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Postdoctoral Position in Computational and Systems Neuroscience
by Escabi, Monty Sept. 9, 2015

Sept. 9, 2015

Dear Colleagues We have a postdoctoral postion available in computational and systems neuroscience. Details of the position can be found at http://escabilab.uconn.edu/2015/08/13/postdoctoral-position-in-computationa… and are also posted below. Please share this information with anyone who may be interested. Thanks very much! Monty _\\|//_ (' O-O ') ---------------------------ooO-(_)-Ooo-------------- Monty A. Escabi, Ph.D. Associate Professor University of Connecticut Electrical & Computer Engineering Biomedical Engineering 371 Fairfield Way, Unit 4157 Storrs, CT 06269-4157 ---------------------------------------------------------- Postdoctoral Position in Computational and Systems Neuroscience Position: The Physiological Acoustics Lab (http://escabilab.uconn.edu) at the University of Connecituct seeks applicants for a postdoctoral position in systems and computational neuroscience. We are seeking applicants that can lead a project on coding of natural sound statistics in the auditory midbrain and cortex of awake animals. The primary appointment will be in Biomedical Engineering, but the work will be conducted in collaboration with Psychology department (Statistical Neuroscience Lab, http://stevenson.lab.uconn.edu; Sensory Perception and Neuroscience Lab, http://read.lab.uconn.edu) and Electrical and Computer Engineering. Qualifications: A PhD in Neuroscience, Biomedical Engineering, Electrical Engineering, Computational Neuroscience or related field is required. The ideal candidate will have an interdisciplinary research background in computational and systems neuroscience with prior research experience in awake animal neurophysiology. A strong computational background in neural data analysis is desirable, particularly modeling complex neural systems and analyzing datasets from large-scale multi-channel neural recordings. Background in acoustic signal processing, sound recognition, and machine learning are also desirable. Appointment: The position is funded through an R01 and is available immediately. Salaries follow NIH post-doctoral scale and are based on experience. Applicants should email “escabi at engr dot uconn dot edu” a single PDF file containing: 1) a resume including past research experience and published work 2) a one page statement of prior research experience 3) a one page statement of future research interests and objectives 4) the names of at least two individuals who can provide reference letters.

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COSYNE 2016: Meeting Announcement and Call for Abstracts
by Tomas Hromadka Sept. 9, 2015

Sept. 9, 2015

==================================================== Computational and Systems Neuroscience 2016 (Cosyne) MAIN MEETING Feb 25 - Feb 28, 2016 Salt Lake City, Utah WORKSHOPS Feb 29 - Mar 01, 2016 Snowbird Ski Resort, Utah www.cosyne.org ==================================================== The annual Cosyne meeting provides an inclusive forum for the exchange of empirical and theoretical approaches to problems in systems neuroscience, in order to understand how neural systems function. The MAIN MEETING is single-track. A set of invited talks are selected by the Executive Committee, and additional talks and posters are selected by the Program Committee, based on submitted abstracts. The WORKSHOPS feature in-depth discussion of current topics of interest, in a small group setting. Cosyne topics include but are not limited to: neural coding, natural scene statistics, dendritic computation, neural basis of persistent activity, nonlinear receptive field mapping, representations of time and sequence, reward systems, decision-making, synaptic plasticity, map formation and plasticity, population coding, attention, and computation with spiking networks. This year we would like to foster increased participation from experimental groups as well as computational ones. Please circulate widely and encourage your students and postdocs to apply. IMPORTANT DATES: Abstract submission opens: 05 October 2015 Abstract submission deadline: 13 November 2015 CONFIRMED SPEAKERS: Blaise Aguera y Arcas (Google) Marisa Carrasco (NYU) Edward Chang (UCSF) Greg DeAngelis (Rochester) Mark Goldman (UC Davis) Richard Mooney (Duke) Mala Murthy (Princeton) Peggy Series (Edinburgh) Reza Shadmehr (Johns Hopkins) Paul Smolensky (Johns Hopkins) Leslie Vosshall (Rockefeller) When preparing an abstract, authors should be aware that not all abstracts can be accepted for the meeting, due to space constraints. Abstracts will be selected based on the clarity with which they convey the substance, significance, and originality of the work to be presented. ORGANIZING COMMITTEE: General Chairs: Maria Geffen (U Penn) and Konrad Körding (Northwestern) Program Chairs: Megan Carey (Champalimaud) and Emilio Salinas (Wake Forest) Workshop Chairs: Claudia Clopath (Imperial College) and Alfonso Renart (Champalimaud) Publicity Chair: Xaq Pitkow (Rice) EXECUTIVE COMMITTEE: Anne Churchland (CSHL) Zachary Mainen (Champalimaud) Alexandre Pouget (U Geneva) Anthony Zador (CSHL) CONTACT cosyne.meeting [at] gmail.com

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Postdoc positions in modeling stochastic spiking neural networks in São Paulo State, Brazil
by Antonio C. Roque Sept. 9, 2015

Sept. 9, 2015

The Research, Innovation and Dissemination Center for Neuromathematics (NeuroMat, http://neuromat.numec.prp.usp.br/ ), hosted by the University of São Paulo, Brazil, and funded by FAPESP (Sao Paulo Research Foundation, http://www.fapesp.br/en/) is offering several postdoctoral fellowships for recent PhDs with outstanding research potential. The research will involve collaborations with mathematicians, computer scientists, physicists and neuroscientists associated to NeuroMat. We seek candidates capable to develop independent research in mathematical and/or computational modeling of stochastic spiking neural networks. Candidates are required to have at least one of the profiles below: - A strong background in probability theory with emphasis on stochastic processes or alternatively in statistics with emphasis on statistical model selection. Previous knowledge of rigorous statistical mechanics, random graphs or stochastic modeling in biosciences will be favorably considered. - A strong mathematical and/or computational background and experience with computers and programming. Previous experience with development and/or simulation of neural brain models, complex networks and parallel computing will be favorably considered. The initial appointment is for two years, with a possible extension to up to four years, conditional on research progress. Salary is competitive at international level, and fellows benefit from extra funds for travel and research expenses plus limited support for relocation expenses. Application instructions Applicants should complete and submit the application form at http://neuromat.numec.prp.usp.br/postdoc-form. The following documents and information are requested (please see the form for further details): - Summary of the Curriculum vitae. Please follow the FAPESP format; see www.fapesp.br/en/6351 for instructions. - List of publications, with links to those available online. - Pointers to other research related output, such as software, web pages, and so forth. Candidates should be willing to send copies of publications, if requested. - A summary of your research plan for the next 2 years, up to 5 pages length. It should explicitly address its place in the framework of the NeuroMat mission and research program ( http://neuromat.numec.prp.usp.br/scientific_project) - Any further information deemed relevant to the application. In addition to the above, we require at least 2 recommendation letters. Those should be mailed by the recommenders directly to postdoc-appl(a)numec.prp.usp.br. Candidates are encouraged to apply at their earliest convenience. Two independent evaluation rounds are planned: 1. On October 12, 2015. 2. On November 16, 2015. Appointments are expected to be effective within 2 to 6 months after evaluation date. Remark Approved candidates will be requested to expand their five-page research plan to a full two-year proposal. For the implementation of the fellowships, those proposals, together with all the application material received, will be submitted to FAPESP for final approval. -- Dr. Antonio C. Roque Professor Associado Departamento de Fisica FFCLRP, Universidade de Sao Paulo 14040-901 Ribeirao Preto-SP Brazil - Brasil E-mails: antonior(a)ffclrp.usp.br aroquesilva(a)gmail.com URL: www.sisne.org Tels: +55 16 3315-3768 (sala/office); +55 16 3315-3859 (lab) FAX: +55 16 3315-4887

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Early Bird Registration Ends Today!!
by neuro girl Sept. 9, 2015

Sept. 9, 2015

Dear Colleagues, Just a reminder that early birds registration ends today!Registration includes breakfast, coffee breaks and lunch. Please note: registration will be limited to encourage open discussion. The Brain States: Characterization and Neuromodulation by DBS will take place on November 11-13, 2015 in Cologne, Germany. This is an interdisciplinary meeting with leading experts in academia and medicine who will present physiological, computational and clinical approaches to the brain dynamics and brain mechanics of complex functional networks in the brain. Transformations of the neurodynamic operations of the brain between the normal to the pathological state will be explored using multivariate data analysis (EEG, MEG, DBS, etc…). Special attention will be given to next-generation approaches which allow the collaboration of clinical practice and science to advance the field from principles of organization to the causal control of function. Brain States: Characterization and Neuromodulation by DBS November 11-13, 2015 Cologne, Germany http://bit.ly/1JVElkf https://dbs.veomed.net/. Confirmed Speakers:Hagai Bergman (Hebrew University of Jerusalem) Peter Brown (University of Oxford) Stephan Chabardes (University Hospital Grenoble) Alain Destexhe (CNRS) Emad N. Eskandar (Massachusetts General Hospital-Harvard Medical School) John J. Foxe (Albert Einstein College of Medicine) Marc Goodfellow (University of Exeter) Anthony A. Grace (University of Pittsburgh) Rowshanak Hashemiyoon (University Hospital of Cologne) Jens Haueisen (Technische Universität Ilmenau) Viktor Jirsa (Aix-Marseille Université /CNRS) Jens Kuhn (University Hospital Cologne) Fernando Lopes da Silva (University of Amsterdam) Andres Lozano (University of Toronto) Cameron McIntyre (Case Western Reserve University) Christoph M. Michel (University of Geneva) Urs Ribary (Simon Fraser University) Günter Schiepek (Paracelsus Medical University) Wolf Singer (Max Planck Institute for Brain Research) Dimitri van de Ville (University of Geneva) Veerle Visser-Vandewalle (University Hospital of Cologne) Jürgen Voges (Otto-von-Guericke-University Magdeburg) Looking forward to seeing you in Cologne! With kind regards, Row Hashemiyoon Rowshanak Hashemiyoon, PhD Chief, Behavioral Neurophysiology and Computational Neuroscience Klinik für Stereotaxie und Funktionelle Neurochirurgie Universitätsklinikum Köln Kerpener Str. 62 D - 50937 Köln Email: row.hashemiyoon(a)uk-koeln.de http://www.uk-koeln.de/de/stereotaxie

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SCiNDU abstract deadline Oct 16th
by Geoffrey Goodhill Sept. 9, 2015

Sept. 9, 2015

SCiNDU: SYSTEMS AND COMPUTATIONAL NEUROSCIENCE DOWN UNDER qbi.uq.edu.au/scindu<http://qbi.uq.edu.au/scindu> December 15-17th, 2015, Queensland Brain Institute, The University of Queensland, Brisbane, Australia. Deadline for abstracts and early registration is Oct 16th 2015. Early bird registration fees: AU$250 (Full), AU$125 (Student). Accommodation is available if required in a residential college at the University of Queensland for AU$85/night. This conference will bring together international leaders in understanding the computational principles underlying how neural circuits decode sensory information, make decisions, and learn from experience. Abstract submissions for poster presentation are welcome. Some abstracts will be selected for short talks. Confirmed speakers include: Ehsan Arabzadeh (ANU) Mark Bear (MIT) Michael Breakspear (QIMR) Allen Cheung (QBI) Yang Dan (UC Berkeley) Peter Dayan (UCL) Geoffrey Goodhill (QBI) Zach Mainen (Champalimaud) Jason Mattingley (QBI) Linda Richards (QBI) Peter Robinson (Sydney) Marcello Rosa (Monash) Pankaj Sah (QBI) Mandyam Srinivasan (QBI) Greg Stuart (ANU) Stephen Williams (QBI) Li Zhaoping (UCL) The conference will commence mid-afternoon on Dec 15th and finish at 4pm on Dec 17th. On Dec 15th at 10am the main conference will be preceded by a choice of 3-hour tutorials (tutorial registration AU$50): Mark Bear: Experience-dependent synaptic plasticity Peter Dayan: Neural reinforcement learning Jason Mattingley: Brain stimulation, attention and plasticity Li Zhaoping: Vision, efficient coding and salience We gratefully acknowledge financial support from the Queensland Brain Institute and the Australian Research Council Centre of Excellence for Integrative Brain Function. Professor Geoffrey J Goodhill Queensland Brain Institute and School of Mathematics & Physics University of Queensland St Lucia, QLD 4072, Australia Email: g.goodhill(a)uq.edu.au<mailto:g.goodhill@uq.edu.au> http://www.qbi.uq.edu.au/professor-geoffrey-goodhill

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Postdoc positions in Computational Neuroscience/Psychiatry
by Murray, John Sept. 8, 2015

Sept. 8, 2015

The lab of Dr. John Murray at Yale University (http://murraylab.yale.edu) invites applications for postdoctoral positions for research in computational neuroscience. Successful candidates are expected to play an active and independent role in one of our research areas. Our work focuses on understanding the mechanisms of neural dynamics and cognitive function. We also apply computational insights from models to advance the study of brain disorders such as schizophrenia, in a framework for Computational Psychiatry. Our group leverages theoretical and computational modeling of neural circuits, as well as analysis of neural data. We emphasize close collaboration with experimental laboratories using a variety of techniques. Lab members will benefit from the rich intellectual environment at Yale, with exposure to cutting-edge experimental neuroscience and quantitative approaches to biology, through venues such as the Swartz Program in Theoretical Neurobiology<https://medicine.yale.edu/neurobiology/swartz/>. Potential research topics include: — Cortical microcircuitry supporting cognitive computations, e.g. roles of interneurons — Dynamics and structure-function relationships in large-scale brain networks — Neural circuit dysfunction in psychiatric disorders — Neural data analysis, ranging from single-neuron recordings to human neuroimaging, in close collaboration with experimentalists Candidates with a Ph.D. in neuroscience or physical sciences, and with a strong background and interest in quantitative approaches to neurobiology or psychiatry, are especially encouraged to apply. Please email Dr. Murray (john.murray(a)yale.edu<mailto:john.murray@yale.edu>) with the following: (1) a CV, (2) a brief (less than 1 page) statement of research interests and how they may fit with those of the lab, and (3) contact information (email and phone) for three references. Informal inquiries are welcome. John D. Murray ----------------------------------------------- Assistant Professor Department of Psychiatry Yale University School of Medicine murraylab.yale.edu<http://murraylab.yale.edu> -----------------------------------------------

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Fwd: [CN-CR] lecturer position in computational neuroscience, at CNCR, Uni Bham, UK
by Chris Miall Sept. 8, 2015

Sept. 8, 2015

Please see link below for 1-year teaching opportunity. Chris Miall Sent from my iPad > > we have an open teaching-focused lecturer position in computational neuroscience and modelling. > We would be very grateful if you could forward the link to potentially interested candidates at this and other institutions. > > https://atsv7.wcn.co.uk/search_engine/jobs.cgi?amNvZGU9MTQ4ODU2OSZ2dF90ZW1w… > > Many thanks and Best wishes > Uta > > > _______________________________________________ > cn-cr mailing list > cn-cr(a)cs.bham.ac.uk > https://mailman.cs.bham.ac.uk/mailman/listinfo/cn-cr

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Recruiting Postdocs in Theoretical / Computational Neuroscience
by Zylberberg, Joel L Sept. 8, 2015

Sept. 8, 2015

Hi All, Several postdoctoral positions in theoretical/computational neuroscience are available in the Department of Physiology and Biophysics (PBio) at the University of Colorado's Anschutz Medical Campus, located in Aurora Colorado. The successful candidate(s) will work under the supervision of Dr. Joel Zylberberg to understand how the brain functions so robustly, despite the high levels of variability in the activities of its component neurons. This work will involve the development of mathematical /computational models of neural computation and/or neural communication that can be tested using experimental data. The PBio department has strengths in olfaction, audition, decision-making, motor control, cardiac pacemaking, and development, providing a rich scientific environment. Dr. Zylberberg also has on-going collaborations with retinal and hippocampal physiologists, providing additional opportunities for theory-experiment interaction. Requirements: Applicants should have (or soon be completing) a Ph.D. in either neuroscience, or in a quantitative discipline like applied mathematics, physics, computer science, electrical engineering, etc. The ideal candidate is a highly motivated problem solver with strong programming skills, previous experience in theoretical / computational neuroscience, and a deep desire to understand the principles underlying the functioning of the nervous system. Excellent communication skills are a must. Applicants should email Dr. Zylberberg (joel(dot)zylberberg(at)ucdenver.edu) with the following (please provide these in .pdf format): 1. C.V. including a list of publications, research experience, and education 2. A 1-2 page summary of previous research accomplishments 3. A 1-2 page description of future research goals and interests 4. Names and contact information for 2-3 people who can provide letters of reference Applications will be reviewed as they arrive. For more information about the PBio department, please visit our website at medschool.ucdenver.edu/physiology. __ Joel Zylberberg Assistant Professor Department of Physiology and Biophysics University of Colorado School of Medicine Aurora, CO ~the neuroscience is theoretical, but the fun is real

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Researcher Position, Machine Learning for User Modelling and HRI, Personal Robotics Lab, Imperial College London
by Demiris, Yiannis Sept. 8, 2015

Sept. 8, 2015

Dear colleagues, a research position (either at PhD-candidate or postdoctoral levels) in machine learning for user-modelling and human-robot Interaction are available at the Personal Robotics Laboratory of the Department of Electrical and Electronic Engineering at Imperial College London. Successful applicants will work under the supervision of Dr Yiannis Demiris (www.demiris.info<http://www.demiris.info/>) in the context of the new EU H2020 project PAL (Personal Assistants for healthy Lifestyle, 2015-2019), which aims to develop personalised robotic systems and avatars to assist diabetic (T1DM) children and their caregivers. The PAL position are available from 1st of October 2015 until the end of the project at the end of Feb 2019 subject to renewal. Applicants should have an excellent background in mathematics, machine learning and software engineering, and should be committed to applying their research to real systems interacting with people in challenging environments. The positions offer an excellent working environment in one of the world's top research universities, in one of the most exciting cities in the world. The Department of Electrical and Electrical Engineering at Imperial was ranked as the top EE department in the UK in the recent REF 2014, while its Personal Robotics Laboratory offers an energetic, friendly intellectual environment with state of the art facilities http://www.imperial.ac.uk/PersonalRobotics For further information and links to application material: http://www.imperial.ac.uk/personalrobotics/join_us With best wishes, Yiannis ---- Dr Yiannis Demiris, FIET, FBCS, FRSS Reader (Associate Professor) in Personal Robotics, Department of Electrical and Electronic Engineering, Rm 1014, Imperial College London, South Kensington Campus, Exhibition Road, London, SW7 2BT, UK Tel: +44-(0)2075946300, Fax: +44-(0)2075946274 http://www.iis.ee.ic.ac.uk/yiannis Lab: http://www.imperial.ac.uk/PersonalRobotics

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Workshop announcement: Supercomputing for Neuroscientists (Juelich, 3.11.2015)
by Abigail Morrison Sept. 7, 2015

Sept. 7, 2015

Supercomputing for Neuroscientists - How High-Performance Computing can help your neuroscience projects Date: 3 November 2015 Venue: Jülich Supercomputing Centre, Forschungszentrum Jülich, Jülich, Germany Registration deadline: 25 October 2015 This workshop aims at bringing neuroscientists interested in using HPC technology for their projects together with experts from the Jülich Supercomputing Centre’s Simulation Laboratory Neuroscience<www.fz-juelich.de:ias:jsc:slns> whose main goal is to bridge the gap between Computational Neuroscience and HPC. The workshop is primarily intended for PIs whose affiliation is in Germany and who may therefore apply for computing time on the Jülich supercomputers through the national GCS and NIC calls<http://www.fz-juelich.de/ias/jsc/EN/Expertise/Supercomputers/ComputingTime/…>, it will also touch on how European supercomputing resources, including those of Jülich, may be accessed by PIs from outside of Germany through the European PRACE access schemes<http://www.prace-ri.eu/hpc-access>. For detailed information on the workshop and registration, please visit: www.fz-juelich.de/ias/jsc/scn<www.fz-juelich.de:ias:jsc:scn> Organizer: SimLab Neuroscience (slns(a)fz-juelich.de) -- Prof. Dr. Abigail Morrison Institute of Neuroscience and Medicine (INM-6) Functional Neural Circuits Group Jülich Research Center http://www.fz-juelich.de/inm/inm-6/ Office: +49 2461 61-9805 Fax # : +49 2461 61-9460 ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Dr. Karl Eugen Huthmacher Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt, Prof. Dr. Sebastian M. Schmidt ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------

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Postdoc positions (Wolpert lab, University of Cambridge)
by Daniel Wolpert Sept. 7, 2015

Sept. 7, 2015

A Postdoc position is available in the Computational and Biological Learning Group, University of Cambridge to work on theoretical and/or experimental approaches to human sensorimotor control. The project is led by Professor Daniel Wolpert and involves investigating the processes involved in sensorimotor decision-making, learning, integration and control. Further details on http://www.wolpertlab.com <http://www.wolpertlab.com/> Closing date Sept 23rd

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CFP: MLINI 2015 - 5th NIPS Workshop on Machine Learning and Interpretation in Neuroimaging: Beyond the Scanner (corrected version)
by Irina Rish Sept. 6, 2015

Sept. 6, 2015

Call for Papers MLINI 2015 - 5th NIPS Workshop on Machine Learning and Interpretation in Neuroimaging: Beyond the Scanner https://sites.google.com/site/mliniworkshop2015/ December 11-12, 2015, Montreal, Quebec, Canada Submission deadline: Monday, October 12th, 2015 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 two-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 12, 2014 - paper submission - October 26, 2014 - notification of acceptance/rejection - December 11-12, 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) Moritz Grosse-Wentrup (Max Plank Institute for Intelligent Systems) 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 (University of California, Berkeley)

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Call for Abstracts: NIPS Workshop on Statistical Methods for Understanding Neural Systems
by Jascha Sohl-Dickstein Sept. 5, 2015

Sept. 5, 2015

NIPS WORKSHOP 2015 CALL FOR ABSTRACTS Statistical Methods for Understanding Neural Systems Friday, December 11th, 2015 Montreal, Canada -------- Organizers: Allie Fletcher Jakob Macke Ryan Adams Jascha Sohl-Dickstein -------- Overview: Recent advances in neural recording technologies, including calcium imaging and high-density electrode arrays, have made it possible to simultaneously record neural activity from large populations of neurons for extended periods of time. These developments promise unprecedented insights into the collective dynamics of neural populations and thereby the underpinnings of brain-like computation. However, this new large-scale regime for neural data brings significant methodological challenges. This workshop seeks to explore the statistical methods and theoretical tools that will be necessary to study these data, build new models of neural dynamics, and increase our understanding of the underlying computation. We have invited researchers across a range of disciplines in statistics, applied physics, machine learning, and both theoretical and experimental neuroscience, with the goal of fostering interdisciplinary insights. We hope that active discussions among these groups can set in motion new collaborations and facilitate future breakthroughs on fundamental research problems. Call for Papers We invite high quality submissions of extended abstracts on topics including, but not limited to, the following fundamental questions: How can we deal with incomplete data in a principled manner? In most experimental settings, even advanced neural recording methods can only sample a small fraction of all neurons that might be involved in a task, and the observations are often indirect and noisy. As a result, many recordings are from neurons that receive inputs from neurons that are not themselves directly observed, at least not over the same time period. How can we deal with this `missing data' problem in a principled manner? How does this sparsity of recordings influence what we can and cannot infer about neural dynamics and mechanisms? How can we incorporate existing models of neural dynamics into neural data analysis? Theoretical neuroscientists have intensely studied neural population dynamics for decades, resulting in a plethora of models of neural population dynamics. However, most analysis methods for neural data do not directly incorporate any models of neural dynamics, but rather build on generic methods for dimensionality reduction or time-series modelling. How can we incorporate existing models of neural dynamics? Conversely, how can we design neural data analysis methods such that they explicitly constrain models of neural dynamics? What synergies are there between analyzing biological and artificial neural systems? The rise of ‘deep learning’ methods has shown that hard computational problems can be solved by machine learning algorithms that are built by cascading many nonlinear units. Although artificial neural systems are fully observable, it has proven challenging to provide a theoretical understanding of how they solve computational problems and which features of a neural network are critical for its performance. While such ‘deep networks’ differ from biological neural networks in many ways, they provide an interesting testing ground for evaluating strategies for understanding neural processing systems. Are there synergies between analysis methods for analyzing biological and artificial neural systems? Has the resurgence of deep learning resulted in new hypotheses or strategies for trying to understand biological neural networks? Confirmed Speakers: Matthias Bethge Mitya Chklovskii John Cunningham Surya Ganguli Neil Lawrence Guillermo Sapiro Tatyana Sharpee Richard Zemel Workshop Website: h <http://users.soe.ucsc.edu/%7Eafletcher/hdnips2013.html> ttps://users.soe.ucsc.edu/~afletcher/neuralsysnips.html <https://users.soe.ucsc.edu/%7Eafletcher/neuralsysnips.html> Email : smnips2015(a)rctn.org Submission details: Submissions should be in the NIPS_2015 format ( http://nips.cc/Conferences/2015/PaperInformation/StyleFiles) with a maximum of four pages, not including references. Submissions will be considered both for poster and oral presentation. Submit at https://cmt.research.microsoft.com/SMN2015/Protected/Author/ or via the link on the workshop website. Important dates: Submission deadline: 10 October, 2015 11:59 PM PDT (UTC -7 hours) Acceptance notification: 24 October, 2015

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Call for Participation: Bernstein Conference Satellite Workshop "In Vitro Neuronal Networks from 2D to 3D, " Sept. 14, 2015, Heidelberg, Germany
by Tanskanen Jarno Sept. 5, 2015

Sept. 5, 2015

Bernstein Conference Satellite Workshop no. 8 ** In Vitro Neuronal Networks from 2D to 3D ** September 14, 2015, 9:00 - 18:30 Ruprecht-Karls-Universität Heidelberg, Neue Universität Universitätsplatz, Grabengasse 3-5, 69117 Heidelberg, Germany More Information and Registration http://www.bernstein-conference.de/ The program and workshop abstract as a pdf: http://goo.gl/D1hwou Welcome! Jari Hyttinen and Jarno Tanskanen Computational Biophysics and Imaging Group Department of Electronics and Communications Engineering Tampere University of Technology, BioMediTech Finland --- P R O G R A M Welcome & Introduction to 3D in Vitro Technologies - Case: 3DNeuroN Jari Hyttinen, Tampere University of Technology * Session 1: 3D and Controlled Culturing of Neuronal Networks 3D Neural Networks in Engineered Hydrogel Matrices Nicolas Broguiere, Swiss Federal Institute of Technology Zurich Forming Neuron Networks with Controlled Topology in 2D and 3D Janos Vörös, Swiss Federal Institute of Technology Zurich * Session 2: Neuronal-astrocytic Networks and their Modeling Role of Astrocytes in Formation of Functional Neuronal Networks in Vitro Susanna Narkilahti, University of Tampere Computational Modeling of Neuronal-astrocytic Networks Kerstin Lenk, Tampere University of Technology * Session 3: Technology Signal Acquisition and Measurement System for Neural Networks in Vitro Peter Husar, Ilmenau University of Technology Technology and Material Developments for 3D Multielectrode Arrays Heike Bartsch, Ilmenau University of Technology Microbioreactor Designs with Integrated 3D MEA Devices for Cultivation of Neuronal Cells Andreas Schober, Ilmenau University of Technology * Session 4: Stimulation, Analysis, and 3D Network Modeling Investigation of Cultured Neuronal Networks and their Dynamics Induced by Novel Stimulation Paradigms Peter Husar, Fraunhofer IDMT Signal Analysis Methods for Neuronal Microelectrode Array Data Jarno Tanskanen, Tampere University of Technology Computational Modeling from 2D to 3D Networks Kerstin Lenk, Tampere University of Technology * Panel Discussion: From 2D to 3D * Closing of the Workshop Jari Hyttinen, Tampere University of Technology ****

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CFP: MLINI 2015 - 5th NIPS Workshop on Machine Learning and Interpretation in Neuroimaging: Beyond the Scanner
by Irina Rish Sept. 4, 2015

Sept. 4, 2015

Call for Papers MLINI 2015 - 5th NIPS Workshop on Machine Learning and Interpretation in Neuroimaging: Beyond the Scanner https://sites.google.com/site/mliniworkshop2015/ December 11-12, 2015, Montreal, Quebec, Canada Submission deadline: Monday, October 12th, 2015 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 two-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 12, 2014 - paper submission - October 26, 2014 - notification of acceptance/rejection - December 11-12, 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 (University of California, Berkeley)

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The ReScience journal
by Nicolas P. Rougier Sept. 4, 2015

Sept. 4, 2015

Following our "Long journey into reproducible computational neuroscience" (http://journal.frontiersin.org/article/10.3389/fncom.2015.00030/full) it's our great pleasure to announce the creation of "ReScience" which is a peer-reviewed journal that targets computational research and encourages the explicit replication of already published research, promoting new and open-source implementations in order to ensure that the original research is reproducible. To achieve such a goal, the whole editing chain is radically different from any other traditional scientific journal. ReScience lives on GitHub where each new implementation is made available together with comments, explanations and tests. Each submission takes the form of a pull request that is publicly reviewed and tested in order to guarantee that any researcher can re-use it. Students are strongly encourage to submit to ReScience. Even if the publishing model is a bit different from other academic journals, this will give them a first experience at peer-reviewed publishing where they have to use a rigorous and scientific approach. • More on the journal website: https://github.com/ReScience/ReScience/wiki • Current issue: https://github.com/ReScience/ReScience/wiki/Current-Issue • FAQ: https://github.com/ReScience/ReScience/wiki/Frequently-Asked-Questions • Follow us on twitter (@ReScienceEds): https://twitter.com/rescienceeds And if you're familiar with Git and GitHub, you can also become a reviewer: just contact us. Konrad Hinsen & Nicolas Rougier

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CFP: 1st International Workshop on Big Data Analytics for Healthcare and Well-being
by Youssef Iraqi Sept. 3, 2015

Sept. 3, 2015

Apologies if you receive multiple copies of this message. ________________________________________________________________ CALL FOR PAPERS 1st International Workshop on Big Data Analytics for Healthcare and Well-being 2016 January 18, 2016, Hong Kong, China http://kecidev.kaist.ac.kr/bigcomp2016/workshop/ In conjunction with the 3rd International Conference on Big Data and Smart Computing (BigComp) 2016 http://conf2016.bigcomputing.org/main/ Purpose and Scope Healthcare and well-being is an important area of research in many countries as one of the emerging application domains for both big data and smart computing. This workshop aims to create opportunities to share on-going works and enhance collaboration among healthcare researchers related to big data or data science, and to foster new innovations of big data and smart computing in the areas of mobile healthcare, smart homes, digital cities, innovations in healthcare and sensing devices, and other related areas. Prospective authors are cordially invited to submit their original contributions covering completed or ongoing work related to the area of big data analytics for healthcare and well-being. The topics include but are not limited to: - Smart health and big data - Data mining, graph mining and data science for healthcare - Big data analytics and social media for healthcare - Smart devices and hardware for healthcare - Smart location-based services for healthcare - Models and tools for smart computing in healthcare - Innovations in healthcare and sensing devices - Security and privacy for big data in healthcare - Cloud and grid computing for healthcare - Standards for big data in healthcare PAPER SUBMISSION Perspective authors are invited to submit their papers, up to 8 pages each, in the IEEE paper template. Papers must be formatted in PDF according to the IEEE two-column format for conference proceedings and submitted through EasyChair, http://www.easychair.org/. The direct link for paper submission is https://easychair.org/conferences/?conf=bigdata4healthcare IMPORTANT DATES Paper Submission Due: September 30, 2015 (23:59, HKT) Notification of Acceptance: November 15, 2015 Camera ready Papers: December 13, 2015 Workshop: January 18, 2016 ORGANIZATIONAL COMMITTEE Workshop Chairs: Youssef Iraqi, Dept. of Electrical & Computer Engineering, Khalifa University, UAE Ho-Jin Choi, School of Computing, KAIST, Korea Min Song, Dept. of Library & Information, Yonsei University, Korea TPC Members: Ae Ran Kim, College of Nursing, Seoul National University, Korea Amjad Gawanmeh, Dept. of Electrical & Computer Engineering, Khalifa University, UAE Byeong-Soo Jeong, Dept. of Computer Engineering, Kyung Hee University, Korea Changseok Bae, SW.Content Research Laboratory, ETRI, Korea Ahsan Khandoker, Department of Biomedical Engineering, Khalifa University, UAE Hani Saleh, Dept. of Electrical & Computer Engineering, Khalifa University, UAE Gwan-Su Yi, Dept. of Bio & Brain Engineering, KAIST, Korea Harish Bhaskar, Dept. of Electrical & Computer Engineering, Khalifa University, UAE Hyeoun-Ae Park, College of Nursing, Seoul National University, Korea Kyuchang Kang, SW.Content Research Laboratory, ETRI, Korea Tae-Min Song, Korea Institute for Health and Social Affairs, Korea Yong-Ik Yoon, Dept. of Multimedia Science, SookMyung Women’s University, Korea Yu-Chae Jung, Dept. of Multimedia Science, SookMyung Women’s University, Korea Nan Xiang, Dept. of Computer Science, Chongqing University of Technology, China Lingyun Zhu, Dept. of Internet of Things, Chongqing University of Technology, China Yong Wang, Dept. of Network Engineering, Chongqing University of Technology, China Dr. Youssef Iraqi Associate Professor Electrical and Computer Engineering Department [cid:logo.gif] PO Box 127788, Abu Dhabi, UAE T +971 (0)2 501 8323 F +971 (0)2 447 2441 Youssef.Iraqi(a)kustar.ac.ae [cid:twitter.jpg]<https://twitter.com/KhalifaUni> [cid:fb.jpg] <https://www.facebook.com/KhalifaUniversity> [cid:youtube.jpg] <http://www.youtube.com/user/KhalifaUniversity> [cid:instagram.jpg] <http://instagram.com/khalifauni> [cid:linkedin.jpg] <https://www.linkedin.com/company/khalifa-university-?trk=biz-companies-cym> [cid:slogan.png]

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Job posting: 5 PhD Positions in the Dutch Research Consortium 'Language in Interaction'
by Lorenz, C.M. Sept. 3, 2015

Sept. 3, 2015

Job posting: 5 PhD Positions in the Dutch Research Consortium 'Language in Interaction' We are looking for highly motivated PhD candidates to enrich a unique consortium of researchers that aims to unravel the neurocognitive mechanisms of language at multiple levels. The goal is to understand both the universality and the variability of the human language faculty from genes to behaviour. The Netherlands has an outstanding track record in the language sciences. This research consortium sponsored by a large grant from the Netherlands Organization for Scientific research (NWO) brings together many of the excellent research groups in the Netherlands with a research programme on the foundations of language. The research team consists of 43 Principal Investigators. In addition to the excellence in the domain of language and related relevant fields of cognition, our consortium provides state-of-the-art research facilities and a research team with ample experience in the complex research methods that will be invoked to address the scientific questions at the highest level of methodological sophistication. These include methods from genetics, neuroimaging, computational modelling, and patient-related research. This consortium realizes both quality and critical mass for studying human language at a scale not easily found anywhere else. Currently, the consortium advertises five PhD positions for a period of 4 years. These positions provide the opportunity for conducting world-class research as a member of an interdisciplinary team. Maximum salary: €2,717 gross/month Closing date for application: 04 October 2015, 23:59 CET For more information on the PhD positions and how to apply: https://www.languageininteraction.nl/ThirdCallGeneral.html <https://www.languageininteraction.nl/ThirdCallGeneral.html>

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SAC2016 - NeuroComputing Track - Paper submission DEADLINE EXTEDED
by Falotico Egidio Sept. 2, 2015

Sept. 2, 2015

Dear Community, The paper submission deadline of SAC2016 conference has been extended to September 21. Please consider to submit a contribution to the NeuroComputing track. ============================== NeuroComputing Track - Call For Papers ============================== The NeuroComputing Track has been proposed as a track of the Symposium on applied Computing (SAC2016) that will be held in Pisa from 4 to 8 April 2016. The ACM Symposium on Applied Computing (SAC) has been a primary gathering forum for applied computer scientists, computer engineers, software engineers, and application developers from around the world. SAC 2016 is sponsored by the ACM Special Interest Group on Applied Computing (SIGAPP). ============================== TRACK AIM The development of computation models of the nervous system and neural processes has risen at a rapid pace. Developing neuro-inspired computing paradigms that mimic nervous system function fosters our model understanding of the biological system and targets technical applications in artificial systems. Today, combined efforts in the fields of the neuroscience and computer science in interdisciplinary research projects like the Human Brain Project enable the simulation of spiking biological neural networks with millions of neurons. In order to deal with the complexity and scaling of such networks a new generation of appropriate tool is needed to simulate the neural network in real-time. Neuromorphic hardware and supercomputers are the ideal candidates on the hardware side, and on the software side tools should ease the development and support the researcher during the evaluation by offering a toolchain for the implementation and simulation. The aim of the ACM Symposium on Applied Computing (SAC) Track on NeuroComputing is to gather innovative works related to the application of computational techniques for the brain simulation, as well as the system software, middleware, interactive computational steering and visualization support necessary to create and simulate multi-scale brain models and to address the hard-scaling challenges of whole brain modelling. ============================== TRACK WEBSITE http://sssa.bioroboticsinstitute.it/tracks/sac2016 ============================== TOPICS OF INTEREST - Neuromorphic hardware - Large scale simulation of NN - Brain visualization tools - Neuro imaging software - Spiking neural networks - Bio-inspired learning mechanisms - Software applications for real-time neural network simulation - Software applications for real-time brain-body simulation - High performance computing for neural simulation - Neural simulators ============================== IMPORTANT DATES September 21, 2015 : Paper submission extended November 13, 2015 : Acceptance notification December 11, 2015 : Camera-ready submission ============================== TRACK CHAIRS Cecilia Laschi, The BioRobotics Institut,e Scuola Superiore SantAnna Pisa, Italy Egidio Falotico, The BioRobotics Institute, Scuola Superiore SantAnna Pisa, Italy Florian Röhrbein, Technical University of Munich, Munich, Germany Marc-Oliver Gewaltig, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland Paul Levi, Research Center for Information Technology,Karlsruhe, Germany Stefan Ulbrich Research Center for Information Technology,Karlsruhe, Germany -- Egidio Falotico Computer Scientist PhD in BioRobotics PhD in Cognitive Science The BioRobotics Institute Polo Sant'Anna Valdera - Scuola Superiore Sant'Anna Viale Rinaldo Piaggio, 34 - 56025 - Pontedera (PI) - Italy Phone: +39 050 883 457 e-mail: e.falotico(a)sssup.it

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Call for abstracts: Bounded optimality and rational metareasoning workshop @ NIPS
by Sam Gershman Sept. 2, 2015

Sept. 2, 2015

We are pleased to announce a NIPS workshop on bounded optimality and rational metareasoning, which will take place in Montreal, Canada on December 11, 2015. This workshop brings together computer scientists working on bounded optimality and metareasoning with psychologists and neuroscientists reverse-engineering the computational principles that make the human brain incredibly resource-efficient. The goal of this workshop is to synthesize these different perspectives on bounded optimality, to promote interdisciplinary interactions and cross-fertilization, and to identify directions for future research. We invite abstract submissions, due October 28: https://sites.google.com/site/boundedoptimalityworkshop/call-for-abstracts Tentative schedule: https://sites.google.com/site/boundedoptimalityworkshop/home Sam Gershman Assistant Professor Department of Psychology and Center for Brain Science Harvard University http://gershmanlab.webfactional.com/index.html

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COSYNE 2016: Call for workshop proposals
by Tomas Hromadka Sept. 2, 2015

Sept. 2, 2015

==================================================== Computational and Systems Neuroscience 2016 (Cosyne) MAIN MEETING Feb 25 - Feb 28, 2016 Salt Lake City, Utah WORKSHOPS Feb 29 - Mar 1, 2016 Snowbird Ski Resort, Utah www.cosyne.org ==================================================== ----------------------------------------------------------------------- CALL FOR WORKSHOP PROPOSALS ----------------------------------------------------------------------- PROPOSAL DEADLINE: 31 October, 2015. PRE-PROPOSALS: In an effort to coordinate submissions, the organizers are encouraged to submit a pre-proposal by October 1st, 2015. Pre-proposals will be shared among submitters. Pre-proposals are requested but not required. The organizers may submit the full proposal by its deadline. A series of workshops will be held after the main Cosyne meeting (www.cosyne.org) The goal is to provide an informal forum for the discussion of important research questions and challenges. Controversial issues, open problems, comparisons of competing approaches, and alternative viewpoints are encouraged. The overarching goal of all workshops should be the integration of empirical and theoretical approaches, in an environment that fosters collegial discussion and debate. Preference will be given to proposals that differ substantially in content, scope, and/or approach from workshops of recent years (examples available at http://www.cosyne.org/c/index.php?title=Workshops) Relevant topics include, but are not limited to: sensory processing; motor planning and control; functional neural circuits; motivation, reward and decision making; learning and memory; adaptation and plasticity; neural coding; neural circuitry and network models; and methods in computational or systems neuroscience. Please note that in an effort to reduce the overlap between workshops, speakers are strongly discouraged from presenting talks at more than one workshop. WORKSHOP DETAILS: - There will be 4-8 workshops/day, running in parallel. - Each workshop is expected to draw between 15 and 80 people. - The workshops will be split into morning (8:00-11:00 AM) and afternoon (4:30-7:30 PM) sessions. - Workshops will be held at Snowbird, a ski resort located 30 miles (typically less than an hour) from the Salt Lake City airport. Buses from the main conference will be provided. SUBMISSION INSTRUCTIONS: Deadline for pre-proposals: 01 October, 2015 Deadline for proposals: 31 October, 2015 Format: plain text only -- please no attachments email to: cosyne16workshops(a)gmail.com (Claudia Clopath, Alfonso Renart) PRE-PROPOSALS should include: - Name(s) and email address(es) of the organizers (no more than 2 organizers per session, please). A primary contact should be designated. - A title. - A brief description of 1) what the workshop will address and accomplish, 2) why the topic is of interest, 3) who is the targeted group of participants. - Names of potential invitees, with indication of confirmed speakers. Preference will be given to workshops with the most confirmed speakers. - Proposed workshop length (1 or 2 days). Most workshops will be limited to a single day. If you think your workshop needs 2 days, please explain why. - A brief resume of the workshop organizer along with a short list of workshop-relevant publications (about half a page total). PROPOSALS should include the list of confirmed speakers in addition to components required for a pre-proposal. Workshop organizer responsibilities include coordinating workshop participation and content, scheduling all speakers and submitting a final schedule for the workshop program, and moderating the discussion. Organizers can be speakers but need not speak depending on scheduling constraints. SUGGESTIONS: Experience has shown that the best discussions during a workshop are those that arise spontaneously. A good way to foster these is to have short talks and long question periods (e.g. 30+15 minutes), and have plenty of breaks. We recommend fewer than 10 talks. WORKSHOP COSTS: Detailed registration costs, etc, will be available at www.cosyne.org. Please note: Cosyne does NOT provide travel funding for workshop speakers. All workshop speakers are expected to pay for workshop registration fees. Participants are encouraged to register early, in order to qualify for discounted registration rates. One complementary (free) organizer registration is provided per workshop. For workshops with 2 organizers, the free registration can be given to one of the organizers or split evenly between them. COSYNE 2016 WORKSHOP CHAIRS: Claudia Clopath (Imperial College London) and Alfonso Renart (Champalimaud Center Lisbon). QUESTIONS: email: cosyne16workshops(a)gmail.com

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Postdoc
by Pestilli, Franco Sept. 1, 2015

Sept. 1, 2015

Dear Community, We are looking for a talented individual to work on a large-scale neuroimaging project funded by the Indiana CTSI<https://www.indianactsi.org/>. The project aims at applying cutting-edge neuroimaging and connectomics methods (Pestilli et al., Nature Methods 2014<http://www.nature.com/nmeth/journal/v11/n10/abs/nmeth.3098.html>; Mišić et al., Neuron 2015<http://www.cell.com/neuron/abstract/S0896-6273(15)00474-2>) on the latest generation of data from Indiana Alzheimer Disease Center<http://iadc.medicine.iu.edu/>. The project is a collaboration between groups at Indiana <https://www.indiana.edu/> University Bloomington<https://www.indiana.edu/> (Franco Pestilli and Olaf Sporns), Indiana University School of Medicine, Indianapolis (Andrew Saykin, Li Shen, and Yu-Chien, Wu) and Purdue University, Lafayette (Joaquin Goñi). The team has strong expertise in aging and Alzheimer’s disease, imaging genetics, network science, magnetic resonance imaging measurements and computational modeling. The ideal candidate will have a PhD in Computer Science, Engineering, Neuroscience, Informatics or Cognitive Science. Strong programming skills (e.g., in Python, MATLAB, or C/C++) and previous background in neuroimaging, computational modeling, or machine learning will be highly valued. The project will involve developing and publishing software products as well as contributing to ongoing software projects such as: https://francopestilli.github.io/life and https://sites.google.com/site/bctnet/. Preference will be given to candidates demonstrating successful productivity by means of scientific articles and software publishing. Interested candidates should send CV, statement of research interests, and names of three references to Dr. Franco Pestilli franpest(a)indiana.edu<mailto:franpest@indiana.edu>. Review of the applications will start immediately and continue until the position is filled. Dr. Pestilli and Professor Sporns will be available at SfN in Chicago for informal meetings with potential candidates. Indiana University is an equal 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, national origin, disability status or protected veteran status. Best regards, Franco Franco Pestilli, PhD Assistant Professor Psychology<http://psych.indiana.edu/>, Neuroscience<http://www.indiana.edu/~neurosci/> and Cognitive Science<http://www.cogs.indiana.edu/> Indiana Network Science Institute<http://iuni.iu.edu/> 𝞇 Indiana University, Bloomington<http://www.iub.edu/>, IN 47405<http://goo.gl/0uVOc8> francopestilli.com<http://www.francopestilli.com/> | franpest(a)indiana.edu<mailto:franpest@indiana.edu> Phone: +1 (812) 856 9967

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open positions in machine learning and computational neuroscience
by Turaga, Srinivas C Sept. 1, 2015

Sept. 1, 2015

The Turaga Lab is looking for exceptional postdoctoral researchers and programmers (and graduate students!) for research at the intersection of machine learning and neuroscience. https://www.janelia.org/lab/turaga-lab With recent technological advances in 3d electron microscopy, optogenetics and large-scale chronic in vivo neural imaging, it is now possible to measure and perturb the activity of large populations of neurons, and to map their connectivity. These new data can be used understand how the structure of a neural circuit gives rise to its function. Our lab develops machine learning algorithms to map neural connectivity, and statistical models to characterize neural activity and to relate activity to connectivity. We have pioneered the use of deep-learning based machine learning algorithms to map neural connectivity from 3d electron microscopic images of brain tissue, and we are now working to improve these methods. This involves solving interesting new problems in structured prediction, active learning and unsupervised learning at an unprecedented scale (imagine working with labeled training datasets with 10^9 examples in a 10^6 dimensional feature space and wanting to achieve accuracies of 99.999%!). We are also developing novel statistical methods to analyze large-scale calcium imaging datasets. This is with an eye towards combining such large-scale activity measurements with structural connectomes in order to relate neural activity to neural connectivity with statistical and mechanistic models. HHMI's Janelia Research Campus is a unique, world-class research community near Washington, D.C. dedicated to understanding the function of neural circuits and developing synergistic imaging technology. Our highly collaborative structure is designed to support interdisciplinary work in small lab groups. We seek candidates who are comfortable with risk and are able to think independently to develop novel approaches. Applicants should have a strong quantitative background with degrees or expertise in machine learning, computational neuroscience, applied mathematics, physics or related discipline. Excellent collaborative programming skills in Python, C/C++, Java or similar languages are essential. To apply, please send a CV and names and addresses of 2-3 references by email to Dr. Srini Turaga, turagas(a)janelia.hhmi.org.

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SFN 2015 Workshop: high performance computing via Neuroscience Gateway
by Ted Carnevale Sept. 1, 2015

Sept. 1, 2015

What: Workshop on the Neuroscience Gateway Portal (NSG, http://www.nsgportal.org) When: 9AM - Noon on Saturday, October 17, 2015. Registration deadline: Friday, October 2, 2015. Where: Downtown Chicago (exact location announced to registrants) Speakers: Amit Majumdar, Subha Sivagnanam, Padraig Gleeson, Simon Rothmeier, Ted Carnevale, Alex Peyser, Hannah Bos. Agenda: Downloadable from http://www.nsgportal.org/workshop.html Why: If you have, or plan to start, a research project that involves computationally intensive modeling or data analysis, you should know about NSG. NSG is being developed with support from NSF to make it easy for neuroscientists to use high performance computing (HPC) resources in their research. Some of NSG's advantages: * Quick and easy account application and approval. * Free computing time. No cost to your account budget! * Simple user interface for uploading data, running simulations or data analysis tasks, and downloading results * Installed software includes MOOSE, GENESIS 3, NEST, NEURON, PyNN, the Freesurfer Software Suite, and the Virtual Brain Empirical Data Pipeline For more information or to sign up, see http://www.neuron.yale.edu/neuron/static/courses/nsg2015/nsg2015.html or contact Ted Carnevale [ted dot carnevale at yale dot edu] or Amit Majumdar [majumdar at sdsc dot edu]

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Postdoctoral position in Pattern Recognition, Machine Learning and Computer Vision for the analysis of retinal electrophysiology in response to visual stimulation, with specific expertise in deep learning and sparse learning BC: 71326 - 71327
by Diego Sona Aug. 31, 2015

Aug. 31, 2015

Postdoctoral position in Pattern Recognition, Machine Learning and Computer Vision for the analysis of retinal electrophysiology in response to visual stimulation, with specific expertise in deep learning and sparse learning BC: 71326 - 71327 Fondazione Istituto Italiano di Tecnologia – IIT – was established by the Italian government to promote technological development and training in the scientific and technological field. Toward this end, IIT is implementing a detailed scientific program, which comprises integration across fundamental research and application. IIT’s research endeavour focuses on high-tech and innovation, representing the forefront of technology with possible application from medicine to industry, computer science, robotics, life sciences and nano-biotechnologies. One postdoctoral position in Computer Vision, Pattern Recognition and Machine Learning is available in the department of Pattern Analysis and Computer Vision (PAVIS) at the Istituto Italiano di Tecnologia (IIT) ,Genova, Italy. PAVIS department has consolidated expertise in image processing, computer vision, pattern recognition and machine learning and aims at studying and designing intelligent systems for the analysis and understanding of real-world problems. PAVIS focuses in particular on activities related, but not limited, to surveillance and security, biomedical imaging, and bioinformatics. Project Description The research position is funded by the European project “RENVISION - Retina-inspired ENcoding for advanced VISION tasks” (http://www.renvision-fp7.eu/ <http://www.renvision-fp7.eu/>). The overall aim of the project is to achieve a comprehensive understanding of how the retina encodes complex visual scenes, and to use such insights to develop new computational models of retina and toapply them to high-level computer vision tasks, such as scene categorization and action recognition. The project is highly interdisciplinary, including neuro-engineering, electrophysiology, high-resolution microscopy imaging, computational modelling, data analysis, machine learning and computer vision. RENVISION is funded by the European Commission FP7 Future Emerging Technologies programme, under contract n. 600847. Description of the research The candidate will design novel methodologies and algorithms based on pattern recognition and machine learning techniques, aiming at analysing electrophysiological recordings in response to visual stimulation of retina. The main objective of the research is the discovery/determination of representative and/or discriminative features in retina coding allowing for high-level vision tasks, such as scene categorization and action recognition. To this purpose, deep learning, sparse and dictionary learning approaches are to be considered. Experience and Qualifications We are seeking a self-motivated individual with the ability to take day-to-day responsibility for the progress of the proposed work. The ideal candidate will have a PhD in Computer Science, Mathematics, Electronic Engineering or a closely-related discipline, with competences on machine learning/pattern recognition/computer vision, coupled with a keen interest in neuroscience and biological data processing and analysis. Expertise in deep learning, compressive sensing, and/or dictionary learning is in general preferred. Experience in spiking networks or retinal function will be appreciated while not being a discriminating factor. A strong programming skill is required. Annual salary will depend on research experience and qualification. Closing Date The initial deadline for applications is September 7th , 2015, however please note that the search will continue until appropriate candidates have been identified. How to apply Completed application forms along with a curriculum listing all publications (possibly including pdfs of the most representative ones), names of 2 referees and a research statement (describing previous research experience and outlining its relevance to the above topics) should be sent by email to Prof. Vittorio Murino vittorio.murino(a)iit.it <mailto:vittorio.murino@iit.it> and/or Diego Sona diego.sona(a)iit.it <mailto:diego.sona@iit.it>, quoting PAVIS-PD 71327 – 71326 as reference number. For informal enquiries please write to Prof. Vittorio Murino vittorio.murino(a)iit.it <mailto:vittorio.murino@iit.it> or Diego Sona diego.sona(a)iit.it <mailto:diego.sona@iit.it>. In order to comply with Italian law (art. 23 of Privacy Law of the Italian Legislative Decree n. 196/03), the candidate is kindly asked to give his/her consent to allow Istituto Italiano di Tecnologia to process his/her personal data. We inform you that the information you provide will be solely used for the purpose of evaluating and selecting candidates in order to meet the requirements of Istituto Italiano di Tecnologia. Your data will be processed by Istituto Italiano di Tecnologia, with its headquarters in Genoa, Via Morego 30, acting as the Data Holder, using computer and paper-based means, observing the rules on the protection of personal data, including those relating to the security of data, and they will not be communicated to thirds. Please also note that, pursuant to art.7 of Legislative Decree 196/2003, you may exercise your rights at any time as a party concerned by contacting the Data Holder. Istituto Italiano di Tecnologia is an Equal Opportunity Employer that actively seeks diversity in its workforce Diego Sona --------------------------------------------------------- Pattern Analysis & Computer Vision (PAVIS) Istituto Italiano di Tecnologia (IIT) Via Morego 30, 16163, Genova, Italy Phone: +39 010 71781 819 E-mail: diego.sona(a)iit.it www.iit.it/pavis.html ---------------------------------------------------------

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