September 2020 - Comp-neuro - lists.cnsorg.org

Up to 6 PhD fellowships in Cognitive Neuroscience at SISSA, Trieste, Italy, to start Oct, 2020
by Alessandro Treves Oct. 12, 2022

Oct. 12, 2022

SISSA is an elite postgraduate research institution located in Trieste, Italy, and focused on Maths, Physics and Neuroscience. It operates in English: many among its students and faculty are not Italian. The Cognitive Neuroscience Department hosts 6 research labs that study the neuronal bases of time and magnitude processing, visual perception, motivation and intelligence, language and reading, tactile perception and learning, and neural computation. The Department is very inter–disciplinary; our approaches include behavioural, psychophysics, and neurophysiological experiments with humans and animals, as well as computational and mathematical models. Students with diverse backgrounds (physics, math, medicine, psychology, biology) are most welcome to apply. The Department has an exceptional track record with highly competitive funds (recent funding includes 4 ERC and 3 Human Frontiers grants) and publication in top journals (Nature, Science, PNAS, Current Biology). Recent placements after PhD include Harvard, MIT, Columbia and Princeton in the US; the NTNU, Manchester and Radboud in Europe; and Sydney University, Australia. Our alumni have been awarded 4 ERC grants, the 2015 Kandel Young Neuroscientist Prize and the 2017 ICTP Prize. More information about the Department is available at our website https://phdcns.sissa.it. The selection procedure is now open; to learn how to apply, please visit https://phdcns.sissa.it/admission-procedure. Please contact the PhD Coordinator (davide.crepaldi(a)sissa.it) and/or your prospective supervisor for more information and informal enquiries. -- Alessandro Treves SISSA, Cognitive Neuroscience, http://people.sissa.it/~ale/limbo.html if in, rm 241, via Bonomea 265, 34136 Trieste, Italy: +39-040-3787623

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Postdoc in neural data analysis
by Mark Humphries June 26, 2022

June 26, 2022

A 3 year postdoc post is available in the lab of Prof Mark Humphries, at the University of Nottingham (UK) In this project, our aim is to test the overarching hypothesis that movement transitions are encoded by the same neural population reconfiguring its joint activity, for both rhythmic and discrete movements. We will tackle this question using newly-available population recordings during rhythmic movement transitions in Aplysia and discrete arm movement transitions in monkeys, The Humphries’ group researches fundamental insights into how the joint activity of neurons encodes information about and actions in the world. For more see: https://www.humphries-lab.org Queries: mark.humphries(a)nottingham.ac.uk Deadline: 5th September Full details, and to apply: https://jobs.nottingham.ac.uk/Vacancy.aspx?id=27005&forced=2 [http://jobs.nottingham.ac.uk/org/images/socialmedia.png]<https://jobs.nottingham.ac.uk/Vacancy.aspx?id=27005&forced=2> Job Vacancy at the University of Nottingham: Research Associate/Fellow (Fixed term)<https://jobs.nottingham.ac.uk/Vacancy.aspx?id=27005&forced=2> Applications are invited for a postdoctoral research fellow to join the Humphries’ group on the MRC-funded project “Uncovering the neural basis of movement transitions”. The Humphries’ group researches fundamental... jobs.nottingham.ac.uk Professor Mark Humphries | MRC Senior non-Clinical Fellow | Chair in Computational Neuroscience Lab: humphries-lab.org<https://www.humphries-lab.org/> Twitter: @markdhumphries Public blog: https://medium.com/the-spike This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please contact the sender and delete the email and attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. Email communications with the University of Nottingham may be monitored where permitted by law.

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Explainable AI: Overcoming problems of Deep Learning problems with Adaptive Resonance
by Grossberg, Stephen April 9, 2022

April 9, 2022

Dear Colleagues, There's currently a lot of interest in AI, notably Deep Learning, and in achieving autonomous adaptive intelligence. The following new article summarizes foundational problems of reliability and trustworthiness of Deep Learning, explains how Adaptive Resonance overcomes them, and outlines a blueprint for achieving autonomous adaptive intelligence: Grossberg, S. (2020). A path towards Explainable AI and autonomous adaptive intelligence: Deep Learning, Adaptive Resonance, and models of perception, emotion, and action. Frontiers in Neurobotics, June 25, 2020. https://doi.org/10.3389/fnbot.2020.00036 Best, Steve Grossberg

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Postdoc at the University of Leicester to work on human single cell recordings
by Quian Quiroga, Rodrigo (Prof.) Nov. 23, 2021

Nov. 23, 2021

The Centre for Systems Neuroscience at the University of Leicester, UK, offers a 3-years postdoc position to study single cell recordings in humans – performed in epileptic patients for curative surgery. The project will investigate concept cells (a.k.a. Jennifer Aniston neurons) – that means, neurons in the hippocampus and surrounding areas that selectively fire to specific concepts, like different pictures and the written or spoken name of a particular person (e.g. Quian Quiroga et al, Nature 2005; Quian Quiroga Nature Reviews Neuroscience 2012), which are involved in declarative memory functions. For more details see: www.le.ac.uk/csn The successful candidate will contribute to performing recordings with patients in collaborating hospitals and the analysis of the data to investigate the role of these neurons in memory. He/She should have very good quantitative skills (data processing, and programing e.g. in Matlab) and a strong background or interest in neuroscience. He/She should be able to work both independently and as part of a research team within the Centre for System Neuroscience at Leicester and with our external collaborators. Informal enquiries are welcome and should be made to Paula Warrington, Research Centre Manager, csn(a)le.ac.uk or 0116 252 3249. To apply, please use this link: https://jobs.le.ac.uk/vacancies/1393/research-associate.html The applications should include a curriculum vitae and a brief description of their scientific interests The closing date for the applications is 21st October 2019. Cheers, Rodrigo Rodrigo Quian Quiroga Centre for Systems Neuroscience University of Leicester www.le.ac.uk/csn

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CFP Frontiers Research Topic: Affective Shared Perception
by Pablo Vinicius Alves De Barros April 20, 2021

April 20, 2021

Call For Papers - Frontiers Research Topic: Affective Shared Perception I. Aim and Scope Our perception of the world depends on both sensory inputs and prior knowledge. This applies in general to sensing and has particular implications for affective understanding. Humans adapt their social and affective perception as a function of the current stimulation, of the context, of the history of the interaction, and as of the status of the partner. This influences their behavior, which in turn modifies the social and affective perception of both partners and the evolution of the interaction. Understanding shared perception as part of affective processing will allow us to tackle this problem and to provide the next step towards a real-world affective computing system. The goal of this research topic is to present and discuss new findings, theories, systems, and trends in affective shared perception and computational models. We are interested in collecting interesting and exciting research from researchers on the areas of social cognition, affective computing, and human-robot interaction, including also, but not restricted to specialists in computer and cognitive science, psychologists, neuroscientists, and specialists in bio-inspired solutions. We envision that it will allow us to tackle the existing problems in this area and it will provide the next step towards a real-world affective computing system. II. Potential Topics Topics include, but are not limited to: - Affective perception and learning - Affective modulation and decision making - Developmental perspectives of shared perception - Machine learning for shared perception - Bio-inspired approaches for affective shared perception - Affective processing for embodied and cognitive robots - Multisensory modeling for conflict resolution in shared perception - New psychological findings on shared perception - Assistive aspects and applications of shared affective perception III. Submission - Abstract - 24 October 2020 - Paper Submission - 21 February 2021 IV. Guest Editors Pablo Vinicius Alves De Barros, Italian Institute of Technology (IIT), Genova, Italy Alessandra Sciutti, Italian Institute of Technology (IIT), Genova, Italy Ginevra Castellano, Uppsala University, Uppsala, Sweden Yukie Nagai, The University of Tokyo, Bunkyō, Japan ---------------------------------------- Dr. Pablo Barros Postdoctoral Researcher - CONTACT Unit Istituto Italiano di Tecnologia – Center for Human Technologies Via Enrico Melen 83, Building B 16152 Genova, Italy email: pablo.alvesdebarros(a)iit.it website: https://www.pablobarros.net<http://www.pablobarros.net><https://www.p> twitter: @PBarros_br

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Postdoc (3 yrs) in dynamical reconfigurations of neural populations during movement
by Mark Humphries March 9, 2021

March 9, 2021

A 3 year postdoc post is available in the lab of Prof Mark Humphries, at the University of Nottingham (UK) In this project, our aim is to test the overarching hypothesis that movement transitions are encoded by the same neural population reconfiguring its joint activity, for both rhythmic and discrete movements. We will tackle this question by developing new computational algorithms for dynamic systems, and applying them to newly-available population recordings during rhythmic movement transitions in Aplysia and discrete arm movement transitions in monkeys, The Humphries’ group researches fundamental insights into how the joint activity of neurons encodes information about and actions in the world. For more see: https://www.humphries-lab.org Queries: mark.humphries(a)nottingham.ac.uk Deadline: 10th January 2020 Full details, and to apply: https://www.nottingham.ac.uk/jobs/currentvacancies/ref/SCI182819X1 Professor Mark Humphries | MRC Senior non-Clinical Fellow | Chair in Computational Neuroscience Lab: humphries-lab.org<https://www.humphries-lab.org/> Twitter: @markdhumphries Public blog: https://medium.com/the-spike This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please contact the sender and delete the email and attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. Email communications with the University of Nottingham may be monitored where permitted by law.

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Announcing the 1st Brain-Computer Interface Un-Conference (BCI-UC)
by Moritz Grosse-Wentrup Feb. 5, 2021

Feb. 5, 2021

Dear Colleagues: We cordially invite you to the 1st Brain-Computer Interface Un-Conference (BCI-UC)! https://bciunconference.univie.ac.at/ The 1st BCI-UC is an entirely virtual event that takes place on July 23rd 2020 from 3 pm to 9:30 pm (CEST). It differs in various ways from traditional conferences in our field: * All presentations are publicly streamed via Crowdcast. * Anybody can apply for a presentation slot by submitting an abstract. All registered attendees can up-vote their favorite abstracts. In this way, the whole community decides which presentations they would like to see presented at the conference. * Voting commences on Monday, June 29th at 8 am (CEST) and ends on Thursday, July 16th at 12 midnight (CEST). The authors of the top-rated abstracts are invited to present their work at the conference. * Registration (free of charge) is required for submitting an abstract and to up-vote submissions. In addition to the contributed talks, the 1st BCI Un-Conference features two keynotes presentations: 1. Mariska J Vansteensel (UMC Utrecht Brain Center): Towards the Daily Life Implementation of ECoG-BCIs 2. Christian Herff (Maastricht University): Decoding Speech from Invasive EEG Please join us in exploring this new way of disseminating research in our community! The BCI-UC Organizing Committee: Moritz Grosse-Wentrup Anja Meunier Philipp Raggam Anita Resch Jiachen Xu -- Univ.-Prof. Dr.-Ing. Moritz Grosse-Wentrup Research Group Neuroinformatics Faculty of Computer Science University of Vienna Hörlgasse 6, A-1090 Wien, Austria moritz.grosse-wentrup(a)univie.ac.at +43-1-4277-79610 http://neural.engineering/

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Funded PhD and Data scientist positions
by Abhishek Banerjee Jan. 14, 2021

Jan. 14, 2021

Dear colleagues, Two funded *Ph.D. positions* are available in the newly established Adaptive Decision-making lab as a part of Neuroscience, Neurodisability and Neurological Disorders research theme, Biosciences Institute, Newcastle University, UK. The research carried out as part of th Ph.D fellowship will investigate the role of behaviourally relevant neural circuits in decision-making and its dysfunctions in neurological disorders using experimental and theoretical approaches (PNAS 2016; BRAIN 2019; bioRxiv 2020). Exciting local and international collaborations will ensure a high standard of training and mentorship. The position is funded (UK/EU rate) for up to 3.5 years and the application deadline is *6th January 2020*. Application details can be found here or by email provided below: https://www.findaphd.com/phds/project/mrc-dimen-doctoral-training-partnersh… . Additionally, the Banerjee Lab is also hiring a *Data Scientist* to be involved in projects that focus on understanding cortical computation during behaviour by combining large-scale recordings and imaging of neuronal populations. This person will be involved in analysing experimental data, developing software tools, and helping with data infrastructure. The application deadline is *31st January 2020*. Qualifications for the Data scientist position: - M.Sc. degree (or exceptional B.Sc.) in Physics, Computer Science, Mathematics, Engineering, or related technical field. - Programming experience in MATLAB is required, and additional experience in Python and LABView is preferred. - Background in computational neuroscience, image analysis, or machine learning is a plus. For informal inquiry, or if interested in applying for the Data scientist position, please submit a CV along with names of 3 referees to: Dr. Abhi Banerjee <abhi.banerjee(a)newcastle.ac.uk>. More details here: https://loop.frontiersin.org/people/11499/overview and http://neuronic.mit.edu/ Best wishes, Abhi -- Abhishek Banerjee Senior Lecturer Head, Adaptive Decision-making Lab Biosciences Institute Newcastle University United Kingdom I neuronic.mit.edu Skype: amiappu I @abhii_mit

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International Symposium on Artificial Intelligence and Brain Science 2020 Online
by Kenji Doya Jan. 9, 2021

Jan. 9, 2021

We are going to hold an online symposium that brings together researchers in the forefront of AI and neuroscience. All talks will be made accessible as pre-recorded movies and we will have two-hour live discussion sessions on October 10-12, 2020. Registration is free and open till September 30. Please register from the web site below. ******** International Symposium on Artificial Intelligence and Brain Science http://www.brain-ai.jp/symposium2020/ Time below is in UTC (i.e., 10pm-0am Japan, 2pm-4pm UK, 9am-11am EDT, 6am-8am PDT) <Saturday, October 10th> 13:00 Get connected 13:15 Greetings: Kenji Doya (OIST) 13:30 Discussion on Keynote: Josh Tenenbaum (MIT) 14:00 Discussion on Session 1: Deep Learning and Reinforcement Learning Chair: Jun Morimoto (ATR) Discussant: Shunichi Amari (RIKEN) Speakers: Yann LeCun (NYU, Facebook), Yutaka Matsuo (U Tokyo), Doina Precup (McGill U) David Silver (DeepMind), Masashi Sugiyama (RIKEN AIP/U Tokyo IRCN) <Sunday, October 11th> 13:00 Discussion on Session 2: World Model Learning and Inference Chair: Hiroaki Gomi (NTT) Discussant: Mitsuo Kawato (ATR) Speakers: Ila Fiete (MIT), Karl Friston (UCL), Yukie Nagai (U Tokyo IRCN) Maneesh Sahani (Gatsby Unit), Tadahiro Taniguchi (Ritsumeikan U) 14:00 Discussion on Session 3: Metacognition and Metalearning Chair: Masayuki Matsumoto (Tsukuba U) Discussant: Keiji Tanaka (RIKEN) Speakers: Matthew Botvinick (DeepMind), Ryota Kanai (ARAYA), Angela Langdon (Princeton U) Hiroyuki Nakahara (RIKEN CBS), Xiao-Jing Wang (NYU) <Monday, October 12th> 13:00 Discussion on Session 4: AI for Neuroscience and Neuromorphic Technologies Chair: Takatoshi Hikida (Osaka U) Discussant: Kunihiko Fukushima (FLSI) Speakers: Jim DiCarlo (MIT), Yukiyaku Kamitani (Kyoto U), Rosalyn Moran (King’s College London) Terry Sejnowski (Salk Institute), Hidehiko Takahashi (Tokyo MDU) 14:00 Discussion on Session 5: Social Impact and Neuro-AI Ethics Chair: Masamichi Sakagami (Tamagawa U) Speakers: Anne Churchland (UCLA), Kenji Doya (OIST), Arisa Ema (U Tokyo IFI) Hiroaki Kitano (SONY CSL), Stuart Russell (UC Berkeley) Sponsor: KAKENHI Project on Artificial Intelligence and Brain Science (http://www.brain-ai.jp) Co-sponsors: RIKEN AIP (https://aip.riken.jp/?lang=en) U Tokyo IFI (https://ifi.u-tokyo.ac.jp/en/) U Tokyo IRCN (https://ircn.jp/en/) Contact: ncus(a)oist.jp ---- Kenji Doya <doya(a)oist.jp> Neural Computation Unit, Okinawa Institute of Science and Technology Graduate University 1919-1 Tancha, Onna, Okinawa 904-0495, Japan Phone: +81-98-966-8594; Fax: +81-98-966-2891 https://groups.oist.jp/ncu

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Creating a list of important computational predictions
by Yiota Poirazi Jan. 4, 2021

Jan. 4, 2021

Dear all, I believe you would agree that, the greatest recognition of our computational work comes with the experimental verification of our computational predictions. To highlight the most important outcomes of our theoretical work and facilitate a closer interaction with experimental labs so as to increase the chances of our predictions being experimentally tested, I would like to encourage you to nominate your favorite prediction at the following google form: https://docs.google.com/forms/d/e/1FAIpQLSeJZ2RrXJ0nZonIuyNzN0Cl gXDKDb7xTzoJOiqZTGxm9Kh7ow/viewform?c=0&w=1&usp=mail_form_link This effort started during the CNS 2017 meeting in Antwerp with the support of the OCNS Board. The resulting list will be posted on the CNS 2017 web site and disseminated in social media, as a reference for experimentalists. Thank you very much for supporting this important effort! Best wishes, Yiota Poirazi -- Panayiota Poirazi, Ph.D. Research Director Computational Biology Laboratory Institute of Molecular Biology and Biotechnology (IMBB) Foundation of Research and Technology-Hellas (FORTH) Vassilika Vouton, P.O.Box 1385, GR 70013, Heraklion, Crete GREECE Tel: +30 2810 391139 Fax: +30 2810 391101 Εmail: poirazi(a)imbb.forth.gr Lab site: www.dendrites.gr FENS-Kavli Network of Excellence <http://www.fens.org/Outreach/FENS-Kavli-Network-of-Excellence/> -- This message has been scanned for viruses and dangerous content by *E.F.A. Project* <http://www.efa-project.org>, and is believed to be clean. Click here to report this message as spam. <http://mailgate1.imbb.forth.gr/cgi-bin/learn-msg.cgi?id=4BCD7A00A1.A57D7&to…> -- Panayiota Poirazi, Ph.D. Research Director Computational Biology Laboratory Institute of Molecular Biology and Biotechnology (IMBB) Foundation of Research and Technology-Hellas (FORTH) Vassilika Vouton, P.O.Box 1385, GR 70013, Heraklion, Crete GREECE Tel: +30 2810 391139 Fax: +30 2810 391101 Εmail: poirazi(a)imbb.forth.gr Lab site: www.dendrites.gr FENS-Kavli Network of Excellence <http://www.fens.org/Outreach/FENS-Kavli-Network-of-Excellence/>

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ANDA 2020 - G-Node Advanced Neural Data Analysis Course, April 14-30, 2020, Jülich, Germany
by Thomas Wachtler Dec. 23, 2020

Dec. 23, 2020

ANDA 2020 - G-NODE ADVANCED NEURAL DATA ANALYSIS COURSE April 14 - 30, 2020 Haus Overbach, Jülich-Barmen, Germany Techniques to record neuronal data from populations of neurons are rapidly improving. Simultaneous recordings from hundreds of channels are possible while animals perform complex behavioral tasks. The analysis of such massive and complex data becomes increasingly challenging. This advanced course aims at providing deeper training in state-of-the-art analysis approaches in systems neuroscience. The course is addressed to excellent master and PhD students and young researchers who are interested in learning advanced techniques in data analytics and in getting hands-on experience in the analysis of electrophysiological data. Internationally renowned researchers will give lectures on statistical data analysis and data mining methods with accompanying exercises. Students will define and perform their own analyses on provided data to solve a challenge. Participants are required to have a strong interest in data analysis, a background in a mathematical or related field, knowledge of algebra, matrix operations, and statistics, and need to have solid programming experience (preferably in Python). FACULTY · Moshe Abeles, Hebrew Univ. Jerusalem, Israel · Michael Denker, Jülich Research Center, Germany · Udo Ernst, Univ. Bremen, Germany · Sonja Grün, Jülich Research Center, Germany · Adam Kohn, Albert Einstein College of Medicine, New York, USA · Jakob Macke, TU Munich, Germany · Luca Mazzucato, Univ. of Oregon, Eugene, USA · Martin Nawrot, Univ. of Cologne, Germany · Yifat Prut, Hebrew Univ. Jerusalem, Israel · Hansjörg Scherberger, German Primate Center, Göttingen, Germany · Thomas Wachtler, LMU Munich, Germany TOPICS COVERED Single neuron properties and statistics · Stochastic processes · Surrogate methods · Detection of spatio-temporal patterns · Unitary Events · Statistical analysis of massively parallel spike data · Higher-order correlation analyses · Elephant toolbox · Spike-LFP relationship · Population coding · State space analysis · Machine learning · Data mining · Research data management and reproducibility REQUIREMENTS Applicants should be familiar with linear algebra, probability, differential and integral calculus and experienced using Python or Matlab. Preparatory reading material will be provided. Students should bring their own laptops and should be able to install software on their system. Students that do not have a suitable laptop should indicate this immediately after acceptance to the course. We will be able to provide a small number of laptops for the time of the course. COURSE FEE A course fee of 1000 Euros will be charged to cover costs for accommodation and meals. Limited financial support may be available for students that otherwise would not be able to attend, which is to be indicated in the application. HOUSING Accommodation in 2-bed rooms for students will be provided at the course site. HOW TO APPLY The application should include · a letter of motivation (max 1 page) · curriculum vitae (please indicate the relevant courses you have taken) · description of programming experience · a letter of recommendation. Please send all documents as a single PDF file to <advanced-course(a)g-node.org>. APPLICATION DEADLINE Applications must be received by NOVEMBER 15, 2019. Early application is encouraged. For further information see http://www.g-node.org/anda

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SMILES virtual workshop @ICDL 2020
by Xavier Hinaut Oct. 28, 2020

Oct. 28, 2020

The SMILES (Sensorimotor Interaction, Language and Embodiment of Symbols) Workshop will take place virtually at the ICDL 2020 (International Conference on Developmental Learning). * Call for abstracts and papers: - Deadline: 25th of September 2020 - papers abstracts: 2 pages - long papers: 4-6 pages - Submissions: smiles.conf(a)gmail.com <mailto:smiles.conf@gmail.com> - Papers format: same as ICDL conference https://cis.ieee.org/publications/t-cognitive-and-developmental-systems/tcd… <https://cis.ieee.org/publications/t-cognitive-and-developmental-systems/tcd…> - Workshop dates (coming soon): the days before or after the ICDL conference (26-30 October 2020) * Workshop Short Description On the one hand, models of sensorimotor interaction are embodied in the environment and in the interaction with other agents. On the other hand, recent Deep Learning development of Natural Language Processing (NLP) models allow to capture increasing language complexity (e.g. compositional representations, word embedding, long term dependencies). However, those NLP models are disembodied in the sense that they are learned from static datasets of text or speech. How can we bridge the gap from low-level sensorimotor interaction to high-level compositional symbolic communication? The SMILES workshop will address this issue through -an interdisciplinary approach involving researchers from (but not limited to): - Sensori-motor learning, - Emergent communication in multi-agent systems, - Chunking of perceptuo-motor gestures (gestures in a general sense: motor, vocal, ...), - Sensori-motor learning, - Symbol grounding and symbol emergence, - Compositional representations for communication and action sequence, - Hierarchical representations of temporal information, - Language processing and acquisition in brains and machines, - Models of animal communication, - Understanding composition and temporal processing in neural network models, and - Enaction, active perception, perception-action loop. * More info - contact: smiles.conf(a)gmail.com <mailto:smiles.conf@gmail.com> - organizers: Xavier Hinaut, Clement Moulin-Frier, Silvia Pagliarini, Joni Zhong, Loo CHU KIONG, Michael Spranger, Tadahiro Taniguchi - invited speakers (coming soon) - workshop website (comming soon): https://sites.google.com/view/smiles-workshop/ <https://sites.google.com/view/smiles-workshop/> - ICDL conference website: https://cdstc.gitlab.io/icdl-2020/ <https://cdstc.gitlab.io/icdl-2020/> * Workshop Long Description Recently Deep Learning networks have broken many benchmarks in Natural Language Processing (NLP), e.g. [1]. Such breakthroughs are realized by a few mechanisms (e.g. continuous representations like word embedding, attention mechanism, ...). However, no equivalent finding happened towards the understanding of which mechanisms enable the brain to perform similar functions. Deep Learning does not reproduce learning mechanisms nor the dynamics of the brain. The brain needs to parse incoming stimuli and learn from them incrementally, it cannot unfold time like deep learning algorithms such as Back-propagation through time (BPTT). Thus, we still lack the key neuronal mechanisms needed to properly model the (hierarchies of) functions in language perception and production. Other models of language processing reproducing the behavior of brain dynamics (Event-Related-Potentials (ERPs) [2] or functional Magnetic Resonance Imaging (fMRI) [3]) have been developed. However, such model softens lack explanatory power demonstrating the causes of such observed dynamics: i.e. what is computed and why is it computed – for which purpose? We need more biologically plausible learning mechanisms while producing causal explanations of the experimental data modelled. There is converging evidence that language production and comprehension are not separated processes in a modular mind, they are rather interwoven, and this interweaving is what enables people to predict themselves and each other [4].Interweaving of action and perception is important because it allows a learning agent (or a baby) to learn from its own actions: for instance, by learning the perceptual consequences(e.g. the heard sounds) of its own actions (e.g. vocal productions) during babbling [5]. Thus, the agent learns in a self-supervised way instead of relying only on supervised learning, which in contrast, imply non-biological teacher signals cleverly designed by the modeler. Explicit neuronal models explaining which are the mechanisms shaping these perceptuo-motor units through development are missing. The existence of sensorimotor (i.e. mirror) neurons at abstract representation levels (often called action-perception circuits [6]), jointly with the perceptuo-motor shaping of sensorimotor gestures [5], suggest the existence of similar action-perception mechanisms implemented at different levels of hierarchy. How could we go towards such hierarchical architectures based on action-perception mechanisms? Importantly, a language processing model needs a way to acquire the semantics of the (symbolic) perceptuo-motor gestures and of the more abstract representations, otherwise it would consider only morphosyntactic and prosodic featuresof language. These symbolic gestures, i.e. signs, need to be grounded to the mental concept, i.e. signified, they are representing. Several theories and robotic experiments give examples of how symbols could be grounded or how symbols could emerge [7]. However, current neurocomputational models aiming to explain brain processes are not grounded. Robotics have an important role here for the grounding of semantics by experiencing the world through interactions with the physical world and with humans. We need mechanisms that start from raw sensory perception and raw motor commands in order to let emerge plausible representations through development, instead of arbitrary representations. Finally, computational models of emergent communication in agent populations are currently gaining interest in the machine learning community [8], [9]. These contributions show how a communication system can emerge to solve cooperative tasks in sequential environments. However, they are still relatively disconnected from the earlier theoretical and computational literature aiming at understanding how language might have emerged from a prelinguistic substance [10], [11]. We need to conceive communication as the emergent result of a collective behavior optimization process and to ground the resulting computational models into the theoretical literature from language evolution research. The SMILES workshop will aim at discussing each of the questions mentioned above, together with original approaches on how to integrate them. [1] J. Devlin et al., 2018. [2] H. Brouwer and J. C. J. Hoeks, 2013. [3] M. Garagnani et al. 2008. [4] M. J. Pickering and S. Garrod, 2013. [5] J.-L. Schwartz et al., 2012. [6] F. Pulvermüller and L. Fadiga, 2010. [7] T. Taniguchi et al., 2016. [8] S. Sukhbaatar et al.,2016. [9] I. Mordatch and P. Abbeel, 2017. [10] M. Tomasello et al., 2005. [11] P.-Y. Oudeyer and L. Smith, 2015. Xavier Hinaut Inria Researcher (CR) Mnemosyne team, Inria LaBRI, Université de Bordeaux Institut des Maladies Neurodégénératives +33 5 33 51 48 01 www.xavierhinaut.com

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Lecture video about brain mechanisms that cause mental disorders
by Grossberg, Stephen Oct. 17, 2020

Oct. 17, 2020

Dear Colleagues, I gave a pre-recorded keynote lecture on Zoom to the World Congress on Computational Intelligence on July 22 about how particular brain dysfunctions can cause symptoms of mental disorders like Alzheimer's disease, autism, amnesia, and neglect: http://sites.bu.edu/steveg/files/2020/07/Grossberg-WCCI-keynote-Glasgow-vid… The lecture can also be found on my web page sites.bu.edu/steveg along with a pdf of its powerpoint slides. Best, Steve Grossberg Stephen Grossberg http://en.wikipedia.org/wiki/Stephen_Grossberg http://scholar.google.com/citations?user=3BIV70wAAAAJ&hl=en https://youtu.be/9n5AnvFur7I https://www.youtube.com/watch?v=_hBye6JQCh4 Wang Professor of Cognitive and Neural Systems Director, Center for Adaptive Systems Professor Emeritus of Mathematics & Statistics, Psychological & Brain Sciences, and Biomedical Engineering Boston University sites.bu.edu/steveg steve(a)bu.edu

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NEURAL COMPUTATION - February 1, 2020
by Terry Sejnowski Oct. 2, 2020

Oct. 2, 2020

Neural Computation - Volume 32, Number 2 - February 1, 2020 Available online for download now: http://www.mitpressjournals.org/toc/neco/32/2 http://cognet.mit.edu/content/neural-computation ----- Article Face Representations via Tensorfaces of Various Complexities Sidney Lehky, Anh-Huy Phan, Andrzej Cichocki, and Keiji Tanaka Letters Transition Scale-spaces: A Computational Theory for the Discretized Entorhinal Cortex Nicolai Waniek From Synaptic Interactions to Collective Dynamics in Random Neuronal Networks Models: Critical Role of Eigenvectors and Transient Behavior Ewa Gudowska-Nowak, Maciej A Nowak, Dante Chialvo, Jeremi K Ochab, and Wojciech Mateusz Tarnowskic Synaptic Scaling Improves the Stability of Neural Mass Models Capable of Simulating Brain Plasticity Jure Demsar, Rob Forsyth Scaled Coupled Norms and Coupled Higher Order Tensor Completion Kishan wimalawarne, Makoto Yamada, and Hiroshi Mamitsuka Improving Generalization via Attribute Selection on Out-of-the-box Data Xiaofeng Xu, Ivor W. Tsang, and Chuancai Liu ------------ ON-LINE -- http://www.mitpressjournals.org/neuralcomp MIT Press Journals, One Rogers Street, Cambridge, MA 02142-1209 Tel: (617) 253-2889 FAX: (617) 577-1545 journals-cs(a)mit.edu ------------

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POSTDOC POSITIONS IN COMPUTATIONAL NEUROSCIENCE IN PARIS AND BASEL
by Rava A. da Silveira Sept. 30, 2020

Sept. 30, 2020

*Several postdoctoral openings in the lab of Rava Azeredo da Silveira **(Paris & Basel)* The lab of Rava Azeredo da Silveira invites applications for *Postdoctoral Researcher* positions at ENS, Paris, and IOB, an associated institute of the University of Basel. Research questions will be chosen from a broad range of topics in theoretical/computational neuroscience and cognitive science (see the description of the lab’s activity, below). One of the postdoc positions to be filled in Basel will be part of a collaborative framework with Michael Woodford (Columbia University) and will involve projects relating the study of decision making to models of perception and memory. Candidates with backgrounds in mathematics, statistics, artificial intelligence, physics, computer science, engineering, biology, and psychology are welcome. Experience with data analysis and proficiency with numerical methods, in addition to familiarity with neuroscience topics and mathematical and statistical methods, are desirable. Equally desirable are a spirit of intellectual adventure, eagerness, and drive. The positions will come with highly competitive work conditions and salaries. *Application deadline:* For full consideration, please apply by 30 October 2020. *How to apply:* Please send the following information *in one single PDF, to * *silveira(a)iob.ch* <silveira(a)iob.ch>*:* 1. letter of motivation; 2. statement of research interests, limited to two pages; 3. curriculum vitæ including a list of publications; 4. any relevant publications that you wish to showcase. In addition, please arrange for three letters of recommendations to be sent to the same email address. In all email correspondence, please include the mention “APPLICATION-POSTDOC” in the subject header, otherwise the application will *not* be considered. *** *ENS,* together with a number of neighboring institutions (College de France, Institut Curie, ESPCI, Sorbonne Université, and Institut Pasteur), offers a rich scientific and intellectual environment, with a strong representation in computational neuroscience and related fields. *IOB* is a research institute combining basic and clinical research. Its mission is to drive innovations in understanding vision and its diseases and develop new therapies for vision loss. IOB is an equal-opportunity employer with family-friendly work policies. *The Silveira** Lab* focuses on a range of topics, which, however, are tied together through a central question: How does the brain represent and manipulate information? Among the more concrete approaches to this question, the lab analyses and models neural activity in circuits that can be identified, recorded from, and perturbed experimentally, such as visual neural circuits in the retina and the cortex. Establishing links between physiological specificity and the structure of neural activity yields an understanding of circuits as building blocks of cerebral information processing. On a more abstract level, the lab investigates the representation of information in populations of neurons, from a statistical and algorithmic—rather than mechanistic—point of view, through theories of coding and data analyses. These studies aim at understanding the statistical nature of high-dimensional neural activity in different conditions, and how this serves to encode and process information from the sensory world. In the context of cognitive studies, the lab investigates mental processes such as inference, learning, and decision-making, through both theoretical developments and behavioral experiments. A particular focus is the study of neural constraints and limitations and, further, their impact on mental processes. Neural limitations impinge on the structure and variability of mental representations, which in turn inform the cognitive algorithms that produce behavior. The lab explores the nature of neural limitations, mental representations, and cognitive algorithms, and their interrelations.

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COSYNE 2021: Meeting announcement and call for abstracts
by Tomas Hromadka Sept. 29, 2020

Sept. 29, 2020

==================================================== Computational and Systems Neuroscience 2021 (Cosyne) MAIN MEETING ONLINE 27 February - 01 March 2021 www.cosyne.org ==================================================== ---------------------------------------------------- MEETING ANNOUNCEMENT ---------------------------------------------------- The annual Cosyne meeting provides an inclusive forum for the exchange of empirical and theoretical approaches to problems in systems neuroscience, in order to understand how neural systems function. Cosyne 2021 will take place online, February 27 - March 1, 2021. The goal of this year’s meeting is to promote early stage investigators. Therefore, there are no invited talks from established researchers. The format will include featured contributed talks and an interactive poster-like presentations (short recorded presentation + live interactions). More details to follow. All abstract submissions will be reviewed as in previous years, but reviewing will be fully double blind. The deadline for Abstract submission will be November 12, 2020. Cosyne topics include but are not limited to: neural basis of behavior, sensory and motor systems, circuitry, learning, neural coding, natural scene statistics, dendritic computation, neural basis of persistent activity, nonlinear receptive field mapping, representations of time and sequence, reward systems, decision-making, synaptic plasticity, map formation and plasticity, population coding, attention, and computation with spiking networks. IMPORTANT DATES Abstract submission opens: 11 October 2020 Abstract submission deadline: 12 November 2020 When preparing an abstract, authors should be aware that not all abstracts can be accepted for the meeting. Abstracts will be selected based on the clarity with which they convey the substance, significance, and originality of the work to be presented. ORGANIZING COMMITTEE General & Program Chairs: Anne-Marie Oswald (U Pittsburgh) and Srdjan Ostojic (Ecole Normale Superieure Paris) Diversity Chairs: Eva Dyer (Georgia Tech, Emory) and Eric Shea-Brown (U Washington) Publicity Chair: Adam Calhoun (Princeton) Development Chair: Michael Long (NYU) EXECUTIVE COMMITTEE Stephanie Palmer (U Chicago) Zachary Mainen (Champalimaud) Alexandre Pouget (U Geneva) Anthony Zador (CSHL) CONTACT meeting [at] cosyne.org COSYNE MAILING LISTS Please consider adding yourself to Cosyne mailing lists (groups) to receive email updates with various Cosyne-related information and join in helpful discussions. See Cosyne.org -> Mailing lists for details.

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(on behalf of Loren Frank) faculty position @ UCSF
by Peter Dayan Sept. 29, 2020

Sept. 29, 2020

The Department of Physiology at UCSF is seeking a visionary neuroscientist to join our vibrant and collaborative discovery research community. This open-rank, tenure-track faculty position is part of a multi-year UCSF institutional initiative that began in 2018 to foster equity and inclusion in biomedical research and to promote the success of our diverse student population. Since launching this effort, UCSF has tripled the number of underrepresented faculty in our basic sciences departments and this critical mass will continue to grow. Candidates are expected to hold a Ph.D. and/or M.D., to have demonstrated significant research accomplishment and potential, and to be committed to the mentorship of students, with a particular emphasis on candidates with demonstrated success mentoring students from groups that are historically underrepresented in biomedical science. We encourage outstanding candidates who are early in their postdoctoral research training to apply, even if their main findings are not yet published. The successful candidate will be expected to establish a dynamic and interactive research program focused in the field of integrative neuroscience, which could include molecular, genetic, cellular, systems, behavioral, computational, and engineering approaches. The candidate would become a member of the Kavli Institute for Fundamental Neuroscience, the Center for Integrative Neuroscience, and the Weill Institute for Neuroscience at UCSF. The candidate would be expected to join the UCSF Neuroscience Graduate Program and, if so desired, one or more of our other top-ranked interdisciplinary graduate programs (see https://graduate.ucsf.edu/list-programs) The candidate, like all faculty at UCSF, will also be expected to contribute to graduate teaching, to be a leader in inclusive mentoring practices, and to participate in activities that promote equity and inclusion at our institution and in the broader scientific community. Service and teaching expectations are comparable to those of any other UCSF tenure-track faculty position. Faculty appointment will be made at a professorial rank commensurate with current academic standing. UCSF offers competitive salaries, research set-up funds, and recruitment allowances, and has numerous opportunities for faculty development and further training in mentorship. Applications must be submitted online and include the following documents in a single PDF: (1) cover letter briefly describing how the candidate fits the position; (2) curriculum vitae; (3) 1-page summary of research accomplishments demonstrating the candidate’s scientific leadership through their contribution to their project(s) and describing the potential impact of their work on the field of neuroscience; (4) 2-page description of future research plans that includes both high risk / high reward projects and an NIH-fundable program; and 5) a statement of personal experiences with, and contributions to, issues related to social and racial justice, equity, diversity, and inclusion, with particular attention to demonstrated success with formal and informal mentoring of individuals from historically underrepresented groups. We encourage candidates to describe specific mentoring strategies to support the success of all trainees in their research group. Copies of major publications that demonstrate the candidate’s ability to carry out creative and impactful work should be included. Applicants should request three to five letters of recommendation describing how the candidate meets the criteria in this job description. We encourage recommenders to provide explicit examples to illustrate their statements. We expect candidates to provide a letter from their postdoctoral and graduate advisors but will consider candidates who can provide justifications when these will be lacking. Review will begin on December 1, 2020 and continue until the position is filled. Please direct inquiries about the position and suggestions of potential candidates to Dr. Loren Frank (loren(a)phy.ucsf.edu) As an institution that values diversity, UC San Francisco especially encourages application from historically excluded groups, including but not limited to racially underrepresented individuals, women, and individuals with a commitment to mentoring historically excluded groups in the sciences. UC San Francisco seeks candidates whose experience, teaching, research, or community service that has prepared them to contribute to our commitment to diversity and excellence. The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status. Please apply online at https://aprecruit.ucsf.edu/JPF03083.

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postdoc/PhD students needed
by Alexey Kuznetsov Sept. 28, 2020

Sept. 28, 2020

*POSTDOCTORAL POSITION* *Indianapolis, Indiana, United States* A postdoctoral position and/or PhD student positions are available for a cutting-edge project on computational modeling of habit formation. The project takes place in the excellent collaborative environment of the Indiana Alcohol Research Center and studies the influence of alcohol on habits. The post-doc will develop a model of the cortico-striatal brain circuitry affected by alcohol. The post-doc will work with Prof. Kuznetsov (Mathematics Dept. IUPUI) and collaborate with experimentalists Prof. Atwood (IUSM) and Prof. Lapish (Psycology Dept. IUPUI). The position is available beginning December 2020 for one year. The continuation is contingent upon the availability of funds. *Qualifications*: Applicants should have a Ph.D. in Mathematics, Physics, or a related field, a background in Dynamical Systems, programming experience and working knowledge in Computational Neuroscience. Experience in modeling the basal ganglia is desirable. *How to Apply:* Send your CV, list of publications, research statement, and contact information for three references to Prof. Alexey Kuznetsov via e-mail: askuznet(a)iupui.edu. IUPUI is an Equal Opportunity/Affirmative Action Institution. Individuals who require a reasonable accommodation in order to participate in the application process must notify Cindy Ritchie at 402 N. Blackford Street, LD 270, Indianapolis, Indiana 46202 or call (317) 274-6920, a reasonable time in advance. IUPUI strongly encourages applications from women and underrepresented minorities. Additional information about IUPUI and the Department is available at www.iupui.edu and www.math.iupui.edu. -- Alexey Kuznetsov Associate Professor Dept. of Mathematical Sciences, IUPUI Science Building, LD 270, 402 N. Blackford St., Indianapolis, IN

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Postdoctoral position at BU (Nancy Kopell) and MIT (Emery Brown)
by McCarthy, Michelle M Sept. 28, 2020

Sept. 28, 2020

Dear Comp-Neuro Community, The Kopell lab at Boston University has an open position (2 years with the possibility of renewal) for a postdoctoral associate to work on computational models concerning mechanisms of anesthesia, with experimental work to be done in the labs of Emery Brown, Earl Miller and others. The models are physiologically detailed (Hodgkin-Huxley based), linking anesthetic-mediated changes in physiology to changes in brain rhythms and their coordination both locally and across the brain; the models further link the brain rhythms to changes in consciousness. The work is relevant to sleep and brain disorders. Programming proficiency and modeling experience is necessary and some neuroscience training is desirable. Please send inquiries and applications to Xiaoshi Shi (xiaoshi(a)bu.edu<mailto:xiaoshi@bu.edu>) and nk(a)bu.edu<mailto:nk@bu.edu>. Nancy Kopell Department of Mathematics and Statistics Boston University, Boston MA 02215

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Two Cardiac Simulation/Computational Neuroscience postdoc computer modeling positions are available for development of a novel ICNS (intrinsic cardiac nervous system) simulation project.
by Salvador Dura Sept. 28, 2020

Sept. 28, 2020

Our new NIH SPARC Initiative ICNS project aims to build and establish a new model of RAGP (right atrial ganglionic plexus) The work is being done as a collaboration between SUNY Downstate (Brooklyn, NY), and Jefferson University (Philadelphia, CT) under the auspices of a 2-year NIH SPARC Initiative grant. The two new postdocs will work closely together - one focusing primarily on cell-level modeling and the other primarily on network but with both expected to work in both areas. Candidates should have a strong background in computer programming, with demonstrated proficiency in Python. Strong interest, though not necessarily research experie nce, in neuroscience is a must. Some experience with NEURON and NetPyNE is desirable. Job Types: Full-time or Contract contact: bill.lytton(a)downstate.edu<mailto:bill.lytton@downstate.edu> -- William W. Lytton, MD SUNY Distinguished Professor Downstate Medical Center, Brooklyn, NY bill.lytton(a)downstate.edu; http://neurosimlab.com ________________________________________________________________

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postdocs with Peter Dayan in Tübingen
by Peter Dayan Sept. 28, 2020

Sept. 28, 2020

Postdoc(s) in Neural Reinforcement Learning / Computational Psychiatry (m/f/d) 100% Peter Dayan is looking to hire one or more postdocs (100%) to work in the areas of neural reinforcement learning, computational neuromodulation, and computational psychiatry. These positions will start in the Faculty of Science, Department of Computer Science, University of Tübingen, as part of an Alexander-von-Humboldt Professorship award. There are also targeted positions on the computational anatomy of cortico-striatal connections (funded by a collaborative NIH grant with Professor Suzanne Haber) and with the International Brain Lab (a large collaboration with 20 other investigators, funded by the Simons Foundation). Peter Dayan has an affiliation with the University of Tübingen and the Max Planck Institute for Biological Cybernetics and collaboration is expected. The salary will be paid in accordance with the collective agreement for the public sector (salary at E13 TV-L, commensurate to experience and qualifications). The positions are available immediately, and are initially limited to two years (with the possibility of extension). Please direct scientific inquiries to dayan(a)tue.mpg.de and administrative inquiries to susan.fischer(a)tue.mpg.de. Responsibilities include: • Planning and carrying out research projects, for instance building theories and computational models of data from human and animal experiments, conducting experiments, analysing behavioural and neural data, writing and editing scientific papers/reports. • Helping to mentor and supervise student projects. • Participating in scientific conferences. • Helping to organize and conduct collaborations in Tübingen as well as nationally and internationally • Helping with building and running an effective academic lab environment at the intersection between the Max Planck Institute for Biological Cybernetics and the science and medical faculties at the University of Tübingen. The successful candidate(s) should have a PhD in computational neuroscience or related fields. Proficiency in a high level mathematical or statistically-oriented programming language such as python, R, Julia or matlab, and intimate familiarity with advanced data analysis are essential. The candidate(s) should be able to work independently and troubleshoot and should show good capacity and value for teamwork and communication skills. The University of Tübingen is one of the Excellence Universities in Germany. It is home to a vibrant research community, with very strong research activity in Neuroscience and Clinical Psychology / Psychiatry as well as Artificial Intelligence and Machine Learning. We offer an open research culture, where original thinking and academic merit are encouraged and nurtured, and encourage applications from all nationalities, backgrounds, and genders. The University of Tübingen is dedicated to increase the percentage of female employees in the field of science. Therefore, female candidates are strongly encouraged to apply. Applications should include a CV, a list of publications, summaries of scientific achievements and research plans, the position for which the application is intended, and the names and contact details of three referees. Applications should be sent in a single PDF to: susan.fischer(a)tue.mpg.de Applications arriving before June 30th 2020 will receive full consideration.

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Join us at the NMC 3.0 conference, Oct 26-30, submissions open now
by Brad Wyble Sept. 27, 2020

Sept. 27, 2020

Dear Neuroscience Community, We are excited to announce the launch of Neuromatch Conference (Oct 26-30). The Neuromatch team has been working hard to bring a virtual conference that accepts submissions from all areas of neuroscience, and where all relevant submissions are accepted as a talk! Our goal with this conference is to provide a place where neuroscientists from all over the world get to share research ideas and come together as a community! We’re working hard to make it the most inclusive neuroscience meeting that has ever existed. The deadline for submissions is October 2, 2020, so we encourage you to get your abstracts ready now! There is a $25 registration fee but this is waivable (no validation required) for anyone who cannot pay to attend for any reason. Please view our website for more information regarding submission and registration: neuromatch.io <http://neuromatch.io/>j The conference will be organized by themes, tailored to fit your area of research best. These themes will be: Theme A: Developmental Disorders and Injury Theme B: Excitability, Synapses, and Glia Theme C: Sensory & Motor Systems, and Physiology & Behavior Theme D: Cognition, Motivation and Emotion Theme E: Computation and Techniques Theme F: History, Education, and Society We developed algorithms that will allow us to place you in a virtual room with other scientists and attendees who are interested in similar topics, therefore ensuring an audience that is excited about your talk. The talks will have two formats, and you will be able to choose which one you prefer - Traditional Talk: 12-minute talk plus 3-minute Q&A - Interactive Talk: 5-minute talk plus 10-minute Q&A (this talk is focused on discussion) We hope that you will attend the Neuromatch Conference and consider submitting your abstract for presentation! We would love to hear from you and see everyone’s latest results.. Best wishes, The Neuromatch Team Please follow our social media and visit our website for regular updates @Neuromatch <https://twitter.com/neuromatch?lang=en> @Neuromatch <https://www.instagram.com/neuromatch/> neuromatch.io -- Brad Wyble Associate Professor Psychology Department Penn State University http://wyblelab.com

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2 postdoc positions in computational neuroscience
by Alain Destexhe Sept. 26, 2020

Sept. 26, 2020

Dear Colleagues, Please pass on these two positions that we have for postdocs in computational neuroscience at the Paris-Saclay Institute of Neuroscience - many thanks. best, Alain ---------------- 2 POSTDOC POSITIONS AVAILABLE Two postdoc positions are available for computational and theoretical studies in the framework of the Human Brain Project. The theoretical work associated to these two postdoctoral positions consists of (1) investigating models and mathematical techniques to model decision making phenomena (in collaboration with Rubem Moreno-Bote in Barcelona), and (2) investigate models of sensory perception, up to consciousness (in collaboration with Fanis Panagiotaropoulos and Stan Dehaene at NeuroSpin). Both postdocs will be supervised by A. Desyexhe and will work in tight collaboration with the European Institute for Theoretical Neuroscience (EITN). DETAILS OF THE FIRST POSTDOC POSITION: We are seeking for a postdoc position in the framework of a project called "COREDEM", and which was recently integrated in the Human Brain Project European flaghsip. COREDEM aims at conceiving decision making models based on electrophysiological recordings in human and monkey, and ultimately test these models on neuromorphic and neuro-robotic applications. The project comprises a significant computational neuroscience component consisting mainly of two laboratories, Alain Destexhe at the CNRS and Paris-Saclay University, and Ruben Moreno-Bote at the UPF in Barcelona. We will consider spiking models that will compare parallel and sequential strategies to decision making, in a way constrained by unit recordings in monkey and human. Mean-field models will be derived from the spiking models, and such mean-field models will be incorporated in large-scale models of interacting brain areas. Both spiking and mean-field models will be integrated in neuromorphic SpiNNaker computers to be simulated in real time, to open the possibility of being used in real-time applications such as neuro-robotics. The postdoc can begin as early as January 2021, and latest on March 2021, and will be for a 2-year period. We expect that candidates have prior experience either in computational neuroscience, or in decision making. The working environment is the Paris-Saclay Institute of Neuroscience (NeuroPSI) of the CNRS, which comprises 22 research labs in experimental and computational neuroscience, mixed in the same environment. The postdoc will thus interact on a daily basis with experimentalists and theoreticians, and regular visits to the experimental labs of COREDEM (Stefano Ferraina from Rome and Tom Theys from Leuven) are planned. The postdoc will also interact strongly with the researchers and staff of Destexhe's lab at NeuroPSI, and will actively participate to the activities of the EITN. DETAILS OF THE SECOND POSTDOC POSITION: We are seeking for a postdoc position in the framework of a project called "BRICON", and which was recently integrated in the Human Brain Project European flaghsip. BRICON aims at investigating mechanisms of sensory perception and consciousness based on a strong interaction between computational models and experiments on human and monkey. The model will consider how the state of the brain interacts with external input and allows neural activity related to external input to propagate (or not) between brain areas. We will constrain the model based on unit recordings obtained in awake monkey collected by the experimental teams (Fanis Panagiotaropoulos and Stanislas Dehaene, NeuroSpin center). Models will start with conventional spiking neural networks, which then will be converted into population models using mean-field techniques. These mean-field model will then form the basis of whole-brain models simulated using The Virtual Brain platform of the HBP. The postdoc can begin as early as January 2021, and latet on June 2021, and will be for a 20 month period. We expect that candidates have prior experience either in computational neuroscience, or in sensory perception. The working environment is the Paris-Saclay Institute of Neuroscience (NeuroPSI) of the CNRS, which comprises 22 research labs in experimental and computational neuroscience, mixed in the same environment. The postdoc will thus interact on a daily basis with experimentalists and theoreticians, and regular visits to the experimental labs of BRICON (Panagiotaropoulos and Dehaene), who are working next-door in the NeuroSpin center. The postdoc will also interact strongly with the researchers and staff of Destexhe's lab at NeuroPSI, and will actively participate to the activities of the EITN. Interested candidates should send a CV and two recommendation letters at Alain Destexhe or email for more details. alain.destexhe (at) cnrs.fr Alain Destexhe Department of Integrative and Computational Neuroscience (ICN), Paris-Saclay Institute of Neuroscience (NeuroPSI), CNRS, Bat 33, 1 Avenue de la Terrasse, 91198 Gif-sur-Yvette, France.

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Postdoctoral position data/knowledge management for open neuroscience
by Andrew Davison Sept. 25, 2020

Sept. 25, 2020

Dear colleagues, A postdoctoral position in neuroscience data curation is available within the Neuroinformatics research group of the Paris-Saclay Institute of Neuroscience, led by Dr Andrew Davison. The Human Brain Project is developing an open data repository for neuroscience, following the FAIR principles of Findability, Accessibility, Interoperability, and Reusability. The role of our group is to strongly focus on Reusability, by ensuring that all datasets have high quality, in-depth metadata so that they can be used in model building, model validation, and further analysis, and by providing tools to facilitate data re-use. The position is available immediately, and is funded until 31st March 2023, with future extensions possible. Salary depends on experience, and will be on the standard CNRS research scale. Application is through the CNRS jobs portal: https://emploi.cnrs.fr/Offres/CDD/UMR9197-ANDDAV-006/Default.aspx?lang=EN Informal inquiries may be addressed to Andrew Davison (andrew.davison(a)cnrs.fr) Activities: The successful candidate will be responsible for developing and improving metadata schemas, protocols, and curation workflows for neural activity data (including patch clamp recordings, fluorescence imaging, multi-electrode array recordings and fMRI), and for coordinating the in-depth curation process. The project will involve intensive collaboration with other researchers, curators and software developers within the research group, within the Human Brain Project, and in the wider neuroscience/neuroinformatics communities. Qualifications: Applicants should have a PhD in either neuroscience, computer science, library/information science, or a closely related discipline, or be nearing completion of PhD studies in one of these domains. Experience with experimental methods in neuroscience, semantic web technologies and/or information management approaches will be of particular benefit. Knowledge of computer programming, in particular using the Python language, would also be an advantage. Knowledge of French would be helpful but is not required, as English is the working language of the project. Context: The Paris-Saclay Institute of Neuroscience (https://neuropsi.cnrs.fr/en/institute-home/) is part of the CNRS and Université Paris-Saclay, situated in Gif-sur-Yvette in the Paris region. The Davison team (https://neuropsi.cnrs.fr/en/icn-home/andrew-davison/) develops tools and methods for data sharing, modelling and simulation in neuroscience and brain-inspired computing. This position is funded by the Human Brain Project, an EU Flagship research project, within which more than 100 universities and research institutions collaborate to build a digital research infrastructure for neuroscience, brain-inspired computing and medicine.

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You are invited to DSP online course
by Maryam Sept. 24, 2020

Sept. 24, 2020

You are invited to “DIGITAL SIGNAL PROCESSING Online Course” Dear researcher; ScienceBeam, which is a forefront technology provider of neuroscience applications, would like to take the opportunity to invite you for 10-sessions “DIGITAL SIGNAL PROCESSING Online Course” that is going to start on October 18,2020. During this course you will learn: • Discrete-time signals and systems • Z-Transform • Transform of continuous-time signals • Transform analysis of linear time invariant systems • Structures for discrete-time systems • Filter design • The discrete Fourier Transform • Computation of the discrete Fourier transform Dr. Luu Gia Thien is an experienced lecturer at Ho Chi Minh City with a Doctor of Philosophy (PhD) focused in Digital signal processing from University of Orléans, France. Registration is open until October 5th. Special discount is considered for students. You won’t want to miss this! Don’t hesitate and register from the link below: https://sciencebeam.com/luu-gia-thien-course/ If you need more information please contact us via Whatsapp or Mail: Whatsapp number: +86 133 8078 1282 Email: workshop(a)sciencebeam.com www.sciencebeam.com

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