November 2020 - Comp-neuro - lists.cnsorg.org

Creating a list of important computational predictions
by Yiota Poirazi Jan. 4, 2021

Jan. 4, 2021

Dear all, I believe you would agree that, the greatest recognition of our computational work comes with the experimental verification of our computational predictions. To highlight the most important outcomes of our theoretical work and facilitate a closer interaction with experimental labs so as to increase the chances of our predictions being experimentally tested, I would like to encourage you to nominate your favorite prediction at the following google form: https://docs.google.com/forms/d/e/1FAIpQLSeJZ2RrXJ0nZonIuyNzN0Cl gXDKDb7xTzoJOiqZTGxm9Kh7ow/viewform?c=0&w=1&usp=mail_form_link This effort started during the CNS 2017 meeting in Antwerp with the support of the OCNS Board. The resulting list will be posted on the CNS 2017 web site and disseminated in social media, as a reference for experimentalists. Thank you very much for supporting this important effort! Best wishes, Yiota Poirazi -- Panayiota Poirazi, Ph.D. Research Director Computational Biology Laboratory Institute of Molecular Biology and Biotechnology (IMBB) Foundation of Research and Technology-Hellas (FORTH) Vassilika Vouton, P.O.Box 1385, GR 70013, Heraklion, Crete GREECE Tel: +30 2810 391139 Fax: +30 2810 391101 Εmail: poirazi(a)imbb.forth.gr Lab site: www.dendrites.gr FENS-Kavli Network of Excellence <http://www.fens.org/Outreach/FENS-Kavli-Network-of-Excellence/> -- This message has been scanned for viruses and dangerous content by *E.F.A. Project* <http://www.efa-project.org>, and is believed to be clean. Click here to report this message as spam. <http://mailgate1.imbb.forth.gr/cgi-bin/learn-msg.cgi?id=4BCD7A00A1.A57D7&to…> -- Panayiota Poirazi, Ph.D. Research Director Computational Biology Laboratory Institute of Molecular Biology and Biotechnology (IMBB) Foundation of Research and Technology-Hellas (FORTH) Vassilika Vouton, P.O.Box 1385, GR 70013, Heraklion, Crete GREECE Tel: +30 2810 391139 Fax: +30 2810 391101 Εmail: poirazi(a)imbb.forth.gr Lab site: www.dendrites.gr FENS-Kavli Network of Excellence <http://www.fens.org/Outreach/FENS-Kavli-Network-of-Excellence/>

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ANDA 2020 - G-Node Advanced Neural Data Analysis Course, April 14-30, 2020, Jülich, Germany
by Thomas Wachtler Dec. 23, 2020

Dec. 23, 2020

ANDA 2020 - G-NODE ADVANCED NEURAL DATA ANALYSIS COURSE April 14 - 30, 2020 Haus Overbach, Jülich-Barmen, Germany Techniques to record neuronal data from populations of neurons are rapidly improving. Simultaneous recordings from hundreds of channels are possible while animals perform complex behavioral tasks. The analysis of such massive and complex data becomes increasingly challenging. This advanced course aims at providing deeper training in state-of-the-art analysis approaches in systems neuroscience. The course is addressed to excellent master and PhD students and young researchers who are interested in learning advanced techniques in data analytics and in getting hands-on experience in the analysis of electrophysiological data. Internationally renowned researchers will give lectures on statistical data analysis and data mining methods with accompanying exercises. Students will define and perform their own analyses on provided data to solve a challenge. Participants are required to have a strong interest in data analysis, a background in a mathematical or related field, knowledge of algebra, matrix operations, and statistics, and need to have solid programming experience (preferably in Python). FACULTY · Moshe Abeles, Hebrew Univ. Jerusalem, Israel · Michael Denker, Jülich Research Center, Germany · Udo Ernst, Univ. Bremen, Germany · Sonja Grün, Jülich Research Center, Germany · Adam Kohn, Albert Einstein College of Medicine, New York, USA · Jakob Macke, TU Munich, Germany · Luca Mazzucato, Univ. of Oregon, Eugene, USA · Martin Nawrot, Univ. of Cologne, Germany · Yifat Prut, Hebrew Univ. Jerusalem, Israel · Hansjörg Scherberger, German Primate Center, Göttingen, Germany · Thomas Wachtler, LMU Munich, Germany TOPICS COVERED Single neuron properties and statistics · Stochastic processes · Surrogate methods · Detection of spatio-temporal patterns · Unitary Events · Statistical analysis of massively parallel spike data · Higher-order correlation analyses · Elephant toolbox · Spike-LFP relationship · Population coding · State space analysis · Machine learning · Data mining · Research data management and reproducibility REQUIREMENTS Applicants should be familiar with linear algebra, probability, differential and integral calculus and experienced using Python or Matlab. Preparatory reading material will be provided. Students should bring their own laptops and should be able to install software on their system. Students that do not have a suitable laptop should indicate this immediately after acceptance to the course. We will be able to provide a small number of laptops for the time of the course. COURSE FEE A course fee of 1000 Euros will be charged to cover costs for accommodation and meals. Limited financial support may be available for students that otherwise would not be able to attend, which is to be indicated in the application. HOUSING Accommodation in 2-bed rooms for students will be provided at the course site. HOW TO APPLY The application should include · a letter of motivation (max 1 page) · curriculum vitae (please indicate the relevant courses you have taken) · description of programming experience · a letter of recommendation. Please send all documents as a single PDF file to <advanced-course(a)g-node.org>. APPLICATION DEADLINE Applications must be received by NOVEMBER 15, 2019. Early application is encouraged. For further information see http://www.g-node.org/anda

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Interdisciplinary Neuroscience PhD programme, Tübingen
by Peter Dayan Dec. 19, 2020

Dec. 19, 2020

The Max Planck Institute for Biological Cybernetics, the Hertie Institute for Clinical Brain Research and the University of Tübingen invite students from all over the world to apply for their interdisciplinary 5-year PhD program leading to a PhD in Neuroscience. Full funding will be available for top-ranked applicants. We are seeking talented, curious and open-minded young scientists with strong backgrounds in neuroscience, biomedical sciences, computational science, applied mathematics, statistics, artificial intelligence, or engineering. Successful candidates will possess a burning aspiration to shape the future of neuroscience and the ability to thrive in a fast-paced, interdisciplinary, environment. The application deadline is 30th November 2020. Please visit: https://www.kyb.tuebingen.mpg.de/imprs-mmfd for more details and information about applying. The PhD program is a collaboration between the Max Planck Institute for Biological Cybernetics, the Hertie Institute for Clinical Brain Research and the University of Tübingen. It is closely affiliated with the renowned Graduate Training Centre of Neuroscience, the centerpiece of neuroscience training in Tübingen. Students (who should have been awarded a Bachelor's degree by September 2021) will receive a broad interdisciplinary training in neuroscience, including expert teaching by international renowned scientists and individual and intensive mentoring. Potential research topics cover a variety of fields in systems neuroscience, cognitive and behavioral neuroscience, computational neuroscience, translational and clinical neuroscience as well as cellular and molecular neuroscience. Teaching and research are conducted in English.

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Computational Neuralengineering Training Program at Georgia Tech/Emory
by Rozell, Christopher J Dec. 1, 2020

Dec. 1, 2020

The Georgia Tech/Emory Computational Neuralengineering Training Program (CNTP) is a collaborative partnership with the mission of training the next generation of researchers at the intersection of computational neuroscience, data science and clinical neurophysiology. The CNTP is a training program supported by the National Institute of Biomedical Imaging and Bioengineering (NIBIB) to address the opportunities provided by the explosion of tools for measurement and manipulation of nervous system function and the challenges posed by neurologic disorders. Trainees in CNTP program consists of PhD students with clear interest in quantitative training and either basic or clinical study of the brain, and who are pursuing studies in any of these degree programs: Biomedical Engineering (GT and Emory), Bioengineering (GT), Electrical and Computer Engineering (GT) or Machine Learning (GT) PhD programs. In addition to the benefits of being part of the broad computational neuroscience community in Atlanta, CNTP trainees have access to a new restricted course on Clinical Experience for Engineers, regular meetings with the cohort for rich discussions in technical and professional development topics, and an annual retreat with faculty and students for deeper dives into research discussions. Fellows in the CNTP receive two years of funding which supports a rotation program between labs in the first year. Fellow applications are solicited in the spring from applicants to the degree programs listed above. To be considered for the CNTP Fellowship, all you need to do is apply to a participating graduate program and have aligned interests expressed in your research statement. Scholars in the CNTP are full members of the community with access to all of the same programming (but without the fellowship funding). Scholar applications will be solicited in the summer from students joining labs in the upcoming fall. While there are low barriers to performing interdisciplinary research across departmental boundaries, admissions are handled separately by each degree program. Students interested in participating in the CNTP program should apply to the program that best fits their goals and interests. Application deadlines are listed below, along with the CNTP training faculty affiliated with each degree program. Please contact crozell(a)gatech.edu with questions. ***DEGREE PROGRAMS*** Biomedical Engineering (GT and Emory) DEADLINE: December 1 Application information: https://www.bme.gatech.edu/bme/grad-prospective-student-apply Bioengineering (GT) DEADLINE: Same as the home school selected during application Application information: https://bioengineering.gatech.edu/applying-bioengineering-program Electrical and Computer Engineering (GT) DEADLINE: December 16 Application information: https://www.ece.gatech.edu/graduate-admissions Machine Learning (GT) DEADLINE: Same as the home school selected during application Application information: http://ml.gatech.edu/phd/admissions ***CNTP Training faculty*** --Georgia Tech-- Garrett Stanley Chris Rozell Rob Butera Hannah Choi Tim Cope Constantin Dovrolis Eva Dyer Irfan Essa Ross Ethier Bilal Haider Hang Lu Susan Margulies Cassie Mitchell Machelle Pardue Peng Qiu Annabelle Singer --Emory University-- Lena Ting Michael Borich Gordon Berman Nick Boulis Gary Clifford Bob Gross Shawn Hochman, Dieter Jaeger Shella Keilholz Robert Liu Babak Mahmoodi Svetlana Miocinovich Ilya Nemenman Chethan Pandarinath Astrid Prinz Sam Sober Thomas Wichmann

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GEM 2021 - Call for papers - deadline extended
by Vinita Samarasinghe Nov. 30, 2020

Nov. 30, 2020

The deadline to submit abstracts for the GEM 2021 workshop has been extended until 30.11.2020. Please visit https://easychair.org/cfp/gem2021 to submit your abstracts for both the main workshop and the PhD symposium. ** *GEM 2021 - Generative Episodic Memory: Interdisciplinary perspectives from psychology, neuroscience and philosophy* https://for2812.rub.de/gem2021 16-18 February 2021 The workshop will take place in virtual space and is free of charge. Abstracts for both the workshop and the PhD symposium, which will precede the workshop, are now being accepted via EasyChair https://easychair.org/cfp/gem2021 Keynote Speakers: Karl-Heinz Bäuml - University Regensburg, Germany Dorthe Berntsen - Aarhus University, Denmark Amy Criss - Syracuse University, USA Dorothea Debus - University of Konstanz, Germany David Huber - University of Massachusetts, USA Sarah Robins - University of Kansas, USA Call for papers The DFG-funded research consortium “FOR 2812 – Constructing scenarios of the past” https://for2812.rub.de is proud to announce a call for papers for its first workshop on generative episodic memory. We invite submissions for talks and posters https://easychair.org/cfp/gem2021. Episodic memories are widely regarded as memories of personally experienced events. Early concepts about episodic memory were based on the storage model, according to which experiential content is preserved in memory and later retrieved. However, overwhelming empirical evidence suggests that the content of episodic memory is – at least to a certain degree – constructed in the act of remembering. Even though very few contemporary researchers would oppose this view of episodic memory as a generative process, it has not become the standard paradigm of empirical memory research. This is particularly true for studies of the neural correlates of episodic memory. Further hindering progress are large conceptual differences regarding episodic memory across different fields, such as neuroscience, philosophy, and psychology. This interdisciplinary workshop therefore aims to bring together researchers from all relevant fields to advance the state of the art in the research on generative episodic memory. FOR 2812 “Constructing scenarios of the past: A new framework in episodic memory” consists of 9 researchers. Seven from the Ruhr University Bochum and two from the University of Münster. The consortium adopts an interdisciplinary approach and investigates generative episodic memory from a conceptual, modeling, and experimental perspective using a common conceptual framework: scenario construction. Paper submission deadlines [GMT +1 (CET)]: Abstract submission - 30.11.2020 Notification of acceptance - 31.12.2020 Submission guidelines: Abstracts must be submitted in English and be no longer than 1 page. Submitted work must be original and unpublished. Abstracts must be submitted electronically through the GEM 2021 paper submission site on EasyChair https://easychair.org/cfp/gem2021. Authors will receive confirmation of receipt of their abstracts including an ID number after submission. You can edit your submission at any time before the deadline. We will consider only the final version. Program committee: Nikolai Axmacher - Faculty of Psychology - Ruhr University Bochum Sen Cheng - Institute for Neural Computation - Ruhr University Bochum Gerald Echterhoff - Faculty of Psychology - University of Münster Albert Newen - Faculty of Philosophy - Ruhr University Bochum Ricarda Schubotz - Faculty of Psychology - University of Münster Markus Werning - Faculty of Philosophy - Ruhr University Bochum Laurenz Wiskott - Institute for Neural Computation - Ruhr University Bochum Oliver Wolf - Faculty of Psychology - Ruhr University Bochum All questions regarding the workshop should be emailed to for2812(a)rub.de <mailto:for2812@rub.de> Coordinator - Vinita Samarasinghe Secretary - Christiane Dahl Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience Institut für Neuroinformatik Ruhr-Universität Bochum, NB 3/26 Postfachnummer 110 Universitätstr. 150 D-44801 Bochum Tel: +49 (0)234 32 27996 Email: samarasinghe(a)ini.rub.de

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[jobs] Postdoc and internship position at AI Lab, Novaquark, Montreal (possibility for remote work)
by Pierre-Yves Oudeyer Nov. 26, 2020

Nov. 26, 2020

Novaquark AI Lab, Postdoc or PhD-level internship open position Title: Intention modeling and joint attention for deep reinforcement learning agents interacting with non-expert caretakers Supervision: Jean-Christophe Baillie Team: Novaquark AI Lab, Montréal Duration: 12-36 months for postdocs, 6 months for PhD-level internships, starting early 2021. Location: in Montréal Lab, or in remote. Keywords: Deep reinforcement learning; language grounding; artificial curiosity; developmental AI; joint attention Details: https://drive.google.com/file/d/1kJl851ciJj9lOU0gZ66zjkiMRLgvSgNZ/view <https://drive.google.com/file/d/1kJl851ciJj9lOU0gZ66zjkiMRLgvSgNZ/view> How to apply: contact ailab(a)novaquark.com with a CV and letter of motivation.

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NEUROTECH Webinar: What are the hardware opportunities for neuromorphic engineering?
by Elisa Donati Nov. 25, 2020

Nov. 25, 2020

We are back with the second NEUROTECH educational webinar on Neuromorphic Computing Technologies! We will have one hour of educational material followed by a panel discussion on the open challenges in the field. Please see below the details and please spread the word! ----- At the second webinar, Prof. Johannes Schemmel, Prof. Jennifer Olson Hasler, Dr. Elisa Vianello and Dr. Bert Jan Offrein will be answering the question “What are the hardware opportunities for neuromorphic engineering?”. Join us on the 1st of December at 16:00 CET. Sign up here for free: https://neurotech.iniforum.ch/educational/ <https://neurotech.iniforum.ch/educational/> ------------------------------------------------------------------------ About NEUROTECH: Our mission is to catalyse research and collaboration in NCT. Today's neuromorphic community in Europe is leading the state of the art in this domain. The community counts an increasing number of labs that work on theory, modelling, and implementation of neuromorphic computing systems. The NEUROTECH Project will create a Cartography of NCT in Europe, explore Roadmaps for its development, collect educational and information resources on NCT, and inform about upcoming and previous events. https://neurotech.iniforum.ch <https://neurotech.iniforum.ch/> NEUROTECH Educational Webinar: As part of the NEUROTECH project, the Educational Team is organizing a webinar series on neuromorphic computing technologies. The objective is to collect educational material about the field but also hold discussions with the experts about how the field started, how it evolved, where it’s going and how it’s going to shape the future industrial landscape. Follow us on LinkedIn: NEUROTECHAI and Twitter: JoinNeurotech ————————————————————————— Elisa Donati, PhD Research Fellow Institute of Neuroinformatics University of Zurich and ETH Zurich Winterthurerstrasse 190, 8057 Zurich E-mail: elisa(a)ini.uzh.ch, eldonati(a)ethz.ch Phone: +41 0446353061 Website: www.ini.uzh.ch/people/elisa

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Open positions in Computational Neuroscience and ML (Denmark / UK)
by Diego Vidaurre Nov. 25, 2020

Nov. 25, 2020

Dear all, Apologies for cross-posting. Funded by an ERC grant, I have two open postdoc positions in my lab in Aarhus University in collaboration with Oxford University, to develop new methods on machine learning and Bayesian time series modelling, with application to specific problems in computational neuroscience. The deadline is on the 30th of May. The positions are initially for 1y, but the idea is to offer longer funding, for up to 5y. https://health.au.dk/en/about-health/vacant-positions/job/postdoc-in-integr… Many thanks d

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CFP: FLAIRS 2021 Special Track Neural Nets and Datamining, May 16-19, N Miami Beach, FL
by David B Nov. 24, 2020

Nov. 24, 2020

Covid Update: FLAIRS will virtualize some or all of the conference,as necessary. FLAIRS is an interdisciplinary conference featuring a double-blind review and free tutorials, sponsored by the Association for the Advancement of Artificial Intelligence (AAAI) www.FLAIRS-34.info May 16-19, 2021 DoubleTree Ocean Point Resort & Spa, North Miami Beach, Florida, USA Paper submission deadline: February 16, 2021 This special track will be devoted to neural networks and data mining with the aim of presenting new and important contributions in these areas. Who might be interested? Papers and contributions are encouraged for any work related to Neural Networks and Data Mining. What kind of studies will be of interest? This special track will be devoted to neural networks and data mining with the aim of presenting new and important contributions in these areas. Papers and contributions are encouraged for any work related to neural networks, data mining, or the intersection thereof. Topics of interest may include (but are in no way limited to): 1. Applications such as Pattern Recognition, Control and Process Monitoring, Biomedical Applications, Robotics, Text Mining, Diagnostic Problems, Telecommunications, Power Systems, Signal Processing; Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cyber security, remote sensing, earth sciences, bioinformatics, and astronomy. 2. Algorithms such as new developments in Back Propagation, RBF, SVM, Deep Learning, Ensemble Methods, Kernel Approaches; hybrid approaches such as Neural Networks/Genetic Algorithms, Neural Network/Expert Systems, Causal Nets trained with Backpropagation, and Neural Network/Fuzzy LogicApplications such as Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cyber security, remote sensing, earth sciences, bioinformatics, and astronomy. 3. Modeling algorithms such as hidden Markov models, decision trees, neural networks, statistical methods, or probabilistic methods; case studies in areas of application, or over different algorithms and approaches. 4. Feature extraction and selection. 5. Post-processing techniques such as visualization, summarization, or trending. 6. Preprocessing and data reduction. 7. Knowledge engineering or warehousing. Papers dealing with Cloud-based unstructured data or Cloud-based tool suites, such as Mahout or Apache Spark, are also encouraged. Track Co-Chairs: David Bisant, Central Security Svcs, bisant(a)umbc.edu Steven Gutstein, Army Research Laboratory, s.m.gutstein(a)gmail.com William Eberle, Tennessee Tech University, weberle(a)tntech.edu Submission Instructions Submitted papers must be original, and not submitted concurrently to a journal or another conference. Full oral presentation papers may be up to 6 pages, short poster presentation papers up to 4 pages, and abstract only poster presentations up to 250 words. Submissions for special tracks, workshops, tutorials, and discussion panels are also welcome. Papers must be in AAAI format, and submitted as PDF through the EasyChair conference system, which can be accessed through the main conference web site http://www.flairs-34.info/. The proceedings of FLAIRS-34 will be published by Florida Online Journals (https://journals.flvc.org/) In order for a paper to be published in the proceedings, the paper must be accompanied by at least one AUTHOR REGISTRATION. It is also expected that for a full (i.e., maximum 6-page) paper, at least one of the authors will attend the conference to present their work. In order for a poster to be presented at the conference, it must also be accompanied by an AUTHOR REGISTRATION. Organization Conference Chair: Keith Brawner, Army Research Lab, USA Roman Barták, Charles University, Czech Republic Program Co-Chairs: Eric Bell, USA Fazel Keshtkar, St John’s University, USA

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Closed-Loop Deep Learning with Robotics, NECO Vol 32, No 11
by Sama Daryanavard (PGR) Nov. 23, 2020

Nov. 23, 2020

Dear Colleagues, In our paper we present Closed-Loop Deep Learning which combines the power of deep learning and classical control to create an efficient analogue multi-layered fast learning paradigm, for robotic navigation. At the heart of this algorithm is an error signal that arises from a reflex which is delicately used to both drive the closed loop system and train the deep learner simultaneously. Through mathematical derivation in z-space we show how to implement back-propagation in a closed-loop system. Preprint: https://arxiv.org/abs/2001.02970 Neural Computation (final version): https://www.mitpressjournals.org/doi/abs/10.1162/neco_a_01317?journalCode=n… Please do not hesitate to get in touch for a copy of the paper and to discuss your thoughts. Warmest Regards, Sama Daryanavard Dr Bernd Porr Biomedical Engineering Division, School of Engineering, University of Glasgow, Glasgow G12 8QQ, U.K.

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