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Postdoctoral position in Multisensory perception and action at New York University Abu Dhabi

by Robert Volcic

The Psychology Department at New York University Abu Dhabi is inviting applications for a fully funded postdoctoral associate position in the area of Psychology with interests in human perceptual and motor systems. The postdoctoral associate will work under the supervision of Dr. Robert Volcic (http://volcic.github.io) and will carry out behavioral studies on human multisensory perception (mainly vision and touch) and action (reaching and grasping). The lab will be equipped with a state of the art system for 3D visualization, a head tracking system, and a motion capture system for monitoring reaching and grasping movements. Moreover, the postdoctoral associate will have access to an eye movement tracker, and to fMRI and EEG facilities. Applicants must hold (or be close to completing) a Ph.D. in Psychology, Cognitive Science, Neuroscience, Biology, or related fields. Prior experience in vision/haptic/motor research is important as is programming efficiency. Applications will be accepted immediately and will be considered on a rolling basis. Please visit our website at http://nyuad.nyu.edu/about/careers/faculty-positions.html for instructions and information on how to apply. To be considered, all applicants must submit a cover letter, a curriculum vitae with full publication list, a statement of research interests, representative publications, expected date of availability, and names of two referees, all in PDF format. If you have any questions, please e-mail robert.volcic(a)nyu.edu. The preferred start date is September 1st, 2016. A later start date is possible based on the needs of the applicant. The duration of employment is for two years with the possibility to renew. This position is based in Abu Dhabi (U.A.E.). The terms of employment are competitive and include housing and other benefits. About NYUAD: New York University has established itself as a Global Network University, a multi-site, organically connected network encompassing key global cities and idea capitals. The network has three foundational degree-granting campuses: New York, Abu Dhabi, and Shanghai, complimented by a network of eleven research and study-away sites across five continents. Faculty and students will circulate within this global network in pursuit of common research interests and the promotion of cross-cultural and interdisciplinary solutions for problems both local and global. Entering its sixth year, NYU Abu Dhabi has recruited a cohort of faculty who are at once distinguished in their research and teaching. Our students are drawn from around the world and surpass all traditional recruitment benchmarks, both US and global. NYU Abu Dhabi’s highly selective liberal arts enterprise is complimented by an institute for advanced research, sponsoring cutting-edge projects across the Arts, Humanities, Social Sciences, Sciences, and Engineering. EOE/Minorities/Females/Vet/Disabled

Feb. 26, 2016

CoSMo 2016 registration open

by Gunnar Blohm

*Sixth Annual Computational Sensory-Motor Neuroscience Summer School (CoSMo 2016)* University of Minnesota, Minneapolis, MN, USA July 31 - August 14, 2016 We would like to invite you to join us for the sixth annual Computational Sensory-Motor Neuroscience Summer School. The course is about experimental, computational and medical aspects of sensory-motor neuroscience with a focus on active learning. Covered topics include multi-sensory integration, motor learning & control, computational methods, sensory-motor transformations and neural coding / decoding. An important focus is on doing research as opposed to just hearing about it. Each teaching module will take up two days with morning lecture sessions. Afternoon sessions involve hands-on Matlab programming, simulation and data-analysis. Newly acquired computational tools can also be applied in 2-week evening group research projects. The course is aimed at students and post-doctoral fellows from diverse backgrounds including Life Sciences, Psychology, Computer Science, Physics, Mathematics and Engineering. Basic knowledge in calculus, linear algebra and Matlab is expected. Enrollment will be limited to 40 trainees. *Application deadline: Apr 11, 2016* For more information and to apply, please go to <http://www.compneurosci.com/CoSMo/>http://www.compneurosci.com/CoSMo/ Scholarship information and the application form can be found here: http://www.compneurosci.com/CoSMo/application.html The school is co-organized by Drs Gunnar Blohm, Paul Schrater, and Konrad Körding. This year, it receives funding from the NIH through a Brain Initiative R25 grant and from The Brain Canada Foundation. -- ------------------------------------------------------- Dr. Gunnar BLOHM Associate Professor in Computational Neuroscience Association for Canadian Neuroinformatics and Computational Neuroscience (CNCN) Centre for Neuroscience Studies, Departments of Biomedical and Molecular Sciences, Mathematics & Statistics, and Psychology, School of Computing, and Canadian Action and Perception Network (CAPnet) Queen’s University 18, Stuart Street Kingston, Ontario, Canada, K7L 3N6 Tel: (613) 533-3385 Fax: (613) 533-6840 Email: Gunnar.Blohm(a)QueensU.ca Web: http://www.compneurosci.com/

Feb. 26, 2016

Neuroimaging Data Analyst Position at the University of Illinois at Chicago (Summer/Fall 2016)

by Sylvia Morelli

Drs. Sylvia Morelli and K. Luan Phan are considering applications for a neuroimaging data analyst to work jointly in the Empathy and Social Connection Lab (http://www.morellilab.com/ <http://www.morellilab.com/>) and the Mood and Anxiety Disorders Research Program (http://www.psych.uic.edu/research/mood-and-anxiety-disorders-research-progr… <http://www.psych.uic.edu/research/mood-and-anxiety-disorders-research-progr…>) at University of Illinois at Chicago. The data analyst will have the opportunity to analyze several data sets related to social cognitive affective neuroscience (e.g., empathy, social networks, reward learning, decision-making, emotional processing and regulation, fear learning and extinction) in healthy and psychiatric populations (e.g., anxiety and depression), as well as pharmacotherapy and psychotherapy treatment response. The analyst will implement the latest approaches developing in the field of imaging neuroscience — including but not limited to pattern classification, prospective prediction, machine learning, effective connectivity, connectomics/graph theory, computational modeling – and train others (faculty, postdocs, graduate students) on conventional and new analysis techniques. The position will involve analyzing data across multiple modalities including self-report, behavior, psychophysiology (SCR, startle), EEG/ERP, DTI, structural MRI and functional MRI – at single-unit and integrated levels. The data analyst will work amongst diverse investigators across disciplines (e.g., neuroscience, psychology, psychiatry). Successful applicants will have a Masters- or PhD-level degree in neuroscience, psychology, computer science, statistics/biostatistics or mathematics and/or a record of extensive experience in analyzing structural and functional MRI data. Applicants should also be fluent in SPM (or AFNI/BrainVoyager), statistical packages (e.g., Matlab and R), and programming languages (e.g., Unix). Excellent communication (verbal and written) and organizational skills are required. The position will be fully funded for at least 2 years with the potential for a longer-term position. We will review applications beginning March 1, until the position is filled. Applicants should send a CV, a statement describing their qualifications for the position and relevant experience, and the names of 2-3 references that may be contacted for a recommendation to Dr. Morelli (smorelli(a)uic.edu <mailto:smorelli@uic.edu>) and Dr. Phan (klphan(a)psych.uic.edu <mailto:klphan@psych.uic.edu>).

Feb. 25, 2016

2 Postdoc positions in modeling dendritic integration and synaptic plasticity

by Walter Senn

Dear Colleagues, dear all, We are inviting applications for 2 postdoc positions (for at least 2 years, earliest start April 1, 2016) in computational neuroscience at the University of Bern, Switzerland. Our research is devoted to models of synaptic plasticity and dendritic integration that serve as a computational paradigm for learning in neuronal networks. We have recently suggested to consider “Learning by the dendritic prediction of somatic spiking” (Neuron 2014) that assigns an intrinsic computational task to neurons and dendrites. This concept will be extended by including dendritic nonlinearities and considering networks of such neuronal prediction elements. The 2 positions are: 1) Postdoc for modeling dendritic integration. We have shown how the error-backpropagation algorithm translates to a dendritic tree that displays NMDA-spikes in individual dendritic branches (PLoS Comp Biol 2016). Along these ideas a biophysical model of dendritic integration will be worked out that makes also contact to Bayesian integration. 2) Postdoc for modeling synaptic plasticity and learning in networks. The neurons as intrinsic prediction elements will be connected to form a network that mimics various learning tasks and that is particularly suited for imitation learning. You will profit from generous travel funding and from collaborations in- and outside the Human Brain Project, and you will also enjoy the beautiful city and surrounding of Switzerland’s capital. Ideal candidates have a strong background in computational neuroscience and machine learning. Please send CV, letter of motivation, and publication list by March 11 to Walter Senn (senn(a)pyl.unibe.ch) and Sabine Herzog (herzog(a)pyl.unibe.ch) With best wishes Walter Senn PS: For recent work of our group see http://www.physio.unibe.ch/~senn/neuroscience.aspx

Feb. 25, 2016

Call for Applications: Paul J. Salem Postdoctoral Scholars in Computational Brain Science – Brown Institute for Brain Science

by Michael J Frank

The Brown Institute for Brain Science Initiative for Computation in Brain and Mind <http://compneuro.clps.brown.edu> is seeking applicants for the Paul J. Salem Postdoctoral Scholarships in Brain Science. The postdoctoral scholars will lead an exciting new project at the interface between machine learning and neuroscience. In particular, we are looking for computational neuroscientists interested in the application and development of novel machine learning methods for the analysis of neural recordings. Candidates are expected to have a solid background in modern machine learning and signal processing as well as demonstrated interest in experimental neuroscience. In addition, to conducting primary research with large neural data sets, candidates will be involved in the mentoring of students, and the organization of workshops. Candidates are expected to interact closely with the Neurotechnology group within the Brain Institute. The initial appointment is for 12 months with the potential to renew. The salary is competitive. The start date is negotiable although funding is available now. Research group: *The Initiative for Computation in Brain and Mind (ICBM;* <http://compneuro.clps.brown.edu>http://compneuro.clps.brown.edu) which began Fall 2013 within the Brown Institute for Brain Science, creates an exciting intellectual environment that fosters synergistic collaborations across departments. Groups affiliated with the initiative work on two core levels of computation. The first level focuses on theoretical neuroscience, including computational perception, control over action and learning, and fundamental questions in neuronal networks (synaptic plasticity, circuits, networks, oscillations). The second level focuses on applications and neurotechnology, including brain-machine interfaces, advanced neural data analysis, computer vision, computational psychiatry, and robotics. ICBM has 16 core computational faculty (http://compneuro.clps.brown.edu/people/) spanning six departments, and many more faculty who incorporate computation for theory development, analysis, or both. Computational neuroscience tools at Brown have been applied in projects including brain-machine control of robotic arms in paralyzed humans; models of visual systems in biological organisms and their innovative application for classifying animal behavioral patterns; predicting and quantifying effects of genetics, disease, medications, and brain stimulation on motor and cognitive function; identification of the source of neural rhythms and their roles in sensorimotor function; development of fundamental theories of brain plasticity, and learning; state-of-the art models of machine learning and reinforcement learning in computer science. The Brown Institute for Brain Science (BIBS) advances multidisciplinary research, technology development, and training in the brain sciences. BIBS unites more than 100 faculty from departments across Brown, spanning basic and clinical departments, and physical and biological sciences. BIBS creates opportunities and essential support to advance interdisciplinary research efforts among these groups including training funds to support interdisciplinary scholarship and research. Requirements: Candidates must have received their PhDs within 3 years of the application deadline, and will work under the supervision of faculty members at Brown University who are affiliated with the Initiative for Computation in Brain and Mind. They must have a strong background in computational neuroscience and machine learning, with a track record of relevant publications at top venues (such as NIPS or ICML). Excellent programming skills are required (C/C++/Matlab/Python). Application: Please send your applications by email to cbm-info(a)brown.edu. Please include a brief statement of interests, a curriculum vitae, a list of publications and 2-3 letters of reference (addressed directly to cbm-info(a)brown.edu) There is no deadline for the application but applicants are encouraged to apply as soon as possible as the position will be filled as soon as a suitable applicant is found. ------------------------------ Michael J Frank, PhD, Professor Laboratory for Neural Computation and Cognition Brown University http://ski.clps.brown.edu (401)-863-6872

Feb. 25, 2016

[IEEE ICCI*CC'16:] RE: IEEE ICCI*CC'16 Update

by Yingxu Wang

Dear Colleague, The 15th IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC'16) will be held at Stanford University, CA, USA during Aug. 22-23, 2016 (http://www.ucalgary.ca/icci_cc/iccicc-16) The IEEE ICCI*CC series is a flagship conference of its field sponsored by IEEE Computer, Computational Intelligence, and SMC Societies. It forms a transdisciplinary field that studies the internal information processing mechanisms of the brain, the underlying abstract intelligence (aI) theories and denotational mathematics, and their engineering applications in cognitive computing, computational intelligence, and cognitive systems. Paper submission is via Easy Chair at: https://www.easychair.org/conferences/?conf=iccicc2016. Submission deadline is approaching on Feb. 29, 2016. Special session papers may get a grace period by coordination of the session chairs. The conference will be featured by a number of keynote speeches that highlight the cutting-edge theories and novel technologies for cognitive systems and computational intelligence inspired by the brain such as: a) Natural Language Understanding vs. Natural Language Precisiation Prof. Lotfi A. Zadeh, UC Berkeley, USA b) Hebbian Learning and the LMS Algorithm Prof. Bernard Widrow, Stanford \university, USA c) Deep Learning and Deep Thinking by Cognitive Robots and Computational Intelligent Systems Prof. Yingxu Wang, University of Calgary, Canada You are welcome to submit a paper to IEEE ICCI*CC'16 or to organize a special session related to the theme of the conference. The Proceedings of ICCI*CC'16 will be published by IEEE CS Press and indexed by EI, DBLP, and IEEE eXplore. Selected papers from the proceedings will be published in leading international journals and IEEE transactions. We look forward to having an opportunity to meet you at IEEE ICCI*CC'16. Best regards, Prof. Yingxu Wang IEEE ICCI*CC'16 Co-Chair _______________________________________________ This message was sent to all subscribers of ieeeicci13-L To unsubscribe, see instructions at: http://www.ucalgary.ca/it/email/mailman E-mail: ieeeicci13-L(a)mailman.ucalgary.ca Homepage: http://mailman.ucalgary.ca/mailman/listinfo/ieeeicci13-l

Feb. 24, 2016

1st Call for Abstracts: the 8th Int'l Workshop on Guided Self-Organization (GSO-2016, Cancun, Mexico, 7 July 2016)

by Joseph Lizier

Dear All, This is an announcement and Call for Abstracts for the Eighth International Workshop on Guided Self-Organization (GSO-2016) to be held on July 7, 2016 at ALIFE XV in Cancun, Mexico: http://guided-self.org/gso8/ The GSO Workshop will bring together invited experts and researchers in self-organizing systems, with particular emphasis on the information- and network-theoretic foundations of GSO and the information dynamics of complex systems. The following topics are of special interest: information-theoretic measures of complexity, nonlinear dynamics, complex networks, information-driven self-organization (IDSO), applications of GSO to complex networks, distributed computation, machine learning, swarm intelligence, bio-inspired systems, computational neuroscience, systems biology, cooperative and modular robotics, etc. Submissions to the workshop are extended abstracts (one page). If interested in participating, please send an extended abstract (by May 29, 2016) by email to: prokopenko.mikhail(a)gmail.com The notifications are expected by June 10, 2016. Authors of accepted submissions will present the content to the workshop. We expect that selected papers of GSO-2016 will be published in a special issue (research topic) of Frontiers of Robotics and AI, or Artificial Life journals. Please consult above website for more information. Best wishes, Mikhail Prokopenko Carlos Gershenson Daniel Polani <apologies for possible cross-posting>

Feb. 24, 2016

Postdoc in Bordeaux, France. Application deadline 01/04/2016.

by Nicolas P. Rougier

Postdoc in Bordeaux, France at the Neurodegenerative Diseases Institute <http://www.imn-bordeaux.org/en/> Application deadline 01/04/2016. Details & application at INRIA website <http://www.inria.fr/en/institute/recruitment/offers/post-doctoral-research-…>. 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 <http://rescience.github.io/>), 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. Nicolas P. Rougier

Feb. 24, 2016

Postdoc and PhD positions and further opportunities in the Bernstein group “Neural network dynamics and computation” (Raoul-Martin Memmesheimer)

by Memmesheimer, Raoul M.

Postdoc and PhD positions and further opportunities in the Bernstein group “Neural network dynamics and computation” (Raoul-Martin Memmesheimer) There are fully funded positions available at the PhD and at the postdoctoral researcher level in my future group at FIAS Frankfurt, with an envisaged starting date of July 2016. At an earlier career stage, you can write your Bachelor’s or Master’s thesis, or do a short-term internship to get to know research in theoretical neuroscience/neurophysics. Depending on the project and the need, financial support is available. Optimal backgrounds of applicants include theoretical neuroscience and/or theoretical physics, computer science, mathematics, quantitative biology. Under the overarching topic “Bridging the scales: Spiking in artificial and biological neural computation”, we aim to develop spiking networks for the solution of artificial intelligence problems and we aim to understand healthy and pathological spike patterns. Your theoretical work in the group may delineate principles underlying effective computations with spiking neurons, investigate the origins of pathological dynamics in the hippocampus, or explore the impact of coupling nonlinearities found in this brain region. Some of the planned projects are directly guided by recent experimental results and aim at explanations that have been requested by experimentally working collaborative partners. Others have a higher level of abstraction and explore rather principal questions. For the different projects, collaborative partnerships have been arranged with experimentally working scientists at Heidelberg University (group of A. Draguhn) and Bonn University (group of H. Beck), and with theoretically working groups at Columbia University (group of L. Abbott), Radboud Unversity (group of H.J. Kappen) and FIAS Frankfurt (group of Jochen Triesch). Of course I am also happy to discuss your own ideas for your future research in the group. If you are interested in more information, see my website (www.memmesheimer.net) contact me via email (rm3354(a)cumc.columbia.edu) at CoSyne 2016, or, if you are in the neighborhood, drop by at my office at Columbia University. -- Raoul-Martin Memmesheimer Center for Theoretical Neuroscience, Columbia University, New York, USA Web: www.memmesheimer.net Phone: +1 (646) 774 7329 Email: rm3354(a)cumc.columbia.edu<mailto:rm3354@cumc.columbia.edu>

Feb. 23, 2016

2016 Summer workshop on the dynamic brain: applications open

by Adrienne Fairhall

View online Announcing the Summer Workshop on the Dynamic Brain, co-hosted 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. This intensive, two-week, projects-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. The workshop will include data analyses, Python and other software boot-camps, and lectures, taught by faculty from the University of Washington and the Allen Institute for Brain Science, on topics focused on the mammalian cortex and closely associated satellite structures. Subscribe | Unsubscribe | Feedback | Privacy Policy Copyright ©2016. Allen Institute for Brain Science. All Rights Reserved.

Feb. 23, 2016