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3rd Model-based Neuroscience Summer School, Amsterdam
by Jane Neumann March 30, 2016

March 30, 2016

Dear colleagues, June 27-July 1 2016 will see the third Model-Based Neuroscience Summer School, hosted at the University of Amsterdam.   The summer school will provide students with hands-on experience in both cognitive modeling using diffusion and accumulator models and simple neuroscience methods. The program includes a series of lectures on model-based decision neuroscience in both humans and non-human primates from experts including Michael Shadlen, Gordon Logan, Andrew Heathcote, Uta Noppeney, Brandon Turner, Jane Neumann, and Birte Forstmann.    *The summer school is aimed at PhD students and early postdocs who wish to combine cognitive modeling with experimental and theoretical neuroscience research. Students should be familiar with general programming concepts and state in their application which programming languages and software packages they typically use. * The summer school will be co-located at the University of Amsterdam with a one-day symposium on model-based neuroscience of mind wandering, to be held on July 2 2016. The symposium will involve a series of lectures from experts in the scientific study of mind wandering with a focus on model-based neuroscience approaches. The symposium will provide a unique opportunity to see how the concepts introduced in the summer school can provide insight on an important research topic. *Application and registration:*  The registration fee for the summer school is 500 euro. The registration fee for combined attendance at the summer school and the one-day mind wandering symposium is 600 euro. We ask that students make their own housing arrangements. Space is limited, therefore we ask that you provide a statement of interest. We will select students based on the relevance of the summer school to their research. The application deadline is 22 April 2016.   More information about the summer school including teachers, preliminary program and application can be found atwww.modelbasedneuroscience.com We look forward to welcoming you in Amsterdam!   Organization:  Jane Neumann, University Medical Center Leipzig and MPI for Human Cognitive and Brain Sciences Leendert van Maanen, University of Amsterdam  Birte Forstmann, University of Amsterdam Guy Hawkins, University of Amsterdam Andrew Heathcote, University of Tasmania

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Gordon Research Seminar on Neurobiology of Cognition
by Sarah Heilbronner March 29, 2016

March 29, 2016

Dear computational neuroscientists, We would like to invite you to apply to the Gordon Research Seminar (GRS) on Neurobiology of Cognition. The GRS is a unique forum for graduate students and postdocs to present and exchange new data and cutting-edge ideas. Following the GRS, attendees are encouraged to stay for the main Gordon Research Conference (GRC). More information, as well as an online application, can be found here: https://www.grc.org/programs.aspx?id=16594 Please note that, in order to be considered for a talk, abstract must be submitted by April 23. We look forward to seeing you this summer! Best, Sarah Heilbronner & Brian Russ Directors, 2016 GRS on Neurobiology of Cognition

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Postdoctoral position: Goldman lab, UC Davis
by Mark Steven Goldman March 28, 2016

March 28, 2016

At least one postdoctoral position is available in the laboratory of Dr. Mark Goldman in the University of California at Davis Center for Neuroscience. UC Davis is a top-ten public research university (US News & World Report) located 1 hour east from the San Francisco Bay Area and 20 minutes from the state capital of Sacramento. The laboratory works on a broad range of problems in computational neuroscience, ranging from neural coding to dynamics and plasticity of single neurons and networks. Current work has focused especially upon issues related to working memory, neural integration, motor learning, and synaptic plasticity as described below. Projects include but are not limited to: 1) Dissecting the function of a biological neural integrator circuit. Work will be modeling the oculomotor neural integrator, a classic model system for working memory and neural integration that is amenable to in vivo whole-circuit optical recording, dendritic imaging, optogenetic perturbation, pharmacology, and connectomic reconstruction. The goal is to identify the cellular and circuit mechanisms underlying neural integration and continuous attractor formation, from subcellular processes to circuits and behavior, as well as to develop optimal experimental design methods for dissecting circuit function. Project in collaboration with the experiments of Dr. Emre Aksay (Weill/Cornell Medical) and connectomic reconstructions of Dr. Sebastian Seung (Princeton University). 2) Mechanisms of analog working memory and neural integration. The goal is to identify novel mechanisms of working memory and neural integration across a range of systems, including mechanisms for context-dependent memory function. 3) Cerebellar mechanisms of motor control and motor learning in the oculomotor system. The goal is to use the oculomotor system as a model system for understanding cerebellar-mediated motor learning. Theory and computational analysis will be used to dissect the circuit mechanisms, sites of plasticity, and broader computational principles underlying oculomotor learning. Theoretical work will provide predictions for, and be conducted in close collaboration with, the experimental laboratories of Dr. Emre Aksay (Weill/Cornell Medical) and Dr. Jennifer Raymond (Stanford University). Candidates are expected to have training in a quantitatively rigorous discipline such as math, physics, engineering, computer science, statistics, or computational neuroscience. Interested candidates should send a CV, brief statement of previous research and future research interests, and contact information for 3 references to: Mark Goldman, msgoldman(a)ucdavis.edu.

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Deadline approaching for Summer Workshop on the Dynamic Brain
by Adrienne Fairhall March 27, 2016

March 27, 2016

Dear Colleagues, Announcing the Summer Workshop on the Dynamic Brain 2016, co-organized by the Allen Institute for Brain Science and the Computational Neuroscience Program at the University of Washington and directed by Drs. Christof Koch and Adrienne Fairhall. Applications are being accepted until April 1, 2016. This intensive two-week, project-based interdisciplinary course aims to give advanced students in neuroscience, biology, physics, engineering and computer science a rapid introduction to the current state of understanding of the neurobiology of sensory processing, including anatomy, physiology and neural coding and a mentored introduction to Allen Institute open data sets. New this year: In 2016 we will hold an optional one-day Python bootcamp in Seattle on August 20. The workshop begins at Friday Harbor on August 21. Cost: Conference fees, housing and meals during the workshop will be covered by the organizers. Additional expenses, including transportation and incidentals, are the responsibility of the attendee. Please share this information with potential students and others in your department. Details and application form available at http://courses.washington.edu/braindyn/ . Thank you! Adrienne Fairhall University of Washington

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ICMNS 2016: Deadline Extended to Feb. 7, 2016
by Zachary Kilpatrick March 27, 2016

March 27, 2016

*Abstract deadline extended to February 7, 2016* https://icmns2016.inria.fr/call-for-contributions/ <https://icmns2016.inria.fr/call-for-contributions/> There will also be a prize for best papers. International Conference on Mathematical Neuroscience (ICMNS 2016) at the Congress Center in Juan-les-Pins on the French Riviera May 29 to June 1, 2016 Tutorials: May 29 Main Conference: May 30 - June 1 https://icmns2016.inria.fr/ <https://icmns2016.inria.fr/> CONFIRMED SPEAKERS Wulfram Gerstner (École polytechnique fédérale de Lausanne) John Rinzel (New York University) Antoine Triller (École Normale Supérieure de Paris) Rachel Kuske (U British Columbia) Jonathan Rubin (U Pittsburgh) Hinke Osinga (U Aukland) Carina Curto (Penn State University) Ruben Moreno-Bote (Foundation Sant Joan de Deu) Hiroya Nakao (Tokyo Institute of Technology) Eric Shea-Brown (U Washington) Si Wu (Beijing Normal University) Alex Roxin (Centre de Recerca Matematica) PROGRAM COMMITTEE Toni Guillamon (Universitat Politècnica de Catalunya) Roland Potthast (U Reading) Gregory Faye (Université Paul Sabatier ) Wilhelm Stannat (TU Berlin) Jonathan Touboul (College de France) Gilles Wainrib (Ecole Normale Supérieure) Suzanne Ditlevsen (University of Copenhagen) Boris Gutkin (Ecole Normale Supérieure) Martin Wechselberger (U Sydney) Jonathan Rubin (U Pittsburgh) Martin Krupa (INRIA Sophia Antipoilis) Carlo Laing (Massey University) Andre Longtin (U Ottawa) Daniele Avitabile (U Nottingham) Jose Carrillo (Imperial College) Pascal Chossat (Université Nice Sophia Antipolis) Carson Chow (National Institutes of Health) Steve Zucker (Yale University) Eric Shea-Brown (U Washington) Rachel Kuske (U British Columbia) Laura Sacerdote (Universita di Torino) Reinhard Hopfner (Johannes-Gutenberg Universitat) Olivier Faugeras (INRIA - Sophia Antipolis) Paul Bressloff (U Utah) Steve Coombes (U Nottingham) CONFERENCE CHAIRS Romain Veltz (INRIA - Sophia Anitpolis) Zachary Kilpatrick (U Houston) Evelyn Buckwar (Johannes Kepler Universitat Linz)

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Two PhD Positions in Computer Vision for Connectomics at INI in Zurich
by Jan Funke March 25, 2016

March 25, 2016

The Institute of Neuroinformatics (INI) of the University of Zurich and ETH Zurich has two PhD positions in the field of computer vision for connectomics, i.e., the reconstruction of neural circuits from electron microscopy volumes. The project aims at improving the current state of the art of discrete optimization models for neuron segmentation by investigating new segmentation methods, the incorporation of biological priors, (deep) learning from sample annotations, and the development of large-scale reconstruction pipelines. A detailed description can be found at: https://docs.google.com/document/d/1hThoBuesWucwCDUmStyCt44VWMscXy9KxBtuyA5… The project will be carried out in collaboration with the HCI Heidelberg (Germany) and the Universitat Politècnica de Catalunya, Barcelona (Spain). Generous funding for at least three years will be provided, including travel costs for regular visits of our collaborators and conference fees. Please send us an email with your CV at funke(a)ini.ethz.ch (Jan Funke) for further information. Regards, Jan Funke

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Post-Doc in Bordeaux, application deadline 01/04/2016 (1 week)
by Nicolas P. Rougier March 25, 2016

March 25, 2016

Actor–critic models of the basal ganglia Postdoc in Bordeaux (12 months), France Application deadline 01/04/2016. Details & application at: http://www.inria.fr/institut/recrutement-metiers/offres/post-doctorat/sejou… Nicolas Rougier --- Actor–critic models of the basal ganglia We developed a model of the basal ganglia (Piron et al., 2016) that introduces an action selection mechanism that is based upon the competition between a positive feedback through the direct pathway and a negative feedback through the hyperdirect pathway. The model also exploits the parallel organization of circuits between the basal ganglia and the cortex using segregated loops: one loop allows to choose the cue and one loop allows to make the actual motor selection. Learning occurs between the cognitive cortex and the cognitive striatum using a simple reinforcement learning where the values of the different cues are updated after each decision. As in most computational models of the basal ganglia, this model relies on an actor-critic architecture where the dopamine signal is used to encode the temporal difference prediction error signal in the critic (Joel et al., 2002; Khamassi et al., 2005). However, this algorithm is not very elaborated and its implementation is not biologically plausible since values are stored outside the model. The objectives of this postdoc is thus to review and to re-implement (Python) main actor-critic models of the literature in order to compare them on a common set of decision tasks (two-arm bandit task for example) in terms of biological plausibility and performances. Special attention will be given to the "Primary Value and Learned Value Pavlovian Learning Algorithm" model (O'Reilly, 2007) and the AGREL model (Roefselma et al. 2005). From these replications (that will be published in ReScience), the most plausible and compatible mechanisms will be implemented in our own model of the basal ganglia in order to replace the current reinforcement learning algorithm (Guthrie et al., 2013, Piron et al. 2016). Profiles PhD in computational neuroscience or computer science (machine learning) with strong experience in Python & the scientific Python stack (numpy, scipy, matplotlib, git/github). References • Joel, D., Niv, Y., & Ruppin, E. (2002). Actor–critic models of the basal ganglia: New anatomical and computational perspectives. Neural Networks, 15(4-6), 535–547. • Khamassi, M., Lachèze, L., Girard, B., Berthoz, A., Guillot, A. (2005). Actor-critic models of reinforcement learning in the basal ganglia: From natural to artificial rats. Adaptive Behavior, 13 (2). • Guthrie, M., Leblois, A., Garenne, A., & Boraud, T. (2013). Interaction between cognitive and motor cortico-basal ganglia loops during decision making: a computational study. Journal of Neurophysiology, 109(12). • C. Piron, D. Kase, M. Topalidou, M. Goillandeau, H. Orignac, T. N'Guyen, N.P. Rougier, T. Boraud, The globus pallidus pars interna in goal oriented and habitual behavior. Resolving an old standing paradox, Movement Disorders, (2016), to appear. • O'Reilly, R. C., Frank, M. J., Hazy, T. E., & Watz, B. (2007). PVLV: The Primary Value and Learned Value Pavlovian Learning Algorithm. Behavioral Neuroscience, 121(1). • Roelfsema, P.R., van Ooyen A. (2005). Attention-gated reinforcement learning of internal representations for classification. Neural Computation.

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Post-Doctoral Positions at Boston University Investigating Long-Range Neocortical Networks
by Chen, Jerry March 24, 2016

March 24, 2016

Post-Doctoral Positions Available --------------------------------- We are a new lab, headed by Jerry Chen, opening our doors in 2016 in the Department of Biology at Boston University SUMMARY: A longstanding goal in neuroscience is to achieve a complete understanding of the central nervous system, from the brain as a whole all the way down to individual neurons and synapses. A fundamental challenge in achieving this goal is bridging knowledge gaps impeded by the difficulty in integrating experimental measurements across different scales. Our lab studies the relationship between local circuits and long-range networks in the mammalian neocortex. We take an integrative approach by combining large-scale in vivo imaging technology with molecular and genetic tools in the awake-behaving animal. RESEARCH PROJECTS: Principles of Long-Range Cortical Communication. We are investigating how behavior-relevant information is processed both locally and globally throughout the neocortex. Using the mouse tactile whisker sensorimotor system as a model for studying long-range cortical communication during sensory processing and decision making, we seek to understand the following questions: - What are the circuits underlying long-range cortical communication? - What are the physiological mechanisms that subserve such operations? - What roles do these processes serve during behavior? Long-Range Cortical Circuits During Development. We are investigating how genes and development define the organization and function of long-range cortical circuits. Gaining a handle on how these circuits form will help us understand the role they serve during behavior. Technologies for Large-Scale Imaging of Neuronal Populations. We recently developed a multi-area two-photon microscope that enables simultaneous functional imaging with cellular resolution across cortical areas. We seek to expand on such methods to enable comprehensive monitoring of neuronal activity across the entire cortex. QUALIFICATIONS: We are seeking highly creative individuals who are interested in pursuing independent projects core to the lab's research interest. A first author publication (submitted or published) is a prerequisite for consideration. While experience with in vivo imaging and rodent behavior and a quantitative background is desired, we are also interested in individuals with a broad range of expertise within and outside of neuroscience. You can even be a mathematician, physicist, engineer, computer scientist, molecular biologist, artist, or musician. Some examples of potential good fits include: - Neurophysiologists with previous experience working with non-human primates interested in addressing similar questions in rodents. - Developmental neurobiologists interested in studying how circuit formation guides circuit function and behavior. - Computational neuroscientists interested in testing theoretical models using experimental data acquired in the lab. - Molecular biologists interested in utilizing molecular and genetic tools for addressing systems-level questions. - Optical engineers interested in developing and applying novel technologies for large-scale recording and stimulation of neuronal populations. For more information, go to www.chen-lab.org. If you are interested in applying, please submit a CV along with 3 references to: jerry(a)chen-lab.org.

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ANNPR 2nd Call for Papers
by Dr. Schwenker March 24, 2016

March 24, 2016

**** Please apologize cross-postings. 2nd Call for Papers IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR 2016) September 28-30, 2016 Ulm University, Ulm, Germany ANNPR 2016 invites papers that present original work in areas of neural networks, machine learning and pattern recognition, focusing on both theoretical and applied aspects. Topics of interest include, but not limited to: Methodological Issues - Supervised learning - Unsupervised learning - Combination of supervised and unsupervised learning - Feed-forward, recurrent, and competitive neural nets - Kernel machines - Hierarchical modular architectures and hybrid systems - Combination of neural networks and Hidden Markov models - Multiple classifier systems and ensemble methods - Probabilistic graphical models - Kernel methods - Deep architectures Applications in Pattern Recognition - Image processing and segmentation - Handwritten recognition and Document analysis - Sensor-fusion and multi-modal processing - Feature extraction, dimension reduction - Clustering and vector quantization - Speech and speaker recognition - Data, text, and web mining - Bioinformatics/Cheminformatics Important Dates Paper submission: May 4, 2016 Notification of acceptance: June 22, 2016 Camera ready due: July 6, 2016 Workshop: September 28-30, 2016 General Chairs Friedhelm Schwenker, Ulm University, Germany Hazem Abbas, German University of Cairo, Egypt Neamat El Gayar, Cairo University, Egypt Edmondo Trentin, University of Siena, Italy For more information, please visit us: http://neuro.informatik.uni-ulm.de/ANNPR2016/ -- Dr. Friedhelm Schwenker University of Ulm Institute of Neural Information Processing D-89069 Ulm, Germany phone: +49-731-50-24159 fax: +49-731-50-24156 email: friedhelm.schwenker(a)uni-ulm.de www: http://www.uni-ulm.de/in/neuroinformatik/mitarbeiter/f-schwenker.html

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Master student / intern position available at Max Planck Institute for Biological Cybernetics, Tübingen, Germany
by Filip Sobczak March 24, 2016

March 24, 2016

OPEN POSITION Master student / intern position at the Max Planck Institute for Biological Cybernetics in Tübingen, Germany The Department of High-field Magnetic Resonance at the Max Planck Institute for Biological Cybernetics in Tübingen is looking for a master’s student or an intern to work under the supervision of Dr. Xin Yu (Group Leader at MPI for Biological Cybernetics). This position is open now until filled. Research description: The project requires applying image processing and computer vision techniques for neuroscientific purposes. The goal is establishing a platform enabling the registration of rat brain MRI scans onto a brain atlas template. This will allow locating specific brain structures in a newly acquired MRI scan. Example applications of the platform are: - increasing the precision of targeting and recording deep brain nuclei, - enabling the use of MRI images as feedback in closed-loop control of a robotic arm operating in a 14T MRI scanner. The candidate should possess sufficient knowledge of image processing techniques to finish the task. Some groundwork has already been done. The Max Planck Institute for Biological Cybernetics is located in Tübingen, Germany. Next door to the MPI for Biological Cybernetics lies the MPI for Intelligent Systems. The Max Planck Society is an affirmative action/equal opportunity employer, and encourages applications from qualified women and minority candidates. Please send your CV (in English) to Dr. Yu if interested. Contact info: Dr. Xin Yu Research Group leader Max-Planck Institute for Biological Cybernetics Spemannstrasse 41, 72076 Tübingen, Germany E-mail: xin.yu(a)tuebingen.mpg.de , phone: 49 7071 601-740 Website: www.kyb.tuebingen.mpg.de/research/rg/yugroup/ Dr. Yu has published seminal papers on small animal high field MRI in Nature Neuroscience, Nature Methods, Neuron, PNAS, NeuroImage etc.

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