September 2018 - Comp-neuro - lists.cnsorg.org

NEURON Course at SFN 2018 meeting

by Ted Carnevale

Space is still available for the NEURON course at this year's meeting of the Society for Neuroscience. Are you a lab director trying to decide whether to add computational modeling to your research program? A grad student or postdoc who is just getting started in modeling? An established NEURON user who wants to find out about NEURON's latest features? If so, this one-day course is for you! The course starts with a practical introduction that reviews basic concepts and presents a workflow for building and using models of cells and networks, and moves on to topics that include: --how to speed up simulations --how to use Python with NEURON (and take advantage of NEURON's GUI!) --how to model reaction-diffusion with the RxD class For more information and the registration form, see https://neuron.yale.edu/neuron/static/courses/sd2018/sd2018.html --Ted

Sept. 5, 2018

High Performance Computing workshop at SFN 2018 meeting

by Ted Carnevale

This year's workshop on High Performance Computing Resources for Parallel Simulations and Data Analysis will be held on Saturday, Nov. 3, from 8:30 AM to 12:30 PM in downtown San Diego as a satellite to the 2018 meeting of the Society for Neuroscience. It will feature presentations from developers and users of powerful hardware and software tools for dealing with computationally-intensive modeling and data analysis tasks. For more information and a link to the registration form, see https://neuron.yale.edu/neuron/static/courses/nsg2018/nsg2018.html The registration deadline for this workshop is Friday Oct. 12, but you should sign up early because space is limited. --Ted

Sept. 4, 2018

Postdoctoral position available in computational muscle modelling

by Sang-Hoon Yeo

Postdoctoral position available: Active spring muscle model - a new phenomenological model of skeletal muscle mechanics Understanding Machina Carnis, how our muscles mechanically generate movement, is one of the fundamental research questions in human movement science and also has significant implications in many application areas. Phenomenological muscle models, such as the Hill-type muscle model, have been widely used in studies on motor control and biomechanics. However, the performances of such models in predicting the dynamic contractile behaviours of the muscle, such as eccentric or sub-maximal contractions, are known to be far from accurate. This BBSRC (Biotechnology and Biological Sciences Research Council, United Kingdom)–funded postdoctoral research associate will join Dr Sang-Hoon Yeo’s research group to develop a new phenomenological model of the skeletal muscle mechanics. The key idea is to incorporate a newly proposed “active spring model” that involves titin as the third filament, together with actin and myosin filament, that actively regulates the mechanical behaviour of the muscle (see figures below). This new model is expected to be effectively utilized in various areas involving musculoskeletal simulation models, where the current prevalent use of the Hill-type model is identified as a major limiting factor. For two years starting in early 2019, the research associate will lead the first stage of the study focusing on in-vitro muscle/fiber experiments and model development. The research programme includes one-month visits to two prominent muscle biomechanics laboratories: 1) Prof Walter Herzog’s lab in University of Calgary (Calgary, Canada) and 2) Prof Kiisa Nisikawa’s lab in Northern Arizona University (Flagstaff, USA) to carry out data collection. Based on the collected data, the research associate will lead the data analysis, computational modelling and simulation of a new muscle mechanics model, and will also collaborate with other research associates to apply the developed muscle model to human biomechanics. The host institution, The University of Birmingham, is a Russell Group university in the vibrant City of Birmingham, United Kingdom. The university has produced eleven affiliated Nobel laureates and is also known as a cradle of modern muscle mechanics, dating back to the seminal work of Peter Rack and David Westbury. The School of Sport Exercise and Rehabilitation Sciences, where the research associate will be based, is a world-leading research institution in sport science, ranked 5th in the world (QS World Ranking, Sport-related subject). This highly interdisciplinary project is waiting for an ambitious and open-minded individual with substantial experience in computational motor control and muscle/musculoskeletal biomechanics. Individuals whose expertise lies in engineering and physical science and want to apply your skills in muscle biomechanics are also strongly encouraged to apply. Experience in wet-lab work is preferred but not strictly required. If you are interested to apply, please contact the principal investigator Dr Sang-Hoon Yeo (s.yeo(a)bham.ac.uk) to initiate discussion. Best wishes, Sang-Hoon -- Dr Sang-Hoon Yeo Lecturer in Biomechanics and Motor Control School of Sport, Exercise & Rehabilitation Sciences The University of Birmingham Edgbaston, Birmingham, B15 2TT, United Kingdom +44(0)121 414 8748

Sept. 4, 2018

Job ad: tenure-track open rank faculty positions in Cognitive Science

by Rajeev Raizada

http://www.sas.rochester.edu/bcs/jobs/faculty.html Cognitive Scientist, Open Rank, University of Rochester The Department of Brain and Cognitive Sciences at the University of Rochester is seeking to hire multiple faculty members in the area of decision making and cognitive or sensorimotor planning at the Assistant (tenure-track) or Associate Professor level. Areas of interest include the roles of learning, prediction, memory, and attention in guiding goal-directed behavior, especially within complex, naturalistic environments. We are primarily interested in candidates using neuroimaging, computational (e.g., Bayesian decision theory, reinforcement learning), behavioral (including technology-driven approaches such as virtual reality), and/or developmental approaches. Both individuals and teams are encouraged to apply. Successful candidates will join a dynamic department with interests in the study of perception, motor control, learning, cognition, language, and development through combined neurobiological, computational, and behavioral research (http://www.sas.rochester.edu/bcs/) she or he will also be part of a university–wide community engaged in graduate and undergraduate education. Candidates should hold a PhD degree (or equivalent) in cognitive science, psychology, neuroscience, or another relevant domain, and should have considerable research experience. Applicants should submit a CV, a statement of research and teaching interests, and contact information for three referees via the following website: http://www.rochester.edu/faculty-recruiting. In addition, team applications should include a joint statement that describes the research synergies of the team. Questions concerning this position can be addressed to Robert Jacobs (rjacobs(a)ur.rochester.edu) and Duje Tadin (dtadin(a)ur.rochester.edu) co-chairs of the search committee. Review of applications will begin on November 1, 2018. The University of Rochester is an Equal Opportunity Employer with a strong commitment to diversity, and actively encourages applications from candidates from groups underrepresented in higher education. EOE / Minorities / Females / Protected Veterans / Disabled

Sept. 4, 2018

An Amazing Job Opportunity at Apple!

by Burak Yildiz

We are looking for a Senior Systems Neuroscientist to join a great team of researchers at Apple in the San Francisco Bay Area. It's a unique opportunity to do research in industry. Please apply at this link: https://jobs.apple.com/us/search#&ss=Neuroscientist&t=0&so=&lo=0*USA&pN=0&o… Thanks, Burak Yildiz Sr. Research Scientist at Apple

Sept. 4, 2018

[meetings] Call for Participation : Workshop on Continual Unsupervised Sensorimotor Learning - Tokyo - September 17th

by Nguyen, Sao Mai

Call for Participation Workshop on Continual Unsupervised Sensorimotor Learning at IEEE ICDL-Epirob 2018 - Tokyo - September 17th Website : http://conferences.au.dk/icdl-epirob-2018-workshop/ ============================================================ Invited Speakers - Jochen Triesch, Frankfurt Institute of Advanced Studies, Germany - David Ha, Google Brain - Lorenzo Jamone, Queen Mary University of London, UK Scope As the algorithms for learning single tasks in restricted environments are improving, new challenges have gained relevance. They include multi-task learning, multimodal sensorimotor learning in open worlds and lifelong adaptation to injury, growth and ageing. In this workshop we will discuss the developmental processes involved in the emergence of representations of action and perception in humans and artificial agents in continual learning. These processes include action-perception cycle, active perception, continual sensory-motor learning, environmental-driven scaffolding, and intrinsic motivation. The discussion will be strongly motivated by behavioural and neural data. We hope to provide a discussion friendly environment to connect with research with similar interest regardless of their area of expertise which could include robotics, computer science, psychology, neuroscience, etc. We would also like to devise a roadmap or strategies to develop mathematical and computational models to improve robot performance and/or to attempt to unveil the underlying mechanisms that lead to continual adaptation to changing environment or embodiment and continual learning in open-ended environments. The primary list of topics covers the following (but not limited to): - Emergence of representations via continual interaction - Continual sensory-motor learning - Action-perception cycle - Active perception - Environmental-driven scaffolding - Intrinsic motivation - Neural substrates, neural circuits and neural plasticity - Human and animal behaviour experiments and models - Reinforcement learning and deep reinforcement learning for life-long learning - Multisensory robot learning - Multimodal sensorimotor learning - Affordance learning - Prediction learning Organizers: - Nicolás Navarro-Guerrero, Aarhus University, Aarhus, Denmark - Sao Mai Nguyen, IMT Atlantique, France - Erhan Öztop, Özyeğin University, Turkey - Junpei Zhong, National Institute of Advanced Industrial Science and Technology (AIST), Japan Nguyen Sao Mai nguyensmai(a)gmail.com Researcher in Cognitive Developmental Robotics http://nguyensmai.free.fr

Sept. 3, 2018

[journals] CfP : Special Issue on Continual Unsupervised Sensorimotor Learning

by Nguyen, Sao Mai

Dear Colleagues, IEEE Transactions on Cognitive and Developmental Systems is currently running a Special Issue entitled " Continual Unsupervised Sensorimotor Learning". Dr. José Antonio Iglesias Martínez, Assoc. Prof. We would like to invite you to prepare a research article or a comprehensive review to be published in this special issue. AIM AND SCOPE Although machine learning algorithms continue to improve at a rapid pace enabling technologies and products such as autonomous driving cars and sophisticated image and speech recognition, it is often forgotten that these applications represent tailored solutions to specific tasks. Thus it is not clear if or how these autonomous systems can pave the road to general purpose machines envisioned by many. The pursuit for higher levels of autonomy and versatility in robotics is arguably lead by two main factors. Firstly, as we push robots out of the labs and productions lines, it becomes increasingly difficult to design for all possible scenarios that a particular robot might encounter. Secondly, the cost of designing, manufacturing, and maintaining such systems becomes prohibitive. As the algorithms for learning single tasks in restricted environments are improving, new challenges have gained relevance in order to get more autonomous artificial systems. These challenges include multi-task learning, multimodal sensorimotor learning and lifelong adaptation to injury, growth and ageing. Addressing these challenges promise higher levels of autonomy and versatility of future robots. This special issue on Continual Unsupervised Sensorimotor Learning is primarily concerned with the developmental processes involved in unsupervised sensorimotor learning in a life-long perspective, and in particular the emergence of representations of action and perception in humans and artificial agents in continual learning. These processes include action-perception cycle, active perception, continual sensory-motor learning, environmental-driven scaffolding, and intrinsic motivation. The special issue will highlight behavioural and neural data, and cognitive and developmental approaches to research in the areas of robotics, computer science, psychology, neuroscience, etc. Contributions might focus on mathematical and computational models to improve robot performance and/or attempt to unveil the underlying mechanisms that lead to continual adaptation to changing environment or embodiment and continual learning in open-ended environments. Contributions from multiple disciplines including cognitive systems, cognitive robotics, developmental and epigenetic robotics, autonomous and evolutionary robotics, social structures, multi-agent and artificial life systems, computational neuroscience, and developmental psychology, on theoretical, computational, application-oriented, and experimental studies as well as reviews in these areas are welcome. THEMES This special issue aims to report state-of-the-art approaches and recent advances on Continual Unsupervised Sensorimotor Learning with a cross-disciplinary perspective. Topics relevant to this special issue include but are not limited to: Emergence of representations via continual interaction Continual sensory-motor learning Action-perception cycle Active perception Environmental-driven scaffolding Intrinsic motivation Neural substrates, neural circuits and neural plasticity Human and animal behaviour experiments and models Reinforcement learning and deep reinforcement learning for life-long learning Multisensory robot learning Multimodal sensorimotor learning Affordance learning Prediction learning SUBMISSION Manuscripts should be prepared according to the “Information for Authors” of the journal found at http://cis.ieee.org/component/content/article/7/131-ieee-transactions-on-au…. Submissions must be done through the IEEE TCDS Manuscript center: https://mc.manuscriptcentral.com/tcds-ieee. Please select the category “SI: Continual Unsupervised Sensorimotor Learning”. IMPORTANT DATES 6th January 2019 – Paper submission deadline 15th March 2019 – Notification for authors 31st May 2019 – Deadline revised papers submission 30th June 2019 – Final notification for authors 31st July 2019 – Deadline for camera-ready versions September 2019 – Expected publication date More information on Continual Unsupervised Sensorimotor Learning http://projects.au.dk/socialrobotics/news-events/show/artikel/special-issue… GUEST EDITORS Nicolás Navarro-Gerrero Aarhus University, Aarhus, Denmark nng(a)eng.au.dk Sao Mai Nguyen IMT Atlantique, Francenguyensmai(a)gmail.com Erhan Öztop Özyeğin University, Turkeyerhan.oztop(a)ozyegin.edu.tr Junpei Zhong National Institute of Advanced Industrial Science and Technology (AIST), Japanjoni.zhong(a)aist.go.jp ---- Nguyen Sao Mai nguyensmai(a)gmail.com Researcher in Cognitive Developmental Robotics http://nguyensmai.free.fr

Sept. 3, 2018

2 open PhD positions in Sprekeler & Kempter labs on models of memory consolidation

by Richard Kempter

Dear all, 2 PhD positions are open in the labs of Henning Sprekeler (TU Berlin) and Richard Kempter (HU Berlin), respectively, to be filled as soon as possible. Both positions are part of the recently established collaborative research center "Mechanisms and disturbances in memory consolidation: >From synapses to systems" https://fis.hu-berlin.de/converis/portal/Project/401700446?auxfun=&lang=en_… The project B01 in this research center focuses on developing computational models of systems memory consolidation, both conceptually and constrained by data from rodents and flies. The two PhD students are expected to collaborate closely. The ideal candidate has a background in computational neuroscience, strong mathematical and programming skills, and a keen interest in synaptic plasticity, learning and memory. If you are interested, please contact Henning Sprekeler or Richard Kempter. Please send the usual application documents (CV, letter of motivation, certificates of BSc and MSc, 2 references) until September 13, 2018. Interviews will take place on September 24/25 and/or September 28, i.e. around the Bernstein Conference in Berlin. Best wishes, Henning & Richard --- Prof. Dr. Henning Sprekeler (TU Berlin) Modelling of cognitive processes Technische Universität Berlin & Bernstein Center for Computational Neuroscience Berlin Sekr. MAR 5-3 Marchstr. 23 10587 Berlin, Germany Email: h.sprekeler(a)tu-berlin.de https://www.cognition.tu-berlin.de/menue/members/henning_sprekeler/ Phone: +49 (0)30 314 73557 Prof. Dr. Richard Kempter (HU Berlin) Theoretical neuroscience Humboldt-Universität zu Berlin & Bernstein Center for Computational Neuroscience Berlin Philippstr. 13, Building number 4 D-10115 Berlin, Germany Email: r.kempter(a)biologie.hu-berlin.de http://itb.biologie.hu-berlin.de/~kempter/index.html Phone +49-(0)30-2093-98404

Sept. 3, 2018

EEG and Machine Learning Postdoctoral Position at Stanford for Personalized Medicine

by Sanggyun Kim

*EEG and Machine Learning Postdoctoral Position at Stanford for PersonalizedMedicine* The Laboratory of Amit Etkin, MD PhD at Stanford University is currently accepting applications for a postdoctoral fellow focused on machine learning and other sophisticated analyses of electroencephalography (EEG) data. This position is funded by an NIH Director’s Pioneer Award. The focus of the position is on creating and applying a variety of data analytic approaches to large EEG data sets (across individuals, or longitudinally within- individual) for the purpose of prediction of clinical outcome and tracking of clinical change. Particular emphasis is on connecting signal processing methodology to the classification challenges, potential use of deep learning, and building on applications from other related areas (e.g. brain-computer interface or other decoding efforts). It is anticipated that this work will contribute to development of clinic-translatable biomarkers, and will be part of FDA approval-directed efforts ongoing in the lab. The successful applicant will have a PhD in Engineering, Statistics, Computer Science, Neuroscience, Neurophysiology, Psychology, or related fields. Advanced experience with EEG data analysis and/or machine learning is required. Additionally, strong quantitative skills and a programming background are important. Duties will also include manuscript preparation, presentation of findings at conferences, and contribution to the preparation of grants. Laboratory and Stanford resources are extensive, MRI scanners, simultaneous EEG/fMRI, multiple high density EEG setups, and concurrent transcranial magnetic stimulation (TMS)/fMRI and concurrent TMS/EEG setups. Salary commensurate with experience. More information about our ongoing studies can be found at: http://etkinlab.stanford.edu. To apply, please send a curriculum vitae, a statement describing research interests and relevant background and the names of three recommenders, as well as relevant reprints/preprints of research articles to: Amit Etkin, MD, PhD Department of Psychiatry and Behavioral Sciences Stanford Neurosciences Institute Stanford University amitetkin(a)stanford.edu

Sept. 1, 2018