August 2018 - Comp-neuro - lists.cnsorg.org

Extension Call for Abstracts: New Deadline August 31 - Cognitive Computing - Merging Concepts with Hardware

by Prof. Dr. Gordon Pipa

Upon demand and the holiday period in August we extend the Deadline for submissions of abstracts until the end of August. New Deadline for Abstract submission: August 31 Call for participation and contributions: COGNITIVE COMPUTING: MERGING CONCEPTS WITH HARDWARE December 18-20, 2018, Hannover, Germany http://www.cognitive-comp.org/ ** An interdisciplinary networking event / scientific conference ** We would like to draw your attention to an upcoming scientific community event. The aim of this conference is to work towards a general, productive, and rigorous theory of “computing” in non-digital, nonlinear physical substrates. Biological brains and unconventional computing machines would become understandable as different instantiations of the same underlying principles. Three scientific communities, namely - cognitive and computational neurosciences, - theory of computation, and - nonlinear materials, devices and systems have since long been exploring diverse facets of such principles of non-digital computing. But differences in terminology, discipline-specific objectives and a scattered spectrum of formal methods have handicapped cross-fertilization. Everything in this conference is geared toward stimulating linkages between these fields: - single-track with few but rather long oral presentations, - long break and poster session times for person-to-person interaction, - keynote and plenary speakers with interdisciplinary renown, - a limited (200) number of participants, - a splendid setting in the Castle of Herrenhausen, a heritage of the Kings of Hannover, with adjoining hectares of classical French gardening. Invited and confirmed speakers: - Kwabena Boahen, Stanford University - Joanna J. Bryson, Univ. of Bath and Princeton University - Chris Eliasmith, University of Waterloo - Edward A. Lee, UC Berkeley - Demetri Psaltis, EPFL Lausanne - Pieter Roelfsema, Vrije Universiteit Amsterdam & Netherlands Institute for Neuroscience - Susan Stepney, University of York - Ipke Wachsmuth, University of Bielefeld - David Wolpert, Santa Fe Institute We solicit the submission of 2-page abstracts, with themes oriented toward our five topical sessions: - applications of unconventional computing systems, - theoretical concepts and mathematical foundations, - neuromorphic hardware, - novel physical substrates, - guides from neuroscience for computing technologies. In addition to latest specific achievements, we specifically encourage survey / introductory / didactic contributions. Detailed information can be found on http://www.cognitive-comp.org/ and in the Call for Abstracts that is posted there. Timelines: - Abstract submission: July 31 - Notification of acceptance: September 30 - Final abstract for online publication: October 31 Registration fees: - Students (incl. PhD students): 150 Euro - Others (academic): 300 Euro - Industry: 900 Euro Contributors of accepted oral presentations will be exempted from fees and will receive travel refunding. The event was made possible by the generous support from the Volkswagen Foundation, Germany’s largest private organization for the advancement of scientific research. The organizers: - Daniel Brunner (photonics, neuromorphic architectures; CNRS / University of Burgundy - Franche-Comté) - Herbert Jaeger (machine learning, nonlinear dynamics; Jacobs University Bremen) - Stuart Parkin (nano systems, quantum electronic materials; Max-Planck-Institute for Microstructure Physics, Halle) - Gordon Pipa (neuroinformatics and cognitive computing; University of Osnabrück)

Aug. 6, 2018

One postdoc and two PhD positions in Emmy-Noether group "Decision Neuroscience of Human Cooperation" in Hamburg, Germany

by Christoph Korn

Dear all, I would be very grateful, if you could circulate the following job announcements. One postdoc and two PhD positions are available within the newly funded Emmy-Noether research group "Decision Neuroscience of Human Cooperation" led by Christoph Korn. *Research topic and group:* The group's aim is to investigate the decision-making and learning processes relevant for successful social cooperation between humans. The planned projects rely on a variety of theoretical and methodological approaches including computational modeling of behavioral data, evolutionary game theory, model-based and multivariate analyses of fMRI data, pupillometry, virtual reality, and testing of psychiatric patients. The group is based at the Institute of Systems Neuroscience (head: Prof. Christian Büchel) at the University Medical Center Hamburg-Eppendorf in Hamburg, Germany. Psychiatric patients are tested in collaboration with Sabine Herpertz and her lab at the Heidelberg University Hospital. You can find more information here: http://christoph-korn.net/ *What the group offers:* - Opportunity to get hands-on supervision for learning various data acquisition and analysis techniques - Dynamic, interdisciplinary, and international research environment within the Institute of Systems Neuroscience - Research-dedicated T3 MR scanner (PRISMA), eye-tracking and VR laboratories, excellent infrastructure for behavioral testing - Multiple training opportunities within the institute (e.g., https://goo.gl/pU44vP) - Possibility to join the local graduate school, which is a member of national and international networks - Possibility of research stay with collaboration partners in the US *Your profile:* - You are interested in investigating how cooperation, decision-making, and learning relate to human brain activity and how they go awry in psychiatric disorders. - You like to design experiments, devise models, and analyze various types of data. - You have experience in conducting and analyzing behavioral experiments with human participants. - You are fluent in English. For the postdoc position and for one of the PhD positions, knowledge of German is not necessary. *Requirements for the postdoc position:* - A PhD (completed or close to the completion) in neuroscience, cognitive science, psychology, economics, medicine, or a related discipline. - Experience in conducting and analyzing neuroimaging experiments (including familiarity with SPM, FSL, or similar programs). - Experience in using programming languages such as Matlab, R, or Python. - Experience in writing and publishing peer reviewed scientific papers. *Requirements for the PhD positions:* - A Master of Science or an equivalent degree in neuroscience, cognitive science, psychology, economics, medicine, or a related discipline. - Experience in programming and in conducting or analyzing neuroimaging experiments is a big plus. - One of the PhD candidates will be (partly) based in Heidelberg to test psychiatric patients. This position is ideal for applicants with an interest in clinical psychiatry and requires knowledge of German to interact with patients. *Application and job specifications:* Applications will be accepted until the positions are filled. The first review of applications will be in the beginning of September 2018. Preferred starting date is January 2019 but later starting dates may be possible. Salary depends on experience and is based on German regulations (the postdoc position is remunerated with the factor 100%, the PhD positions with the factor 65%). The appointments will be initially for 3 years with the possibility for continuation. The group is committed to maintaining a diverse and inclusive environment. If you are interested, please send one pdf-document including your CV, a brief statement of research interest, and the contact details of two academic referees to *c.korn(a)uke.de <c.korn(a)uke.de>*. Informal inquiries are welcome. Looking forward to hearing from you, Christoph

Aug. 3, 2018

A biologically motivated and more powerful alternative to locality-sensitive hashing

by Rod Rinkus

I believe this community will be interested in a new downloadable Java app that I 've just made available on my web site (on this page <http://www.sparsey.com/CSA_explainer_app_page.html>), which describes an alternative, biologically motivated/plausible, way to achieve the goals of locality-sensitive hashing (LSH). This alternative model, called Sparsey, achieves a more graded notion of similarity preservation than LSH, and has many other advantages as well. Sparsey has a natural correspondence to the brain's cortex, centering on the idea that all items of information are stored as sparse distributed codes (SDCs), a.k.a., cell assemblies, in superposition in mesoscale cortical modules, e.g., macrocolumns (though other structures, e.g., mushroom bodies, are also candidates). Briefly, Sparsey preserves similarity from input space to SDR code space (measured as intersection size) as follows. - The process of choosing an SDC takes the form of Q independent softmax choices, one in each of the Q WTA competitive modules (CMs) that comprise the SDR coding field. - The familiarity (inverse novelty) of the input, denoted "G", which is in [0,1], is computed. This is an extremely simple computation. - The amount of noise in those Q softmax choice processes is modulated as a function of G. Basically, the softmax is over the distribution of input summations of the competing cells (in a given CM), but we use G to modulate (i.e. sharpen vs. flatten) those distributions. - When G is near 1 (perfect familiarity), the distributions are greatly sharpened, causing the expected number of CMs in which the cell with the highest input summation wins (and thus, the expected intersection of the resulting SDR with the closest matching previously stored SDR) to increase towards Q. When G is near 0 (completely novel), the distributions are flattened, causing the expected number of CMs in which the cell with max input summation wins (and thus, the expected intersection of the resulting SDR with the closest matching previously stored SDR) to decrease towards chance. In other words, this G-based modulation of the distributions, which can be viewed as varying the amount of noise in the choice process, achieves similarity preservation. I encourage members of this community to explore the app to understand this simple and more powerful alternative to LSH. I welcome your feedback. Sincerely, Rod Rinkus -- Gerard (Rod) Rinkus, PhD President, rod at neurithmicsystems dot com Neurithmic Systems LLC <http://sparsey.com> 275 Grove Street, Suite 2-400 Newton, MA 02466 617-997-6272 Visiting Scientist, Lisman Lab Volen Center for Complex Systems Brandeis University, Waltham, MA grinkus at brandeis dot edu http://people.brandeis.edu/~grinkus/ <http://people.brandeis.edu/%7Egrinkus/>

Aug. 2, 2018

Postdoc position in Geometric Methods for Deep and Reinforcement Learning at RIST

by Luigi Malagò

=========================================================== *Subject*: Postdoc position in Machine Learning (1 year, renewable up to 2 years) *Institution*: RIST - Romanian Institute of Science and Technology, Cluj-Napoca *Keywords*: Deep Learning, Reinforcement Learning, Stochastic Optimization, Optimization over Manifolds, Information Geometry, Riemannian Geometry *Application deadline*: 15 August 2018 (applicants are encouraged to apply earlier) *Salary*: around 2200 euro net *Official announcement*: http://rist.ro/en/details/news/postdoc-positio ns-in-deep-learning-and-machine-learning.html =========================================================== Dear colleagues, the Romanian Institute of Science and Technology (RIST) has an opening for a postdoc position, in the context of the DeepRiemann project “Riemannian Optimization Methods for Deep Learning”, funded by European structural funds through the Competitiveness Operational Program (POC 2014-2020). The appointments will be for 1 year, with possible extensions up to 2 years. The DeepRiemann project aims at the design and analysis of novel training algorithms for Neural Networks in Deep Learning, by applying notions of Riemannian optimization and differential geometry. The task of the training a Neural Network is studied by employing tools from Optimization over Manifolds and Information Geometry, by casting the learning process to an optimization problem defined over a statistical manifold, i.e., a set of probability distributions. The project is highly interdisciplinary, with competences spanning from Machine Learning to Optimization, Deep Learning, Statistics, and Differential Geometry. The objectives of the project are multiple and include both theoretical and applied research, together with industrial activities oriented to transfer knowledge, from the institute to a startup or spin-off of the research group. The positions will be part of the new Machine Learning and Optimization group https://rist.ro/en/teams.html, which performs research at the intersection of Machine Learning, Stochastic Optimization, Deep Learning, and Optimization over Manifolds, using geometric methods based on Information Geometry. The group is one of two newly-formed groups in Machine Learning at RIST. The official job announcement can be seen here: http://rist.ro/en/details/news/postdoc-positions-in-deep-lea rning-and-machine-learning.html Informal inquiries can be sent to Dr. Luigi Malagò <malago(a)rist.ro>, principal investigator of the DeepRiemann project. Application deadline: 15 August 2018 (applicants are encouraged to apply earlier) best regards, Luigi Malagò

Aug. 2, 2018

PhD positions at the Univ. of Leicester (for UK/EU candidates only)

by Okun, Michael (Dr.)

Fully Funded PhD Studentships (for UK/EU candidates only) to work at Prof. Quian Quiroga's lab at the Centre for Systems Neuroscience, University of Leicester, UK ( www.le.ac.uk/csn ). The Centre for Systems Neuroscience at the University of Leicester, UK, offers up to 2, 3-Year Fully Funded (stipend plus fees) PhD positions for UK/EU candidates, to study single cell recordings in humans – performed in epileptic patients for curative surgery. The project will investigate concept cells (a.k.a. Jennifer Aniston neurons) – that means, neurons in the hippocampus and surrounding areas that selectively fire to specific concepts, like different pictures and the written or spoken name of a particular person (e.g. Quian Quiroga et al, Nature 2005; Quian Quiroga Nature Reviews Neuroscience 2012), which are involved in declarative memory functions. The successful candidate will contribute to performing recordings with patients in collaborating hospitals and the analysis of the data to investigate the role of these neurons in memory formation. Candidates should have very good quantitative skills (data processing, and programing e.g. in Matlab) and a strong background or interest in neuroscience. They should be able to work both independently and as part of a research team within the Centre for System Neuroscience at Leicester and with our external collaborators. Informal enquiries are welcome and should be made to Emma Hawkins, Research Centre Manager, eeh18(a)le.ac.uk or 0116 252 3249. Interested candidates should send their curriculum vitae and a brief description of their scientific interests to Emma Hawkins (eeh18(a)le.ac.uk) The closing date for the applications is Friday 5th September. Interviews are anticipated to take place on the 12th September.

Aug. 2, 2018