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Postdoctoral fellowship in statistical neuroscience at Boston University

by Mark Kramer

Postdoctoral fellowship in statistical neuroscience at Boston University A postdoctoral position is available for working in an NIH-funded BRAIN initiative project focused on understanding the computational principles and neural circuit mechanisms that underlie complex interactions across distributed circuits during brain function. The candidate will be responsible for developing data analysis and statistical modeling methods to characterize simultaneous LFP and spike train recordings from multiple brain regions during decision-making tasks. The successful candidate will have a strong background in statistics and computer programming; experience in interdisciplinary neuroscience research is preferred, although not essential. The position is based at Boston University in the labs of Uri Eden and Mark Kramer. The project is highly interdisciplinary and will involve frequent and extensive interactions with experimentalists at UCSF (Loren Frank) and Cold Spring Harbor (Adam Kepecs). Please contact Uri Eden or Mark Kramer (see links below) for more information. Boston University offers a vibrant community of statistical, mathematical, and neuroscience faculty and students, and many opportunities for collaboration within and outside the University. http://math.bu.edu/people/tzvi/ http://math.bu.edu/people/mak/

Dec. 20, 2015

[INNS-BigData 2016] Updated Call for Papers

by Teng Teck Hou

[Apologies for cross-postings] ########################################################### CALL FOR PAPERS The 2nd INNS Conference on Big Data 2016 October 23-25, 2016, Thessaloniki, Greece http://conferences.cwa.gr/inns-big-data2016/ ########################################################### Big data is not just about storage of and access to data. Analytics play a big role in making sense of that data and exploiting its value. But learning from big data has become a significant challenge and requires development of new types of algorithms. Most machine learning algorithms can't easily scale up to big data. Plus there are challenges of high-dimensionality, velocity and variety. The neural network field has historically focused on algorithms that learn in an online, incremental mode without requiring in-memory access to huge amounts of data. This type of learning is not only ideal for streaming data (as in the Industrial Internet or the Internet of Things), but could also be used on stored big data. Neural network technologies thus can become significant components of big data analytics platforms and this inaugural INNS Conference on Big Data will begin that collaborative adventure with big data and other learning technologies. Thus the aim of this conference is to promote new advances and research directions in efficient and innovative algorithmic approaches to analyzing big data (e.g. deep networks, nature-inspired and brain-inspired algorithms), implementations on different computing platforms (e.g. neuromorphic, GPUs, clouds, clusters) and applications of Big Data Analytics to solve real-world problems (e.g. weather prediction, transportation, energy management). #################### Important dates ##################### - Tutorial and workshops proposals: February 15th, 2016 - Notification of tutorial and workshops proposals: February 20th, 2016 - Paper submission: April 30th, 2016 - Notification of paper acceptance: May 30th, 2016 - Camera-ready submission (AISC): June 11th, 2016 - Early registration: June 20th, 2016 Registration deadline: papers without confirmed registration by June 24th 2016 risk their inclusion in the proceedings ########################################################## #################### Invited speakers #################### - Francesco Bonchi, ISI Foundation, Torino, Italy - Stephen Furber, University of Manchester, UK - Rudolf Kruse, OVG University of Magdeburg, Germany - Piotr Mirowski, Google Deep Mind, London, UK ########################################################## #################### Organizing committees ############### General Chairs - Plamen Angelov, Lancaster University, UK - Yannis Manolopoulos, Aristotle University of Thessaloniki, Greece Program Chairs - Lazaros Iliadis, Democritus University of Thrace, Greece - Asim Roy, Arizona State University, Tempe USA - Marley Vellasco, PUC-Rio, Rio de Janeiro, Brazil Advisory Board - Nikola Kasabov, Auckland University of Technology, New Zealand - Ali Minai, University of Cincinnati, USA - Danil Prokhorov, Toyota Tech Center, Michigan, USA - Theodore Trafalis University of Oklahoma, USA - G. Kumar Venayagamoorthy, Clemson University, USA Tutorials/Workshop Chairs - Apostolos Papadopoulos, Aristotle University of Thessaloniki, Greece - Bernardete Ribeiro, Portugal Poster Session Chairs - Yi Lu Murphey, University of Michigan-Dearborn, USA Special Sessions Chairs - Irwin King, Chinese University of Hong Kong, China - Luca Oneto, University of Genoa, Italy Panel Chairs - Leonid Perlovsky, Harvard University, Boston, USA Awards Chair - Araceli Sanchis de Miguel, Carlos III University, Spain Competitions Chairs - Adel Alimi, University of Sfax, Tunisia Publication Chairs - Mariette Awad, American University of Beirut, Lebanon - Danilo Mandic, Imperial College, London, UK Publicity Chairs - Jose Antonio Iglesias Martinez, Carlos III University of Madrid, Spain - Simone Scardapane, The Sapienza University of Rome, Italy - Teck Hou Teng, Singapore Management University, Singapore International Liaison Chairs - Petia Georgieva, University of Aveiro, Portugal - De-Shuang Huang, Tongji University, Shanghai, China Local Organizing Committee: - Anastasios Gounaris, Aristotle University of Thessaloniki, Greece WebMaster - Yannis Karydis, Ionian University, Greece ########################################################## ############# Paper Submission and Publication ########### * Original works submitted as a regular paper limited to a maximum of 14 pages in Springer format will be published in the proceedings to be available electronically as a Springer book in ADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING Series, to download for delegates. * It will be peer-reviewed by at least three PC members on the basis of technical quality, relevance, originality, significance and clarity. * At least one author of an accepted submission to the conference should register with a regular fee to present their work at the conference. ########################################################## #################### Awards ############################## * Best papers will be selected and awarded as follows: - Best regular paper - Best student paper * This will be based on a combination of reviewers' comments, presentations and importance and quality judged by a panel. * Best paper awards (500 Euros) are donated by the sponsor Springer Verlag, Germany and will be commemorated by a certificate. ########################################################## ###### Topics and Areas include, but not limited to ###### * Autonomous, online, incremental learning - theory, algorithms and applications in big data * High dimensional data, feature selection, feature transformation - theory, algorithms and applications for big data * Scalable algorithms for big data * Learning algorithms for high-velocity streaming data * Big data streams analytics * Deep neural network learning * Machine vision and big data * Brain-machine interfaces and big data * Cognitive modeling and big data * Embodied robotics and big data * Fuzzy systems and big data * Evolutionary systems and big data * Evolving systems for big data analytics * Neuromorphic hardware for scalable machine learning * Parallel and distributed computing for big data analytics (cloud, map-reduce, etc.) * Big data and collective intelligence/collaborative learning * Big data and hybrid systems * Big data and self-aware systems * Big Data and infrastructure * Big data analytics and healthcare/medical applications * Big data analytics and energy systems/smart grids * Big data analytics and transportation systems * Big data analytics in large sensor networks * Big data and machine learning in computational biology, bioinformatics * Recommendation systems/collaborative filtering for big data * Big data visualization * Online multimedia/ stream/ text analytics * Link and graph mining * Big data and cloud computing, large scale stream processing on the cloud ########################################################## #################### Co-Sponsors ######################### * International Neural Network Society (INNS) * Springer ##########################################################

Dec. 20, 2015

CFP: VECPAR 2016 - High Performance Computing for Computational Science

by Carlos Ferreira

------------------------------------------------------------------------------------------ CALL FOR PAPERS 12th International Meeting on High-Performance Computing for Computational Science (VECPAR 2016) University of Porto, Porto, Portugal June 27 - 30, 2016 http://vecpar.fe.up.pt/2016/ ------------------------------------------------------------------------------------------- IMPORTANT DATES: Deadline for submission: January 15th, 2016 notification of acceptance: March 3rd, 2016 camera ready version: April 25th, 2016, on easychair.org. The International Meeting on High Performance Computing for Computational Science (VECPAR) is the premier venue for presenting and discussing the latest research and practice in high end computer modeling and complex systems. VECPAR encourages submission of research contributions from academia, research laboratories and industry to address pressing issues in computational science resulting from applications of interest to society and hardware innovations. VECPAR'16, the 12th edition of the VECPAR series of conferences is organized by the University of Porto, Portugal, and will be held at the Department of Computer Science, School of Sciences. An award is planned for best student papers. Contributions are solicited in all areas of computational science and engineering (CS&E), including (but not limited to) the following topics: * Large scale Simulations in CS&E * Parallel and Distributed Computing * Parallel Algorithms * Numerical Algorithms on Multicore, GPUs and Emerging Architectures * Symbolic algorithms on Multicore, GPUs and Emerging Architectures * Support Tools and Environments * Scheduling and Load Balancing * Performance Analysis, Evaluation and Tuning You should make your submissions through EasyChair at: https://www.easychair.org/conferences/?conf=vecpar2016 Submitted papers must be formatted according to the rules of the Springer Series Lecture Notes in Computer Science (LNCS): http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0 Please note that papers (for conference presentation) must not exceed 8 pages in length, using the LNCS format. Accepted papers will be distributed in electronic format to participants of VECPAR'16. Printed versions of the invited talks and a set of selected papers will be published by Springer in the series entitled Lecture Notes in Computer Science. Selected papers will be limited to 14 pages and will be judged based on relevance, significance, originality, correctness and clarity. More information about this process will be sent to interested authors after the conference. Carlos Ferreira [http://www2.isep.ipp.pt/assinatura_email/EMAIL_ISEP.png] ISEP | Instituto Superior de Engenharia do Porto Rua Dr. António Bernardino de Almeida, 431 4249-015 Porto - PORTUGAL tel. +351 228 340 500 | fax +351 228 321 159 mail(a)isep.ipp.pt | www.isep.ipp.pt<http://www.isep.ipp.pt>

Dec. 18, 2015

[Call for applications] *Graduate Programs in Computational Neuroscience* in Berlin; MSc and PhD; 6 PhD scholarships; deadline March 15, 2016

by Robert Martin

[Apologies for cross-posting] *Doctoral* and *Master Program* "Computational Neuroscience" at the Bernstein Center for Computational Neuroscience Berlin in Berlin, Germany Application deadline: *March 15, 2016* Begin of courses: October 2016 Internet: www.computational-neuroscience-berlin.de _Doctoral Program_ The Bernstein Center for Computational Neuroscience Berlin and the TU Berlin invite applications for *6 fellowships* of the Research Training Group "Sensory Computation in Neural Systems" (GRK 1589/2, https://www.eecs.tu-berlin.de/grk_15891/) The *scientific program* of the research training group combines techniques and concepts from machine learning, computational neuroscience, and systems neurobiology in order to specifically address sensory computation. Doctoral candidates will work on interdisciplinary projects investigating the mechanisms of neural computation, address the processes underlying perception on different scales and different levels of abstraction, and develop new theories of computation hand in hand with well-controlled experiments in order to put functional hypotheses to the test. The training group offers structured supervision complemented by a teaching and training program. Each student will be supervised by two investigators with complementary expertise and will be associated with the Bernstein Center for Computational Neuroscience Berlin (https://www.bccn-berlin.de/) a leading research center dedicated to the theoretical study of neural processing. Candidates are expected to hold a Masters degree (or equivalent) in a relevant subject (e.g., neuroscience, cognitive science, computer science, physics, mathematics, etc.) and have the required advanced mathematical background. Candidates selected in the first application step will be invited for lab visits and an interview, expected to take place in June 2015. The *fellowships of 1468 €/month* - with additional children allowances if applicable---will be granted for up to three years. _Master's Program_ The tuition-free Master program in Computational Neuroscience offers *15 places* per year, has a duration of 2 years and is fully taught in English. The *curriculum* is subdivided into ten modules, whose content includes theoretical neuroscience, programming, machine learning, cognitive neuroscience, acquisition, modelling, and computational analysis of neural data, with a strong focus on a complementary theoretical and experimental training. Three lab rotations and a Master's thesis are accomplished in the second year. The aim of the program is to provide the students with an interdisciplinary education and an early contact to the neurocomputational research environment. *Requirements* BSc or equivalent degree in a relevant subject (typically in the natural sciences, in an engineering discipline, in cognitive science, or in mathematics), certificate of English proficiency, proof of sufficient mathematical knowledge (at least 24 ECTS credit points). ~~~ _For more information_ ... ... come and visit us on our *information day* on January 27, 2016, at 3 PM (sharp) at the BCCN Berlin: https://www.bccn-berlin.de/Calendar/Events/event/?contentId=3822 ... or browse: www.computational-neuroscience-berlin.de ... or e-mail: graduateprograms(a)bccn-berlin.de . Best regards, Robert Martin -- Robert Martin, PhD Teaching Coordinator Bernstein Center for Computational Neuroscience Humboldt-Universitaet zu Berlin Philippstr. 13 House 6; 10115 Berlin; Germany Phone/Fax +49 (0)30 2093 6773/6771 http://www.computational-neuroscience-berlin.de GRK 1589/1, Sensory Computation in Neural Systems Technische Universitaet Berlin Sekretariat MAR 5-6; Marchstr. 23; 10587 Berlin Phone/Fax +49 (0)30 314 72006/73121 http://www.eecs.tu-berlin.de/grk_15891/

Dec. 18, 2015

CFP on "Computationally Intelligent Methods in Neural Information Processing" at the IEEE WCCI2016.

by Mufti Mahmud

Sorry for cross-posting. Please consider circulating and contributing to the session. Thanks and regards, Mufti *Call for Paper for Special Session on * *Computationally Intelligent Methods in Neural Information Processing* *at the IEEE World Congress on Computational Intelligence (IEEE WCCI) 2016* Organized by: Mufti Mahmud 1-4, €, Amir Hussain 4, 5, £ 1*NeuroChip Lab, University of Padova, 35131 – Padova, Italy, *2*Institute of Information Technology, Jahangirnagar University, 1342 – Dhaka, Bangladesh, *3*Theoretical Neurobiology & Neuroengineering Lab, University of Antwerp, 2610 – Wilrijk, Belgium, *4*COSIPRA Lab, University of Stirling, FK9 4LA – Stirling, UK, *5*Anhui University, Hefei, Anhui, 230601 - China* €*Email: muftimahmud(a)gmail.com <muftimahmud(a)gmail.com>, *£*Email: ahu(a)cs.stir.ac.uk <ahu(a)cs.stir.ac.uk>* *Introduction:* The brain, being the most complex organ in human body, is specialized to process information simultaneously coming from many different sources. The neurons work as basic information processing units in the brain and interconnect to each other to form hierarchical and/or parallel pathways. These pathways are mainly involved in transforming information originated from one or more sources into either action (as in motor movements) or specialized information understood by the brain itself (as in cognitive functions). To have a detailed and better understanding of these biological phenomena two approaches have been practiced by the research community – experimental and theoretical studies. Also, some theoretical studies are inspired by the nature itself which reframes earlier computational techniques to suggest research on biophysical basis of brain research and its information processing capabilities. Needless to say that most of these studies are results of interdisciplinary research involving medical sciences, life sciences, physical sciences, engineering, and cognitive sciences. *Scope:* The focus of this special session is to address the recent advances in computationally intelligent techniques in processing neural information. Developing intelligent methods capable of deciphering brain’s information processing capability is one the biggest challenges in brain research. The objective of this special session is to provide updated information and a forum for the scientists and researchers who are looking for more relevant information in decoding brain functions using expert and computationally intelligent systems. This special session is expected to attract papers on recent research progress in the area of intelligent methods in processing neural signals. The targeted research topics are, but not limited to, the following: Ø Computationally intelligent tools for analysis of Spikes, LFP, EEG, MEG, MRI/fMRI, PET, and fNIRS; Ø Computationally intelligent methods for modeling and estimating neural signals; Ø Computational intelligence in developing smart BMI and neural prosthesis; Ø Biologically inspired methods for pattern analysis in neuronal signals; Ø Machine learning methods applied to brain research; *Submission of papers:* Submit IEEE US Letter complaint pdf papers to IEEE CEC 2016, following the steps below: Ø Visit http://ieee-cis.org/conferences/cec2016/upload.php Ø Provide paper details (i.e., Paper Title, Author(s), PDF file to upload, Abstract, Preferred form of presentation, Main paper focus) Ø At '*Main research topic*' or '*Additional research topics'*, select '*8bc. Computationally Intelligent Methods in Neural Information Processing*' from the dropdown list. *Important dates:* Ø Paper submission deadline: *15 January 2016* Ø Decision notification: *15 March 2016* Ø Final paper submission and early registration deadline: *15 April 2016* Ø Conference dates: *25-29 July 2016*. -- Mufti Mahmud, PhD Postdoctoral Research Fellow NeuroChip Lab <http://www.vassanellilab.eu/> - Dept. of Biomedical Sciences <http://www.biomed.unipd.it/?L=1> University of Padova Via f. Marzolo 3 35131 - Padova, Italy Lab: +39 049 827 5308 Fax: +39 049 827 5301 https://sites.google.com/site/muftimahmud/ & Assistant Professor (on leave) Institute of Information Technology Jahangirnagar University Savar, 1342 - Dhaka, Bangladesh

Dec. 17, 2015

Fwd: EANN 2016 CFP Scotland

by Chrisina Jayne

Dear Colleague, The 17th International Conference on Engineering Applications of Neural Networks will take place in Aberdeen, Scotland, between *2nd-5th September 2016* (EANN 2016 – http://www.eann.org.uk/eann2016/index.php) The INNS (International Neural Network Society) is the primary sponsor of EANN. Authors are invited to submit electronically original, English-language research contributions or experience reports not concurrently submitted elsewhere. The proceedings of the conference will be published in *Springer CCIS Series*. Extended contributions will also be considered for publication in a *Special Issue of Neural Computing and Applications Journal (Springer)*. In the spirit of the previous EANN conferences, the paper should concentrate on the application rather than just the algorithm or the theory. All application areas are relevant. Novel contributions related to deep learning and application of neural networks to data science applications are encouraged. The deadline for paper submission is *20th April 2016*. Proposals for Workshops that examine emerging, innovative, or otherwise provocative issues within the conference area are encouraged as well. Workshop proposals should include a 1-2 page summary of the topic and the names and affiliations of 3-4 panellists who have made a commitment to participate. A mix of industry and academic panel members is recommended. Proposals for 90-minute tutorials are also invited on topics within the conference area. Tutorial proposals must be at most 5 pages, they must identify the intendedaudience, and they must give enough material to provide a sense of what will be covered. Full CFP is available at http://www.eann.org.uk/eann2016/cfp.php Important deadlines are available at http://www.eann.org.uk/eann2016/timeline.php If you have any questions please email Chrisina Jayne at ( c.p.jayne(a)rgu.ac.uk) Best wishes, Prof Chrisina Jayne and Prof Lazaros Iliadis Programme Chairs for EANN2016

Dec. 17, 2015

4 faculty positions: Centre for Cognitive Science at Technische Universitaet Darmstadt

by Constantin Rothkopf

Technische Universität Darmstadt is establishing a Centre for Cognitive Science and invites applications for 4 tenured professorships. The Centre’s research programme will be based on computational and engineering approaches to Cognitive Science, with strong interactions with the engineering departments. Research methodologies will include, but are not limited to, theoretical studies, human experimental work, cognitive engineering applications, the use of big data, and ubiquitous sensing. The professorships are to be filled in the Department of Human Sciences (Institutes of Psychology and of Sports Science) and in the Department of Computer Science, and will complement and interact with the existing research activities in Cognitive science at Technische Universität Darmstadt. The four positions are to be filled in the following areas: 1) One professorship (W2/W3) in the Institute of Sports Sciences in the area Sensorimotor Control & Learning 2) two professorships (W2/W3) in the Institute of Psychology in the areas Perception, Decision Making & Preference or Models of Higher Cognition (e.g. reasoning, natural language, learning and memory), 3) and one professorship (W3) in the Department of Computer Science in the areas Machine Learning or Biosignal Processing (e.g. prosthetics, brain-computer interface). Successful appointees are expected to contribute to teaching in the study programme for cognitive science, which is currently being developed, and to the undergraduate and graduate level courses of their respective departments. The positions are tenured with a remuneration package commensurate with experience and qualifications, following the German "W-Besoldung". The regulations for employment are specified under §§ 61 and 62 HHG (Hessisches Hochschulgesetz). The Technische Universität Darmstadt intends to increase the number of female faculty members and encourages female candidates to apply. In case of equal qualifications applicants with a degree of disability of at least 50 or equal will be given preference. The Technische Universität Darmstadt is certified as a familiy-friendly university and offers a dual career program. Applications should include a curriculum vitae, list of publications, copies of relevant diplomas, as well as a research and teaching statement, preferably all in a single PDF file. Applications for the positions in the Institute of Sport Science and the Institute of Psychology should be directed to the Dean of the Department of Human Sciences, Professor Frank Hänsel (dekanat(a)humanw.tu-darmstadt.de) applications for the position in Computer Science should be directed to the Dean of the Department of Computer Science, Professor Reiner Hähnle (dekanat(a)informatik.tu-darmstadt.de) It is possible to apply for several of the positions. Please include the code number of the position(s) you apply for. Informal enquiries may be addressed to Professor Constantin Rothkopf (Tel +49 6151 16-76084; rothkopf(a)psychologie.tu-darmstadt.de) or Professor Jan Peters (Tel +49-6151-16-7351; peters(a)ias.tu-darmstadt.de) For further information please also visit www.cogsci.tu-darmstadt.de. Code No. 489 (Sensorimotor Control) Code No. 490 (Perception, Decision Making & Preference, Models of Higher Cognition) Code No. 491 (Machine Learning, Biosignal Processing) Application deadline: January 31, 2016 -- Constantin A. Rothkopf, PhD Technical University Darmstadt & FIAS phone: +49 6151 16-76084 http://www.pip.tu-darmstadt.de/ mailto:rothkopf@psychologie.tu-darmstadt.de

Dec. 17, 2015

PhD position in computational neuroscience. 'Identification of Metastable Cortical Dynamics Underlying Cognitive Decisions'. Bournemouth & Barcelona Universities

by Emili Balaguer-Ballester

PhD position in computational neuroscience. "Identification of Metastable Cortical Dynamics Underlying Cognitive Decisions? Bournemouth University-IDIBAPS". A PhD position is available in 3-years fully-funded project "Identification of Metastable Cortical Dynamics Underlying Cognitive Decisions"; based at Bournemouth University (UK) https://research.bournemouth.ac.uk/centre/interdisciplinary-neuroscience-re… and at the Biomedical Research Institute August Pi I Sunyer (IDIBAPS, http://www.idibaps.org/en_index.htm, University of Barcelona, Spain). Do we have analysis tools for a reliable identification of the dynamical processes underlying decision-making? This is a fundamental question, touching the very basics of our understanding of neural computation and hence one of the most exciting topics in neuroscience. However, to reconstruct in detail neural dynamics generating cognitive decisions is a major challenge for current methodologies. This would be a highly significant advance; for instance the identification of stable dynamical patterns of activity in hippocampus deserved to win the last Nobel Prize. The aim of the project is to develop innovative approaches designed for the identification of metastable dynamics underlying cognitive decisions. We aim for the fusion of statistical learning approaches to pattern discovery with methods for identifying neural attractor dynamics and neurocomputational modelling. The novel approach will reconstruct neural dynamics during tasks specifically designed at Sanchez-Vives Lab in rodents and in human subjects at the Bournemouth EEG lab. The training possibilities that this interdisciplinary project offers are multiple and relevant in building-up a high-profile as a neuroscientist. The student will benefit from the vibrant scientific environment of neural computation and neurosciences at BU https://research.bournemouth.ac.uk/centre/interdisciplinary-neuroscience-re… and at the cortical networks lab; embedded in the renowned systems neuroscience network in Barcelona http://www.sanchez-vives.org/. Applicants holding a degree in Physics, Mathematics, Engineering, Computer Science or similar disciplines are welcome. Interest or previous training in neuroscience or laboratory experience and a strong mathematical or machine learning background would be very welcome. The researcher will be based at the Faculty of Science, Bournemouth University, and work with Dr Balaguer-Ballester at the Computational Neuroscience laboratory in the context of the interdisciplinary group for neurosciences; and will spend prolonged periods of time in the Cortical Networks Lab (IDIBAPS, Barcelona) led by Prof. Maria Victoria Sanchez-Vives; providing an outstanding opportunity to gain a diverse experience of both neuro-computational and experimental approaches. For formally applying and more information please visit https://research.bournemouth.ac.uk/pgr/funded-phd-studentships-in-the-facul… Please Cc your application to eb-ballester(a)bournemouth.ac.uk For further details please do not hesitate to contact me any time: eb-ballester(a)bournemouth.ac.uk: Twitter: @emilibalball; http://dec.bournemouth.ac.uk/staff/ebb/ Kind regards, Emili BU is a Disability Two Ticks Employer and has signed up to the Mindful Employer charter. Information about the accessibility of University buildings can be found on the BU DisabledGo webpages This email is intended only for the person to whom it is addressed and may contain confidential information. If you have received this email in error, please notify the sender and delete this email, which must not be copied, distributed or disclosed to any other person. Any views or opinions presented are solely those of the author and do not necessarily represent those of Bournemouth University or its subsidiary companies. Nor can any contract be formed on behalf of the University or its subsidiary companies via email.

Dec. 17, 2015

Workshop "modeling the early visual system" in Paris, January 19-20th

by Olivier Marre

INTRODUCTION Do we know what the early visual system does? This question was the topic of a workshop at the SFN meeting ten years ago. Over the last decade, there has been tremendous progress in understanding the computations performed in the visual system, and how they are implemented by the neural circuitry. The purpose of this workshop is to gather both theoreticians and experimentalists in the field to take stock and debate about the current challenges when trying to understand the computations performed by the early visual system, and how they result from both bottom-up and top-down processes. CONFIRMED SPEAKERS Philipp Berens, University of Tuebingen, Germany Laura Busse, University of Tuebingen, Germany Matteo Carandini, UCL, UK Frédéric Chavane, INT, Marseille, France Karl Farrow, NERF, Belgium Yves Frégnac, UNIC laboratory, CNRS, Gif sur Yvette, France Charles Gilbert, Rockefeller University, New York, USA Tim Gollisch, University of Gottingen, Germany Peter Neri, Ecole Normale Supérieure, Paris, France Elad Schneidman, Weizman Institute of Science, Israel Andreas Tolias, Baylor College of Medicine, Austin, USA Shimon Ullman, Weizman Institute of Science, Israel REGISTRATION This workshop will take place in the European Institute for Theoretical Neuroscience ( http://www.eitn.eu/ ), Paris, January 19th and 20th. Registration is free but mandatory. We have a few slots for posters that will be presented during the meeting. If you are interested in presenting a poster. For registration and/or abstract submission, please refer to the workshop website: http://eitnconf-190116.sciencesconf.org/ On behalf of the organizing committee, Olivier Marre Institut de la Vision F-75012 Paris

Dec. 17, 2015

International Conference on Mathematical Neuroscience (ICMNS) 2016

by Zachary Kilpatrick

We would like to remind you about… The 2nd International Conference on Mathematical Neuroscience (ICMNS 2016) at the Congress Center in Juan-les-Pins on the French Riviera May 29 to June 1, 2016 Tutorials: May 29 Main Conference: May 30 - June 1 https://icmns2016.inria.fr/ <https://icmns2016.inria.fr/> One page abstracts will be reviewed by a Program Committee and divided into three categories: featured talks, session talks, and posters. https://icmns2016.inria.fr/call-for-contributions/ <https://icmns2016.inria.fr/call-for-contributions/> The abstract submission deadline is January 7, 2016. Meeting registration will open shortly thereafter. Questions should be directed to the conference email: icmns2016-contact(a)inria.fr <mailto:icmns2016-contact@inria.fr> CONFIRMED SPEAKERS Wulfram Gerstner (École polytechnique fédérale de Lausanne) John Rinzel (New York University) Antoine Triller (École Normale Supérieure de Paris) Rachel Kuske (U British Columbia) Jonathan Rubin (U Pittsburgh) Hinke Osinga (U Aukland) Carina Curto (Penn State University) Ruben Moreno-Bote (Foundation Sant Joan de Deu) Hiroya Nakao (Tokyo Institute of Technology) Eric Shea-Brown (U Washington) Si Wu (Beijing Normal University) Alex Roxin (Centre de Recerca Matematica) PROGRAM COMMITTEE Toni Guillamon (Universitat Politècnica de Catalunya) Roland Potthast (U Reading) Gregory Faye (Université Paul Sabatier ) Wilhelm Stannat (TU Berlin) Jonathan Touboul (College de France) Gilles Wainrib (Ecole Normale Supérieure) Suzanne Ditlevsen (University of Copenhagen) Boris Gutkin (Ecole Normale Supérieure) Martin Wechselberger (U Sydney) Jonathan Rubin (U Pittsburgh) Martin Krupa (INRIA Sophia Antipoilis) Carlo Laing (Massey University) Andre Longtin (U Ottawa) Daniele Avitabile (U Nottingham) Jose Carrillo (Imperial College) Pascal Chossat (Université Nice Sophia Antipolis) Carson Chow (National Institutes of Health) Steve Zucker (Yale University) Eric Shea-Brown (U Washington) Rachel Kuske (U British Columbia) Laura Sacerdote (Universita di Torino) Reinhard Hopfner (Johannes-Gutenberg Universitat) Olivier Faugeras (INRIA - Sophia Antipolis) Paul Bressloff (U Utah) Steve Coombes (U Nottingham) CONFERENCE CHAIRS Romain Veltz (INRIA - Sophia Anitpolis) Zachary Kilpatrick (U Houston) Evelyn Buckwar (Johannes Kepler Universitat Linz) We hope to see you in Juan-les-Pins! All the best Romain, Zack, and Evelyn

Dec. 17, 2015