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Call for Papers: IEEE Computational Intelligence Magazine (CIM) Special Issue: "Computational Intelligence for Changing Environments"
by Dr Amir Hussain Aug. 11, 2014

Aug. 11, 2014

Call for Papers (Please also forward to any interested colleagues - with advance apologies for any cross-postings!) IEEE Computational Intelligence Magazine (CIM) (http://cis.ieee.org/ieee-computational-intelligence-magazine.html) Special Issue on "Computational Intelligence for Changing Environments" (Submission Deadline: 15 Nov 2014) (http://www.cs.stir.ac.uk/~ahu/IEEE-CIM-CICE2015.pdf) Guest Editors: Amir Hussain, Dacheng Tao, Jonathan Wu and Dongbin Zhao Aims and Scope: Over the past decade or so, computational intelligence techniques have been highly successful for solving big data challenges in changing environments. In particular, there has been growing interest in so called biologically inspired learning (BIL), which refers to a wide range of learning techniques, motivated by biology, that try to mimic specific biological functions or behaviors. Examples include the hierarchy of the brain neocortex and neural circuits, which have resulted in biologically-inspired features for encoding, deep neural networks for classification, and spiking neural networks for general modelling. To ensure these models are generalizable to unseen data, it is common to assume that the training and test data are independently sampled from an identical distribution, known as the sample i.i.d. assumption. In dynamic and non-stationary environments, the distribution of data changes over time, resulting in the phenomenon of ‘concept drift’ (also known as population drift or concept shift), which is a generalization of covariance shift in statistics. Over the last five years, transfer learning and multitask learning have been used to tackle this problem. Fundamental analyses using probably approximately correct (PAC) and Rademacher complexity frameworks have explained why appropriate incorporation of context and concept drift can improve generalizability in changing environments. It is possible to use human-level processing power to tackle concept drift in changing environments. Concept drift is a real-world problem, usually associated with online and concept learning, where the relationships between input data and target variables dynamically change over time. Traditional learning schemes do not adequately address this issue, either because they are offline or because they avoid dynamic learning. However, BIL seems to possess properties that would be helpful for solving concept drift problems in changing environments. Intuitively, the human capacity to deal with concept drift is innate to cognitive processes, and the learning problems susceptible to concept drift seem to share some of the dynamic demands placed on plastic neural areas in the brain. Using improved biological models in neural networks can provide insight into cognitive computational phenomena. However, a main outstanding issue in using computational intelligence for changing environments and domain adaptation is how to build complex networks, or how networks should be connected to the features, samples, and distribution drifts. Manual design and building of these networks are beyond current human capabilities. Recently, computational intelligence methods has been used to address concept drift in changing environments, with promising results. A Hebbian learning model has been used to handle random, as well as correlated, concept drift. Neural networks have been used for concept drift detection, and the influence of latent variables on concept drift in a neural network has been studied. In another study, a timing-dependent synapse model has been applied to concept drift. These works mainly apply biologically-plausible computational models to concept drift problems. Although these results are still in their infancy, they open up new possibilities to achieve brain-like intelligence for solving concept drift problems in changing environments. Taking the current state of research in computational intelligence for changing environments into account, the objective of this special issue is to collate this research to help unify the concepts and terminology of computational intelligence in changing environments, and to survey state-of-the-art computational intelligence methodologies and the key techniques investigated to date. Therefore, this special issue invites submissions on the most recent developments in computational intelligence for changing environments algorithms and architectures, theoretical foundations, and representations, & their application to real world problems. We also welcome timely surveys & review papers. Topics of Interest include (but are not limited to): • Computational intelligence methodologies and implementation for changing environments • Transfer learning, Multitask learning, Domain adaption • Incremental Learning architectures, Unsupervised and semi-supervised learning architectures • Incremental Knowledge augmentation, Representation learning and disentangling • Incremental Adaptive Neuro-fuzzy systems • Incremental and single-pass data mining • Incremental Neural Clustering & Regression • Incremental Adaptive decision systems • Incremental Feature selection and reduction • Incremental Constructive Learning • Novelty detection in Incremental learning Submission Process The maximum length for the manuscript is typically 25 pages in single column format with double-spacing, including figures and references. Authors should specify in the first page of their manuscripts the corresponding author’s contact and up to 5 keywords. Submission should be made via: https://easychair.org/conferences/?conf=ieee-cim-cice2015 Important Dates (for August 2015 Issue) 15th November, 2014: Submission of Manuscripts 15th January, 2015: Notification of Review Results 15th February, 2015: Submission of Revised Manuscripts 15th March, 2015: Submission of Final Manuscripts Guest Editors Professor Amir Hussain, University of Stirling, Stirling FK9 4LA, Scotland UK Email: ahu(a)cs.stir.ac.uk http://cs.stir.ac.uk/~ahu/ Professor Dacheng Tao, University of Technology, Sydney, 235 Jones Street, Ultimo, NSW 2007, Australia Email: dacheng.tao(a)uts.edu.au Professor Jonathan Wu University of Windsor 401 Sunset Avenue, Windsor, ON, Canada Email: jwu(a)uwindsor.ca Professor Dongbin Zhao Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China E-mail: dongbin.zhao(a)gmail.com -- The University of Stirling has been ranked in the top 12 of UK universities for graduate employment*. 94% of our 2012 graduates were in work and/or further study within six months of graduation. *The Telegraph The University of Stirling is a charity registered in Scotland, number SC 011159.

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FW: PhD/Researcher positions in Electrical Engineering, Computer Science or Biomedical Engineering
by Morgado Dias Aug. 9, 2014

Aug. 9, 2014

Dear Members, Positions 3 and 4 might be interesting for the community. Best regards, Morgado ------------------------------------------------------ PhD/Researcher positions in Electrical Engineering, Computer Science or Biomedical Engineering The research group of Prof. Morgado Dias (Madeira Interactive Technologies Institute - Partner of the Carnegie Mellon University - Portugal program) is looking for PhD students and researchers for: (1) Monitoring and Fault detection in Photovoltaic parks (funded project-1year-possible follow-up with a PhD) (2) 3D Image Processing (funded project-1year- possible follow-up with a PhD) (3) Hardware for Artificial Neural Networks, with emphasis on emerging architectures (PhD, but needs to be externally funded) (4) FPGA prototype for detecting sleep APNEA disorders (PhD – needs to apply to a specific program in Portugal for funding if required) Information about the Institute, University and Region: Madeira Interactive Technologies Institute - Partner of the Carnegie Mellon University - Portugal program, is an innovation institute established as an associated independent non-profit R&D organization whose founding members are the University of Madeira, Madeira Tecnopolo S. A. and Carnegie Mellon University. Recently awarded a 2,4M€ funding, Madeira-ITI operates in the interdisciplinary domain of human-computer interaction encapsulating contributions from computer science, psychology and design in order to address/engage in important scientific and technological challenges that are both relevant to society and have significant economic impact (www.m-iti.org <http://www.m-iti.org> ). The University of Madeira is an active public university integrated in Portuguese Higher Education System and the European Community. Madeira is a small island with paradisiac living conditions and warm people. Recently elected as the Best European Island, you will find in a small place a diversity of landscapes that go from the beach to the mountain with low living costs and almost no crime. Prof. Morgado Dias research expertise includes Artificial Neural Networks, FPGAs and Renewable Energy. More information can be found at: http://www.cee.uma.pt/morgado/ Profile for candidates: (1) A master’s degree in Electrical Engineering, Computer Science, Biomedical Engineering or Computer Engineering (preferred) or an undergraduate degree in the same areas, completed before arrival. (2) Good oral and spoken English as well as good communication skills. TOEFL or IELTS scores are encouraged. At least the English proficiency that fulfills the requirements of CSC applications is necessary. (3) Teamwork spirit. (4) Self-motivation and independent working ability. (5) Knowledge of and research experience related to the above fields are strongly preferred. (6) Previous published work and interest in pursuing a PhD is preferred. Application: If you are interested, please address your motivation letter (with a brief description of yourself, research ability & interest) and CV to: morgadoatuma.pt <mailto:morgado@uma.pt> --- Este email está livre de vírus e malware porque a proteção avast! Antivirus está ativa. http://www.avast.com

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PhD opportunities at the Queensland Brain Institute
by Geoffrey Goodhill Aug. 8, 2014

Aug. 8, 2014

PhD Positions at the Queensland Brain Institute (QBI), The University of Queensland Application deadline Oct 1st 2014 The Queensland Brain Institute (www.qbi.uq.edu.au) is seeking exceptional and highly motivated PhD candidates to undertake neuroscience research at its state-of-the-art building located at The University of Queensland’s (UQ) St Lucia campus, Brisbane, Australia. UQ has 45,000 students (12,000 postgraduate) and is ranked in the top 100 universities in the world. QBI is one of UQ’s flagship research institutes, with researchers working to understand the fundamental mechanisms of brain function, and applying such research to the development of new therapeutics to combat diseases where brain function is compromised. The Institute’s multidisciplinary environment is home to more than 400 staff and students. Key areas of interest include: • Ageing Dementia and Alzheimer’s Disease • Cognition and Behaviour • Computation and Neuronal Circuits • Neurogenesis and Neuronal Survival • Genetics and Epigenetics • Neuronal Development and Connectivity • Sensory Systems • Synaptic Function Since establishment in 2003 QBI researchers have published >1200 papers in the world’s foremost journals, including 460 in the past 2 years. QBI is 100 metres from UQ's Centre for Advanced imaging (www.cai.uq.edu.au) which houses 7T human and 16.4T animal MRI scanners. Scholarships and Remuneration QBI offers full-time PhD scholarships for outstanding Australian and International students (living allowance AU$25,392 per annum, indexed annually, tax exempt) for 3 years with a possible 6 month extension. In addition, QBI supports high quality domestic and international applicants in their nomination to The University of Queensland’s competitive scholarship rounds (three rounds per year). A QBI top-up scholarship of $5,000 per annum may also be available to successful candidates. Candidates should have a First Class Honours degree (or equivalent) in neuroscience, molecular biology, bioscience, psychology, genetics, physical sciences, engineering, mathematics or a related discipline. Strong academic performance, the commitment to conduct high quality neuroscience research, and published output are highly desirable. For further information on the Basis of Admission to a UQ research higher degree, please visit http://www.uq.edu.au/grad-school/our-research-degrees. Successful applicants must accept and commence within 6 months of receiving an award. Enquiries and Applications Please review the research interests of QBI Group Leaders at http://www.qbi.uq.edu.au/group-leaders and make direct contact with a Group Leader working in an area of greatest interest to you, providing your detailed academic resume and complete academic records (including GPA scores/grades, and grading scale details). The Group Leader will work with you to develop your application for submission to QBI. Applications close on 1 October, 2014 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 http://www.qbi.uq.edu.au/professor-geoffrey-goodhill

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PhD Studentship in Neural Fields and Movement Control, University of Reading, UK
by Ingo Bojak Aug. 7, 2014

Aug. 7, 2014

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Fellowships in Neural Engineering at the University of Washington
by Adrienne Fairhall Aug. 6, 2014

Aug. 6, 2014

We invite applications for the Washington Research Foundation Innovation Fellowships in Neuroengineering at the University of Washington in Seattle. These fellowships will be offered through the recently established UW Institute for Neuroengineering, which aims to aims to solve some of today’s greatest scientific challenges about neural system function by linking advances in biology, computing, devices, data science, and computational neuroscience. These highly selective fellowships will fund research in computational and engineering approaches to neuroscience; joint mentoring between faculty in different disciplines (CS, engineering, mathematics, neurobiology) is strongly encouraged. Applications are due September 1, 2014. Please see http://uwin.washington.edu/post-docs/ for more details of the application procedure.

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IWSP7: Epilepsy Mechanisms, Models, Prediction & Control
by Levin Kuhlmann Aug. 6, 2014

Aug. 6, 2014

Dear Colleagues, It is with unbridled excitement that we announce the date of the 7th International Workshop on Seizure Prediction: IWSP7: Epilepsy Mechanisms, Models, Prediction & Control Date: 3-6 August 2015 Location: Melbourne, Australia Website: www.iwsp7.org<http://www.iwsp7.org> The IWSP series of conferences bring together researchers across multiple disciplines to focus on epilepsy research. This conference will centre on the engineering and science of epilepsy from basic mechanisms and imaging, to computational modelling for analysis and prediction, through to feedback control of epilepsy. Invited Speakers: Samuel Berkovic, University of Melbourne, Australia (Genetics and individual-specific nature of epilepsy) Bin He, University of Minnesota, USA (EEG-based imaging to localise seizure and high frequency activity) Louis Lemieux, University College London, UK (Multi-modal imaging of human epileptic zone and networks) Martha Morrell, Stanford University, Neuropace, USA (Responsive seizure control and clinical implications) John Terry, University of Exeter, UK (Modelling multiscale brain networks: seizure initiation, evolution and prediction) Gregory Worrell, Mayo Clinic, USA (Forecasting epileptic seizures in dogs) Please forward this notice to anyone that you think might be interested. We look forward to seeing you at the meeting! On behalf of the local organizing committee Levin Kuhlmann, PhD David B. Grayden, PhD Mark J. Cook, MD Dean R. Freestone, PhD Alan Lai, PhD Elma O'Sullivan-Greene, PhD Andre Petersen, BSc(hons) Email: organizingcommittee(a)iwsp7.org<mailto:organizingcommittee@iwsp7.org>

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Wanted: neurotheory postdoc, to catch fireflies
by Xaq Pitkow Aug. 6, 2014

Aug. 6, 2014

POSITION: Xaq Pitkow's Computational Neuroscience group jointly at Rice University and the Baylor College of Medicine, in Houston, Texas, is seeking a highly motivated postdoctoral researcher who will develop theory and analyses of dynamic neural representations in animal brains. This is for a newly funded project to test how neural computations enable animals to catch fireflies in a virtual reality environment. The project will require multiple interlocking theoretical components and hands-on engagement with neural data analysis. We aim to understand the interplay between vision, spatial navigation, and decision-making in the face of uncertainty during a naturalistic, continuous-time task. LAB ENVIRONMENT: Our research focuses on computational functions of neural networks, especially how they compute properties of the world using ambiguous sensory evidence. A few related topics include: distributed neural representations, biological algorithms for statistical inference, and computation by nonlinear recurrent networks. This project is a close collaboration with the labs of Dora Angelaki, Greg DeAngelis, and Paul Schrater, all highly quantitative researchers in behavioral and cognitive neuroscience. QUALIFICATIONS: Important selection criteria include strong mathematical skills, practical knowledge of machine learning tools, and past research accomplishments. Applicants must have a Ph.D. in a relevant quantitative discipline, e.g. physics, math, machine learning, or statistics. Previous experience with neurobiology is advantageous but not essential. APPLYING: Applicants should email a letter of research interests and CV to Xaq Pitkow (xaq(a)rice.edu) The position is available immediately, and we look forward to reviewing applications as they arrive.

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Postdoc position in machine/biological vision – Serre lab, Brown University (Providence, RI)
by Thomas Serre Aug. 5, 2014

Aug. 5, 2014

The computational vision research group, headed by Dr. Thomas Serre at Brown University, has an opening for a postdoctoral fellow to work at the interface between computational neuroscience and computer vision. In particular, we are looking for computer scientists interested in the development of novel machine learning / computer vision algorithms derived from high-fidelity representations of cortical microcircuits to achieve human-like performance on complex information processing tasks. Candidates are expected to have a solid background in modern computer vision and machine learning methods and in particular, strong expertise in optimization techniques and deep learning methods. An interest in biological vision and applications of computer vision to the biological sciences would also be a strong plus. The initial appointment is for 12 months, renewable for another year, and potentially longer depending on funding. The start date is negotiable though an early start is strongly preferred. Salary is commensurate with experience and is competitive. Representative recent work related to the project: D. Reichert & T. Serre. Neuronal synchrony in complex-valued deep networks. International Conference on Learning Representations, 2014 T. Serre and T. Poggio. Reverse-engineering the brain. In: the Communications of the Association for Computing Machinery (CACM), 53(10), pp. 54-61, Oct 2010 Research group: Our research group is located within the Department of Cognitive Linguistic & Psychological sciences at Brown University. We maintain strong ties with the neuroscience, computer science, engineering and applied math departments as part of the Brain Institute. Through Brown’s Center for Computation and Visualization (https://www.ccv.brown.edu) our group has access to a state-of-the-art computing facility with includes over 300K GPU cores and over 500 Teraflops of GPU computing power. Information about Dr. Serre and his research group can be found at http://serre-lab.clps.brown.edu . Requirements: Applicants are expected to have finished, or be about to finish their Ph.D. degrees. They must have a strong background in computer vision and/or machine learning, with a track record of relevant publications at top venues (such as NIPS, CVPR, ICCV, ICML or ECCV). Excellent programming skills are required (C/C++/Matlab/Python). Programming experience in CUDA and/or parallel computing would be a strong plus. Application: Please send your applications by email to serre-admin(a)correct_university_name.edu where correct_university_name should be replaced by brown. Please include a brief statement of interests, a curriculum vita, a list of publications and contact details for 2-3 letters of reference (no letters required at this stage).

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Two Postdoctoral Positions in Computational Modeling of Primate Motor Control
by Ilya Rybak Aug. 4, 2014

Aug. 4, 2014

=============== Two postdoctoral/research associate positions in computational neuroscience for the duration of up to three years are available in the externally funded project focusing on multiscale computational modeling of motor control mechanisms, involving interactions between basal ganglia, thalamus, cerebellum, cortex, and spinal cord in connection with realistic simulation of pathological changes in motor control during Huntington’s disease. This collaborative project is performed jointly by the groups of Drs. Ilya Rybak (Dept. of Neurobiology and Anatomy, Drexel University, Philadelphia, PA, USA) and Yaroslav Molkov (Dept. of Mathematical Science, Indiana University – Purdue University, Indianapolis, IN, USA). Applicants must have a PhD degree in Neuroscience, Applied Mathematics, Physics, or a related discipline and have excellent C++ programming skills. Previous experience in computational neuronal modeling is a plus. Interested candidates are encouraged to contact Dr. Rybak (rybak(a)drexel.edu) or Dr. Molkov (ymolkov(a)iupui.edu) by email. To apply, please send an email along with (1) curriculum vitae; (2) a cover letter describing previous research experience and interests; (3) the names and contact information of three references. ================================= Ilya A. Rybak, Ph.D. Professor Department of Neurobiology and Anatomy Drexel University College of Medicine 2900 Queen Lane Philadelphia, PA 19129 USA Tel.: (215) 991-8596 FAX: (215) 843-9082 E-mail: rybak(a)drexel.edu http://neurobio.drexelmed.edu/rybakweb/rybak.html http://www.drexelmed.edu/Home/AboutOurFaculty/IlyaARybak.aspx https://www.researchgate.net/profile/Ilya_Rybak/publications/ http://scholar.google.com/citations?hl=en&user=SnA068QAAAAJ http://www.pubfacts.com/author/Ilya+A+Rybak Yaroslav Molkov, Ph.D. Assistant Professor Indiana University - Purdue University Indianapolis Department of Mathematical Sciences 402 N. Blackford St, LD 270, Indianapolis, IN 46202 Office: LD 224U Phone: (317) 274-6934 Fax: (317) 274-3460 Email: ymolkov(a)iupui.edu

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Tenure Track Assistant Professor of Cognitive Psychology
by Aaron Seitz Aug. 4, 2014

Aug. 4, 2014

The Department of Psychology,University of California, Riverside, invites applications for a tenure-track Assistant Professor position in Cognitive Psychology, beginning July 1, 2015. We seek applicants whose research examines language learning, at any time scale, and/or bilingualism. The ideal candidate will contribute to our emerging emphasis in experience- dependent change. Applicants should demonstrate a record of research excellence using methodological approaches involving human behavior, neuroimaging, and/or computational modeling. Applicants should be committed to excellence in undergraduate and graduate education. The Ph.D. degree is required at time of hire. Salary will be commensurate with education and experience. Review of completed applications begins October 10, 2014 and continues until the position is filled. Interested candidates should send a cover letter describing research and teaching interests, their curriculum vitae, reprints and preprints, and arrange to have three letters of recommendation provided, all using the following link: https://aprecruit.ucr.edu/apply/JPF00159. Questions about the position should be directed to Professor Christine Chiarello, Chair, Cognitive Area Search Committee, at christine.chiarello(a)ucr.edu. The Riverside campus of the University of California is growing rapidly and has an excellent psychology department with a strong record of success in research, teaching and extramural funding. For information on the Department of Psychology, see our web site at: http://www.psych.ucr.edu. The campus is centrally located in Southern California, about 50 miles east of Los Angeles and less than an hour's drive from the area's mountains, deserts and beaches. The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, protected veteran status, or any other characteristic protected by law. *Note Applicants who use Interfolio may utilize a feature provided by the Interfolio Service to allow Interfolio to upload their letters directly into AP Recruit without bothering the letter writer. Applicants can input an Interfolio-generated email address in place of their letter writer¹s email address. Interfolio refers to this as online application deliveries. The following link on the Interfolio website shows how to set this up: http://help.interfolio.com/entries/24062742-Uploading-Letters-to-an-Online- application-System ************************************************** Aaron Seitz, Ph.D. Professor Department of Psychology University of California, Riverside 900 University Ave. Riverside, CA 92521 Ph: (951) 827-6422 Fax: (951) 827-3985 Email: aseitz(a)ucr.edu Web: http://faculty.ucr.edu/~aseitz/ **************************************************

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Call for Papers: Tha ICIISCT2015 Conference in India
by Grace Allas Aug. 2, 2014

Aug. 2, 2014

[My apology for receiving multiple copies] ----------------------------------------------------------------- http://sdiwc.net/conferences/iciisct2015/ *International Conference on Innovations in Intelligent Systems and Computing Technologies (ICIISCT2015)* September 18-20, 2015 Rajasthan Vidyapeeth (D) University, India Udaipur, Rajasthan, India All registered papers will be included in SDIWC Digital Library. ============================================================== The conference aims to enable researchers build connections between different digital applications. The event will be held over three days, with presentations delivered by researchers from the international community, including presentations from keynote speakers and state-of-the-art lectures. RESEARCH TOPICS ARE NOT LIMITED TO: - Information and Data Management - Social Networks - Data Compression - Information Content Security - E-Technology - Mobile, Ad Hoc and Sensor Network Management - E-Government - Web Services Architecture, Modelling and Design - E-Learning - Semantic Web, Ontologies - Wireless Communications - Web Services Security - Mobile Networking, Mobility and Nomadicity - Quality of Service, Scalability and Performance - Ubiquitous Computing, Services and Applications - Self-Organizing Networks and Networked Systems - Data Mining - Data Management in Mobile Peer-to-Peer Networks - Computational Intelligence - Data Stream Processing in Mobile/Sensor Networks - Biometrics Technologies - Indexing and Query Processing for Moving Objects - Forensics, Recognition Technologies and Applications - Cryptography and Data Protection - Information Ethics - User Interfaces and Usability Issues form Mobile Applications - Fuzzy and Neural Network Systems - Mobile Social Networks - Signal Processing, Pattern Recognition and Applications - Peer-to-Peer Social Networks -Image Processing - Sensor Networks and Social Sensing - Distributed and parallel applications - Social Search - Internet Modeling - Embedded Systems and Software - User Interfaces,Visualization and Modeling - Real-Time Systems - XML-Based Languages - Multimedia Computing - Network Security - Software Engineering - Remote Sensing Researchers are encouraged to submit their work electronically. All papers will be fully refereed by a minimum of two specialized referees. Before final acceptance, all referees comments must be considered. Paper Submission: http://sdiwc.net/conferences/iciisct2015/openconf/openconf.php IMPORTANT DATES: Submission Deadline : open from now until August 18, 2015 Notification of Acceptance : 2 - 4 weeks from the submission date Camera Ready Submission : September 05, 2015 Registration Date : September 05, 2015 Conference Dates : September 18-20, 2015 Contact email: : iciisct2015(a)sdiwc.net

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PhD position
by Lendasse, Amaury Aug. 1, 2014

Aug. 1, 2014

One PhD student position available (Research Assistant and Teaching Assistant) Topic: Machine Learning for Big Data Where: Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, Iowa, USA (http://www.engineering.uiowa.edu/mie) Starting date: January 15th 2015 Requirements: Applicants should have a keen interest in Machine Learning and hold a Master or equivalent degree in a relevant field such as Computer Science, Industrial Engineering, or Mathematics. The candidate should have excellent programming skills (e.g. Matlab, Python, C/C++) and good analytic skills. Experience with Big Data in Machine Learning (e.g., Hadoop, MapReduce, GPU computing,...), Data Mining and Data Analysis (time series analysis, visualization,...) are a plus. Minimum TOEFL Score Requirements: a score of 600 or higher on the paper-based (PBT) version of the test, or a score of 100 or higher on the Internet-based version of the test (iBT). The selected candidate will then apply officially to the UIOWA: http://www.engineering.uiowa.edu/mie/graduate-program/industrial-engineerin… Interested candidates are encouraged to contact Associate Prof. Lendasse (amaury-lendasse(a)uiowa.edu) by email. To apply, please send an email (subject: PhD Position MIE IOWA) along with a SINGLE PDF file including: (1) a cover letter describing previous experiences and interests (maximum 1 page) (2) Curriculum Vitae (maximum 2 pages) (3) academic transcripts (4) the names and contact information of two or three references (maximum 1 page) (5) Skype Name Application Deadline: August 17th 2014 Amaury Lendasse, Associate Professor Department of Mechanical and Industrial Engineering 2403 Seamans Center for the Engineering Arts and Sciences The University of Iowa Iowa City, Iowa, 52242, USA email: amaury-lendasse(a)uiowa.edu WWW: http://www.engineering.uiowa.edu/mie/faculty-staff/amaury-lendasse

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Kind Reminder:: CFP:: 3rd ICIEIS2014- Poland
by The Third International Conference on Informatics Engineering and Information Science (ICIEIS2014) Aug. 1, 2014

Aug. 1, 2014

| Please accept our apology for multiple posting. THANK YOU | +-----------------------------------------------------------+ The Third International Conference on Informatics Engineering and Information Science (ICIEIS2014) Lodz University of Technology, Lodz, Poland September 22-24, 2014 http://sdiwc.net/conferences/2014/icieis2014/ ============================================================================ The proposed conference will be held at Lodz University of Technology Lodz, Poland from September 22-24, 2014 which aims to enable researchers to build connections between different digital applications. The conference welcomes papers on the following (but not limited to) research topics: - Real-Time Systems - Software Engineering - Biometrics Technologies - Mobile Social Networks - Information Ethics - Information Content Security - Information and Data Management - Network Security - Social Networks - Wireless Communications - Information Propagation on Social Networks Researchers are encouraged to submit their work electronically. All papers will be fully refereed by a minimum of two specialized referees. Before final acceptance, all referees comments must be considered. Important Dates ============================================================================ Submission Date : Open from now until August 20, 2014 Notification of acceptance: 2-3 weeks from the submission date Camera Ready submission : Sept. 12, 2014 Registration : Sept. 12, 2014 Conference dates : Sept. 22-24, 2014

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Open Position: Software Developer in Neuroinformatics at LMU Munich
by Thomas Wachtler July 31, 2014

July 31, 2014

At the German Neuroinformatics Node (G-Node, http://www.g-node.org) Ludwig-Maximilians-Universität München, a full-time position is available to join the G-Node team in developing neuroinformatics solutions for data management in neurophysiology. Variety and complexity of data in this field bring the challenge of large-scale data access, consistent storage and efficient data analysis. G-Node is interacting closely with research labs to address these challenges with state of the art neuroinformatics methods. Current developments include a data sharing platform and tools for metadata management and data annotation. G-Node is part of the Bernstein Network Computational Neuroscience (http://nncn.de) is collaborating with the International Neuroinformatics Coordination Facility (INCF, http://incf.org) Secretariat and other INCF National Nodes, and is involved in teaching and training activities. The position involves working in a small team of developers within a lively neuroscience environment, with ample opportunities for bridging between neuroscience research and neuroinformatics. Tasks will include contributing to the development and enhancement of G-Node tools and services (http://www.g-node.org/tools-and-services) working closely with neuroscience laboratories that use, or plan to use, neuroinformatics solutions. Candidates should have excellent programming skills, preferably in Python and C++ or Java, knowledge about relational databases, the ability to work in a team, and a strong interest in the development of novel open-source solutions for neuroscience. Experience in further fields of relevance, such as web development (Javascript, HTML/CSS, web frameworks), semantic web technologies, scientific software and analysis, experimental or computational neuroscience, would be beneficial. The position is available immediately, salary level is according to TV-L, duration is one year with possibility of extension. Severely disabled applicants will be given preference in case of equal qualification. Applications by women are specifically encouraged. Applications should include CV, statement of experience and motivation, and names of referees. Informal inquiries prior to application are welcome. Applications will be accepted until the position is filled. Applications should be sent, preferably as pdf file by email, to Thomas Wachtler <wachtler(a)bio.lmu.de> -- Dr. Thomas Wachtler <wachtler(a)bio.lmu.de> Scientific Director German Neuroinformatics Node Department Biology II Ludwig-Maximilians-Universität München Grosshaderner Str. 2 82152 Planegg-Martinsried Germany

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Postdoctoral Position in Computational Motor Control
by Jon Sensinger July 31, 2014

July 31, 2014

A postdoctoral position in computational motor control is available to apply optimal control and computational motor control methods to improve the control, sensory feedback, and outcome measures used in prosthetics. The successful applicant will join an interdisciplinary team at the University of New Brunswick’s Institute of Biomedical Engineering that includes scientists, clinicians, and engineers focused on improving clinically viable prostheses and exoskeleton design and control. He or she will be expected to leverage research from the broader neuroscience research community to develop computational approaches for addressing real-world problems, and will have the opportunity to interact on a daily basis with patients. This collaborative project is performed jointly by the groups of Drs. Jon Sensinger (Institute of Biomedical Engineering, University of New Brunswick, Canada) Levi Hargrove (Center for Bionic Medicine, Rehabilitation Institute of Chicago, USA), and Konrad Kording (Northwestern University, Chicago USA). A layman’s overview of the project is video-scribed here: https://www.youtube.com/watch?v=eEzbuiJi0T0 Applicants must have a PhD degree in Neuroscience, Applied Mathematics, Physics, or a related discipline and have excellent Matlab programming skills. Previous experience in computational motor control or optimal control is a plus. Interested candidates are encouraged to contact Dr. Sensinger (j.sensinger(a)unb.ca<mailto:j.sensinger@unb.ca>) by email. To apply, please send an email along with (1) curriculum vitae; (2) a cover letter describing previous research experience and interests; (3) the names and contact information of three references. Dr. Sensinger will be available to answer questions and discuss this job opportunity with potential candidates at the EMBC 2014 meeting in Chicago, USA (August 27-30). Jon Sensinger, PhD Associate Director, Institute of Biomedical Engineering Associate Professor, Electrical and Computer Engineering University of New Brunswick http://www.ece.unb.ca/jsensing Twitter: @jsensinger LinkedIn: http://www.linkedin.com/pub/jon-sensinger/9a/1b2/a09

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[meetings] ICANN 2014 - Final Program and Call for Participation
by Stefan Wermter July 31, 2014

July 31, 2014

------------------------------------------------------------------- Call for Participation and Conference Program ICANN 2014: 24th Annual Conference on Artificial Neural Networks 15 - 19 September 2014, University of Hamburg, Germany http://icann2014.org/ =================================================================== We invite you to attend the 2014 International Conference on Artificial Neural Networks (ICANN), which is the annual flagship conference of the European Neural Network Society (ENNS). In 2014 the University of Hamburg will organize the 24th ICANN Conference from 15th to 19th September 2014 in Hamburg, Germany. CONFERENCE PROGRAM: The main conference program is now available. The program includes 72 oral presentations, 33 posters and 2 live Demonstrations. http://icann2014.org/program/ REGISTRATION: The ICANN 2014 registration is open. The full registration costs 490 € and 390 € for students. ENNS members pay a reduced rate of 440 €, and 340 € for students. The registration includes access to scientific sessions and plenary talks, coffee breaks during the main conference, welcome event, conference dinner, one copy of the proceedings (USB), one conference bag. Additional tickets for the conference dinner can be purchased for 70 €. http://icann2014.org/registration/ VENUE AND TRANSPORTATION: Hamburg is the second-largest city in Germany, home to over 1.8 million people. Situated at the river Elbe, the port of Hamburg is the second-largest port in Europe. The University of Hamburg is the largest institution for research and education in the north of Germany. The venue of the conference is the ESA building of the University of Hamburg, situated at Edmund-Siemers-Allee near the city centre and easily reachable from Dammtor Railway Station. Hamburg Airport can be reached easily via public transport. ACCOMMODATION: For the accomodation we arranged guaranteed rates for a couple of hotels in Hamburg for ICANN 2014. http://icann2014.org/accommodation/ CHAIRS and ORGANISATION: General Chair: Stefan Wermter (Hamburg, Germany) Program co-Chairs Alessandro E.P. Villa (Lausanne, Switzerland, ENNS President) Wlodzislaw Duch (Torun, Poland, ENNS Past-President) Timo Honkela (Helsinki, Finland) Petia Koprinkova-Hristova (Sofia, Bulgaria) Günther Palm (Ulm, Germany) Cornelius Weber (Hamburg, Germany) Local Organizing Committee Chairs: Sven Magg, Johannes Bauer, Jorge Chacon, Stefan Heinrich, Doreen Jirak, Katja Koesters, Erik Strahl KEYNOTE SPEAKERS: Christopher M. Bishop (Microsoft Research, Cambridge, UK) Jun Tani (KAIST, Daejeon, Republic of Korea) Paul Verschure (Universitat Pompeu Fabra, Barcelona, Spain) Yann LeCun (New York University, NY, USA) Barbara Hammer (Bielefeld University, Bielefeld, Germany) Kevin Gurney (University of Sheffield, Sheffield, UK) CONFERENCE TOPICS: ICANN 2014 will feature the main tracks Brain Inspired Computing and Machine Learning research, with strong cross-disciplinary interactions and applications. All research fields dealing with Neural Networks will be present at the conference. A non-exhaustive list of topics includes: Brain Inspired Computing: Cognitive models, Computational Neuroscience, Self-organization, Reinforcement Learning, Neural Control and Planning, Hybrid Neural-Symbolic Architectures, Neural Dynamics, Recurrent Networks, Deep Learning. Machine Learning: Neural Network Theory, Neural Network Models, Graphical Models, Bayesian Networks, Kernel Methods, Generative Models, Information Theoretic Learning, Reinforcement Learning, Relational Learning, Dynamical Models. Neural Applications for: Intelligent Robotics, Neurorobotics, Language Processing, Image Processing, Sensor Fusion, Pattern Recognition, Data Mining, Neural Agents, Brain-Computer Interaction, Neural Hardware, Evolutionary Neural Networks. CONFERENCE WEBSITE: http://www.icann2014.org *********************************************** Professor Dr. Stefan Wermter Chair of Knowledge Technology Department of Computer Science University of Hamburg Vogt Koelln Str. 30 22527 Hamburg, Germany http://www.informatik.uni-hamburg.de/~wermter/ http://www.informatik.uni-hamburg.de/WTM/ ***********************************************

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FINAL CALL for Goettingen's 12th annual comp-neuro summer course. DEADLINE: Aug. 6th.
by Maximilian Puelma Touzel July 29, 2014

July 29, 2014

Final call for applicants to apply to the 12th summer course on COMPUTATIONAL NEUROSCIENCE in Göttingen, Germany September 08th - 12th, 2014 Organized by Agostina Palmigiano, Joscha Liedtke and Maximilian Puelma-Touzel Sponsored by -the Bernstein Centre for Computation Neuroscience, Göttingen -the International Max Planck Research School for the Physics of Biological and Complex Systems -the Goettingen Graduate School for Neurosciences, Biophysics, and Molecular Biosciences ______________________________ The course is intended to provide graduate students and young researchers from within and outside of neuroscience with working knowledge of theory and analysis methods used in the field and to acquaint them with recent developments therein. The focus of this year's course is modelling and theory of neuronal ensembles. The course includes tutorials and lectures from the following researchers: * Carl Van Vreesijk, Universite Rene Descartes, Paris, France * Claudia Clopath, Imperial College London, London, England * Srdjan Ostojic, École Normale Supérieure, Paris, France * Gasper Tkacik, Institute of Science and Technology, Vienna, Austria * Alfonso Renart, Champalimaud Centre for the Unknown, Lisbon, Portugal The course takes place at the Department of Nonlinear Dynamics of the Max-Planck Institute for Dynamics and Self-Organization, Göttingen. A course fee of 100 Euro includes participation in the tutorials, study materials, and part of the social events. The number of participants is limited to 30. Course language is English. To apply please fill out the application form at: http://www.bccn-goettingen.de/events/cns-course by *August 6, 2014* Best wishes and looking forward to seeing you in Göttingen, Max Puelma Touzel (on behalf of the organizers) Max Planck Institute for Dynamics and Self-Organization Fassberg 17, 37077 Goettingen, Germany +49 551 5176 444 Office +49 (0)176 6 876 2821 Mobile mptouzel(a)nld.ds.mpg.de www.nld.ds.mpg.de

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Postdoc in computational neuroscience
by Joaquín Navajas July 29, 2014

July 29, 2014

Post doc in computational neuroscience (Centre for Systems Neuroscience - University of Leicester, UK) Spike sorting is the classification of single neurons from extra cellular recordings based on their spike shapes. The main focus of your research will be the study and implementation of optimal spike detection and sorting techniques. For this you will study different techniques to improve the spike detection and sorting results and will then implement these advances in a graphic user interphase and in batch codes to run in matlab. Link for more details: http://www.le.ac.uk/jobs/external/SEN00493_Job_Summary.pdf <https://email.le.ac.uk/owa/redir.aspx?C=6xLmoEDA8kadrrcI2z0-IpKjtXikftEISUM…> Informal enquiries are welcome and should be made to Sue Atkinson, Research Centre Manager, sam45(a)le.ac.uk <https://email.le.ac.uk/owa/redir.aspx?C=RXnrNoZO4k-7v7qrCHbb4FuwAk44fdEIFNi…> or 0116 252 3249

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CNS workshop
by Jonathan Rubin July 28, 2014

July 28, 2014

Dear Comp-Neuro members who are attending the CNS*2014 meeting, We are happy to invite you attend the workshop “Dynamics of Disease States” that will take place on Wednesday, July 30th at the CNS*2014 meeting in Quebec. The workshop will be held in room 2104A and the full program is available at: http://wwwhome.math.utwente.nl/~gilssa/cns2014/?page=program best regards, Stephan van Gils and Jon Rubin

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Columbia+Janelia postdoc positions: zebrafish computational neuroscience and machine learning
by Liam Paninski July 28, 2014

July 28, 2014

Colleagues, Will you please circulate this postdoc ad amongst your students or anyone else who might be interested: http://grossmancenter.columbia.edu/zebrafish.html? Thank you. Liam Paninski ------------------------------------------------------------------------------------------ Postdoctoral position in large-scale computational neuroscience A full-time postdoctoral position is available immediately, jointly between Columbia University's Grossman Center for the Statistics of Mind and HHMI's Janelia Research Campus. The aim is to understand whole-brain activity at the cellular level using large-scale computational methods. The position is co-supervised by Liam Paninski, John Cunningham and Larry Abbott (at Columbia) and Jeremy Freeman and Misha Ahrens (at Janelia Research Campus) and is centered around understanding the dynamics of all neurons in the brain of behaving larval zebrafish. We use light-sheet imaging to record simultaneously from most of the ~10^5 neurons during behavior, and use large-scale cluster computing and machine learning, statistics, and modeling to gain insight into how brain-wide network dynamics underlies behavior. The position will be based at Columbia University and HHMI Janelia Research Campus, and we will encourage applicants to spend time at both campuses. Requirements: Qualifications include primarily a strong research portfolio in computational neuroscience, statistical neuroscience, machine learning, or a related field. Backgrounds in analyzing large neural datasets, modeling complex neural systems, and in cutting-edge machine learning will be particularly valuable. These positions are highly quantitative and highly interdisciplinary; applicants should have a PhD in Electrical Engineering, Statistics, Machine Learning, Physics, Applied Mathematics, or Computational Neuroscience. Appointment: The initial appointments will be for one year, and are renewable. Salaries will be set based on experience and skills. Applicants should send an email to zebrafish.computation(a)gmail.com providing: 1. a one-page description of past research experience 2. a one-page description of future research interests and goals 3. a resume of educational and research experience, including publications 4. names of three people who could provide letters of reference All materials should be in pdf or plain text. Applications will be reviewed as they arrive until the positions are filled; interested candidates are encouraged to express their interest early. Due to demand, we may not be able to reply to all applications.

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ONLY FOR STUDENTS - 2 weeks mini computational neuroscience freelance project for students from home
by Robert Schindle July 28, 2014

July 28, 2014

Hello All, We are currently working on a project in the field of computational neuroscience which requires some help with analyzing data and documenting the research within the next 2 weeks. We are looking for someone with good c++ and Python skills. You will be compensated accordingly. If you are interested please contact us immediately so that we can discuss other details and start the work immediately. Thanks a lot, Robert Schindle.

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Postdoctoral Position- Arizona
by Jean-Marc July 26, 2014

July 26, 2014

The Computational and Experimental Neuroscience Laboratory is looking to fill a position for a Postdoctoral Research Fellow. The research project is geared towards understanding the role of awake hippocampal replay in spatial navigation. The techniques used include high density electrophysiology in the behaving rat. The project is multidisciplinary and involves collaboration with a robotics team (University of Florida, Tampa) and a computational neuroscience team (INSERM, Lyon, France). Good communication skills are necessary. This position is appropriate for a computational neuroscientist with some experimental background interested in branching out to experimental neuroscience. Applicants with a subset of the following skill set are strongly encouraged to apply: - Scientific expertise or interests in hippocampus and/or prefrontal-cortex - Electrophysiology (in vivo chronic behaving or in vitro) - Behavioral Neuroscience (rat training/testing) - General laboratory skills (e.g. histology, surgery) - Matlab programming and spike-data analyses Applicant should send a cover letter, CV and the names of at least 2 references to Dr. Jean-Marc Fellous (fellous(a)email.arizona.edu) The search is ongoing and is projected to be completed by October 30th, 2014. Information about the laboratory can be found at: http://amygdala.psychdept.arizona.edu/lab.html The CENL and the University of Arizona are committed to maintaining a diverse and inclusive work environment and women and minorities are encouraged to apply. The University of Arizona is an equal opportunity, affirmative action employer.

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Postdoctoral positions: Memory, motor, & learning dynamics
by Mark Goldman July 25, 2014

July 25, 2014

Two theoretical postdoctoral positions and 1-2 collaborative experiment-theory positions are available in the laboratory of Dr. Mark Goldman at the University of California at Davis.The lab works on a broad range of problems in computational neuroscience ranging from neural coding to dynamics and plasticity of single neurons and networks. Immediate funding is available for a range of projects related to working memory, neural integration, motor learning, and synaptic plasticity as described below.The postdoctoral candidate also would have flexibility to work on a range of issues of his or her choosing.Candidates are expected to have strong training in an analytically rigorous discipline such as theoretical neuroscience, physics, mathematics, computer science, or engineering.The postdoctoral candidate will have ample opportunity to interact within the vibrant computational and systems neuroscience communities at UC Davis and the greater San Francisco Bay Area. Candidates should send a CV, brief statement of previous research and future research interests, and contact information for three references to: Mark Goldman, msgoldman(a)ucdavis.edu. Specific positions with funding include: 1) *Theoretical positions:Dynamics of memory and motor-related neural activity* /Challenging the attractor picture of working memory/.In the traditional attractor picture of working memory, memory storage results from positive feedback processes that lead to the formation of self-sustained attractors.In one project, we are exploring how functionally feedforward, rather than feedback, network architectures can generate flexible codes for storing memories and producing a broad range of input-output transformations.In a second project, we are utilizing methods from engineering control theory to show how balanced cortical networks can utilize negative feedback to stabilize persistent patterns of neural activity. /Multi-scale modeling of neural integration./The oculomotor neural integrator, which transforms eye-velocity encoding motor commands into eye-position encoding commands, is a model system for understanding the mathematical integration of inputs and the maintenance of memory-storing activity.We seek to determine the respective roles of cellular and circuit mechanisms of memory storage in this system.Multi-scale models, from ion channels to behavior, will be generated based upon electrophysiological and optical imaging recordings and optogenetic manipulations performed in our experimental collaborators' laboratories. /Context-dependent memory storage./Recent experiments suggest that the oculomotor neural integrator functions in a context-dependent manner, producing spatially distinct activity patterns depending upon whether eye movements are being made in the context of rapid changes in gaze (saccades) versus smooth tracking of moving objects.We seek to determine the circuit mechanisms underlying this context-dependent activity and to propose general frameworks, applicable to both oculomotor and cortical memory systems, for how multiple context-dependent inputs can be separately stored in a single network. /Role of the granule cell layer in cerebellar motor learning./The eye movement system provides a highly tractable setting for studying motor learning because it is well-characterized experimentally and has fewer degrees of freedom than more complicated movement systems.In collaboration with whole-circuit optical imaging and optogenetic perturbation experiments in the Aksay laboratory at Cornell Medical University and genetic manipulations, electrophysiological recording, and optogenetic perturbations in Jennifer Raymond's laboratory at Stanford University, we are modeling the neural dynamics and coding of cerebellar granule neurons and their relation to Purkinje cell firing and the plasticity of eye movement behaviors. 2) *Experimental positions:* *Development, dynamics, and plasticity of neural networks: *In collaboration with Kim McAllister (kmcallister(a)ucdavis.edu <mailto:kmcallister@ucdavis.edu>), we are seeking to understand the learning rules underlying development and learning in neural networks. We will use cutting-edge technology in patterned substrates, optogenetics, and uncaging in a novel long-term imaging assay for synapse dynamics that allows recording and single synapse or single cell manipulation of neuronal and network activity. These cultured networks will be used to directly test central tenets of Hebbian, spike-timing dependent, and homeostatic learning over development. The applicant will perform these imaging experiments as well as apply theoretical models to better understand and predict our results. *Dynamics of memory and motor-related neural activity:*There are also possibilities for joint experimental-theoretical work with Emre Aksay's laboratory at Weill Medical College of Cornell University (in New York City) on either oculomotor memory storage or cerebellar motor learning, using /in vivo/ two-photon optical recording and stimulation to dissect circuit function and plasticity.Interested candidates should contact Dr. Aksay at ema2004(a)med.cornell.edu <mailto:ema2004@med.cornell.edu>.

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PhD Position in Brain-Inspired Computing (Theory)
by Mihai A. Petrovici July 25, 2014

July 25, 2014

The Kirchhoff-Institut für Physik at the Ruprecht-Karls-Universität Heidelberg (Germany) has an immediate opening for a * PhD Position in Brain-Inspired Computing (Theory)* The position is located in the Electronic Vision(s) Lab of Prof. Karlheinz Meier. The group develops large-scale hardware for brain-inspired computing and investigates novel theoretical paradigms of neural computation. The Heidelberg group works on the development of brain-inspired electronic circuits, so-called neuromorphic systems. These systems implement physical models of neurons and synapses in-silico, with fully configurable parameters and connectivity. Throughout a series of international projects, the hardware systems have evolved from single chips to wafer-scale devices with hundreds of thousands of neurons (Schemmel et al., 2010) and are planned to be further scaled up in the framework of the EU Human Brain project (HBP). The configurability of these systems fosters their use as general-purpose emulation devices for neuroscientific research (Pfeil et al., 2013). Their intrinsic parallelism, low power consumption and high acceleration sets them apart from conventional computing architectures. The heterogeneity of neuromorphic substrates requires novel theoretical approaches (Petrovici et al., 2014). The Heidelberg group is also involved in theoretical research and modeling of spike-based computational principles. In particular, the use of stochasticity for Bayesian inference is a major focus. These models provide useful architectures for machine learning, while at the same time advancing the study of possible computational paradigms in the mammalian neocortex (Petrovici et al., 2013). The successful candidate will join the theory and modeling section of the group in developing new stochastic models that exploit the heterogeneity of the hardware substrate, thereby benefitting from its significant speed advantage over conventional simulators. ------------------------------------------ Candidates are expected to hold a Masters degree or equivalent in Physics, Mathematics, Computer Science or a related discipline. Knowledge in neuroscience is not required but would be an advantage. The candidates should have a deep interest in theoretical and computational neuroscience, as well as excellent mathematical abilities. An important part of their work will consist in acquiring new skills from various fields of neuroscience, as required by the interdisciplinary nature of the research topic. The successful candidates will use complex simulation software and are therefore required to have very good programming skills. ------------------------------------------ Applications should addressed to Prof. Karlheinz Meier (meierk(a)kip.uni-heidelberg.de) and Mihai Petrovici (mpedro(a)kip.uni-heidelberg.de) including the following information in a single pdf-file : - Statement of research - CV - Two names (with email addresses) of suggested referees - Copies of university degrees and additional certificates - URLs of master /diploma) thesis and related publications

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CNS*14 Tutorial on Neuronal Model Parameter Search Techniques
by Cengiz Günay July 24, 2014

July 24, 2014

Dear colleagues, You are invited to attend our shortly upcoming full-day tutorial session at CNS*2014 in Quebec City. *Where:* Organization for Computational Neurosciences (OCNS) Conference, Quebec City Conference Center, Room 2105 *When:* Saturday July 26, 2014 between 9am - 4:30pm *T9: Neuronal Model Parameter Search Techniques* Parameter tuning of model neurons to mimic biologically realistic activity is a non‐trivial task. Multiple models may exhibit similar dynamics that match experimental data – i.e., there is no single “correct” model. To address this issue, the ensemble modeling technique proposes to represent properties of living neurons with a set of neuronal models. Several approaches to ensemble modeling have been proposed over the years, but the two most prevalent parameter tuning methods are systematic “brute‐force” searches [1, 2] and various evolutionary algorithms‐based techniques [3, 4, 5, 6]. Both approaches relay on traversing a very large parameter space (with thousands to millions of model instances), but utilize diametrically different ways to accomplish that. In both cases, however, entire collections of biologically realistic models are generated, whose neural activity characteristics can then be cataloged and studied using a database [1, 2]. The tutorial covers “tips and tricks,” as well as various pitfalls in all stages of model construction, large‐scale simulations on high performance computing clusters [S2], database construction and analysis of neural data, along with a discussion about the strengths and weaknesses of the two parameter search techniques. We will review software implementations for each technique: PANDORA Matlab Toolbox [7][S1] for the brute force method and NeRvolver (i.e., evolver of nerve cells) for evolutionary algorithms. PANDORA was used in recent projects for tuning models of rat globus pallidus neurons [2][M1], lobster pyloric network calcium sensors [8][M2], leech heart interneurons [9][M3,S3] and hippocampal O‐LM interneurons (Skinner Lab, TWRI/UHN and Univ. Toronto). NeRvolver is a prototype of a computational intelligence‐based system for automated construction, tuning, and analysis of neuronal models, which is currently under development in the Computational Intelligence and Bio (logical) informatics Laboratory at Delaware State University [10]. Through the utilization of computational intelligence methods (i.e., Multi‐Objective Evolutionary Algorithms and Fuzzy Logic), the NeRvolver system generates classification rules describing biological phenomena discovered during the process of model creation or tuning. Thus in addition to producing neuronal models, NeRvolver provides–via such rules–insights into the functioning of the biological neurons being modeled. In the tutorial, we will present basic functionalities of the system and demonstrate how to analyze the results returned by the software. We will allocate enough time for Q&A and if participants bring a laptop pre‐loaded with Matlab, they can follow some of our examples. *Lecturers/Organizers:* Cengiz Günay, Anca Doloc-Mihu (Emory University, USA) Vladislav Sekulić (University of Toronto, Canada), Tomasz G. Smolinski (Delaware State University, USA) *References * [1] Astrid A. Prinz, Cyrus P. Billimoria, and Eve Marder. Alternative to hand‐tuning conductance‐based models: Construction and analysis of databases of model neurons. J Neurophysiol, 90:3998–4015, 2003. [2] Cengiz Günay, Jeremy R. Edgerton, and Dieter Jaeger. Channel density distributions explain spiking variability in the globus pallidus: A combined physiology and computer simulation database approach. J. Neurosci., 28(30):7476–91, July 2008. [3] Pablo Achard and Erik De Schutter. Complex parameter landscape for a complex neuron model. PLoS Comput Biol, 2(7):794–804, Jul 2006. [4] Tomasz G. Smolinski and Astrid A. Prinz. Computational intelligence in modeling of biological neurons: A case study of an invertebrate pacemaker neuron. In Proceedings of the International Joint Conference on Neural Networks, pages 2964–2970, Atlanta, GA, 2009. [5] Tomasz G. Smolinski and Astrid A. Prinz. Multi‐objective evolutionary algorithms for model neuron parameter value selection matching biological behavior under different simulation scenarios. BMC Neuroscience, 10(Suppl 1):P260, 2009. [6] Damon G. Lamb and Ronald L. Calabrese. Correlated conductance parameters in leech heart motor neurons contribute to motor pattern formation. PLoS One, 8(11):e79267, 2013. [7] Cengiz Günay, Jeremy R. Edgerton, Su Li, Thomas Sangrey, Astrid A. Prinz, and Dieter Jaeger. Database analysis of simulated and recorded electrophysiological datasets with PANDORA’s Toolbox. Neuroinformatics, 7(2):93–111, 2009. [8] Cengiz Günay and Astrid A. Prinz. Model calcium sensors for network homeostasis: Sensor and readout parameter analysis from a database of model neuronal networks. J Neurosci, 30:1686–1698, Feb 2010. NIHMS176368,PMC2851246. [9] Anca Doloc‐Mihu and Ronald L. Calabrese. A database of computational models of a half‐center oscillator for analyzing how neuronal parameters influence network activity. J Biol Phys, 37(3):263–283, Jun 2011. [10] Emlyne Forren, Myles Johnson‐Gray, Parth Patel, and Tomasz G. Smolinski. Nervolver: a computational intelligence‐based system for automated construction, tuning, and analysis of neuronal models. BMC Neuroscience, 13(Suppl 1):P36, 2012. -Cengiz -- Cengiz Gunay Postdoctoral Fellow, Dept. of Biology Visiting Faculty, Dept. of Math & CS Emory University cgunay(a)emory.edu http://www.biology.emory.edu/research/Prinz/Cengiz/

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