- Comp-neuro - lists.cnsorg.org

Seeking Grad students --Fall 2018
by Stephen Jose Hanson Feb. 22, 2018

Feb. 22, 2018

Seeking Cognitive and/or Computational Neuroscience Graduate Students Accepting applications Fall 2018. Rutgers University. We are seeking graduate students interested in the study of cognitive processes (e.g, memory, attention, language, category learning, Neural Networks) using neuroimaging techniques and computational modeling (Deep Learning). Our lab is focused on understanding the dynamics underlying brain response during rest (resting state) and during the performance of cognitive tasks. Within this overall framework, we have conducted research with both neurotypical and clinical populations (e.g., addiction, ASD, GAD), and have conducted studies focused on memory, language processing, preference decisions, face processing, and event perception. Our lab was jointly involved in the development of MVPA as well as IMaGES and other brain connectivity methods (lab has been continuously funded by NSF, McDonnell Foundation and NIH). Dr. SJ Hanson (Psychology, RUBIC) and Dr. C Hanson (CMBN, RUBIC) directs the lab and participates in both the Psychology graduate program and the Behavioral Neuroscience program. Dr. SJ Hanson is also Director of the Rutgers University Brain Imaging Center (RUBIC http://rubic.rutgers.edu) RUBIC houses a Siemens 3T Trio MR scanner to collect MR data and a variety of resources are available to complete any MR neuroimaging study. The lab also has a compute cluster with dual P100 GPUs as well as access to larger clusters available on various campuses. The campus is well serviced by train, subway, and bus service and is surrounded by a diversity of shops and restaurants. Manhattan is a twenty minute train ride from the Newark Penn Station and offers world class cultural and entertainment opportunities. For further inquiry or arrange a visit to our lab and RUBIC please send email to jose(a)rubic.rutgers.edu

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Workshop: Dynamics of learning and computations in neuronal circuits, June 27-29, 2018, Göttingen
by farzad Feb. 22, 2018

Feb. 22, 2018

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funded postdoc positions: mechanisms of perception
by Haider, Bilal Feb. 22, 2018

Feb. 22, 2018

Postdoctoral position: Synaptic mechanisms controlling perception The Haider Lab<haider.gatech.edu> in the Dept. of Biomedical Engineering (BME) at Georgia Tech & Emory University seeks a highly motivated and skilled postdoctoral fellow for a 3-year funded project examining synaptic and network mechanisms supporting sensory perception. The project offers significant opportunity to learn cutting-edge research techniques in vivo, including neural population recording with high-density silicon electrodes, optogenetic circuit manipulation, and whole-cell patch-clamp recording in mice performing visual behaviors. The ideal candidate has expertise in electrophysiology in vitro or in vivo, and quantitative skill in data acquisition and analysis (preferably with MATLAB). Candidates should have excellent written and verbal communication skills, an inquisitive mindset, and enthusiasm to work in a multi-disciplinary team. The position is funded for up to 3 years, pending satisfactory performance upon annual review. We are enthusiastic to form a diverse, international research group. All candidates will be mentored to obtain independent funding as part of their career development. There is a strong, multidisciplinary concentration of labs focusing on Neuroscience @ GT<http://neuro.gatech.edu/> and at Emory<http://biomed.emory.edu/PROGRAM_SITES/NS/>. Atlanta is vibrant, green, and one of the most affordable and livable major cities of the US. Applications should include a CV, a brief statement of research goals, expected date of availability, and names and contact information of three references. Please email these materials to bilal.haider(a)bme.gatech.edu<mailto:bilal.haider@bme.gatech.edu>. The position is available starting March 2018. The Wallace H. Coulter Dept. of Biomedical Engineering<https://www.bme.gatech.edu/> at Georgia Tech and Emory University is an equal opportunity employer committed to diversity. The Department is a unique enterprise, spanning two of the top Engineering and Medical institutes in the country. This environment offers unparalleled facilities and resources for the pursuit of understanding neural circuits and their relationship to behavior and neurological dysfunction. Further information and recent lab publications can be found at haider.gatech.edu<file:///C:/Users/bilal/Dropbox/Docs/GTech%20Docs/haider.gatech.edu> Thank you Bilal Haider, Ph.D. Assistant Professor Coulter Dept. of Biomedical Engineering Georgia Tech & Emory University 313 Ferst Drive, Suite 3104 Atlanta, GA 30332 tel: +1 404 385 4935 fax: +1 404 385 5044 site: haider.gatech.edu<http://haider.gatech.edu/> twitter: @haiderlab<https://twitter.com/haiderlab>

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MODVIS 2018 - call for papers
by Yalda Mohsenzadeh Feb. 21, 2018

Feb. 21, 2018

We are pleased to announce that Eero Simoncelli (NYU, HHMI) will be keynote speaker at the 7th annual VSS satellite workshop on Computational and Mathematical Models in Vision (MODVIS). MODVIS 2018 will be held May 16-18, at the Tradewinds Resort in St. Pete Beach, Florida (USA), immediately preceding the annual meeting of the Vision Sciences Society. Submissions consist of single-page extended abstracts that may contain figures and equations, which will be published on the Purdue e-Pubs system. Abstract submission will open on January 8th, 2017, and close on March 4th. For complete details, please visit the MODVIS web site at https://www.conf.purdue.edu/modvis/. on behalf of the MODVIS organizing committee: Yalda Mohsenzadeh (MIT) Jeff Mulligan (NASA Ames Research Center) Zygmunt Pizlo (UC Irvine) Anne Sereno (Purdue University) Qasim Zaidi (SUNY College of Optometry) Michael Rudd (University of Washington)

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Valentino Braitenberg Award for Computational Neuroscience - Call for Nominations
by Alexandra Stein Feb. 21, 2018

Feb. 21, 2018

Dear Colleagues, The Bernstein Association for Computational Neuroscience invites nominations for the Valentino Braitenberg Award for Computational Neuroscience. The Bernstein Association for Computational Neuroscience presents the award biennially to a scientist in recognition of outstanding research that contributes to the understanding of the functioning of the brain. The major criterion for the award is the impact or potential impact of the recipient's research on the field of brain science. In the spirit of Valentino Braitenberg's own research, special emphasis is given to theoretical studies elucidating the functional implications of brain structures and their neuronal network dynamics. The awardee receives €5.000 prize money, donated by the Autonome Provinz Bozen Südtirol, as well as an invitation to the Bernstein Conference 2018 (including registration fee, travel- and accommodation expenses). The award will be presented together with a Golden Neuron pin in a special award ceremony at the Bernstein Conference, followed by a lecture of the Braitenberg Awardee. Nominations may be submitted by scientists working in the field of computational neuroscience and should include the following documents: - One-page laudation, in which the scientific work of the candidate is honored with regard to the award criteria - CV and list of publications Deadline for nominations is April 30, 2018 by email to a.stein(a)fz-juelich.de<mailto:a.stein@fz-juelich.de> Please note that self-nominations are not permitted. The call for nominations can be found under the following URL: www.nncn.de/en/bernstein-conference/2018/braitenberg_award<http://www.nncn.de/en/bernstein-conference/2018/braitenberg_award> For inquiries please contact a.stein(a)fz-juelich.de<mailto:a.stein@fz-juelich.de>. Best regards, Alexandra Stein -- Dr. Alexandra Stein Head of Bernstein Coordination Site Bernstein Network Computational Neuroscience | Bernstein Coordination Site (BCOS) Branch Office of the Forschungszentrum Jülich at the University of Freiburg Hansastr. 9A | 79104 Freiburg, Germany phone: (+49) 0761 203 9583 mobile: (+49) 0151 67114645 mail: a.stein(a)fz-juelich.de<mailto:a.stein@fz-juelich.de> web: www.bernstein-network.de<http://www.bernstein-network.de> Twitter: NNCN_Germany YouTube: Bernstein TV Facebook: Bernstein Network Computational Neuroscience, Germany LinkedIn: Bernstein Network Computational Neuroscience, Germany ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ 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- ACM-THRI Special Issue on Representation Learning for Human and Robot Cognition
by Amir Aly Feb. 21, 2018

Feb. 21, 2018

*ACM Transactions on Human-Robot Interaction (T-HRI) * CALL FOR PAPERS **Apologies for cross posting ** We are happy to call for papers for the journal special issue: *"Representation Learning for Human and Robot Cognition"* *Webpage: **https://thri.acm.org/CFP-RLHRC.cfm <https://thri.acm.org/CFP-RLHRC.cfm> * <http://cognitive-mirroring.org/en/events/hai2017_workshop/> *I. Aim and Scope *Intelligent robots are rapidly moving to the center of human environment; they collaborate with human users in different applications that require high-level cognitive functions so as to allow them to understand and learn from human behavior within different Human-Robot Interaction (HRI) contexts. To this end, a stubborn challenge that attracts much attention in artificial intelligence is representation learning, which refers to learning representations of data so as to efficiently extract relevant features for probabilistic, nonprobabilistic, or connectionist classifiers. This active area of research spans different fields and applications including speech recognition, object recognition, emotion recognition, natural language processing, language emergence and development, in addition to mirroring different human cognitive processes through appropriate computational modeling. Learning constitutes a basic operation in the human cognitive system and developmental process, where perceptual information enhances the ability of the sensory system to respond to external stimuli through interaction with the environment. This learning process depends on the optimality of features (representations of data), which allows humans to make sense of everything they feel, hear, touch, and see in the environment. Using intelligent robots could open the door to shed light on the underlying mechanisms of representation learning and its associated cognitive processes so as to take a closer step towards making robots able to better collaborate with human users in space. This special issue aims to shed light on cutting edge lines of interdisciplinary research in artificial intelligence, cognitive science, neuroscience, cognitive robotics, and human-robot interaction, focusing on representation learning with the objective of creating natural and intelligent interaction between humans and robots. Recent advances and future research lines in representation learning will be discussed in detail in this journal special issue. *II. Potential Topics* Topics relevant to this special issue include, but are not limited to: - Language learning, embodiment, and social intelligence - Human symbol system and symbol emergence in robotics - Computational modeling for high-level human cognitive functions - Predictive learning from sensorimotor information - Multimodal interaction and concept formulation - Language and action development - Learning, reasoning, and adaptation in collaborative human-robot tasks - Affordance learning - Cross-situational learning - Learning by demonstration and imitation - Language and grammar induction in robots *III. Submission* ACM Transactions on Human-Robot Interaction is a peer-reviewed, interdisciplinary, open-access journal using an online submission and manuscript tracking system. To submit your paper, please: - Go to https://mc.manuscriptcentral.com/thri and login or follow the "Create an account" link to register. - After logging in, click the "Author" tab. - Follow the instructions to "Start New Submission". - Choose the submission category “*SI: Representation Learning for Human and Robot Cognition*”. *IV. Timline* - Deadline for paper submission: July 1, 2018 - First notification for authors: September 15, 2018 - Deadline for revised papers submission: November 15, 2018 - Final notification for authors: January 15, 2019 - Deadline for submission of camera-ready manuscripts: March 1, 2019 - Expected publication date: May 2019 *V. Guest editors* Takato Horii, The University of Electro-Communications, Japan ( takato(a)uec.ac.jp) Dr. Amir Aly, Ritsumeikan University, Japan (amir.aly(a)em.ci.ritsumei.ac.jp) Dr. Yukie Nagai, National Institute of Information and Communications Technology (NICT), Japan (yukie(a)nict.go.jp) Prof. Takayuki Nagai, The University of Electro-Communications, Japan ( nagai(a)ee.uet.at.jp) --------- *Amir Aly, Ph.D.* Senior Researcher Emergent Systems Laboratory College of Information Science and Engineering Ritsumeikan University 1-1-1 Noji Higashi, Kusatsu, Shiga 525-8577 Japan

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PhD Opening - TEMPORAL NETWORKS: FROM NETWORK THEORY TO BRAIN SCIENCE AND NEUROLOGY
by Demian Battaglia Feb. 20, 2018

Feb. 20, 2018

We are seeking for excellent and motivated candidates for a PhD project based at Aix-Marseille University (AMU, southern France) focusing on: TEMPORAL NETWORKS: FROM NETWORK THEORY TO BRAIN SCIENCE AND NEUROLOGY The student will be jointly directed by Alain Barrat (AMU, Center for Theoretical Physics) and Demian Battaglia (AMU, Institute for Systems Neuroscience). The project, with a strong interdisciplinary component, aims at developing new techniques for the extraction and analysis of time-dependent networks of functional connectivity, based on time-series of neural activity, and, in particular, of human intracranial recordings during resting state, task conditions and stimulation. Mean-field whole brain models may also be used to explore the link between Functional Connectivity Dynamics and the underlying collective thalamocortical dynamics. Any application must be formally submitted on a devoted Web Portal: https://doc2amu.univ-amu.fr/en/temporal-networks-from-network-theory-to-bra… DEADLINE: April 9th, 2018 at 23:59 (Paris Time) The selection will occur through a TWO-STEPS EVALUATION, involving a first pre-selection (2 May 2018) and then a competitive oral examination of the retained applicants (31 May - 1 June 2018). ELIGIBILITY CRITERIA: - You must be in the first four years (full-time equivalent research experience) of your research career (career breaks excluded) - You must be at the time of recruitment, in possession/or finalizing the master degree or equivalent - You must be available to engage in the programme at the starting date (October 1st, 2018) - At the time of recruitment, not to have resided or carried out their main activity (work, studies, etc.) in France for more than 12 months in the 3 years immediately prior to the reference date (October 1st, 2018) The fellowship of the successful PhD candidate will be co-funded by the prestigious Marie Skłodowska-Curie COFUND action within the H2020 Research and Innovation programme of the European Union. Within this programme, the PhD fellows will sign a three-year work contract with numerous advantages: - PhD fellowships above that of a standard French PhD contract (approximately 1625€/month net) - A 500€ travel allowance per year for the fellows to travel between Marseille and their place of origin. - Approx 10’000 € financial support for international research training, conferences and research costs - Tailored training and personalised mentoring within the excellence graduate schools of Aix-Marseille University (NEUROSCHOOL in Neuroscience and CENTURI in Physics of complex living systems) Doctoral fellows will also benefit from support in the administrative procedures, reserved rooms in university housing, several activities to promote integration in the local student life and cultural activities, French language courses covered by the fellowship, etc. For any inquiry feel free to contact us: Demian Battaglia (demian.battaglia(a)univ-amu.fr) Alain Barrat (alain.barrat(a)cpt.univ-mrs.fr)

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Information Theory Tutorial
by James V Stone Feb. 20, 2018

Feb. 20, 2018

For those interested in a gentle introduction to information theory, please see: Information Theory: A Tutorial Introduction by James V Stone Abstract Shannon's mathematical theory of communication defines fundamental limits on how much information can be transmitted between the different components of any man-made or biological system. This paper is an informal but rigorous introduction to the main ideas implicit in Shannon's theory. An annotated reading list is provided for further reading. A pdf file of the article can be downloaded from the Cornell University Library archive: https://arxiv.org/abs/1802.05968 Comments and corrections welcome. regards, James V Stone -- Dr James V Stone Honorary Reader, Sheffield University, UK. http://jim-stone.staff.shef.ac.uk/BookBayes2012/books_by_jv_stone/index.html

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Carolina Neurostimulation Conference - May 21-23, 2018, Chapel Hill NC
by Sankar Alagapan Feb. 20, 2018

Feb. 20, 2018

Dear Colleagues, It is with great pleasure that we invite you to participate in the 1st Carolina Neurostimulation Conference (CNC) to be held *May 21-23, 2018 in Chapel Hill, NC, USA*. This is a premier conference for those working to advance our understanding of dynamics of the brain, body, and behavior, investigating the response to stimulation, and translating discoveries into clinical applications. Hosted by the Carolina Center for Neurostimulation <http://www.carolinaneurostimulation.org/>, CNC serves as a platform for networking for all researchers and specialists and exchanging ideas about the latest discoveries and innovations in brain stimulation and clinical treatments. We have a great lineup of speakers including keynotes from *Dr. Sarah Lisanby (NIH) *and* Dr. Kaspar Schindler (Inselspital)*. Central topics for discussion and presentations include TMS, tACS, tDCS, and methods such as modeling, imaging, analysis, and devices. * ------------------------------ * *Registration:* Please register at the link provided here <http://www.neurostimcarolina.org/registration.html> . The deadline for Registration is *May 1st 2018* Regular (Faculty, Postdocs, Industry Professionals) $165 Students (Graduate, Undergraduate) $95 UNC Members *(Registration required)* Free For a full program, and information regarding registration, travel, and accommodations please visit our conference website <http://www.neurostimcarolina.org/>. Like us on Facebook <http://www.facebook.com/NeurostimCarolina/> for updates. * ------------------------------ * *Abstract Submission for Posters:* In addition to attending the plenary sessions, registrants are invited to participate in the conference’s poster session. Original contributions addressing theory, research, practice, and training/education issues, in any areas of neuromodulation and brain network dynamics are welcome. The deadline for abstract submission is *March 15th 2018.* Authors will be notified of acceptance in the first week of April. *Please follow the guidelines for the submission of your abstract.* · Max 500 words and 1 page including title, author(s), affiliation(s), and main body. · Structure: Background, Methods, Results, and Conclusions (References and Funding) · File format: single PDF file converted from the provided template <http://www.neurostimcarolina.org/abstract.html> · Email us to submit your abstract (neurostimulation(a)unc.edu) * ------------------------------ * *Travel Awards for Trainees:* We have funds allocated for trainee travel awards. All trainees (undergraduate students, graduate students, post docs, research associates) who will be presenting posters at the conference are eligible for travel awards. To apply for a travel award please complete the form in this link <http://www.neurostimcarolina.org/abstract.html> and email us at neurostimulation(a)unc.edu along with your CV. Please note that you must attend the conference and present your poster to receive the travel award. The deadline for Travel Awards is *March 15th 2018* * ------------------------------ * *Transcranial Electrical Stimulation Workshop:* Trainees and conference attendees are encouraged to attend the preliminary neurostimulation workshop on May 21st, 2018. This one-day innovative hands-on transcranial electrical stimulation (TES) workshop will be taught by Dr. Flavio Frohlich. The workshop will focus on transcranial alternating current stimulation (tACS) and transcranial direct current stimulation (tDCS) with an exciting overview of theory, research, and methods. Click here <http://www.neurostimcarolina.org/workshop.html> for registration information. When completing registration, please be sure to provide feedback regarding your current knowledge of TES as well as some questions or techniques you are interested in. We want this course to be as interactive as possible. Lunch and beverages will be provided. * ------------------------------ * *About the Carolina Center for Neurostimulation:* The Carolina Center for Neurostimulation <http://www.carolinaneurostimulation.org/> is part of the Department of Psychiatry at The University of North Carolina at Chapel Hill and is directed by Dr. Flavio Frohlich. Established in 2017, the Center seeks to revolutionize psychiatry and neurology by studying the dynamics of brain, body, and behavior, investigating the response to stimulation, and translating discoveries into clinical treatments.

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[Call for postdoc application] Automated discovery of physico-chemical structures with intrinsically motivated deep learning algorithms
by Pierre-Yves Oudeyer Feb. 20, 2018

Feb. 20, 2018

Call for postdoc application: Automated discovery of physico-chemical structures with intrinsically motivated deep learning algorithms Project Team Inria: Flowers, Inria Bordeaux, https://flowers.inria.fr Contact: Pierre-Yves Oudeyer, pierre-yves.oudeyer(a)inria.fr Deadline for applying: 19th april 2018 How to apply: send email to PY Oudeyer and post application to https://jobs.inria.fr/public/classic/fr/offres/2018-00413 Duration: 16 months Scientific context: Intrinsically motivated goal exploration algorithms enable machines to discover repertoires of action policies that produce a diversity of effects in complex environments. In robotics, these exploration algorithms have been shown to allow real world robots to acquire skills such as tool use in high-dimensional continuous state and action spaces (e.g. Baranes and Oudeyer, 2013; Forestier et al., 2017). An example is the Poppy/Explauto experiment with a humanoid robot learning to use tools in a few hours, which obtained the 2nd position in the demonstration competition at NIPS 2016 (See https://www.youtube.com/watch?v=NOLAwD4ZTW0 , Forestier et al., 2016). In other domains such as chemistry and physics, they open the possibility to automate the discovery of novel chemical or physical structures produced by complex dynamical systems (e.g. Grizou, Points et al., 2017) However, they have so far assumed that self-generated goals are sampled in a specifically engineered feature space, limiting their autonomy. Recent work has shown how unsupervised deep learning approaches could be used to learn goal space representations (e.g. Péré et al., 2018), but they have focused on goals represented as static target configurations of the environment in robotics sensorimotor spaces. In this project, we will study how these new families of machine learning algorithms can be extended and used for automated discovery of behaviours of dynamical systems in physics/chemistry, through exploration of their parameter space, and when these behaviours are perceived through raw sensors (e.g. pixels of images). Web site of Flowers Lab: https://flowers.inria.fr Post-doctoral researcher work description The work will begin by a familiarization with algorithms for intrinsically motivated exploration with unsupervised learning of goal spaces developed in the team. Then, a few interesting numerical/simulation models of physical/chemical phenomena, associated to rich behavioral patterns (such as Turing-like reaction-diffusion models or oil droplet models), will be selected as a basis for developing and experimenting updates of existing exploration and learning algorithms. These algorithmic updates will focus in particular on the use of recurrent neural networks to learn goal spaces that can encode dynamical phenomena. Several algorithmic implementations will be compared, e.g. using several techniques for encoding times series as goal spaces, and compared using various information theoretic measures of the diversity of discovered behaviours in the target dynamical systems. It will be also possible to test these algorithmic updates in more traditional (simulated) sensorimotor learning problems, using standard benchmarks of the literature (e.g. Open Gym environments or Minecraft/Malmo). Experiments will possibly extend the DeepExplauto open-source library developed in the team, as well as standard Deep Learning libraries for the algorithms. Required knowledge and background: Candidates should have a strong expertise in at least one of these areas: - Experience with Deep Learning algorithms (theory and practical implementations) - Stochastic optimization, black-box optimization - Intrinsically motivated exploration algorithms Knowledge and competence in physics/chemical modelling would be welcome. Other requirements: - strong skills in mathematics, statistical inference, machine learning - Advanced programming skills in script languages like python - Motivation to work in an interdisciplinary project References : Baranes, A., & Oudeyer, P. Y. (2013). Active learning of inverse models with intrinsically motivated goal exploration in robots. Robotics and Autonomous Systems, 61(1), 49-73. Forestier, S., Mollard, Y., Caselli, D., & Oudeyer, P. Y. (2016). Autonomous exploration, active learning and human guidance with open-source Poppy humanoid robot platform and Explauto library. In The Thirtieth Annual Conference on Neural Information Processing Systems (NIPS 2016). Grizou, J., Point, L. and the Cronin lab (2017) Tutorial on “Developmental robotics in a chemistry lab », https://croningp.github.io/tutorial_icdl_epirob_2017/. Péré, A., Forestier, S., Oudeyer, P-Y. (2018) Unsupervised learning of goal spaces for intrinsically motivated goal exploration, in proceedings of ICLR 2018. Points, L. J., Taylor, J. W., Grizou, J., Donkers, K., & Cronin, L. (2018). Artificial intelligence exploration of unstable protocells leads to predictable properties and discovery of collective behavior. Proceedings of the National Academy of Sciences, 201711089. LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436-444. Keywords: deep learning; intrinsically motivated exploration; unsupervised learning; automated discovery; complex systems; dynamical systems Pierre-Yves Oudeyer Research director, Flowers lab Inria and Ensta ParisTech, France http://www.pyoudeyer.com

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