- Comp-neuro - lists.cnsorg.org

CFP: Workshop on Crossmodal Learning for Intelligent Robotics in conjunction with IEEE/RSJ IROS 2018

by Pablo Barros

**Apologies for cross-posting** 1st CALL FOR PAPERS for the international workshop: * Crossmodal Learning for Intelligent Robotics * in conjunction with IEEE/RSJ IROS 2018 * Madrid, Spain - Friday 5 October 2018 * * Website: http://www.informatik.uni-hamburg.de/wtm/WorkshopCLIR18/index.php * I. Aim and Scope The ability to efficiently process crossmodal information is a key feature of the human brain that provides a robust perceptual experience and behavioural responses. Consequently, the processing and integration of multisensory information streams such as vision, audio, haptics and proprioception play a crucial role in the development of autonomous agents and cognitive robots, yielding an efficient interaction with the environment also under conditions of sensory uncertainty. Multisensory representations have been shown to improve performance in the research areas of human-robot interaction and sensory-driven motor behaviour. The perception, integration, and segregation of multisensory cues improve the capability to physically interact with objects and persons with higher levels of autonomy. However, the multisensory input must be represented and integrated in an appropriate way so that they result in a reliable perceptual experience aimed to trigger adequate behavioural responses. The interplay of multisensory representations can be used to solve stimulus-driven conflicts for executive control. Embodied agents can develop complex sensorimotor behaviour through the interaction with a crossmodal environment, leading to the development and evaluation of scenarios that better reflect the challenges faced by operating robots in the real world. This half-day workshop focuses on presenting and discussing new findings, theories, systems, and trends in crossmodal learning applied to neurocognitive robotics. The workshop will feature a list of invited speakers with outstanding expertise in crossmodal learning. II. Target Audience This workshop is open to doctoral students and senior researchers working in computer and cognitive science, psychology, neuroscience and related areas with the focus on crossmodal learning. III. Confirmed Speakers 1. * Yulia Sandamirskaya * Institute of Neuroinformatics (INI), University and ETH Zurich 2. * Angelo Cangelosi * Plymouth University and University of Manchester, UK 3. * Stefan Wermter * Hamburg Universit, Germany IV. Submission 1. Topics of interest: - New methods and applications for crossmodal processing (e.g., integrating vision, audio, haptics, proprioception) - Machine learning and neural networks for multisensory robot perception - Computational models of crossmodal attention and perception - Bio-inspired approaches for crossmodal learning - Crossmodal conflict resolution and executive control - Sensorimotor learning for autonomous agents and robots - Crossmodal learning for embodied and cognitive robots 2. For paper submission, use the following IEEE template: <http://ras.papercept.net/conferences/support/support.php>* 3. Submitted papers should be limited to *2 pages (extended abstract)* or *4 pages (short paper)*. 4. Send your pdf file to barros(a)informatik.uni-hamburg.de AND jirak(a)informatik.uni-hamburg.de Selected contributions will be presented during the workshop as spotlight talks and in a poster session. Contributors to the workshop will be invited to submit extended versions of the manuscripts to a special issue (to be arranged). Submissions will be peer reviewed consistent with the journal practices. V. Important Dates * Paper submission deadline: August 15, 2018 * Notification of acceptance: September 5, 2018 * Camera-ready version: September 15, 2018 * Workshop: Friday 5 October 2018 VI. Organizers * German I. Parisi * Hamburg University, Germany * Pablo Barros * Hamburg University, Germany * Doreen Jirak * Hamburg University, Germany * Jun Tani * Okinawa Institute of Science and Technology, Japan * Yoonsuck Choe * Samsung Research & Texas A&M University, TX, USA -- Dr.rer.nat. Pablo Barros Postdoctoral Research Associate - Crossmodal Learning Project (CML) Knowledge Technology Department of Informatics University of Hamburg Vogt-Koelln-Str. 30 22527 Hamburg, Germany Phone: +49 40 42883 2535 Fax: +49 40 42883 2515 barros at informatik.uni-hamburg.de https://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.html https://www.inf.uni-hamburg.de/en/inst/ab/wtm/

June 1, 2018

Deadline extended to June 15th for abstracts for the 2nd International Youth Conference of Bionic Science and Engineering (IYCBE2018), 7th-9th November 2018, Odense, Denmark

by Jan-Matthias Braun

The deadline for abstract submission has been extended to June 15th, 23:59:59 Coordinated Universal Time (UTC). The 2nd International Youth Conference of Bionic Engineering (IYCBE2018) will be held on 7th-9th November 2018 in Odense, Denmark. WEBPAGE: http://iycbe2018.sdu.dk/ ****Abstract Submission Instructions and Publication Details**** The abstract should fit into 500 words, the title into 500 characters. Up to one figure or table can also be added. *Direct links to updated templates and all details are available at the conference webpage.* Then, submit your abstract on our submission page until 15th June 2018. https://easychair.org/my/conference.cgi?welcome=1;a=13832989;conf=iycbe2018 All accepted abstracts with oral or poster presentation will be published in Frontiers in Neurorobotics as an e-book. Selected authors may additionally be invited to submit extended versions for a conference Special Issue of Frontiers in Neurorobotics and Journal of Bionic Engineering. ****Plenary Talks**** John Hallam, University of Southern Denmark, Denmark Title: From Lizards to LEGO, and back again? Zhendong Dai, Nanjing University of Aeronautics and Astronautics, China Title: Biomimetic on gecko locomotion: revealing the biology mechanism and developing robot for engineering. Han Zhiwu, Jilin University, China Title: Title: Fabrication and Performance of Bionic Strain Component ****Keynote speakers**** Thierry Darmanin, University of Nice-Sophia Antipolis, France Title: Tunable Conducting Polymer Nanotubes with Special Wetting Properties Zhiguang Guo, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, China Title: Bioinspired Separation Materials for Liquid Lubricants Alexander Spröwitz, Max Planck Institute for Intelligent Systems, Germany Title: Implementing and Testing Bioinspired Mechanisms on Robots to Understand Legged Locomotion Massimo Sartori, University of Twente, Netherlands Title: Neuro-Mechanical Modelling for Man-Machine Interaction Lars Heepe, Kiel University, Germany Title: Biological and Biomimetic Surfaces: Adhesion, Friction, and Applications Limei Tian, Jilin University, China Title: Non-bactericidal coating of bionic surfaces used for anti-biofouling ****Important Dates**** *Extended* Abstract Submission Deadline: 15th June 2018, 23:59:59 UTC – SUBMISSION IS OPEN Notification of Acceptance: 20th August 2018 Camera Ready Submission: 20th September 2018 Early Registration: 20th September 2018 Conference: 7th-9th November 2018 ****Scope of the Conference**** To meet the demand of the bionic scientists for academic communication, the 2nd International Youth Conference of Bionic Engineering (ICBSE2018) will be held on 7th-9th November 2018 in Odense, Denmark. This conference will be supported by the Youth Committee of International Society of Bionic Engineering (ISBE) and Frontiers in Neurorobotics and organized by University of Southern Denmark and Nanjing University of Aeronautics & Astronautics. The objective of this interdisciplinary conference is to provide an international forum for youth or outstanding scientists and engineers around the world who are interested in the field of bionic science and engineering. All aspects of bionic science and engineering and application areas are welcome, including, but not limited to, the following topics: Bio-inspired Robotics Bio-inspired Sensors and Actuators Bio-inspired Energy Storage Bio-inspired Flexible Electronics Bio-Inspired Solar Cells Biomimetic Engineering Embodied Artificial Intelligence and Neurorobotics Functional Morphology Musculoskeletal Systems, Biomechanics Biological Interface and Functionalization Biomimetic Materials, Biomimetic Structures Mechanics, Biomimetic Surfaces Biomimetic Design Methodologies Bionic Fluid, Biological Systems and Brain-Inspired Computing and Neuromorphic Systems. ****Awards**** The best abstract, as well as the best poster, will be awarded at the conference. ****Conference Format**** The conference will be single track with additional poster sessions. ORGANIZING COMMITTEE The Honorary Chair: Julian Vincent General Chair: Poramate Manoonpong Vice-General Chairs: Limei Tian, Zhiguang Guo Program Chair: Jørgen C. Larsen Local Arrangement Chair: Danish Shaikh Publication Chairs: Jan-Matthias Braun, Xiaofeng Xiong Registration Chair: Tórur Andreassen Media Operation Chair: Mathias Thor Technical Support: Peter Billeschou, Leon Bonde Larsen, David Docherty

May 31, 2018

CfP: Computationally Intelligent Methods in Processing and Analysis of Neuronal Big Data at BI 2018, Arlington, Texas, USA.

by Mufti Mahmud

*[Apologies for cross posting.]* *Call for Paper for Special Session on * *Computationally Intelligent Methods in Processing and Analysis of Neuronal Big Data* *11th Brain Informatics Conference (BI 2018), Arlington, Texas, USA, December 7-9, 2018* *Web: http://uta.engineering/conferences/bi-2018/ <http://uta.engineering/conferences/bi-2018/>* Organizers: *Mufti Mahmud1, M Shamim Kaiser2, Ning Zhong3, Nitish V Thakor4* *1* *Computing and Technology, Nottingham Trent University, NG11 8NS – Nottingham, UK* 2*Institute of Information Technology, Jahangirnagar University, Savar, 1342 – Dhaka, Bangladesh* 3*Dept. of Life Science and Informatics, Maebashi Institute of Technology, 371-0816 - Maebashi-City, Japan* *4**Singapore Institute for Neurotechnology, National University of Singapore, 117456 – Singapore; & * *Dept. of Biomedical Engineering, Johns Hopkins University, Baltimore, 21205 – MD, USA* *Introduction:* The brain receives and processes information simultaneously coming from diverse sources. The neurons, being the basic information processing units, interconnect to each other to form hierarchical and/or parallel pathways. Technologies related to neural systems engineering have been employed to study these pathways along with processing and modelling of neuronal data for disease diagnosis and brain decoding purposes. Combining both experimental and computational approaches in recent years, thanks to the advancements in neurotechniques, scientists can access large amount of neuronal data and apply computationally intelligent and nature-inspired machine learning techniques including deep learning and reinforcement learning on those data to suggest next generation experimental design aiming to decipher brain’s information processing capabilities and diagnose its diseases. *Scope:* Developing data-intensive and intelligent tools, as well as sophisticated neurotechniques, to process and analyse the neuronal big data is one of the biggest challenges posed to today’s multidisciplinary brain science community. To share recent progress in decoding neuronal information processing, both in healthy and diseased brain, this special session aims to provide a forum for scientists from diverse disciplines including – computer, electrical, biomedical, and neuro engineering – who are looking for more relevant information in interpreting brain functions and diagnosing diseases using expert and computationally intelligent systems. This special session expects to attract papers on recent research progress in the area of intelligent computational tools and techniques in acquiring and processing neuronal big data. The focus areas include, but not limited to, the following: Ø Neural systems engineering and technology to study neural pathways; Ø Processing and modelling of neuronal data for disease diagnosis and brain decoding; Ø Bio-inspired methods for network analysis and pattern recognition in neural data; Ø Novel machine learning techniques for neuronal big data analysis; Ø Application of deep and reinforcement learning to neuronal big data analysis; Ø Computationally intelligent techniques for neuroscience applications; Ø Neuroinformatics (including cloud computing and real-time systems); Ø Cognitive science applications (learning, workload, decision making, etc.) and data analytics; Ø Computational and imaging methods for human brain connectome; and Ø Information analysis in human brain machine interface (invasive, noninvasive). *Submission of papers:* Submit Springer Lecture Notes in Computer Science (LNCS) complaint – 10 page – pdf paper to the Special Session following the steps below: Ø Prepare the paper as per the Springer LNCS template from: http://www.springer.com/us/computer-science/lncs/conference-proceedings-gui… Ø Visit https://wi-lab.com/cyberchair/2018/bi18/scripts/ws_submit.php?subarea=S Ø Select the link: Special session on Computationally Intelligent Methods in Processing and Analysis of Neuronal Big Data Ø Select the link Submit a New Paper (TYPE I Submission) Ø Provide paper details (i.e., Author(s), Paper Title, Abstract, Keywords, PDF file to upload). *Important dates:* Ø Paper submission deadline: *30 July 2018* Ø Decision notification: *30 August 2018* Ø Special Session date: *7 December 2018* Ø Conference dates: *8-9 December 2018*. -- *Mufti Mahmud, PhD* | (Senior) Lecturer of Computing & Technology <https://www.ntu.ac.uk/sat/about/academic_teams/comp_tech.html> | School of Science & Technology <https://www.ntu.ac.uk/sat/> Office: ERD200 | Nottingham Trent University <https://www.ntu.ac.uk/> | Clifton Campus | NG11 8NS – Nottingham, UK Phone: +44 (0)115 84 83202 | Email: mufti.mahmud(a)ntu.ac.uk Meeting requests: https://doodle.com/mufti http://orcid.org/0000-0002-2037-8348 https://sites.google.com/site/muftimahmud/ https://scholar.google.com/citations?user=L8em2YoAAAAJ&hl=en Senior Member, IEEE <https://www.ieee.org/> & ACM <https://www.acm.org/> Associate Editor, IEEE Access <http://ieeeaccess.ieee.org/> Editorial Board Member, Cognitive Computation <https://www.springer.com/biomed/neuroscience/journal/12559> & Big Data Analytics <https://bdataanalytics.biomedcentral.com/>

May 31, 2018

New book: Neural Information Theory

by James V Stone

I'd like to announce the publication of this book: Principles of Neural Information Theory: Computational Neuroscience and Metabolic Efficiency by James V Stone. Reviews, synopsis, and table of contents can be found here: http://sebtelpress.com regards, James V Stone, University of Sheffield, UK.

May 31, 2018

[High Performance Computing] Become a specialist!

by Master in HPC

May 31, 2018

PhD studentship in Biocomputation Research Group, Centre for Computer Science and Informatics Research, University of Hertfordshire

by Shabnam Kadir

Applications are invited for a *PhD studentship* on *Computational frameworks for high-dimensional neural data* with *Dr. Shabnam Kadir *in the *Biocomputation Research Group* in the Centre for Computer Science and Informatics Research, University of Hertfordshire, U.K. *Project Description* New developments in experimental technology have led to petabytes of raw data being produced by experimental neuroscientists, which are increasingly publicly available, e.g. Allen Institute data http://www.brain-map.org/. In particular, we are in the realm where population recordings of tens of thousands of neurons are feasible thanks to, e.g. a new generation of large dense probes for electrophysiological recordings, imaging using 2-photon microscopy coupled with calcium fluorescent sensors. Large scale neuronal recordings require novel approaches for both processing and quantitative analysis. As well as using techniques from high-dimensional statistics, machine learning, information theory, we aim to explore new approaches from mathematical fields outside statistics, such as algebraic topology. The study of networks is a particularly important topic in neuroscience: neurons communicate with each other electrically via synapses, forming intricate networks. These networks can be studied using techniques from computational topology (e.g. persistent homology, clique topology). These could be used to extract information about subnetworks and assemblies, both from large scale recordings, and via connectomics derived from simulations (Blue Brain Project). We aim in this project to go beyond spike sorting and develop new tools and computational frameworks which would help interpret high dimensional data and interrogate how information is being processed by the brain, e.g. How are sensory stimuli (location in environment, visual and auditory stimuli) encoded? How can we characterise the neural activity associated with memory, attention, decision making and motor control? We shall be collaborating with labs at Imperial, Pennsylvania State University and UCL. More information can be found here: http://www.herts.ac.uk/_ _data/assets/pdf_file/0003/187455/Dec2017-computational-fram eworks-for-high-dimensional-neural-data.pdf *Requirements * We are looking for candidates with the following profile: - Strong first degree in a quantitative field such as mathematics, physics, computer science, engineering, computational neuroscience. - Strong programming skills (e.g. Python, MATLAB, C++). - Interest in neuroscience and biology would be helpful. A studentship from the PhD Programme in Computer Science provides approximately £14,750 per annum bursary plus the payment of student fees. Applicants from outside the UK or EU are eligible. Research in Computer Science at the University of Hertfordshire has been recognised as excellent in the latest Research Excellence Framework Assessment (2014), with 50% of the research submitted rated as internationally excellent or world-leading. The Centre for Computer Science and Informatics Research provides a very stimulating environment, offering a large number of specialised and interdisciplinary seminars as well as general training and researcher development opportunities. The University is situated in Hatfield, in the green belt just north of London. Please contact *Dr Shabnam Kadir* (s.kadir2(a)herts.ac.uk) for informal enquiries. Application forms are available under http://www.herts.ac.uk/a pply/schools-of-study/computer-science/our-research/the-phd- programme-in-computer-science and should be returned to Mrs Lorraine Nicholls and Mrs Emma Thorogood, Research Student Administrators, University of Hertfordshire, College Lane, Hatfield, Herts, AL10 9AB, Tel: 01707 286083, doctoralcollegeadmissions(a)herts.ac.uk. The short-listing process will begin on 25th June 2018. ------------------------------------------------------------ ---------------------------------------------------- Dr Shabnam Kadir Senior Lecturer School of Computer Science, University of Hertfordshire, Hatfield, Hertfordshire AL10 9AB, United Kingdom. Tel. +44 1707 284641 ------------------------------------------------------------ ----------------------------------------------------

May 30, 2018

Faculty position in systems neuroscience, U of Montreal

by Paul Cisek

Professor in Systems/Computational Neuroscience Faculty of medicine / Department of neurosciences Mandate description The Département de neurosciences at the Université de Montréal invites applications for a faculty position at the assistant or associate level, in Systems/Computational Neuroscience. We are seeking candidates who use experimental and/or computational approaches to study how large-scale distributed brain networks implement behavioural-level phenomena such as sensorimotor control and decision-making, with a particular emphasis on system-level learning mechanisms. Ideal candidates will either combine multi-electrode, multi-area neurophysiological studies in behaving animals (in particular non-human primates) with sophisticated computational modeling of brain function, or alternatively, will use predominantly computational approaches to study how biologically realistic large-scale and recurrent network models simulate behavioral-level phenomena. The Département de neurosciences offers state of the art laboratory space and animal facilities for rodent and non-human primates research. Montréal is a rich academic environment, with 4 major universities and a strong tradition of systems neuroscience. The candidates will have outstanding opportunities for collaborations with other systems neuroscientists at the Université de Montréal, McGill University, Concordia University and the Université du Québec à Montréal, as well as with leading experts in artificial intelligence, machine learning and deep-learning networks who are centered in the MILA/IVADO at the Université de Montréal. Responsibilities - The appointed candidate will be expected to maintain an active research program, supervise graduate students, have international collaborations, contribute to the academic life of the Department of Neurosciences, and teach undergraduate and graduate courses. - The candidate will collaborate closely with researchers working in three affiliated research centers at University of Montreal: CHU-Ste Justine (Pediatric Hospital), Centre Hospitalier Universitaire de Montréal, Hôpital du Sacré-Coeur de Montréal. - The teaching language is French; consequently, non-French-speaking candidates should become able to teach in French no longer than three years after their appointment. Requirements - The candidate needs to hold a PhD in neurosciences (or equivalent) and demonstrate significant experience at the post-doctoral level in the field of computational neurosciences. - The candidate needs to show exceptional track record in the field, including in sensorimotor control, decision making, neurophysiological studies in living animal, and computational approaches in order to study how neural network are modeling behavior. - The candidate needs to hold teaching experience at graduate and undergraduate levels, as well as experience in supervising post-doctoral fellowships, research assistants, and highly qualified research personal. - We will prioritize candidates with exceptional research productivity with a publication of articles in the best journals in the field, as well as a strong track record of research funding from national and international research agencies. - The ability and interest of the candidate to work in a multidisciplinary team (biochemists, biologists, engineers, bio informaticians, and clinicians) is mandatory. - Have sufficient knowledge of the French language (written and spoken) or be determined to learn it *. General information Posting No: MED 4-18 / 4 Posting period: June 15th, 2018 Salary: The University of Montreal offers a competitive salary and a complete range of employee benefits Start date: Autumn 2018. The announcement will remain open until the selection committee finds an acceptable candidacy. Application procedure Interested candidates should send their curriculum vitae, a letter explaining their motivation, research interest and competence in their area of expertise, and three letters of support, no later than June 15th 2018; at the following address (email correspondence is preferred): Dr Patrick Cossette, directeur Département de neurosciences Faculté de médecine Université de Montréal C.P. 6128, succursale Centre-ville Montréal (Québec) H3C 3J7 E-mail : nancy.crete(a)umontreal.ca <mailto:nancy.crete@umontreal.ca> *Linguistic Policy The Université de Montréal is a Québec University with an international reputation. French is the language of instruction. To renew its teaching faculty, the University is intensively recruiting the worlds best specialists. In accordance with the institutions language policy, the Université de Montréal provides support for newly-recruited faculty to attain proficiency in French. Confidentiality The Université de Montréal application process allows all regular professors in the Department to have access to all documents unless the applicant explicitly states in her or his cover letter that access to the application should be limited to the selection committee. This restriction on accessibility will be lifted if the applicant is invited for an interview. Equal Access Employment Program Université de Montréal promotes diversity in its workforce and encourages members of visible and ethnic minorities as well as women, Aboriginal people, persons with disabilities and people of all sexual orientations and gender identities to apply. Immigration Requirements We invite all qualified candidates to apply at Université de Montréal. However, in accordance with immigration requirements in Canada, please note that priority will be given to Canadian citizens and permanent residents. Paul Cisek, PhD Département de neurosciences Université de Montréal Physical: 2960 chemin de la tour, local 4117 Montréal, QC H3T 1J4 CANADA Mailing: CP 6128 Succursale centre-ville, Montréal, QC H3C 3J7 CANADA e-mail: <mailto:paul.cisek@gmail.com> paul.cisek(a)gmail.com Web: www.cisek.org/pavel <http://www.cisek.org/pavel>

May 30, 2018

SenseLab survey

by Ted Carnevale

The SenseLab project applies neuroinformatics methods to make it easier to discover, understand, and reuse neuroscience models, and to relate those models to experimental data. We invite you to help guide the future development of ModelDB http://modeldb.yale.edu and the other SenseLab databases by taking this short survey: https://yalesurvey.ca1.qualtrics.com/jfe/form/SV_2sZuf5bxk99nTnf (Yale recipients: the survey's original URL is https:// yalesurvey.ca1.qualtrics.com/jfe/form/SV_2sZuf5bxk99nTnf minus the space between // and yalesurvey) The SenseLab Team https://senselab.med.yale.edu/ModelDB/modeldb_credits.cshtml

May 29, 2018

Multiple Openings for Research Scientists and Engineers to Reverse Engineer intelligence

by Lopez, Camila

Hi, Can you please post this job ad? Multiple Openings for Research Scientists and Engineers to Reverse Engineer intelligence We are looking for exceptionally talented researchers that share our vision: to discover new computational principles of brain intelligence and apply these principles to create fundamentally new algorithms for machine intelligence. We are particularly interested in candidates with expertise in machine learning, computational neuroscience or with strong quantitative background in Mathematics, Statistics, Physics or Computer Science. Our NINAI (Neuro-Inspired Networks for Artificial Intelligence) research team is interdisciplinary and international, with expertise ranging from large-scale neurophysiology and brain circuit analysis to deep learning. POSITIONS: We have opportunities in several project components and multiple locations, and all participants will interact extensively across multiple scientific disciplines and multiple sites. Highest-priority topics include: * Developing new architectures for deep networks * Neuro-inspired networks for real-world tasks * Functional modeling of neuronal microcircuits * Probabilistic inference by population codes * Statistical analysis of large-scale neural data from behaving animals THE TEAM: The project is led by Andreas Tolias (PI) and Xaq Pitkow (co-PI), from Baylor College of Medicine, and includes researchers from Columbia, Cornell, Rice University, University of Toronto, University of Tübingen, the Allen Institute, and Princeton: Matthias Bethge, Liam Paninski, Ankit Patel, Clay Reid, Sebastian Seung, Raquel Urtasun, Chris Xu, Richard Zemel. For detailed information about the team and its members, please see our website, ninai.org<http://ninai.org/>. QUALIFICATIONS: Candidates must have a record of productivity, excellent quantitative skills, good communication skills, and creativity. Experience in Machine Learning and in particular Deep Learning is desired. APPLYING: The positions provide a competitive annual salary and benefits, and outstanding scientific opportunities. Applicants should email a CV, letter of research interests, and contact information for three references to info(a)ninai.org<mailto:info@ninai.org>, camilal(a)bcm.edu<mailto:camilal@bcm.edu> and astolias(a)bcm.edu<mailto:astolias@bcm.edu>. We look forward to hearing from you!

May 29, 2018

IEEE Special issue deadline extended!

by Steve Mehrkanoon

Paper Submission Deadline Extended! CALL FOR PAPERS Special issue: Neural Systems Engineering and Mathematical Modelling of Brain dynamics using ECoG/EEG/MEG oscillations and Machine learning methods Journal IEEE Transactions on Neural Systems and Rehabilitation Engineering New Submission Deadline: 01/07/2018 Submission portal: https://mc.manuscriptcentral.com/tnsre-embs Contributions will receive prompt and thorough peer review and will be published online ahead of print after acceptance. In humans, interactions between neuronal circuits, systems and signals among micro-, meso- and macro-scales of brain dynamics underpin the functional organisation of the brain that supports our daily life activity. How efficiently neuronal circuits such as cortico-cortical, cortico-thalamic and thalamo-cortical networks interact among these multiple spatial scales remains to be fully elucidated. Mathematical, computational and experimental neuroscientists apply a variety of methods, techniques and algorithms, both in animals and humans, ranging from single cell recordings to whole brain imaging, in order to identify the core mechanisms that govern the interactions among these scales. Although our knowledge of neural mechanisms, circuits and networks underlying brain dynamics and functions constantly grows, the integration of this knowledge to provide a conceptual framework of emergent behaviour and pattern formation occurring on different levels of spatial organisation remains challenging. Authors are invited to submit original or review articles addressing mechanisms of emergent brain dynamics inferred from the analysis of ECoG/EEG/MEG, on all levels of complexity. Specifically, articles integrating (i) computational neuroscience, and (ii) mathematical models of biologically realistic neuronal networks and machine learning methods are welcome. In this special issue, Guest Editor Dr Steve Mehrkanoon welcomes papers that address many of the challenges of mathematical and computational models of the brain networks and dynamics given the measurement data ECoG/EEG/MEG. The scope of this special issue is interdisciplinary. The list of possible topics includes, but is not limited to: * New developments in computational and mathematical models of mean field theory integrated with ECoG/EEG/MEG modalities. * Multi-modal and combinatorial fusion of ECoG/EEG/MEG data and brain connectivity machine learning. * Development of data-driven machine learning techniques to identify the mechanisms of emergent spatia-temporal dynamics within the framework of network topology. * Development of computational and mathematical models for bridging the scales of brain dynamics. * Cortical network modelling and formal conceptual models of cortical oscillations. * Application of deep learning and machine learning algorithms in functional, structural and effective network analysis and predictive models of brain dynamics. * New cutting-edge numerical analysis and techniques to simulate meso- and macro-scale brain dynamics. * Adaptive mathematical and computational models of network dynamics (e.g., brain development and aging studies). * Statistical methods for assessing individual and population brain connectivity data. Guest Editors 1. Dr Steve Mehrkanoon The University of Queensland Centre for Clinical Research, Faculty of Medicine, School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia Contact: s.mehrkanoon(a)uq.edu.au<mailto:s.mehrkanoon@uq.edu.au> 1. Professor David Liley Centre for Human Psychopharmacology, School of Health Sciences, Swinburne University of Technology, Melbourne, Australia Contact: dliley(a)swin.edu.au<mailto:dliley@swin.edu.au> 1. Dr Siamak Mehrkanoon Department of Electrical Engineering (ESAT), University of Leuven, KU Leuven, Belgium Contact: Siamak.Mehrkanoon(a)esat.kuleuven.be<mailto:Siamak.Mehrkanoon@esat.kuleuven.be> IMPORTANT DATES Extended Submission Deadline: 01/07/2018 Notification Of Acceptance: 31/08/2018 https://tnsre.embs.org/2018/04/13/call-for-papers-special-issue-on-neural-s…) - - - Dr Steve Mehrkanoon Mathematical Neuroscientist, Advance Queensland Research Fellow, Perinatal Research Centre, Faculty of Medicine, Home: http://researchers.uq.edu.au/researcher/14135 Level 4, UQ Centre for Clinical Research, Building 71/918<https://www.google.com.au/maps/place/UQCCR/@-27.448514,153.028703,15z/data=…> Royal Brisbane and Women’s Hospital, Qld 4029 T: +61 7 3346 6012 E: s.mehrkanoon(a)uq.edu.au<mailto:j.wixey@uq.edu.au>

May 29, 2018

PhD Position available: Computational methods for longitudinal studies of structural brain connectivity, Deadline 31/5/18

by Emanuele Olivetti

PhD position available (online application details below) Title: Computational methods for longitudinal studies of structural brain connectivity Topic: machine learning / pattern recognition for diffusion MRI data analysis Description: Diffusion MRI provides indirect information of the anatomical structure of the white matter of the brain. Neurological diseases and brain disorders may introduce alterations in such structures. Additionally, after neurosurgery and cognitive rehabilitation, there may be reorganization of the white matter. The goal of this project is to design computational methods to detect and characterize white matter changes over time, disentangling the intrinsic variability of brain recordings from actual anatomical changes, in order to support neuroscientific and clinical inference. References: - https://doi.org/10.3389/fnins.2016.00554 - https://doi.org/10.3389/fnins.2017.00754 Emanuele Olivetti ---------- Forwarded message ---------- From: *PhD CIMeC* <phd.cimec(a)unitn.it <mailto:phd.cimec@unitn.it>> Date: Thu, May 24, 2018 at 10:04 AM Subject: PhD Position available: Computational methods for longitudinal studies of structural brain connectivity, Deadline 31/5/18 To: CIMeC is pleased to announce the opening of a call for 11 fellowships for our international PhD Program in Cognitive and Brain Sciences (CIMeC), commencing November 2018 at the University of Trento, Italy. As you will see from the links below, the PhD call is open to several fields of cognitive neuroscience research. Candidates interested in*Computational methods for longitudinal studies of structural brain connectivity <http://www.unitn.it/drcimec/topic-specific-grants> *should contact *Emanuele Olivetti *at olivetti(a)fbk.eu <mailto:olivetti@fbk.eu>**immediately*.* * *Admissions*: http://www.unitn.it/drcimec/admission <http://www.unitn.it/drcimec/admission> * PhD research areas outline: http://www.unitn.it/drcimec/research-topics <http://www.unitn.it/drcimec/research-topics> * PhD Application*summary*: http://www.unitn.it/drcimec/node/118 <http://www.unitn.it/drcimec/node/118> * PhD*Application*link:https://webapps.unitn.it/Apply/en/MyUnitn/Home/669/dott/cbs34 <https://webapps.unitn.it/Apply/en/MyUnitn/Home/669/dott/cbs34> * PhD Application*Deadline*:*Thursday May 31, 2018, at 4pm (Italian time)* * *CIMeC*:http://www.unitn.it/cimec <http://www.unitn.it/cimec> This year’s research topics proposed by the Doctoral Program Committee for 5 UNITN grants are visible here:http://www.unitn.it/drcimec/research-topics <http://www.unitn.it/drcimec/research-topics>, while the 6 topic-specific grants’ details can be found here:http://www.unitn.it/drcimec/topic-specific-grants <http://www.unitn.it/drcimec/topic-specific-grants> _The CIMeC, it’s doctoral program and UNITN in numbers:_ * 2018 UNITrento ranks among top Italian Universities in THE - Times Higher Education * *4-yr program*(Nov. 1, 2018- Oct. 31, 2022). * Why a 4-yr program <http://www.unitn.it/drcimec/node/117> * Courses are given in English * 11 positions, 100% funded * Salary: starting at approximately €1.200/mo., net * Winners receive a €4887 tax-free research/mobility budget * Why choose UNITRENTO <http://www.unitn.it/en/ateneo/1629/why-choose-the-university-of-trento> Please feel free to browse theFAQ <http://www.unitn.it/drcimec/node/122>pages on our website for further information, or contact the Director of the Programme, Prof. Francesco Pavaniphd.cimec(a)unitn.it <mailto:phd.cimec@unitn.it>. Regards, Leah Mercanti -- Leah Mercanti CIMeC PhD Program Administrator -------------------------------------------------------- CIMeC - Center for Mind/Brain Sciences University of Trento <https://maps.google.com/?q=Trento+Corso+Bettini,+31+I-38068,+Rovereto&entry…> Corso Bettini, 31 <https://maps.google.com/?q=Trento+Corso+Bettini,+31+I-38068,+Rovereto&entry…> I-38068, Rovereto <https://maps.google.com/?q=Trento+Corso+Bettini,+31+I-38068,+Rovereto&entry…> (TN) Tel: +39 0464 80 8617 Fax: +39 0461 28 8690 Skypename: lleahhatwork Email: phd.cimec(a)unitn.it <mailto:phd.cimec@unitn.it> http://www.unitn.it/drcimec/ -- Le informazioni contenute nella presente comunicazione sono di natura privata e come tali sono da considerarsi riservate ed indirizzate esclusivamente ai destinatari indicati e per le finalità strettamente legate al relativo contenuto. Se avete ricevuto questo messaggio per errore, vi preghiamo di eliminarlo e di inviare una comunicazione all’indirizzo e-mail del mittente. -- The information transmitted is intended only for the person or entity to which it is addressed and may contain confidential and/or privileged material. If you received this in error, please contact the sender and delete the material.

May 28, 2018

Professorship in Computational Neuroscience

by Steuber, Volker

Professor of Computational Neuroscience University of Hertfordshire School of Computer Science, College Lane Campus, Hatfield, UK Salary £58,293 to £67,437 pa depending on skills and experience FTE: Full time position working 37 hours per week (1.0 FTE). Closing date: 21 June 2018 Duration of Contract: Permanent. Applications are invited for an exceptionally well qualified Professor of Computational Neuroscience of international standing, who shares our commitment to research-informed teaching, embraces the research impact agenda, and values collegiality. Applicants will strengthen existing activity within the School and develop it further, enhancing the research strengths and external reputation of the School of Computer Science and contributing significantly to its performance in future research assessments and collaborations with commercial and public partners. The successful applicant will complement the research conducted by the Biocomputation Research Group within the Centre for Computer Science and Informatics Research. As well as providing research supervision at PhD and MSc level, the School of Computer Science offers modules in neural computing and machine learning on the BSc and MSc programmes. Applicants must hold a PhD (or equivalent) in a relevant subject, possess excellent communication skills in English, an internationally excellent research record and reputation, including publications of the highest quality suitable for submission to the REF. Applicants must show evidence of experience and success in research/commercial income generation, engagement with the research impact agenda, engagement with key stakeholders in the Computational Neuroscience community, and management and leadership ability.? Interview Date: Week commencing 17 September 2018. The University offers a range of benefits including a pension scheme, professional development, family friendly policies, child care vouchers, a fee waiver of 50% for all children of staff under the age of 21 at the start of the course, discounted memberships at the Hertfordshire Sports Village and generous annual leave. The University is situated in Hatfield, in the green belt just north of London. Applications must be made online https://www.herts.ac.uk/contact-us/jobs-and-vacancies/academic-vacancies?, reference 016195?. For informal enquiries contact Dr Volker Steuber (v.steuber(a)herts.ac.uk, Head of Biocomputation Research Group, Associate Dean Research) or Prof William Clocksin (w.clocksin(a)herts.ac.uk, Dean of School of Computer Science).

May 25, 2018

PhD Studentship in Multilevel modelling of neuronal function: combining metabotropic pathways and membrane excitability in-silico for the quick screening of drugs

by Tsaneva-Atanasova, Krasimira

PhD Studentship in Quantitative Pharmacology and Neuroscience: Multilevel modelling of neuronal function: combining metabotropic pathways and membrane excitability in-silico for the quick screening of drugs University of Reading - School of Pharmacy Supervisors: Dr Francesco Tamagnini (Pharmacy), Dr Marcus Tindall (Mathematics & Statistics), Prof Krasimira Tsaneva-Atanasova (University of Exeter, College of Mathematics, Engineering and Physical Sciences). Project overview: Neurons work as information relays. They integrate information received from the environment at the subcellular scale, generating an appropriate electrophysiological response. The understanding of electrical processes happening at the plasma membrane level has been clarified by Hodgkin and Huxley, combining experimental recordings to mathematical modelling of equivalent electrical circuits. However, quantitative models describing the effects of cell signalling on the cellular response are lacking. Adenosine is a neurotransmitter binding both A1 (Gi) and A2 (Gs) receptors. A1 and A2 stimulation results in altered neuronal excitability via K+ permeability changes. In this project, we aim to combine a mathematical model of adenosine receptor signal transduction (Tindall) with the Hodgkin-Huxley model of a neuron (Tsaneva-Atanasova), to generate an in-silico multiscale model of electrophysiological response to chemical stimulation. We will test the predictive capability of the model with whole-neuron patch-clamp recordings (Tamagnini). The mathematical models formulated during the project will utilise the theory of differential equations (ordinary and partial) solved and analysed both numerically and analytically (e.g. dynamical systems theory, asymptotic methods). The successful candidate will be involved in the design and undertaking of wet laboratory experiments for informing the mathematical models. The final aim of this project is to develop and validate a software capable of predicting changes to an artificial neuron based on its exposure to varying concentrations of a given ligand. Eligibility: * Applicants should hold or expect to gain a minimum of a 2:1 Bachelor Degree or equivalent in Mathematics, Engineering or Neuroscience related subjects. The applicant will have a strong background in mathematics and computer coding (Matlab, Python, C++) and a keenness to engage with and learn wet lab techniques (i.e. pipetting, solution making, single cell electrophysiology); * This studentship is open to UK/EU students only. Funding details: * Starts 10/2018; * 3-year award; * Tuition fees plus stipend (Research Council UK 2018/19 rate is currently £14,777). How to apply: To apply for this studentship, please submit an application for a PhD in Pharmacy at http://www.reading.ac.uk/graduateschool/prospectivestudents/gs-how-to-apply…. Important notes: 1. Please quote the reference ‘GS18-018’ in the ‘Scholarships applied for’ box which appears within the Funding Section of your online application. 2. When you are prompted to upload a research proposal, please omit this step. Application deadline: 30th June 2018. Further enquiries: Please note that, where a candidate is successful in being awarded funding, this will be confirmed via a formal studentship award letter; this will be provided separately from any Offer of Admission and will be subject to standard checks for eligibility and other criteria. For further details, please contact: f.tamagnini(a)reading.ac.uk.<mailto:f.tamagnini@reading.ac.uk>

May 25, 2018

Faculty position at UNAM Institute of Neurobiology (Mexico)

by Fidel Santamaria

Computational and Genomic Neuroscience at UNAM The Institute of Neurobiology, UNAM (www.inb.unam.mx<http://www.inb.unam.mx>) invites applications for two tenure-track positions, one in Computational Neuroscience and another one in Genomic Neuroscience. We seek experienced scientists with proven record of publications to develop innovative research programs employing on-campus high performance computing resources to complement the current neuroscience research at the Institute. The successful applicants will be expected to establish externally funded research programs, to engage in intramural collaborative projects, to supervise undergraduate and graduate students, and to teach basic and advanced courses in their field of expertise. Applicants should send their CV, addresses of three references, a five-page research proposal and a one-page statement on their views on teaching to ataulfo(a)unam.mx<mailto:ataulfo@unam.mx>. The application deadline is August 15th, 2018. We encourage applications from women. Instituto de Neurobiología Universidad Nacional Autónoma de México Laboratorio de Neurobiología Molecular y Celular (D15) Juriquilla, Querétaro, QRO CP 76230 Tel. +52 (442) 238-1064 Email ataulfo(a)unam.mx<mailto:ataulfo@unam.mx> atanez(a)gmail.com<mailto:atanez@gmail.com> Skype atanez1

May 24, 2018

Post-baccalaureate research position in neuronal mechanism of episodic memory at Max Planck Florida Institute for Neuroscience

by Yingxue.Wang＠mpfi.org

*** Apologies for cross posting*** Post-Baccalaureate Research Experience Summary The Wang Lab at the Max Planck Florida Institute for Neuroscience (links to website<https://yingxuewang.org/>) is inviting applications for the post-baccalaureate research program. This one-year program provides research experience and exposure to students who have graduated from college and are planning to apply to graduate school. We seek highly motivated and independent individuals to join our effort focused on the neuronal mechanisms of learning and episodic memory. Essential Duties & Responsibilities The Wang Lab investigates the circuit underpinnings of episodic memory. In particular, we intend to isolate the hippocampal neuronal activities that are independent of sensory inputs and potentially represent memory traces. We seek to understand how elements of the hippocampal circuit cooperate to generate the internally generated neuronal activities and support the formation and retrieval of memory. Our investigation employs a combination of in vivo electrophysiological, advanced two-photon imaging, optogenetic, and pharmacological approaches, and couples experiments with computational modeling. We encourage applications from candidates who are interested in applying multidisciplinary approaches to examine circuit mechanisms of memory. Education and/or Experience The ideal candidates should have an upcoming or recent bachelor degree in neuroscience or related fields. Candidates holding a degree in electrical engineering, biomedical engineering, computer science, or physics and interested in understanding the neuronal mechanisms of learning and memory are also welcome to apply. Previous experience with in vivo electrophysiology and/or two-photon imaging, quantitative data analysis and computer programming is preferred. Excellent communication skills and an ability to work well in a team are required. Additional Information Max Planck Florida Institute for Neuroscience is part of the Jupiter Neuroscience Research Campus that also includes the Scripps Research Institute Florida and Florida Atlantic University. It provides a flourishing interdisciplinary research environment for neuroscience. Interested candidates are encouraged to send the following documents to Dr. Yingxue Wang (email address: Yingxue.Wang(a)mpfi.org<mailto:Yingxue.Wang@mpfi.org>): - Curriculum vitae - A statement of motivation and interests (1-2 pages) - Academic certificates and transcripts - The names and contact information of two references Please find more details about this program at https://www.maxplanckflorida.org/education/training-programs/pre/. The official application deadline has already passed. Please address the request directly to the above email address. Best regards, Yingxue Wang Research Group Leader Max Planck Florida Institute for Neuroscience

May 23, 2018

Postdoctoral Position in Brain-Computer Interfaces

by Tomislav Milekovic

The research group Dr. Tomislav Milekovic at the University of Geneva is offering a postdoctoral position financed by the Wyss Center for Bio and Neuroengineering and the Swiss National Science Foundation to work on restoring communication and independence of people with tetraplegia and locked-in syndrome using brain-computer interfaces. The successful applicant will work to develop and advance brain-computer interfaces based on electroencephalography (EEG) and intracortical microelectrode array recordings. The ideal candidate will have: 1. Experience in assembling and maintaining brain-computer interface systems 2. Leading brain-computer interface experiments with human or animal subjects 3. Experience in the quantitative analysis of electrophysiological neural signals (EEG, ECoG, LFP, spikes) 4. Background in computational/theoretical neuroscience, physics or mathematics 5. Experience in developing and using neural decoders 6. Experience in C/C++ software development The qualified candidate will benefit from joining a very dynamic and multidisciplinary group working at the interface of neuroscience, engineering and prosthetics. They will collaborate with several labs of the Campus Biotech in Geneva, and be strongly supported by the Wyss center for Bio and Neuroengineering led by Prof. John Donoghue. University of Geneva provides state-of-the-art facilities is one of the leading technical universities worldwide. In addition, University of Geneva offers competitive postdoctoral salaries ranking among the highest in the world. Applications including a CV and the statement of research interests should be sent to tomislav.milekovic(a)unige.ch<mailto:tomislav.milekovic@unige.ch>.

May 23, 2018

Postdoc position in neuronal mechanism of episodic memory at Max Planck Florida Institute for Neuroscience

by Yingxue.Wang＠mpfi.org

*** Apologies for cross posting*** Postdoctoral Fellow Summary The Wang Lab at the Max Planck Florida Institute for Neuroscience (links to website<https://yingxuewang.org/>) is inviting applications for postdoctoral positions. Our group seeks highly motivated and independent individuals to join our effort focused on the neuronal mechanisms of learning and episodic memory. Essential Duties & Responsibilities The Wang Lab investigates the circuit underpinnings of episodic memory. In particular, we intend to isolate the hippocampal neuronal activities that are independent of sensory inputs and potentially represent memory traces. We seek to understand how elements of the hippocampal circuit cooperate to generate the internally generated neuronal activities and support the formation and retrieval of memory. Our investigation employs a combination of in vivo electrophysiological, advanced two-photon imaging, optogenetic, and pharmacological approaches, and couples experiments with computational modeling. We encourage applications from candidates who are interested in applying multidisciplinary approaches to examine circuit mechanisms of memory. Education and/or Experience The ideal candidates should have an upcoming or recent Ph.D. or MD/Ph.D. in neuroscience or related fields. Candidates holding a Ph.D. in electrical engineering, biomedical engineering, computer science, or physics and interested in understanding the neuronal mechanisms of learning and memory are also welcome to apply. Previous experience with in vivo electrophysiology and/or two-photon imaging, quantitative data analysis and computer programming is highly preferred. Excellent communication skills and an ability to work well in a team are required. Additional Information Max Planck Florida Institute for Neuroscience is part of the Jupiter Neuroscience Research Campus that also includes the Scripps Research Institute Florida and Florida Atlantic University. It provides a flourishing interdisciplinary research environment for neuroscience. We offer outstanding benefits and salary compensation above the NIH scales. Interested candidates are encouraged to send the following documents to Dr. Yingxue Wang (email address: Yingxue.Wang(a)mpfi.org<mailto:Yingxue.Wang@mpfi.org>): - Curriculum vitae with a list of publications - A statement of research experiences and interests (1-2 pages) - The names and contact information of three references Personal contact can be addressed to the above email address prior to the application.

May 23, 2018

PhD studentships in Neuromorphic computing and Data Science

by Schmuker, Michael

We are offering a several PhD studentships in the Biocomputation group at the University of Hertfordshire. Details here: https://www.herts.ac.uk/__data/assets/pdf_file/0007/209365/Data-Science-and… Our group translates processes from the brain into algorithms for efficient computing. A particular area of interest is Neural Data Science, where we extract information from complex data sets obtained in neuroscience. Our goal is to shed light on how the brain is processing information and to cast this knowledge into efficient algorithms for pattern recognition and signal processing. We implement such algorithms by leveraging so-called neuromorphic hardware, i.e., specialised computer chips that mimic the massively parallel architecture of the brain, which greatly accelerate brain-inspired neural computing. We are looking for highly motivated candidates with a keen interest in squeezing every bit of information out of complex data sets, to understand how the brain copes with the relentless onslaught of sensory information, and to implement those aspects on a new computer architecture. A diverse choice of topics is available, including but not limited to: • Data mining in neuronal imaging using matrix factorisation and machine learning • Brain-inspired pattern recognition using supervised and unsupervised learning • Olfaction-inspired signal processing and odor recognition for electronic gas sensors It is also possible to suggest topics. Candidates should have excellent programming skills and also some experience in data mining. Previous exposure to low-level hardware programming (e.g. microcontrollers, GPUs) and/or computer engineering is a plus. We collaborate with world-leading neuroscience labs in the UK and abroad to investigate how the brain is processing dynamic sensory information. As a member of the Human Brain Project we pioneer the use of neuromorphic hardware for Data Science. This guarantees a stimulating research environment for a project that aims not only at generating theoretical insight but also validating the findings with experimental scientists and pursuing applications in the real world. Successful candidates are eligible for a research studentship award from the University (approximately GBP 14,777 per annum bursary plus the payment of the standard UK student fees). Applicants from outside the UK or EU are eligible, but will have to pay half of the overseas fees out of their bursary. Please contact Principal Investigator Dr. Michael Schmuker prior to application to scope out a project proposal that is tailored to your background, via email: m.schmuker(a)herts.ac.uk. More info and instructions how to apply are available at https://www.herts.ac.uk/study/schools-of- study/computer-science/our-research/the-phd-programme-in-computer-science . The next short-listing process for studentship applications will begin on 25 June 2018. — Dr Michael Schmuker AFHEA Reader in Data Science Biocomputation Group University of Hertfordshire http://biomachinelearning.net

May 23, 2018

PhD position in systems/computational neuroscience, Leicester, UK

by Okun, Michael (Dr.)

A PhD position is available at Centre for Systems Neuroscience, Leicester, UK. The project will focus on organisation and mechanisms of resting state cortical dynamics, particularly in the infraslow (0.01 - 1 Hz) timescales. Additional details are available at https://www.findaphd.com/search/ProjectDetails.aspx?PJID=97389 or by contacting Michael Okun (m.okun(a)le.ac.uk) The deadline for applications is 7th of June.

May 22, 2018

OMG- Emotion Recognition Challenge - Final Results

by Pablo Barros

Dear all, I would like to share with you all the results of our first OMG- Emotion Recognition Challenge. Our challenge is based on the One-Minute-Gradual Emotion Dataset (OMG-Emotion Dataset), which is composed of 567 emotion videos with an average length of 1 minute, collected from a variety of Youtube channels. Each team had a task to describe each video with a continuous space of arousal/valence domain. The challenge had a total of 34 teams registered, from which we got 11 final submissions. Each final submission was composed of a short paper describing the solution and the link to the code repository. The solutions used different modalities (ranging from unimodal audio and vision to multimodal audio, vision, and text), and thus provide us with a very complex evaluation scenario. All the submissions were based on neural network models. We split results into arousal and valence. For arousal, the best results came from the GammaLab team. Their three submissions are our top 3 CCC arousal, followed by the three submissions from the audEERING team, and the two submissions from the HKUST-NISL2018 team. For valence, the GammaLab team stays still in first (with their three submissions), followed by the two submissions of ADSC team and the three submissions from the iBug team. Congratulations to you all! We provide a leaderboard on our website ( https://www2.informatik.uni-hamburg.de/wtm/OMG-EmotionChallenge/ ), which will be permanently stored. This way, everyone can see the final results of the challenge, have a quick access to a formal description of the solutions and to the codes. This will help to disseminate knowledge even further and will improve the reproducibility of your solutions. We also provide a general leaderboard which will be updated constantly with new submissions. If you are interested in having your score in our general leaderboard, just send us an e-mail following the instructions on our website. I would also to invite you all to the presentation of the challenge summary during the WCCI/IJCNN 2018 in Rio de Janeiro, Brasil. Best Regards, Pablo -- Dr. Pablo Barros Postdoctoral Research Associate - Crossmodal Learning Project (CML) Knowledge Technology Department of Informatics University of Hamburg Vogt-Koelln-Str. 30 22527 Hamburg, Germany Phone: +49 40 42883 2535 Fax: +49 40 42883 2515 barros at informatik.uni-hamburg.de https://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.html https://www.inf.uni-hamburg.de/en/inst/ab/wtm/

May 22, 2018

Call for Papers: Special Session on Computational Methods for Neuroimaging Analysis, 6-8 September, Portugal

by Tiago Azevedo

Dear all, Below find the call for papers for the special session "Computational Methods for Neuroimaging Analysis". It will be be held during the 15th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistics, at Caparica, Portugal, from 6 to 8 September. **Important Dates** Paper submission deadline: 10 June 2018 Acceptance notification: 9 July 2018 Author registration due: 20 July 2018 Camera ready due: 29 July 2018 Conference: 6-8 September 2018 **Link** https://eventos.fct.unl.pt/cibb2018/pages/special-sessions **Aim and scope** There is an increasing need for the application of machine learning (ML) techniques which can perform image processing operations such as segmentation, coregistration, classification and dimensionality reduction in the field of neuroimaging. Although the manual approach often remains the golden standard in some tasks (like segmentation), ML can be utilised to automate and facilitate the work of researchers and clinicians. Frequently used techniques include support vector machines (SVMs) for classification problems, graph-based methods for brain network analysis and recently artificial neural networks (ANNs). Deep ANNs, i.e. deep learning, have proved to be very successful in computer vision tasks owing to the ability to automatically extract hierarchical descriptive features from input images. It has also been used in the medical and neuroimaging domains for automatic disease diagnosis, tissue segmentation and even synthetic image generation. The issue, however, is the relative sample paucity in typical neuroimaging datasets which leads to poor generalisation considering the high number of parameters employed in typical deep neural networks. Consequently, parameter- efficient design paradigms ought to be created. Another approach to investigate degeneration is the study and mapping of the neural connections in the brain known as the connectome. The connectome can be seen as a matrix representing all possible pairwise connections between different neural areas. Researchers study both the structural and functional connectivity in order to understand important brain patterns, such as how the connectome impacts the dynamics of disease spreading, ageing and learning. Topics of interest includes but are not limited to: • Machine learning techniques for segmentation, coregistration, classification or dimensionality reduction of neuroimages   • Deep learning for neuroimaging analysis   • Brain network analysis   • Applications of graph theory to MRI and fMRI data   • Applications of machine learning methodologies for neurodegenerative disease studies   • Computational modelling and analysis of neuroimaging   • Methods of analysis for structural or functional connectivity   • Development of new neuroimaging tools **Session chairs** Tiago Azevedo, University of Cambridge, UK Giovanna Maria Dimitri, University of Cambridge, UK Pietro Liò, University of Cambridge, UK Angela Serra, University of Salerno, Italy Simeon Spasov, University of Cambridge, UK

May 22, 2018

Two postdoc positions at Champalimaud Centre for the Unknown, Lisbon

by Christian Machens

POSTDOC POSITIONS IN COMPUTATIONAL / SYSTEMS NEUROSCIENCE Two postdoctoral positions - one in theory and one in experiment - are available in a joint project between the labs of Alfonso Renart and Christian Machens at the Champalimaud Centre for the Unknown in Lisbon, Portugal. Location: The Champalimaud Centre for the Unknown is situated on the waterfront in central Lisbon. English is the official language of the Centre. The center is composed of about 20 main research groups who study diverse topics in neuroscience using advanced, cutting edge techniques. Project: The proposed project will investigate to what extent neural circuits actively compensate random perturbations. The project involves the recordings and partial silencing of neural populations, population-level analysis using dimensionality reduction and other techniques, and the modeling of the results with spiking networks. Relevant background literature: Renart, de la Rocha, et al (2010), Science 327:587-90; Barrett et al (2016), eLife 5:12454; Deneve and Machens (2016), Nat Neurosci 19:375-82. Profile (theory): The ideal candidate should have a PhD with a strong, quantitative background (ideally in fields such as machine learning and/or computational neuroscience). The position is funded for two years with possibility of extension. Profile (experiment): The ideal candidate should have experience in electrophysiology (e.g. recordings from behaving head-fixed mice) and data analysis (e.g. dimensionality reduction methods etc). Applications should include a CV, a statement of research interests (max 1 page), and two letters of recommendation. Feel free to ask any informal questions about the positions if you are interested. Electronic submissions in pdf-format are preferred and should be send to both of the following email addresses: christian.machens(a)neuro.fchampalimaud.org alfonso.renart(a)neuro.fchampalimaud.org

May 21, 2018

project in neuromath & circuit-based neuron classification

by NeuroMorpho Administrator

Dear colleagues, Please find below an advertisement for a postdoc position in my lab. Thanks in advance for spreading the opportunity! Giorgio Ascoli Postdoctoral Research Fellow - Department of Bioengineering The George Mason University Department of Bioengineering, within the Volgenau School of Engineering, is seeking a postdoctoral research fellow to contribute to ongoing cutting-edge neuroinformatics research funded by the National Institutes of Health (NIH) under the BRAIN initiative. George Mason University has a strong institutional commitment to the achievement of excellence and diversity among its faculty and staff, and strongly encourages candidates to apply who will enrich Mason’s academic and culturally inclusive environment. Responsibilities: The initial focus is on quantitative analysis, modeling, and simulations of neuronal classification, network connectivity, and circuit dynamics. Post-doc will join the Center for Neural Informatics, Structures, and Plasticity (CN3) in George Mason University’s Volgenau School of Engineering in northern Virginia (20 miles west of Washington DC). CN3 is an interdisciplinary, energetic, and creative research group in the Krasnow Institute for Advanced Study of the main Fairfax campus. The position entails tight collaborations with faculty and trainees in the Bioengineering, Neuroscience, and Mathematics programs. The successful applicant will work directly with the CN3 director and will have unlimited access to dedicated supercomputer and server facilities, flexible working schedule, salary based on the NIH postdoctoral scale, and state employee benefits. Required Qualifications: The successful candidate is expected to have a Ph.D. in a discipline related to biomedical engineering, applied mathematics, computer science, neuroscience, physics, data science, or related fields. Preferred Qualifications: The incumbent should have research experience with programming and scripting languages (C++, Java, R, MatLab). Working knowledge of network neuroscience, clustering techniques, statistics, graph theory, and/or machine learning are desirable. About Mason: George Mason University, a tier-1 research institution, is considered one of the top “Up and Coming” educational institutions in America by the U.S. News and World Report. It is conveniently located in the Washington D.C., metropolitan area within easy access to several national laboratories and research centers (including the National Institutes of Health and the Janelia Research Campus of the Howard Hughes Medical Institute), and provides a highly stimulating environment for interdisciplinary science. Biomedical research is a major area of strategic focus for Mason, and the Center for Neural Informatics has been at the forefront of computational neuroscience research since its establishment in 2006. For full consideration, applicants must complete and submit the online application at https://jobs.gmu.edu/postings/42954 [http://jobs.gmu.edu/hr/assets/social_share.jpg]<https://jobs.gmu.edu/postings/42954> Postdoctoral Research Fellow<https://jobs.gmu.edu/postings/42954> jobs.gmu.edu Postdoctoral Research Fellow, Department of Bioengineering The George Mason University Department of Bioengineering, within the Volgenau School of Engineering, is seeking a postdoctoral research fellow to contribute to ongoing cutting-edge neuroinformatics research funded by the National Institutes of Health (NIH) under the BRAIN initiative. George Mason University has a strong institutional commitment to the achievement of excellence and diversity among its faculty and staff, and strongly encourages candidates to apply who will enrich Mason’s academic and culturally inclusive environment. Responsibilities: The initial focus is on quantitative analysis, modeling, and simulations of neuronal classification, network connectivity, and circuit dynamics. Post-doc will join the Center for Neural Informatics, Structures, and Plasticity (CN3) in George Mason University’s Volgenau School of Engineering in northern Virginia (20 miles west of Washington DC). CN3 is an interdisciplinary, energetic, and creative resea Finalist will be required to submit three letters of recommendation upon request. Review of applications will begin on June 1, 2018, and continue until the position is filled. This position will be renewed annually subject to satisfactory performance and availability of funds. Non-resident aliens are welcome to apply. Questions regarding the position should be directed to ascoli(a)gmu.edu<mailto:ascoli@gmu.edu> George Mason University is an equal opportunity/affirmative action employer, committed to promoting inclusion and equity in its community. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, disability, or protected veteran status. ---------------- Giorgio Ascoli, PhD University Professor Bioengineering Department, Volgenau School of Engineering Neuroscience Program, Krasnow Institute for Advanced Study Director, Center for Neural Informatics, Structures, & Plasticity MS2A1 - George Mason University, Fairfax, VA 22030-4444 Ph. +1(703)993-4383/+1(703)673-8894 Author of “Trees of the Brain, Roots of the Mind” (MIT Press, 2015) Founding Editor-in-Chief, Neuroinformatics

May 21, 2018

Project in neurotechnology/vision in mice in the Roelfsema lab - Amsterdam

by Pieter Roelfsema

Dear colleagues, Please find below an advertisement for a PhD or postdoc position in my lab. Thanks for spreading the advertisement! Pieter Roelfsema A postdoc or PhD-student position is available in the Vision & Cognition group at the Netherlands Institute for Neuroscience in Amsterdam. The aim is to understand visual perception and plasticity elicited by electrical stimulation of the visual cortex in mice, with the ultimate aim to create a visual cortical prosthesis to restore a rudimentary form of vision for the blind. Project description: Visual perception elicited by electrical stimulation of mouse visual cortex Electrical stimulation of the visual cortex elicits a “phosphene”, an artificial percept of light. By stimulating multiple electrodes at the same time, it might prove possible evoke pattern vision. The aims of this project are to (1) develop new methods for electrical stimulation in mice; (2) to study the patterns of activated neurons using two-photon imaging and (3) to test visual perception of electrical percepts and its plasticity in mice. Qualifications We will consider highly motivated, self-driven candidates with a degree in neuroscience, (neuro)psychology, biomedical sciences, natural sciences, material science, mathematics, physics, etc. A high level of written and spoken English and good programming skills are required. The ideal candidate will have experience with neurophysiological techniques, the analysis of neuronal activity in alert animals, and a background in neuroscience. Interest in the translation of fundamental research into clinical applications and collaboration with high-tech companies is a plus. All qualified applicants will receive consideration for employment without regard to race, religion, sexual orientation, nationality, disability, etc. Appointment The position involves a fulltime temporary appointment for 3 years (postdoc) or 4 years (PhD student). Starting date: Mid-2018. Salary PhD position: The gross monthly salary coming with a full-time appointment will amount to a minimum of € 2.191 in the first year to € 2.801 in the fourth year (P scale of the Collective Labour Agreement for Dutch Universities). Postdoctoral position: This will be commensurate with experience and institutional guidelines based on the Collective Labour Agreement for Dutch Universities; CAO NU). In addition, an 8% holiday allowance and 8.3% year-end bonus will be provided. We offer an extensive package of fringe benefits. To apply, please send an application letter, CV, and two letters of recommendation to: Tini Eikelboom The Netherlands Institute for Neuroscience Meibergdreef 47, 1105 BA Amsterdam, The Netherlands Telephone: +31-20-5664587 E-mail: t.eikelboom(a)nin.knaw.nl<mailto:t.eikelboom@nin.knaw.nl> Evaluation of candidates will begin immediately, and continue until the position is filled. We aim to fill the position mid-July 2018.

May 21, 2018

[job] PhD position opening in Machine Learning for Adaptive Language interaction with an intelligent dialog companion.

by Pierre-Yves Oudeyer

*Title: Machine Learning for Adaptive Language interaction with an intelligent dialog companion *Keywords: Deep reinforcement learning, interactive machine learning, natural language processing, neural networks, intelligent dialog companion *Context: The thesis takes place in the context of a collaboration between the Robot Cognition Laboratory (INSERM/CNRS), the innovation services department of Intrinsic Cloud Temple, and the Flowers laboratory (Inria). *Background: Based on RCL experience in human-robot cooperation and learning, we have developed an intelligent agent that accompanies humans in their experience using web-based tools, learns from explicit demonstration, and allows the user to re-use and recompose learned plans to form more complex structured plans. *Project: For the moment, the system learns from demonstration. The project will extend and study algorithms for interactive machine learning (using Deep RL) to include language instructions as one of the ways that the system can learn, that is, by using the invariant structure of the human verbal description to organize procedural representations. This will advance the state of the art in the integration of language into reinforcement learning systems. * Location: Lyon and Nanterre, France (Inserm and Cloud Temple) * Response modalities: Send (1) a letter of motivation stating your interest in the project, (2) a CV, and (3) two letters of recommendation to the three addresses for Jean-Michel Dussoux, Peter Ford Dominey, and Pierre-Yves Oudeyer listed in the call, with the subject [Intelligent Assistant PhD]. jmd(a)intrinsec.com; pierre-yves.oudeyer(a)inria.fr; peter.dominey(a)inserm.fr More details: https://www.dropbox.com/s/g5ksylrrlgatkf2/RCL-CT-THESE-interaction-manager-…

May 18, 2018