December 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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Call for Papers: IEEE IJCNN'2015 Special Session on: "Emerging Methodologies for Big Data Integration"
by Dr Amir Hussain Dec. 28, 2014

Dec. 28, 2014

CALL FOR PAPERS IEEE IJCNN 2015 Special Session on *"*Emerging Methodologies for Big Data Integration*"* July 12 - 17, 2015, Killarney, Ireland ( http://www.ijcnn.org/ ) ********************************************************** IMPORTANT DATES Paper submission: January 15th, 2015 Paper Decision notification: March 15th, 2015 Camera-ready submission: April 15th, 2015 Conference Dates: July 12 - 17th, 2015 *********************************************************** Over the years, huge quantities of data have been generated by large-scale scientific experiments (biomedical, “omic”, imaging, astronomical, etc.), big industrial companies and on the web. One of the main characteristics of such Big Data is that they are multi-view, i.e. there are multiple sources (in the “omics” sciences, experiments related to mRNA, miRNA etc.), relate the same patterns (in this case patients) or multi-domain (in biomedical applications for examples, “omics, imaging and clinical data). As a consequence, new methodologies based on neural networks, machine and statistical learning, computation Intelligence and others, have been proposed to integrate these kinds of big data and to elicit relevant information to infer novel models and correlations. The aim of the special session is to solicit new approaches to real world scientific and industrial big data integration, as well as applications of above mentioned Big Data methodologies. *Topics** Papers must present original work or review the state-of-the-art in the following non-exhaustive list of topics: Multi-view learning Multi-view clustering data fusion data integration multi-view data applications multi domain data applications THE DEADLINE FOR THE PAPER SUBMISSION TO THE SPECIAL SESSION IS THE SAME OF IJCNN 2015, January 15th 2015. All the submissions will be peer-reviewed with the same criteria used for other contributed papers. Perspective authors will submit their papers through the IJCNN2015 conference submission system at http://www.ijcnn.org/ Please make sure to select the Special Session "Emerging Methodologies for Big Data Integration " from the "S. SPECIAL SESSION TOPICS" name in the "Main Research topic" dropdown list; Templates and instructions for authors will be provided on the IJCNN webpage http://www.ijcnn.org/ All papers submitted to the special sessions will be subject to the same peer-review procedure as regular papers, accepted papers will be published in the conference proceedings. Further information about IJCNN 2015 can be fond at http://www.ijcnn.org/ and about the special session at http://neuronelab.unisa.it/emerging-methodologies-for-big-data-integration/ *********************************************************** **Organizers** - Amir Hussain Professor of Computing Science and founding Director of the Cognitive Signal-Image Processing and Control Systems Research (COSIPRA) Laboratory, University of Stirling, UK (E-mail: ahu(a)cs.stir.ac.uk http://cs.stir.ac.uk/~ahu) - Giovanni Montana Professor and Chair in Biostatistics and Bioinformatics, Biomedical Engineering Department, King’s College, London, UK - Francesco Carlo Morabito Professor and Chair of the Neurolab, Dipartimento DICEAM, Università Mediterranea di Reggio Calabria, Italy - Roberto TAGLIAFERRI Professor and Chair of the Neuronelab, Dipartimento di Informatica, Università di Salerno, Italy **Technical Program Committee (being continuously updated)** Elia Mario Biganzoli, Università di Milano, Italy Erik Cambria, NTU, Singapore Ciro Donalek, Caltech, CA, USA Anna Esposito, Seconda Università di Napoli, Italy Marcos Faundez-Zanuy, Escola Universitaria Politecnica de Mataro (Tecnocampus), Spain Alexander Gelbukh, National Polytechnic Institute, Mexico Dario Greco, FIOH, Finland Newton Howard, MIT Media Lab, USA Pietro Liò, University of Cambridge, UK Bin Luo, Anhui University, China Mufti Mahmud, Antwerp University, Belgium Riccardo Rizzo, CNR, Italy Jingpeng Li, University of Stirling, UK Domenico Ursino, Università Mediterranea di Reggio Calabria, Italy Alfredo Vellido, Universidad Politécnica de Cataluña, Spain Pierangelo Veltri, Università "Magna Graecia" di Catanzaro, Italy Jonathan Wu, University of Windsor, Canada Yunqing Xia, Tsinghua University, China Kang Li, Queen's University, Belfast, UK Dongbing Gu, Essex University, UK Vincent C. Müller, Anatolia College/ACT, Greece & Oxford University, UK Dongbin Zhao, Chinese Academy of Sciences, Beijing, China *********************************************************** -- The University of Stirling has been ranked in the top 12 of UK universities for graduate employment*. 94% of our 2012 graduates were in work and/or further study within six months of graduation. *The Telegraph The University of Stirling is a charity registered in Scotland, number SC 011159.

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Teaching Computational Neuroscience
by Érdi Péter Dec. 28, 2014

Dec. 28, 2014

A multiple book review: http://arxiv.org/abs/1412.5909 Péter Érdi http://people.kzoo.edu/~perdi/

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UC Santa Barbara Postdoc fellowship announcement
by John Hajda Dec. 23, 2014

Dec. 23, 2014

SAGE JUNIOR FELLOW PROGRAM, SAGE CENTER FOR THE STUDY OF MIND, UNIVERSITY OF CALIFORNIA, SANTA BARBARA Job number JPF00417 Four postdoctoral positions will be available beginning on September 1, 2015. This is a three-year fellowship, and the competition is open to all qualified candidates regardless of institutional affiliation. The SAGE Center Junior Fellowship Program, established in 2011, fosters interdisciplinary research in the study of brain-mind interaction at the postdoctoral level. We are seeking a group of highly collaborative, interacting fellows who are willing to take different approaches to shared conceptual challenges. Qualified applicants should be able and will be encouraged to utilize the UCSB Brain Imaging Center (http://www.bic.ucsb.edu/) The Center supports the new PRISMA (3T) Siemens magnet as well as MRI compatible high density electroencephalography hardware. Center funding will be available for imaging studies. In addition to developing research programs in close collaboration with individual faculty, Junior Fellows will enjoy special privileges, including access to visiting SAGE Scholars and attendance at regular group meetings to collaborate and share information about the role of psychology, cognitive neuroscience, economics, political science, anthropology, biology, physics, engineering, the arts, philosophy and other disciplines on the study of brain, mind and behavior. To be eligible for the Junior Fellows program, a candidate must have been awarded a doctoral degree or foreign equivalent within the past five years. Proposed research topics must be related to brain-mind interaction. Interdisciplinary approaches are encouraged. We will strive to create a team based on common interests of the top applicants. To apply, please submit: 1. A complete CV, published article and three letters of recommendation 2. A statement of your research interests and a description of how those interests complement the goals of the SAGE Center. For primary consideration, apply by February 1, 2015, although we will accept applications until the positions are filled. Please submit your application at https://recruit.ap.ucsb.edu/apply/JPF00417. Inquiries about your application may be directed to juniorfellows(a)sagecenter.ucsb.edu; include your last name in the subject line of all correspondence. Michael S. Gazzaniga, Ph.D. Director, SAGE Center for the Study of Mind University of California, Santa Barbara http://www.sagecenter.ucsb.edu/ http://www.psych.ucsb.edu/~gazzanig/ The department is especially interested in candidates who can contribute to the diversity and excellence of the academic community through research, teaching and service. The University of California is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, or any other characteristic protected by law including protected Veterans and individuals with disabilities. -- John Hajda, Ph.D. Associate Director Sage Center for the Study of the Mind Department of Psychological and Brain Sciences University of California, Santa Barbara Santa Barbara, CA 93106-9660 Phone 805-893-4460 Fax 805-893-3228 hajda(a)sagecenter.ucsb.edu http://www.sagecenter.ucsb.edu/

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