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Postdoc in Warsaw - kernel-based method of electrophysiological source imaging

by Daniel Wójcik

https://neuroinflab.wordpress.com/jobs/ POSTDOCTORAL POSITION IN COMPUTATIONAL NEUROSCIENCE: kESI – kernel-based method of electrophysiological source imaging The Neuroinformatics Laboratory (https://neuroinflab.wordpress.com/) at the Nencki Institute of Experimental Biology (http://www.nencki.gov.pl) invites applications for a postdoctoral position (36 months). The goal of the project is to develop, implement and investigate a new technique of source localization of specific events in neural activity, such as a seizure, from multimodal imaging data, including ECoG (strip and grid electrodes), depth electrophysiological recordings, and MRI data from humans. The method will be validated with ground truth model data and tested on clinical data obtained from epilepsy patients. The fellow will build on already existing tools and techniques developed in the lab, see especially Potworowski et al. 2012 and Ness et al. 2015. The ideal candidate will have a strong computational background, experience in numerical solutions of PDEs, electrodynamics, computational neuroscience, or brain imaging. We can only accept candidates 0 to 7 years after reception of PhD. To apply or ask for further information send email to d.wojcik(a)nencki.gov.pl. Applications should include a CV, statement of research interests, and the names and full contact details of three referees. We are accepting applications until the position is filled. -- Prof. Daniel K. Wojcik Laboratory of Neuroinformatics, Head PhD Studies, Head Nencki Institute of Experimental Biology 3 Pasteur St, 02-093 Warsaw, Poland tel: (+48 22) 5892348 fax: (+48 22) 8225342 skype: danek8317 http://dwojcik.pl/ http://neuroinflab.wordpress.com/ http://orcid.org/0000-0003-0812-9872

Oct. 10, 2016

RAHA 2016 - Invitation and late Breaking Poster Session

by Dr. Shyam Diwakar

Dear Colleagues, Apologies for cross-posting. Amrita University, India at its backwater-nestled campus in Kollam, Kerala is set for RAHA 2016 - International Conference on Robotics and automation for Humanitarian Applications to be held from December 18-20, 2016. The organizers are calling in for late-breaking posters in robotics, neurorobotics, societal and humanitarian applications and related topics. We welcome you to submit content and showcase new studies in the fields of robotics and related topics. RAHA 2016 brings together top researchers, practitioners, and experts from the field of robotics for humanitarian applications. The conference will host 6 plenary and 16 keynote speakers from top universities and industry. Poster session Details: http://raha2016.org/call-for-abstracts-late-breaking-posters Conference website: http://raha2016.org Speakers: http://raha2016.org/speakers I look forward to meeting you in December. Shyam -- Shyam Diwakar, Ph.D. Amrita University http://www.amrita.edu/compneuro Disclaimer : The information transmitted in this email, including attachments, is intended only for the person(s) or entity to which it is addressed and may contain confidential and/or privileged material. Any review, retransmission, dissemination or other use of, or taking of any action in reliance upon this information by persons or entities other than the intended recipient is prohibited. Any views expressed in any message are those of the individual sender and may not necessarily reflect the views of Amrita University. If you received this in error, please contact the sender and destroy any copies of this information.

Oct. 8, 2016

Please post to the comp-neuro list

by McCormick, David

POSTDOCTORAL POSITIONS in Theoretical and Computational Neuroscience The Swartz Center in Theoretical Neurobiology at Yale University invites applications for two postdoctoral positions in Theoretical and Computational Neuroscience. We seek exceptional candidates with experience in computational and/or quantitative neuroscience to collaborate with computational/experimental biologists towards the understanding of the nervous system from the level of synapses to complex networks. The candidate may work in one or more laboratories of Jessica Cardin, Damon Clark, Michael Crair, George Dragoi, Thierry Emonet, Michael Higley, Joe Howard, Alex Kwan, Daeyeol Lee, David McCormick, John Murray, and Steven Zucker (see http://swartz-initiative.medicine.yale.edu<http://swartz-initiative.medicine.yale.edu/>). Candidates must hold a Ph.D. or equivalent degree. Please send a Curriculum Vitae, selected reprints, and a statement of research plans including the laboratories of interest. All application materials should be sent electronically to the following e-mail address: david.mccormick(a)yale.edu<mailto:david.mccormick@yale.edu>. Applications will be reviewed as they are received, with a target date of November 30th, 2016. Positions are available starting January 2017. Yale University is an affirmative action/equal opportunity employer. Yale values diversity in its faculty, students, and staff and especially welcomes applications from women and underrepresented minorities. ----------------------------------------------------------- Thanks! David A. McCormick Professor, Neuroscience | Yale University School of Medicine Dept. Neuroscience 333 Cedar Street | New Haven, CT 06510 | 203.785.5981 www.mccormicklab.org<http://www.mccormicklab.org/> | www.neurobiology.org<http://www.neurobiology.org/>

Oct. 7, 2016

"Closed Loop Neuroscience" book release

by ahmed el hady

Dear All, I would like to share with you the exciting news that my edited volume "Closed Loop Neuroscience", has just been published by Academic Press. The following is the link for the book: http://store.elsevier.com/Closed-Loop-Neuroscience/Ahmed-El-Hady/isbn-97801… . This reference book gathers work from across neuroscience, which employs closed loop methodologies, under the umbrella of what can be called “Closed Loop Neuroscience”. The book is built on three axes: theoretical, experimental and philosophical. The contributors come from a myriad of disciplines from physics, mathematics, linguistics, neuroscience, philosophy, engineering and computer science. The following is the table of contents: Theoretical Axis 1. Adaptive Bayesian methods for closed-loop neurophysiology 2. Information geometric analysis of neurophysiological data 3. Control theory for closed loop neurophysiology 4. Testing the theory of practopoiesis using closed loops 5. Local field potential analysis for closed loop neuromodulation 6. Online event detection requirements in closed-loop neuroscience 7. Closing Dewey's Circuit 8. Stochastic optimal control of spike times in single neurons 9. Hybrid systems neuroscience 10. Computational Complexity and the Function-Structure-Environment Loop of the Brain 11. Subjective Physics 12. Contextual emergence in neuroscience Experimental Axis 13. Closed loop methodologies for cellular electrophysiology 14. Bidirectional Brain-Machine Interfaces 15. Adaptive brain stimulation for Parkinson’s disease 16. Closed loop neuroprosthetics 17. Closed Loop Limbic Neurostimulation 18. Conscious brain-to-brain communication Philosophical Axis 19. Philosophical aspects of closed loop neuroscience 20. Closed Loops in Neuroscience and Computation: What It Means and Why It Matters Your feedback is very important for me so please let me know if you have any comments about it. My email is ahady(a)princeton.edu. I would really appreciate if you recommend the book to your librarian, colleagues and anyone you think might benefit from it. I hope you will enjoy the book , All the best, Ahmed El Hady Dr. Ahmed El Hady Princeton Neuroscience Institute Howard Hughes Medical Institute Washington Road | Princeton, NJ 08544 Tel: +1-609-258-7954 Fax: +1-609-258-1028 Website: http://scholar.princeton.edu/ahmedelhady/home

Oct. 7, 2016

Open positions in Theoretical/Computational Neuroscience at the Max Planck Institute for Brain Research in Frankfurt

by Gjorgjieva, Julijana

We invite applications for PhD positions and have openings for Master and Bachelor students interested in writing their thesis or doing internships in our group 'Computation in Neural Circuits' at the Max Planck Institute for Brain Research in Frankfurt, Germany. Postdoctoral candidates are also encouraged to inquire for open positions. We use mathematical and computational approaches to study how neurons and the connections between them get organized into circuits that are flexible to learn, yet remain robust to external perturbations. We focus on the emergence of complex properties at the single neuron and circuit level during early development. For example, we study how synaptic plasticity, homeostasis and development of ion channel expression interact to produce functional adult circuits. We are also interested in how these specific properties emerge evolutionarily, shaped by various biophysical constraints. Our work is supported by close experimental collaborations based on different animal models, from rodent to fruit fly, giving us access to individual circuit components. Successful applicants can work on a range of projects including theoretical model development and analytical calculations, numerical simulations, data analysis, and applications to novel datasets from collaborating labs. Applicants should have a strong quantitative background (in mathematics, physics, engineering, computer science, or related fields) and interest in interdisciplinary research. Background in neuroscience is desirable but not required, and some programming experience is necessary. To apply for these positions, please submit the following to comp.neural.circuits(a)gmail.com<mailto:comp.neural.circuits@gmail.com> 1. A curriculum vitae 2. A motivation letter or a description of research interests (please explain your scientific interests, what are you strengths when working on a problem, why our group) 3. Contact details for 2-3 referees 4. A written sample of scientific research, e.g. a manuscript, thesis, or code Our institute also hosts the IMPRS graduate school in 'Neural Circuits' which has an open call for PhD applications with a deadline of December 15, 2016: http://brain.mpg.de/graduate-studies/call.html For more information or informal inquiries, please get in touch! Julijana Gjorgjieva, PhD Group Leader Max Planck Institute for Brain Research Max-von-Laue-Str. 4 60438 Frankfurt/Main, Germany http://brain.mpg.de/research/computation-in-neural-circuits-group.html

Oct. 7, 2016

Symposia on Memory, March 6-10 2017, Barcelona

by Alex Roxin

Dear all, I'm happy to announce that registration is open for the week-long series of Symposia on Memory at the Centre de Recerca Matemàtica from 6-10 of March, 2017 in Barcelona, Spain. These symposia bring together experimental and theoretical researchers in the neuroscience of memory to present and discuss work on topics such as: sleep, hippocampal function, the molecular basis of memory, synaptic plasticity, spatial learning, human memory, and more. The full list of invited speakers as well as a partial list of abstracts for the invited talks is on the website. A detailed schedule is forthcoming. As a registered participant you can submit an abstract for a contributed talk or a poster. For more information and to register see http://www.crm.cat/en/Activities/Curs_2016-2017/Pages/MATHMEM_Symposia.aspx The symposia are part of the Intensive Research Program (IRP) on the Mathematics of Memory at the Centre de Recerca Matemàtica in Bellaterra (Barcelona), Spain. The program kick-off is a week-long winter school on the mathematics of memory, the Memory School, from the 16th to the 20th of January, 2017. A preliminary course schedule is available on the website. As a registered participant at the school you can submit an abstract to present a poster. Registration is open! http://www.crm.cat/en/Activities/Curs_2016-2017/Pages/MATHMEM_School.aspx For more information on the IRP on Memory please visit the website below http://www.crm.cat/en/Activities/Curs_2016-2017/Pages/IRP-MATHMEM.aspx best regards, Alex (on behalf of the coordinators: Nicolas Brunel, Sandro Romani and Alex Roxin)

Oct. 6, 2016

Call for posters and participation: The 3rd International Symposium on Cognitive Neuroscience Robotics

by amser116

Call for posters and participation: (apologies for cross-posting) The following international symposium will be held in Osaka, Japan in December 2016. The theme of the symposium is Constructive Developmental Science, which aims at understanding human cognition by means of interdisciplinary approach (e.g., psychology, cognitive science, neuroscience, and robotics). We will have world-leading researchers from different disciplines as invited speakers and would like to invite you to present a poster of your recent achievement. Please see the symposium homepage for more details: http://www.cnr.osaka-u.ac.jp/?p=1835&lang=en ============================================ The 3rd International Symposium on Cognitive Neuroscience Robotics: Toward Constructive Developmental Science ============================================ Date: Sunday, December 11 – Tuesday, December 13, 2016 Place: Science Hall, Senri Life Science Center, Osaka, Japan Fee: No fee except banquet Registration: Advance registration is required (see the following homepage) Program: http://www.cnr.osaka-u.ac.jp/?p=1835&lang=en Invited speakers: - Rechele Brooks, University of Washington - Helge Ritter, Bielefeld University - Giulio Sandini, Italian Institute of Technology - Shinsuke Shimojo, California Institute of Technology Sponsors: - Institute for Academic Initiatives, Osaka University “Division of Cognitive Neuroscience Robotics” - JSPS Grant-in-Aid for Specially Promoted Research “Constructive Developmental Science Based on Understanding the Process from Neuro-Dynamics to Social Interaction” Best regards, Yukie Nagai, on behalf of the symposium organizers — Yukie Nagai, Ph.D. Specially Appointed Associate Professor, Osaka University Visiting Researcher, Bielefeld University yukie(a)ams.eng.osaka-u.ac.jp http://cnr.ams.eng.osaka-u.ac.jp/~yukie/

Oct. 6, 2016

high performance computing with the Neuroscience Gateway Portal

by Ted Carnevale

Space is still available in the workshop on the Neuroscience Gateway Portal (NSG), but if you are interested you should act soon because space is limited and the registration deadline is Friday Oct. 28. The NSG is an NSF-supported resource for neuroscientists whose research involves computationally intensive modeling and/or data analysis. It has a simple, convenient user interface for running simulations and data analysis tasks on HPC hardware, and provides free CPU time. Currently installed software includes Brian, GENESIS, MOOSE, NEST, NEURON, PyNN, Freesurfer, and the Virtual Personalized Multimodal Connectome Pipeline. The workshop will be held on Saturday, Nov. 12, from 9 AM to noon, just before the start of the 2016 SFN meeting, at a downtown San Diego location near the convention center. The agenda includes instruction on how to use the NSG in your own research, a hands-on exercise, and presentations by research teams about how they are using the NSG for their own high performance computing needs. See http://www.neuron.yale.edu/neuron/static/courses/nsg2016/nsg2016.html for more information and a link to the registration form. --Ted

Oct. 6, 2016

Postdoctoral Fellowship in System Neuroscience

by Majid Mohajerani

A position as Postdoctoral Fellow is now open for an outstanding postdoctoral associate to conduct research in the field of neural network functions at the Canadian Centre for Behavioural Neuroscience at the University of Lethbridge, Alberta. Our goal is to understand cellular and brain system mechanisms of memory and cognitive processing in animal models of healthy brain and memory disorders associated with aging and brain damage. Our research focusses on information coding, neural dynamics and system level neural interactions among diverse brain regions (e.g., hippocampus, prefrontal, retrosplenial, parietal and anterior cingulate cortices). This research will be supported by state-of-the-art facilities including advanced two-photon imaging, microendoscope imaging, wide-field voltage and calcium imaging, and high-density multi-unit electrophysiological recording and optogenetic techniques. The project is a collaborative effort between the research groups of Prof. Bruce McNaughton and Dr. Majid Mohajerani. Successful candidates will join the highly collaborative and interdisciplinary Canadian Centre for Behavioural Neuroscience (http://www.uleth.ca/artsci/neuroscience/our-faculty) and Brain Dynamics group (http://lethbridgebraindynamics.com/) which has outstanding research strengths in the areas of learning and memory, decision making, information coding and related diseases such as Alzheimer's, schizophrenia, addiction and stroke. Salary scales will be competitive with NIH standards for postdoctoral researchers. The position will be initially for 1 year with possibility of renewal depending on performance review at the end of the first 9 months. QUALIFICATIONS Preference will be given to candidates with strong quantitative and neuroscience methodological backgrounds such as neural ensemble recording, 2-photon or other in vivo neural activity imaging or in brain mapping. Good verbal and written communication skills are a must. Experience in MATLAB will be an asset. Candidates should be prepared to learn and use cutting-edge physiological, anatomical, and computational techniques, such as virtual reality-based rodent behavioural systems, optogenetic manipulations, and statistical methods for the analysis and modelling of data. HOW TO APPLY Interested applicants should send an email to Dr. McNaughton ( <mailto:bruce.mcnaughton@uleth.ca> bruce.mcnaughton(a)uleth.ca) with cc to Dr. Mohajerani ( <mailto:mohajerani@uleth.ca> mohajerani(a)uleth.ca ) and include a cover letter, curriculum vitae, a brief statement of research interests, and contact information of three references. Applications are encouraged from women and minorities.

Oct. 5, 2016

POSTDOCTORAL POSITIONS IN COMPUTATIONAL NEUROSCIENCE AT BROWN UNIVERSITY

by Wilson Truccolo

Applications for post-doctoral positions are invited for the Laboratory of Dr. Wilson Truccolo in the Department of Neuroscience at Brown University, Providence, RI, USA. The positions are for the development of data-driven stochastic models of multiscale neural dynamics. Neural data consist of recordings of single-neuron ensembles and local field potentials obtained via multiple intracortical microelectrode arrays implanted in human and non-human primates. Research topics include: (1) Role of neuronal network intrinsic dynamics in neural encoding and decoding. (2) Multiscale neocortical dynamics in human focal epilepsy: seizure transition, propagation and termination. (3) Precursor signatures of focal seizure transitions, prediction and control. The ideal candidate will have a strong background in computational/theoretical neuroscience and modeling of stochastic neural dynamics. Related publications can be found on the Truccolo lab website ( http://www.truccololab.com/ <http://dl.dropbox.com/u/983891/Truccolo_home.htm>). Inquiries should be addressed to Dr. Truccolo (wilson_truccolo(a)brown.edu) Applications including a CV, statement of research interests, and the names and full contact details of three referees should be sent to wilson_truccolo(a)brown.edu. -- Wilson Truccolo, Ph.D. Pablo J. Salame '88 Goldman Sachs Assistant Professor of Computational Neuroscience Department of Neuroscience & Institute for Brain Science, Brown University Lab website: http://www.truccololab.com/

Oct. 4, 2016

Two PhD Positions for Neural Network Research Using High-density Microelectrode Arrays

by Felix Franke

*PhD Positions for Students with Neurobiology Background or Engineering/Data-analysis Background for Neural Network Research Using High-density Microelectrode Arrays* We are currently seeking PhD students with a neurobiology background, or with an engineering/data analysis background, who will conduct electrophysiological experiments with high-density microelectrode arrays. The students will investigate how information is processed by neuronal networks and by the corresponding individual neurons and subcellular units within active networks. Suitable candidates should either have a background in neurobiology/neuroscience, or interest in evaluating large-scale complex data sets and a background in engineering or computer science. The candidate should be interested in interdisciplinary collaborative work in the area of electronics/neurobiology/data processing. Programming skills (for example Matlab, Python, R, etc.) are required, and knowledge of mathematics, statistics and data analysis methods, or experience in cell culturing and sterile techniques, or - possibly - patch clamp will be an asset. For more information see: https://www.bsse.ethz.ch/bel/open-positions.html -- Felix Franke, PhD ETH Zürich, D-BSSE Bio Engineering Laboratory (BEL) http://www.bsse.ethz.ch/bel

Oct. 4, 2016

Deadline extended for Brains and Bits NIPS Workshop

by Konrad Kording

We just expanded the NIPS brains and bits deadline by a week: http://www.stat.ucla.edu/~akfletcher/brainsbits.html Consider joining us if you are interested in neural data science.

Sept. 29, 2016

Open PhD Position in Neuroscience at the University of Bremen, Germany

by David Rotermund

The Institute for Theoretical Physics at the University of Bremen, headed by Prof. Dr. Klaus Pawelzik, offers a PhD position in the field of Complex Adaptive Systems. Successful candidates will join an international research group that is located in the field of Complex Adaptive Systems with a specialization in Econophysics, Psychophysics and Computational Neuroscience. In the latter we work on Attention, Neuronal Dynamics, Learning and Neurotechnology. The project funded by the DFG is entitled: “Dynamic instabilities from information annihilation in neuronal networks” Many Complex Adaptive Systems, including human balancing behavior, financial markets, and neuronal networks, exhibit complex spatio-temporal activity. Interestingly, all these systems feature a dynamic balance of opposing influences. In this project we will investigate the consequences of simple but biologically realistic mechanisms that yield a balance of excitatory and inhibitory inputs into neurons. In particular, we will determine the conditions where this balance does not result in simple equilibria but causes complex temporal dynamics and power-law distributed avalanches of activity in recurrent networks. This topic is part of a long term research program where we investigate whether a single general principle, by which criticality emerges from an efficient absorption of information, can account for these observations in a wide range of systems. The position is funded with a salary comparable to a 65 % TVL13 position and comes with support for 3 years and direct supervision by the principal investigator. Ideal candidates have a MSc degree in Physics or Mathematics. In any case they must have a strong background in physics and/or computational neuroscience and solid programming skills. Above all, they must have a strong motivation, a sense for responsibility, interest for detailed analysis, and a distinct desire to learn. Fluency in English is required (both written and spoken). If you are interested, please send your complete application by 23th October 2016 by e-mail (see detailed instructions below) to ajanssen(a)neuro.uni-bremen.de. Severely disabled applicants and women with essentially identical and personal suitability will be preferentially selected. Detailed instructions for applicants ===================== Your application must comprise: Motivation letter -------------------- Your 1-2 page essay should reply the following questions: What is your background? In which fields have you worked before and how do you think this can be useful for the present job? What attracts you to the field of neuroscience? Which problem(s) in neuroscience are you most interested in? Which kind of person are you (e.g. creative, analytic, communicative, pragmatic, etc.) and how do you approach a research problem? What are your plans for your future career? Curriculum Vitae --------------------- Send a classical tabular CV with your contact details, your date-of-birth, a current photograph, and all stages of education and employment. List of skills, awards, publications List your skills, especially proficiency in languages (including the level of proficiency), that you think might be useful for the job. Also list awards you might have got and peer-reviewed papers, in case there are some. Contact details of two academic references -------------------------------------------------------- One of the references should be your MSc advisor. Please contact the references prior to listing their names so that they are not surprised if they get contacted. Your application can be in English or German, whatever language you are more familiar with. Please send your application to ajanssen(a)neuro.uni-bremen.de by 23th October 2016! All documents must be in PDF format and must not be compressed. Combine all documents to a single PDF file or at least name the separate files appropriately. If we find your application interesting, we will let you know within two weeks and potentially ask for more documents.

Sept. 29, 2016

2 Available PhD Positions in Artificial Intelligence and Neuro-Cognitive Robotics, Ritsumeikan University, Japan

by Amir Aly

**Apologies for Cross Posting ** *2 Available PhD Positions in Artificial Intelligence and Neuro-Cognitive Robotics at the Emergent Systems Laboratory, Ritsumeikan University, Japan* The Emergent Systems Laboratory [Link <http://www.em.ci.ritsumei.ac.jp/en>] at Ritsumeikan University in Japan (nearby Kyoto) announces 2 available PhD positions in artificial intelligence and neuro-cognitive robotics as a part of the new project: *"*Comparison and Fusion of Artificial Intelligence and Brain Science*"*. The successful PhD candidates will be involved in research about: *Understanding Neural Computation for Double Articulation Analysis Bridging Sensory-motor Information and Natural Language in Human Brain*, under the supervision of Tadahiro Taniguchi (Project Coordinator) [ Link <http://www.tanichu.com/profile>]. *I. Positions Description * Human brain can analyze a two-layer hierarchical structure embedded in speech signal called *double articulation structure* (i.e., speech signal is segmented into words and phonemes in a hierarchical manner). However, the computational process of double articulation analysis in human brain has not been revealed in neuroscience. In artificial intelligence and developmental robotics, we have not developed - yet - a robot that can automatically learn language from human-robot and sensorimotor real-world interactions in an unsupervised manner. This project aims to contribute to : - Understanding the neural mechanism supporting human and robot language acquisition involving double articulation analysis. - Developing unsupervised machine learning methods for building the next-generation communicative robots. - Developing deep learning and Bayesian probabilistic models integrating language, planning, and sensorimotor behaviors. - Investigating theories bridging between deep learning and Bayesian nonparametrics. Each PhD candidate is expected to contribute to a part of the project. *II. Candidate Profile* - Good mathematical background. - English communication skill for daily discussion and writing papers: IELTS 6 (TOEIC 740). - Programming skills in C++, Python, or Matlab for machine learning and intelligent robot. - Applicants are expected to be interested in natural language, language acquisition, and the human cognitive neural system of social behavior. *III. Application* Please send your application to (adm(a)em.ci.ritsumei.ac.jp) no later than *31 October 2016*, including: - List of publications. - Copies of 2 major publications. - Outline of past research (free format). - Motivation letter (free format). - Outline of prospective research (free format). - 2 Reference letters. Further details about the available positions and admission procedures are available on: *PhD Positions in Artificial Intelligence and Neuro-Cognitive Robotics <http://www.em.ci.ritsumei.ac.jp/info/call-for-phd-candidates-research-assis…>* . Ritsumeikan University is a fast growing international research environment with interdisciplinary research areas, and is the biggest private university in the west of Japan. The College of Information Science and Engineering is the biggest college in the field of Information Science in Japan, and the Graduate School is receiving a large number of KAKENHI Japanese governmental research grants. *IV. Related Papers* [1] Tadahiro Taniguchi, Shogo Nagasaka, Ryo Nakashima, Nonparametric Bayesian Double Articulation Analyzer for Direct Language Acquisition from Continuous Speech Signals, IEEE Transactions on Cognitive and Developmental Systems, Vol. PP (99) .(2016) DOI: 10.1109/TCDS.2016.2550591 [2] Tadahiro Taniguchi, Takayuki Nagai, Tomoaki Nakamura, Naoto Iwahashi, Tetsuya Ogata, and Hideki Asoh, Symbol Emergence in Robotics: A Survey, Advanced Robotics, Vol.30, (11-12) pp. 706-728 .(2016) DOI:10.1080/01691864.2016.1164622 ---------------------------------------------- Amir Aly, Ph.D. Postdoctoral Research Associate Emergent Systems Laboratory College of Information Science and Engineering - Ritsumeikan University 1-1-1 Noji Higashi, Kusatsu, Shiga 525-8577 Japan

Sept. 28, 2016

International Workshop on Computational Psychiatry at KAIST (Sang Wan Lee)

by Sang Wan Lee

We are pleased to host a single day workshop on computational psychiatry, entitled "Computational approaches to understanding memory, learning, decision making, and emotion processing". The brain is an immensely complex system, making it hard to account for the brain's high-level functions, such as cognitive, emotional, and social components. The impairments of these circuits often lead to mental illness. A new approach, dubbed as computational psychiatry, combines experiments with computational modelling to provide the means to prevent psychiatric disorders. This workshop discusses recent advances in applying neuroeconomics, computational neuroscience, artificial intelligence to the study decision making, learning and memory. A deeper insight into these functions is expected to permit development of model-based diagnosis of mental disorders. * List of speakers : Benedetto de Martino (University of Cambridge, UK) Robb Rutledge (University College London, UK) Shinsuke Suzuki (Tohoku University, Japan) Sukbin Lim (New York University Shanghai, China) Sang Wan Lee (KAIST, South Korea) * Date: OCT 5 Wednesday, 2016 * Venue: Dream Hall (1st floor), CHUNG Moon Soul building (E16), KAIST * Program: http://www.aibrainlab.com/cp2016/ (free registration) - Host: Department of Bio and Brain Engineering, KAIST - Organizer: Sang Wan Lee (inquiries: Hana Park, <mailto:hnpark@kaist.ac.kr> hnpark(a)kaist.ac.kr) -- Sang Wan Lee, Ph. D Assistant Professor Laboratory for Brain and Machine Intelligence Department of Bio and Brain Engineering, KAIST 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea +82-42-350-4334 sangwan(a)kaist.ac.kr <mailto:sangwan@kaist.ac.kr> http://aibrain.kaist.ac.kr

Sept. 27, 2016

Two Postdoc Positions in Model-based fMRI and Machine Learning at KAIST (Sang Wan Lee)

by Sang Wan Lee

*Postdoctoral positions in model-based fMRI and machine learning at KAIST* Two postdoctoral positions, funded through Samsung future technology foundation, are immediately available in the Laboratory for Brain and Machine Intelligence, led by Sang Wan Lee, at KAIST (http://aibrain.kaist.ac.kr/openings) The laboratory is affiliated with the department of Bio and Brain Engineering, Brain and Cognitive Engineering program, and KAIST Institute for Health Science and Technology (KIHST). The positions are initially appointed for one year, and may be extended for up to three years. We offer a competitive salary plus benefits. We also provide opportunities for working with our collaborators (refer to our website for more information). The project, AI-human coevolution engine, aims to develop a framework that boosts human learning and inference performance. It requires a combination of model-based neuroimaging techniques and a design of various learning algorithms. Research topics include model-based/model-free reinforcement learning, inductive/deductive/transitive inference, and one-shot learning. Details about the project is confidential, but the research proposal will be outlined during an interview. Qualifications (type1): - PhD in cognitive neuroscience, computational neuroscience, or physics - prior experience in (model-based) fMRI analysis is preferred. Qualifications (type2): - PhD in electrical engineering, computer science, or applied mathematics - strong quantitative background with expertise in machine learning The positions are open until filled. Interested please send a cover letter, a CV and a list of two references to sangwan(a)kaist.ac.kr. Applications will be reviewed on a rolling basis. -- Sang Wan Lee, Ph. D Assistant Professor Laboratory for Brain and Machine Intelligence Department of Bio and Brain Engineering, KAIST 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea +82-42-350-4334 sangwan(a)kaist.ac.kr <mailto:sangwan@kaist.ac.kr> http://aibrain.kaist.ac.kr

Sept. 27, 2016

Faculty Positions in Applied Mathematics at Northwestern University

by William L. Kath

The Department of Engineering Sciences and Applied Mathematics at Northwestern University (http://www.mccormick.northwestern.edu/applied-math/) invites applications for two full-time, tenure-track faculty positions. Hiring will be focused on the assistant professor level, although exceptional applicants at a more senior level will be considered. Requirements include a Ph.D. and demonstrated ability to conduct high-impact interdisciplinary research in applied mathematics. Candidates in all areas are encouraged to apply. We are seeking candidates with strong connections to applications who can enhance the breadth of research activities of the department. Duties involve teaching and research. The application package should include a curriculum vita, a statement of research accomplishments and interests, and a statement of teaching experience and philosophy. Send applications to https://facultysearch.mccormick.northwestern.edu/apply/index/ODg In addition, the applicant should arrange for at least three, but no more than four letters of recommendation. Recommendation letters will be automatically solicited from the letter writers by email after the names are entered in the online application system. Questions may be sent to esam-facultysearch(a)northwestern.edu (Subject line: 2017 Faculty Search). Review of applications will begin November 15, 2016, and will continue until the positions are filled. For further information, see: http://www.mccormick.northwestern.edu/applied-math/. Northwestern University is an Equal Opportunity, Affirmative Action Employer of all protected classes including veterans and individuals with disabilities. Women and minorities are encouraged to apply. Hiring is contingent upon eligibility to work in the United States. -- William L. Kath, Professor Engineering Sciences and Applied Mathematics McCormick School of Engineering, Northwestern University 2145 Sheridan Road, Evanston, IL 60208-3125 Phone: 847-491-8784 Fax: 847-491-2178

Sept. 26, 2016

Reminder: deadline (October 1st 2016) approaching for manuscript submission to the Research Topic 'Burst coding: from cell to cognition'

by Fleur Zeldenrust

This is a reminder: The deadline for manuscript submission to the Research Topic below is on Extended Article Submission Deadline: 01 Oct 2016 . Research Topic Title: Burst coding: from cell to cognition Topic Editor(s): Wytse J. Wadman, Fleur Zeldenrust, Bernhard Englitz Hosting Field: Frontiers in Neuroscience Journal: Frontiers in Computational Neuroscience Here are quick links to: - Manuscript guidelines: http://home.frontiersin.org/about/author-guidelines - Online submission: http://frontiersin.org/Computational_Neuroscience/researchtopics/Burst_codi… - List of article types and publishing fees: http://www.frontiersin.org/about/PublishingFees With best regards, Fleur Zeldenrust Guest Associate Editor, Frontiers in Computational Neuroscience Department of Neurophysiology Donders Centre for Neuroscience Faculty of Science, Radboud Universiteit Heyendaalseweg 135, postvak 33 6525 AJ Nijmegen tel +31 24 36 53195 www.frontiersin.org

Sept. 26, 2016

Brainhack: Anatomy edition in Paris, 24-26 October 2016

by Anastasia Osoianu

Registration is now open for Brain-anatomy-hack in Paris. Brain-anatomy-hack aims at promoting the interaction between scientists on questions concerning (1) the investigation of brain anatomy based on magnetic resonance imaging or post mortem dissection; (2) the evolution of nervous systems across species; (3) the variability of brain features across healthy participants; (4) the insurgence of brain pathologies. Program Each of the three days will begin with an “Ignite Session” in which speakers will give 15-30 minute talks that will address wide questions in neuroanatomy that would benefit from open, interdisciplinary collaborations. The “Ignite Session” will be followed by a “hack session” and a dynamic set of talks organized by attendees. During the “hack sessions”, participants will be encouraged to work together in small groups on relevant projects. The workshop will culminate on the last day, when participants will have the opportunity to present a brief overview of their project. Participants can bring their own dataset, discuss a project and recruit a team of collaborators on site. Access to free big online databases of MRI images will be also available during the three days, for new creative ideas to be tested. This workshop is also an opportunity to learn methods, develop skills and collaborate with other participants. Participants will be supervised and receive advice on methods from a team of very capable nerds including Roberto Toro, Michel Thiebaut de Schotten, Alexandros Goulas, Julien Lefèvre, Daniel Margulies and Leonardo Cerliani throughout the three days. A constant flow of food and drinks (especially coffee…) will be provided during the conference breaks. We kindly request an online preregistration (70€) in order to cover the expenses for the venue, the equipment and the food/drinks. Deadline is 16th of October 2016. For more information and preliminary schedule visit: http://neuroanatomy.github.io/events/brainhack/ To learn more about Brainhack and previous events: http://brainhack.org/

Sept. 24, 2016

Job Posting--Senior Data Analyst--DiCarlo Lab

by Christopher Shay

SENIOR DATA ANALYST Massachusetts Institute of Technology Brain and Cognitive Sciences McGovern Institute for Brain Research Lab of James J. DiCarlo http://dicarlolab.mit.edu/ <http://dicarlolab.mit.edu/> To develop and lead an open science framework for a small, but growing consortium of neuroscience research labs that together aim to build computational models of the brain’s visual processing system. Primary responsibilities are to (i.) develop and perform data packaging and analytics on visual neuroscience and behavioral psychophysics data, (ii.) implement existing and novel computational models of the visual system, and (iii.) build metrics and visualizations that quantitatively compare computational models to experimental data. The candidate will be based at the DiCarlo Lab at McGovern Institute for Brain Research at MIT. He or she will develop and implement standardized data formats, apply computational and statistical tools for data analysis, develop web-based graphical visualization interfaces to display results and present reports/results to the PIs, collaborators, and the research group. The data analyst will also oversee the lab’s local and remote computing hardware resources. REQUIRED: Bachelor’s degree, preferably in Computer Science or Software Engineering; Masters degree in (e.g.) Machine Learning, Statistics, or related field highly desirable; extensive familiarity with and high level of demonstrated competence in Python and Javascript absolutely required; working knowledge of C++ and C# languages highly desirable; minimum of five years’ experience with large-scale data-science activities, including organizing, analyzing, and synthesizing complex datasets to produce readable, informative automated web-based reports; demonstrated competence in modern data visualization tools such as Tableau, R, and D3.js; minimum of two years’ experience with large-scale database design and usage; minimum of two years' experience with building and maintaining a medium-to-large scale web-based application stack; experience with statistical languages/programming packages such as MATLAB (preferred), R, Stata, SPSS, or SAS highly desirable; experience with executing neural network feature extraction procedures on GPUs highly desirable. Demonstrated ability to partner with colleagues; ability to independently manage multiple projects/priorities while meeting changing deadlines, adapt to new technologies, and present information in a clear and cohesive manner; creative problem solving skills; ability to approach tasks with an eye toward efficiency and reproducibility; excellent written and oral communications skills; meticulous attention to detail; and proactive approach to investigative analysis. Experience in academic research, particularly computational neuroscience, is highly desirable. Christopher Shay, PhD Lab Manager DiCarlo Lab McGovern Institute Lab: (617) 452-3261 Fax:(617) 253-0104

Sept. 23, 2016

Software Engineer position in modeling at the Allen Institute for Brain Science

by Anton Arkhipov

A new position is open at the Allen Institute for Brain Science: http://www.alleninstitute.org/what-we-do/brain-science/careers/job-search/ 2260-Modeling Analysis and Theory Software Engineer II Please apply at the link above! If you have any questions, please feel free to email antona(a)alleninstitute.org<mailto:antona@alleninstitute.org>. Job description. The Modeling, Analysis and Theory group is seeking a Software Engineer to contribute to one of our most crucial efforts - development of software tools for building, simulating, and analyzing models of brain cells and circuits. This individual will design and implement integrated software to enable modeling of brain activity and computations at several levels of resolution - from biophysically detailed to abstract, machine-intelligence-type models. The Software Engineer will be embedded in our Modeling team and will work closely with team members to combine the existing research code with newly designed and developed modules, in order to produce a high-quality modeling software suite for public release and continuous support. Job Responsibilities: * Design, implement, and maintain software for model building, simulation, and analysis/visualization across several modeling approaches using best software engineering practices. * In a team setting, actively participate in algorithm design and software planning and provide thoughtful solutions and alternatives. * Transform complex and high level requirement specifications into software code. * Present design solutions to peers, both within and outside of the Institute. * Manage multiple tasks, set clear priorities, and accomplish tasks with minimal supervision. Basic Qualifications: * BS, MS, or PhD in physical science, math, engineering or computer science discipline. * Strong background in scientific computing; experience in developing scientific modeling software, especially in computational neuroscience, is preferred. Experience with parallel computing is a plus. * At least 5 years of experience with python; familiarity with numpy/scipy. * Familiarity with modern version control systems, such as git. * Experience with Linux is essential; versatility in Windows and Mac platforms is desirable. * Experience in developing, shipping and maintaining robust, data-intensive applications. * Ability to meet aggressive timelines and deliverables in a collaborative environment. Desirable Qualifications: * C/C++ experience. * Graphics and/or data visualization experience. * Some experience in working with relational databases. * Familiarity with SQL. * Experience with maintaining open-source projects.

Sept. 23, 2016

postdoctoral position CRM, Barcelona

by Alex Roxin

Dear all, The Computational Neuroscience Group at the Centre de Recerca Matemàtica in Barcelona, Spain is looking for applicants for a two-year postdoctoral position in the framework of the Collaborative Research Program funded by the Caixa Foundation, to foster collaboration between theory and experiment. Project Description: This project involves data analysis from animal experiments, computational modeling and translation of the results to a clinical setting. The candidate will study how cortical, brain stem and spinal cord circuits interact to drive motor function. This will involve analysis and modeling of high-dimensional data from experiments with stimulating electrodes in the motor cortex and spinal cord, and recording electrodes in forelimb muscles of rats, as well as experiments in which the EMG activity of muscles is recorded while the animal is engaged in a reaching and grasping task. In addition, we are initiating a collaboration with the Guttmann Institute for Neurorehabilitation to translate our results to human patients, in order to find a therapy to recover arm/hand function in patients with high spinal cord injuries. The candidate will work in close collaboration with Alex Roxin at the Group for Computational Neuroscience at the CRM and Guillermo Garcia Alias at the Neuroscience Institute at the UAB. Candiate Profile: We are looking for an enthusiastic and scientifically curious researcher with a strong technical background, ideally in mathematics, physics, engineering or related fields. A background in biology or neuroscience is not required. Application Deadline: October 24th. Decision early November. For more information and to apply go to http://www.crm.cat/en/Pages/DetallNoticia.aspx?ItemID=112 best regards, Alex

Sept. 22, 2016

MIT searching for tenure-track faculty at the assistant professor level

by Kate White

The Department of Brain & Cognitive Sciences (BCS) (http://bcs.mit.edu<http://bcs.mit.edu/>) at MIT is looking to hire multiple tenure-track faculty at the assistant professor level. Affiliations with the Picower Institute for Learning & Memory and the McGovern Institute for Brain Research are possible. We are most excited about candidates who work in one or more of the following three areas: i. Computational approaches to neuroscience and cognition. Possible areas of focus include but are not limited to: statistical analysis of neural data and neural signal processing; computational modeling of neural circuits, of neural population representations and transformations; and/or of human cognitive processes. Candidates with the ability to build bridges across empirical domains are especially attractive. An affiliation with Electrical Engineering and Computer Science (EECS), the Computer Science and Artificial Intelligence Laboratory (CSAIL), the newly formed Statistics and Data Science Center, and Society (IDSS), or other allied departments is possible. The Department aims to make multiple hires in this area. ii. Systems neuroscience in non-human animals. The ideal candidate will be driven by the goal of reverse-engineering neural circuits underlying complex behaviors, and will employ novel technologies and computational approaches to understand the coding, dynamics, and/or anatomical underpinnings of these circuits. We will consider applicants who are working on a broad range of model organisms. iii. Cognitive neuroscience in humans and/or non-human primates. The ideal candidate would be conducting research that informs our understanding of cognition while bridging levels of analysis and using multiple methods, e.g. ECoG, fMRI, electrophysiology, MEG, computational modeling, genetics and reverse engineering approaches. Successful applicants are expected to develop and lead independent, internationally competitive research programs and to share in our commitment to excellence in undergraduate and graduate education by teaching courses and mentoring graduate and undergraduate students. PhD must be completed by start day of employment and some postdoctoral training is preferred. Please submit application materials - cover letter, CV, statement of research and teaching interests and representative reprints - online at https://academicjobsonline.org/ajo/jobs/8024. Please state research area in cover letter. To help direct the application, applicants should indicate which of the areas listed above is their main research area by selecting from the drop down list included in the application. In addition, please arrange to have three letters of recommendation submitted online. All application materials are due by midnight (EST) on October 31, 2016. MIT is an equal employment opportunity employer<https://www1.eeoc.gov/employers/upload/eeoc_self_print_poster.pdf>. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability. Best regards, Kate White Human Resources Administrator MIT | Department of Brain and Cognitive Sciences (BCS) 77 Massachusetts Ave., Bldg 46-2005A Cambridge, MA 02139 T: 617-253-5749 | E: kowhite(a)mit.edu<mailto:kowhite@mit.edu> Visit us online at http://bcs.mit.edu<http://bcs.mit.edu/> [cid:5DC388A1-6756-4BB2-81B2-79C29D68B533] *Please note, BCS HQ is currently located in temporary office space on the 5th floor, suite 46-5065 until further notice. I am located in office 46-5065C.

Sept. 21, 2016

Brian 2.0 release

by Dan Goodman

We are very pleased to announce the release of version 2.0 of the Brian neural network simulator. Brian is a free, open source simulator for spiking neural networks. It is written in the Python programming language and is available on almost all platforms. We believe that a simulator should not only save the time of processors, but also the time of scientists. Brian is therefore designed to be easy to learn and use, highly flexible and easily extensible. You can learn more about Brian at our website (http://briansimulator.org) You can also try out Brian from your web browser, without having to install any software, using our interactive demo (http://mybinder.org/repo/brian-team/brian2-binder/notebooks/demo.ipynb) Major new features in 2.0 ------------------------- * Much more flexible model definitions. The behaviour of all model elements can now be defined by arbitrary equations specified in standard mathematical notation. * Code generation as standard. Behind the scenes, Brian automatically generates and compiles C++ code to simulate your model, making it much faster. * "Standalone mode". In this mode, Brian generates a complete C++ project tree that implements your model. This can be then be compiled and run entirely independently of Brian. This leads to both highly efficient code, as well as making it much easier to run simulations on non-standard computational hardware, for example on robotics platforms. * Multicompartmental modelling. * Python 2 and 3 support. That's just a small fraction of the new features in 2.0. For the full list, see http://brian2.readthedocs.io/en/stable/introduction/release_notes.html. Upgrading from Brian 1.4 ------------------------ Brian 2 is a rewrite from scratch, and introduces some backwards incompatible changes. In most cases, these should be relatively simple. We've written a detailed guide on how to update your simulations: http://brian2.readthedocs.io/en/stable/introduction/changes.html. Note that you can have both Brian 1 and Brian 2 installed simultaneously, so you can switch gradually. Thanks ------ Brian 2 was written by Marcel Stimberg, Dan Goodman and Romain Brette. Do please remember to cite Brian if you use it for your research. We would also like to thank the large number of users (over 40) who contributed code, bug reports, etc.

Sept. 21, 2016

MLINI 2016: NIPS Representation Learning in Artificial and Biological Neural Networks Workshop

by Leila Wehbe

NIPS Workshop on Representation Learning in Artificial and Biological Neural Networks (MLINI 2016) December 9th, 2016, Centre Convencions Internacional Barcelona, Barcelona, SPAIN *Call for papers and abstracts:* Submission deadline: *Tuesday, September 27th, 2016* Notification of acceptance: Wednesday, October 5th, 2016 Submission website: *https://cmt3.research.microsoft.com/MLINI2016 <https://cmt3.research.microsoft.com/MLINI2016>* Workshop Website: https://sites.google.com/site/mlini2016nips We invite submissions that are related, but not limited to: - Use of neural network and other methods as models of brain function - Machine learning methods, including deep learning, to analyze brain data - Cognitively plausible learning algorithms, or in general models that take insights from human brains or behavior We invite both: - Paper submissions, to be considered for online publication in arXiv proceedings, and poster presentation. The length should not exceed 6 pages in Springer format <http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0> (here are the LaTeX2e style files <ftp://ftp.springer.de/pub/tex/latex/llncs/latex2e/llncs2e.zip>), excluding the references. - Abstract submission, to be considered for poster presentation. The abstract should not exceed 500 words (figures are allowed). This workshop is in conjunction with a Frontiers topic entitled: Artificial neural networks as models of human brain function http://journal.frontiersin.org/researchtopic/4817/artificial -neural-networks-as-models-of-neural-information-processing Participants are strongly encouraged to submit their work to the Frontiers special topic edition (deadline is November 1st). *About the workshop:* This one day workshop is about the interface between cognitive neuroscience and recent advances in AI fields that aim to reproduce human performance, such as natural language processing or computer vision, and specifically the deep learning approaches in these disciplines. When studying the cognitive capabilities of the brain, scientists follow a system identification approach in which they present different stimuli to the subjects and try to model the evoked brain responses. The goal is to understand the brain by trying to find the function that expresses the activity of brain areas in terms of different properties of the stimulus. Experimental stimuli are becoming increasingly complex with more and more researchers studying real life phenomena such as the perception of natural images or natural sentences. There is therefore a need for rich and adequate representations of the properties of the stimulus, that can be obtained using advances in NLP, computer vision or other relevant ML disciplines. In parallel, many new ML approaches, especially in deep learning, are inspired to a certain extent by human behavior or biological principles. Neural networks for example were originally inspired by biological neurons. More recently, processes such as attention are being used which are inspired by human behavior. However, the large bulk of these methods are independent of findings about brain function, and it is unclear whether it is at all beneficial for machine learning to try to emulate brain function in order to achieve the same tasks that humans are capable of performing. In order to shed some light on this difficult but exciting question, we plan to bring together many experts from these seemingly converging fields to discuss these problems, in a new highly interactive format consisting of two short lectures from experts in both fields, followed by a guided discussion. This workshop is a continuation of the Machine Learning and Interpretation in Neuroimaging (MLINI) series. MLINI has already had 5 iterations in which methods for analyzing and interpreting neuroimaging data were discussed in depth. In keeping with tradition, we also invite contributions from the expanding field of machine learning applied to neuroimaging data, and specifically the recent trend of utilizing neural network models to analyze brain data, which is evolving in parallel to the use of these algorithms as models of the information content in the brain. This way we will complete the loop: we will explore how neural networks and other machine learning tools contribute to neuroscience, both as a source of models for brain representations, and as a tool for brain image analysis. *Organizers:* Guillermo Cecchi (IBM T.J. Watson Research Center) Moritz Grosse-Wentrup (Max Plank Institute for Intelligent Systems) Georg Langs (Medical University of Vienna, CSAIL, MIT) Brian Murphy (Queens University, Belfast) Anwar Nunez-Elizalde (Helen Wills Neuroscience Institute, University of California, Berkeley) Irina Rish (IBM T.J. Watson Research Center) Marcel van Gerven (Donders Institute for Brain, Cognition and Behaviour, Nijmegen) *Leila Wehbe (Helen Wills Neuroscience Institute, University of California, Berkeley) - main contact

Sept. 20, 2016