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

3 Independent Academic Fellowship positions Computational Neuroscience
by Mark van Rossum 31 Jul '18

31 Jul '18

Academic Fellowship positions The University of Nottingham is a research intensive university ranked in the top 10 in the UK and in the top 30 of Europe. It has a strong tradition in Cognition, Perception, Mathematical Biology, and structural and functional Imaging. To support further development across these areas, and stimulate new research opportunities, the University has recently made a major investment in Computational Neuroscience. As part of this investment we are inviting applications for three independent fellowships (3 years). The positions are ideal for researchers with a strong vision that are planning to develop their own research group in a supportive, interdisciplinary environment with outstanding research facilities. We are interested in candidates working across a broad spectrum of research topics areas in Computational Neuroscience, including functional neuroimaging, neural networks, and models of cognition. Research methodologies could include numerical simulation, machine learning, theoretical neuroscience, and innovative data analysis. The Fellows will be based in the School of Psychology and/or Mathematical Sciences. For the online application form see https://www.nottingham.ac.uk/jobs/currentvacancies/ref/SCI219418 Informal inquiries: Prof Mark van Rossum, mark.vanrossum(a)nottingham.ac.uk, or Prof Mark Humphries, lpzmdh(a)exmail.nottingham.ac.uk. -- Mark van Rossum, Professor, Schools of Psychology and Maths, U Nottingham Psych Bldg Rm LG.19, 44-115-74 86851, 44-7722049644 This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please contact the sender and delete the email and attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. Email communications with the University of Nottingham may be monitored where permitted by law.

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CFP: Workshop on Crossmodal Learning for Intelligent Robotics in conjunction with IEEE/RSJ IROS 2018
by Pablo Barros 30 Jul '18

30 Jul '18

**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 University, 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/

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Four-year PhD in Computational Psychiatry at University College London
by Hrvoje Stojic 30 Jul '18

30 Jul '18

Four-year PhD in Computational Psychiatry at University College London The International Max Planck Research School on Computational Methods in Psychiatry and Ageing Research (https://www.mps-ucl-centre.mpg.de/en) seeks applicants for PhD fellowships to be based at University College London (UCL). The PhD programme is strongly interdisciplinary and invites applications from potential students with a broad range of backgrounds including, but not limited to, neuroscience, mathematics, statistics, machine learning, computer science, physics, psychology, and medicine. This is an international doctoral programme of the Max Planck UCL Centre for Computational Psychiatry and Ageing Research, which has sites in London and Berlin. The programme offers unique training in concepts and methods from computer science and statistics in relation to substantive research questions in cognitive neuroscience, psychiatry, and lifespan psychology. Training involves seminars, methods workshops, participation in summer schools, and collaboratively supervised research. Students will take one module per semester for the first two years of the programme on topics that range from psychiatry and decision science to advanced computational and statistical methods. The main focus of the London site is to address cognitive and theoretical neuroscience questions relevant to understanding psychiatric disorders. Methods include neuroimaging and pharmacology, computational modelling of behaviour (learning, decision-making, emotion), and large-scale smartphone- and internet-based data collection. Students will have a primary supervisor within the Centre and possible supervisors include Tobias Hauser (http://v1.tobiashauser.ch/) and Quentin Huys (https://quentinhuys.com/) Collaboration is encouraged within the Centre and with other UCL departments including the Wellcome Centre for Human Neuroimaging (https://www.fil.ion.ucl.ac.uk/) and Gatsby Computational Neuroscience Unit (http://www.gatsby.ucl.ac.uk/) We offer a generous four-year studentship stipend of £23,263 (tax free) per year, PhD registration fees at the current Home/EU rate, research expenses, and funds for travel to conferences or courses. (If you are an international student please note that this studentship only covers UK/EU fees and you will need to provide the difference between UK/EU and overseas fees.) Students will participate in international summer schools, seminars and workshops linked to the Berlin site, and have the opportunity to conduct a research project of up to 6 months in Berlin. Requirements: This is a highly competitive programme. Successful applicants should have, or expect to get, at least an upper 2nd class degree (or the foreign equivalent), and should have some familiarity with computational and statistical methods. Students wishing to undertake a PhD with Quentin Huys are expected to take and pass courses (http://www.gatsby.ucl.ac.uk/teaching/courses/index.html) at the Gatsby Computational Unit. The next intake of students will be October 2018 (with the possibility for a later start date). UCL is committed to employing more people with disabilities and especially encourages them to apply. UCL also seeks to increase the number of women in those areas where they are underrepresented and therefore explicitly encourages women to apply. Deadline: 26 August 2018. Shortlisted candidates will be interviewed in early September 2018 via Skype. HOW TO APPLY. Please send: 1) a CV, 2) a statement of why you want to do the PhD (no more than 1 page), 3) a copy of your strongest piece of academic work (e.g., thesis, publication). Please also arrange for two reference letters to be sent to us by referees. Your surname should be the first word in the subject line of these emails. The statement should indicate which of the named supervisors you would be most interested in having as a primary supervisor (multiple faculty can be listed as potential supervisors). Please ensure that your surname is the first word in the subject line of the email and that all documents are clearly labelled with your surname and the type of document. All documents and references should be sent to MaxPlanckPhD(a)ucl.ac.uk by 26 August 2018 at midnight. Questions about the programme can be directed to MaxPlanckPhD(a)ucl.ac.uk.

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PhD Studentship, University College London, Centre for Medical Image Computing (CMIC)
by Andre Altmann 30 Jul '18

30 Jul '18

We are looking to fill a 4-year PhD studentship in the field of imaging genetics to work on drug resistant Epilepsy: Epilepsy is a group of neurological conditions that share the common characteristic of epileptic seizures. There are many types of epilepsy and many types of seizure. The diagnosis of epilepsy typically follows the occurrence of two or more seizures. While anyone can develop epilepsy at any point in life, it is most commonly diagnosed in children and people over 65 years of age. Currently, about 60 million people are suffering from epilepsy worldwide and over 500,000 in the UK alone. Anti-epileptic drugs (AED) are intended to reduce the frequency of seizures or even completely eliminate them. If AED treatment works, it allows people living with epilepsy to lead normal lives. However, in about one third of people none of the available drugs or combinations of drugs stop the seizures. These cases are considered treatment-resistant epilepsies and the underlying biology is still poorly understood. In this project, the successful candidate will help to advance knowledge about drug-resistant epilepsy. Using a large database of neuroimaging data from people with epilepsy, the first aim is to establish the imaging signature of drug-resistant epilepsy compared to drug-responsive epilepsy. That is, which brain regions show different cortical thickness or structural and functional connectivity changes in resistant vs responsive epilepsy? The second phase of the project involves an imaging-genetics approach to elucidate the genetic origin of drug-resistant epilepsy, which may help to identify drug targets for currently drug-resistant epilepsy. More information on requirements and the medical imaging CDT can be found here: http://medicalimaging-cdt.ucl.ac.uk/news/machine-learning-based-investigati… Kind regards, Andre

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ANDA 2019 - G-Node Advanced Neural Data Analysis Course, April 1-18, 2019, Jülich, Germany
by Thomas Wachtler 30 Jul '18

30 Jul '18

ANDA 2019 - G-NODE ADVANCED NEURAL DATA ANALYSIS COURSE April 1 - 18, 2019 Haus Overbach, Juelich-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, Bar-Ilan Univ, Israel · Izhar Bar Gad, Bar-Ilan Univ, Israel · Michael Denker, Juelich Research Center and RWTH Aachen Univ, Germany · Sonja Grün, Juelich Research Center and RWTH Aachen Univ, Germany · Björn Kampa, RWTH Aachen, Germany · Tatiana Korotkova, MPI and University of Cologne, Germany · Christian Machens, Champalimaud Centre for the Unknown, Portugal · Martin Nawrot, University of Cologne, Germany · Yifat Prut, Hebrew Univ Jerusalem, Israel · Alexa Riehle, CNRS, Marseille, France · Alexander Thiele, University of Newcastle, UK · Thomas Wachtler, G-Node, 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 · Spike-LFP relationship · Population coding · State space analysis · Machine learning · Data mining · Data management, reproducibility, data sharing · Elephant toolbox 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 SEPTEMBER 30, 2018. Early application is encouraged. For further information see http://www.g-node.org/anda2019 ORGANIZERS · Sonja Grün, Juelich Research Center and RWTH Aachen Univ, Germany · Martin Nawrot, University of Cologne, Germany · Yifat Prut, Hebrew University Jerusalem, Israel · Thomas Wachtler, G-Node, Ludwig-Maximilians-Universität München, Germany

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Call for participants – workshop on Computational Neuroscience and Robotics: Astrocyte-Neuron interactions, Spiking Neural Networks and Autonomous robotics. University of York, 3-5 Sep 2018.
by David Halliday 30 Jul '18

30 Jul '18

This 2.5 day workshop in the historic city of York is accepting applications for participation. We have invited speakers from USA, EU and UK. Due to sponsorship from EPSRC we can offer free registration for all participants. Free accommodation is available for PhD, early career researchers and workshop presenters. Travel bursaries for registered PhD students are also available. For an up to date list of speakers and details of how to register see the website: https://www.york.ac.uk/spanner-workshop We are still accepting abstracts for posters or contributed talks. Further details: https://www.york.ac.uk/spanner-workshop

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Cognitive Computing - Merging Concepts with Hardware - Call for Abstracts: Deadline Approaching: July 31
by Prof. Dr. Gordon Pipa 30 Jul '18

30 Jul '18

- - - Call for Abstracts: Deadline Approaching: July 31 - - - 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 a slightly unorthodox scientific community event that could be realized with the generous support from the Volkswagen Foundation, Germany’s largest private organization for the advancement of scientific research. The aim of this event 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 rather few, rather long oral presentations, • long break and poster session times for person-to-person talking, • keynote and plenary speakers of 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 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, encouraging survey / introductory / didactic contributions (besides the standard discipline-specific result reports which are also possible). 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 organizers: • Daniel Brunner (photonics, neuromorphic architectures; University of Besançon) • 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)

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PhD Studentship, University of Osnabrueck- Research Training School on Computaional Cognition
by Prof. Dr. Gordon Pipa 30 Jul '18

30 Jul '18

We are looking for 9 PhD candidate for Research Training School funded by the DFG (German science foundation) on "Computational Cognition". The positions are to be filled by October 1, 2018 for a period of 3 years. More information: http://computational-cognition.eu/ https://www.uni-osnabrueck.de/universitaet/stellenangebote/stellenangebote_d etail/109_ikw_phd_candidates.html The RTG Computational Cognition aims at reintegrating Cognitive Science and Artificial Intelligence. PhD students of the RTG will be educated in both subjects in order to combine the findings of these fields and thus to get a better understanding of human and machine intelligence. Research fields involved in the RTG are Neuroinformatics, Neurobiopsychology, Bio-Inspired Computer Vision, Knowledge-Based Systems, Cognitive Natural Language Processing & Communication, Cognitive Modeling, Artificial Intelligence, Psycho/Neurolinguistics, Computational Linguistics and Cognitive Computing. The RTG will focus on the integration of two research fields and has a focus on machine learning, deep learning and dynamical systems, computer vision combined with experimental methods including EEG and Eye tracking. Detailed information on the core areas of the offered PhD projects can be obtained from the spokesmen of the RTG, Prof. Dr. Gordon Pipa (gpipa(a)uni-osnabrueck.de) and Prof. Dr. Peter König (pkoenig(a)uni-osnabrueck.de) The RTG will be incorporated into the Cognitive Science PhD program founded in 2002. PhD students of the RTG will take advantage of an interdisciplinary environment, which nevertheless focuses on a common research topic and offers a broad range of methodological synergies between the projects. Required Qualifications: Applicants are expected to have an academic degree (Master/Diploma), experience in at least one of the domains listed above, proven experience in interdisciplinary work as well as a good command of the English language. Osnabrück University has been certified as a family-friendly university committed to helping working/studying parents and carers balance their family and work life. The university aspires to ensure equal opportunities for men and women and strives to work towards a gender balance in schools or departments where new appointments are made. If equally qualified candidates apply, preference will be given to those with special needs. Applications with the usual documentation should be submitted by e-mail in a single PDF file to the director of the Institute of Cognitive Science, Prof. Dr. Kai-Uwe Kühnberger (kkuehnbe(a)uni-osnabrueck.de) with a cc to office(a)ikw.uni-osnabrueck.de no later than August 23, 2018.We will consider applicants who have: Best Gordon ---------------------------------------------------------------------------- ----------- Professor and Chair of the Neuroinformatics Department Dr. rer. nat. Gordon Pipa Institute of Cognitive Science, Room 50/218 University of Osnabrueck Wachsbleiche 27, 49090 Osnabrück, Germany tel. +49 (0) 541-969-2277 fax (private). +49 (0) 5405- 500 80 98 home office. +49 (0) 5405- 500 90 95 e-mail: gpipa(a)uos.de webpage: http://www.ni.uos.de research gate: https://www.researchgate.net/profile/Gordon_Pipa/?ev=prf_act linkedin: https://de.linkedin.com/in/gordon-pipa-47771539 Personal Assistent and Secretary of the Neuroinformatic lab: Anna Jungeilges Tel. +49 (0)541 969-2390 Fax +49 (0)541 969-2246 Email: anna.jungeilges(a)uni-osnabrueck.de visit us on http://www.facebook.com/CognitiveScienceOsnabruck https://twitter.com/#!/CogSciUOS

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PhD position in Neuroscience available immediately (Italy / USA)
by Marco Tamietto 27 Jul '18

27 Jul '18

A new European Research Council (ERC) Consolidator grant starts at the University of Torino, Italy, for 5 years (~ 2 million euros). The grant “LIGHTUP – Turning the cortically blind brain to see” is awarded to prof. Marco Tamietto (www.marcotamietto.com) The project investigates the neural correlates of visual awareness and of non-conscious vision in patients with *blindsight* and in non-human primates (macaques) with V1 destruction. To this aim, a broad range of methods will be used, including 3T and 7T (f)MRI, neurophysiological recordings and brain stimulation (TMS). The project is embedded in an outstanding international and interdisciplinary context, including the University of Oxford (UK), Tilburg University (NL) and NIH (USA), with granted access to their excellent facilities. We offer a full-time PhD Student post for 4 years. Applications of highly motivated candidates with interests in systems neuroscience, vision sciences and neuroimaging are welcomed. The successful applicant will be appointed by the University of Torino, but he/she will be expected to spend a significant amount of time at the NIH in Bethesda (USA). In fact, the PhD student will be co-supervised by prof. M. Tamietto and prof. D. Leopold, and the position is specifically focused on behavioural and fMRI studies in non-human primates. For further information please visit http://www.marcotamietto.com or contact Prof. M. Tamietto (marco.tamietto(a)unito.it) or Prof. D. Leopold ( leopoldd(a)mail.nih.gov)

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[Deadline Approaching] CfP: CI Methods in Processing and Analysis of Neuronal Big Data at BI 2018, Texas, Dec. 7-9.
by Mufti Mahmud 24 Jul '18

24 Jul '18

*[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*. With kindest regards, *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/> | Nottingham Trent University <https://www.ntu.ac.uk/> Office: ERD200 | Erasmus Darwin Building | Clifton Campus | NG11 8NS – Nottingham | United Kingdom 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> http://orcid.org/0000-0002-2037-8348 https://scholar.google.com/citations?user=L8em2YoAAAAJ&hl=en https://sites.google.com/site/muftimahmud/ https://www.ntu.ac.uk/staff-profiles/science-technology/mufti-mahmud 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/> Student consultation hours: Drop-in sessions on Thursdays between 11.00 am and 12.30 pm. Appointments for a different time can also be arranged through email.

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