- Comp-neuro - lists.cnsorg.org

Scientist I/II - Computational Neuroscience at Allen Institute for Brain Science
by Stefan Mihalas Sept. 1, 2017

Sept. 1, 2017

POSITION SUMMARY We are seeking to fill a position at the level of Scientist to work on coarse-grained models of cortical networks aiming to understand how the observed structure and activity gives relate to cortical computations necessary for visual processing (e.g. figure ground segregation, integration of context). We use mouse vision as a model system and this position will focus on using population statistics (http://alleninstitute.github.io/dipde/) and filter neuron model simulation tools. More specifically, the scientist will work on (i) fitting network models with simple neurons which network structures are consistent with the observed mesoscopic connectivity and in vivo cellular activity, (ii) simulate the activity of such networks at neuronal an population levels and (iii) analyzing the relation between observed network structure and that predicted from different models of cortical computations. ESSENTIAL DUTIES AND RESPONSIBILITIES * Participate in team efforts to find network parameters which are consistent with activity (http://observatory.brain-map.org/visualcoding/) and connectivity (http://connectivity.brain-map.org/) data. * Simulate cortical networks parameterized from experimental data using population and simplified neuron model simulation tools. * Analyze how computations in vision (e.g. figure/ground segregation, integration of context) result from networks similar to those simulated. * Interact with groups performing simulations at other levels of resolution and with experimental groups. * Maintain clear and accurate communication with supervisor and team members. * Publish/present findings in peer-reviewed journals/scientific conferences. BASIC QUALIFICATIONS SCIENTIST I * PhD degree in computational neuroscience, physics, mathematics, applied mathematics or related field. * Strong background in scientific computing is required. * Experience in computational neuroscience is preferred. SCIENTIST II * PhD degree in computational neuroscience, physics, mathematics, applied mathematics or related field. * 4+ years of postdoctoral experience in computational science * Preferred Computational neuroscience * Strong background in scientific computing is required. * Strong publication record. Preferred Qualifications: * Ability to meet aggressive timelines and deliverables in a collaborative environment. * Proven independent thinking and flexibility. * Strong written and verbal communication skills * Experience in pursuing research projects in collaborative fashion. Our mission at the Allen Institute for Brain Science is to accelerate the understanding of how the human brain works in health and disease. By implementing a team science approach on a large scale, we strive to generate useful public resources, drive technological innovations and discover fundamental brain properties through integration of experiments, modeling and theory. To apply please visit https://www.alleninstitute.org/what-we-do/brain-science/careers/job-search/. Applications will be considered on an ongoing basis. Apologies for coss-posting, Stefan Mihalas Assistant Investigator Allen Institute for Brain Science www.alleninstitute.org<http://www.alleninstitute.org/> Affiliate Assistant Professor Department of Applied Mathematics University of Washington

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5th Baltic-Nordic School on Neuroinformatics (BNNI 2017)
by Marja-Leena Linne Sept. 1, 2017

Sept. 1, 2017

5th Baltic-Nordic School on Neuroinformatics BNNI 2017 Theoretical modelling of brain functions in neurological and psychiatric disorders: Advancing future neuroscience and medicine through Neuroinformatics methods Place: Neuroscience Institute Lithuanian University of Health Sciences Eiveniu str.4, Kaunas Lithuania Time: 6-7 October 2017 More information and applications at: web.lsmuni.lt/bnni/en Important dates: 10 September 2017: Application deadline 12 September 2017: Acceptance notification 6-7 October 2017: School We invite advanced master students, doctoral students, and postdoctoral researchers to participate in the BNNI 2017 to be held at the Neuroscience Institute, Lithuanian University of Health Sciences, Kaunas, Lithuania. The course is interdisciplinary and covers modeling at different levels of organization of the brain, focusing on neurological and psychiatric disorders. The course combines lectures, tutorials and computer exercises. This school is the fifth in the series of the Baltic-Nordic Courses on Neuroinformatics (BNNI 2013 in Kaunas, Lithuania; BNNI 2014 in Tampere, Finland; BNNI 2015 in Tartu, Estonia; BNNI in Warsaw 2016, Poland). The target audience of the course will be advanced master students, doctoral students and postdoctoral researchers in biomedical and technology sciences, from medicine, biology, psychology, to mathematics, informatics, information technology, physics, chemistry, who would like to get an introduction to neuroinformatics and computational neuroscience. Some experience with programming and quantitative reasoning as well as strong interest in computational and mathematical modeling of the brain will be desirable but not necessary to benefit from the school. Last year we had participants from 14 countries all over the world! Faculty includes: Marja-Leena Linne, Tampere University of Technology, Finland; The Human Brain Project Bruce Graham, University of Stirling, UK Daniel Wojcik, Nencki Institute of Experimental Biology, Warsaw, Poland Arnd Roth, University College London, UK Peter Jedlicka, NeuroScience Center, Goethe-University, Frankfurt, Germany Tuomo Mäki-Marttunen, Simula Research Laboratory, Oslo, Norway Inga Griskova-Bulanova, Institute of Bioscience, Vilnius University, Lithuania Rima Naginiene, Neuroscience Institute, Lithuanian University of Health Sciences, Kaunas, Lithuania Andrius Radziunas, Department of Neurosurgery, Medical Academy, and Neuroscience Institute, Lithuanian University of Health Sciences, Kaunas, Lithuania Ausra Saudargiene, Neuroscience Institute, Lithuanian University of Health Sciences, and Vytautas Magnus University, Kaunas, Lithuania and others. Venue: The lectures will be held at the Neuroscience Institute, Lithuanian University of Health Sciences, Eivenių str. 4, Kaunas, Lithuania Practical arrangements: There is a small tuition fee of 50 euros. The organizers will provide teaching materials, meals and coffee during the course. The participants are expected to cover their travel and health insurance expenses as well as lodging. The course is supported by the Research Council of Lithuania and Lithuanian University of Health Sciences. We are looking forward to welcoming you at the BNNI 2017 in Kaunas, Lithuania!

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Doctoral student position - Robot-assisted modeling of spatial navigation paradigms in biological organisms - DEADLINE EXTENDED
by samarasinghe＠ini.rub.de Sept. 1, 2017

Sept. 1, 2017

Please note that the deadline for applications to the position below has been extended to *15.09.2017*. *Research **Position **at the Institute for Neural Compu**ta**ti**o**n * A position as *d**octoral student **in integrative **n**euroscience and **c**ognitive **s**cience *is available immediately in the group of Prof. Sen Cheng in the Institute for Neural Computation at the Ruhr University Bochum, Germany. The research will focus on robot-assisted modeling of spatial navigation paradigms in biological organisms. Robotic simulations, as well as, physical robots will be used to develop and evaluate the desired models. The position will be funded at 50% of the standard salary scale TV-L E13. It is initially limited to 1 year with the possibility of extension, depending on the availability of funding. Candidates should have an excellent degree in neuroscience, physics, mathematics, engineering, or a related field. Competence in mathematical modeling, and excellent programming skills (Python, C/C++, or Matlab) are mandatory. Candidates are further required to have a strong background in at least one of the following fields: robotics, computational neuroscience, or cognitive modeling. Experience with interdisciplinary research in integrative neuroscience and cognitive science and with collaborative research would be a further asset. The working language at the institute is English. To apply, please send a statement of your research interests, academic transcripts, and a complete CV in one PDF file to samarasinghe(a)ini.rub.de <mailto:samarasinghe@ini.rub.de> by *15**.09****.2017*. Please also request from at least two academic referees that they send letters of reference directly to the same email address. Further information may be available at https://www.ini.rub.de/the_institute/jobs/. The Ruhr University Bochum provides a dynamic research environment in neuroscience and cognitive science. The Institute for Neural Computation unifies various core competencies extending from experimental and theoretical neuroscience to machine learning and robotics. The Ruhr University Bochum is committed to equal opportunity. We strongly encourage applications from qualified women and persons with disabilities. -- Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience Institut für Neuroinformatik Ruhr-Universität Bochum, NB 3/26 Universitätstr. 150 D-44780 Bochum Tel: +49 (0)234 32 27316 Email: samarasinghe(a)ini.rub.de Hours: Monday 9-12 & 14-16; Friday 9-12 & 14-16; Wednesday 12 - 16

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Postdoc position: computational models of visual memory, Rust lab, UPenn
by Rust, Nicole C Sept. 1, 2017

Sept. 1, 2017

A postdoctoral position focused on developing computational models of visual memory is available in the laboratory of Nicole Rust at the University of Pennsylvania. The lab is broadly interested in understanding the neural processing supporting massive-capacity, single-trial visual memories of images. This specific position involves developing classes of computational models that describe where and how visual memories are stored in the brain as well as how the percept of visual familiarity is signaled. Models include extensions of state-of-the-art descriptions of visual processing (e.g. deep neural networks) as well as more dynamic, mechanistic descriptions. To constrain these models, the researcher will interface with experimentalists in the lab who record and perturb neural signals in monkeys and tree shrews. Opportunities also exist to collaborate with the Simoncelli lab at NYU, the Yamins lab at Stanford, and with other members of the Penn Computational Neuroscience Initiative. Candidates should have a Ph.D. in Computational Neuroscience, Computer Science or a related field prior to starting. The ideal candidate has extensive experience in computational modeling as well as working with behavioral and/or neural data. To inquire about this position, please submit a CV and a brief statement of research interests to nrust(a)psych.upenn.edu<mailto:nrust@psych.upenn.edu>. Nicole Rust Associate Professor Department of Psychology University of Pennsylvania Philadelphia, PA http://www.sas.upenn.edu/psych/rust-lab/

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[EAIS 2018] Paper Submission deadline is on Saturday, 20th of January 2018 2359 UTC-12hr
by Teng Teck Hou Sept. 1, 2017

Sept. 1, 2017

[Apologies for cross-postings] ################################################## CALL FOR PAPERS IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2018) 25-27 of May 2018, Island of Rhodes, Greece http://easyconferences.eu/eais2018/ ################################################## Contributions will be selected based upon their quality as evaluated by the reviewers. An online submission system for contributions will be made available on this webpage soon. Papers must be comprised of up to 8 pages and they will be published in the IEEE Explore All contributions have to be prepared according to the IEEE conference style guidelines. To see the Topics please visit: http://easyconferences.eu/eais2018/topics.html ################################################## The 2018 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2018) will be held in The 2018 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2018) will be held in the exotic island of Rhodes (Greece) which has a beautiful medieval town built by the crusaders and it is preserved as UNESCO monument. A main characteristic of Rhodes is its long ancient history with many ancient Greek sites. Set against the historic backdrop of Rhodes island is the elegant and pisturesque lowrise architecture of Aldemar Amilia Mare Village, an all-inclusive seaside resort. Newly refurbished luxury rooms with sea or garden views are the perfect choice for all holidaymakers, f rom singles to families. Dive into crystal clear swimming pools, try a wide range of watersports at the beach, enjoy the Spa Centre with its fully equipped fitness area and sample the cosmopolitan delights of the themed restaurants. ##############################Important Dates############################## * Paper Submission January 20, 2018 * Special Session Proposals 20 December, 2017 * Paper Decision Notification January 15, 2018 * Camera-Ready Submission February 15, 2018 * Authors registration To be announced * Conference May 25 - 27 2018 ########################################################################### ########################## At least three distinguished Keynote Speakers will be invited ########################## ##################### SPECIAL ISSUES ################################### Selected papers (from the list of the accepted and presented ones) will be considered for publication and inclusion in Special Issue of the EVOLVING SYSTEMS (EVOS) Springer Journal. At least one more Special Issue will be edited ##################Topics and Areas of Interest################## This conference solicits papers addressing original works in topics and areas of interest including, but are not limited to: * Basic Methologies Evolving Soft Computing Techniques Evolving Fuzzy Systems Evolving Rule-Based Classifiers Evolving Neuro-Fuzzy Systems Adaptive Evolving Neural Networks Adaptive Evolving Fuzzy Systems Online Genetic and Evolutionary Algorithms Data Stream Mining Incremental and Evolving Clustering Approaches Adaptive Control Adaptive Pattern Recognition Computational Intelligence in Control and Estimation Incremental and Evolving ML Classifiers Adaptive Statistical Techniques Evolving Decision Systems Big Data Advanced Concepts * Problems and Methodologies in Data Streams Stability, Robustness, Convergence in Evolving Systems Online Feature Selection and Dimension Reduction Online Active and Semi-supervised Learning Online Complexity Reduction Computational Aspects Interpretability Issues Incremental Adaptive Ensemble Methods Online Bagging and Boosting Self-monitoring Evolving Systems Human-Machine Interaction Issues Hybrid Modeling Transfer Learning Reservoir Computing Real-world Applications * EIS for On-Line Modeling, System Identification, and Control EIS for Time Series Prediction EIS for Data Stream Mining and Adaptive Knowledge Discovery EIS in Robotics, Intelligent Transport and Advanced Manufacturing EIS in Advanced Communications and Multi-Media Applications EIS in Bioinformatics and Medicine EIS in Online Quality Control and Fault Diagnosis EIS in Condition Monitoring Systems EIS in Adaptive Evolving Controller Design EIS in User Activities Recognition EIS in Huge Database and Web Mining EIS in Visual Inspection and Image Classification EIS in Image Processing EIS in Cloud Computing EIS in Multiple Sensor Networks EIS in Query Systems and Social Networks EIS in Alternative Statistical and Machine Learning Approaches ################################################################ ##########################Organizing Committee########################## * General co-Chairs Plamen Angelov, Lancaster University, UK Yannis Manolopoulos, Aristotle University of Thessaloniki, Greece PC co-Chairs Edwin Lughofer Johannes, Kepler University Linz, Austria Lazaros Iliadis, Democritus University of Thrace Honorary co-Chairs Dimitar Filev, Ford Motor Company, USA Nikola Kasabov, Auckland University of Technology, New Zealand Special session co-Chairs Abdelhamid Bouchachia, University of Bournemouth, UK Jose Antonio Iglesias, Carlos III University of Madrid (Leganes, Spain) Organizing Chair Apostolos Papadopoulos, Aristotle University of Thessaloniki, Greece Local Organizing co-Chairs Constantinos Demertzis, Democritus University of Thrace, Greece Antonis Papaleonidas, Democritus University of Thrace, Greece Workshop co-chairs M. Sayed - Mouchaweich, Universite Lille, France Andre Paim Lemos, Univerity Minas Gerais, Brazil Publicity and Publication co-Chairs Teck-Hou, Teng Singapore Management University, Singapore Antonis Papaleonidas, Democritus University of Thrace, Greece Web Admin Kyriakos Georgiades, Easy Conferences, Cyprus * International Program Committe Plamen Angelov, Lancaster University, UK Rosangela Ballini, University of Campinas, Brazil Jorge Cassillas, University of Granada, Spain Dejan Dovzan, University of Ljubljana, Slovenia Nadine Gaertner, SAP, Germany Lazaros Iliadis, Democritus University of Thrace, Greece Nik Kasabov, Auckland University of Technology, New Zealand Spyros Likothanasis, University of Patras, Greece Daniel Furtado Leite, Federal University of Lavras, Brazil Andre Lemos, Federal University of Minas Gerais, Brazil Edwin Lughofer, Johannes Kepler University, Linz, Austria Yannis Manolopoulos, Aristotle University of Thessalonii, Greece Trevor Martin, University of Bristol, UK Seiichi Ozawa, Kobe University, Japan Witold Pedrycz, University of Alberta, Canada Radu-Emil Precup, University of Timisoara, Romania Olga Senyukova, Lomonosov Moscow State University, Moscow, Russia El Mustapha Mouaddib, Universite de Picardie Jules Verne, France Jus Kocijan, Jozef Stefan Institute, Ljubljana,Slovenia ####################################################################### #########################Sponsoring Organizations######################### * IEEE * Aristotle University of Thessaloniki, Greece * Democritus University of thrace, Greece ##########################################################################

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Penn Psych - Faculty Search
by Rust, Nicole C Aug. 29, 2017

Aug. 29, 2017

Assistant Professor, Cognitive or Affective Science Department of Psychology, University of Pennsylvania The Department of Psychology at the University of Pennsylvania intends to make multiple appointments in the areas of Cognitive Science and Affective Science over the next several years. Our primary focus is at the junior, Assistant Professor level, but in exceptional circumstances a more senior hire may be considered. We are interested in candidates with research interests in the areas, broadly defined, of cognitive science (e.g., learning and memory, perception, attention, language, or decision making) or affective science (e.g., clinical or health psychology; social, moral, or political psychology; positive psychology; or the psychology of individual differences), and who use any number of approaches, including but not limited to computational, neuroscientific (behavioral, systems, or cognitive), or developmental. Interested candidates should submit materials online at http://facultysearches.provost.upenn.edu/postings/1121 and include a curriculum vitae, statements of research and teaching interests, and the names and contact information of three referees. Candidates will contribute to the teaching mission of the university with introductory courses such as Introduction to Psychology, Introduction to Brain and Behavior, Cognitive Psychology, or Abnormal Psychology, as well as advanced undergraduate or graduate courses in specific areas of interest. Referees will be contacted by the University with instructions on how to submit a recommendation letter to the website. Review of applications will begin on September 18, 2017 and continue until the position is filled. The Department of Psychology is strongly committed to Penn’s Action Plan for Faculty Diversity and Excellence and to creating a more diverse faculty (for more information, see http://www.upenn.edu/almanac/volumes/v58/n02/diversityplan.html) The University of Pennsylvania is an equal opportunity employer. Minorities, women, individuals with disabilities, and protected veterans are encouraged to apply. Nicole Rust, Ph.D. Associate Professor Department of Psychology University of Pennsylvania Philadelphia, PA 19104 http://www.sas.upenn.edu/psych/rust-lab/

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[jobs] Researcher in Cognitive Robotics
by Di Nuovo, Alessandro Aug. 29, 2017

Aug. 29, 2017

Apologies for multiple postings. A fixed-term position is available at Sheffield Hallam University (UK), within Sheffield Robotics. The post is funded by the EPSRC project EP/P030033/1 - Number Understanding Modelling in Behavioural Embodied Robotic Systems (NUMBERS). Details of the post and the link for applying can be found here: http://www.jobs.ac.uk/job/BDR925/researcher-cognitive-robotics/ NUMBERS is a highly inter-disciplinary cutting-edge cognitive robotics research programme lead by Dr Alessandro Di Nuovo and developed in collaboration with Sheffield Robotics. The project sees the participation of Plymouth University and Stanford University (USA), and received the support of the NVIDIA Corporation (USA). It will utilise one of the most advanced child-like robotic platforms (the "iCub") to construct a novel artificial cognitive model of mathematical cognition by imitating human like learning approaches for developing number understanding. The researcher will contribute to the project by carrying out experiments with the iCub, including: Software development. Collecting and analysing data. Guaranteeing continuity of the robotic experiments. The researcher will also be an active member of the Sheffield Robotics team contributing to scientific publications and supporting exhibitions and demonstrations. Experience of working with the iCub robotic platform would be an advantage as well as the knowledge of deep learning software frameworks. This is an exciting opportunity to contribute to the development of the next generation of socially interactive robots capable of learning and mimicking advanced capabilities of human intelligence. Contact e-mail: a.dinuovo(a)shu.ac.uk

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[Extended Deadline-CFP] - HAI 2017 Workshop: Representation Learning for Human and Robot Cognition
by Amir Aly Aug. 28, 2017

Aug. 28, 2017

CALL FOR PAPERS **Apologies for cross posting ** The full day workshop: "*Representation Learning for Human and Robot Cognition*" In conjunction with the *5th International Conference on Human-Agent Interaction* *- Bielefeld - Germany - October * *17th, 2017* *Webpage: **http://cognitive-mirroring.org/en/events/hai2017_workshop/* <http://cognitive-mirroring.org/en/events/hai2017_workshop/> *I. Aim and Scope *Creating intelligent and interactive robots has been subject to extensive research studies. They are rapidly moving to the center of human environment so that they collaborate with human users in different applications, which requires high-level cognitive functions so as to allow them to understand and learn from human behavior. To this end, an important challenge that attracts much attention in cognitive science and artificial intelligence, is the “Symbol Emergence” problem, which investigates the bottom-up development of symbols through social interaction. This research line employs representation learning based models for understanding language and action in a developmentally plausible manner so as to make robots able to behave appropriately on their own. This could open the door to robots to understand syntactic formalisms and semantic references of human speech, and to associate language knowledge to perceptual knowledge so as to successfully collaborate with human users in space. Another interesting approach to study representation learning is “Cognitive Mirroring”, which refers to artificial systems that could make cognitive processes observable, such as the models that could learn concepts of objects, actions, and/or emotions from humans through interaction. A key idea of this approach is that robots learn individual characteristics of human cognition rather than acquiring a general representation of cognition. In this way, the characteristics of human cognition become observable and can be measured as modifications in model parameters, which is difficult to verify through neuroscience studies only. In this workshop, we invite researchers in artificial intelligence, cognitive science, cognitive robotics, and neuroscience to share their knowledge and research findings on representation learning, and to engage in cutting-edge discussions with other experienced researchers so as to help promoting this research line in the Human-Agent Interaction (HAI) community. *II. Keynote Speakers * 1. *Beata Joanna Grzyb *– Radboud University – The Netherlands 2. *Thomas Hermann*– Bielefeld University – Germany 3. *Tetsuya Ogata *– Waseda University – Japan 4. *Erhan Oztop *– Ozyegin Universiy – Turkey 5. * Stefan Wermter *– University of Hamburg – Germany *III. Submission * 1. For paper submission, use the following EasyChair web link: *Paper Submission <https://easychair.org/conferences/?conf=rlhrc2017>*. 2. Use the ACM SIGCHI format: *ACM SIGCHI Templates <http://www.sigchi.org/publications/chipubform>*. 3. Submitted papers should be limited to 2-4 pages maximum. The primary list of topics covers the following points (but not limited to): - Computational model for high-level cognitive capabilities - Predictive learning from sensorimotor information - Multimodal interaction and concept formulation - Human-robot communication and collaboration based on machine learning - Learning supported by external trainers by demonstration and imitation - Bayesian modeling - Learning with hierarchical and deep architectures - Interactive reinforcement learning * IV. Important Dates * 1. Paper submission: *15-September-2017* 2. Notification of acceptance: *25-September-2017* 3. Camera-ready version: *5-**October-2017* 4. Workshop: *17-October-2017* *V. Organizers * 1. *Takato Horii *– Osaka University – Japan 2. *Amir Aly *– Ritsumeikan University – Japan 3. *Yukie Nagai *– National Institute of Information and Communications Technology – Japan 4. * Takayuki Nagai *– The University of Electro-Communications – Japan -- *Amir Aly, Ph.D.* Senior Researcher Emergent Systems Laboratory College of Information Science and Engineering Ritsumeikan University 1-1-1 Noji Higashi, Kusatsu, Shiga 525-8577 Japan

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Postdoc position in electrophysiology/neural coding at Columbia University
by Qi Wang Aug. 28, 2017

Aug. 28, 2017

A postdoc position is available in the Laboratory for Neural Engineering and Control in the Department of Biomedical Engineering at Columbia University (http://neclab.bme.columbia.edu/) The project investigates the role of the locus coeruleus – norepinephrine (LC-NE) system in modulating neural coding, perception, and learning. The successful applicant should have a background in in-vivo single-unit recording and quantitative analytical methods. Experiences in behavioral training of rodents is a plus. We are looking for highly motivated researchers with a strong technical background, ideally with a PhD or equivalent in Biomedical Engineering, Neuroscience, Psychology, or a related discipline. Applicants should demonstrate excellent oral and written communication skills, and the ability to work effectively independently and as part of a multidisciplinary team. Start date is flexible. Salary will be commensurate to the candidate qualifications. Applicants should submit a CV, a brief description of research interests, and a list of three references. All application materials as well as any inquiries should be sent to qi.wang(a)columbia.edu.

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Bernstein 2017 Workshop: "Multiscale modeling and simulation"
by Salvador Dura Aug. 27, 2017

Aug. 27, 2017

Dear All, We would like to bring your attention to the* "Multiscale modeling and simulation" workshop* at the *Bernstein Conference 2017, Sept 12-13, Göttingen, Germany.* *Website: *http://www.nncn.de/en/bernstein-conference/2017/ satellite-workshops/multiscale-modeling-and-simulation-dura-bernal-lytton *Short abstract:* Understanding brain function requires characterizing the *interactions occurring across many temporal and spatial scales*. Mechanistic multiscale modeling aims to organize and explore these interactions across these scales. Multiscale models can provide insights into how changes at the molecular and cellular levels affect dynamics at local networks and brain areas. At the highest levels, they allow us to connect neural activity to theories of behavior, memory and cognition. The recent introduction of large neuroscience projects in US and EU Brain Research through Advancing Innovative Neurotechnologies (BRAIN) and Human Brain Project (HBP) respectively provide an opportunity to rapidly gather new and more accurate data to incorporate into the multiscale models. This workshop will present some of the* latest multiscale modeling tools and approaches in neuroscience, as well as representative examples of datadriven multiscale neural simulations*. The workshop aims to encourage both computational and experimental neuroscientists to make use of multiscale modeling in their research. *Organizers: *Salvador Dura-Bernal and Bill Lytton (SUNY Downstate) *Speakers:* *Tue, Sept 12:* - Bill Lytton (SUNY Downstate) - Jean Pierre Changeux (Pasteur Institute) - Volker Steuber (University of Hertfordshire) - Robert McDougal (Yale University) - Salvador Dura-Bernal (SUNY Downstate) - Cliff C Kerr (University of Sydney) *Wed, Sept 13:* - Szabolcs Kali (Hungarian Academy of Science/HBP) - Marianne Bezaire (Boston University) - Daniel Durstewitz (ZI Mannheim) - Kael Dali (Allen Institute for Brain Science) We look forward to seeing you there! Best Salva -- Salvador Durá-Bernal, Ph.D. Research Assistant Professor State University of New York Downstate Medical Center

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