November 2016 - Comp-neuro - lists.cnsorg.org

PhD positions at the University of Exeter: Controlling noise effects in models of excitable cells

by Tsaneva-Atanasova, Krasimira

About the award This project is one of a number which are funded by the Engineering and Physical Sciences Research Council (EPSRC) Doctoral Training Partnership to commence in September 2017. The studentships will provide funding for a stipend which, is currently £14,296 per annum for 2016-2017, 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. Supervisors: Main supervisor: Prof Krasimira Tsaneva-Atanasova<http://emps.exeter.ac.uk/mathematics/staff/kt298> (University of Exeter) Co-supervisor: Dr Jan Sieber<http://emps.exeter.ac.uk/mathematics/staff/js543> (University of Exeter) Co-supervisor: Dr Joël Tabak<http://medicine.exeter.ac.uk/about/profiles/index.php?web_id=Joel_Tabak-Szn…> (University of Exeter) Location: University of Exeter, Streatham Campus, Exeter, Devon Project Description: This is a project that combines biological modelling and general mathematical analysis of the influence of noise on multiple-timescale systems. It will give the student the opportunity to work on open mathematical questions and see their results applied in experiments on living cells. Many types of cells such as neurons, heart and hormone-releasing cells generate impulses of electrical activity, organized as single spikes or bursts of impulses. In cells of the pituitary gland – the master hormonal gland of the body – the features of electrical activity patterns determine how much hormone is released into the circulation. Hence, understanding how the characteristic features of electrical activity arise is crucial to understanding how these cells function, and how they may malfunction in disease. Mathematical modelling and analysis techniques have proven very successful in helping unravel fundamental mechanisms controlling the behaviour of excitable cells. Electrical activity is driven by the interactions between ion channels of the cell membrane, which produce noisy electrical currents. The mathematical models of electrical activity thus contain random and deterministic parts, which typically appear as separate terms (e.g., the deterministic drift and the Brownian-motion induced diffusion in stochastic differential equations). In experimental practice this distinction is not as clear. For example, ion channels in cells with electrical activity generate noisy signals, driving systematically the electrical and chemical activity in the cell, which operate also on several time scales. It is still unclear how this randomness influences electrical activity in real cells. This PhD project will investigate how one can use control to identify the systematic (deterministic) component of trajectories in dynamical systems with random inputs (such as ion channel noise) that operate on two or three different time scales (such as spiking or bursting cells). A first goal to separate a systematic, approximately periodic, signal without knowledge of the period using control and geometric methods in a reconstructed phase space. Preliminary investigations with noise on a single time scale interacting with a two-timescale oscillation (spiking) have shown that this is in principle possible. It is an open question how this can be generalized to periodic behaviours with a more complicated geometry (such as bursting), interacting with noise effects that occur on two time scales. Another open question is how the geometric control and noise identification is related to extended time-delayed feedback, which creates a reference signal from a geometric time series of past outputs. Entry requirements: Applicants should have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK. Applicants with a Lower Second Class degree will be considered if they also have Master’s degree. Applicants with a minimum of Upper Second Class degree and significant relevant non-academic experience are encouraged to apply. All applicants would need to meet our English language requirements by the start of the project http://www.exeter.ac.uk/postgraduate/apply/english/. 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; however up to 9 fully-funded studentships across the DTP are available for EU/EEA applicants not ordinarily resident in the UK. Applicants who are classed as International for tuition fee purposes are not eligible for funding. Summary Application deadline: 11th January 2017 Value: 3.5 year studentship: UK/EU tuition fees and an annual maintenance allowance at current Research Council rate. Current rate of £14,296 per year. Duration of award: per year Contact: Doctoral College: 01392 722737 doctoral.college(a)exeter.ac.uk<mailto:doctoral.college@exeter.ac.uk> How to apply Click here to apply<http://www.exeter.ac.uk/postgraduate/money/funding/application/> Please be aware you will be asked 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 on 11 January 2017. Interviews will be held at the University of Exeter between 13 February and 17 February 2017. If you have any general enquiries about the application process please email Doctoral.College(a)exeter.ac.uk<mailto:Doctoral.College@exeter.ac.uk> or phone +44 (0)1392 722311. Project-specific queries should be directed to the supervisor. During the application process, the University may need to make certain disclosures of your personal data to third parties to be able to administer your application, carry out interviews and select candidates. These are not limited to, but may include disclosures to: • the selection panel and/or management board or equivalent of the relevant programme, which is likely to include staff from one or more other HEIs; • administrative staff at one or more other HEIs participating in the relevant programme. Such disclosures will always be kept to the minimum amount of personal data required for the specific purpose. Your sensitive personal data (relating to disability and race/ethnicity) will not be disclosed without your explicit consent. Krasimira Tsaneva-Atanasova Professor of Mathematics for Healthcare Department of Mathematics College of Engineering, Mathematics and Physical Sciences University of Exeter Exeter, Devon, EX4 4QF, UK tel: +44 (0) 1392 723615 email: k.tsaneva-atanasova(a)exeter.ac.uk<mailto:k.tsaneva-atanasova@exeter.ac.uk> web: http://emps.exeter.ac.uk/mathematics/staff/kt298

Nov. 19, 2016

PhD Position: Modelling spine calcium dynamics and cross talk: implications for synaptic plasticity and ischaemia

by Tsaneva-Atanasova, Krasimira

PhD Position: Modelling Spine Calcium Dynamics, University of Exeter Project Description: Nerve cells (neurones) in the brain communicate with one another at connect ions called synapses. A chemical (neurotransmitter) is released from a neuron and travels across the synapse to activate receptors in the adjacent neuron. Synapses can change their strength (known as “synaptic plasticity”) by altering the number of receptors found on the surface of the neuron in the synapse. This process is thought to underlie learning and memory, because the memory is likely to be stored in a circuit of interconnected neurons. The critical trigger for synaptic plasticity is the influx of calcium ions into very small compartments of neurones called spines, tiny structures approximately 1 millionth of a metre in diameter. However, this influx of calcium ions can also trigger cell death after ischaemic injury that occurs during stroke so it must be tightly regulated. Plasticity of excitatory synapses is a key mechanism by which we alter the flow of information in the brain and encode memories. Individual synapses occur at thousands of postsynaptic dendritic spines separated from the dendrite by a thin neck making each spine a semi-autonomous entity. It is thought that this is what underpins synapse specific plasticity enabling high capacity memory. However, recently it has become clear that cross talk between coactive spines is the basis for many forms of synaptic plasticity, but the mechanism, requirements and biological function for this spine-spine communication remain unknown. Similarly, the precise calcium signals that differentiate plasticity from cell death processes are also unknown. This project aims to address these questions using a combination of mathematical modelling and high-resolution imaging data collected with high-powered laser microscope. In order to capture the complex geometry of the system we will employ advanced mathematical techniques for spatio-temporal modelling and analysis such as finite element methods. This work is important because it will lead to a wealth of new information about synaptic plasticity and cell death processes, and hence the mechanisms underlying learning and memory and ischaemic brain damage. Furthermore, dysfunction in the ability to undergo synaptic plasticity is thought to underlie the altered neuronal activity in several brain diseases, such as Alzheimer’s disease, schizophrenia and autism. Therefore, the mechanisms that we will study in this research will add to our knowledge about these debilitating diseases, and may contribute to developing therapies. Academic Supervisors: Main Supervisor: Professor Krasimira Tsaneva-Atanasova (University of Exeter) Co-supervisor: Dr Jack Mellor (University of Bristol) Summary Application deadline: 5th December 2016 Value: £14,296 per annum for 2016-17 How to apply Click here to apply<http://www.exeter.ac.uk/postgraduate/money/funding//application/> Please be aware you will be asked to upload the following documents: • CV • Letter of application outlining your academic interests, prior research experience and reasons for wishing to undertake the project. Please indicate your preferred project choice if applying for multiple BBSRC SWBio DTP projects. • 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 proficiency in English (see entry requirements above) You will be asked to name 2 referees as part of the application process however we will not contact these people until the shortlisting stage. Your referees should not be from the prospective supervisory team. The closing date for applications is midnight on Monday, 5 December 2016. Interviews will be held at the University of Exeter in early February 2017. If you have any general enquiries about the application process please email cles-pgr-support(a)exeter.ac.uk<mailto:cles-pgr-support@exeter.ac.uk> or phone +44 (0)1392 725150 / 723706. Project-specific queries should be directed to the supervisor. ----------------------------------------------------------- BBSRC SWBio DTP PhD studentship: Modelling spine calcium dynamics and cross talk: implications for synaptic plasticity and ischaemia About the South West Biosciences Doctoral Training Partnership: The South West Biosciences Doctoral Training Partnership (SWBio DTP) is a BBSRC-funded PhD training programme in the biosciences, delivered by a consortium comprising the Universities of Bristol (lead), Bath, Cardiff, Exeter, and Rothamsted Research. Together, these institutions present a distinctive cadre of bioscience research staff and students with established international, national and regional networks and widely recognised research excellence. The partnership has a strong track record in advancing knowledge through high quality research and teaching in partnership with industry and government. The aim of the SWBio DTP is to produce highly motivated and excellently trained postgraduates in the BBSRC priority areas of Agriculture & Food Security (AFS) and World-Class Underpinning Bioscience (WCUB). These are growth areas of the biosciences and for which there will be considerable future demand. About the award: This project is one of a number that are in competition for funding from the South West Biosciences Doctoral Training Partnership (SWBio DTP). Up to 4 fully-funded studentships are being offered to start in September 2017 at the University of Exeter. For UK/EU nationals who meet the residency requirements outlined by the BBSRC, the studentship will cover funding for 4 years (48 months) as follows. These awards might be available to part-time students, but only in exceptional circumstances, in which case the funding will be paid on a pro-rata basis. • a stipend at the standard Research Council UK rate; currently £14,296 per annum for 2016-2017 • research and training costs • tuition fees (at the standard Research Councils UK rate • additional funds to support fieldwork, conferences and a 3-month internship Location: University of Exeter, Streatham Campus, Exeter Entry requirements: Applicants should have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of science or technology. Applicants with a Lower Second Class degree will be considered if they also have Masters degree or have significant relevant non-academic experience. In addition, due to the strong mathematical component of the taught course in the first year and the quantitative emphasis in our projects, a minimum of a grade B in A-level Maths or an equivalent qualification or experience is required. If English is not your first language you will need to have achieved at least 6.5 in IELTS and no less than 6.5 in any section by the start of the project. Alternative tests may be acceptable, please see http://www.bristol.ac.uk/study/language-requirements/profile-c/. Students from EU countries who do not meet the residency requirements may still be eligible for a fees-only award but no stipend. Applicants who are classed as International for tuition fee purposes are not eligible for funding. Further information about eligibility can be found in the following document: http://www.bbsrc.ac.uk/documents/studentship-eligibility-pdf/ Selection process: Please note, the studentship selection process will take place in two stages: 1. The project supervisors will consider your application and may invite you to visit for an informal interview. You can apply for more than one BBSRC SWBio DTP project, although supervisors may take into account your interest and commitment to their particular project. If you apply for multiple projects, please indicate your preferred project choice in your letter of application. Each application for an individual project will be considered separately by the project supervisors. 2. After closure of applications, each supervisory team will then nominate their preferred applicant. A shortlist will be selected from these nominations and shortlisted applicants will be invited for interview on a selection day at the University of Exeter. Please note that nomination by a project supervisor therefore does not guarantee the award of a studentship. ----------------------------------------------------------- Krasimira Tsaneva-Atanasova Professor of Mathematics for Healthcare College of Engineering, Mathematics and Physical Sciences University of Exeter Exeter, Devon, EX4 4QF, UK tel: +44 (0) 1392 723615 email: k.tsaneva-atanasova(a)exeter.ac.uk<mailto:k.tsaneva-atanasova@exeter.ac.uk> web: http://emps.exeter.ac.uk/mathematics/staff/kt298

Nov. 19, 2016

Call for Registration: Computational Neurology 2017. Newcastle upon Tyne, UK

by roman bauer

Dear all, We are pleased to announce that the registration for the Computational Neurology Conference in Newcastle upon Tyne, UK has opened. *Please register here:* https://conferences.ncl.ac.uk/compneurology/registration/ - Registration is free and includes lunch/coffee breaks on both days - Speakers are not required to register *Registration deadline:* February 5, 2017 *List of confirmed speakers:* - Javier Escudero - Edinburgh - Marc Goodfellow - Exeter - Andrew Jackson - Newcastle - Viktor Jirsa – Marseille - Marcus Kaiser - Newcastle - Dimitri Kullmann – University College London - Marco Manca - CERN - Florian Mormann - Bonn - Matthew Nolan – Edinburgh - Gregory Scott - Imperial College London - Evelyne Sernagor - Newcastle - Peter Uhlhaas – Glasgow Additionally, there will be multiple mini-talks from selected poster presenters. More information on the conference can be found at the dedicated website: https://conferences.ncl.ac.uk/compneurology/ Thanks and we look forward to seeing you in Newcastle upon Tyne! On behalf of the organizers: Roman Bauer, Anupam Hazra, Luis Peraza Rodriguez, Peter Taylor, Yujiang Wang -- Roman Bauer, Ph.D. MRC Research Fellow Institute of Neuroscience Newcastle University Newcastle upon Tyne NE1 7RU, UK tel: +44 (0) 191 208 8933 <+44%20(0)%20191%20208%208933>

Nov. 19, 2016

Funded PhD places at Royal Holloway

by Durant, Szonya

Applications are open for funded PhD places starting 2017 in the Dept. of Psychology, Royal Holloway University of London. Further details: https://www.royalholloway.ac.uk/psychology/prospectivestudents/postgraduate… The following projects may be of interest to the readers of this list (linked the project descriptions below), please contact the primary supervisor for more information. ? The perceived duration of actions (Primary Supervisor: Dr Durant<https://pure.royalholloway.ac.uk/portal/en/persons/szonya-durant_64105598-7…>; Second Supervisor: Dr Lingnau<https://pure.royalholloway.ac.uk/portal/en/persons/angelika-lingnau%283be38…>) ? Semantic information transfer from audition to vision (Primary Supervisor: Dr Vetter<https://pure.royalholloway.ac.uk/portal/en/persons/petra-vetter(cdfd308c-1e…>; Second Supervisor: Dr Auer) ? Perceptual and physiological correlates of aesthetic preferences (Primary supervisor: Prof Zanker<https://pure.royalholloway.ac.uk/portal/en/persons/johannes-zanker_350450c5…>; Second Supervisor: Dr Durant<https://pure.royalholloway.ac.uk/portal/en/persons/szonya-durant_64105598-7…>) ? The neuroscience of facial attractiveness choices (Primary Supervisor: Dr Furl<https://pure.royalholloway.ac.uk/portal/en/persons/nicholas-furl(ea2a352b-6…> ; Second Supervisor: Dr McKay<https://pure.royalholloway.ac.uk/portal/en/persons/ryan-mckay_cda72457-6d2a…>) ? Detection of emotion and trustworthiness across the lifespan (Primary Supervisor : Dr Watling<https://pure.royalholloway.ac.uk/portal/en/persons/dawn-watling_70194d88-af…>; Second Supervisor : Dr Durant<https://pure.royalholloway.ac.uk/portal/en/persons/szonya-durant_64105598-7…> ) Szonya Durant, RHUL Angelika Lingnau, RHUL The perceived duration of actions Project Summary The perception of duration is often cited as being crucial for action. Overlapping neural areas have been found to be involved in motor planning and duration perception. However, dissociations have been found in time judgement for action and perception. Our ability to judge the duration of our own and others' actions has been little investigated. Additionally, predictability affects duration perception and neural signal change - do expected actions differ from unexpected ones in their perceived duration? This project combines psychophysical, EEG and fMRI techniques, providing the PhD candidate with a broad training in neuroscientific techniques. The behavioural experiments compare the perceived duration of action to matched non-action visual stimuli. We test if judging our own actions cued by a visual stimulus improves accuracy or shifts means compared to action or non-action visual stimuli alone. We will also manipulate predictability of actions, both by probability of occurrence or expectation in terms of object affordance. The fMRI studies will contrast judging the duration of another person's actions versus one's own as well as non-action visual stimuli. We will examine which brain areas are modulated by perceived duration and by predictability. Moreover, we will use MVPA to examine predictability effects on the ability to categorize actions. The EEG experiments will use the visual mismatch negativity signal as a measure of what is considered a predictable action when attention is not directed towards it and relate this to the psychophysical results. Petra Vetter, RHUL Tibor Auer, RHUL Semantic information transfer from audition to vision Project summary: Our brain integrates a multitude of sensory information into one coherent percept so that we can interact with the world. Previous research typically focussed on how multisensory information is integrated across space and time, but so far little research has attempted to determine the semantic meaning of the communicated information across the senses. However, knowing the semantic content of cross-modally transmitted information is crucial to optimise multimedia environments and sensory substitution devices for the blind. The goal of this project is to characterise the semantic information content that is transferred from audition to vision in the human brain, and to identify the neural pathways of this information transfer. The predominant methods will be functional MRI in combination with multivariate brain decoding techniques and transcranial magnetic stimulation (TMS). The project will address two main questions: 1. Which semantic categories of auditory information are distinguished in visual cortex and to which level of abstraction? Here we will decode natural sounds of several semantic categories (e.g. animals versus humans, female versus male, tools versus instruments) from fMRI activity patterns in early visual cortex in the absence of visual stimulation. 2. Where in the brain are these semantic categories distinguished? Here the brain pathways of audio-visual information transfer will be identified by connectivity and whole brain decoding analyses, as well as by stimulating multi-sensory brain areas with TMS prior to MRI scanning. The latter allows to identify the brain areas that are causally involved in mediating semantic information transfer from audition to vision. Johannes Zanker, RHUL Szonya Durant, RHUL Perceptual and physiological correlates of aesthetic preferences Project summary Arts history has plenty of 'theoretical' concepts on offer to explain what human spectators regard as beautiful (Gombrich 1977), which often closer to believe systems than being based on evidence. With the advent of psychophysics, investigating the relationship between the physical world and its mental representation, aesthetic judgement became accessible to empirical study (Fechner 1860), soon to be aided by some physiological and behavioural methods (Yarbus 1967, Berlyne 1971). The proposed project is planned to extend previous work that established (a) quantitative methods to measure aesthetic attributes - such as complexity, regularity, liking - that were applied to both to synthetic stimuli and samples of artwork, and (b) an analysis method for preferential eye movements for the same stimulus material, and complement it with (c) recordings of cortical activity recorded with the EEG system. The combination of methods offers the opportunity to directly link the perceptual tasks, recordings of eye movement signals (which are also picked up by the EEG system) and neural responses and align preference data sets from a single experiment. The goal of this project is to explore whether features such as style aspect, particular composition schemes, geometric properties such as perspective or symmetry, and mathematical properties such as the complexity of a piece of art, are reflected in the activity of the early visual system, and to what extent such cortical activity in the early visual system can contribute to for what participants perceive as pleasing, and describe as 'beautiful'. Dawn Watling, RHUL Szonya Durant, RHUL Detection of emotion and trustworthiness across the lifespan Project Summary Emotion recognition is a key social skill which we use on a daily basis to navigate successfully through social interactions. Individuals use facial expressions to infer and make judgments about the attitude and/or feelings of another (Cunningham & Odom, 1986) and the judgments that one makes are often used to guide future behaviour within the interaction (Gao & Maurer, 2009). Children recognize from 6-years-old that facial expressions of emotion do not always match true feelings. This PhD will address: first, what factors influence one's ability to detect a genuine (or faked) facial expression of emotion, how does this relate to judgements of trustworthiness; second, are their age related changes in detection and judgements across the lifespan? Throughout this PhD a series of studies will be designed to address these questions using static and dynamic images, and live interactions. The proposed cross-sectional design will include participant groups from early childhood to late adulthood. Participants will visit the Oculomotor lab and be asked to make judgements on genuineness of emotional expressions and how trustworthy an individual is. Participants' eye movements and gaze fixations will be recorded and analysed in terms of scan paths, gaze duration at targeted areas, and related to the perceived genuineness of the individual. There are important implications for the understanding of how a child may respond to an approaching strangers or how an elderly individual may respond to a stranger who makes a request (e.g., for money, to enter their home). Nicholas Furl, RHUL Ryan McKay, RHUL Bruno Averbeck, NIMH/NIH Davide Rivolta, University of East London The neuroscience of facial attractiveness choices Project summary Users of modern dating applications (e.g., Tinder) face a classic decision problem. This "best choice" or "marriage" problem requires participants to view a series of options one at a time (e.g., a series of used cars) and to decide whether to accept or reject each option. A participant's task is to find a high-ranking option in the series (e.g., a car with low mileage), with the restriction that declined options cannot be returned to. The problem is known as the "marriage" problem after the decision process adopted by astronomer Johannes Kepler when searching for a wife; after considering several candidates, Kepler returned to a previous candidate and was duly rejected. Our research team has shown that humans confronted by a similar mate choice task make suboptimal decisions, compared to computational "ideal observer" models. Further, parietal cortex activity may contribute to these decisions. Our Ph.D. project will use brain imaging to assess how suboptimal searches for the most attractive face arise from interactions between brain activity involved in decision making (parietal cortex) and social perception. Our student will also test whether brain stimulation (e.g., to parietal cortex) changes participants' ability to "wait for the right person". Our Ph.D. student will lead a project with potential for broad scientific and social impact and will receive training in brain imaging, brain stimulation and behavioural and computational methods. Szonya Durant Department of Psychology Royal Holloway, University of London Egham TW20 0EX 01784 276522

Nov. 18, 2016

Workshop on Tactile coding and neuroprostheses - Pontedera (Pisa), Italy - Dec 1-2 2016

by Alberto Mazzoni

Workshop announcement (apologies for cross-postings) *Workshop on Tactile coding and neuroprostheses * *December 1-2 2016, Pontedera (Pisa) - Italy * *@ The Biorobotics Institute of the Scuola Superiore Sant'Anna* *ABSTRACT* Neurophysiology of touch and development of artificial tactile sensation are two fields of research with an ever-increasing interchange. Advanced neuroprostheses are progressively focusing on reproducing the naturalistic processing of tactile sensations in the peripheral and central nervous system. In turn, biomimetic tactile sensors and behavioral studies on patient implanted with tactile neuroprostheses can contribute to the understanding of tactile coding. This workshop aims at fostering the integration of neurophysiological, computational and robotics studies on touch with contribution of leading experts in the different fields. *WORKSHOP SESSIONS* *Neurophysiology of touch *- keynote speaker *Roland S Johannson* (Umea University, Sweden) *Touch perception and tactile coding *- keynote speaker *Vincent Hayward* (Institut des Systèmes Intelligents et de Robotique, Paris, France) *Touch restoration, neuroprostheses and biorobotics *- keynote speaker *Sliman Bensmaia* (University of Chicago, USA) *DETAILS* The workshop takes place on the premises of The Biorobotics Institute of Scuola Superiore Sant'Anna, viale Rinaldo Piaggio 24, in Pontedera (15 mins by train from Pisa, 50 mins from Florence). The event is free, but registration is compulsory. *To register, please write to local organizer Alberto Mazzoni (a.mazzoni(a)sssup.it <a.mazzoni(a)sssup.it>)* *ORGANIZERS* Silvestro Micera (Scuola Superiore Sant'Anna, Pisa, Italy / École polytechnique fédérale de Lausanne, Switzerland) Henrik Jorntell (Lund University, Sweden) Calogero Oddo (Scuola Superiore Sant'Anna, Pisa, Italy) Alberto Mazzoni (Scuola Superiore Sant'Anna, Pisa, Italy) *ACKNOWLEDGMENTS* Italian Ministry of Foreign Affairs and International Cooperation, Directorate General for Country Promotion (Economy, Culture and Science)—Unit for Scientific and Technological Cooperation, via the Italy-Sweden bilateral research project on "Brain network mechanisms for integration of natural tactile input patterns", NEBIAS European project (EUFP7-ICT-611687) and Scuola Superiore Sant'Anna fund IEXERC14AM.

Nov. 18, 2016

Hiring Interviews at NIPS Barcelona for NEURAL DATA ANALYTICS - Post Docs, Staff Scientists, & Electrical Engineers

by Platt, Jo Ann

Bioelectronic Medicine is the new frontier of medicine - challenging and changing the way we diagnose, manage, and treat disease. Today's discoveries and devices are successfully replacing drugs. We aim to treat bleeding, cancer, diabetes, lupus, obesity, paralysis, rheumatoid arthritis, sepsis, and many other diseases and conditions. The Center for Bioelectronic Medicine at the Feinstein Institute for Medical Research is conducting interviews at Neural Information Processing Systems (NIPS) for multiple positions in the fields of machine learning, neural engineering, neural decoding and data analytics, microfabrication, bioelectronics and biosensing, and neurophysiology. Each successful candidate will work as part of a multidisciplinary team to determine the nature of neural control over molecular, cellular and organ functions of the body, the parts of the brain that regulate those nerves, and the signals that the brain receives to monitor cell and organ function. The candidates will work on projects involving development of novel signal processing and machine learning methods to gain insights into decoding and encoding mechanisms of the brain and peripheral nerves, reinforcement learning approaches used to optimize neural stimulation, techniques to directionally transmit or receive neural signals and numerical and biophysical modeling of neural circuits. Submit your resume to japlatt(a)northwell.edu<mailto:japlatt@northwell.edu> for consideration and to arrange an onsite interview. Jo Ann Platt The Feinstein Institute for Medical Research Cell: (415) 265-0441<tel:(415)%20265-0441> 350 Community Drive<x-apple-data-detectors://2/1> Manhasset, NY 11030<x-apple-data-detectors://2/1> The information contained in this electronic e-mail transmission and any attachments are intended only for the use of the individual or entity to whom or to which it is addressed, and may contain information that is privileged, confidential and exempt from disclosure under applicable law. If the reader of this communication is not the intended recipient, or the employee or agent responsible for delivering this communication to the intended recipient, you are hereby notified that any dissemination, distribution, copying or disclosure of this communication and any attachment is strictly prohibited. If you have received this transmission in error, please notify the sender immediately by telephone and electronic mail, and delete the original communication and any attachment from any computer, server or other electronic recording or storage device or medium. Receipt by anyone other than the intended recipient is not a waiver of any attorney-client, physician-patient or other privilege.

Nov. 17, 2016

[ECSQARU 2017] First Call for Papers

by Alessandro Antonucci

The Fourteenth European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty FIRST CALL FOR PAPERS http://ecsqaru.idsia.ch The biennial ECSQARU conferences constitute a major forum for advances in the theory and practice of reasoning under uncertainty. Contributions come from researchers interested in advancing the scientific knowledge and from practitioners using uncertainty techniques in real-world applications. The scope of the ECSQARU conferences encompasses fundamental issues, representation, inference, learning, and decision making in qualitative and numeric uncertainty paradigms. Previous ECSQARU events have been held in Marseille (1991), Granada (1993), Fribourg (1995), Bonn (1997), London (1999), Toulouse (2001), Aalborg (2003), Barcelona (2005), Hammamet (2007), Verona (2009), Belfast (2011), Utrecht (2013), and Compiègne (2015). ECSQARU 2017 will be co-located with ISIPTA '17, the Tenth International Symposium on Imprecise Probability: Theories and Applications. The joint event will be held in Lugano (Switzerland), on July 10-14, 2017. ::: SCOPE ::: For ECSQARU 2017 we invite submissions of conference papers on topics which include but are not limited to: - Algorithms for uncertain inference - Applications of uncertain systems - Argumentation systems - Automated planning and acting under uncertainty - Belief functions - Belief revision & merging - Classification & clustering - Decision theory & decision graphs - Default reasoning - Description logics with uncertainty - Foundations of reasoning under uncertainty - Fuzzy sets & fuzzy logic - Game theory - Imprecise probabilities - Inconsistency handling - Information fusion - Learning for uncertainty formalisms - Logics for reasoning under uncertainty - Markov decision processes - Possibility theory & possibilistic logic - Preferences - Probabilistic graphical models - Probabilistic logics - Qualitative uncertainty models - Rough sets - Uncertainty & data ::: INVITED SPEAKERS ::: We are delighted of having the following invited speakers: - Leila Amgoud (IRIT, France) - Alessio Benavoli (IDSIA, Switzerland) - Jim Berger (Duke University, USA) - Didier Dubois (IRIT, France) - Eyke Hüllermeier (Paderborn University, Germany) ::: PROCEEDINGS AND SUBMISSIONS ::: In accordance with the previous conferences, the proceedings of ECSQARU 2015 will be published in the Springer Lecture Notes in Artificial Intelligence series. Authors are requested to prepare their conference papers in the LNCS/LNAI format. Submitted papers will be evaluated by peer reviews based on originality, significance, technical soundness, and clarity of exposition. Authors of accepted papers are expected to attend the conference to present their work. The instructions for submission and the author kit are available here: http://ecsqaru.idsia.ch/submissions-ecsqaru/ ::: IMPORTANT DATES ::: - Tuesday, February 21, 2017: Paper submission deadline - Tuesday, April 18, 2017: Author notification - Friday, April 28, 2017: Camera-ready copy due ::: IJAR SPECIAL ISSUE ::: Authors of selected papers will be invited to submit an extended version of their work to a special issue of the International Journal of Approximate Reasoning (IJAR, Elsevier). ::: SPRINGER YOUNG RESEARCHER AWARD ::: We also invite applications for the Springer Young Researcher Award. The prize, granted by Springer, will be awarded to one young researcher for excellent research in fields related to the ECSQARU scope. The award is open to Master students, PhD students and young post-doc researchers who have received their PhD in 2016 (or 2017). Applicants should have submitted a paper (not necessarily as first authors) to ECSQARU 2017. Applications should be received by the paper submission deadline (February 21, 2017). _________________________________ Alessandro Antonucci IDSIA Dalle Molle Institute for Artificial Intelligence Via Cantonale (Galleria 2) CH-6928, Manno-Lugano, CH mail: alessandro(a)idsia.ch skype: alessandro.antonucci tel: +41 916108515 web: www.idsia.ch/~alessandro _________________________________

Nov. 17, 2016

[ICANN 2017] Preliminary announcement, 26th International Conference on Artificial Neural Networks, Alghero, Sardinia, Italy

by ENNS Secretary

Preliminary Announcement [Apologies for cross-postings] =========================================================== www.icann2017.org <http://www.icann2017.org/> ICANN 2017 26th International Conference on Artificial Neural Networks Alghero/Sassari, Sardinia, Italy 11th - 15th September 2017 =========================================================== The International Conference on Artificial Neural Networks (ICANN) is the annual flagship conference of the European Neural Network Society (ENNS). In 2017, the 26th ICANN will be organised from the 11th to the 15th of September 2017 in Alghero/Sassari, Sardinia, Italy. Conference proceedings will be published in Springer-Verlag Lecture Notes in Computer Science (LNCS) series. IMPORTANT DATES Special session / workshop proposals: 15 January 2017 Proposals for competitions and tutorials: 31 January 2017 Submission of demonstration proposals: 1 March 2017 Submission of abstracts and papers: 19 March 2017 Notification of acceptance: 30 April 2017 Camera-ready paper and registration: 15 May 2017 Conference dates: 11 - 15 September 2017 CONFERENCE TOPICS ICANN 2017 will feature the main tracks Brain Inspired computing and Machine Learning research, with strong cross-disciplinary interactions and applications. All research fields dealing with Neural Networks will be present at the conference. A non-exhaustive list of topics includes: • Brain Inspired Computing: Cognitive models, Computational Neuroscience, Self-organization, Reinforcement Learning, Neural Control and Planning, Hybrid Neural-Symbolic Architectures, Neural Dynamics, Recurrent Networks, Deep Learning. • Machine Learning: Neural Network Theory, Neural Network Models, Graphical Models, Bayesian Networks, Kernel Methods, Generative Models, Information Theoretic Learning, Reinforcement Learning, Relational Learning, Dynamical Models. • Neural Applications for: Intelligent Robotics, Neurorobotics, Language Processing, Image Processing, Sensor Fusion, Pattern Recognition, Data Mining, Neural Agents, Brain-Computer Interaction, Neural Hardware, Evolutionary Neural Networks. CONFERENCE OBJECTIVES - To bring together researchers from two worlds: Information Sciences and Neurosciences - To keep a wide scope, ranging from Machine Learning Algorithms to models of real nervous systems - To facilitate discussions and interactions in the effort towards developing more intelligent computational systems and increasing our understanding of neural and cognitive processes in the brain. - To help researchers to meet, mingle and network with colleagues from all over the world. - To be the meeting point between research and business. - To be a global interdisciplinary meeting encompassing Machine Learning and Neural Computation. BENEFITS OF ATTENDING THE CONFERENCE - A solid cutting-edge scientific programme including talks from the world experts in the field of artificial neural networks. - A conference schedule tailored to encourage interaction between the attendees, with time for networking and discussion. - The publication of all accepted contributions in the peer-reviewed book of conference proceedings, in the Springer-Verlag Lecture Notes in Computer Science (LNCS) series. - The opportunity to vote and to be considered for the best paper awards, presented during the final ceremony of ICANN. - A top-level conference in the field with a reasonable registration fee, thanks to the not-for-profit policy of the ENNS organisation. Students can apply for ENNS funded travel grants to attend. - An overly attractive conference location in the beautiful setting of the Sardinian coast, with social events to explore the area. http://www.alghero-turismo.it/en/ <http://www.alghero-turismo.it/en/> CONFERENCE REGISTRATION FEES Early registration fees have been kept particularly low for this kind of event because ENNS and ICANN aim at full implementation of the academic not-for-profit policy. Undergraduate students (Bachelor and Master level): 100 EUR PhD Students: 240 EUR Regular delegates: 290 EUR ENNS members have a reduction of 40 EUR Students can apply for ENNS funded travel grants to attend (see the conference website). CALL FOR CONTRIBUTED SCIENTIFIC COMMUNICATIONS All scientific communications presented at ICANN 2017 will be reviewed and scientifically evaluated by a panel of experts. The conference will feature three categories of communications: - oral communications (15'+5') - poster communications (on permanent display and 2 hours presentation) - demonstrations Authors willing to present original contributions for any category must submit a manuscript of maximum 8 pages length that will be refereed to international standards by at least three referees. Accepted papers of contributing authors will be published in Springer-Verlag Lecture Notes in Computer Science (LNCS) series. Selected papers will be invited after the conference for a full journal paper submission. Authors willing to present a contribution for oral communications and posters without submitting a full manuscript must submit a 1-page abstract that will also be refereed by at least three referees. The abstracts will be published all together in a proceedings section without an author index. In case of program constraints the priority will be given to original contributions accompanied by a full paper submission. WORKSHOPS, SPECIAL SESSIONS, DEMONSTRATIONS, COMPETITION PROPOSALS and TUTORIALS ICANN 2017 invites proposals for workshops, special sessions, demonstrations, competitions and tutorials to be held during the conference. For more information, please refer to the website. BEST PAPER AWARDS ENNS will sponsor several best paper awards, in the Brain Inspired Computing track and in the Machine Learning research track. All awardees will be presented during the final ceremony. ORGANISATION General Chair: Alessandro E.P. Villa General Co-chairs: Alessandra Lintas, Věra Kůrková, Stefano Rovetta, Paul F.M.J. Verschure Local Co-chairs: Eugenio Lintas, Anna Mura Program and Workshop Committee: Cesare Alippi, Jérémie Cabessa, Barbara Hammer, Petia Koprinkova-Hristova, Jaako Peltonen, Antonio J. Pons, Yifat Prut, Stefano Rovetta, Igor V. Tetko, Paul F.M.J. Verschure, Alessandro E.P. Villa, Francisco Zamora-Martinéz Communications Chair: Paolo Masulli Organisation Università degli Studi di Sassari, Italy University of Lausanne, Switzerland Universitat Pompeu Fabra, Spain ENNS Secretariat, Switzerland -- Caroline Kleinheny secretary ENNS University of Lausanne Laboratoire de Neuroheuristique Internef - 137 CH - 1015 Lausanne Switzerland Tel : +41 21 692 33 88 secretary(a)e-nns.org <mailto:secretary@e-nns.org>--

Nov. 17, 2016

Grants for independent young scientists - Romanian Institute of Science and Technology

by R. Valentin Florian

Nov. 16, 2016

[IJCNN 2017] Submission deadline is extended to Thursday, 1st December 2359 hr (UTC-8 hr)

by Teng Teck Hou

[Apologies for cross-postings] ################################################## CALL FOR PAPERS International Joint Conference on Neural Networks May 14-19, 2017, Anchorage, Alaska, USA http://www.ijcnn.org/ http://www.ijcnn.org/call-for-papers ################################################## IJCNN is the premier international conference in the area of neural network theory, analysis, and applications. Co-sponsored by the International Neural Network Society (INNS) and the IEEE Computational Intelligence Society (IEEE-CIS), over the last three decades this conference and its predecessors has hosted [past, present, and future] leaders of neural network research. IJCNN 2017 will feature invited plenary talks by world-renowned speakers in the areas of neural network theory and applications, computational neuroscience, robotics, and distributed intelligence. In addition to regular technical sessions with oral and poster presentations, the conference program will include special sessions, competitions, tutorials and workshops on topics of current interest. The 2017 International Joint Conference on Neural Networks (IJCNN 2017) will be held at the William A. Egan Civic and Convention Center in Anchorage, Alaska, USA, May 14-19, 2017. "... Only in Anchorage can you meet a moose, walk on a glacier and explore a vast, natural park all in a single day. Between mountains and an inlet, surrounded by national parks and filled with Alaska wildlife, Anchorage combines the best of Alaska in a city that has the comforts of home and the hospitality of the Last Frontier. ..." For the latest updates, follow us on Facebook (https://fb.me/ijcnn2017/) and Twitter (@ijcnn2017). ##############################Important Dates############################## * Paper Submission December 1, 2016 * Paper Decision Notification January 20, 2017 * Camera-Ready Submission February 20, 2017 ########################################################################### ##########################Plenary Speakers########################## * Alex Graves, Research Scientist, Google DeepMind * Stephen Grossberg, Wang Professor of Cognitive and Neural Systems, Boston University, USA * Odest Chadwicke Jenkins, Associate Professor of Computer Science and Engineering, University of Michigan * Christof Koch, President and Chief Scientific Officer, Allen Institute for Brain Science, USA * Jose C. Principle, Distinguished Professor, University of Florida, USA * Hava Siegelmann, Program Manager, DARPA * Paul Werbos, Program Director (retired), National Science Foundation #################################################################### ##########################Accepted Special Sessions########################## 1 Advanced Data Analytics for Large-scale Complex Data Environment Jia, Wu (University of Technology Sydney); Shirui, Pan; Xiangnan, Kong; Ivor W., Tsang 2 Advances in Computational Intelligence for applied Time Series Forecasting (ACIATSF) Rodriguez Rivero (Universidad Nacional de Crdoba, Argentina), Cristian; Leonardo, Franco; Julian, Pucheta; Juarez, Gustavo 3 Artificial Neural Network Solutions in Power Plant Safety and Security Alamaniotis, Miltos (Purdue University, USA); Tambouratzis, Tatiana 4 Artificial Neural Network-Based Methodologies for Environmental Sustainability Development: Theory and Practice Souliou, Dora (National Technical University of Athens, Greece);Tambouratzis, Tatiana 5 Biologically Inspired Computational Vision Iftekharuddin, Khan (Old Dominion Univ., USA) 6 Biologically-inspired Neural Networks and Learning Systems for Robotics Luo, Chaomin (Univ. of Detroit City, USA) 7 Cognition and Development Alessandro Di Nuovo (Sheffield Hallam Univ., UK); Pierre-Yves Oudeyer; Angelo Cangelosi 8 Computational Intelligence Algorithms for Digital Audio Applications Principi, Emanuele (Universita Politecnica delle Marche, Italy); Uncini, Aurelio; Schuller, Björn; Squartini, Stefano 9 Concept Drift, Domain Adaptation & Learning in Dynamic Environments Giacomo, Boracchi (Politecnico de Milano, Italy); Robi, Polikar; Manuel, Roveri; regory Ditzler 10 Cybersecurity Analytics Catherine Huang (Intel) 11 Data Mining and Knowledge Discovery in Cyber-Physical Systems Bo, Tang (Hofstra Univ. USA); Ozawa, Seiichi; Alippi, Cerase; He, Haibo 12 Data stream mining in industry Xu, Rui (General Electric); Xu, YunWen; Yan, Weizhong 13 Deep and Reinforcement Learning (DRL) Altahhan, Abdulrahman (Coventry Univ., UK); Palade, Vasile; Razavi-Far, Roozbeh; 14 Explainability of Learning Machines Guyon, Isabelle (Universit Paris-Saclay, France); Escalante, Hugo Jair; Escalera, Sergio; Viegas, Evelyne 15 Extreme Learning Machines (ELM) Huang, Guang-Bin (Nanyang Technological Univ., Singapore); Cambria, Erik; Weizhong, Yan; Wunsch II, Donald C. 16 Incremental Machine Learning: Methods and Applications Nicoleta Rogovschi (Paris Descartes Univ., France); Seiichi Ozawa (Kobe University, Japan) 17 Intelligent Vehicle and Transportation Systems Murphey, Yi (Univ. of Michigan-Dearborn, USA); Abou-Nasr, Mahmoud; Sethi, Ishwar K; Robert, Karlsen; Ahmadi , Majid; Luo, Chaomin; Dauwels, Justin; Kocchar, Dev; 18 Interpretable Models in Machine Learning for Advanced Data Analysis Biehl, Michael (Univ. of Groningen, Netherlands); Villmann, Thomas 19 Large Datasets and Big Data Analytics: Theory, Methods, and Applications Oneto, Luca (University of Genoa, Italy); Navarin, Nicolo?; Donini, Michele; Aiolli, Fabio; Anguita Davide 20 Machine Learning for Business Analytics Sung, Chul (IBM); Higgins, Chunhui; Zhang Bo; Park, Chanjin 21 Machine Learning for Enhancing Biomedical Data Analysis Martin-Guerrero, Jose D. (Univ. of Valencia, Spain); Lisboa, Paulo J. G.; Vellido, Alfredo; Taktak, Azzam F. G.; Peterson, Leif E. 22 Machine Learning Methods Applied to Medicine Bolon-Canedo, Veronica (Univ. of A Corua, Spain); Remeseiro, Beatriz; Alonso-Betanzos, Amparo; Campilho, Aurelio 23 Machine Learning Methods applied to Vision and Robotics (MLMVR) Garcia-Rodriguez, Jose (Univ. of Alicante, Spain); Escalera, Sergio; Psarrou, Alexandra;Guyo, Isabel; Lewis, Andrew; Leitner, Juxi; Dominguez, Enrique 24 Machine Learning Techniques for Data-Driven Cyber Security Hongmei He (Cranfield Univ., UK) 25 Mind, Brain, and Cognitive Algorithms Perlovsky, Leonid (Northeastern Univ., USA); Fontanari, Jose F.; Roy, Asim; Cangelosi, Angelo; Levine, Daniel 26 Nature-Inspired Neural Network Optimization Bosman (Rakitianskaia), Anna (Univ. of Pretoria, South Africa); Engelbrecht, Andries 27 Neuro-Inspired Computing with Nanoelectronic Devices Saibal Mukhopadhyay (Georgia Tech, USA); Kaushik Roy 28 Neural Network Transfer Learning for the Recognition of Human Behavior and Affect Schwenker, Friedhelm (Univ. of Ulm, Germany); Scherer, Stefan; 29 Online Real-Time Strategies for Data Stream Mining Mahardhika Pratama (La Trobe University, Australia), Plamen P. Angelov, Meng Joo Er, Edwin Lughofer 30 Optimizing Neural Networks via Evolutionary Computation and Swarm Intelligence Wei-Chang Yeh (National Tsing Hua Univ. Taiwan), Yew-Soon Ong 31 Probabilistic Models and Kernel Methods Sun, Shiliang (East China Normal Univ. China); Ding, Shifei; Liu, Huawen; Wang, Wenjian; Yang, Xiaowei; Zhang, Li; Zhao, Jing 32 Reservoir Computing in Hardware Merkel, Cory (Airforce Research Laboratory, USA); McDonald, Nathan; Thiem, Clare; Wysocki, Bryant 33 Smart Educational Techniques in Big Data Age Guandong Xu (Univ. Technology Sydney, Australia), Gang Li, and Wu He ############################################################################ # ############Paper Submission and Publication############ * Regular paper can have up to 8 pages in double-column IEEE Conference format * All papers are to be prepared using IEEE-compliant Latex or Word templates on paper of U.S. letter size. * All submitted papers will be checked for plagiarism through the IEEE CrossCheck system. * Papers with significant overlap with the authors own papers or other papers will be rejected without review. ######################################################## ##################Topics and Areas of Interest################## This conference solicits papers addressing original works in topics and areas of interest including, but are not limited to: NEURAL NETWORK MODELS * Feedforward neural networks * Recurrent neural networks * Self-organizing maps * Radial basis function networks * Attractor neural networks and associative memory * Modular networks * Fuzzy neural networks * Spiking neural networks * Reservoir networks (echo-state networks, liquid-state machines, etc.) * Large-scale neural networks * Other topics in artificial neural networks MACHINE LEARNING * Supervised learning * Unsupervised learning and clustering, (including PCA, and ICA) * Reinforcement learning * Probabilistic and information-theoretic methods * Support vector machines and kernel methods * EM algorithms * Mixture models, ensemble learning, and other meta-learning or committee algorithms * Bayesian, belief, causal, and semantic networks * Statistical and pattern recognition algorithms * Visualization of data * Feature selection, extraction, and aggregation * Evolutionary learning * Hybrid learning methods * Computational power of neural networks * Deep learning * Other topics in machine learning NEURODYNAMICS * Dynamical models of spiking neurons * Synchronization and temporal correlation in neural networks * Dynamics of neural systems * Chaotic neural networks * Dynamics of analog networks * Neural oscillators and oscillator networks * Dynamics of attractor networks * Other topics in neurodynamics COMPUTATIONAL NEUROSCIENCE * Connectomics * Models of large-scale networks in the nervous system * Models of neurons and local circuits * Models of synaptic learning and synaptic dynamics * Models of neuromodulation * Brain imaging * Analysis of neurophysiological and neuroanatomical data * Cognitive neuroscience * Models of neural development * Models of neurochemical processes * Neuroinformatics * Other topics in computational neuroscience NEURAL MODELS OF PERCEPTION, COGNITION AND ACTION * Neurocognitive networks * Cognitive architectures * Models of conditioning, reward and behavior * Cognitive models of decision-making * Embodied cognition * Cognitive agents * Multi-agent models of group cognition * Developmental and evolutionary models of cognition * Visual system * Auditory system * Olfactory system * Other sensory systems * Attention * Learning and memory * Spatial cognition, representation and navigation * Semantic cognition and language * Neural models of symbolic processing * Reasoning and problem-solving * Working memory and cognitive control * Emotion and motivation * Motor control and action * Dynamical models of coordination and behavior * Consciousness and awareness * Models of sleep and diurnal rhythms * Mental disorders * Other topics in neural models of perception, cognition and action NEUROENGINEERING * Brain-machine interfaces * Neural prostheses * Neuromorphic hardware * Embedded neural systems * Other topics in neuroengineering BIO-INSPIRED AND BIOMORPHIC SYSTEMS * Brain-inspired cognitive architectures * Embodied robotics * Evolutionary robotics * Developmental robotics * Computational models of development * Collective intelligence * Swarms * Autonomous complex systems * Self-configuring systems * Self-healing systems * Self-aware systems * Emotional computation * Artificial life * Other topics in bio-inspired and biomorphic systems APPLICATIONS * Bioinformatics * Biomedical engineering * Data analysis and pattern recognition * Speech recognition and speech production * Robotics * Neurocontrol * Approximate dynamic programming, adaptive critics, and Markov decision processes * Neural network approaches to optimization * Signal processing, image processing, and multi-media * Temporal data analysis, prediction, and forecasting; time series analysis * Communications and computer networks * Data mining and knowledge discovery * Power system applications * Financial engineering applications * Applications in multi-agent systems and social computing * Manufacturing and industrial applications * Expert systems * Clinical applications * Big data applications * Smart grid applications * Other applications CROSS-DISCIPLINARY TOPICS * Hybrid intelligent systems * Swarm intelligence * Sensor networks * Quantum computation * Computational biology * Molecular and DNA computation * Computation in tissues and cells * Artificial immune systems * Other cross-disciplinary topics ################################################################ ##########################Organizing Committee########################## General Chair * Yoonsuck Choe, Texas A and M University, USA Program Chair * Christina Jayne, Robert Gordon University, UK Technical Co-Chairs * Irwin King, The Chinese University of Hong Kong, China * Barbara Hammer, University of Bielefeld, Germany Plenary Chair * Cesare Alippi, Politecnico di Milano, Italy Special Session Co-Chairs * Derong Liu, University of Chicago, USA * Tatiana Tambouriatzis, University of Piraeus, Greece Tutorial Chair * Asim Roy, Arizona State University, USA Workshop Chair * Lazaros Iliadis, Democritus University of Thrace, Greece Poster Session Chair * Richard Duro, Universidad Coruna, Spain Competition Chair * Juyang (John) Weng, Michigan State University, USA Panels Chair * Robert Kozma, University of Memphis, USA Awards Chair * Nikola Kasabov, Auckland University of Technology, Australia Web Reviews Chair * Tomasz Cholewo, Lexmark International Inc., USA Sponsors & Exhibits Chair * Lipo Wang, Nanyang Technological University, Singapore Publication Chair * Bill Howell, Natural Resources Canada (retired), Canada International Liaison * Teresa Ludermir, Universidade Federal de Pernambuco, Brazil European Liaison * Danilo P. Mandic, Imperial College, UK Asia-Pacific Liaison * Minho Lee, Kyungpook National University, Korea Neuroscience Liaison * Péter Érdi, Kalamazoo College, USA Robotics Liaison * Pierre-Yves Oudeyer, INRIA, France Industry Liaison * Sven F. Crone, Lancaster University, UK Publicity Co-Chairs * Giacomo Boracchi, Politecnico di Milano, Italy * Simone Scardapane, Sapienza University, Italy * Teck-Hou Teng, Singapore Management University, Singapore Local Arrangements Co-Chairs * Frank W. Moore, University of Alaska, USA * Kenrick Mock, University of Alaska, USA Registration Chair * Jaerock Kwon, Kettering University, USA Webmaster * Jaewook Yoo, Texas A & M University, USA ####################################################################### ##################Sponsoring Organizations################## * INNS - International Neural Network Society * IEEE - Computational Intelligence Society * BSCS - Budapest Semester in Cognitive Science * BMI - Brain-Mind Institute ############################################################

Nov. 16, 2016