- Comp-neuro - lists.cnsorg.org

Program and preliminary schedule for CNS*2021 Online
by Martin Zapotocky June 27, 2021

June 27, 2021

**Organization for Computational Neurosciences 2885 Sanford Ave SW #15359 Grandville, MI 49418 USA*** Program and preliminary schedule available for 30th Annual Computational Neuroscience Meeting (CNS*2021 Online, **July 3-7)***** The program of the CNS*2021 Meeting can now be viewed at https://www.cnsorg.org/cns-2021-calendar <https://www.cnsorg.org/cns-2021-calendar> Please note that this year, the main days of the meeting (*July 3-7*) are preceded by software tutorials on *J**une 28-29*, and satellite tutorials on *June 30 - July 2*. For registration information, please visit https://www.cnsorg.org/cns-2021-registration-fees <https://www.cnsorg.org/cns-2021-registration-fees> Following registration, the attendees can use the conference Sched page to access detailed information for each session and to assemble a personalized schedule. Instructions are sent upon registration. Please follow the Sched page for up-to-date information on the event schedule. -------------------------------------------------------------------------------------------- OCNS is the international member-based society for computational neuroscientists. Become a member to be eligible for awards and other benefits. Visit our website for more information: https://www.cnsorg.org <https://www.cnsorg.org> -------------------------------------------------------------------------------------------- ------------------------------------------------------------------------

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Open postdoctoral position in Niv lab at Princeton University
by Angela Langdon June 25, 2021

June 25, 2021

The lab of Dr Yael Niv in the Princeton Neuroscience Institute and Department of Psychology at Princeton University is looking for a talented and motivated postdoctoral researcher to join our team to study the neural mechanisms of reward prediction and learning in animals. This position is to work primarily with Dr Angela Langdon on a NIDA-funded project modeling behavior and neural recording data from rodents in a reward learning task (start date: as soon as possible). The ideal candidate will 1) have experience in computational or theoretical modeling, such as reinforcement learning, Bayesian inference, machine learning and/or neural circuit modeling; 2) be excited about mapping theories of learning and decision making onto behavior and its neural basis; 3) be keen to work in a collaborative and interdisciplinary scientific environment. More broadly, members of the lab study the behavioral and neural computations that support learning and decision making, and their interaction with attention and memory mechanisms. Our research spans a diverse set of theoretical tools from reinforcement learning, Bayesian inference and machine learning alongside various empirical techniques, including targeted behavioral experiments, eye tracking and fMRI. In addition, we work closely with our collaborators on model-guided analysis of animal behavior and neural activity across a number of learning paradigms – the current position is for a project in this domain, working with existing neural and behavioral data from rodents. We have a particular interest in research that can shed light on the changes to learning and decision making that are prevalent in a range of clinical disorders. The Princeton Neuroscience Institute and the Psychology Department at Princeton are highly interdisciplinary and collaborative, and provide excellent support for career development. You will be joining a vibrant and international research group, and will have opportunities to interact with and learn from a large number of researchers in cognitive and computational neuroscience. To apply, send your CV and statement of research interests to Yael Niv: yael(a)princeton.edu <mailto:yael@princeton.edu> and Angela Langdon: alangdon(a)princeton.edu <mailto:alangdon@princeton.edu>.

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Workshop on Clinical Computational Neuroscience at OCNS*2021
by Laure Buhry June 25, 2021

June 25, 2021

Dear all, We would like to announce the Workshop on *“Clinical computational neuroscience: How computational neuroscience can solve problems from the clinic”,* which will be held on *July 7th* during the OCNS annual meeting from 9:30 am to 5:45 am (Paris time) / 3:30 am to 11:45 am (NY time)/ 5:30 pm to 1:45 am (Sydney time). Please keep in mind that for workshop attendance a registration at the main conference (https://www.cnsorg.org/cns-2021-registration-fees) is necessary. More information here: https://xenia-kobeleva.com/CNS2021/ We would love to see you there! Organizing Committee: Laure Buhry (co-chair) Xenia Kobeleva -- Dr Laure Buhry Associate Professor LORIA UMR CNRS 7503 - INRIA - University of Lorraine, France

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Postdoc position in neuronal network modelling and simulation
by Andrew Davison June 24, 2021

June 24, 2021

Dear colleagues, A postdoc position in neuronal network modelling and simulation is available within the Neuroinformatics research group of the Paris-Saclay Institute of Neuroscience, as part of the Human Brain Project (https://neuropsi.cnrs.fr/en/departments/icn/group-leader-andrew-davison/) The large number of different simulation environments in neuroscience presents both a problem and an opportunity. Since each simulator has its own programming interface and output data format, reproducing, reusing, or combining models written for different simulators typically presents considerable difficulty. On the other hand, since each simulation environment has a different balance between efficiency, flexibility, scalability and user-friendliness, we can choose the most appropriate one for a given problem, or cross-check the results obtained with different tools. Simulator-agnostic model representation languages such as NeuroML and PyNN allow us to preserve the advantages of simulator diversity while reducing or eliminating the disadvantages, thereby making reproducibility and reuse much easier. Such languages let us take a single model description and simulate it in different environments without having to reimplement the model each time. The aim of this project is to expand the scope of PyNN from networks of simplified neuron models, such as integrate-and-fire, to networks consisting of biophysically- and morphologically-detailed neuron models, targeting the NEURON and Arbor simulators, the SpiNNaker and BrainScaleS neuromorphic computing systems, and interoperability with NeuroML and the SONATA format. We offer a flexible and collaborative working environment, including remote working up to two days per week. For more details and to apply, see https://emploi.cnrs.fr/Offres/CDD/UMR9197-ANDDAV-007/Default.aspx?lang=EN Informal enquiries are welcome, contact andrew.davison(a)cnrs.fr Andrew Davison, PhD Group leader, Neuroinformatics Department for Integrative and Computational Neuroscience (ICN) NeuroPSI - Paris-Saclay Institute of Neuroscience CNRS - Université Paris-Saclay 1, avenue de la Terrasse 91198 Gif-sur-Yvette France Tel: +33 1 69 82 34 51 Twitter: @apdavison https://neuropsi.cnrs.fr/en/departments/icn/group-leader-andrew-davison/

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Tutorial on "Understanding early visual receptive fields from efficient coding principles"
by Zhaoping Li June 23, 2021

June 23, 2021

Understanding principles of efficient coding can enable you to answer questions such as: why should the input contrast response function of a neuron take its particular form? Why do retinal ganglion cells have center-surround receptive fields? How correlated or uncorrelated should the visual responses from different retinal ganglion cells be? Why do receptive fields of retinal ganglion cells increase their sizes in dim light? How could visual coding depend on animal species? Why are color selective V1 neurons less sensitive to visual motion signals? How can one predict the ocular dominance properties of V1 neurons from developmental conditions? How should neurons adapt to changes in visual environment? This tutorial guides you on how to answer such questions. It contains: (1) A list of 45 short video lecture clips (about 10 minutes each on average) on YouTube, see http://www.lizhaoping.org/zhaoping/EfficientVisualCoding_Playlist.html (2) In addition to (1), you can join CNS *2021 (see https://www.cnsorg.org/cns-2021-tutorials#T3 ), which enables social interactions with the lecturer and other students via Discord, and on July 3rd (the tutorial day) for highlights, Q&As, and discussions. best, Li Zhaoping -- Li Zhaoping Ph.D. Prof. of Cognitive Science, University of Tuebingen Head of Dept of Sensory and Sensorimotor Systems, Max Planck Institute of Biological Cybernetics Author of "Understanding vision: theory, models, and data", Oxford University Press, 2014 www.lizhaoping.org

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CNS*2021 Workshop: Computational approaches for studying astrocyte dynamics and astrocyte-neuron communication (July 6-7, Online)
by Marsa Taheri June 23, 2021

June 23, 2021

Dear all, We are pleased to announce a workshop on “*Computational approaches for studying astrocyte dynamics and astrocyte-neuron communication*” at this year’s Annual Computational Neuroscience Meeting (CNS*2021). This workshop will run over 2 half-days: July 6-7 (9 am – 12:30 pm UTC-7). ------------------- *Brief Description*: Exciting experimental studies in the last decade have led to an entirely new body of work on the participation of astrocytes in normal and pathological brain function. However, the development of a solid theoretical framework to support and quantify some of the pathways has been somewhat limited, first, due to the lack of intensive collaboration between experimentalists and theorists, and second, due to a persistent neurocentrist view of brain function. Please join us to hear from an incredible lineup of speakers, bringing together specialists, theorists, and experimentalists in the field of astrocyte-neuron signaling: Yukiko Goda, Riken, Japan Alla Borisyuk, University of Utah, USA Jennifer Shih, MIT, USA Annalisa Scimemi, University of Albany, USA Guoqiang Yu, Virginia Tech, USA Laszlo Heja, Hungarian Academy of Sciences, Hungary Anup Pillai, University of Ottawa, Canada Renaud Jolivet, Université de Genève, Switzerland Max Collard, UCSF, USA Audrey Denizot, Okinawa Institute of Science and Technology, Japan Ron Refaeli, The Hebrew University, Israel Kerstin Lenk, Graz University of Technology, Austria ------------------- More information on the workshop at: https://astrocytenet.org/cns2021-online-workshop/ Register and gain access to all CNS*2021 presentations, tutorials, and workshops at: https://www.cnsorg.org/cns-2021 We look forward to your participation! *On behalf of the workshop organizers:* *Kerstin Lenk*, Institute for Neural Engineering, Graz University of Technology, Graz, Austria *Audrey Denizot*, Okinawa Institute of Science and Technology, Computational Neuroscience Unit, Onna-Son, Japan *Barbara Genocchi*, Faculty of Medicine and Health Technology, BioMediTech, Tampere University, Tampere, Finland *Suhita Nadkarni*, Indian Institute of Science Education and Research Pune (IISER Pune), Pune, India *Marsa Taheri*, Department of Neurobiology, University of California Los Angeles, CA, USA Contact information: cns2021.astro.workshop(a)gmail.com

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Software WG satellite tutorials at CNS*2021 on Bash, Git, and Python: June 28, 29 2021
by Ankur Sinha June 23, 2021

June 23, 2021

Dear all, Apologies for the cross-posts. The INCF/OCNS Software Working Group is running three beginner/intermediate level satellite tutorials on Bash, Git, and Python at CNS*2021. These tutorials are on Monday and Tuesday (28/29 June). They are intended for both complete beginners and occasional/regular users who are looking to expand and refresh their skills. More information on these, including topics that we will cover can be seen on our website: https://ocns.github.io/SoftwareWG/2021/06/09/software-wg-tutorials-at-cns-2… - Effective use of Bash (Felix B. Kern): 28 June, 2021 1200 UTC - Effective use of Git (Ankur Sinha): June 28, 2021 1700 UTC - Python for beginners (Joe Graham, Shailesh Appukuttan, Ankur Sinha): 29 June, 2021 1300 UTC One can register for CNS*2021 here to gain access to excellent set of tutorials/workshops/posters and oral presentations that are being organised this year: https://www.cnsorg.org/cns-2021 More information on the Software working group, our work, how you can contact us, and how you can join us (it is open to all) is here: https://ocns.github.io/SoftwareWG/index.html On behalf of the Software WG, -- Thanks, Regards, Ankur Sinha (He / Him / His) Research Fellow at the Silver Lab | http://silverlab.org/ Department of Neuroscience, Physiology, & Pharmacology University College London, London, UK Time zone: Europe/London

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Post-doc position on machine learning and human motion/physiological data analysis at AIST, Japan
by 平山淳一郎 June 23, 2021

June 23, 2021

Dear colleagues, We invite applications for a postdoctoral researcher position on machine learning and human motion/physiological data analysis, available at Mathematical Neuroscience Research Group, Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST) (https://www.aist.go.jp/index_en.html) Japan. The successful candidate will join a collaborative project with ATR, Kyoto University and Hokkaido University on human-AI co-evolution, funded by NEDO (https://www.nedo.go.jp/english/) and conduct research on machine learning modeling and analysis of human motion data and/or related physiological signals from the brain and body, depending on his/her interests. The starting date is negotiable, with a preference for candidates who can start early. The initial appointment will be until March 2022, with the possibility of extension until March 31, 2025. Salary for the postdoctoral fellow will follow the AIST guideline. To apply, please visit https://jrecin.jst.go.jp/seek/SeekJorDetail?fn=3&ln=1&id=D121020014&ln_jor=1 and send the required application documents to junichiro.hirayama(a)aist.go.jp. The deadline of application is August 31, 2021. The deadline may be extended until the position is filled. -- Jun-ichiro Hirayama Senior Researcher Human Informatics and Interaction Research Institute National Institute of Advanced Industrial Science and Technology (AIST) junichiro.hirayama(a)aist.go.jp https://staff.aist.go.jp/junichiro.hirayama

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Postdoctoral positions in the Geffen lab at the University of Pennsylvania
by Maria Geffen June 22, 2021

June 22, 2021

The Geffen laboratory <http://hosting.med.upenn.edu/hearing> at the University of Pennsylvania <http://www.upenn.edu/> has multiple postdoctoral positions open in systems neuroscience with the broad goal of understanding the neuronal circuits for auditory perception and learning. We are looking for energetic and talented scientists interested in studying the function of the brain. The postdoctoral fellow will have the opportunity to learn and apply a host of systems neuroscience techniques, including two-photon imaging of population activity, optogenetic manipulations, large-scale electrophysiology and behavior in mice. Prior experience with some of these methods is preferred, but not required. Depending on the candidate’s interests, all projects provide an opportunity to learn and apply advanced computational methods, including dynamic systems analysis of neuronal population activity; Bayesian approaches for understanding the relation between neuronal activity and behavior; machine learning methods to understand large-scale neuronal activity. We currently have openings for postdoctoral fellows for three projects: (1) Neuronal mechanisms for predictive coding: Auditory perception relies on predicting statistics of incoming signals, be it identifying the speech of a conversation partner in a crowded room or recognizing the sound of a babbling brook in a forest. The human brain detects statistical regularities in sounds as a fundamental aspect of prediction, evidenced by reduced responses to repeated sound patterns and enhanced responses to unexpected sounds. Multiple studies demonstrate that the neuronal responses to regular signals are reduced through adaptation, which can contribute to prediction. However, adaptation alone is not sufficient to account for prediction and studies at cellular and neuronal population levels in animals thus far lend only partial support to existing theories of predictive coding. The goal of the project is to close this gap in knowledge and to determine the circuits that predict signals and detect statistical regularity and its violation in auditory behavior. Funded by NIH NIDCD. (2) Neuronal circuits for learning-driven changes in auditory perception: Everyday auditory behavior depends critically on learning-driven changes in auditory perception that rely on neuronal plasticity within the auditory pathway. By combining state-of-the-art optogenetic, electrophysiological, behavioral and computational approaches, the project seeks to identify the function of specific circuit elements in auditory learning. Funded by NIH NIDCD. (3) Neuronal mechanisms for hearing under uncertainty: In everyday life, because both sensory signals and neuronal responses are noisy, important cognitive tasks, such as auditory categorization, are based on uncertain information. To overcome this limitation, listeners incorporate other types of signals, such as the statistics of sounds over short and long time scales and signals from other sensory modalities into their categorization decision processes. This project will identify the contribution of specific cell types to categorization and the neuronal mechanisms for how contextual signals bias auditory categorization. In collaboration with Dr. Yale Cohen <https://auditoryresearchlaboratory.weebly.com/> and Dr. Konrad Kording <http://kordinglab.com/>, funded by NIH BRAIN Initiative. Our laboratory is a close community of fun-loving scientists, striving to help each other while exploring the mysteries of the brain. Our trainees have won numerous awards and have been awarded government and private foundation grants. We value diversity and promote equity in the scientific community and beyond <https://hosting.med.upenn.edu/hearing/philosophy/>. The systems neuroscience community at the University of Pennsylvania is top-notch and highly collaborative, and postdoctoral fellows will have opportunities to engage in interdepartmental initiatives, including MindCore <https://mindcore.sas.upenn.edu/>, MINS <https://www.med.upenn.edu/ins/> and CNI <https://www.cni.upenn.edu/>. Penn has a gorgeous campus and offers many cultural activities. Philadelphia is a beautiful city with world-class music, food and entertainment. To apply, please email Dr. Geffen at mgeffen(a)pennmedicine.upenn.edu <mailto:mgeffen@pennmedicine.upenn.edu> : a cover letter (summarize your prior research experience, why you are interested in the position, and your future plans) and your CV. __________________________ Maria N. Geffen, Ph.D. (she/her) Associate Professor Department of Otorhinolaryngology Department of Neuroscience Department of Neurology Stemmler Hall G14 3450 Hamilton Walk Philadelphia PA 19104 (215)898-0782 mgeffen(a)pennmedicine.upenn.edu http://hosting.med.upenn.edu/hearing Twitter: @neimarkgeffen

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Three Assistant Professor Positions at University of Sussex
by Thomas Nowotny June 22, 2021

June 22, 2021

Dear all, The School of Engineering and Informatics at the University of Sussex is seeking to hire three Assistant Professors (“Lecturers”, permanent position) in Computer Science and AI. One of the positions is particularly focused on a researcher with interests in one or more of the following areas: machine learning, ethical AI, computational Neuroscience, complexity science, consciousness science and bio-inspired AI and robotic control. They should be able to teach general subjects in Computer Science and Artificial Intelligence at Undergraduate and Taught Postgraduate levels. They will work within the Artificial Intelligence Research Group, including opportunities to interact with the robotics group in the Department of Engineering. The AI Research Group at the University of Sussex was created through the merger of the Evolutionary and Adaptive Systems (EASy) and the Data Science groups. We conduct research and teach a wide range of AI related topics, often cross-disciplinary and with a unique Sussex angle. We collaborate internationally and locally with academics, businesses, and public stakeholders, working at the frontiers of knowledge, on solving real-world problems, and in policy and public outreach. Applications should be accompanied by a full CV, and statements of future research plans and ways in which the applicant could contribute to teaching across the School. Please contact Dr Ian Mackie I.Mackie(a)sussex.ac.uk<mailto:I.Mackie@sussex.ac.uk> , Head of the Department of Informatics, for informal enquiries. The full job advert is posted at https://t.co/K0CdIYx6xH?amp=1 including a detailed person specification and details how to apply. Please get in touch if you are interested in these positions and forward to any interested colleagues. Kind regards, Thomas -- Prof Thomas Nowotny Head of the AI Research Group Director of Research and Knowledge Exchange School of Engineering and Informatics University of Sussex Falmer, Brighton BN1 9QJ, UK Phone: +44-1273-678593 FAX: +44-1273-877873

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