November 2014 - 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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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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New book "Understanding Vision: theory, models, and data"
by Zhaoping Li Feb. 13, 2015

Feb. 13, 2015

This book "Understanding Vision: theory, models, and data" is published by Oxford University Press in May 2014 and, by now, it is available from various online sites and shops worldwide. For more information, go to http://www0.cs.ucl.ac.uk/staff/zhaoping.li/VisionBook.html The book's Table of Contents can be viewed at http://www0.cs.ucl.ac.uk/staff/zhaoping.li/prints/TableOfContents.pdf Teaching and learning support for the book (e.g., ppt files for the figures in the book) is also available and will be updated at http://www0.cs.ucl.ac.uk/staff/zhaoping.li/VisionBook.html . Readership: Computational neuroscientists, visual psychologists/cognitive scientists, Visual neuroscientists/physiologists/anatomists, Researchers in machine vision or computer vision or robot vision The book is written in such a way that vision scientists, unfamiliar with mathematical details, should be able to conceptually follow the theoretical principles and their relationship with physiological, anatomical, and psychological observations, without going through the more mathematical pages. For those with a physical science background, especially those from machine vision, this book serves as an analytical introduction to biological vision. It can be used as a textbook or a reference book in a vision course, or a computational neuroscience course for graduate students or advanced undergraduate students. It is also suitable for self-learning by motivated readers. In addition, for those with a focused interest in just one of the topics in the book, it is feasible to read just the chapter on this topic without having read or fully comprehended the other chapters. In particular, Chapter 2 presents a brief overview of experimental observations on biological vision; Chapter 3 is on encoding of visual inputs, Chapter 5 is on visual attentional selection driven by sensory inputs, and Chapter 6 is on visual perception or decoding. Please let me know if you need more information. best wishes, Li Zhaoping

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2 Post-doc positions on the relation of information and causation (Prof. Giulio Tononi)
by Larissa Albantakis Dec. 17, 2014

Dec. 17, 2014

Up to 2 postdoctoral positions are available at the center for sleep and consciousness science in the laboratory of Dr. Giulio Tononi (University of Wisconsin, Madison), to study the relation of information and causation within the framework of the integrated information theory of consciousness (Balduzzi & Tononi, 2008; Tononi, 2012). Immediate funding is available for a range of projects related to foundational questions regarding the ontological status of information, and its relation to causation, emergence, adaptation, evolution, and consciousness (see detailed scope of work below). Successful candidates will work at the center for sleep and consciousness science, dedicated to a broad range of research problems focused on two neurobiological problems -- the mechanisms and functions of sleep and the neural substrates of consciousness. Candidates are expected to have strong training in an analytically rigorous discipline such as theoretical biology/neuroscience, physics, mathematics, computer science, or engineering. For at least one of the positions, we explicitely encourage mathematicians to apply. Experience in information theory, complex systems, and an interest in the philosophy of information/causation are a plus. Programming experience is required (knowledge of MATLAB and/or C++ is of advantage). Appointments are renewable from year to year for up to 3 years, starting as soon as possible or until the positions are filled. Post-doc salaries correspond to the National Institutes of Health National Research Service Award (NRSA) stipend schedule for postdoc trainees, based on number of years of postdoctoral experience. Candidates should send a CV, brief statement of previous research and future research interests, and email addresses and phone numbers of three references to: Giulio Tononi, gtononi(a)wisc.edu. Balduzzi D, Tononi G (2008) Integrated information in discrete dynamical systems: motivation and theoretical framework. /PLoS Comput Biol/ 4:e1000091. Hoel, E. P., Albantakis, L., & Tononi, G. (2013). Quantifying causal emergence shows that macro can beat micro. /PNAS/, /110/(49), 19790--19795. Tononi G (2012) Integrated Information Theory of Consciousness: An Updated Account. /Arch Ital Biol/ 150:56--90. The scope of work will range from: -theoretical development and computational implementation of the notion of intrinsic causal information -causal analysis, including the systematic use of perturbations, counterfactuals, and irreducibility -analysis of complex systems in terms their causal/informational structure -meaning (understanding and control) from the intrinsic perspective of the system -actual causation (causal explanation) -examining similarities and differences between existing notions of information and causation (Shannon information, algorithmic information,...) -defining emergence in terms of the spatio-temporal grain size at which a system of elements achieves a maximum of causal power -evolutionary/adaptive aspects of information/causation including simulations based on small adaptive neural networks (animats), which evolve and adapt to an environment that requires sensitivity to context for survival

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Postdoctoral position in cerebellar network modeling in Okinawa
by Erik De Schutter Nov. 30, 2014

Nov. 30, 2014

A postdoctoral researcher position to model cerebellar function is available in the Computational Neuroscience Unit (https://groups.oist.jp/cnu) of Prof. Erik De Schutter at the Okinawa Institute of Science and Technology Graduate University. Depending on previous experience research emphasis can be on analyzing population activity in network models of the olivocerebellum or on further development of XML-based methods for network model description and simulation, or a combination of both. Candidates should have experience in network modeling, preferentially using the parallel NEURON environment. Prior knowledge of cerebellar anatomy and physiology is a plus but not required. The postdoc will interact with other researchers and students in the lab who are working on cerebellar modeling projects. We offer attractive financial and working conditions in an English language graduate university that emphasizes interdisciplinary research, located on a beautiful subtropical island. Send curriculum vitae, Candidates should mail a summary of research interests and experience, and the names of three referees to Prof. Erik De Schutter at erik(a)oist.jp

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Two postdoctoral/research associate positions in computational neuroscience at Drexel University College of Medicine.
by Ilya Rybak Nov. 29, 2014

Nov. 29, 2014

Two postdoctoral/research associate positions in computational neuroscience at Drexel University College of Medicine Two postdoctoral/research associate positions in computational neuroscience for the duration of up to three years are available at Drexel University College of Medicine (Theoretical and Computational Neuroscience Lab of Dr. Ilya A. Rybak) to participate in externally funded projects. One position is for computational modeling of neural control mechanisms, involving interactions between basal ganglia, thalamus, cerebellum, cortex and spinal cord in connection with simulation of pathological changes in motor control during Huntington’s disease. The other position involves modeling of spinal cord circuits, including the circuits of locomotor CPG, in close interactive collaboration with several world leading laboratories performing experimental studies in the isolated rodent spinal cord. Applicants must have a PhD degree in Applied Mathematics, Physics, Computer Science, Neuroscience, or related discipline and have excellent C++ programming skills. Previous experience in computational modeling of biological neurons and neural networks is a plus. Interested candidates are encouraged to contact Dr. Rybak (rybak(a)drexel.edu) by email. To apply, please send an email along with (1) curriculum vitae; (2) a cover letter describing previous research experience and interests; (3) the names and contact information of three references. ================================= Ilya A. Rybak, Ph.D. Professor Department of Neurobiology and Anatomy Drexel University College of Medicine 2900 Queen Lane Philadelphia, PA 19129 USA Tel.: (215) 991-8596 FAX: (215) 843-9082 E-mail: rybak(a)drexel.edu http://neurobio.drexelmed.edu/rybakweb/rybak.html http://www.drexelmed.edu/Home/AboutOurFaculty/IlyaARybak.aspx https://www.researchgate.net/profile/Ilya_Rybak/publications/ http://scholar.google.com/citations?hl=en&user=SnA068QAAAAJ http://www.pubfacts.com/author/Ilya+A+Rybak

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