April 2014 - Comp-neuro - lists.cnsorg.org

DecMeg2014 data analysis competition
by Emanuele Olivetti 22 Apr '14

22 Apr '14

DecMeg2014 data analysis competition Biomag 2014 Decoding Challenge - Brain Decoding Across Subjects https://www.kaggle.com/c/decoding-the-human-brain Decoding mental states from functional neuroimaging data is a data analysis paradigm adopted both in neuroscience studies and in brain-computer interface applications. Decoding means determining, from the recorded brain activity, what stimulus was provided to a subject. In this competition, a large number of trials, from a face vs. scrambled face visual task, are available from multiple subjects. The brain activity was recorded by means of magnetoencephalography (MEG). MEG recordings from various subjects and the category of the associated visual stimuli are given to the participants of the competition in order to train their prediction algorithms. With their algorithms, the participants will have to predict the category of the stimulus of a different set of MEG recordings, from other subjects. Each submission to the competition will be scored according to the accuracy of prediction. Decoding across subjects is a difficult task because of the variability in head shape, cortical folding and functional organisation. For MEG data, the literature on decoding across subjects is still in early stages and this competition aims at raising the awareness about this complex scientific problem. This competition is associated with the the 19th International Conference on Biomagnetism, Biomag 2014, Halifax (Canada), August 24-28, 2014. The competition begins: April 21st, 2014. The competition ends: July 27th, 2014. Prizes: 1st 3,000 USD, 2nd 1,500 USD, 3rd 500 USD. Organizers: Emanuele Olivetti, Seyed Mostafa Kia and Paolo Avesani (NeuroInformatics Lab, Bruno Kessler Foundation and University of Trento, IT), e-mail: decmeg2014(a)list.fbk.eu . Scientific steering committee: Ole Jensen (Donders Institute, NL), Nathan Weisz (University of Trento, IT), Richard Henson (MRC/CBU, UK) and Alexandre Gramfort (Telecom ParisTech, CNRS, CEA / Neurospin). We would also like to thank Daniel Wakeman (Martinos Center, MGH, USA). The awards for this competition are funded by Elekta Oy, MEG International Services Ltd (MISL), Fondazione Bruno Kessler and Besa Gmbh. Relevant links: - competition website: https://www.kaggle.com/c/decoding-the-human-brain - Biomag 2014: http://www.biomag2014.org - NeuroInformatics Lab: http://nilab.fbk.eu - Elekta Oy: http://www.elekta.com - MISL (CTF MEG): http://www.ctfmeg.com - Fondazione Bruno Kessler: http://www.fbk.eu - Besa GmbH: http://www.besa.de Please feel free to forward this message to your colleagues or contacts who might be interested in this competition.

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NEURON Summer Course deadline approaching
by Ted Carnevale 22 Apr '14

22 Apr '14

The early registration deadline for the NEURON Summer Course is Friday, May 9, less than three weeks from today. Applicants who sign up by that date are eligible for reduced registration fees. NEURON Fundamentals June 21-24 This course shows how to model individual neurons and networks of neurons, and introduces parallel simulation. The early registration fee is $1050, but after May 9 registration goes up to $1200. Parallel Simulation with NEURON June 25-26 This is for users who are already familiar with NEURON and now need to parallelize an existing model or create a new model that will run on parallel hardware. The early registration fee is $650, but after May 9 it goes up to $750. Sign up for both courses by May 9 and pay only $1600, or wait until May 10 or later and pay $1800. Registration is limited, and the final registration deadline is Friday, May 30, 2014. For more information about these courses see http://www.neuron.yale.edu/neuron/courses or contact Ted Carnevale ted dot carnevale at yale edu 203-494-7381

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CoSMo 2014: application deadline approaching!
by Gunnar Blohm 22 Apr '14

22 Apr '14

Just a quick reminder that the application deadline for the summer school on Computational Sensory-Motor Neuroscience (CoSMo 2014) is approaching fast: Apr 28, 2014!!! http://www.compneurosci.com/CoSMo/ Best Gunnar Blohm, Konrad Körding, Paul Schrater -- ------------------------------------------------------- Dr. Gunnar BLOHM Assistant Professor in Computational Neuroscience Centre for Neuroscience Studies, Departments of Biomedical and Molecular Sciences, Mathematics & Statistics, and Psychology, School of Computing, and Canadian Action and Perception Network (CAPnet) Queen’s University 18, Stuart Street Kingston, Ontario, Canada, K7L 3N6 Tel: (613) 533-3385 Fax: (613) 533-6840 Email: Gunnar.Blohm(a)QueensU.ca Web: http://www.compneurosci.com/

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Advanced Statistics and Data Mining Summer School (Madrid) - Early registration deadline
by asdm＠fi.upm.es 22 Apr '14

22 Apr '14

Dear colleagues, We would like to remind you that the early registration period for the Advanced Statistics and Data Mining Summer School will finish on June 2nd. The summer school will be held in Madrid, from June 23rd to July 4th. This year's programme comprises 12 courses and runs for 2 weeks. Attendees may register in each course independently. Extended information on course programmes, price, venue, accommodation and transport is available at the school's website: http://www.dia.fi.upm.es/ASDM Please, send this information to your colleagues, students, and whoever you think may find it interesting. Best regards, Pedro Larranaga, Concha Bielza, Bojan Mihaljevic and Laura Anton-Sanchez. -- School coordinators. *** List of courses and brief description *** * Week 1 (June 23rd - June 27th, 2014) * 1st session: 9:30 - 12:30 Course 1: Bayesian Networks (15 h) Basics of Bayesian networks. Inference in Bayesian networks. Learning Bayesian networks from data. Real applications. Course 2: Time Series(15 h) Basic concepts in time series. Descriptive methods for time series. Linear models for time series. Extensions. 2nd session: 13:30 - 16:30 Course 3: Supervised Pattern Recognition (15 h) Introduction. Assessing the performance of supervised classification algorithms. Preprocessing. Classification techniques. Combining multiple classifiers. Comparing supervised classification algorithms. Course 4: Bayesian Inference (15 h) Introduction: Bayesian basics. Conjugate models. MCMC and other simulation methods. Regression and Hierarchical models. Model selection. 3rd session: 17:00 - 20:00 Course 5: Neural Networks and Deep Learning (15 h) Introduction. Training algorithms. Learning and Optimization. MLPs in practice. Deep Networks. Course 6: Feature Subset Selection (15 h) Introduction. Filter approaches. Wrapper methods. Embedded methods. Advanced topics. Practical session. * Week 2 (June 30th - July 4th, 2014) * 1st session: 9:30 - 12:30 Course 7: Statistical Inference(15 h) Introduction. Some basic statistical test. Multiple testing. Introduction to bootstrap methods. Introduction to Robust Statistics. Course 8: Bayesian Classifiers (15 h) Discrete predictors. Gaussian Bayesian networks-based classifiers. Other Bayesian classifiers. Bayesian classifiers for: positive and unlabeled data, semi-supervised learning, data streams, temporal data. 2nd session: 13:30 - 16:30 Course 9: Text Mining (15 h) Introduction. Fundamentals. Language Modeling. Text Classification. Information Extraction. Course 10: Unsupervised Pattern Recognition (15 h) Introduction to clustering. Data exploration and preparation. Prototype-based clustering. Density-based clustering. Graph-based clustering. Cluster evaluation. Miscellanea. Conclusions and final advise. 3rd session: 17:00 - 20:00 Course 11: Support Vector Machines and Convex Optimization (15 h) Introduction. SVM models. SVM learning algorithms. Convex non differentiable optimization. Course 12: Hidden Markov Models (15 h) Introduction. Discrete Hidden Markov Models. Basic algorithms for Hidden Markov Models. Semicontinuous Hidden Markov Models. Continuous Hidden Markov Models. Unit selection and clustering. Speaker and Environment Adaptation for HMMs. Other applications of HMMs.

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2nd call for papers - 2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP)
by 2014 IEEE International Workshop on Machine Learning fo Signal Processing 22 Apr '14

22 Apr '14

2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP) September 21-24, 2014 Reims, France http://mlsp2014.conwiz.dk CALL FOR PAPERS The 24th MLSP workshop in the series of workshops organized by the IEEE Signal Processing Society MLSP Technical Committee will present the most recent and exciting advances in machine learning for signal processing through keynote talks, tutorials as well as special and regular single-track sessions. Prospective authors are invited to submit papers on relevant algorithms and applications including, but not limited to: - Learning theory and techniques - Graphical models and kernel methods - Data-driven adaptive systems and models - Pattern recognition and classification - Distributed, Bayesian, subspace/manifold and sparsity-aware learning - Multiset data analysis and multimodal data fusion - Perceptual signal processing in audio, image and video - Cognitive information processing - Multichannel adaptive and nonlinear signal processing - Applications, including: speech and audio, image and video, music, biomedical signals and images; communications; bioinformatics; biometrics, computational intelligence, genomic signals and sequences; social networks; games, and smart grid. DATA ANALYSIS AND SIGNAL PROCESSING COMPETITION Data Analysis and Signal Processing Competition is being organized in conjunction with the workshop. The goal of the competition is to advance the current state-of-the-art in theoretical and practical aspects of signal processing domains. The problems are selected to reflect current trends, evaluate existing approaches on common benchmarks, and identify critical new areas of research. Winners will be announced and awards given at the workshop. BEST STUDENT AWARD The MLSP Best Student Paper Award will be granted to the best overall paper for which a student is the principal author and presenter. This author must be a registered student at the time of paper submission to be eligible for this award. The award will be presented during the conference and consists of a honorarium (to be divided equally between all student authors of the paper), and a certificate for each such author. The award will be selected by a subcommittee of the program committee. The selection is based on the quality, originality, and clarity of the submission. PAPER SUBMISSION Prospective authors are invited to submit a double column paper of up to six pages using the electronic submission procedure at http://mlsp2014.conwiz.dk/paper_submission.htm Accepted papers will be published on memory sticks to be distributed at the workshop. The presented papers will be published in and indexed by IEEE Xplore. SCHEDULE: - Submission of full paper: May 5, 2014 - Notification of acceptance: June 27, 2014 - Advance registration before: July 25, 2014 - Camera-ready paper: July 25, 2014 ORGANIZING COMMITTEE: General Chair Mamadou Mboup Contact general chair at mlsp2014-chair(a)conwiz.dk Program Chairs Tülay Adali Eric Moreau Contact program chairs at mlsp2014-programchairs(a)conwiz.dk Data Competition Chair Vince Calhoun Special Session Chair Jean-Yves Tourneret Publicity Chair Marc Van Hulle Web and Publication Chair Jan Larsen Kevin Guelton Local Arrangement Chairs Valeriu Vrabie Hassan Fenniri

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Endeavour Scholarships and Fellowships
by Naotsugu Tsuchiya 22 Apr '14

22 Apr '14

Dear all, The Australian government is offering Endeavour Scholarships and Fellowships https://aei.gov.au/scholarships-and-fellowships/international-applicants/pa… to those competitive international students and postdocs to visit and conduct short-term research in Australia. Please see the web site if you are interested. In my lab, we are looking for students/postdocs who are proficient in Matlab (and preferably signal processing and/or information theory as well) and interested in 1) application of the integrated information theory of consciosness to the real neuronal data, 2) analysis of intracranial recording data (using decoding, cross-frequency coupling etc) to understand the neuronal basis of consciousness. Please send me <naotsugu.tsuchiya(a)monash.edu> your CV if you are interested. Endeavour Awards will be closing 30 June 2013. Regards Nao Tsuchiya -- ------------------------------------------------------------------------- Nao (Naotsugu) Tsuchiya, Ph.D. 1. Associate Professor School of Psychological Sciences Faculty of Medicine, Nursing and Health Sciences, Monash University 2. ARC Future Fellow homepage: http://users.monash.edu.au/~naotsugt/Tsuchiya_Labs_Homepage/Main.html

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NIPS 2014 Call for Papers
by Chris Hiestand 22 Apr '14

22 Apr '14

Neural Information Processing Systems Conference and Workshops December 8-13, 2014 Montreal Convention Center, Montreal, Canada Deadline for Paper Submissions: Friday, June 6, 2014, 11 pm Universal Time (4 pm Pacific Daylight Time). Submit at: https://cmt.research.microsoft.com/NIPS2014/ Submissions are solicited for the Twenty-Eigth Annual Conference on Neural Information Processing Systems, an interdisciplinary conference that brings together researchers in all aspects of neural and statistical information processing and computation, and their applications. The conference is a highly selective, single track meeting that includes oral and poster presentations of refereed papers as well as invited talks. The 2014 conference will be held on December 8-11 at Montreal Convention Center, Montreal, Canada. One day of tutorials (December 8) will precede the main conference, and two days of workshops (December 12-13) will follow it at the same location. Complete details: http://nips.cc/Conferences/2014/CallForPapers

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Postdoctoral Position in Computational and Experimental Social Neuroscience
by Emmanuelle Tognoli 20 Apr '14

20 Apr '14

The Human Brain and Behavior Laboratory (HBBL), Center for Complex Systems and Brain Sciences at Florida Atlantic University (FAU) invites applications for a Postdoctoral Position in Experimental and Computational Social Neuroscience. The research program aims to advance our understanding of basic forms of real-time social behavior. This new NIMH-supported program employs a three-pronged approach that combines (1) experimental studies aimed at elucidating how neuromarkers are organized dynamically during the course of social interaction (2) the design and analysis of the Human Dynamic Clamp (reciprocal coupling between humans and mathematical models of a social partner) and (3) multiscale neurocomputational modeling of both structure and function. The postdoctoral scientist will be highly motivated and able to work independently. He/she will also collaborate within an interdisciplinary team of researchers whose expertise spans Neuroscience, Psychology and Physics. The successful applicant will contribute to the design and conduct of neurobehavioral experiments and to theoretical modeling in which social interactions are treated as meaningfully coupled dynamical systems (Coordination Dynamics). Candidates should have a PhD degree or equivalent. Experience or willingness to learn in one or more relevant domains will be considered an advantage: - Theoretical modeling, dynamical systems - Preparation and conduct of social, neurobehavioral and neurocognitive experiments - Recording and analysis of brain activity and behavior (e.g. EEG, MEG, fMRI, etc) - Digital signal processing and statistical analysis - Programming (Matlab, C, visual basic), - Excellent writing skills The position will be for one year with a possibility of extension depending on satisfactory progress. Salary will be commensurable with experience. Review of applications will begin immediately and continue until the position is filled. Qualified candidates should send a CV and arrange for 3 reference letters via email to: J. A. Scott Kelso & Emmanuelle Tognoli, kelso at ccs.fau.edu, tognoli at ccs.fau.edu www.ccs.fau.edu/hbbl.html HBBL, Center for Complex Systems & Brain Sciences, Florida Atlantic University, Boca Raton, FL USA -- This message has been scanned for viruses and dangerous content by MailScanner, and is believed to be clean.

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OpenWorm for scientists
by Stephen Larson 19 Apr '14

19 Apr '14

Hi all, OpenWorm <http://openworm.org/> is an open source project and open science community dedicated to creating the world’s first whole organism in a computer, a C. elegans nematode<https://en.wikipedia.org/wiki/Caenorhabditis_elegans>, via bottom-up computational modeling. It is an association of highly motivated scientists, engineers, coders, and curious citizens from around the world who believe in open science and open access. While our ultimate goal is to simulate every cell in the c. elegans, we are starting out by building a model of its body and environment, its nervous system, and its muscle cells. At the center of this is an incrementally improving detailed multi-compartmental representation of the c. elegans nervous system<http://docs.openworm.org/en/latest/Projects/datarep.html#neuroml-connectome>. You can read more about our neuromechanical modeling approach in our online documentation<http://docs.openworm.org/en/latest/modeling.html#closing-the-loop-with-neur…> . We've recently pulled together a page<http://www.openworm.org/science.html> that focuses content that is relevant to experimental biologists and other scientists in a single place online. http://www.openworm.org/science.html This outreach effort is aimed at creating a conversation between biologists collecting data and making observations and computational modelers building models and validating them against real data. We invite the comp-neuro community to have a look, provide feedback, and join the conversation! Thanks, Stephen Larson, Ph.D Project coordinator http://openworm.org

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Postdoc/engineer positions in Parkinsons/DBS and Neuroprosthetics
by Dawn Taylor 18 Apr '14

18 Apr '14

We currently have multiple openings for Postdocs and/or engineers for two newly funded studies. Detailed descriptions of each study are listed below. If interested, please send a CV to Dr. Dawn Taylor at dxt42(a)case.edu. 1) The goal of the *Parkinson's* project is to understand how Parkinson's disease alters cortical network processing and how *Deep Brain Stimulation (DBS)* can be improved to better re-normalize motor processing. Cortical network activity will be recorded in monkeys via intracortical electrode arrays before and after making the animals hemi-Parkinsonian via injections of the selective neurotoxin MPTP (note this toxin is initially applied in such a way that the animal only develops parkinsonian symptoms on one half of its body so the animal can still groom, ambulate, and take care of itself). DBS will then be applied to two subcortical regions (subthalamic nucleus and globus pallidus) to alleviate Parkinsonian symptoms. Computational models of the cortical microcircuit will be developed that accurately reflect the recorded cortical activity in the normal and Parkinsonian states as well as under the influence of different DBS patterns. The model parameters that need to be changed to make the network computational model behave like the recorded experimental data under the different conditions will be informative regarding the underlying mechanisms of DBS. The refined computational model will also be used to rapidly screen for new DBS patterns that are more effective at restoring normal cortical network processing. The improved DBS patterns suggested by the computational model will then be validated by testing those novel patterns in the monkeys. This project is being done in conjunction with Dr. Cameron McIntyre who will oversee the computational modelling part of the study. We are looking for multiple post docs that can focus on either the animal work, the computational modeling, or both depending on their skills and interests. 2) The long-term goal of the *Neuroprosthetics* project is to enable paralyzed individuals to use their brain signals to control their upper limb via implanted muscle stimulators. Most labs working on brain-controlled neuroprosthetics decode intended limb kinematics (e.g. velocity, joint angles, etc.) from the recorded brain signals. However, that approach still requires converting those kinematic commands into the appropriate stimulation patterns required to generate the desired limb motion. That conversion process has not been resolved for the upper limb due to the limb's complex dynamical nature and the fact that the limb is subject to unknown external forces during use. We bypass this obstacle by retraining the brain to control muscle stimulators directly. We have come up with some novel, but clinically feasible ways of mapping neural signals directly to muscle stimulators. Our methods can enable the user to have good control over both limb motion and stiffness. To demonstrate and refine our methods, we are training monkeys to control the movements of a realistic musculoskeletal model of a paralyzed limb activated via implanted muscle stimulators. The paralyzed limb simulator (developed by the lab of Robert Krisch) provides real-time visual feedback to the animal of the limb motion that would result from stimulating the paralyzed muscles based on the animal's neural signals decoded in real time. The use of this real-time paralyzed arm simulator allows us to test and refine our process of brain-controlled muscle stimulation in monkeys without actually having to paralyze any animals. -- Dawn M. Taylor, Ph.D. Assistant Professor of Neuroscience, Cleveland Clinic Researcher Scientist, Cleveland VA Medical Center, Functional Electrical Stimulation Center Assistant Professor of Biomedical Engineering & of Molecular Medicine, Case Western Reserve University The Cleveland Clinic Lerner Research Institute 9500 Euclid Ave. / NC30 Cleveland, OH 44195 email: dxt42(a)case.edu or taylord8(a)ccf.org Phone: (216) 636-0140 Fax: (216) 778-4259

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