- Comp-neuro - lists.cnsorg.org

PhD position announcement in computational neuroscience

by Mike X Cohen

Mike X Cohen and Paul Tiesinga are searching for a PhD Candidate to work on a project entitled “Midfrontal Cortex Theta Oscillations: Causes and Consequences”. This project is funded by the European Research Council and is hosted by the Donders Centre for Neuroscience. Theta-band oscillations (~6 Hz) in the medial prefrontal cortex are a signature of several important cognitive functions, including behaviour monitoring, action adjustments and feedback-driven learning. Although this consistent finding has emerged in several species including humans, monkeys, and rats, little is known about the microcircuits in the medial prefrontal cortex that generate theta oscillations and the role of those oscillations in the neural computations underlying cognitive control functions. In this project, we aim to gain more insight into these processes by employing biophysically-informed computational models to simulate the genesis and significance of midfrontal theta for coordinating local and long-range network dynamics. Empirical experiments in humans and rodents may be incorporated into the research in order to test/refine the models. Please see http://www.ru.nl/overons/werken-radboud/details/details_vacature_0/?recid=5… for additional details. -- Mike X Cohen, PhD mikexcohen.com

July 22, 2015

Bernstein Conference: Early registration ends on July 24, 2015

by Seeger, Simone

BERNSTEIN CONFERENCE 2015 in Heidelberg Early registration ends on July 24, 2015! Please register here<https://mi3.lambdalogic.de/forms/Bernstein2015.do>. *************************************************************************** Satellite Workshops<http://www.nncn.de/en/bernstein-conference/2015/satellite-workshops> September 14, 2015 Main Conference<http://www.nncn.de/en/bernstein-conference/2015/program> September 15-17, 2015 *************************************************************************** The Bernstein Conference has become the largest annual Computational Neuroscience Conference in Europe and now regularly attracts more than 500 international participants. This year, the Conference is organized by the Bernstein Center Heidelberg-Mannheim and will take place in Heidelberg on September 15-17, 2015. In addition, there will be a series of pre-conference satellite workshops on September 14, 2015. The Bernstein Conference is a single-track conference, covering all aspects of Computational Neuroscience and Neurotechnology, and sessions for poster presentations are an integral part of the conference. The Bernstein conference will also feature a series of satellite workshops on September 14, 2015. The goal is to provide an informal forum for the discussion of timely research questions and challenges. For more information on the conference, please visit: http://www.bernstein-conference.de<https://mail.zi-mannheim.de/OWA/redir.aspx?C=mYOXLQcyKEWWGs2ITdwALYoLj0aoVt…> CONFERENCE DATE AND VENUE: Satellite Workshops September 14, 2015 Main Conference September 15-17, 2015 Venue: Neue Universität, Grabengasse 3-5, 69117 Heidelberg, Germany PHD STUDENT EVENT: September 17-18, 2015 ORGANIZING COMMITTEE: Peter Bastian Andreas Draguhn Daniel Durstewitz Martin Gerchen Joachim Hass Elke Jochum Peter Kirsch Andreas Meyer-Lindenberg Christoph Schuster Simone Seeger We look forward to seeing you in Heidelberg in September! *** Simone Seeger, M.A. Administration Bernstein Center for Computational Neuroscience Zentralinstitut für Seelische Gesundheit Postfach 12 21 20, 68072 Mannheim J5, 68159 Mannheim Telefon: 0621/1703-1326 oder 06221/54-8310 Fax: 0621/1703-2915 E-Mail: Simone.Seeger(a)zi-mannheim.de<mailto:Simone.Seeger@zi-mannheim.de> Internet: http://www.bccn-heidelberg-mannheim.de<http://www.bccn-heidelberg-mannheim.de/>

July 22, 2015

CFP: ICDM Workshop HealthMining 2015 and HISS Special Issue (Deadline extended: Aug 3, 2015)

by william

[Please accept our apologies if you receive multiple copies of this email] CALL FOR PAPERS (Submission Deadline Extended: >>>Aug 3<<<, 2015) HEALTHMINING 2015 - The ICDM Workshop on Data Mining and Decision Analytics on Public Health and Wellness (URL: http://www.comp.hkbu.edu.hk/~healthmining2015/) In conjunction with the IEEE International Conference on Data Mining (ICDM 2015) >>> SPECIAL ISSUE <<< Selected papers of the workshop will be invited for revision to be included in a special issue to be published in Health Information Science and Systems (URL: http://www.hissjournal.com/) AIMS and SCOPE For many years, data mining and decision analytics techniques have already been extensively applied to various domains, such as smart environments, social networks, marketing, and web technology. The focus of this workshop is mainly on the issues and challenges of data mining techniques with the purpose of improving human well-being and quality of life. It is expected that the workshop may increase the diversity of application areas that can benefit from data mining. At the same time, it is also desirable that the discussion and vision of this workshop would also offer further insights into, as well as new tools for, the issues of data collection, processing, system modeling, simulation and optimization arising from various public health topics. The objective of this workshop is to serve as a venue for researchers to discuss how data mining and analytics methods can contribute to improving public health quality in clinical, medical/biomedical, and healthcare systems in smart ways, including evidence-based medicine, personalized treatment and healthcare, assistive technology and active surveillance and control of diseases. In addition to mining statistical regularities, associations, or causalities from large-scale health-related datasets, it would be more desirable to further investigate how the results can effectively and efficiently support decision-making, system modeling, optimization, and simulation in various healthcare systems. TOPICS OF INTEREST - Large-scale data acquisition and management issues for public health - Social and other network-based analysis for public health - Medical big data mining and innovative applications - Mining risk patterns in medical data - Mental and physical health data integration - Biomarker discovery and biomedical data mining - Clinical data mining for practice knowledge building - Data mining from clinical decision-making, and practitioner reflection - Data mining from genetic data of diseases - Data mining for disease profiling and personalized treatment - Data mining for (active) syndromic surveillance - Data mining for infectious/chronic disease epidemiology and control - Data mining for exploring hidden patterns in clinical systems - Data mining for medical/biomedical, and healthcare systems - Data mining for assistive environments - Data modeling and information management forpervasive assistive environments - Data mining and knowledge modeling for wellness - Spatiotemporal data exploration and mining of diseases - Unstructured data mining in medicine and healthcare - Semantic data mining in medicine and healthcare - Scalable data integration in medicine and healthcare - Evidence-based decision-support systems - Healthcare knowledge abstraction, classification, and summarization - Healthcare knowledge computerization, execution, inference, and representation IMPORTANT DATES - Paper Submission Due: >>>Aug 3<<<, 2015 - Paper Notification Date: Sep 1, 2015 - Workshop Date: Nov 13, 2015 ORGANIZING COMMITTEE - William K. Cheung, Hong Kong Baptist University, Hong Kong - Jiming Liu, Hong Kong Baptist University, Hong Kong - Parisa Rashidi, University of Florida, USA - Fei Wang, University of Connecticut, USA Department of Computer Science: http://www.comp.hkbu.edu.hk HKBU Faculty of Science: http://www.sci.hkbu.edu.hk Disclaimer: http://www.comp.hkbu.edu.hk/disclaimer

July 21, 2015

NEURAL COMPUTATION - August 1, 2015

by Terry Sejnowski

Neural Computation - Volume 27, Number 8 - August 1, 2015 Available online for download now: http://www.mitpressjournals.org/toc/neco/27/8 ----- Article A Statistical Framework to Infer Delay and Direction of Information Flow From Measurements of Complex Systems Johannes Schumacher, Thomas Wunderle, Pascal Fries, Frank Jakel, and Gordon Pipa *FREE* Letters An Empirical Model for Reliable Spiking Activity Wanjie Wang, Shreejoy J Tripathy, Krishnan Padmanabhan, Nathaniel N. Urban, and Robert E. Kass Inheritance of Hippocampal Place Fields Through Hebbian Learning: Effects of Theta Modulation and Phase Precession on Structure Formation Tiziano D'Albis, Jorge Jaramillo, Henning Sprekeler, and Richard Kempter Competitive STDP Learning of Overlapping Spatial Patterns Dalius Krunglevicius A Reward-Maximizing Spiking Neuron as a Bounded Rational Decision-Maker Felix Leibfried, Daniel A. Braun Optimality of Upper-Arm Reaching Trajectories Based on the Expected Value of the Metabolic Energy Cost Yoshiaki Taniai, Jun Nishii Active Learning Using Hint Information Chun-Liang Li, Chun-Sung Ferng, and Hsuan-Tien Lin Subsampled Hessian Newton Methods for Supervised Learning Chien-Chih Wang, Chun-Heng Huang, and Chih-Jen Lin Minimal Sign Representation of Boolean Functions: Algorithms and Exact Results for Low Dimensions Can Eren Sezener, Erhan Oztop ------------ ON-LINE -- http://www.mitpressjournals.org/neuralcomp SUBSCRIPTIONS - 2015 - VOLUME 27 - 12 ISSUES Student/Retired $75 Individual $134 Institution $1,075 MIT Press Journals, One Rogers Street, Cambridge, MA 02142-1209 Tel: (617) 253-2889 FAX: (617) 577-1545 journals-cs(a)mit.edu ------------

July 20, 2015

Journal of Mathematical Neuroscience - recent articles

by Stephen Coombes

Dear all, The Journal of Mathematical Neuroscience publishes research articles on the mathematical modeling and analysis of all areas of neuroscience. The current list of journal articles is available at http://www.mathematical-neuroscience.com/ : Conditions for Multi-functionality in a Rhythm Generating Network Inspired by Turtle Scratching Snyder AC and Rubin JE http://www.mathematical-neuroscience.com/content/5/1/15 The Minimal k-Core Problem for Modeling k-Assemblies Wood CI and Hicks IV http://www.mathematical-neuroscience.com/content/5/1/14 Stochastic Synchronization in Purkinje Cells with Feedforward Inhibition Could Be Studied with Equivalent Phase-Response Curves Verduzco-Flores S http://www.mathematical-neuroscience.com/content/5/1/13 Orientation Maps in V1 and Non-Euclidean Geometry Afgoustidis A http://www.mathematical-neuroscience.com/content/5/1/12 On the Effects on Cortical Spontaneous Activity of the Symmetries of the Network of Pinwheels in Visual Area V1 Veltz R, Chossat P and Faugeras O http://www.mathematical-neuroscience.com/content/5/1/11 and see also the recent Special Issue on Stochastic Network Models in Neuroscience http://www.mathematical-neuroscience.com/series/SNMN<http://www.mathematical-neuroscience.com/series/UB> All articles are Open Access. Best regards, Steve ------------------------------------------------------- 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 send it back to me, and immediately delete it. Please do not use, copy or disclose the information contained in this message or in any attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. This message has been checked for viruses but the contents of an attachment may still contain software viruses which could damage your computer system, you are advised to perform your own checks. Email communications with the University of Nottingham may be monitored as permitted by UK legislation.

July 20, 2015

WORKHOP Nonlinear Dynamics in Computational Neuroscience, Turin 7-9 sept 2015

by Alessandro Torcini

Deadline 30th August: Nonlinear Dynamics in Computational Neuroscience: from Physics and Biology to ICT to be held on September 07-09, 2015 in Turin, Italy Organizers: Fernando Corinto (Politecnico di Torino, Turin, Italy) and Alessandro Torcini (ISC-CNR, Florence, Italy) More information on the workshop can be found in the web page: http://www.neuro-eng-comp.polito.it/workshop/ Confirmed invited speakers include Cristina Becchio (University of Turin, Italy) Ruben Moreno Bote (CIBERSAM - Barcelona, Spain) George Bourianov (Intel/University of Texas at Austin, USA) Emilio Carbone (University of Turin, Italy) Stephen Coombes (University of Nottingham, UK) Steve Furber (The University of Manchester, UK) Julius Georgiou (University of Cyprus, Cyprus) Viktor Jirsa (INSERM - Marseille, France) Luke P. Lee (UC Berkeley, USA) Stefano Luccioli (ISC CNR - Florence, Italy) Maurizio Mattia (ISS - Roma, Italy) Benedetto Sacchetti (University of Turin, Italy) Maria Sanchez-Vives (IDIBAPS - Barcelona, Spain) Ronald Tetzlaff (TU Dresden, Germany) The poster can be downloaded from here http://goo.gl/CDY0Eg The workshop is kindly supported by the: SICC - Italian Society for Chaos and Complexity, IEEE CASS Outreach 2015 Initiative, CRT Foundation, Marie Curie Initial Training project NETT - Neural Engineering Transformative Technologies, Ministry of Foreign Affairs (Italy)

July 19, 2015

Postdoctoral Position in Computational Neuroscience at IUPUI

by Yaroslav Molkov

A postdoctoral/research associate position in computational neuroscience for the duration of up to two years is available in the externally funded project focusing on multiscale computational modeling of motor control mechanisms, involving interactions between basal ganglia, thalamus, cerebellum, cortex, and spinal cord in connection with realistic simulation of pathological changes in motor control during Huntington’s disease. This collaborative project is performed jointly by the groups of Drs. Ilya Rybak (Dept. of Neurobiology and Anatomy, Drexel University, Philadelphia, PA, USA) and Yaroslav Molkov (Dept. of Mathematical Science, Indiana University – Purdue University, Indianapolis, IN, USA). Applicants must have a PhD degree in Neuroscience, Applied Mathematics, Physics, or a related discipline, a *strong research record*, and excellent C++ programming skills. Previous experience in computational neuronal modeling is a plus. Interested candidates are encouraged to contact Dr. Molkov ( ymolkov(a)iupui.edu) by email. To apply, please send an email along with (1) curriculum vitae; (2) a cover letter describing previous research experience and interests; (3) the names and contact information of three references. I will be available to answer questions and discuss this job opportunity with potential candidates at the CNS’2015 meeting in Prague, Czech Republic (July 18-23). Please email me to arrange a meeting. ================================= Yaroslav Molkov, Ph.D. Assistant Professor Indiana University - Purdue University at Indianapolis Department of Mathematical Sciences 402 N. Blackford St, LD 270, Indianapolis, IN 46202 Office: LD 224U Phone: (317) 274-6934 Fax: (317) 274-3460 Email: ymolkov(a)iupui.edu

July 16, 2015

Postdoc in Computational Visual Neuroscience (Alicante-Valencia, SPAIN)

by Jesus Malo Lopez

The Neuroscience Institute of Alicante (CSIC) and the Universitat de Valencia are involved on a multiyear project to study neural computation and coding in visual cortex. We have an opening for a 3 year postdoc position to model information processing in the retina-cortex pathway. Job title: "The human camera: compressive sensing in brain networks and decoding from neural responses" (see additional information about the project at http://isp.uv.es/bmi.html ) Applications are invited for the above position to work with Dr. Luis Martinez (Neuroscience Institute of Alicante, CSIC, http://thevisualanalogylab.wix.com/valab) and Dr. Jesús Malo (Image & Signal Processing Lab, Universitat de Valencia, http://isp.uv.es ). The aim of this work is understanding dimensionality reduction in the retina-cortex bottleneck and enabling image reconstruction from actual neural recordings at cortical level. The "Human Camera" could be seen as a new Brain Machine Interface for image transmission in which the nontrivial/adaptive feature extraction stage is done by a brain instead of by the conventional compression algorithm. The input signal should be reconstructed from the neural signal at the receiver. Candidates must be in possession of a doctoral degree in computational neuroscience, machine learning, physics, mathematics or engineering. Preference will be given to candidates with experience and genuine interest in vision science phenomena and models. Work will be developed both at the Neuroscience Institute of Alicante and at the Universitat de València, with strong collaboration between the experimental and theoretical members of the team. Salary: according to CSIC Postdoc scales including social security, health insurance benefits, and travel money. Contact: Please email jesus.malo(a)uv.es or luis.m.martinez.otero(a)gmail.com for any queries about the position.

July 16, 2015

Special Issue on Emerging Spatial Competences: From Machine Perception to Sensorimotor Intelligence

by Agostino Gibaldi

APOLOGIES FOR CROSS-POSTING. Dear Researcher, we are very glad to inform you that the Special Issue “Emerging Spatial Competences: From Machine Perception to Sensorimotor Intelligence” (http://www.sciencedirect.com/science/journal/09218890) has been published on the Robotics and Autonomous System Journal (http://www.journals.elsevier.com/robotics-and-autonomous-systems) The aim of this special issue is to survey a state of the art of methodologies, concepts, algorithms and techniques that would serve as bricks on which to build and develop artificial agents with such a spatial competence; perceptual and cognitive understanding of space should emerge from sensorimotor exercise. The Special Issue includes 13 papers (acceptance rate 40%) plus the editorial: Emerging spatial competences: From machine perception to sensorimotor intelligence Agostino Gibaldi, Silvio P. Sabatini, Sylvain Argentieri, Zhengping Ji Self-calibrating smooth pursuit through active efficient coding C. Teulière, S. Forestier, L. Lonini, C. Zhang, Y. Zhao, B. Shi, J. Triesch Learning the visual–oculomotor transformation: Effects on saccade control and space representation Marco Antonelli, Angel J. Duran, Eris Chinellato, Angel P. del Pobil Autonomous learning of disparity–vergence behavior through distributed coding and population reward: Basic mechanisms and real-world conditioning on a robot stereo head Agostino Gibaldi, Andrea Canessa, Fabio Solari, Silvio P. Sabatini A developmental where–what network for concurrent and interactive visual attention and recognition Zhengping Ji, Juyang Weng Learning agent’s spatial configuration from sensorimotor invariants Alban Laflaquière, J. Kevin O’Regan, Sylvain Argentieri, Bruno Gas, Alexander V. Terekhov Trainable sensorimotor mapping in a neuromorphic robot Jörg Conradt, Francesco Galluppi, Terrence C. Stewart Cortically inspired sensor fusion network for mobile robot egomotion estimation Cristian Axenie, Jörg Conradt Deep unsupervised network for multimodal perception, representation and classification Alain Droniou, Serena Ivaldi, Olivier Sigaud Support relation analysis and decision making for safe robotic manipulation tasks Rasoul Mojtahedzadeh, Abdelbaki Bouguerra, Erik Schaffernicht, Achim J. Lilienthal Model-free incremental learning of the semantics of manipulation actions Eren Erdal Aksoy, Minija Tamosiunaite, Florentin Wörgötter Human motion based intent recognition using a deep dynamic neural model Zhibin Yu, Minho Lee Hybrid learning model and MMSVM classification for on-line visual imitation of a human with 3-D motions Chih-Lyang Hwang, Bo-Lin Chen, Hsing-Hao Huang, Huei-Ting Syu Interfacing robotic tactile sensation with human vibrotactile perception for digit recognition Anwesha Khasnobish, Shreyasi Datta, Dwaipayan Sardar, D.N. Tibarewala, Amit Konar Cordially, the Guest Editors: Agostino Gibaldi and Silvio P. Sabatini Department of Informatics, Bioengineering, Robotics and System Engineering PSPC Lab (www.pspc.unige.it) University of Genoa, Italy Sylvain Argentieri Institute for Intelligent Systems and Robotics (ISIR), Sorbonne Universités, UPMC University, Paris 06, France Zhengping Ji Advanced Image Research Laboratory (AIRL), Samsung, Pasadena, CA, USA

July 15, 2015

Software for Non-parametric directionality analysis

by David Halliday

[Apologies for cross posting] MATLAB software to implement non-parametric directionality analysis for spike-train and time-series data is available for free download from the NeuroSpec archive. A user guide and demonstration scripts are included. http://www.neurospec.org/ An accompanying journal article is published in the Journal of Integrative Neuroscience: "Nonparametric directionality measures for time series and point process data", J. Integr. Neurosci., 14, 253-277 (2015). DOI: 10.1142/S0219635215300127 http://dx.doi.org/10.1142/S0219635215300127 Abstract The need to determine the directionality of interactions between neural signals is a key requirement for analysis of multichannel recordings. Approaches most commonly used are parametric, typically relying on autoregressive models. A number of concerns have been expressed regarding parametric approaches, thus there is a need to consider alternatives. We present an alternative nonparametric approach for construction of directionality measures for bivariate random processes. The method combines time and frequency domain representations of bivariate data to decompose the correlation by direction. Our framework generates two sets of complementary measures, a set of scalar measures, which decompose the total product moment correlation coefficient summatively into three terms by direction and a set of functions which decompose the coherence summatively at each frequency into three terms by direction: forward direction, reverse direction and instantaneous interaction. It can be undertaken as an addition to a standard bivariate spectral and coherence analysis, and applied to either time series or point-process (spike train) data or mixtures of the two (hybrid data). In this paper, we demonstrate application to spike train data using simulated cortical neurone networks and application to experimental data from isolated muscle spindle sensory endings subject to random efferent stimulation. - David Halliday Department of Electronics University of York YORK YO10 5DD, UK. E-Mail: david.halliday(a)york.ac.uk

July 14, 2015