- Comp-neuro - lists.cnsorg.org

Master 2 internship
by Bruno Cessac Dec. 4, 2017

Dec. 4, 2017

Decoding cortical activity evoked by artificial retinal implants The NeOpTo team (Institut des Neurosciences de la Timone, Marseille, France) and the Biovision Team (Inria, Sophia Antipolis, France) propose a joint Master 2 internship, entitled "Decoding cortical activity evoked by artificial retinal implants" from March 2018 to August 2018. The details of the internship can be found here https://team.inria.fr/biovision/files/2017/11/StageINT.pdf To apply, please send us a CV, a letter of application outlining your academic interests, prior research experience and reasons for wishing to undertake the project, a transcript(s) giving full details of subjects studied and grades/marks obtained. Dr Bruno Cessac, Research Director at INRIA, Head of the BioVision team -INRIA 2004 Route des Lucioles-BP93 FR-06902 Sophia Antipolis Cedex

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PhD position at the University of Exeter
by Tsaneva-Atanasova, Krasimira Dec. 2, 2017

Dec. 2, 2017

Mathematical Modelling of Event-Related Potentials in Semantic Representation and Memory - Mathematics - EPSRC DTP funded PhD Studentship Ref: 2891 About the award This project is one of a number funded by the Engineering and Physical Sciences Research Council (EPSRC<https://www.epsrc.ac.uk/skills/students/>) Doctoral Training Partnership to commence in September 2018. This project is in direct competition with others for funding; the projects which receive the best applicants will be awarded the funding. The studentships will provide funding for a stipend which is currently £14,553 per annum for 2017-2018. It will provide research costs and UK/EU tuition fees at Research Council UK rates for 42 months (3.5 years) for full-time students, pro rata for part-time students. Please note that of the total number of projects within the competition, up to 15 studentships will be filled. Supervisors Professor Krasimira Tsaneva-Atanasova<http://emps.exeter.ac.uk/mathematics/staff/kt298> Location Streatham Campus, Exeter Project Description N400 is an event-related potential (ERP) component that tap into semantic representation and memory and is an important markers of cognitive function, hence valuable clinical tools for quantifying integrity of the semantic system in populations with semantic comprehension deficit including stroke survivors, patients with traumatic brain injuries (TBI) or focal seizure disorders. Yet the neural origin of this component is largely unknown, which limits robustness of its measurement and clinical applicability. This project investigates the origin of N400, i.e., whether it emerges as a result of phase alignment in the ongoing oscillatory activity or as a result of an evoked neural activity. In the first stage of the project, the student will explore the neural dynamics of N400 by applying model-based data analysis and feature extraction to already collected in the second supervisor’s lab in Bristol human scalp electroencephalogram (EEG) data from healthy younger and older people responding to meaningful stimuli such as words, sentences or pictures of objects. This analysis will inform data-driven generative model(s) parameterization. In the second stage, the network models developed in stage 1 will be perturbed to identify the parameters (features) for conditions such as stroke and traumatic brain injuries (TBI). The final stage of the project will aim to link the event-related response with the underlying induced and evoked activity and to further investigate this activity using learning in the model space approach. There is a potential to reveal therapeutic targets for stroke and TBI. Entry Requirements You should have or expect to achieve at least a 2:1 Honours degree, or equivalent, in applied mathematics, computer science, physics or engineering. Experience in biomedical engineering or experimental psychology is desirable. The majority of the studentships are available for applicants who are ordinarily resident in the UK and are classed as UK/EU for tuition fee purposes. If you have not resided in the UK for at least 3 years prior to the start of the studentship, you are not eligible for a maintenance allowance so you would need an alternative source of funding for living costs. To be eligible for fees-only funding you must be ordinarily resident in a member state of the EU. For information on EPSRC residency criteria click here<https://www.epsrc.ac.uk/skills/students/help/eligibility/>. Applicants who are classed as International for tuition fee purposes are NOT eligible for funding. International students interested in studying at the University of Exeter should search our funding database<http://www.exeter.ac.uk/postgraduate/money/fundingsearch/> for alternative options. Summary Application deadline: 10th January 2018 Value: 3.5 year studentship: UK/EU tuition fees and an annual maintenance allowance at current Research Council rate. Current rate of £14,553 per year. Duration of award: per year Contact: Doctoral College pgrenquiries(a)exeter.ac.uk<mailto:pgrenquiries@exeter.ac.uk> How to apply Apply now You will be required to upload the following documents: • CV • Letter of application outlining your academic interests, prior research experience and reasons for wishing to undertake the project. • Transcript(s) giving full details of subjects studied and grades/marks obtained. This should be an interim transcript if you are still studying. • If you are not a national of a majority English-speaking country you will need to submit evidence of your current proficiency in English. For further details of the University’s English language requirements please see http://www.exeter.ac.uk/postgraduate/apply/english/. The closing date for applications is midnight (GMT) on Wednesday 10 January 2018. Interviews will be held at the University of Exeter in late February 2018. If you have any general enquiries about the application process please email: pgrenquiries(a)exeter.ac.uk<mailto:pgrenquiries@exeter.ac.uk>. Project-specific queries should be directed to the supervisor. ________________________________ Krasimira Tsaneva-Atanasova Professor of Mathematics for Healthcare Department of Mathematics & Living Systems Institute, T02.17 University of Exeter, Stocker Road, Exeter, EX4 4QD, UK email: k.tsaneva-atanasova(a)exeter.ac.uk<mailto:k.tsaneva-atanasova@exeter.ac.uk> tel: +44 (0) 1392 723615 web: http://emps.exeter.ac.uk/mathematics/staff/kt298

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PhD position at the University of Exeter
by Tsaneva-Atanasova, Krasimira Dec. 2, 2017

Dec. 2, 2017

Developing Gaze Training for Skilled Upper-Limb Prosthetic Use - Mathematics - EPSRC DTP funded PhD Studentship Ref: 2892 About the award This project is one of a number funded by the Engineering and Physical Sciences Research Council (EPSRC<https://www.epsrc.ac.uk/skills/students/>) Doctoral Training Partnership to commence in September 2018. This project is in direct competition with others for funding; the projects which receive the best applicants will be awarded the funding. The studentships will provide funding for a stipend which is currently £14,553 per annum for 2017-2018. It will provide research costs and UK/EU tuition fees at Research Council UK rates for 42 months (3.5 years) for full-time students, pro rata for part-time students. Please note that of the total number of projects within the competition, up to 15 studentships will be filled. Supervisors Professor Krasimira Tsaneva-Atanasova<http://emps.exeter.ac.uk/mathematics/staff/kt298> Dr Gavin Buckingham<http://sshs.exeter.ac.uk/staff/index.php?web_id=Gavin_Buckingham> Dr Sam Vine<http://sshs.exeter.ac.uk/staff/index.php?web_id=Samuel_Vine> Professor Mark Wilson<http://sshs.exeter.ac.uk/staff/index.php?web_id=Mark_Wilson> Location Streatham Campus, Exeter Project Description Learning to use a prosthetic limb is inherently difficult and requires a huge amount of concentration. Like learning how to wield a new tool for the first time, amputees need to acquire the confidence and dexterity required for skilled action. In order to produce accurate goal-directed movements the motor system requires accurate and timely visual information making the timing and location of the person’s gaze, with relation to the movement of their limbs, critical for skilled behaviour. There is, however, no structured training protocol for use with prosthetic hands. We aim to develop a novel gaze training regime to facilitate the use of a prosthetic hand to skilfully interact with objects. In the first phase of the project, the student will undertake an observational study to determine what factors lead some individuals to become skilled with a prosthesis faster than others. We will test large numbers of intact (i.e., without amputation) participants learning to use a state-of-the-art myoelectric prosthetic arm simulator, which is controlled by muscle feedback but ergonomically designed to fit over the wrist of an intact hand. Participants will move objects of different of sizes and weights from one location to another with a range of precision requirements and in the presence of a range of obstacles. Over multiple sessions we will measure hand and object kinematics, fingertip forces, and eye path with a head-mounted eye tracker. We will then develop a data-driven mathematical model of the eye tracking and biomechanical performance data. Statistical analysis of the patterns of eye movement will provide new insights into the ‘signature’ of good performance using the prosthetic arm. The second phase will use the data from Project 1 to develop a training protocol that will adopt the ‘expert signatures’ from Phase 1 as a prototype for a trainee to follow. We will focus predominantly on the signature of expertise derived from the gaze behaviour measures and implement a gaze training protocol. We will then test the efficacy of this novel training regime with new set of intact participants using the prosthetic simulator, tracking their performance in comparison to individuals who will receive a sham training protocol. In the final phase of the project, the gaze training protocol will be used in a sample of upper-limb-amputees as they learn how to use their new prosthesis. As this stage of the project will not be limited to myoelectric prosthetic users, this will also allow us to test the generalizability of our training protocol. Entry Requirements You should have or expect to achieve at least a 2:1 Honours degree, or equivalent, in applied mathematics, computer science, physics or engineering. Experience in biomedical engineering or robotics is desirable. The majority of the studentships are available for applicants who are ordinarily resident in the UK and are classed as UK/EU for tuition fee purposes. If you have not resided in the UK for at least 3 years prior to the start of the studentship, you are not eligible for a maintenance allowance so you would need an alternative source of funding for living costs. To be eligible for fees-only funding you must be ordinarily resident in a member state of the EU. For information on EPSRC residency criteria click here<https://www.epsrc.ac.uk/skills/students/help/eligibility/>. Applicants who are classed as International for tuition fee purposes are NOT eligible for funding. International students interested in studying at the University of Exeter should search our funding database<http://www.exeter.ac.uk/postgraduate/money/fundingsearch/> for alternative options. Summary Application deadline: 10th January 2018 Value: 3.5 year studentship: UK/EU tuition fees and an annual maintenance allowance at current Research Council rate. Current rate of £14,553 per year. Duration of award: per year Contact: Doctoral College pgrenquiries(a)exeter.ac.uk<mailto:pgrenquiries@exeter.ac.uk> How to apply Apply now You will be required to upload the following documents: • CV • Letter of application outlining your academic interests, prior research experience and reasons for wishing to undertake the project. • Transcript(s) giving full details of subjects studied and grades/marks obtained. This should be an interim transcript if you are still studying. • If you are not a national of a majority English-speaking country you will need to submit evidence of your current proficiency in English. For further details of the University’s English language requirements please see http://www.exeter.ac.uk/postgraduate/apply/english/. The closing date for applications is midnight (GMT) on Wednesday 10 January 2018. Interviews will be held at the University of Exeter in late February 2018. If you have any general enquiries about the application process please email: pgrenquiries(a)exeter.ac.uk<mailto:pgrenquiries@exeter.ac.uk>. Project-specific queries should be directed to the supervisor. ________________________________ Krasimira Tsaneva-Atanasova Professor of Mathematics for Healthcare Department of Mathematics & Living Systems Institute, T02.17 University of Exeter, Stocker Road, Exeter, EX4 4QD, UK email: k.tsaneva-atanasova(a)exeter.ac.uk<mailto:k.tsaneva-atanasova@exeter.ac.uk> tel: +44 (0) 1392 723615 web: http://emps.exeter.ac.uk/mathematics/staff/kt298

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PhD position at the University of Exeter
by Tsaneva-Atanasova, Krasimira Dec. 2, 2017

Dec. 2, 2017

Understanding Emergent Complex Noisy Patterns in Biological Cells - Mathematics - EPSRC DTP funded PhD Studentship Ref: 2890 About the award This project is one of a number funded by the Engineering and Physical Sciences Research Council (EPSRC<https://www.epsrc.ac.uk/skills/students/>) Doctoral Training Partnership to commence in September 2018. This project is in direct competition with others for funding; the projects which receive the best applicants will be awarded the funding. The studentships will provide funding for a stipend which is currently £14,553 per annum for 2017-2018. It will provide research costs and UK/EU tuition fees at Research Council UK rates for 42 months (3.5 years) for full-time students, pro rata for part-time students. Please note that of the total number of projects within the competition, up to 15 studentships will be filled. Supervisors Associate Professor Jan Sieber<http://emps.exeter.ac.uk/mathematics/staff/js543> Prof Krasimira Tsaneva-Atanasova<https://emps.exeter.ac.uk/mathematics/staff/kt298> Dr Joel Tabak<http://medicine.exeter.ac.uk/people/profile/index.php?web_id=Joel_Tabak-Szn…> Location Streatham Campus, Exeter Project Description One of the most fascinating phenomena in nature is that small random disturbances can create systematic large-scale patterns of motion. Mathematically, this is described by the theory of nonlinear dynamics. One essential process governed by this theory is electrical signalling in animal and plant cells. Biological cells communicate with periodic or more complex patterns of electrical signals that underlie thinking, hormone release or muscle movement. These patterns are extremely sensitive to various types of noise present in cells such as rapid fluctuations and slow random drift. A general mathematical question is how precisely the different types of small noise perturbations influence the emergent patterns in nonlinear systems. Applications of the insights gained from mathematical analysis to understanding and controlling living cells would allow us to inform novel therapies for hormonal or neural disorders such as chronic stress response or essential tremor for example. Traditionally, mathematical modelling of cells has been applied to idealised, noise-free models. This funded PhD studentship will investigate how small noise drives and controls periodic and non-periodic patterns in general, and specifically in excitable cell models and experiments. The student will design a method to remove noise from emergent electrical patterns, using techniques from dynamical systems theory and feedback control theory. Joel Tabak (one of the project supervisors) has developed a proof of concept methodology for periodic patterns that is similar to what is used in noise-cancelling headphones, but uses concepts from dynamical systems to determine the perturbing noise. Being able to remove noise will allow us to compare the patterns in noisy and noise-free conditions. This will help scientists understanding how noise controls electrical patterns in many types of electrically active cells. The student will design further new methods for removing noise in mathematical models (ordinary differential equations) of electrically active cells. The PhD studentship will benefit from close collaboration with Joel Tabak’s neuroscience laboratory. This laboratory is able to perform experiments with live cells in real time using electrical signals in dynamic clamp experiments. Thus, the student will have the opportunity to immediately test how their methods perform in a real biological system, and use the experimental results as a guide to refine their methodology. By interacting with experimental researchers, the student will also gain important experience in working within a multidisciplinary scientific team. Depending on the student’s interests and progress during the PhD studentship, there will also be the opportunity to learn electrophysiology in order to record the electrical activity from live cells. This project would suit a student keen to 1) learn and apply new maths concepts (nonlinear dynamical systems, multi-scale analysis, stochastic processes); 2) interact with people from different scientific fields; and 3) present their results at national and international conferences. Entry Requirements You should have or expect to achieve at least a 2:1 Honours degree, or equivalent, in mathematics or a natural sciences or engineering programme with a strong quantitative component. Experience in nonlinear dynamics, mathematical biology or probability, and some programming experience are desirable. The majority of the studentships are available for applicants who are ordinarily resident in the UK and are classed as UK/EU for tuition fee purposes. If you have not resided in the UK for at least 3 years prior to the start of the studentship, you are not eligible for a maintenance allowance so you would need an alternative source of funding for living costs. To be eligible for fees-only funding you must be ordinarily resident in a member state of the EU. For information on EPSRC residency criteria click here<https://www.epsrc.ac.uk/skills/students/help/eligibility/>. Applicants who are classed as International for tuition fee purposes are NOT eligible for funding. International students interested in studying at the University of Exeter should search our funding database<http://www.exeter.ac.uk/postgraduate/money/fundingsearch/> for alternative options. Summary Application deadline: 10th January 2018 Value: 3.5 year studentship: UK/EU tuition fees and an annual maintenance allowance at current Research Council rate. Current rate of £14,553 per year. Duration of award: per year Contact: Doctoral College pgrenquiries(a)exeter.ac.uk<mailto:pgrenquiries@exeter.ac.uk> How to apply Apply now You will be required to upload the following documents: • CV • Letter of application outlining your academic interests, prior research experience and reasons for wishing to undertake the project. • Transcript(s) giving full details of subjects studied and grades/marks obtained. This should be an interim transcript if you are still studying. • If you are not a national of a majority English-speaking country you will need to submit evidence of your current proficiency in English. For further details of the University’s English language requirements please see http://www.exeter.ac.uk/postgraduate/apply/english/. The closing date for applications is midnight (GMT) on Wednesday 10 January 2018. Interviews will be held at the University of Exeter in late February 2018. If you have any general enquiries about the application process please email: pgrenquiries(a)exeter.ac.uk<mailto:pgrenquiries@exeter.ac.uk>. Project-specific queries should be directed to the supervisor. ________________________________ Krasimira Tsaneva-Atanasova Professor of Mathematics for Healthcare Department of Mathematics & Living Systems Institute, T02.17 University of Exeter, Stocker Road, Exeter, EX4 4QD, UK email: k.tsaneva-atanasova(a)exeter.ac.uk<mailto:k.tsaneva-atanasova@exeter.ac.uk> tel: +44 (0) 1392 723615 web: http://emps.exeter.ac.uk/mathematics/staff/kt298 ________________________________ Krasimira Tsaneva-Atanasova Professor of Mathematics for Healthcare Department of Mathematics & Living Systems Institute, T02.17 University of Exeter, Stocker Road, Exeter, EX4 4QD, UK email: k.tsaneva-atanasova(a)exeter.ac.uk<mailto:k.tsaneva-atanasova@exeter.ac.uk> tel: +44 (0) 1392 723615 web: http://emps.exeter.ac.uk/mathematics/staff/kt298

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NeuroMorpho.Org v7.3 released November 28th, 2017
by NeuroMorpho Administrator Dec. 2, 2017

Dec. 2, 2017

Dear colleagues, We’re pleased to announce the November 28, 2017 release of Version 7.3 of NeuroMorpho.Org<http://neuromorpho.org/>, adding 9987 reconstructions from 96 new datasets. The repository now provides access to 80,012 cells and passed 8 million downloads in 166 countries. Please visit the What’s new page<http://neuromorpho.org/WIN.jsp> for details on the added data and metadata. The literature coverage was also updated to include publications through October 2017, with more than 1000 articles referencing data in this resource. We are continuously grateful to all data contributors<http://neuromorpho.org/acknowl.jsp#DC> who freely share their hard-won tracings with the community. We appreciate any and all feedback and comments. Our apologies if you receive multiple versions of this message through cross-listing. Sincerely, The NeuroMorpho.Org team<http://neuromorpho.org/acknowl.jsp#NMO> ---------------- Giorgio Ascoli<http://krasnow1.gmu.edu/cn3/ascoli>, PhD University Professor Bioengineering Department<http://bioengineering.gmu.edu/>, Volgenau School of Engineering<http://volgenau.gmu.edu/> Neuroscience Program<http://neuroscience.gmu.edu/>, Krasnow Institute for Advanced Study<http://krasnow1.gmu.edu/> Director, Center for Neural Informatics, Structures, & Plasticity<http://krasnow1.gmu.edu/cn3> MS2A1 - George Mason University<http://gmu.edu/>, Fairfax, VA 22030-4444 Ph. +1(703)993-4383/+1(703)673-8894 Author of “Trees of the Brain, Roots of the Mind<http://www.amazon.com/Trees-Brain-Roots-Giorgio-Ascoli/dp/0262028980/>” (MIT Press, 2015<http://mitpress.mit.edu/books/trees-brain-roots-mind>) Founding Editor-in-Chief, Neuroinformatics<http://link.springer.com/journal/12021>

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BECNC 2018 Conference
by Narges Chinichian Dec. 2, 2017

Dec. 2, 2017

[Apologies for cross posting] Dear All I'm glad to announce that the "Brain Engineering & Computational Neuroscience Conference BECNC 2018" will be held on Jan 31 to Feb 2 in Tehran, Iran. Here is the link to register: https://becnc.ir/?page_id=452 <https://becnc.ir/?page_id=452> Keynote Speakers: Prof. Tipu Aziz (Oxford Univ., UK) Prof. Kenneth Miller (Columbia Univ., USA) Prof. Reza Shadmehr (JHU, USA) Prof. Pieter Roelfsema (NIN, Netherlands) Prof. Alexandre Pouget (Univ of Geneva) Prof. Susana Martinez-Conde (SUNY, USA) Prof. Susan J. Sara (College de France) Prof. Winrich Freiwald (Rockefeller Univ, USA) Prof. Gregor Rainer (Univ. of Fribourg, Switzerland) Prof. James Bisley (UCLA, USA) Prof. Qasim Zaidi (SUNY, USA) Prof. Yasser Roudi (NTNU, Norway) Prof. Valentin Dragoi (UT, USA) Prof. Frank Scharnowski (Univ. of Zürich, Switzerland) Prof. Alexander Thiele (Newcastle Univ., UK) Dr. Kamran Diba (Univ. of Michigan, USA) Dr. Ali Borji (UCF, USA) Dr. Qolamreza (Ray) Razlighi (Columbia Univ., USA) Dr. Morteza M. Goudarzi (MIT, USA) Dr. Koorosh Mirpour (UCLA, USA) Dr. Athena Akrami (Princeton Univ., USA) Dr. Yousef Salimpour (JHU, USA) Dr. Abbas Khani (Univ. of Geneva, Switzerland) see the complete list here: <http://goog_1578179254/> https://becnc.ir/?page_id=91 Dates & Deadlines: Abstract and full paper submission opening: November 4, 2017 Abstract submission deadline: January 10, 2018 Full paper submission deadline: January 11, 2018 Conference registration deadline: January 23, 2018 Late conference registration deadline (limited number): January 30, 2018 Main event: January 31 – February 2, 2018 There are also a workshop and a one-day course at the same time which you may like to attend. Find the details here: https://becnc.ir/?page_id=488 For more information, visit: https://becnc.ir/ Regards

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Data Engineer at Columbia University's Zuckerman Mind Brain Behavior Institute
by Rajendra Bose Dec. 1, 2017

Dec. 1, 2017

Columbia University's Mortimer B. Zuckerman Mind Brain Behavior Institute (Zuckerman Institute) is seeking a highly motivated individual with strong software engineering skills, some familiarity with machine learning, and an interest in neuroscience and teaching to facilitate data analysis and sharing across 10 laboratories <https://zuckermaninstitute.columbia.edu/columbia-s-zuckerman-institute-awar…> investigating the computational and circuit mechanisms underlying motor control. For more information and to apply, see: https://zuckermaninstitute.columbia.edu/data-engineer Thank you— Raj Rajendra Bose, Ph.D. Director, Research Computing Mortimer B. Zuckerman Mind Brain Behavior Institute Columbia University Tel: 212-851-2918 http://zuckermaninstitute.columbia.edu

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Real World Eye Tracking course 2018 - booking now open
by Durant, Szonya Nov. 27, 2017

Nov. 27, 2017

We are pleased to announce that booking for the Real World Eye Tracking Course April 16 +17, 2018 at Royal Holloway, University of London, is now open. This course is supported by the BBSRC and is accredited by the Market Research Society (counting for 12h Continued Professional Development). It is run jointly by the Dept. of Psychology, Royal Holloway and Acuity Intelligence Ltd. Why do you need to know about eye tracking? >From glasses you can use almost anywhere to laptops with them built-in and now augmented and virtual reality headsets - eye tracking is everywhere! But not all eye trackers are created equal, and to get the best out of this technology you need look around. Whether for simply knowing where a person looks or understanding cognitive states in high pressure environments, this is a technology you can't afford to ignore. Why we run this course We believe you need some theoretical background to get the most out of eye-tracking, but we also recognise the value that comes from the hands-on experience of designing, running and analysing real studies. Our aim is to give you the confidence to dive in and save you from drowning when you do! No other course offers this range of cutting edge multi-platform systems in one place, without a sales-person in sight! Try things out, and see the results for yourself. What you will learn How to justify your use of eye tracking methods and understand the evidence they provide Where to find further information when running your own projects How to choose the right tools and begin running your own project How to get the most out of your research through good design and great analysis Course content The course contains a mix of interactive lectures and small team project work supervised by an expert in the field. All attendees will experience running an eye tracking project from start to finish. You will also get to chat with experts and develop a feel for issues, independent of hardware and software platforms, from various research applications. Please see further details on https://www.royalholloway.ac.uk/psychology/research/eyetracking.aspx or book directly on https://www.eventbrite.com/e/real-world-eye-tracking-course-tickets-3969635… Please note, places often sell out quickly! We look forward to welcoming you in April! Best wishes Szonya Durant (RHUL) Tim Holmes (AI Ltd) ********************************************************************** Szonya Durant Department of Psychology Royal Holloway, University of London Egham TW20 0EX 01784 276522

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Postdoctoral Researcher at MPI Leipzig
by Thomas Knoesche Nov. 27, 2017

Nov. 27, 2017

Dear colleagues, the Max-Planck-Institute for Human Cognitive and Brain Sciences (MPI-CBS, Leipzig, Germany) in seeking a Postdoctoral Researcher for a period of 3 years. The position is part of a collaboration between the Pompeu Fabra University at Barcelona, (G. Deco) and the MPI-CBS (A.D. Friederici, A. Anwander, T.R. Knösche), entitled "The Dynamic Connectome Underlying Language in the Brain" financed by the DFG priority program “Computational Connectomics”. You will work in a multidisciplinary team of computational and cognitive neuroscientists, imaging experts, biomedical engineers, neurologists, etc. The MPI-CBS offers excellent research facilities and prime imaging equipment (including 7T and CONNECTOM scanners). Project Description The neural language network is well described by systematic neuroscientific studies and may serve as an example for large scale cognitive networks within the human connectome. Important parameters of dynamic network models concern the structural/effective connectivity between brain areas. These connections are realized by bundles of axons with variable density, myelination status, and diameters. This results in complex transfer behavior, which is likely to have a profound influence onto the dynamics of the entire network. We plan to (i) establish a mathematical model for the transfer function between brain areas through fiber bundles, (ii) parameterize this model with individually measured white matter microstructure (acquired partly using novel high-gradient MR technology – CONNECTOM) and general data from the literature, (iii) incorporate this model into a dynamic network model (iv) explore the effect of the parameters onto the dynamics of canonical network architectures, (v) validate the model with electrophysiological calibration experiments, and (vi) use it to establish relations between language function and microstructural properties of brain tissue. The successful applicant should have a strong background in Computational Neuroscience, preferably including a PhD thesis in that area. Experience with modeling dynamic systems in neuroscience is necessary. A fair degree of neurobiological and neuroimaging understanding will be an advantage. Remuneration is based on the payscale of the Max Planck Society. The Max Planck society is committed to increasing the number of individuals with disabilities in its workforce and therefore encourages applications from such qualified individuals. Please submit your application via our online system at http://www.cbs.mpg.de/vacancies (using subject heading “PD 24/17”). Closing date for applications is December 15th, 2017. Contact for informal enquiries regarding the post: PD Dr.habil. Thomas R. Knösche (knoesche(a)cbs.mpg.de) For more information about the group see: http://www.cbs.mpg.de/methods-and-development-groups/meg-and-cortical-netwo… -- --- PD Dr.habil. Thomas R. Knösche Group Leader Research group "Cortical Networks and Cognitive Functions" Max Planck Institute for Human Cognitive and Brain Sciences Stephanstraße 1A, 04103 Leipzig, Germany Phone: +49 341 9940-2619 Fax: +49 341 9940 2624 Email: knoesche(a)cbs.mpg.de http://www.cbs.mpg.de/~knoesche

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[WCCI 2018 Special Session] Interpretable Deep Learning Classifiers
by Teng Teck Hou Nov. 23, 2017

Nov. 23, 2017

[Apologies for cross-postings] Special Session on Interpretable Deep Learning Classifiers IEEE World Congress on Computational Intelligence 8 - 13 July 2018, Rio de Janeiro, Brazil www.ieee-wcci.org Chairs: Plamen P. Angelov, Lancaster University, UK p.angelov(a)lancaster.ac.uk Jose C. Principe, University of Florida, principe(a)cnel.ufl.edu Synopsis: Deep Learning is becoming a synonym of highly precise (reaching or surpassing capabilities of a human) computational intelligence technique. Very interesting and important results were reported recently in both scientific literature and also grabbed the imagination of the wider public and industry helping propel the interest towards AI, neural networks, machine learning. It was applied mostly to solve classification problems in image processing, but also for predictive tasks in speech processing and other problems. Despite the undoubted success in achieving high precision and avoiding handcrafting in feature selection a number of issues remain unresolved, such as: i) transparency and interpretability; ii) the requirement for extremely large training data set, computational resources and time; iii) overfitting and catastrophic failures with high confidence in some cases; iv) convergence proof for the case of reinforcement learning; v) rigid structure unable to be adapted/to dynamically evolve with new samples and/or new classes; vi)repeatability of the results. Methodologically, the vast majority of the techniques of this hot and quickly developing area are based exclusively on neural networks (convolutional, belief based, etc.). Very recently publications appear where the deep learning (multi-layer) architecture with different levels of abstraction is build based on fuzzy rulebased systems or fuzzy sets are used to represent coefficients/weights in Restricted Bolzman Machines, etc. The aim of the special session is to address the bottleneck issues listed above and discuss and represent alternative and most recent methods, techniques and approaches that can help resolve these issues. The specific sub-topics that will be of interest include: * Interpretable/Transparent Deep Learning * Computational and time complexity/efficiency of Deep Learning Methods * Repeatability of the results of Deep Learning Methods * Degree of confidence in the results of Deep Learning * Highly Parallelisable Deep Learning Methods * Deep Learning with proven convergence * Re-trainability and dynamically evolving structures/architectures for Deep Learning * Ensembles of Deep Learning Classifiers * Fuzzy Deep Rule-based Classifiers * Self-adaptive and Self-organising Deep Learning Architectures Also applications to: * Computer Vision * Image Classification * Robotics * Remote Sensing * Biology and Tomography * Surveillance and Defense * Industry 4.0 * Assistive Technologies and Digital Health Important dates: * Paper Submission Deadline 15 January, 2018 * Paper acceptance notification date 15 March, 2018 * Final paper submission deadline 1 May, 2018 Conference: 8-13 July, 2018 Submission Guidelines: Please follow the regular submission guidelines of WCCI 2018. Please notify the chairs of your submission by sending an email to: p.angelov(a)lancaster.ac.uk or principe(a)cnel.ufl.edu This special session is supported by the IEEE Task Forces on Deep Learning http://deeplearning.math.unipd.it/ and on Evolving and Adaptive Fuzzy Systems, http://www.caos.inf.uc3m.es/aefs/

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