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

PhD position in Visual Psychophysics at the Institute of Vision in Paris, France
by Angelo ARLEO Aug. 29, 2014

Aug. 29, 2014

One fully-funded PhD position in Visual Psychophysics at the Institute of Vision in Paris, France Job description Applications are invited for one PhD position in the Aging in Vision and Action laboratory at the Institute of Vision (INSERM-CNRS-University Pierre & Marie Curie) Paris, France. The gradual impairment of vision-dependent functions in the elderly is at the core of the research carried out in the Aging in Vision and Action laboratory. The main goal is to characterize how healthy aging shapes perceptual and cognitive aspects of vision. This PhD project will focus on the impact of healthy aging on low-level visual perception and visual processing functions. Requirements Applicants’ background should be in cognitive neuroscience/psychology. Previous experience with visual psychophysics, eye-movement analysis, visual space perception, or aging is welcome. Computer programming skills are also a plus. Proficiency in oral and written English is required. Knowledge of French is not mandatory. Successful candidates are expected to work in an interdisciplinary environment with collaborations with biologists, theoreticians and clinicians. They will be awarded a 3-year PhD fellowship from the University Pierre and Marie Curie Paris. Working environment and laboratory The Institute of Vision is one of the top international centers for integrated research on vision and eye diseases. It is located at the heart of Paris, on the campus of the National Hospital Center for Ophthalmology. The Institute of Vision includes multidisciplinary research groups, which share state-of-the-art platforms for human and animal experimentation. It also harbors a clinical investigation center, which fosters truly translational research activity. More information can be found online (http://www.institut-vision.org) The Institute of Vision and Essilor International, world leader in ophthalmic optics, have recently supported the creation of the laboratory of Aging in Vision and Action. This new laboratory aims at evaluating and understanding the functional aspects of the degeneration mechanisms related to visual aging. This research has the potential to produce fundamental knowledge suited for opening to assistive technological developments and rehabilitation solutions. The faculty members of the Aging in Vision and Action laboratory, led by Angelo Arleo, are specialized in visual psychophysics, neurobiology of spatial orientation, neural coding, neurocomputational modeling, and preclinical evaluation. The group has access to a wide range of state-of-the-art platforms including eye trackers, motion capture rooms, virtual reality environments, brain imaging, artificial street labs and home labs (http://www.streetlab-vision.com/en/) How to apply Candidates should send a single pdf file containing a motivation letter, a full CV, and names and contact information of at least two referees, to angelo.arleo(a)inserm.fr. Short listed candidates will be contacted for an interview (either face-to-face or via videoconference). For further inquiries, please contact Angelo Arleo, angelo.arleo(a)inserm.fr, phone: +33 (0)1 53 46 26 52. Angelo ARLEO Institute of Vision, Aging in Vision and Action Lab, CNRS - INSERM - University Pierre&Marie Curie, 17, rue Moreau F-75012 Paris, France Phone: +33 (0)1 53 46 26 52 Mobile: +33 (0)6 89 89 07 23 email: angelo.arleo(a)inserm.fr; angelo.arleo(a)upmc.fr

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PhD Studentship in Computer Science: Understanding and modelling emergent functionality in small biological neural systems
by Peter Andras Aug. 29, 2014

Aug. 29, 2014

PhD Studentship in Computer Science Understanding and modelling emergent functionality in small biological neural systems Reference Number: EPSAM2014-1 Application Deadline: 15th September 2014 Supervisor: Professor Peter Andras, School of Computing and Mathematics, Keele University Project description: The functionality of biological neural systems emerges through the interaction of neurons. Recent technological advances allow the recording and analysis of many neurons individually, making possible the understanding and modelling the emergence of system level functionality in biological neural circuits. This project will use as model system the stomatogastric ganglion (STG) of brown crabs. The focus will be on the understanding how the roles of neurons may change in response to neuromodulation in the context of changing functional behaviour of the pyloric rhythm neural circuit within the STG. We will use fast voltage-sensitive dye imaging to collect the data about the activity of neurons and computational modelling of these neurons and the impact of neuromodulators on them in order to model and explain the observed activity of the STG. We aim to analyse the roles of apparently functionally equivalent neurons (e.g. two PD neurons, five PY neurons) and model computationally the changes in their functional roles in response to neuromodulation. The successful candidate will be expected to learn the relevant biological experimental techniques, perform biological experiments, learn the relevant computational modelling techniques, and build and analyse computational models of neurons and neural circuits. The stipend is £13,863 (2014/15) per year. The studentship is not available for candidates from outside of the EU. Person specification: You should have either a First class honours degree in Computing Science, Mathematics, Physics, Biology or other relevant science or engineering subject, or a or 2.1 in Computing Science, Mathematics, Physics, Biology or other relevant science or engineering subject and a distinction level Masters degree in a related subject. Equivalent experience will also be considered. Application procedure: You must apply through the Universitys online postgraduate application website (http://www.keele.ac.uk/pgresearch/howtoapply/) specifying the reference number EPSAM2014-1 and selecting PhD in Computer Science, as the programme of study. Only mandatory fields need to be completed and a personal statement, CV and (if English is not your first language) a copy of your English language qualifications must be attached. The personal statement must state the title of the studentship, quote the reference number EPSAM2014-1 and describe how your research interests fit with the topic of the research projected outlined in the advertisement (max. 2 pages). If you already have published research papers a list of these providing bibliographic details should be included in the covering letter. You should also send your personal statement and CV by e-mail to Professor Peter Andras, ( <mailto:p.andras@keele.ac.uk> p.andras(a)keele.ac.uk) Further information: For further details, please contact Professor Peter Andras ( <mailto:%20p.andras@keele.ac.uk> p.andras(a)keele.ac.uk) 01782 733412 For general enquiries contact: http://www.keele.ac.uk/pgresearch/howtoapply --- Professor Peter Andras Professor of Computer Science and Informatics Head of Computing Division School of Computing and Mathematics Keele University Keele, Staffordshire ST5 5BG UK Tel. +44-1782-733412 Fax. +44-1782-734268 E-mail: p.andras(a)keele.ac.uk Web: www.scm.keele.ac.uk/staff/p_andras/

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New book: Growing Adaptive Machines
by Nicolas Bredeche Aug. 29, 2014

Aug. 29, 2014

<We are sorry if you have received multiple copies of this email> Dear all, Some of you will be interested in our recent book, Growing Adaptive Machines: Combining Development and Learning in Artificial Neural Networks. The topic is the generation of low-level neural network architectures using bio-inspired models and simulations. By emulating the biological process of development, we can incorporate desirable characteristics of natural neural systems into engineered designs and thus move closer towards the creation of brain-like systems. The book includes two broad reviews, summaries of research portfolios from established researchers, and new research contributions. We believe it will form a valuable reference for advanced students and practitioners. See below for the table of contents. http://www.springer.com/engineering/computational+intelligence+and+complexi… http://www.amazon.com/Growing-Adaptive-Machines-Computational-Intelligence/… Best regards, Taras Kowaliw, Nicolas Bredeche, René Doursat (Editors) =-=-=-=-= Table of Contents Artificial Neurogenesis: An Introduction and Selective Review. T. Kowaliw, N. Bredeche, S. Chevallier and R. Doursat A Brief Introduction to Probabilistic Machine Learning and Its Relation to Neuroscience. T. Trappenberg Evolving Culture Versus Local Minima. Y. Bengio Learning Sparse Features with an Auto-Associator. S. Rebecchi, H. Paugam-Moisy and M. Sebag HyperNEAT: The First Five Years. D. D’Ambrosio, J. Gauci and K. Stanley Using the Genetic Regulatory Evolving Artificial Networks (GReaNs) Platform for Signal Processing, Animat Control, and Artificial Multicellular Development. B. Wróbel and M. Joachimczak Constructing Complex Systems Via Activity-Driven Unsupervised Hebbian Self-Organization J. Bednar Neuro-Centric and Holocentric Approaches to the Evolution of Developmental Neural Networks. J. Miller Artificial Evolution of Plastic Neural Networks: A Few Key Concepts. J.-B. Mouret and P. Tonelli

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Director of Robotics Institute at HKUST
by Bert Shi Aug. 28, 2014

Aug. 28, 2014

Professor Position cum Director of Robotics Institute Applications and nominations are invited for the joint faculty position as Professor cum Director of Robotics Institute in the Hong Kong University of Science and Technology. The successful candidate will hold a joint appointment as a full Professor in two or more of the following departments: Electronic and Computer Engineering, Mechanical and Aerospace Engineering, Computer Science and Engineering, Industrial Engineering and Logistics Management, and Mathematics. HKUST Robotics Institute is a newly established research institute. Its mission is to (i) conduct fundamental and cutting-edge research in the area of robotics, unmanned aerial vehicles (UAVs), manufacturing automation, autonomous systems, and medical robotics; (ii) provide a world class educational platform for robotics teaching and learning; (iii) transfer knowledge related to robotic technology to the community, industry and government; and (iv) create an entrepreneurial environment for students and faculty. Major stakeholders of the Institute include faculty, staff and students of various departments. Applicants/nominees for the position should have a PhD degree, demonstrated leadership abilities, extensive teaching and research experience as well as an ability to interact effectively with students, faculty, industry and the Government. Salary will be highly competitive with generous fringe benefits. Appointment of professorship will be made on substantive terms of service. Fringe benefits including housing, annual leave, medical and dental benefits will be provided where applicable. HKUST is committed to increasing the diversity of its faculty and has a range of family-friendly policies in place. More information about the School of Engineering is available at: www.seng.ust.hk<http://www.seng.ust.hk/> Applications/Nominations, together with a full curriculum vitae, list of publications, names and contacts of five referees, should be addressed to Professor Amine Bermak, Chair of the Search Committee by email to: drisearch(a)ust.hk<mailto:drisearch@ust.hk> on or before 15 November 2014<x-apple-data-detectors://2>. Review of applications/nominations will start immediately, and will continue until the position is filled. (Information provided by applicants will be used for recruitment and other employment-related purposes.)

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PhD position in computational neuroimaging
by Igor Yakushev Aug. 27, 2014

Aug. 27, 2014

A PhD position is open in the research group Multimodal Imaging in Normal and Pathological Cognition (Head: Dr. Igor Yakushev) at the Department of Nuclear Medicine, Technische Universität München (TUM), Munich, Germany. The project is dedicated to modeling/reconstruction of cerebral networks on the basis of brain images, as obtained using PET, DTI, and fMRI. Disease-related changes in patterns of cerebral connectivity should be quantified in patients with cognitive impairment and subjects at risk. The research group is integrated into the TUM Neuroimaging Center, which possesses a broad methodological and thematic expertise: http://www.tumnic.mri.tum.de/tumnic/index.html The PhD student will be enrolled at the TUM graduate school, which offers a structured curriculum of courses and seminars (in English) and supports participation in conferences and international exchange: http://www.gs.tum.de/en/home/ The Dept. of Nuclear Medicine offers exciting opportunities for neuroimaging research, in an interdisciplinary environment consisting of medical physicists, radiopharmacists and clinicians, and access to state-of-the-art technology including a hybrid PET/MR scanner (Siemens Biograph mMR). Eligible candidates should have a background in applied mathematics, computer science, image analysis or related disciplines. Prior experience with image analysis, Matlab programming and good statistical skills are required. A co-authorship in a scientific paper (at least in submission) is advantageous. The student will be co-supervised by a partner department of the TUM (e.g., Informatics), depending on his/her academic background. The salary/stipend is 1500-2000 EUR net / month, depending on performance of the student and availability of funds. There is no tuition fee at the TUM. The position can commence immediately, by 1.2015 at the latest. Interested researchers should submit their applications including CV, two recommendation letters (or names and contact details of personal references), and a brief letter of motivation to Dr. Yakushev at igor.yakushev(a)lrz.tum.de Applications will be considered until the position has been filled.

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AES Seizure Prediction Challenge
by Levin Kuhlmann Aug. 27, 2014

Aug. 27, 2014

Posted by Levin Kuhlmann on behalf of Ben Brinkmann Dear Colleagues, We had a phenomenal response to the Seizure Detection challenge (hosted through Kaggle.com<http://kaggle.com/>), which closed last week with 205 teams participating. We would like to call to your attention the AES Seizure Prediction challenge on Kaggle, which is now open to competitors at https://www.kaggle.com/c/seizure-prediction/. There is $USD 20,000 in prize money up for grabs! Sincerely, Ben =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- Benjamin H. Brinkmann, PhD Mayo Systems Electrophysiology Lab Alfred 9-441C, SMH 1216 Second St. SW Rochester, MN 55902 (507)538-5719 http://scholar.google.com/citations?user=ax95gtwAAAAJ&hl=en ________________________________

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A mailing list for Computational Glioscience
by Hugues Berry Aug. 26, 2014

Aug. 26, 2014

Dear colleagues, A spinoff of the recent OCNS workshop on the modelling of glia-neuron interactions, we have started a new mailing list. It is intended to share items of interest (new results, papers, events, trainings, jobs...) to the computational glioscience community, i.e. researchers implicated in the modelling and simulation of glial cells at large (astrocytes, microglia, oligodendrocytes, Schwann cells...) and their interactions with neurons. To subscribe, send an email to : sympa(a)inria.fr with the following Subject: subscribe comput-gliosci your_name Sincerely yours Maurizio De Pitta' Hugues Berry -------------------------------------------------------------------------------- Maurizio De Pitta' - https://sites.google.com/site/mauriziodepitta Hugues Berry - http://www.inrialpes.fr/Berry -------------------------------------------------------------------------------- Project-Team BEAGLE INRIA Rhone-Alpes Université de Lyon LIRIS UMR5205 Antenne INRIA de La Doua Batiment CEI-1 66 Blvd Niels Bohr CS 52132 69603 Villeurbanne cedex France

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Neural Circuits and Behavior Faculty Position
by Olaf Sporns Aug. 26, 2014

Aug. 26, 2014

NEURAL CIRCUITS AND BEHAVIOR FACULTY POSITION, INDIANA UNIVERSITY: The Department of Psychological and Brain Sciences at Indiana University -- Bloomington seeks to fill a faculty position at the level of Assistant Professor (tenure-track) to begin August 2015. Applicants for this position must have a doctorate, a strong record of publication, and the potential for research funding. The applicant's research should focus on using innovative experimental techniques in animal models to understand mechanisms and causal relationships between neural circuit activity and ethologically relevant behavior. We seek cutting-edge integration between new and emerging capabilities for large scale recording and/or manipulation of circuits combined with sophisticated analysis of large-scale data. Examples of behaviors of interest include those related to learning and memory, perception, decision making, reward, timing, pain, adaptation to stress, and developmental processes. Experimental techniques include various methods for recording and manipulating neural circuits at single-cell resolution, including multi-electrode recordings, imaging of circuit activity, and optogenetics. Candidates using circuit-based approaches to study preclinical models of schizophrenia, autism, and other difficult to treat psychiatric diseases are encouraged to apply. The successful candidate is expected to assemble a vibrant, externally-funded research program and to achieve excellence in both undergraduate and graduate education. Indiana University is in the midst of a multi-year initiative to build excellence in network science, and it is anticipated that the candidate's research will both benefit from, and contribute to the initiative's computational neuroscience components. To apply, please include a curriculum vita, copies of representative publications, statements of research and teaching interests, and three (3) letters of recommendation. Interested candidates should review the application requirements and submit their application at: https://indiana.peopleadmin.com. Questions regarding the position or application process can be directed to: William P. Hetrick, Ph.D., Professor and Chair, Department of Psychology and Brain Sciences, 1101 E. 10th St., Indiana University, Bloomington, IN 47405 or via email at whetrick(a)indiana.edu <mailto:whetrick@indiana.edu>. Review of all applications will begin on November 1, 2014 and will continue until the position is filled. Indiana University is an equal opportunity employment and affirmative action employer and a provider of ADA services. All qualified applicants will receive consideration for employment without regard to age, ethnicity, color, race, religion, sex, sexual orientation or identity, national origin, disability status or protected veteran status. Information about the department and the university is available at *http://psych.indiana.edu/faculty/opportunities.asp * * * -- Olaf Sporns -- @spornslab Department of Psychological and Brain Sciences Programs in Neuroscience and Cognitive Science Indiana University Bloomington, IN 47405

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CFP: MLINI 2014 - 4th NIPS Workshop on Machine Learning and Interpretation in Neuroimaging: Beyond the Scanner
by Irina Rish Aug. 25, 2014

Aug. 25, 2014

Call for Papers MLINI 2014 - 4th NIPS Workshop on Machine Learning and Interpretation in Neuroimaging: Beyond the Scanner https://sites.google.com/site/mlininips2014/ Friday, December 12, 2014, Montreal, Quebec, Canada Submission deadline: October 10th, 2014 Workshop Overview: ----------------------- MLINI workshop focuses on machine learning approaches in neuroscience, neuroimaging, with an extension to behavioral experiments and psychology. This year, our focus is specifically on "Going Beyond the Scanner", which includes making inferences about mental states of a subject from ''cheaper'' (as opposed to fMRI) behavioral data such as subject's speech and/or text, audio, video, EEG and signals collected from various wearable devices. We believe that machine learning has a prominent role in shaping how questions in neuroscience are framed, and that the machine-learning mind set is now entering modern psychology and behavioral studies. It is also equally important that practical applications in these fields motivate a rapidly evolving line or research in the machine learning community. In parallel, there is an intense interest in learning more about brain function in the context of rich naturalistic environments and scenes. Efforts to go beyond highly specific paradigms that pinpoint a single function, towards schemes for measuring the interaction with natural and more varied scene are made. In this context, many controversies and open questions exist. The goal of the workshop is to pinpoint the most pressing issues and common challenges across the fields, and to sketch future directions and open questions in the light of novel methodology. The proposed workshop is aimed at offering a forum that joins machine learning, neuroscience, and psychology community, and should facilitate formulating and discussing the issues at their interface. Motivated by the previous workshops in this series, MLINI ‘11, MLINI’12, and MLINI’13, we will center this workshop around invited talks and a panel discussion. Triggered by the discussions, this year we plan to adapt the workshop topics to a less traditional scope neuroimaging scope and investigate the role of behavioral models and psychology, including topics such as psycholinguistics. Open questions and possible topics for contribution include, but are not limited to, the following: - How can we move towards more naturalistic stimuli, tasks and paradigms in neuroimaging and neuro-signal analysis? - What kind of mental states can be inferred from cheaper and easier to collect data sources (as an alternative to fMRI), such as text, speech, audio, video, EEG, and wearable devices? - How can we leave the lab when acquiring neuroimaging data, towards exploiting mobile acquisition (EEG and NIRS)? - What type of features should be extracted from naturalistic stimuli such as text, voice, etc., to detect specific mental states and/or mental disorders? - How can we combine traditional neuroimaging with naturalistic data collected from a subject or group of subjects? - In general, can we characterize situations when multivariate predictive analysis (MVPA) and inference methods are better suited for brain imaging analysis than more traditional techniques? - Given recent advances of deep learning in image analysis and other applications, a natural question to ask is whether neuroimaging analysis can benefit from such approaches? - How well can functional networks and dynamical models capture the brain activity, and when using network and dynamics information is superior to standard task-based brain activations? Workshop Format: -------------------------- In this one-day workshop we will explore perspectives and novel methodology at the interface of Machine Learning, Inference, Neuroimaging and Neuroscience. We aim to bring researchers from machine learning and neuroscience community together, in order to discuss open questions, identify the core points for a number of the controversial issues, and eventually propose approaches to solving those issues. Each session will be opened by several invited talks, and an in depth discussion. This will be followed by original contributions. Original contributions will also be presented and discussed during a poster session. The workshop will end with a panel discussion, during which we will address specific questions, and invited speakers will open each segment with a brief presentation of their opinion. Paper Submission: -------------------------- We seek for submission of original (previously unpublished) research papers. The length of the submitted papers should not exceed 8 pages in Springer format, excluding the references (LaTeX2e style files are available on the workshop page). Submission of previously published work is possible as well, but the authors are required to mention this explicitly. Previously published work can be presented at the workshop, but will not be included into the workshop proceedings (which are considered peer-reviewed publications of novel contributions). Moreover, the authors are welcome to present their novel work but choose to opt out of the workshop proceedings in case they have alternative publication plans. Important dates: -------------------------- - October 10, 2014 - paper submission - October 24, 2014 - notification of acceptance/rejection - December 12, 2014 - Workshop at Montreal, Quebec, Canada , following the NIPS conference Organizing Committee: -------------------------- Guillermo Cecchi (IBM T.J. Watson Research Center) Kai-min Kevin Chang (Language Technologies Institute, Carnegie Mellon University) Georg Langs (Medical University of Vienna, CSAIL, MIT) Brian Murphy (Machine Learning Department, Carngie Mellon University) *Irina Rish (IBM T.J. Watson Research Center) - main contact Leila Wehbe (CMU)

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First release of VERTEX cortical tissue LFP simulator
by Marcus Kaiser Aug. 25, 2014

Aug. 25, 2014

Dear colleagues, Many of you may be interested the first release of our VERTEX simulator for biologically realistic models of *primate* cortical tissue. The Virtual Electrode Recording Tool for EXtracellular potentials (VERTEX) is a Matlab tool for simulating extracellular potential recordings in spiking neural network (SNN) models. As a first application, our model allows us to reproduce temporal and spatial gamma oscillation features of in vitro MEA recordings of macaque cortex using more than 100,000 model neurons. However, adapting the code to other species or tissue types is also possible in the future (see FAQ on our website). VERTEX 1.0 Release Features - VERTEX simulator allows large simulations (> 100 000 neurons) on single computers - *In silico* neuronal network model of an *in vitro* brain slice recording - Realistic local field potential recording with “virtual electrodes” at any 3D point - Direct comparisons between simulated and experimentally observed tissue Software, a two-minute introductory video, tutorials, manuals, and a FAQ can be found at: http://www.vertexsimulator.org/ This release is in conjunction with our publication: Tomsett RJ, Ainsworth M, Thiele A, Sanayei M, Chen X, Gieselmann A, Whittington MA, Cunningham MO, Kaiser M. Virtual Electrode Recording Tool for EXtracellular potentials (VERTEX): Comparing multi-electrode recordings from simulated and biological mammalian cortical tissue. Brain Structure and Function (in press) http://dx.doi.org/10.1007/s00429–014–0793-x <http://dx.doi.org/10.1007/s00429-014-0793-x> Best, Marcus -- Marcus Kaiser, Ph.D. Associate Professor (Reader) in Neuroinformatics School of Computing Science Newcastle University Claremont Tower Newcastle upon Tyne NE1 7RU, UK Lab website: http://www.dynamic-connectome.org/ Neuroinformatics@Newcastle: http://neuroinformatics.ncl.ac.uk/ -- Best, Marcus -- Marcus Kaiser, Ph.D. Associate Professor (Reader) in Neuroinformatics School of Computing Science Newcastle University Claremont Tower Newcastle upon Tyne NE1 7RU, UK Lab website: http://www. <http://www.biological-networks.org/>dynamic-connectome.org <http://www.dynamic-connectome.org/> Neuroinformatics@Newcastle: http://neuroinformatics.ncl.ac.uk/

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