by NeuroMorpho Administrator March 10, 2016

March 10, 2016

Version 5.7 of NeuroMorpho.Org was released on 30 May, 2014. The release included 29 new data sets (1341 reconstructions), including from three new animal species (dragonfly, moth, and sheep). The database now contains 11,335 reconstructions from 144 contributing labs. More than 3.2 million reconstructions were downloaded in over 130,000 unique visits from 146 countries. Please visit the What's new<http://neuromorpho.org/neuroMorpho/WIN.jsp> page for details on data included in this release, including new species strains, brain regions, cell types, and experimental conditions. The Acknowledgements <http://neuromorpho.org/neuroMorpho/acknowl.jsp> include details on contributing labs, and the About<http://neuromorpho.org/neuroMorpho/about.jsp> page provides an updated overview of the repository content. A new user-friendly functionality, OntoSearch<http://neuromorpho.org/neuroMorpho/OntoSearch.jsp>, was introduced in this release, enabling more powerful searches of species and strains with automated synonym translation, taxonomical relations, and keyword auto-completion. The literature coverage database was also updated to include publications through March 2014. We are continuously grateful to all the data owners who freely share their data with the community. We always appreciate any and all feedback and comments. Sincerely, The NeuroMorpho.Org team -- Ruchi Parekh, Ph.D. NeuroMorpho.Org Project Lead Postdoctoral Research Fellow Center for Neural Informatics, Structures, and Plasticity Krasnow Institute for Advanced Study MS2A1, George Mason University Fairfax, VA 22030 (USA) Ph - +1-703-993-4382<tel:%2B1-703-993-4382> www.neuromorpho.org<http://www.neuromorpho.org/> nmadmin(a)gmu.edu<mailto:nmadmin@gmu.edu>?

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FACULTY POSITION IN QUANTITATIVE LIFE SCIENCES AT ICTP, TRIESTE ITALY
by Matteo Marsili Jan. 14, 2016

Jan. 14, 2016

FACULTY POSITION IN QUANTITATIVE LIFE SCIENCES AT THE ABDUS SALAM INTERNATIONAL CENTRE FOR THEORETICAL PHYSICS (ICTP). ICTP is seeking applicants for a new faculty position in its recently established Quantitative Life Sciences (QLS) research section. QLS responds to the theoretical challenges arising from recent advances in large-scale experiments in biology and neurosciences. The successful applicant will play a leading role in establishing the new section, promoting cutting-edge research in quantitative biology and supervising graduate students. Areas of interest include systems biology, biological networks, systems and computational neuroscience. Applicants should have an outstanding international reputation with at least 4 years of scientific research experience. The position, which will start in October 2015, will be at the P3 UNESCO level, with a starting salary of $78100. Other benefits include family allowance, home travel, education grant for dependent children, pension plan and medical insurance. Full details of the position, along with a link to the UNESCO online application, are available on ICTP's employment webpage and at http://www.ictp.it/about-ictp/personnel-office/employment.aspx <http://www.ictp.it/about-ictp/personnel-office/employment.aspx> The deadline is 3 June 2015. For further information please contact ICTP's Personnel Office at personnel_office(a)ictp.it <mailto:personnel_office@ictp.it>. ICTP, based in Trieste, Italy, provides a top class multi-disciplinary research environment in theoretical sciences, with cutting edge research, education and training, and it has been a driving force behind global efforts for the advancement of science in the developing world.

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PhD positions in computational neuroscience
by Dan Goodman Nov. 2, 2015

Nov. 2, 2015

One or more PhD positions in computational neuroscience are available in the Neural Reckoning Group of Dan Goodman at the Department of Electrical and Electronic Engineering, Imperial College London. I am interested in supervising students with a strong mathematical, computational or neuroscience background. Projects could be carried out in several possible areas, including neuroinformatics (i.e simulation and analysis of neural data) or sensory neuroscience (e.g. spiking neural models in the auditory system). For more information about the group, including some suggestions for research topics, see http://neural-reckoning.org/openings.html. In addition to working within the group, studying at Imperial College provides excellent opportunities for interacting with other theoretical and experimental researchers, both at Imperial (recently ranked 2nd in the world in the QS world university rankings) and in the many neuroscience groups in London. Applicants should initially send me a brief CV and cover letter with a description of research interests or a proposed project, and will eventually have to formally apply through the standard Imperial College mechanism (for more information, see http://www3.imperial.ac.uk/electricalengineering/courses/phd) Funding is available for at least one student, and there are several competitive funding schemes at Imperial which would provide funding for additional students. Also, please forward this message on to any of your students or colleagues with students that you think may be interested. Dan Goodman

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Neuroscience Graduate Group at the University of Pennsylvania
by Joshua Gold Oct. 8, 2015

Oct. 8, 2015

The Neuroscience Graduate Group (NGG) at the University of Pennsylvania is a collaborative and interdisciplinary PhD program that is currently accepting applications for matriculation in the fall of 2015. We are particularly interested in attracting exceptional applicants with backgrounds in Neuroscience, Computer Science, Cognitive Science, Mathematics, Engineering, Physics, and/or Psychology and are interested in the broadly defined field of Computational Neuroscience. We have a robust and growing community of scholars in this field, including: Vijay Balasubramanian, Department of Physics Danielle S Bassett, Department of Bioengineering David H Brainard, Department of Psychology Maja Bucan, Department of Genetics Johannes Burge, Department of Psychology Alice S Chen-Plotkin, Department of Neurology Brian Chow, Department of Bioengineering Yale E Cohen, Department of Otorhinolaryngology Diego Contreras, Department of Neuroscience Christopher M Fang-Yen, Department of Bioengineering Maria Neimark Geffen, Department of Otorhinolaryngology Joshua I Gold, Department of Neuroscience John B Hogenesch, Department of Pharmacology Joseph W Kable, Department of Psychology Michael J Kahana, Department of Psychology Max Kelz, Department of Anesthesiology Brian Litt, Departments of Neurology and Bioengineering Joel D Mainland, Department of Neuroscience Javier F Medina, Department of Psychology Nicole C Rust, Department of Psychology Robert G Smith, Department of Neuroscience Alan A Stocker, Department of Psychology Penn also has strong programs in Statistics, Computer Science, Engineering, and Psychology with faculty actively involved in machine learning, decision making, perception, and computational learning theory. NGG students are encouraged to pursue collaborations and interactions with these groups. The application deadline for the NGG is December 1, 2014. For more details please see our website: http://www.med.upenn.edu/ngg/app_info.shtml ----- Joshua Gold University of Pennsylvania Department of Neuroscience 116 Johnson Pavilion 3610 Hamilton Walk Philadelphia, PA 19104-6074 office phone: 215-746-0028 lab phone: 215-746-0168 e-mail: jigold(a)mail.med.upenn.edu http://www.med.upenn.edu/goldlab

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Gatsby Computational Neuroscience Unit, PhD Programme
by Peter Dayan Sept. 24, 2015

Sept. 24, 2015

Gatsby Computational Neuroscience Unit, University College London 4 year PhD Programme The Gatsby Unit is a centre for theoretical neuroscience and machine learning, focusing on unsupervised, semi-supervised and reinforcement learning, neural dynamics, population coding, Bayesian and nonparametric statistics, kernel methods, and applications of these to the analysis of perceptual processing, neural data, machine vision and bioinformatics. It provides a unique opportunity for a critical mass of theoreticians to interact closely with each other, and with other world-class research groups in related departments at UCL, including the Sainsbury Wellcome Centre for Neural Circuits and Behaviour, with which we will shortly share a building, and Biosciences, Computer Science, Functional Imaging, Physics, Physiology, Psychology, Neurology, Ophthalmology and Statistics, the cross-faculty Centre for Computational Statistics and Machine Learning, and also with other UK and overseas universities. The Unit has openings for exceptional PhD candidates. Applicants should have a strong analytical background, a keen interest in neuroscience and/or machine learning and a relevant first degree, for example in Computer Science, Engineering, Mathematics, Neuroscience, Physics, Psychology or Statistics. The PhD programme lasts four years, including a first year of intensive instruction in techniques and research in theoretical neuroscience and machine learning. All students are fully funded, regardless of nationality. The Unit also welcomes applications from students with pre-secured funding or who are currently soliciting other scholarship/studentships. We will review applications as soon as they are complete (including a CV, statement of research interests and letters from three referees) until the positions are filled. Early application is thus advised. Full details of our programme, and how to apply, are available at: http://www.gatsby.ucl.ac.uk/teaching/phd For further details of research interests please see http://www.gatsby.ucl.ac.uk/research.html and the individual faculty webpages at http://www.gatsby.ucl.ac.uk/members.html

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PhD studentships in computational neuroscience and machine learning
by Steuber, Volker Aug. 28, 2015

Aug. 28, 2015

Applications are invited for PhD studentships in the Biocomputation Research Group at the Science and Technology Research Institute at the University of Hertfordshire. PhD projects involve the development of computer simulations of neurons and neuronal networks to study information processing in the brain, and/or the application of machine learning techniques to analyse electrophysiological data. More details about our research and a list of potential projects can be found on our homepage (http://homepages.herts.ac.uk/~comqvs/research.html) Applicants should have good computational and numerical skills and an excellent first degree in computer science, biology, maths, physics, neuroscience, or a related discipline. Previous experience in neuroscience is not required but would be an advantage. Successful candidates are eligible for a research studentship award from the University (approximately GBP 13,800 per annum bursary plus the payment of the standard UK student fees). Applicants from outside the UK or EU are eligible, but will have to pay half of the overseas fees out of their bursary. Research in Computer Science at the University of Hertfordshire has been recognized as excellent by the latest Research Assessment Exercise, with 55% of the research submitted being rated as world leading or internationally excellent. The Science and Technology Research Institute provides a very stimulating environment, offering a large number of specialized and interdisciplinary seminars as well as general training opportunities. The University of Hertfordshire is situated in Hatfield, in the green belt just north of London. Please contact Dr Volker Steuber (v.steuber @ herts.ac.uk) for informal enquiries. Application forms can be obtained from Mrs Lorraine Nicholls, Research Student Administrator, STRI, University of Hertfordshire, College Lane, Hatfield, Herts, AL10 9AB, Tel: 01707 286083, l.nicholls @ herts.ac.uk. The short-listing process will begin on 9 June 2014.

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Postdoctoral Research Associate in Computational Modelling of Decision Making at the University of Ulster
by Wong-Lin, Kongfatt April 30, 2015

April 30, 2015

Applications are invited for the following post: Postdoctoral Research Associate in Computational Modelling of Decision Making at the University of Ulster There is an important practical need and challenge for autonomous systems to perform multisensory decision-making and report decision uncertainty. This project aims to develop a neural computational model of decision-making capable of performing such tasks. The model will be tested under various complex simulated environments and implemented in reconfigurable and programmable hardware for real-time applications, hence bridging from basic neuroscience research to engineering applications. This project is available in the University of Ulster's Computer Science Research Institute (in collaboration with University of Wolverhampton) and is tenable in the Faculty of Computing and Engineering at the Magee Campus. The successful applicant will utilize knowledge in computational neuroscience, embedded systems and machine learning. The postholder will join an externally funded multidisciplinary research team, and will benefit from the expertise of computational neuroscience, cognitive robotics and neuroengineering at Ulster and Wolverhampton. All applicants should hold or about to obtain a Ph.D. degree in Computing, Engineering, Computational Neuroscience, Computational Sciences, Neuroscience, Mathematics, Physics, Cognitive Science, or a related discipline. Applicants must be highly motivated and willing to pursue research and develop skills and knowledge across disciplines. The application process for the post is opened with a closing date for applications on the 11th May 2015, and interviews will be held shortly after. The successful applicant is expected to be able to begin work in June 2015. Further details can be found at: http://www.jobs.ac.uk/job/ALA611/research-associate-in-computational-modell… We prefer to issue and receive applications via our on-line recruitment website at www.ulster.ac.uk/jobs<http://www.ulster.ac.uk/jobs> If you wish to discuss further regarding this post or the research project, please contact: Dr. KongFatt Wong-Lin, tel: +44 028 7167 5320, e-mail: k.wong-lin(a)ulster.ac.uk ________________________________ This email and any attachments are confidential and intended solely for the use of the addressee and may contain information which is covered by legal, professional or other privilege. If you have received this email in error please notify the system manager at postmaster(a)ulster.ac.uk and delete this email immediately. Any views or opinions expressed are solely those of the author and do not necessarily represent those of Ulster University. The University's computer systems may be monitored and communications carried out on them may be recorded to secure the effective operation of the system and for other lawful purposes. Ulster University does not guarantee that this email or any attachments are free from viruses or 100% secure. Unless expressly stated in the body of a separate attachment, the text of email is not intended to form a binding contract. Correspondence to and from the University may be subject to requests for disclosure by 3rd parties under relevant legislation. The University of Ulster was founded by Royal Charter in 1984 and is registered with company number RC000726 and VAT registered number GB672390524.The primary contact address for Ulster University in Northern Ireland is Cromore Road, Coleraine, Co. Londonderry BT52 1SA

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Large-Scale and HPC data analysis in bioinformatics, system and synthetic biology - 2nd cfp
by Andrea Bracciali April 30, 2015

April 30, 2015

CIBB 2015 — CALL FOR PAPERS – Special Session on Large-Scale and HPC data analysis in bioinformatics: intelligent methods for computational, systems and synthetic biology. CIBB 2015 12th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics CNR Research Area, Naples, Italy 10-12 September 2015 http://bioinfo.na.iac.cnr.it/cibb2015/ cibb2015(a)gmail.com Aims and scope Biomedical research is currently facing the Big Data wave created by the huge amount of experiments performed every day in omics sciences. This new situation demands appropriate IT-infrastructures and scalable software to analyse data within an acceptable timespan. Massive parallel clusters, distributed technologies, on-Chip solutions such as GPGPU and Xeon Phi must be exploited with adequate algorithmic solutions to reach their full potential. The aim of this special session is to bring together researchers interested in cutting-edge methods to address the challenges posed by the huge amount of data produced in omics sciences and in application to systems and synthetic biology. The track aims to present latest advancements concerning High Performance Computing solutions required to treat multi-omics Bid Data and to support the various Large-Scale challenges of current computational biology. Relevant topics within this context include all the field of Next-Generation Sequencing data analysis and interpretation, Genomics patterns identification and mining, Transcriptomics and Proteomics data integration, Systems Biology models simulation and optimization, Structural Biology and Molecular Dynamics, Synthetic Biology circuits design and simulation. Organisers Dr. Andrea Bracciali Dept. of Computing Science and Mathematics, University of Stirling, UK Dr. Ivan Merelli Institute for Biomedical Technologies Italian National Research Council, Italy Dr. Mario Guarracino High Performance Computing and Networking Institute Italian National Research Council, Italy Submissions Conference papers must be prepared following the guidelines illustrated on the CIBB website, which include the requirement of being between 4 and 6 pages in length and having five sections: 1. Scientific background 2. Material and methods 3. Results 4. Conclusion 5. References (no more than 10) These papers should be submitted in PDF format on the Easy Chair conference system (it is necessary to select this special session in the submission system). A second submission after the conference, in an extended version, is required to be considered for publication in the Springer’s Lecture Notes in Bioinformatics (LNBI) series (http://www.springer.com/computer/lncs?SGWID=0-164-6-73658-0) Moreover, as it has been the case in previous CIBB conferences, we are planning to publish the best papers of CIBB 2015 in an extended form in a special issue of an international scientific journal, including special session papers. Important dates Paper submission deadline : May 10, 2015 Abstract submission deadline: May 10, 2015 Notification of Acceptance: July 1, 2015 Final papers due: July 30, 2015 (*) Conference: September 10-12, 2015 (*) for the inclusion in the CIBB15 conference proceeding ICT COST Action High-Performance Modelling and Simulation for Big Data Applications (cHiPSet) The organiser of this special sessions are actively involved in the ICT COST Action High-Performance Modelling and Simulation for Big Data Applications (cHiPSet), due to formally start in June. The possibility of a co-located event is being explored. Italian Flagship initiative Interomics The special sessions will be supported by the Flagship initiative Interomics (PB05). About the organisers Dr. Andrea Bracciali is currently a SICSA lecturer at the Department of Computing Science and Mathematics of the University of Stirling (from August 2010). Before that, he worked as a postdoctoral researcher at CNR, Italy (2009-2010) in the Applied Formal Methods group, and at the Computer Science Department of the University of Pisa (2003-2008), where he received his Ph.D. (2003) in Computer Science. His main research interests are centred in the formal description of interaction in computing with application for Systems Biology and Crowd Dynamics. His main research interests regard the formal description of interaction in computational systems and theories and tools for reasoning about such descriptions. This stream of research spawns form Theoretical Computer Science, Concurrency Theory and, more recently, Systems Biology. Web: http://www.cs.stir.ac.uk/~abb/ Dr. Ivan Merelli is currently research fellow at the Institute for Biomedical Technologies (ITB) of the National Research Council (CNR) in the Bioinformatics Division. He received his Master of Science in Biomedical Engineering from the Politecnico di Milano, with a thesis about molecular surface modelling and analysis. In February 2009 he received a PhD in Computer Science from the university of Milano - Bicocca with a research project about surface matching for macromolecular docking and functional annotation. His research activities concern the development of software for sequence based genomics and for structural proteomics research, with particular interest in protein-protein interactions. He works actively on the implementation of high performance bioinformatics software using cluster infrastructures and grid distributed platforms. He has been involved in the development of databases and computational solutions for projects of Integrative System Biology, gene expression analyses and drug discovery. Web: http://www.itb.cnr.it/web/bioinformatics/staff Dr. Mario Guarracino is researcher at High Performance Computing and Networking Institute of the Italian National Research Council. He received a PhD in Mathematics defending a thesis on projection techniques for parallel sparse linear algebra and an Ms in Applied Mathematics. His postdoctoral training from National Research Council focused on low cost high performance architectures for scientific computing. He has been collaborating with Center for Applied Optimization at University of Florida since 2005. He has taught various undergraduate courses in both computer science and mathematics. His research interests include machine learning methods for computational biology and planning and development of high performance computational components for parallel and distributed problem solving environments. He is author of publications in the field of high performance scientific computing, computational biology and machine learning. Web: http://www.na.icar.cnr.it/~mariog/

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Network Plasticity as Bayesian Inference
by David Kappel April 30, 2015

April 30, 2015

We would like to announce our new paper on stable network function through stochastic plasticity. Summary: Networks of neurons in the brain are exposed to a multitude of internal and external changes and perturbations, to which they have to respond quickly in order to maintain stable functionality. In addition, experimental data suggest that these networks are simultaneously able to maintain structural constraints such as the empirically found connection probability between specific types of neurons, and heavy-tailed distributions of synaptic weights. Other experimental data point to surprising ongoing fluctuations in dendritic spines and spine volumes, to some extent even in the adult brain and in the absence of synaptic activity. In our paper "Network Plasticity as Bayesian Inference" we have shown that stochasticity of synaptic connection may support stable network function. It enables networks to sample parameters from some low-dimensional manifold in a high-dimensional parameter space that represents attractive combinations of structural constraints and a good fit to empirical evidence (e.g., sensory inputs). The resulting new theory of network plasticity explains from a functional perspective the experimentally observed ongoing fluctuations and structural priors that previously appeared to be quite puzzling, and provides a viable alternative to existing models that propose convergence of parameters to point estimates of their optimal values, e.g. to maximum likelihood values. A preprint of the paper is available at: http://arxiv.org/abs/1504.05143v1 The supplement at: http://www.igi.tugraz.at/kappel/pdfs/ms-541-suppl.pdf -- David Kappel Institute for Theoretical Computer Science Graz University of Technology Inffeldgasse 16b, A-8010 Graz, Austria Tel.: ++43/316/873-5847 http://www.igi.tugraz.at/kappel/

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