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

Creating a list of important computational predictions
by Yiota Poirazi 04 Jan '21

04 Jan '21

Dear all, I believe you would agree that, the greatest recognition of our computational work comes with the experimental verification of our computational predictions. To highlight the most important outcomes of our theoretical work and facilitate a closer interaction with experimental labs so as to increase the chances of our predictions being experimentally tested, I would like to encourage you to nominate your favorite prediction at the following google form: https://docs.google.com/forms/d/e/1FAIpQLSeJZ2RrXJ0nZonIuyNzN0Cl gXDKDb7xTzoJOiqZTGxm9Kh7ow/viewform?c=0&w=1&usp=mail_form_link This effort started during the CNS 2017 meeting in Antwerp with the support of the OCNS Board. The resulting list will be posted on the CNS 2017 web site and disseminated in social media, as a reference for experimentalists. Thank you very much for supporting this important effort! Best wishes, Yiota Poirazi -- Panayiota Poirazi, Ph.D. Research Director Computational Biology Laboratory Institute of Molecular Biology and Biotechnology (IMBB) Foundation of Research and Technology-Hellas (FORTH) Vassilika Vouton, P.O.Box 1385, GR 70013, Heraklion, Crete GREECE Tel: +30 2810 391139 Fax: +30 2810 391101 Εmail: poirazi(a)imbb.forth.gr Lab site: www.dendrites.gr FENS-Kavli Network of Excellence <http://www.fens.org/Outreach/FENS-Kavli-Network-of-Excellence/> -- This message has been scanned for viruses and dangerous content by *E.F.A. Project* <http://www.efa-project.org>, and is believed to be clean. Click here to report this message as spam. <http://mailgate1.imbb.forth.gr/cgi-bin/learn-msg.cgi?id=4BCD7A00A1.A57D7&to…> -- Panayiota Poirazi, Ph.D. Research Director Computational Biology Laboratory Institute of Molecular Biology and Biotechnology (IMBB) Foundation of Research and Technology-Hellas (FORTH) Vassilika Vouton, P.O.Box 1385, GR 70013, Heraklion, Crete GREECE Tel: +30 2810 391139 Fax: +30 2810 391101 Εmail: poirazi(a)imbb.forth.gr Lab site: www.dendrites.gr FENS-Kavli Network of Excellence <http://www.fens.org/Outreach/FENS-Kavli-Network-of-Excellence/>

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Professorship in Artificial Intelligence
by Steuber, Volker 08 May '19

08 May '19

Professor of Artificial Intelligence University of Hertfordshire, UK School of Computer Science, College Lane Campus, Hatfield Salary £58,293 to £64,397 pa dependent on skills and experience FTE: Full time position working 37 hours per week (1.0FTE) Duration of Contract: Permanent position Closing date: 3 September 2018 Applications are invited for an exceptionally well qualified Professor of Artificial Intelligence of international standing who shares our commitment to research-informed teaching, embraces the research impact agenda, and values collegiality. Applicants will strengthen existing activity within the School and develop it further, enhancing the research strengths and external reputation of the School of Computer Science and contributing significantly to its performance in future research assessments and collaborations with public and commercial partners. The successful applicant will connect to and complement the research conducted by the Adaptive Systems Research Group within the Centre for Computer Science and Informatics Research. The School hosts the University of Hertfordshire Robot House, a facility ubiquitously equipped with low-cost sensors providing a realistic environment for experiments with robotics in a smart home; a fully-fledged RoboCup lab for development of humanoid robots participating in international competitions, and a large variety of different robotic platforms, including iCub and Baxter. We encourage applications from researchers across a wide spectrum of AI, and particularly encourage applications from researchers working on emerging topics in AI. Possible fields include, but are not limited to: • Machine learning: reinforcement learning, Deep Methods, statistical methods, large scale data modelling/intelligent processing and high-performance learning algorithms • Robotics: embodied and/or cognitive robotics, HRI, robot safety, emotional/social robots, smart homes and sensors, sensor fusion, assistive robotics • Complex Systems: collective intelligence, adaptive, autonomous and multi-agent/robot systems, collective and swarm intelligence, social and market modelling, adaptive, evolutionary and unconventional computation • Mathematical Modelling: statistical modelling, information-theoretic methods, compressive sensing, intelligent data visualization, multiscale models, optimization • Emerging Topics in AI: computer algebra and AI, topological methods (e.g. persistent homology), modern topics in games and AI • AI and applications: financial modelling, AI and biology/physics/cognitive sciences • Foundations: fundamental questions of intelligence and computation, emergence of life/intelligence, Artificial Life As well as providing research supervision at PhD and MSc level, the School of Computer Science offers modules in Artificial Intelligence, machine learning, neural and evolutionary computing, as well as Artificial Life on the BSc and MSc programmes. Applicants will be committed to a strong research and research-informed teaching agenda, and will actively contribute to increase research impact of the School, in the enthusiastic, welcoming and collegiate environment of the school. Applicants must hold a PhD (or equivalent) in a relevant subject, possess excellent communication skills in English, an internationally excellent research record and reputation, including publications of the highest quality suitable for submission to the REF (UK Research Excellence Framework). Applicants are expected to show evidence of experience and success in research/commercial income generation, engagement with the research impact agenda, engagement with key stakeholders in the relevant Artificial Intelligence community and management and leadership ability. The professor will have opportunity to contribute actively to interdisciplinary research projects at the school and university level. Applications must be made online https://www.herts.ac.uk/contact-us/jobs-and-vacancies/academic-vacancies?, reference 016194?. Informal enquiries may be addressed to Dr Volker Steuber (Associate Dean Research, v.steuber(a)herts.ac.uk) or Professor William Clocksin (Dean of School, w.clocksin(a)herts.ac.uk) Please note that applications sent directly by email will not be accepted.

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Postdoctoral positions in computational neuroscience and artificial intelligence
by Maxim Bazhenov 01 Mar '19

01 Mar '19

Applications are invited for post-doctoral research positions in the laboratory of Dr. Maxim Bazhenov at the University of California, San Diego to study memory and learning and to develop neuroscience inspired computer algorithms capable of continual learning and adapting to the novel situations and contexts.This project involves close collaboration with the experimental laboratory of Dr. Bruce McNaughton (UC Irvine). The ultimate goal of the work is to advance the knowledge of how human and animal brains learn from experience and apply these principles to the artificial systems to enable continuous learning without catastrophic forgetting. The successful candidate will collaborate with a team of researchers to design neural network models of dynamic interactions between the hippocampus and neocortex during learning and memory consolidation in sleep and awake based on experimental data. These models will be used to derive learning principles that can be combined with advances in artificial intelligence and machine learning. An ideal candidate should have experience in computational/theoretical neuroscience and a basic knowledge of machine learning, or, alternatively, experience in machine learning algorithms and some basic knowledge of neuroscience. Experience with hierarchical learning, reinforcement learning, and/or goal-directed decision-making would be particularly helpful. The University of California offers excellent benefits. Salary is based on research experience. Applicants should send a brief statement of research interests, a CV and the names of three references to Maxim Bazhenov at mbazhenov(a)ucsd.edu -- Maxim Bazhenov, Ph.D. Professor, Department of Medicine, Neurosciences Graduate Program, UCSD, School of Medicine http://www.bazhlab.ucsd.edu/

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Columbia Workshop on Brain Circuits, Memory and Computation 2018
by Aurel A. Lazar 16 Dec '18

16 Dec '18

Columbia Workshop on Brain Circuits, Memory and Computation 2018 <http://www.bionet.ee.columbia.edu/workshops/bcmc/2018> BCMC 2018 March 15-16, 2018 Center for Neural Engineering and Computation <http://cnec.columbia.edu/> Columbia University, New York, NY, USA Overview The goal of the workshop is to bring together researchers interested in developing executable models of neural computation/processing of the brain of model organisms. Of interest are models of computation that consist of elementary units of processing using brain circuits and memory elements. Elementary units of computation/processing include population encoding/decoding circuits with biophysically-grounded neuron models, non-linear dendritic processors for motion detection/direction selectivity, spike processing and pattern recognition neural circuits, movement control and decision-making circuits, etc. Memory units include models of spatio-temporal memory circuits, circuit models for memory access and storage, etc. A major aim of the workshop is to explore the integration of various sensory and control circuits in higher brain centers. A Fruit Fly Brain Hackathon <http://www.bionet.ee.columbia.edu/hackathons/ffbh/2018> is being conducted in conjunction with the workshop. Workshop participants are welcome to attend the hackathon. Registration Registration is free but all participants have to register <https://bcmc2018.eventbrite.com/>. Thank you! Organizer and Program Chair Aurel A. Lazar <http://www.ee.columbia.edu/~aurel>, Department of Electrical Engineering, Columbia University. Program Overview (Confirmed Speakers) Misha B. Ahrens <https://www.janelia.org/lab/ahrens-lab>, Janelia Research Campus, Ashburn, VA. Davi Bock <https://www.janelia.org/lab/bock-lab>, Janelia Research Campus, Ashburn, VA. Claude Desplan <https://wp.nyu.edu/desplanlab/>, Department of Biology, New York University. Mark A. Frye <http://www.fryelab.net/>, Department of Integrative Biology and Physiology, University of California, Los Angeles. C. Giovanni Galizia <http://neuro.uni-konstanz.de/03team/content/galizia.html>, Department of Biology, University of Konstanz. Maria N. Geffen <https://geffenlab.weebly.com/maria.html>, Department of Otorhinolaryngology and Department of Neuroscience, University of Pennsylvania. Hokto Kazama <http://kazama.brain.riken.jp/index.php>, Riken Brain Science Institute, Tokyo. Donggen Luo <http://mgv.pku.edu.cn/?co=posts&ac=faculty&catalog=enpiintro&pname=en_Dongg…>, McGovern Institute for Brain Research, Peking University, Beijing. Thomas Nowotny <http://www.sussex.ac.uk/profiles/206151>, Department of Informatics, University of Sussex. Pavan Ramdya <https://ramdya-lab.epfl.ch/home>, Brain Mind Institute, EPFL, Lausanne. Aravinthan D.T. Samuel <https://scholar.harvard.edu/aravisamuel/home>, Department of Physics and center for Brain Science, Harvard University. Simon G. Sprecher <http://www.sprecherlab.com/simon-sprecher/>, Department of Biology, University of Fribourg. Seth Tomchik <http://www.scripps.edu/tomchik/>, The Scripps Research Institute Florida. Joshua T. Vogelstein <http://jovo.me/>, Dept. of Biomedical Engineering and Institute for Computational Medicine, Johns Hopkins University. Scott Waddell <https://www.dpag.ox.ac.uk/research/waddell-group>, Department of Physiology, Anatomy and Genetics, University of Oxford. Anthony M. Zador <http://zadorlab.cshl.edu/>, Cold Spring Harbor Laboratory. Aurel http://www.bionet.ee.columbia.edu

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CFP: FLAIRS 2017, Marco Island, FL,
by bisant＠umbc.edu 18 Oct '18

18 Oct '18

CALL FOR PAPERS FLAIRS 2017, Florida Artificial Intelligence Research Symposium Special Tracks on Data mining and Special Track on Cyber Security Marco Island, Florida http://www.flairs-30.info/ Paper submission deadline: November 21, 2016. Notifications: January 23, 2017. Camera ready version due: February 27, 2017. FLAIRS is an interdisciplinary artificial intelligence conference which especially encourages novel ideas and which features a double-blind review process. Data Mining Track This special track will be devoted to data mining with the aim of presenting new and important contributions in this area. Papers and contributions are encouraged for any work related to Data Mining. Topics of interest may include (but are in no way limited to): 1. Applications such as Intelligence analysis, medical and health applications, text, video, and multi-media mining, E-commerce and web data, financial data analysis, cyber security, remote sensing, earth sciences, bioinformatics, and astronomy. 2. Modeling algorithms such as hidden Markov models, decision trees, neural networks, statistical methods, or probabilistic methods; case studies in areas of application, or over different algorithms and approaches. 3. Feature extraction and selection. 4. Post-processing techniques such as visualization, summarization, or trending. 5. Preprocessing and data reduction. 6. Knowledge engineering or warehousing. Papers dealing with Cloud-based unstructured data or Cloud-based tool suites, such as Mahout or Apache Spark, are also encouraged. Cyber-Security Track Original high quality papers are sought for leading edge research and applications relating to the application of AI and Cyber Security. Topics of interest may include but are not limited to: · Machine Learning for Intrusion Detection Systems · NLP for text analysis in Cyber Security · Video and CCTV semantic analysis for terrorist or criminal action detection · AI & Biometrics, Internet of Things, and Cloud Computing security · AI & SCADA systems, Network Systems, and Embedded Systems security · Formal and theoretical approaches of intelligent security in WSNs · Legal and policy issues in intelligent security · Integrity, privacy, authentication and access control · Intelligent secure systems in multimedia databases · Social networks security · Intelligent incident response techniques in network and communication systems · Risk analysis and intelligent management · Virtual Private Networks intelligent security · Automated reasoning techniques of incidents and evidence analysis · Evidentiary aspects of digital forensics · Collaborative intelligent investigation · Intelligent systems in management, storage and reassembly · Steganography, watermarking, and forensic techniques in multimedia content processing · Lightweight security techniques · Intelligent Large-scale investigations and Big Data · Innovative non-repudiation techniques · Intelligent vulnerability analysis and assessment · Attacks tracking · Data hiding, tamper detection and recovery techniques · Security of e- healthcare systems and applications Note: We invite original papers (i.e. work not previously submitted, in submission, or to be submitted to another conference during the reviewing process). Submission Guidelines Interested authors should format their papers according to AAAI formatting guidelines. The papers should be original work (i.e., not submitted, in submission, or submitted to another conference while in review). Papers should not exceed 6 pages (or 4 pages for short paper, to be presented as a poster) and are due by November 21, 2016. For FLAIRS-30, the 2017 conference, the reviewing is a double blind process. Author names and affiliations should be Xd out on submitted papers to provide double-blind reviewing. Papers must be submitted as PDF through the EasyChair conference system, which can be accessed through the main conference web site (http://www.flairs-30.info/) Note: do not use a fake name for your EasyChair login - your EasyChair account information is hidden from reviewers. Authors should indicate which special track they are submitting to. The proceedings of FLAIRS will be published by the AAAI. Authors of accepted papers will be required to sign a form transferring copyright of their contribution to AAAI. FLAIRS requires that there be at least one full author registration per paper.

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Up to 8 PhD fellowships in Cognitive Neuroscience at SISSA, Trieste, Italy
by Alessandro Treves 16 Aug '18

16 Aug '18

SISSA is an elite postgraduate research institution, focused on Maths, Physics and Neuroscience. It operates in English: many among its students and faculty are not Italian. Campus above Trieste, overlooking the Gulf. Research approaches in the CNS PhD https://phdcns.sissa.it/ span the range from cognitive psychology and imaging in humans to behavioural neuroscience and multiple single-unit recording in rats, mathematical and computational modeling; with research groups led by Domenica Bueti, Davide Crepaldi, Mathew Diamond, Chris Mathys, Raffaella Rumiati, Alessandro Treves and Davide Zoccolan. Allied approaches are pursued in other SISSA PhDs. All admitted students receive a 4-year fellowship and engage full-time in research based in Trieste, with limited coursework in the first few months, talks and seminars throughout the year and a TEX event in the summer, see https://indico.sissa.it/event/26/ First deadline for EU candidates: March 2, 2018, for nonEU: March 31, 2018 -- Alessandro Treves http://people.sissa.it/~ale/limbo.html SISSA - Cognitive Neuroscience, via Bonomea 265, 34136 Trieste, Italy +39-040-3787623 Ambassador (BlaBlaCar) +39-349-2504602

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Postdoc position in calcium imaging of Fragile X zebrafish
by Geoffrey Goodhill 01 Jul '18

01 Jul '18

Geoff Goodhill's lab at the University of Queensland is looking for an experimental postdoc to analyse a zebrafish model of Fragile X syndrome using behavioural and calcium imaging approaches. The salary range is AU$81k-87k (US$60-64k). We are particular interested in how neural coding emerges over development in these fish. The project will involve both high-speed video recording of zebrafish larvae behaviour, and large scale 2-photon recording of GCaMP6s neural activity using confocal and light-sheet microscopy. The successful candidate will work closely with an interdisciplinary team with a strong computational focus. A new review paper discussing some of the relevant background is Avitan L & Goodhill GJ (2018). Code Under Construction: Neural Coding Over Development Trends in Neurosciences, online June 20th https://www.cell.com/trends/neurosciences/abstract/S0166-2236(18)30158-9 The University of Queensland (UQ) is ranked in the top 3 universities in Australia and the top 100 in the world. The Goodhill lab is part of the Queensland Brain Institute at UQ, a leading neuroscience institute consisting of over 40 labs, including ~100 PhD students and ~100 postdocs. For more details and to apply please see the following link: http://jobs.uq.edu.au/caw/en/job/504708/postdoctoral-research-fellow The closing date is July 25th AEST. Informal enquiries are also welcome. Professor Geoffrey J Goodhill Queensland Brain Institute and School of Mathematics & Physics University of Queensland St Lucia, QLD 4072, Australia Email: g.goodhill(a)uq.edu.au<mailto:g.goodhill@uq.edu.au> http://www.qbi.uq.edu.au/professor-geoffrey-goodhill

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PhD and post-doctoral positions in Electrophysiology / Brain-machine interface at the Université de Sherbrooke, Canada
by Jean Rouat 29 Jun '18

29 Jun '18

Dear list, We have PhD and one post-doctoral positions in our research group. Please communicate with my colleague Eric Plourde for further details. 1) PhD positions in Electrophysiology / Brain-machine interface at the Université de Sherbrooke, Canada (co-supervision at the University of Minnesota, USA) for IC implants Auditory implants aim at restoring audition by stimulating a specific structure of the auditory system with an electrode array. The most successful auditory implant, the cochlear implant that stimulates the spiral ganglions in the cochlea, has allowed more than 325 000 people worldwide to regain audition. However, cochlear implants are not appropriate for patients that have a disfunctionnal auditory nerve or for which the cochlea cannot be implanted. Alternative implants have therefore been developed such as the auditory midbrain implant (AMI) that stimulates a structure named the inferior colliculus (IC). One aspect that limits the development of the AMI is the lack of knowledge regarding the optimal approach to stimulate the IC. The proposed project aims at gaining more insight into the optimal design of stimulation patterns for the IC. Objectives: Design optimal inferior colliculus stimulation patterns using adaptive filters specifically adapted for neural signals: the neural activity will be recorded in the auditory cortex and optimal stimulation in the inferior colliculus will be evaluated using a closed-loop approach. A financial support will be provided. Requirements: - Excellent academic record. - Master’s degree in biomedical engineering, electrical engineering, computer engineering, physics, biophysics or other related field with a strong background in mathematics and signal processing. - Willing to conduct experiments in electrophysiology to record the neural activity of the auditory system. No prior knowledge in electrophysiology is required. - Excellent ability to communicate in English, knowledge of French is considered an advantage. Interested candidates should send their CV, academic transcripts and relevant publications as well as the names of 2 references to Prof. Eric Plourde. Contact: Eric Plourde, Eng., Ph.D., Université de Sherbrooke (eric.plourde(a)usherbrooke.ca) 2) Postdoctoral position in statistical signal processing / Brain-machine interface at the Université de Sherbrooke A retinal prosthesis aims at giving back vision to blind people. To do so, an external camera captures visual scenes and sends this information to an electrode array, which is positioned in the eye, in order to stimulate directly the retina. The electric pulses from the electrodes are sent to the brain along the optic nerve and interpreted as sight. The objective of this study is to decode a perceived image using Bayesian decoding approaches. Many types of patterns can be used to stimulate the different electrodes comprising the array and not all are efficient. The research proposal aims at simulating a perceived image using an adapted stimulation approach and Bayesian decoding and comparing it with an image obtained with traditional stimulation approaches. The contract is for a 6-months period. Requirements: - Ph.D. degree in statistical signal processing, biomedical engineering, bio-informatics or other related field - Proven publication record - Excellent ability to communicate in English. Interested candidates should send their CV, academic transcripts and relevant publications as well as the names of 2 references to Prof. Eric Plourde. Contact: Eric Plourde, Eng., Ph.D., Université de Sherbrooke (eric.plourde(a)usherbrooke.ca) ==================================================== The Université de Sherbrooke is a French-speaking institution located in the province of Quebec, Canada, and the heart of an international research pole. It is host to more than 40 000 students from over 120 different countries worldwide. (Source: UdeS) ==================================================== Jean Rouat, Prof., coord. IGLU, http://iglu-chistera.github.io Université de Sherbrooke Université de Montréal Member of the centre for Interdisciplinary research Professeur titulaire, Professeur associé in Music Media and Technology NECOTIS: Computational Neurosciences Vision, neuroscience Lab McGill Schulich School of Music and Intelligent Signal Processing FAS- Sciences biologiques 527 Sherbrooke St. West Faculté de génie, GEGI, C1-3108 90 avenue Vincent-d’Indy Montreal, Qc, 2500 boul. de l'université Montréal, Qc, Canada, H3A 1E3 Sherbrooke, Québec Canada, H3C 3J7 Canada, J1K 2R1 Tél.: +1(819)-821-8000 ext. 63864 http://www.gel.usherbrooke.ca/rouat http://www.gel.usherbrooke.ca/necotis http://www.usherbrooke.ca/gelecinfo/fr/pers/profs/rouj-fr/ Jean.Rouat(a)umontreal.ca ou Jean.Rouat(a)usherbrooke.ca Publications: https://www.gel.usherbrooke.ca/rouat/publications/publiDeJRouat.html

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PhD opening in Machine learning for Neural Encoding of Naturalistic Auditory Scenes
by Nicolas Farrugia 29 Jun '18

29 Jun '18

Dear list, We invite applications for a fully-funded PhD between Université de Montréal, computer science department, and IMT Atlantique, Brest, France. The goal is to model the perception of complex natural auditory stimuli using signals on dynamic brain graphs, and deep learning. Details are here : https://t.co/963vd9Pizg and below Deadline for application is July 15th. The project aims to model natural auditory perception using artificial neural networks and graph signal processing, applied to human functional magnetic resonance imaging (fMRI) and electroencephalograph (EEG) data. Recent advances in artificial intelligence are largely due to the outstanding performance obtained by deep neural networks on the classification of composite natural stimuli. Deep learning however still faces important challenges with natural auditory perception [1], in particular in complex, noisy scenes involving several simultaneous sources. This thesis will use human neuroimaging data to improve the ability of artificial networks to classify natural auditory stimuli. Recent works have demonstrated the feasibility of building artificial models to link computational musical features with brain activity [2]. Such models perform as well as human listeners on both music, and simple speech discrimination tasks [3]. The internal layers of the deep networks have also been used to predict brain activity related to natural sounds, by modeling each individual voxel of fMRI activity using combinations of feature maps [3]. We propose to investigate extensions of the current approaches to consider graph convolutional networks [4], signal processing on graphs [5], and to model temporal signals on dynamic graphs [6]. We will build a series of artificial models, using extensive recordings of EEG/fMRI brain activity acquired from participants performing auditory tasks of increasing complexity. This PhD project is a collaboration between the laboratories of Dr. Nicolas Farrugia and Dr Vincent Gripon (Brain Inspired Artificial Intelligence Project, at IMT Atlantique, Brest, France), and the lab of Dr. Pierre Bellec (NeuroMod - Courtois Project on Neuronal Modelling - CRIUGM, Department of Computer Science and Operational Research, Université de Montréal, Montréal, Qc, Canada). The candidate will be expected to share their time between Montreal and Brest. IMT Atlantique is a public technological university focusing on the training of engineers at the MSc. level and junior researchers at the PhD level. Université de Montréal is a world-renowned institution, training elite scientist, and is currently one of the main hubs for artificial intelligence and neuroinformatics research in North America.

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The Journal of Mathematical Neuroscience - recent articles
by Stephen Coombes 28 Jun '18

28 Jun '18

The Journal of Mathematical Neuroscience publishes research articles on the mathematical modeling and analysis of all areas of neuroscience. The new Impact Factor of the journal is 2.414 The current list of journal articles is available at http://www.mathematical-neuroscience.com/ : Investigating the Correlation–Firing Rate Relationship in Heterogeneous Recurrent Networks Andrea K. Barreiro and Cheng Ly https://mathematical-neuroscience.springeropen.com/articles/10.1186/s13408-… Effect of Neuromodulation of Short-term Plasticity on Information Processing in Hippocampal Interneuron Synapses Elham Bayat Mokhtari, J. Josh Lawrence and Emily F. Stone https://mathematical-neuroscience.springeropen.com/articles/10.1186/s13408-… Analysis of an Attractor Neural Network’s Response to Conflicting External Inputs Kathryn Hedrick and Kechen Zhang https://mathematical-neuroscience.springeropen.com/articles/10.1186/s13408-… Saddle Slow Manifolds and Canard Orbits in R^4 and Application to the Full Hodgkin–Huxley Model Cris R. Hasan, Bernd Krauskopf and Hinke M. Osinga https://mathematical-neuroscience.springeropen.com/articles/10.1186/s13408-… Kernel Reconstruction for Delayed Neural Field Equations Jehan Alswaihli, Roland Potthast, Ingo Bojak, Douglas Saddy and Axel Hutt https://mathematical-neuroscience.springeropen.com/articles/10.1186/s13408-… All articles are Open Access. ------------------------------------------------------- Stephen Coombes Professor of Applied Mathematics School of Mathematical Sciences Nottingham, UK Tel: 0115 846 7836 http://www.maths.nott.ac.uk/~sc/ ------------------------------------------------------- This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please contact the sender and delete the email and attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. Email communications with the University of Nottingham may be monitored where permitted by law.

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