October 2015 - Comp-neuro - lists.cnsorg.org

Fully-funded PhD position in Computational Neuroscience at the Vision Institute, Paris, France
by angelo.arleo＠inserm.fr 17 Oct '15

17 Oct '15

PHD POSITION IN COMPUTATIONAL NEUROSCIENCE AT THE INSTITUTE OF VISION, PARIS, FRANCE Job description Applications are invited for one PhD position at the Aging in Vision and Action laboratory, Institute of Vision (University Pierre & Marie Curie Sorbonne Universities, INSERM CNRS, Paris, France). The PhD student will model visual-based spatial cognitive functions. She/he will build a spatial learning model based on spiking neural networks accounting for existing knowledge on the neural substrates of spatial memory and navigation in animals and humans. She/he will use this model to study the impact of healthy visual aging on neural coding and adaptation mechanisms mediating spatial orientation and navigation. The PhD student will work hand-in-hand with experimentalists in our laboratory. This project will be carried under the supervision of Angelo Arleo & Denis Sheynikhovich (Institute of Vision, Paris, France). Requirements Applicants should have a strong quantitative background (physics, engineering, computer science, applied mathematics), and a keen interest in reverse-engineering the brain. Knowledge on computational neuroscience, machine learning, image processing and programming languages (Matlab, C or Python) are a plus. The successful candidate is expected to work in an interdisciplinary environment with collaborations with biologists, theoreticians and clinicians. She/he will be awarded a 3-year PhD fellowship from the University Pierre and Marie Curie Sorbonne Universities. Working environment and laboratory The Institute of Vision is one of the top international centers for integrated research on vision and eye diseases. It is located at the heart of Paris, on the campus of the National Hospital Center for Ophthalmology. The Institute of Vision includes multidisciplinary research groups, which share state-of-the-art platforms for human and animal experimentation. It also harbors a clinical investigation center, which fosters truly translational research activity. More information can be found online. The Aging in Vision and Action laboratory aims at evaluating and understanding the functional aspects of the degeneration mechanisms related to visual aging. This research has the potential to produce fundamental knowledge suited for opening to assistive technological developments and rehabilitation solutions. The faculty members of the Aging in Vision and Action laboratory are specialized in visual psychophysics, neurobiology of spatial orientation, neural coding, neurocomputational modeling, and clinical evaluation. The group has access to a wide range of state-of-the-art platforms including eye trackers, motion capture rooms, virtual reality environments, brain imaging, artificial street labs and home labs. How to apply Candidates should send a single pdf file containing a motivation letter, a full CV, and names and contact information of at least two referees, to angelo.arleo(a)inserm.fr. Short listed candidates will be contacted for an interview (either face-to-face or via videoconference). For further inquiries, please contact Angelo Arleo, angelo.arleo(a)inserm.fr, phone: +33 (0)1 53 46 26 52. Best regards, Angelo Arleo Institute of Vision, Aging in Vision and Action Lab, CNRS - INSERM - University Pierre&Marie Curie, 17, rue Moreau F-75012 Paris, France Phone: +33 (0)1 53 46 26 52 Mobile: +33 (0)6 46 84 09 56 Email: angelo.arleo(a)inserm.fr; angelo.arleo(a)upmc.fr

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Postdoctoral opportunities in London and Stockholm
by Harris, Kenneth 16 Oct '15

16 Oct '15

Dear Computational Neuroscientists, I would like to advertise three postdoctoral jobs at the interface of computational, systems, and molecular neuroscience. These positions form part of a new collaboration between UCL, University of Oxford, and the Karolinska Institute. The aim of this project is to understand the great diversity of cell types present in cortex, and their roles in cortical circuits and in the resulting computations. While the three positions require diverse skill sets, all offer the opportunity to work as part of a closely integrated, multidisciplinary team focused on solving one of the most important challenges in current neuroscience. Further details about the project can be found at https://www.ucl.ac.uk/cortexlab/neuromics. Position 1: Molecular analysis of cortical tissue The successful applicant will apply novel multiplexed RNA analysis techniques to cortical tissue, to characterize the molecular fingerprints of distinct cortical cell types. This position would suit a scientist with experience of molecular biology, as well as strong knowledge and interest in systems neuroscience. Prior experience of in situ RNA methods would be beneficial but is not essential for outstanding applicants. The successful applicant will be based initially in Stockholm to learn and refine the novel molecular techniques to be used, and will then move to London to apply them to tissue previously studied in vivo two-photon calcium imaging. Position 2: In vivo recording The successful applicant will use two-photon microscopy with genetically encoded calcium sensors to record from large neuronal populations in subjects performing behavioral tasks, which will then be subjected to post-hoc molecular analysis. In addition to experimental recordings, this position will involve computational work to analyze the large amount of data produced by these experiments. This position would suit a scientist with experience of experimental neurophysiology as well as strong quantitative/computational skills. Prior experience with two-photon microscopy would be beneficial but is not essential for outstanding applicants. The position will be based in London. Position 3: Computational analysis and modeling The successful applicant will develop new computational methods to process the large amounts of data arising from these experiments, and to use it to build computational models of cortical circuit interactions. The data arising from the project is diverse, consisting of images, video, and high-dimensional gene expression vectors. Analysis of this unique data set will require a combination of techniques including digital image processing, machine learning, as well as neural circuit modeling. The position would suit a candidate with a background in computational neuroscience, theoretical physics, computer science, mathematics, or engineering. Prior experience with digital image processing and machine learning techniques would be beneficial but is not essential for outstanding applicants. The position will be based in London. To apply for one of the positions, go to http://www.ucl.ac.uk/hr/jobs, click "Current employment opportunities at UCL", and enter Reference number 1501576 (molecular), 1503273 (recording), or 1503434 (computational). For an informal discussion, please send a CV to kenneth.harris(a)ucl.ac.uk<mailto:kenneth.harris@ucl.ac.uk>. The closing date for applications is November 8th, 2015. --------------------- Kenneth D. Harris Professor of Quantitative Neuroscience Institute of Neurology, Department of Neuroscience, Physiology, and Pharmacology University College London 21 University Street London WC1E 6DE Phone: +44 (0) 20 3108 2410

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Reminder: CFP: MLINI 2015 - 5th NIPS Workshop on Machine Learning and Interpretation in Neuroimaging: Beyond the Scanner
by Irina Rish 16 Oct '15

16 Oct '15

Call for Papers MLINI 2015 - 5th NIPS Workshop on Machine Learning and Interpretation in Neuroimaging: Beyond the Scanner https://sites.google.com/site/mliniworkshop2015/ December 11-12, 2015, Montreal, Quebec, Canada Submission deadline: Monday, October 19th, 2015 Workshop Overview: ----------------------- MLINI workshop focuses on machine learning approaches in neuroscience, neuroimaging, with an extension to behavioral experiments and psychology. This year, our focus is specifically on "Going Beyond the Scanner", which includes making inferences about mental states of a subject from ''cheaper'' (as opposed to fMRI) behavioral data such as subject's speech and/or text, audio, video, EEG and signals collected from various wearable devices. We believe that machine learning has a prominent role in shaping how questions in neuroscience are framed, and that the machine-learning mind set is now entering modern psychology and behavioral studies. It is also equally important that practical applications in these fields motivate a rapidly evolving line or research in the machine learning community. In parallel, there is an intense interest in learning more about brain function in the context of rich naturalistic environments and scenes. Efforts to go beyond highly specific paradigms that pinpoint a single function, towards schemes for measuring the interaction with natural and more varied scene are made. In this context, many controversies and open questions exist. The goal of the workshop is to pinpoint the most pressing issues and common challenges across the fields, and to sketch future directions and open questions in the light of novel methodology. The proposed workshop is aimed at offering a forum that joins machine learning, neuroscience, and psychology community, and should facilitate formulating and discussing the issues at their interface. Motivated by the previous workshops in this series, MLINI ‘11, MLINI’12, and MLINI’13, we will center this workshop around invited talks and a panel discussion. Triggered by the discussions, this year we plan to adapt the workshop topics to a less traditional scope neuroimaging scope and investigate the role of behavioral models and psychology, including topics such as psycholinguistics. Open questions and possible topics for contribution include, but are not limited to, the following: - How can we move towards more naturalistic stimuli, tasks and paradigms in neuroimaging and neuro-signal analysis? - What kind of mental states can be inferred from cheaper and easier to collect data sources (as an alternative to fMRI), such as text, speech, audio, video, EEG, and wearable devices? - How can we leave the lab when acquiring neuroimaging data, towards exploiting mobile acquisition (EEG and NIRS)? - What type of features should be extracted from naturalistic stimuli such as text, voice, etc., to detect specific mental states and/or mental disorders? - How can we combine traditional neuroimaging with naturalistic data collected from a subject or group of subjects? - In general, can we characterize situations when multivariate predictive analysis (MVPA) and inference methods are better suited for brain imaging analysis than more traditional techniques? - Given recent advances of deep learning in image analysis and other applications, a natural question to ask is whether neuroimaging analysis can benefit from such approaches? - How well can functional networks and dynamical models capture the brain activity, and when using network and dynamics information is superior to standard task-based brain activations? Workshop Format: -------------------------- In this two-day workshop we will explore perspectives and novel methodology at the interface of Machine Learning, Inference, Neuroimaging and Neuroscience. We aim to bring researchers from machine learning and neuroscience community together, in order to discuss open questions, identify the core points for a number of the controversial issues, and eventually propose approaches to solving those issues. Each session will be opened by several invited talks, and an in depth discussion. This will be followed by original contributions. Original contributions will also be presented and discussed during a poster session. The workshop will end with a panel discussion, during which we will address specific questions, and invited speakers will open each segment with a brief presentation of their opinion. Paper Submission: -------------------------- We seek for submission of original (previously unpublished) research papers. The length of the submitted papers should not exceed 8 pages in Springer format, excluding the references (LaTeX2e style files are available on the workshop page). Submission of previously published work is possible as well, but the authors are required to mention this explicitly. Previously published work can be presented at the workshop, but will not be included into the workshop proceedings (which are considered peer-reviewed publications of novel contributions). Moreover, the authors are welcome to present their novel work but choose to opt out of the workshop proceedings in case they have alternative publication plans. Important dates: -------------------------- - October 19, 2015 - paper submission - October 30, 2015 - notification of acceptance/rejection - December 11-12, 2015 - Workshop at Montreal, Quebec, Canada , following the NIPS conference Organizing Committee: -------------------------- Guillermo Cecchi (IBM T.J. Watson Research Center) Kai-min Kevin Chang (Language Technologies Institute, Carnegie Mellon University) Moritz Grosse-Wentrup (Max Plank Institute for Intelligent Systems) Georg Langs (Medical University of Vienna, CSAIL, MIT) Brian Murphy (Machine Learning Department, Carngie Mellon University) *Irina Rish (IBM T.J. Watson Research Center) - main contact Leila Wehbe (University of California, Berkeley)

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Aspects of Neuroscience 2015 - invitation for the conference
by Daniel Borek 16 Oct '15

16 Oct '15

Dear Friends, On behalf of the Board of the Neurobiology Student Scientific Association operating at the Faculty of Biology of the University of Warsaw we would like to invite you to *the 5th **International Conference " Aspects of Neuroscience" *that will be held in Warsaw, Poland, from *November 27th to 29th 2015*. As in the following years, this time the Conference also consists of poster and report symposia. November symposia will be devoted to: *Neurobiology, Cognitive Neuroscience, **Clinical Neuroscience* and* Neuroinformatics*. Each of the thematic symposium will be preceded by a lecture delivered by one of the guests, a specialist of a given domain. This year we will have privilege to host such outstanding neuroscientists as *Prof. Gaute Einevoll, Prof. Fernando H. Lopes da Silva, Dr. Tor Stensola, Prof. Wojciech Maksymowicz, Dr. Esha Massand* and *Prof. Peter de Weerd.* The conference is intended for students, doctoral students and research workers related to neuroscience. The student lectures will take place simultaneously in two rooms, in *basic *and *extended* version. The basic session provides an opportunity to present theoretical and review talks for the students who do not conduct their own research yet. We would like the conference to gather academics with different background and level of expertise, who share the common passion for neuroscience. Language of conference is English. *Active registration for the conference is open till November 1st .* More information about conference and the whole Project: www.neuronauka.org/eng Find us on facebook: https://www.facebook.com/AspectsOfNeuroscience?fref=ts Yours sincerely, Daniel Borek Neurobiology Student Scientific Association at the University of Warsaw Organizing Committee of the International Conference of Students and Young Scientists "The Aspects of Neuroscience"

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fully funded PhD position on modelling distraction & mind-wandering at University of Groningen
by Marieke van Vugt RUG 15 Oct '15

15 Oct '15

Dear colleagues, Prof. Niels Taatgen and myself have a joint PhD position available in the Cognitive Modelling group at the University of Groningen, in a project working on models of distraction and mind-wandering. http://www.rug.nl/about-us/work-with-us/job-opportunities/overview?details=… <http://www.rug.nl/about-us/work-with-us/job-opportunities/overview?details=…> Job description The main aim of the project is to investigate when, how, and why we become distracted, and how cognitive training may reduce our tendency to become distracted. In particular, this project will look at different types of distraction (such as rumination) and different circumstances that induce distraction (e.g. cat videos). The PhD student will create models of these different types of distraction, and make predictions of how those affect performance on cognitive tasks. These predictions will be tested in behavioural experiments. The final component of the PhD involves using a novel cognitive modeling framework developed in our group to predict what training methods should reduce distraction, and to test those predictions in cognitive training studies. Qualifications A successful candidate has a master's degree in Cognitive Neuroscience, Cognitive Science, Experimental Psychology, Artificial Intelligence or a related field, experience in cognitive modeling, and has programming skills in MATLAB, C, or Python. Conditions of employment The University of Groningen offers a salary of € 2,125 gross per month in the first year up to a maximum of € 2,717 (salary scale PhD students Dutch University) gross per month in the final year. The appointment is for a period of four years, which should be finished with a PhD examination. The fulltime appointment is temporary for 1 year with the perspective of prolongation for another 3 years. After nine months, an evaluation will take place of the feasibility of successful completion of the PhD thesis within the next three years. A training programme within the Graduate School of Science is part of the agreement. You and your supervisor will make up a plan for additional education and supervising that is specific to your needs. Starting date: as soon as possible. How to apply Send a cover letter (with professional goals and a statement of interest), a curriculum vitae and two letters of recommendation (PDF format) to the job application portal until 29 October / before 30 October 2015 Dutch local time by means of the application form (click on "Apply" below on the advertisement on the university website). Although applications received after the deadline may be considered. Unsolicited marketing is not appreciated. Information For information you can contact: • Dr Marieke van Vugt, m.k.van.vugt(a)rug.nl <mailto:m.k.van.vugt@rug.nl> http://www.ai.rug.nl/~mkvanvugt/ <http://www.ai.rug.nl/~mkvanvugt/> Dr. Niels Taatgen n.a.taatgen(a)rug.nl <mailto:n.a.taatgen@rug.nl> http://www.ai.rug.nl/~niels/ <http://www.ai.rug.nl/~niels/> -------------------------------------------------------------------- Marieke van Vugt, PhD Assistant Professor, Cognitive Modelling Group University of Groningen Bernoulliborg, room 326 Nijenborgh 9 9747 AG Groningen The Netherlands phone: +31-6-5195-4984 (cell) +31-50-363-9487 (office) http://www.ai.rug.nl/~mkvanvugt <http://www.ai.rug.nl/~mkvanvugt> twitter: @mvugt m.k.van.vugt(a)rug.nl <mailto:m.k.van.vugt@rug.nl> / mkvanvugt(a)gmail.com

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BSCS Systems Neuroscience study abroad program at SfN
by Érdi Péter 15 Oct '15

15 Oct '15

BSCS Systems Neuroscience: a study abroad summer program in Budapest for undergraduates in systems neuroscience, computational neuroscience, neurodynamics (http://sysneuro-semester.org/) will exhibit at the SfN Meeting 2015 (Booth #2167). Come and visit us! Kind regards, Péter Érdi General Director

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Fellowships in Theoretical and Computational Neuroscience at the University of Pennsylvania
by Vijay Balasubramanian 15 Oct '15

15 Oct '15

*Postdoctoral Fellowships with the Computational Neuroscience Initiative **at the University of Pennsylvania* The Computational Neuroscience Initiative (CNI) of the University of Pennsylvania seeks exceptional candidates for a CNI Postdoctoral Fellowship. Candidates with strong quantitative skills from a variety of fields including neuroscience, cognitive science, psychology, physics, mathematics, and engineering will be considered. The selected Fellow will join an inter-disciplinary research environment in historic Philadelphia. CNI Fellows will be encouraged to foster collaborative research between multiple labs. The CNI supports interdisciplinary and collaborative research at the frontier of knowledge about the brain, behavior, and the mind. We focus on systems-level approaches that integrate theory and computation with experiment. Our members include faculty, post-docs, and students from multiple programs and departments at Penn. Our research and training spans the three major elements of the field of Computational Neuroscience: 1) Theory – understanding the brain as an information-processing machine; 2) Experiments – providing quantitative methods to aid in the design, implementation, analysis, and interpretation of empirical studies that probe all levels of brain function, from molecules to behavior; and 3) Applications – including robotics, brain-machine interfaces, and new clinical tools. For more information about the CNI, please visit our website at https://cni.upenn.edu. Applications may be submitted by email to compneuro(a)sas.upenn.edu, and should consist of a CV and a cover letter stating the candidate's research experience and reasons for applying to this Fellowship. Please arrange for up to three letters of recommendation to be sent to the same email address with the candidate's name in the subject line. Review of applications will begin on November 15 and continue on a rolling basis until the positions are filled. The University of Pennsylvania values diversity and seeks talented individuals from diverse backgrounds (http://jobs.hr.upenn.edu). Vijay Balasubramanian, Director David Brainard, Co-Director Joshua Gold, Co-Director

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faculty position in applied mathematics at IUPUI
by Leonid Rubchinsky 14 Oct '15

14 Oct '15

Our department has an opening in applied mathematics and computational neuroscientists/mathematical biologist are encouraged to apply: The Department of Mathematical Sciences at IUPUI invites applications for an Assistant or Associate Professor in applied mathematics to begin August 1, 2016. Responsibilities include teaching six courses over the first two years, with at least one course each term, and then four courses a year regularly, maintaining a strong research program, publishing the results of the research, and customary student advising and departmental and university service. The Department has a strong research faculty, many funded research projects and close collaboration with other departments within the School of Science and the Indiana University School of Medicine. Qualifications: Applicants must have an earned doctorate in the mathematical sciences or related areas, a strong research program and be able to teach effectively at the undergraduate and graduate levels. A successful candidate at the Assistant Professor level will be expected to develop and maintain an active, externally-funded research program. Applicants at the Associate Professor level must have a record of significant research accomplishments and external funding. Tenure may be offered to a successful senior candidate, depending on the candidate's qualifications and achievements. The successful candidate will be expected to maintain an active, externally-funded research program. How to Apply: A complete application must include: a letter of interest, curriculum vitae, statements on research plans and teaching philosophy, and a) for an Assistant Professor applicant three letters of recommendation, b) for an Associate Professor applicant, please provide the names of six references. Applications should be submitted electronically via the American Mathematical Society's MathJobs website (https://www.mathjobs.org/jobs/jobs/7582), the position ID is 7582. Screening of completed applications will begin on November 1, 2015, and will continue until all approved positions are filled. *********************** Leonid Rubchinsky, PhD Associate Professor Department of Mathematical Sciences, Indiana University - Purdue University, Indianapolis Stark Neurosciences Research Institute, Indiana University School of Medicine 402 N. Blackford St Indianapolis, IN 46202 leo(a)math.iupui.edu <mailto:leo@math.iupui.edu> http://www.math.iupui.edu/~leo 317-274-9745 317-274-3460 (fax) ***********************

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Doctoral studies in Computational/Theoretical Neuroscience at NYU
by Eero Simoncelli 14 Oct '15

14 Oct '15

New York University is home to a thriving interdisciplinary community of researchers using computational and theoretical approaches in neuroscience. We are interested in exceptional PhD candidates with strong quantitative training (e.g., physics, mathematics, engineering) coupled with a clear interest in brain sciences. A listing of faculty, sorted by their primary departmental affiliation, is given below. Doctoral programs are flexible, allowing students to pursue research across departmental boundaries. Nevertheless, admissions are handled separately by each department, and students interested in pursuing graduate studies should submit an application to the program that best fits their goals and interests. Center for Neural Science (CNS) (deadline: 1 December) [http://www.cns.nyu.edu/doctoral/] • André A. Fenton - Molecular, neural, behavioral, and computationalaspects of memory. • Paul W. Glimcher - Decision-making in humans and animals. Neuroeconomics. • Roozbeh Kiani - Vision and decision-making. • Wei Ji Ma (also in Psychology) - Perception, working memory, and decision making. • Tony Movshon - Vision and visual development. • Bijan Pesaran - Neuronal dynamics and decision making. • Alex Reyes - Functional interactions of neurons in a network. • John Rinzel (also in Mathematics) - Biophysical mechanisms and theory of neural computation. • Robert Shapley - Visual physiology and perception. • Eero Simoncelli - Computational vision and audition. • Xiao-Jing Wang - Computational neuroscience, decision-making and working memory, neural circuits. Neuroscience and Physiology program, School of Medicine (deadline: 1 December) [http://neuroscience.med.nyu.edu/training-programs/graduate-program-neurosci…] • Gyorgy Buzsaki - Rhythms in neural networks. • Dmitry Rinberg - Sensory information processing in the behaving animal. • Mario Svirsky - Auditory neural prostheses; experimental/computational studies of speech production/perception. Psychology, Cognition & Perception program (deadline: 1 December) [http://www.psych.nyu.edu/programs/cp/] • Todd Gureckis - Memory, learning, and decision processes. • David Heeger (also in CNS) - fMRI, computational neuroscience, vision, attention. • Michael Landy - Computational approaches to vision. • Laurence Maloney - Mathematical approaches to psychology and neuroscience. • Gary Marcus - Origins of the human mind. • Denis Pelli - Visual object recognition. • Jonathan Winawer - Visual perception and memory. Mathematics (deadline: 18 December ) [http://math.nyu.edu/degree/phd/] • David Cai - Nonlinear stochastic behavior in physical and biological systems. • David McLaughlin - Nonlinear wave equations, computational visual neuroscience. • Aaditya Rangan - computational neurobiology, numerical analysis. • Charles Peskin - Mathematical biology. • Michael Shelley - Modeling and large-scale computation, computational visual neuroscience. • Daniel Tranchina - Information processing in the retina. • Lai-Sang Young - Dynamical systems, statistical physics, computational modeling and theoretical neuroscience. Computer Science (deadline: 12 December) [http://www.cs.nyu.edu/web/Research/Areas/graphicsvisionui.html] • Davi Geiger - Computational vision and learning. • Yann LeCun - machine learning, hierarchical visual processing, robotics. Economics (deadline: 18 December) [http://econ.as.nyu.edu/page/phd] • Andrew Caplin - Economic theory, neurobiology of decision. • Andrew Schotter - Experimental economics, game theory, neurobiology of decision.

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1st CfP: CMN'16, Seventh International Workshop on Computational Models of Narrative (7 March 2016 / 11-13 July 2016)
by Ben Miller 14 Oct '15

14 Oct '15

* ---FIRST CALL FOR PAPERS--- Seventh International Workshop on Computational Models of Narrative (CMN'16) Advancing the Science of Narrative Special Focus: Computational Narrative and the Humanities a satellite workshop of: Digital Humanities 2016 (DH2016) 11-13 July 2016 Kraków, Poland http://narrative.csail.mit.edu/cmn16/ ---IMPORTANT DATES--- 7 March 2016. Submission deadline. 11 April 2016. Notification of acceptance. 16 May 2016. Final Camera Ready Versions Due. 11-13 July 2016. CMN’16. 11-16 July 2016. DH2016. ---WORKSHOP AIMS--- The workshop series, Computational Models of Narrative (CMN) is dedicated to advancing the computationally-grounded scientific study of narrative. Now in its seventh iteration, the workshop has a tradition of crossing academic borders and bringing together researchers from different disciplines on a common object of study. Narrative provides a model for organizing and communicating experience, knowledge, and culture. Investigations of narrative operations in textual, aural, and visual media have been systematically pursued in the humanities since before the early structural linguistics and folklorist inspired work of the Russian Formalists, and in the computing sciences since before the early cognitive science inspired work on scripts and frames. Research continues on computational approaches across the humanities and sciences. In order to appreciate the various domains and approaches connected to the computationally enabled study of narratives and narrative theory, it is becoming increasingly clear that research in this area requires engagement from many communities of interest. Peer-reviewed full proceedings from CMN’13, ‘14, and ‘15 are each available in the OpenAccess Series in Informatics (OASIcs) published by Schloss Dagstuhl; peer-reviewed proceedings from CMN’11 and CMN’12 were published by AAAI and LREC, respectively. ---SPECIAL FOCUS: COMPUTATIONAL NARRATIVE AND THE HUMANITIES--- This inter-disciplinary workshop will be an appropriate venue for papers addressing fundamental topics and questions regarding narrative. Papers should be relevant to the computational modeling, and scientific or humanistic understanding of narrative. The workshop will have a special focus on how the computational modeling, analysis, or generation of narrative has affected approaches in the humanities for studying and generating narrative in or across textual, aural, or visual media. Possible themes could connect to the representation of narrative, connections between cognition and narrative or knowledge representation and narrative, the use of heuristics to handle complexity, incorporation of insights about human thinking, the use of narrative to organize information in the humanities, the relationship between top-down and bottom-up approaches for narrative understanding, or how narrative is seen to function differently depending upon the medium. Regardless of its topic, reported work should provide insight of use to the scientific understanding or computational modeling of narratives. Discussing technological applications or motivations is not prohibited, but is not required. We accept both finished research and more tentative exploratory work. We invite and encourage submissions either as full papers or position papers, through the workshop's EasyChair website:https://easychair.org/conferences/?conf=cmn16 We also invite you to submit an abstract soon so that we can gauge the number of submissions we can expect. (Submitting an abstract is possible without submitting the full paper at the same time.) Full papers should contain original research and have to fit within 16 pages; position papers can report on work-in-progress, research plans or projects and have to fit within four pages plus one page of references. Illustrative Topics and Questions - How can computational narratives be studied from a humanities point of view? - Are generative models of narrative texts, movies or video games possible, desirable, and useful? - What comprises the set of possible narrative arcs? Is there such a set? How many possible story lines are there? - Is narrative structure universal, or are there systematic differences in narratives from different cultures? - How are narratives affected by the media used to convey them? - What aspects of cross-linguistic work has narrative research neglected? - What opportunities are there for narrative analysis across languages? - What makes narrative different from a list of events or facts? - How do conceptions and models of spatiality or temporality influence narrative and narrative theory? - What are the details of the relationship between narrative and language, image, or sound? - How is narrative knowledge captured and represented? - How are narratives indexed and retrieved? Is there a universal scheme for encoding episodic information? - What shared resources are required for the computational study of narrative? What should a “Story Bank” contain? - What shared resources and tools are available, or how can already-extant resources be adapted to the study of narrative? - What are appropriate formal or computational representations for narrative? - How should we evaluate computational and formal models of narrative? - Can narrative be subsumed by current models of higher-level cognition, or does it require new approaches? - How do narratives mediate our cognitive experiences, or affect our cognitive abilities? - How can narrative systems be applied to problem-solving? - How far are we from a theory of narrative adaptation across media? ---ORGANIZING COMMITTEE--- - Antonio Lieto (University of Turin, Italy) - Ben Miller (Georgia State University, USA) - Rémi Ronfard (Inria, LJK, University of Grenoble, France) - Stephen Ware (University of New Orleans, USA) - Mark A. Finlayson (Florida International University, USA) ---PROGRAM COMMITTEE--- David Elson, Columbia University & Google Floris Bex, Utrecht University Rossana Damiano, University of Turin Kerstin Dautenhahn, University of Hertfordshire Pablo Gervás, Complutense University of Madrid Andrew Gordon, ICT Livia Polanyi, LDM Associates Marie-Laure Ryan, University of Colorado Boulder Tim Tangherlini, UCLA Mariet Theune, University of Twente Atif Waraich, Manchester Metropolitan University Mehul Bhatt, University of Bremen Emmett Tomai, University of Texas-Pan American Neil Cohn, UCSD Inderjeet Mani, Yahoo Labs Loizos Michael, Open University of Cyprus Chris Meister, Hamburg University Fritz Breithaupt, Indiana University Benedikt Löwe, Universität Hamburg *

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