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Postdoctoral Position in Computational Neuroscience at IUPUI
by Yaroslav Molkov July 16, 2015

July 16, 2015

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

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Postdoc in Computational Visual Neuroscience (Alicante-Valencia, SPAIN)
by Jesus Malo Lopez July 16, 2015

July 16, 2015

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.

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Special Issue on Emerging Spatial Competences: From Machine Perception to Sensorimotor Intelligence
by Agostino Gibaldi July 15, 2015

July 15, 2015

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

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Software for Non-parametric directionality analysis
by David Halliday July 14, 2015

July 14, 2015

[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

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Tutorial on Interfaces in Computational Neuroscience Software
by Jochen Martin Eppler July 14, 2015

July 14, 2015

[Sorry if you receive this mail through multiple channels] This is to inform you about the CNS2015 tutorial entitled "Interfaces in Computational Neuroscience Software". In the tutorial, Jochen M. Eppler (Research Centre Jülich, Germany), Mikael Djurfeldt (INCF and KTH PDC, Sweden) and Janne Moren (OIST and RIKEN AICS, Japan) will present the combined use of the tools NEST, CSA and MUSIC. Introductory talks will explain the concepts behind the tools and libraries, while hands-on sessions will allow the participants to gather some experience with them. The software for the hands-on sessions will be provided in the form of a virtual machine image readily usable on top of your laptop. More information on the tutorial can be found on the homepage of the meeting at http://www.cnsorg.org/cns-2015-tutorials#t6 Looking forward to seeing you in Prague! Best regards, Jochen Eppler -- Dr. Jochen Martin Eppler Phone: +49 2461 61-9471 ---------------------------------- Simulation Laboratory Neuroscience Jülich Supercomputing Centre Institute for Advanced Simulation ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Dr. Karl Eugen Huthmacher Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt, Prof. Dr. Sebastian M. Schmidt ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------

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CFP: The First International Workshop on Computational Models of the Visual Cortex (CMVC) as part of the BICT, New York, 3-5 Dec 2015
by George Azzopardi July 14, 2015

July 14, 2015

Dear All, We are pleased to announce The First International Workshop on Computational Models of the Visual Cortex (CMVC) as part of the BICT (Bio-inspired Information and Communication Technologies) conference, which will be held in New York City, New York, 3-5 December (http://bionetics.org/2015/show/home) Background Much has been advanced since the early works of the Nobel prize winners Hubel and Wiesel about the function of neurons in the primary visual cortex of cats’ brains. That work has been the source of inspiration of abundant neurophysiological studies to unveil the functionality of neurons in different areas of visual cortex. These experiments resulted in large amounts of data, which could then be used to design computational models to behave similarly to certain neurons in visual cortex. The contribution of such models is two-fold. They contribute to the better understanding of how visual information is processed in the brain, and they also contribute for the development of more robust algorithms in computer vision applications. The aim of this workshop is to bring together recent development of computational modelling of the visual cortex of the brain: Single cell modeling. Hierarchy of visual cortex areas Feedforward, feedback and inhibitory mechanisms. The appearance of neuronal properties: sparsity and selectivity. Circuitry: hierarchical representations and connections between layers. Selecting where to look: saliency and attention. Object recognition Contour detection Stereo Learning Important Dates Full papers due: July 31, 2015 Authors Notified: August 31, 2015 Camera-ready due: September 30, 2015 Paper submission We invite you to submit regular papers (up to 8 pages each), short papers (up to 4 pages each) or poster/demo papers (up to 2 pages each) in ACM's paper template. Up to two extra pages are allowed for each paper with extra page charges. See http://bionetics.org/2015/show/initial-submission for more details. Paper Submission Only PDF format is acceptable. Papers must be submitted to EasyChair: https://easychair.org/conferences/?conf=cmvc2015 For more information about the CMVC workshop please visit: http://cmvc.bionetics.org/2015/show/home Sincerely yours, Antonio Rodriguez-Sanchez, PhD George Azzopardi, PhD Co-chairs of CMVC’2015

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NEURON course and NSG Workshop at SFN 2015 meeting
by Ted Carnevale July 13, 2015

July 13, 2015

Two events of particular interest to computational neuroscientists will be presented as satellite sessions to the 2015 SFN meeting in Chicago. Using NEURON to Model Cells and Networks Friday, Oct. 16 from 9 AM to 5 PM at a site in downtown Chicago This course provides a practical introduction to building and using models of neurons and networks with NEURON. Covered topics include basic concepts, workflow for building and using models, speeding up simulations with parallel hardware from multicore personal computers to massively parallel supercomputers, using Python with NEURON, and modeling reactive diffusion with the RxD class. Using the Neuroscience Gateway Portal for Parallel Simulation Saturday, Oct. 17 from 9 AM to noon at a site in downtown Chicago This workshop combines didactic presentations with hands on instruction on how to use the Neuroscience Gateway Portal (NSG) for parallel simulations. NSG eliminates most adminstrative and technical barriers to using high performance computing resources--it even gives away free CPU time. Simulators that are currently installed on NSG include NEST, PyNN, Brian, GENESIS3, NEURON, and MOOSE. Also available is FreeSurfer, a set of tools for analysis and visualization of structural and functional brain imaging data. Friday, Oct. 2, is the registration deadline for both of these events, but you should sign up early because space is limited. See https://www.neuron.yale.edu/neuron/courses for more information and links to registration forms. --Ted

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Workshop at CNS2015 on Dopamine neurons and the circuits they participate in
by Canavier, Carmen C. July 13, 2015

July 13, 2015

Title: Computational Models of Midbrain Dopamine Neurons and Dopaminergic Signaling Organizer: Carmen Canavier ccanav(a)lsuhsc.edu<mailto:ccanav@lsuhsc.edu> July 23, Prague, Room RB209 (subject to change) Description: This workshop features recent experimental and modeling work on SNc and VTA dopamine neurons in the context of addiction, Parkinson’s disease and schizophrenia. Time Speaker Title 9-9:30 Alexey Kuznetsov A model for VTA circuitry: toolbox for the study of addictions 9:30-10 Eleftheria Pissadaki From the axons of the SNc dopamine neurons to their dendritic processes: further clues to susceptibility in Parkinson's disease 10-10:30 COFFEE BREAK 10:30-11 Rebekah Evans T type calcium channels trigger a hyperpolarization induced after depolarization (HI-ADP) in SNc dopamine neurons 11-11:30 Andy Oster VTA Dopamine Neuron Dynamics: response to ramping applied currents 11:30-12:00 Carmen Canavier Dynamic Diversity of Dopamine Neurons 12:00-1:30 LUNCH BREAK 1:30-2 Guillaume Drion Potential functional implications of a hidden variability in SNc DA neuron excitability 2-2:30 Jinyoung Jang Spontaneous firing system in the midbrain dopamine neu- ron 2:30-3 Boris Gutkin VTA circuit models and nicotine/alcohol effects on DA dynamics 3-3:30 DISCUSSION AND CLOSING REMARKS

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Workshop at CNS2015: Open Collaboration in Computational Neuroscience
by Padraig Gleeson July 13, 2015

July 13, 2015

[Apology for cross-postings] Announcing a workshop at the CNS2015 meeting in Prague, Thursday July 23: Open Collaboration in Computational Neuroscience http://opensourcebrain.org/docs/Help/Meetings#CNS_2015 Building and analysing biophysically and anatomically detailed neuronal networks is a complex and time consuming task, which ideally involves researchers with a range of backgrounds and technical skills. However, most labs cannot expect to have all of these researchers present at any given time. This can lead to stalled projects, lost data and software and needless repetition of experimental and computational work. A number of initiatives have been started which address these issues. Some are creating public resources with freely available data to constrain such models. Others are using best practices from open source software development to encourage building and sharing of models in a collaborative environment. This workshop will serve as an informative introduction to these projects as well as a discussion forum for getting feedback and gathering requirements from the community for the developers of these initiatives. There are still a number of slots available for *5-10 minute lightning talks*, so if you are involved in a project in this area and wish to publicise it, please get in contact. *Confirmed speakers:* Jan Antolik (CNRS) Collaboration in neuronal modelling: model sharing, workflows and provenance Nicholas Cain (Allen Brain Institute) Resources for Open Collaboration at the Allen Brain Institute <http://www.brain-map.org/> Padraig Gleeson (University College London) NeuroML <https://neuroml.org/> & the Open Source Brain Initiative <http://opensourcebrain.org/> Adrian Quintana (University College London) Geppetto <http://www.geppetto.org/>: online visualisation & simulation for neuronal models Michael Sonntag (LMU München) The NIX Project: Comprehensive Storage of Neuroscience Data and Metadata <https://github.com/G-Node/nix> Matteo Cantarelli (MetaCell Ltd) OpenWorm <http://www.openworm.org/> Aurel A. Lazar (Columbia University) Neurokernel <http://neurokernel.github.io/>: An Open Source Platform for Emulating the Fruit Fly Brain Bill Lytton (SUNY Downstate Medical Center) ModelDB <http://senselab.med.yale.edu/ModelDB/> Eilif Muller (EPFL) Human Brain Project <https://www.humanbrainproject.eu/> resources for the integrative modelling community Shreejoy Tripathy (University of British Columbia) Open electrophysiology data and Neuroelectro.org <http://neuroelectro.org/> ----------------------------------------------------- Padraig Gleeson Room 321, Anatomy Building Department of Neuroscience, Physiology& Pharmacology University College London Gower Street London WC1E 6BT United Kingdom +44 207 679 3214 p.gleeson(a)ucl.ac.uk -----------------------------------------------------

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postdoc in computational neuroscience
by Máté Lengyel July 13, 2015

July 13, 2015

Postdoctoral Fellow in Computational Neuroscience University of Cambridge We are seeking a highly creative and motivated postdoctoral fellow (research associate or senior research associate) to work in the group of Máté Lengyel (http://learning.eng.cam.ac.uk/Public/Lengyel/) at the Computational and Biological Learning Lab, Department of Engineering, University of Cambridge to work on circuit- and systems-level of memory, in particular the interaction between recollective and familiarity-based forms of recognition memory. The project involves collaboration with Peter Dayan (Gatsby Computational Neuroscience Unit, UCL), and also Richard Henson (MRC Cognition and Brain Unit, Cambridge) providing direct access to relevant behavioural and imaging data. More broadly, the group studies learning and memory from computational, algorithmic/representational and neurobiological viewpoints. Computationally and algorithmically, we use ideas from Bayesian approaches to statistical inference and reinforcement learning to characterize the goals and mechanisms of learning in terms of normative principles and behavioral results. We also perform dynamical systems analyses of reduced biophysical models to understand the mapping of these mechanisms into cellular and network models. We collaborate very closely with experimental neuroscience groups, doing in vitro intracellular recordings, multi-unit recordings in behaving animals, human psychophysical, and fMRI experiments. The successful candidate will have a strong analytical background and demonstrable interest in theoretical neuroscience. They should have or be close to completion of a PhD or equivalent in computational neuroscience, physics, mathematics, computer science, machine learning or a related field. Previous experience in computational neuroscience is not required, but preference will be given to candidates with sufficient programming skills to run numerical simulations, or expertise with neural network models, analysis of dynamical systems, and Bayesian techniques. The position is funded for several years, with an initial one-year appointment and an expectation of extension to at least two years given satisfactory performance. Salary depends on experience and is in the range £28,695 - £48,743 p.a. Further information: http://www.jobs.cam.ac.uk/job/7261/ http://www.jobs.cam.ac.uk/job/7176/ For informal queries, please contact Mate Lengyel <m.lengyel(a)eng.cam.ac.uk>. Mate Lengyel -- Mate Lengyel, PhD Computational and Biological Learning Lab Cambridge University Engineering Department Trumpington Street, Cambridge CB2 1PZ, UK tel: +44 (0)1223 748 532, fax: +44 (0)1223 765 587 email: m.lengyel(a)eng.cam.ac.uk web: www.eng.cam.ac.uk/~m.lengyel

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